The objective of this study is to develop a new method for predicting the processing times of workers in cellular manufacturing systems. In our previous researches, a statistical approach was proposed for predicting the processing times of workers. However, the predicted processing times may not always coincide with the actual processing times since there are individual differences of the learning levels for workers and the decrease ratio of processing times of workers. Therefore, the new method uses the individual biological information such as the heart rate variability in workers in order to estimate the individual difference of learning levels of workers.

Most of the existing studies about production scheduling aim to find an optimum production schedule before starting production activities. However, unpredictable disruptions may occur in the actual manufacturing environment. Therefore, the disturbed production schedule needs to be modified for the unpredictable disruptions. In our previous studies, a reactive scheduling method has been proposed by using a genetic algorithm in order to modify the disturbed production schedule without stopping production activities. However, the proposed scheduling method significantly changes the initial production schedule in the modification process of the production schedule in order to optimize the production schedule. The significant changes of production schedules may confuse the actual manufacturing environment. In this research, we propose a partial modification approach by extending the reactive scheduling method. A hybrid genetic algorithm is developed to improve the disturbed production schedule without greatly changing the initial production schedule. Computational experiments demonstrate that the new method is superior to the previous method.

The growing amount of waste has caused severe environmental problems such as the shortage of landfill space and the high costs of waste disposal. Therefore, it is required to reuse and recycle the end-of-life products effectively from the viewpoint of economic efficiency. In this paper, we propose a disassembly scheduling method which uses a genetic algorithm to generate an optimal disassembly schedule including both the disassembly processes of multiple products and the post processes for reusing and recycling the disassembled parts for the minimization of the whole disassembly and post process times. (C) 2017 The Authors. Published by Elsevier B.V.

In recent years, many used products are returned from customers through reverse supply chains in order to be reused and recycled. Therefore, it is necessary to provide suitable disassembly procedures from the view point of economic efficiency. This research proposes a scheduling method for open-shop scheduling problems containing both disassembly operations and post-processing operations. A co-evolutionary algorithm is proposed to modify not only the sequences of disassembly and post-processing operations of products but also the sequences of products loaded on disassembly and post-processing machines. Two different kinds of individuals are modeled for both the sequences of operations and the sequences of products in the co-evolutionary algorithm. These individuals alternately repeat evolution at short time intervals, and affect their fitness values each other. We developed a prototype of scheduling system and applied it to some computational experiments for open-shop type scheduling problems including disassembly and post-processing operations. The experimental results of the proposed method were compared with the one of another scheduling method with various heuristic rules in order to evaluate the effectiveness of the proposed method. (C) 2017 The Authors. Published by Elsevier B.V.

Plant factories daily produce large amount of high quality vegetables under artificially controlled environments. One of the important problems to be considered is to establish suitable storage systems to achieve an acceptable length of shelf life and to minimize the risk to food borne illnesses. Temperature control is an essential part of food storage in food production and distribution network. Recent researches into food storage technologies have proposed alternative method of extending the shelf life of vegetables, including the use of superchilling (partial freezing) and supercooling (cooling below the freezing point without phase change). This study deals with the application of the supercooling technologies to the extension of the shelf life of the high quality leaf lettuces produced by the plant factories.

Some researches have been carried out to deal with the distributed architectures of AGV (Automated Guided Vehicle) systems for ADMS (Autonomous Distributed Manufacturing Systems). However, motion analyses of individual AGV and their influence on efficiency of transportation processes are not considered enough. The Social Force Model is introduced to represent physical interactions and congestions among the people and the environment. The Social Force Model computes a force impact from the pedestrian's self-consciousness while the other two interaction forces from other pedestrians and the walls. The interaction force consists of a psychological force resulting from distance between each other, and a physical force inspired by counteracting body compression and sliding friction. The Social Force Model is applied to the autonomous distributed AGV in order to analyze motion of them and to improve the efficiency of transportation process, in this research.

The objective of the research is to establish a systematic design method applicable to analysis and design of kinematic motion deviations of five-axis machining centers based on the tolerances of the guide-ways. A systematic procedure is proposed to determine the tolerance values of the guide-ways theoretically under the constraints on the kinematic motion deviations of five-axis machining centers, by applying ISO Tolerance definitions. The proposed method provides us with theoretical way to design the geometric tolerances of the guide-ways connecting the components of five-axis machining centers, based on allowance of the kinematic motion deviation of the tools against the workpieces.

green supply chain has been attracting attention as a new approach to minimize a product or service ecological footprint. Our previous researches proposed a basic green supply chain network model consisting of two model components, clients and suppliers. The model provided a numerical method to determine suitable prices and delivery times of ordered products through the modification processes of both production schedules by using genetic algorithms and transportation schedules by heuristic rules and the negotiation processes between suppliers and clients by using an auction based method. The objective of this paper is to propose an integrated scheduling method of production and transportation problems in order to further reduce carbon dioxide emissions without decreasing profits of suppliers. The proposed method makes an efficient transportation schedule that ensures a low vacancy rate and a high loading ratio of transportation vehicles by repeating the modification processes of production and transportation schedules alternately. Experiments were carried by using a developed supply chain simulation system. As the results of the experiments, new method was able to decrease carbon dioxide emissions without decreasing profits. (C) 2016 The Authors. Published by Elsevier B.V.

The geometric dimensioning and tolerancing is one of the most important characteristics of machined parts. A systematic method is proposed in the paper to simulate the shape generation processes in turning operations, to estimate the geometric dimensioning and tolerancing of the turned faces, based on the machining parameters. The simulation model includes both the models of the shape generation motions considering kinematic motion deviations and the cutting tool geometries. The shape generation motions with deviations are mathematically described by combining 4 by 4 transformation matrices. A set of points on the turned faces are generated through the simulations, and an assessment surface is obtained as the datum reference to estimate the 3-dimensional (3D) tolerances, based on the points generated by the turning process simulations. The proposed method provides us with a systematic method to estimate the geometric dimensioning and tolerancing in the turning processes including the kinematic motion deviations.

Much emphasis is now given to development of fully closed and controlled plant factories, aimed at supplying various vegetables safely and constantly. However, one of the most important issues of the plant factories is the high production costs due to the investment and equipment in the factories and the daily operations. Systematic methods are considered here increase the delivery prices of the vegetables and to reduce the running costs in the plant factories.

Lean is a management philosophy to eliminate waste both in the inside and from the outside of factories. A supply chain strategy is a key issue for the improvement of the outside. Recent information technologies provide even small- and medium-sized supplier companies with a chance for entering into contracts with major supplier companies and large manufacturing companies in different Keiretsu groups, but will give the trouble for surviving in the dynamic supply chain environment at the same time. This chapter proposes a strategy for MTO (Make To Order) companies to find suitable business partners in the dynamic supply chain environment and to enter into proper contracts with the partners as well as to obtain appropriate profits. A supply chain model proposed in the chapter provides a negotiation protocol to determine suitable prices and delivery times for ordered products through the iteration of the negotiation process between the organizations, as well as through the modification processes of production schedules. A twolayered supply chain model is firstly proposed as a basic model for dynamic supply chain management of MTO companies. The model is extended to a three-layered supply chain model for representing the negotiation protocol among multi-layered organizations. A prototype of a supply chain simulation system is developed and computational experiments are carried out to evaluate the effectiveness of changing business partners and negotiating among the partners cooperatively.

This paper deals with an education planning method of human operators considering production plans. The human operators carry out machining operations by using manual machine tools based on their skills in target manufacturing systems. The individual human operators can obtain new skills to operate the machine tools by receiving trainings. New education planning method is proposed based on mixed integer programming problems in this research. The mixed integer programming problem determines suitable numbers of the trainings and that of the machining operations executed by the human operators for productions. Objective functions of the mixed integer programming problem are minimizing overtime hours and maximizing sum of training priorities. The training priorities represent indices of required skills according to production plans, and number of the skills which have already been obtained. Some case studies have been carried out to verify the effectiveness of the proposed education planning method.

Cellular manufacturing systems are well known as flexible manufacturing systems for assembly processes. Single workers carry out all assembly processes of products in the typical cellular manufacturing systems. The cellular manufacturing systems are required to cope with dynamic changes of product mix and production volumes. The workers are not able to be trained by repeating same assembly processes. The objective of this study is to propose a work instruction system for workers to understand the assembly processes quickly and reduce their assembly times of products without repeating same assembly processes. According to the learning curve of workers, it is important that the assembly time should be reduced from the first time the workers assemble the products in order to increase the productivity of cellular manufacturing systems. This study firstly records workers' assembly processes by using video equipment and analyzes the learning processes of the workers in order to propose an effective strategy for the workers to reduce the assembly processes in the cellular manufacturing systems. According to the proposed strategy, a prototype of a work instruction system is developed for an assembly cell. The prototype system provides a graphical user interface explaining the information of assembly processes for the workers to facilitate understanding the assembly processes. Some experiments are carried out for assembling a toy car built with Lego blocks in order to evaluate the effectiveness of the developed work instruction system. Experimental results of the proposed work instruction system are compared with the ones of a simple work instruction system. Through the comparison, it is recognized that the proposed work instruction system is superior to the simple work instruction system from the viewpoint of the reduction of assembly times.

The surface roughness is one of the most important characteristics of machined parts. A systematic method is proposed in the paper to simulate the shape generation processes in the boring operations and to estimate the surface roughness of the generated faces, based on the machining parameters. The simulation model includes both the models of the shape generation motions considering kinematic motion deviations and the cutting tool geometries. The shape generation motions with deviations are mathematically described by 4 by 4 transformation matrices. A set of points on the bored holes are generated through the simulations, and an assessment surface is obtained as the datum reference to estimate the 2-dimensional (2D) and the 3-dimensional (3D) surface roughness, based on the points generated by the boring process simulations. The proposed method provides us with a systematic method to estimate the surface roughness in the boring processes including the kinematic motion deviations.

The objectives of the present research are to investigate relationships between kinematic motion deviations of machine tools and geometric tolerances of their components, to propose mathematical models representing kinematic motion deviations of five-axis machining centers, and to apply the models to analysis of the kinematic motion deviations of five-axis machining centers. A set of models is proposed to represent kinematic motion deviations of both the linear tables and the rotary tables, based on the geometric tolerances of the guide-ways connecting the components. By combing the models, three models of the five-axis machining centers are developed and applied to the analysis of the standard deviations of the shape generation motions of the tools and the workpieces. The proposed models provides us with a systematic method to analyze and to estimate the kinematic motion deviations of the five-axis machining centers, based on the geometric tolerances of the guide-ways connecting the components.

A cellular manufacturing system is a kind of lean and flexible manufacturing systems in which a worker or a group of workers carry out all assembly processes of a product. Assembly times of workers are generally improved in an exponential manner by repeating same assembly processes. However, the workers in the cellular manufacturing system are not provided with enough time to learn the assembly processes, since product mixes and production volumes are changeable in a short period of time. The objective of this study is to propose a work instruction system for untrained workers in assembly cells to understand the assembly processes quickly and reduce their assembly times of products without repeating same assembly processes. This study firstly records workers' assembly processes by using video equipment and analyzes the learning processes of the workers in order to propose an effective strategy for the workers to reduce the assembly processes in the cellular manufacturing system. According to the proposed strategy, a prototype of a work instruction system is developed for untrained workers in assembly cells. The prototype system provides graphical user interfaces explaining the information of assembly processes for the workers to facilitate understanding the assembly processes. Some experiments are carried out for assembling same toy cars built with Lego blocks in order to evaluate the effectiveness of the developed work instruction system. Experimental results of the proposed work instruction system are compared with the ones of a simple work instruction system. Through the comparison, it is recognized that the proposed work instruction system is superior to the simple work instruction system from the viewpoint of the reduction of assembly times. At the last part of this study, we propose a prediction method of assembly times of workers by measuring biological information as a heart rate, in order to carry out dynamic production management through the work instruction system.

This study proposes a basic model for closed-loop supply chains which includes not only traditional forward supply chains for the generation of products but also reverse supply chains for the reuse and recycling of products in consideration of economic efficiency for make-to-order and remanufacturing-to-order companies. The basic model consists of four model components, i.e., clients, manufacturers, suppliers, and remanufacturers. A remanufacturer is added to the previous model of forward supply chains in this study as a new model component which collects used products from clients and provides reusable parts to manufacturers in consideration of the demand of products. Remanufacturers as well as manufacturers and suppliers modify their schedules and negotiate with each other in order to determine suitable prices and delivery times of products. Remanufacturers stimulate clients to discard used products to meet the demand of reusable parts. They can increase the amount of reused products and reduce wastes by creating a balance between supply and demand of reusable parts. A prototype of a simulation system for closed-loop supply chains is developed in order to evaluate the effectiveness of the proposed model and negotiation protocol. Experimental results of the proposed model are compared with the ones of a conventional model which discards the used products without negotiation processes between remanufacturers and clients. Experimental results show that the proposed model can reuse more products than the conventional model.

Environmental problems are recognized as one of the most serious issues in these last few decades. Green supply chain management and sustainable supply chain management have gained increasing attention within both academia and industry. Previous studies proposed a closed-loop supply chain model and a negotiation protocol for increasing the amount of reused products and reducing waste products. This study improves the negotiation protocol for further increasing the reused products and reducing the waste. A remanufacturer can economically collect a lot of used products by negotiating with a client in consideration of both the required prices from the remanufacture and the possible times to dispose of the used products from the client. A prototype of a simulation system for a closed-loop supply chain is developed in order to evaluate the effectiveness of the new negotiation protocol. Experimental results show that the new protocol can reuse more products than the previous one.

Unexpected disruptions, such as delays of manufacturing processes, addition of emergent jobs and failures in manufacturing equipment, often occur in the actual manufacturing systems, and a predetermined production schedule may not satisfy given constraints due to the disruptions in the manufacturing systems. This research proposed a new reactive scheduling method using the co-evolutionary genetic algorithm. The proposed method alternately modifies the loading sequences of jobs and the machining sequences of jobs in a very short time, in order to improve the disturbed production schedules without interrupting the progress of manufacturing process. A prototype of an extended reactive scheduling system is developed to evaluate the effectiveness of the proposed method. Some computational experiments are carried out for unexpected delays of manufacturing processes. © 2013 The Japan Society of Mechanical Engineers.

Autonomous Distributed Manufacturing Systems (ADMS) have been proposed to realize flexible control structures of manufacturing systems. In the previous researches, a real-time scheduling method based on utility values has been proposed and appliedto the ADMS. In the proposed method, all the job agents and the resource agents evaluate the utility values for the cases where the agent selects the individual candidate agents for the next machining operations. Multi-agent reinforcement learning is newly proposed and implemented to the job agents and resource agents, in order to improve their coordination processes. In the reinforcement learning method, an agent must be able to sense the status of the environment to some extent and must be able to takeactions that affect the status. The agent also must have a goal or goals relating to the status of the environment. The status, the action and the reward are defined for the individual job agents and the resource agents to evaluate the suitable utility values based on the status of the ADMS. <br>

Unexpected disruptions, such as delays of manufacturing processes, addition of emergent jobs and failures in manufacturing equipment, often occur in the actual manufacturing systems, and a predetermined production schedule may not satisfy given constraints due to the disruptions in the manufacturing systems. This research proposed a new reactive scheduling method using the co-evolutionary genetic algorithm. The proposed method alternately modifies the loading sequences of jobs and the machining sequences of jobs in a very short time, in order to improve the disturbed production schedules without interrupting the progress of manufacturing process. A prototype of an extended reactive scheduling system is developed to evaluate the effectiveness of the proposed method. Some computational experiments are carried out for unexpected delays of manufacturing processes. © 2013 The Japan Society of Mechanical Engineers.

A real-time scheduling method considering human operators has been proposed to generate suitable production schedules for human operators, manufacturing equipment and jobs real-timely in the autonomous distributed manufacturing systems (ADMSs). The proposed scheduling method gives the higher priorities to the human operators, and generates the production schedules based on preference values, in order to improve the human operator's motivation. It was shown, through case studies, that the proposed real-time scheduling method is effective to satisfy the preferences of the human operators. However, the make span is deteriorated especially for the cases where the human operators have similar preferences. Therefore, a new method is proposed to calculate the preference values considering not only the preferences of human operators but also improvement of productivity.

A real-time scheduling method considering human operators has been proposed to generate suitable production schedules for human operators, manufacturing equipment and jobs real-timely in the autonomous distributed manufacturing systems (ADMSs). The proposed scheduling method gives the higher priorities to the human operators, and generates the production schedules based on preference values, in order to improve the human operator's motivation. It was shown, through case studies, that the proposed real-time scheduling method is effective to satisfy the preferences of the human operators. However, the make span is deteriorated especially for the cases where the human operators have similar preferences. Therefore, a new method is proposed to calculate the preference values considering not only the preferences of human operators but also improvement of productivity.

Supply chain management has been investigated for the configuring and controlling of material and information flows among different organizations. The trend has been toward even more flexible or dynamic supply chains to find suitable business partners and enter into profitable contracts. Previous studies have proposed a two-layered supply chain model consisting of two kinds of organization: clients and suppliers. This study proposes a new model representing multi-layered dynamic supply chains and a negotiation protocol in multi-layered organizations. The organizations in the middle-layers generate both orders of parts for suppliers and offers of products for clients. Production schedules in the middle-layers continue to be modified after orders are sent to suppliers. Suppliers simultaneously generate and modify sets of production schedules for individual orders to find the most profitable order of all. The effectiveness of the model and the negotiation protocol is evaluated through computational experiments.

Previous researches proposed a dynamic supply chain model, which consists of three model components; those are clients, manufacturers, and suppliers. The model provided a numerical method to determine suitable prices and delivery times of products through the iteration of both the modification processes of production schedules and the negotiation processes among the model components. This paper proposes an effective order selection method for suppliers to find a suitable order in a number of orders sent from the lower-layer organizations. Computational experiments were carried to evaluate the effectiveness of the proposed method by using a developed supply chain simulation system. (c) 2012 The Authors. Published by Elsevier B.V. Selection and/or peer-review under responsibility of Professor D. Mourtzis and Professor G. Chryssolouris.

Machine tools are recognized as key components of manufacturing systems, and product quality and cost mainly depend on performances of the machine tools. Much progress has been made in the machine tool technologies, aimed at improving the performances of the machine tools from various viewpoints, such as accuracy, reliability, productivity, and flexibility. The machining accuracy is one of the most important characteristics of the machine tools. From the viewpoints of the design and the manufacturing of the machine tools and their components, one of the important issues is to clarify the relationships between the kinematic motion deviations of the machine tools and the geometric tolerances of the components, such as the guide ways and the bearings. The objective of the present research is to establish mathematical models representing the kinematic motion deviations of the machine tools, on the basis of the geometric tolerances of the components, and to apply the models to theoretical analysis of the kinematic motion deviations of the machine tool components. Copyright © 2012 by ASME.

A new scheduling method is proposed, in this paper, to consider the statistical distributions of the processing times which are represented by normal distributions for the manufacturing systems where the human operators carry out the machining operations by using manual machine tools. The proposed scheduling method consists of two steps. In the first step, the machining schedules are determined for the individual machine tools based on average processing times by using utility value based method. In the second step, the candidate human operators are assigned to the individual machine tools taking into consideration of the statistical distributions of the processing times. A new scheduling system is also developed to generate suitable schedules based on the proposed scheduling method by using the processing time data executed by the combination of human operators, manual machine tools and machining operations. Some case studies have been carried out to verify the effectiveness of the proposed method.

Machine tools are recognized as key elements of manufacturing systems, and product quality and cost mainly depend on performances of the machine tools. Much progress has been made in the machine tool technologies, aimed at improving the performances of the machine tools from various viewpoints, such as accuracy, reliability, productivity, and flexibility. The machining accuracy is one of the most important characteristics of the machine tools. From the viewpoints of the design and the manufacturing of the machine tools and their components, one of the important issues is to clarify the relationships between the kinematic motion deviations of the machine tools and the geometric tolerances of the components, such as the guide ways and the bearings. The objectives of the present research are to establish mathematical models representing the kinematic motion deviations of the machine tools, on the basis of the geometric tolerances of the components, and to apply the models to theoretical analysis of the kinematic motion deviations of the machine tool components.

Much progress has been made in the machine tool technologies, aimed at improving the performances of the machine tools from various viewpoints, such as accuracy, reliability, productivity, and flexibility. The machining accuracy is one of the most important characteristics of the machine tools. From the viewpoints of the design and the manufacturing of the machine tools and their components, one of the important issues is to clarify the relationships between the kinematic motion deviations of the machine tools and the geometric tolerances of the components, such as the guide ways and the bearings. The objective of the present research is to establish mathematical models representing the kinematic motion deviations of the machine tools, on the basis of the geometric tolerances of the components, and to apply the models to analysis of the kinematic motion deviations.

Machine tools are recognized as key components of manufacturing systems, and product quality and cost mainly depend on performances of the machine tools. Much progress has been made in the machine tool technologies, aimed at improving the performances of the machine tools from various viewpoints, such as accuracy, reliability, productivity, and flexibility. The machining accuracy is one of the most important characteristics of the machine tools. From the viewpoints of the design and the manufacturing of the machine tools and their components, one of the important issues is to clarify the relationships between the kinematic motion deviations of the machine tools and the geometric tolerances of the components, such as the guide ways and the bearings. The objective of the present research is to establish mathematical models representing the kinematic motion deviations of the machine tools, on the basis of the geometric tolerances of the components, and to apply the models to theoretical analysis of the kinematic motion deviations of the machine tool components. Copyright © 2012 by ASME.

Previous studies have proposed a dynamic configuration method for two-layered supply chains consisting of a set of clients and suppliers. The proposed method provides suitable delivery times and prices of products through the modification process of production schedules of the suppliers and the negotiation process between the clients and the suppliers in consideration of transportation constraints. This research proposes a new supply chain model extended for carbon dioxide emissions reductions in the two-layered dynamic supply chains. The suppliers provide transportation plans to reduce carbon dioxide emissions in transportation processes without losing chances to enter into a large number contracts with the clients. The effectiveness of the proposed model is verified through computational experiments from the viewpoints of both the amount of carbon dioxide emitted in transportation processes and the profits of the suppliers.

Our previous researches proposed a dynamic supply chain model, which consists of model components such as suppliers, manufacturers, and clients. The model provided a systematic method to determine suitable prices and delivery times of ordered products based on both scheduling processes and negotiation processes among the model components. This research proposes an order selection method using parallel scheduling for suppliers to select a suitable order in a number of orders sent from lower model components in dynamic supply chains. Some heuristic rules are also proposed as other selection methods for suitable orders in the research. The scheduling based selection method is compared with the rule based selection methods though some computational experiments in order to evaluate the effectiveness of the proposed methods. © 2011 The Japan Society of Mechanical Engineers.

Due to rapid changes of markets and pressures of competitions, industries are adopting their production ways to support diversity of customer's needs and increase of new product developments. This paper deals with development of an agent-based architecture of dynamic systems for process planning in the manufacturing systems. In consideration of alternative manufacturing processes and machine tools, the process plans and the schedules of the manufacturing resources are generated incrementally and dynamically. A previously proposed negotiation protocol is customized and improved to generate suitable process plans for the target products real-timely and dynamically, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks and the suitable process plans are searched and generated to cope with both the dynamic status and disturbances of the manufacturing systems. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans.

This research proposes a two-layered supply chain model consisting of a set of clients and suppliers for dynamic supply chain management considering production and transportation scheduling problems. The model provides a method to optimize both production schedules and transportation schedules simultaneously, in order to estimate suitable prices and delivery times of products. A prototype of simulation system for dynamic supply chain management was developed and some computational experiments were carried out in order to verify the effectiveness of the model. Experimental results show that the prototype system is available to determine suitable production schedules and transportation schedules from the viewpoint of the number of contracted orders and the cost for wasteful shipping. copy
2010 IEEE.

A real-time scheduling method based on utility values has been proposed and applied to the holonic manufacturing systems (HMS), in the previous paper. In the proposed method, all the job holons and the resource holons firstly evaluate the utility values for the cases where the holon selects all the candidate holons for the next machining operations. The coordination holon secondly determine a suitable combination of the resource holons and the job holons, based on the utility values. Reinforcement learning is newly proposed and implemented to the individual job holons and resource holons, in order to improve their capabilities for evaluating the utility values.

Cellular manufacturing systems are well known as flexible and reliable manufacturing systems for assembly processes. A suitable control method is required for the cellular manufacturing systems to keep the production capacity in the case where unforeseen changes, such as delays of assembly processes, addition of new orders, and unscheduled workers' absences, occur during the progress of assembly processes. This research proposes a dynamic task reallocation and rescheduling method in the cellular manufacturing systems, consisting of a set of assembly cells in which all the assembly processes are carried out by single workers. The method proposed here dynamically modifies an initial production schedule and minimizes the total tardiness by a genetic algorithm and a heuristic rule, called as EDD (Earliest Due Date), to cope with unforeseen changes in the cellular manufacturing systems. A prototype of dynamic task reallocation and rescheduling system was developed and applied to some computational experiments in order to evaluate the effectiveness of the proposed method.

Previous researches provided a reactive scheduling method using a genetic algorithm to improve disturbed production schedules, due to unexpected disruptions, such as delays of manufacturing operations. This paper deals with an extension of the reactive scheduling method to modify not only the loading sequences but also machining sequences of jobs by using a co-evolutionary genetic algorithm. Two different kinds of individuals for the loading sequences and the machining sequences are generated and improved in co-evolutionary processes. A prototype of new reactive scheduling system was developed, and the effectiveness of the proposed method was verified through computational experiments.

This research proposes a two-layered model for dynamic supply chain management considering transportation constraint. The model provides a method for suppliers to estimate suitable prices and delivery times of products based on not only production schedules but also transportation plans in consideration of constraints about shipping times and loading capacities for transportation. A prototype of dynamic supply chain simulation system was developed and some computational experiments were carried out in order to verify the effectiveness of the model. The prototype system is available to determine suitable shipping times and loading capacities of transportation vehicles.

This research deals with a two-layered dynamic supply chain model representing decisionmaking processes of individual clients and suppliers, and also negotiation processes among all clients and suppliers. In the model, suitable prices and delivery times are determined through both the scheduling processes of the individual suppliers and the negotiation processes among the clients and the suppliers. Dynamic production scheduling processes of the suppliers are newly considered in the model to deal with the trade-off between the prices and the delively times. The effectiveness of the proposed model is verified through computational experiments from the viewpoints of the profits of the suppliers.

This research proposes a new model of two-layered dynamic supply chains considering transportation constraint. The new model provides a method for suppliers to estimate delivery times and prices of products based on not only production schedules but also transportation plans. The transportation plans generally include constraints about shipping times and loading capacities for transportation. A prototype of dynamic supply chain simulation system was developed and some computational experiments were carried out in order to verify the effectiveness of the new model. The prototype system is available to determine suitable shipping times and loading capacities of transportation vehicles.

This paper deals with a real-time scheduling method for holonic manufacturing systems (HMS). In the previous paper, a real-time scheduling method based on utility values has been proposed and applied to the HMS. In the proposed method, all the job holons and the resource holons firstly evaluate the utility values for the cases where the holon selects the individual candidate holons for the next machining operations. The coordination holon secondly determine a suitable combination of the resource holons and the job holons which carry out the next machining operations, based on the utility values. Multi-agent reinforcement learning is newly proposed and implemented to the job holons and the resource holons, in order to improve their capabilities for evaluating the utility values of the candidate holons. The individual job holons and resource holons evaluate the suitable utility values according to the status of the HMS, by applying the proposed learning method.

Process planning and scheduling are important manufacturing planning activities which deal with resource utilization and time span of manufacturing operations. The process plans and the schedules generated in the planning phase shall be modified in the execution phase due to the disturbances in the manufacturing systems. This paper deals with a multi-agent architecture of an integrated and dynamic system for process planning and scheduling for multi jobs. A negotiation protocol is discussed, in this paper, to generate the process plans and the schedules of the manufacturing resources and the individual jobs, dynamically and incrementally, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks discussed in the previous paper, and the suitable process plans and schedules are searched and generated to cope with both the dynamic status and the disturbances of the manufacturing systems. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans and schedules in the dynamic manufacturing environment. A simulation software has been developed to carry out case studies, aimed at verifying the performance of the proposed multi-agent architecture.

A reactive scheduling method is one of the scheduling methods that improve an initial production schedule disturbed by environmental changes in manufacturing systems. In the previous research, Genetic Algorithm based reactive scheduling method have been proposed. In case of dealing with the aggregate production schedule, it is difficult to modify the initial schedule because of the unknown factors which occur in the manufacturing system. In this research, only part of the initial schedule is modified by setting the suitable scheduling range. Consequently, the reactive scheduling method can be applied for the aggregate production scheduling.

This paper deals with an agent-based architecture of an integrated system for process planning and scheduling for multi jobs in flexible manufacturing systems. The process plans and the schedules of the manufacturing resources and the individual jobs are generated dynamically and incrementally. The architecture does not employ a set of predefined process plans, and the process plans of the individual jobs are incrementally and real timely generated from the alternative production routes in the process plan networks. Coordination agents are proposed to generate a suitable the assignment of the job agents to the machine tool agents at each step of the negotiation.

A real-time scheduling method considering human operators is proposed, in this paper, to select suitable combinations of the human operators, the manufacturing equipment and the jobs for the manufacturing processes. The proposed scheduling method consists of three steps. In the first step, the human operators select their favourite processes which they will carry out in the next time period, based on their preferences. In the second step, the machine tools and the jobs select suitable combinations for the next machining processes. In the third step, the automated guided vehicles and the jobs select suitable combinations for the next transportation processes.

Machine tools are recognized as key components of manufacturing systems, and product quality and cost mainly depend on performances of the machine tools. Much progress has been made in the machine tool technologies, aimed at improving the performances of the machine tools from various viewpoints, such as accuracy, reliability, productivity, and flexibility. The machining accuracy is one of the most important characteristics of the machine tools. From the viewpoints of the design and the manufacturing of the machine tools and their components, one of the important issues is to clarify the relationships between the kinematic motion deviations of the machine tools and the geometric tolerances of the components, such as the guide ways and the bearings. The objective of the present research is to establish mathematical models representing the kinematic motion deviations of the machine tools, on the basis of the geometric tolerances of the components, and to apply the models to theoretical analysis of the kinematic motion deviations of the machine tools.

Process planning and scheduling are important manufacturing planning activities which deal with resource utilization and time span of the manufacturing operations. The process plans and the schedules generated in the planning phase shall be modified in the execution phase due to the disturbances in the manufacturing systems. This paper deals with a multi-agent architecture of an integrated and dynamic system for process planning and scheduling for multi jobs. Systematic methods are proposed to generate the process plans and the schedules of the manufacturing resources and the individual jobs, dynamically and incrementally. A simulation software has been prepared to carry out case studies, aimed at verifying the performance of the proposed multi-agent architecture.

This research proposes a new model representing multi-layered dynamic supply chains. The proposed model consists of three kinds of components. They are clients, manufacturers, and suppliers. The manufacturers, proposed in this research, not only generate the orders to the suppliers but also generate the offers to the clients. The manufacturers continue to modify their production schedules after sending the orders to the suppliers, in order to get the contract with the clients, even if the possible delivery time from suppliers do not satisfy the required delivery time from the manufacturers. The effectiveness of the proposed model is verified through some computational experiments from the viewpoint of the completion of the contracts.

Real-time scheduling processes based on the utility values have been proposed and applied to the Holonic Manufacturing Systems (HMS), in the previous papers. A simulation based procedure has also been implemented to estimate the future status of HMS and to determine the utility values aiming at improving scheduling method. However, it was assumed that only one holon in the HMS carries out the estimation for the ease of the estimation process. A simulation based real-time scheduling method is newly proposed, in the paper, to improve the estimation process which enable all the holons to estimate the future status of the HMS.

A genetic algorithm based reactive scheduling method was proposed in the previous research, in oder to modify and improve a disturbed initial production schedule without suspending the progress of manufacturing process. This paper proposes a new crossover method to improve the performance of the reactive scheduling method for total tardiness minimization problems and total flow time minimization problems. A multi-objective reactive scheduling method is also proposed based on the reactive scheduling method improved in this research. A prototype of multi-objective reactive scheduling system is developed and applied to computational experiments for job-shop type scheduling problems.

Capabilities and complexity of manufacturing systems are increasing and striving for an integrated manufacturing environment. Availability of alternative process plans is a key factor for integration of design, process planning and scheduling. This paper describes an algorithm for generation of alternative process plans by extending the existing framework of the process plan networks. A class diagram is introduced for generating process plans and process plan networks from the viewpoint of the integrated process planning and scheduling systems. An incomplete search algorithm is developed for generating and searching the process plan networks. The benefit of this algorithm is that the whole process plan network does not have to be generated before the search algorithm starts. This algorithm is applicable to large and enormous process plan networks and also to search wide areas of the network based on the user requirement. The algorithm can generate alternative process plans and to select a suitable one based on the objective functions.

This paper deals with a real-time scheduling system of the holonic manufacturing systems (HMS). In the previous papers, real-time scheduling processes based on the utility values have been proposed and applied to the HMS. A simulation based procedure has also been implemented to estimate the future status of HMS and to determine the utility values aiming at improving scheduling method. However, it was assumed that only one holon in the HMS carries out the estimation for the ease of the estimation process. A simulation based real-time scheduling method is newly proposed, in the paper, to improve the estimation process which enable all the holons to estimate the future status of the HMS. An estimation process is developed for the individual holons to estimate the future status of HMS through the simulation. Some case studies of the real-time scheduling are carried out to verify the effectiveness of the proposed method.

This paper deals with a real-time scheduling system of holonic manufacturing systems (HMSs), which were proposed by an international cooperative research consortium called The HMS Consortium for Autonomous Distributed Management and Control of the Manufacturing Systems. The scheduling system generates real-time suitable production schedules, based on decision making by individual constituents named holons and their coordination. The objective of the present research is to improve the decision-making processes of the individual holons through the use of estimation process of the future status of the HMS. Procedures are developed and implemented to the individual holons, in order to estimate the future status of the HMS by applying the simulation model of the HMS. A neural network model is proposed to represent and to simulate the decision-making process of the individual holons.

A predetermined production schedule is often disturbed in agile manufacturing systems, due to unscheduled disruptions, such as delays of manufacturing operations and addition of new jobs. The objective of the research is to propose a new reactive scheduling method based on the Genetic Algorithm (GA), which generates improved production schedules reactively against the disturbances. A basic reactive scheduling method was proposed in the previous research. The proposed method continuously creates new feasible production schedules, until a new production schedule satisfies the given constraint or all the manufacturing operations have started. This paper deals with a new evolutional method to improve the performance of the GA-based reactive scheduling process for adding new jobs. Several computational experiments were carried out for the delays of manufacturing operations and the addition of new jobs by using the developed prototype system for reactive scheduling, in order to verify the effectiveness of the proposed method. © 2006 Taylor &amp
Francis Group, LLC.

Recently, automation of manufacturing systems has been developed, aimed at realizing flexible small volume batch productions. New distributed architectures of manufacturing systems have been proposed to realize more flexible control structures of the manufacturing systems for coping with the dynamic changes in the volume and the variety of the products and also the unforeseen disruptions, such as malfunction of manufacturing equipment and interruption by high priority jobs. They are called autonomous distributed manufacturing systems, biological manufacturing systems, and holonic manufacturing systems (HMS). The chapter proposes a new real-time scheduling method for HMS to consider both the objective functions of the individual holons and the whole HMS. In this method, all the pareto optimal combinations of the resource holons and the job holons for the machining processes are generated, based on the objective functions of the individual holons. Following this, a most suitable combination is selected from the pareto optimal ones, based on the objective functions of the whole HMS, such as the total make span and the total tardiness. © 2006 Elsevier Ltd. All rights reserved.

Unscheduled disruptions, such as delays of manufacturing processes, addition of emergent jobs and failures in manufacturing equipment, often occur in the actual manufacturing systems. However, most of the traditional scheduling researches assume that manufacturing environments are well stabilized. The manufacturing system becomes impossible for satisfying the constraints on the due dates and the make-span, when the initial schedules are delayed because of the unscheduled disruptions. The chapter discusses a reactive scheduling method based on genetic algorithm (GA) to improve an initial production schedule delayed because of unscheduled disruptions, such as delays of manufacturing processes. The chapter proposes a new GA based reactive scheduling method for tardiness minimization scheduling problems, aiming at improving the disturbed production schedule efficiently and generating suitable production schedules faster than the previous reactive scheduling method. A prototype of reactive scheduling system is developed and applied to computational experiments. © 2006 Elsevier Ltd. All rights reserved.

This research deals with a dynamic supply chain model representing decision-making processes of individual clients and suppliers, and also negotiation processes among all clients and suppliers. In the model, suitable prices and delivery time are determined based on both the scheduling processes of the individual suppliers and the negotiation processes among the clients and the suppliers. The production scheduling process of the suppliers are newly considered in the model to deal with the trade-off between the prices and the delivery time. The effectiveness of the proposed model is verified through computational experiments from the viewpoints of the prices, the delivery time and the benefit of the suppliers.

Recently, new architectures of manufacturing systems have been proposed to realize flexible control structures of the manufacturing systems, which can cope with the dynamic changes in the volume and the variety of the products and also the unforeseen disruptions, such as failures of manufacturing resources and interruptions by high priority jobs. They are so called as the autonomous distributed manufacturing system, the biological manufacturing system and the holonic manufacturing system. Rule-based scheduling methods were proposed and applied to the real-time production scheduling problems of the HMS (Holonic Manufacturing System) in the previous report. However, there are still remaining problems from the viewpoint of the optimization of the whole production schedules. New procedures are proposed, in the present paper, to select the production schedules, aimed at generating effective production schedules in real-time. The proposed methods enable the individual holons to select suitable machining operations to be carried out in the next time period. Coordination process among the holons is also proposed to carry out the coordination based on the effectiveness values of the individual holons.

In design and planning of manufacturing systems, a wide variety of models representing the manufacturing systems are required for simulation and verification from various viewpoints. These models are concurrently developed and applied to various application fields, therefore, a computerized support system is needed for concurrent development and consistency management of the various manufacturing system models. The objective of the research is to develop an object-oriented model repository aiming at supporting concurrent development and consistency management of the various manufacturing system models for production planning. Contents and structures of manufacturing system models are discussed from the viewpoint of the concurrent and hierarchical production planning problems. Model components and their relations to be stored in the model repository are proposed. A prototype of a model repository is developed and applied to the production planning problems.

In design and planning of manufacturing systems, a wide variety of models representing the manufacturing systems are required for simulation and verification from various view points. These models may be concurrently developed and applied to various application fields, therefore, a computerized support system is needed for concurrent development and consistency management of the various manufacturing system models. The objective of the research is to develop an object-oriented model repository aiming at supporting concurrent development and consistency management of the various manufacturing system models for production planning. Contents and structures of manufacturing system models are discussed from the viewpoint of the concurrent and hierarchical production planning problems, and model components and their relations to be stored in the model repository are proposed A prototype of a model repository is developed and applied to the production planning problems.

The objective of the present research is to develop a formal modeling method, aimed at realising concurrent development and integration of various manufacturing system models. An object-oriented model repository of the manufacturing system is discussed to establish a systematic and logical criteria for classifying the manufacturing system models from various viewpoints. Contents and structures of manufacturing system models are discussed from the viewpoint of the concurrent and hierarchical production planning problems, and model components and their relations to be stored in the model repository are proposed. A prototype of a model repository is developed and applied to the production planning problems.

Computer-integrated manufacturing (CIM) draws upon many important areas of manufacturing automation, such as CAD, CAM and MRP. It is not necessarily the sum of these compooents but the linking of them into an interoperable system that satisfies the various strategies and objectives of the CIM systems. The objective of the present research is to develop a formal modelling method in order to realize concurrent development and integration of the various CIM models. A model architecture of the CIM is discussed to establish systematic and logical criteria for classifying the CIM models. A computer-aided method is also proposed based on the model architecture in order to examine the consistency among a set of CIM models which are designed to represent the various aspects of the CIM system being analyzed.

<p>Recently, off-market distribution of fresh sea foods becomes popular as diversifying of demands, increasing of internet sales, and growing retail businesses. However, it is difficult to determine suitable prices of fresh sea foods in off-market distribution since sea foods cannot be caught stably and stored for a long time. A dead stock or an out of stock of sea foods usually occurs.</p><p>In this paper, we propose a new pricing method of sea foods in off-market distribution. The proposed method changes selling prices of sea foods according to selling times in order to reduce the dead stock and prevent the out of stock of sea foods. A genetic algorithm is applied to the method for determining suitable prices of sea foods hourly to provide a large profit for fishermen.</p><p>Furthermore, we developed a sales simulation system and carried out computational experiments. We compared experimental results using a genetic algorithm and ones using an exhaustive search as a comparative method to verify the effectiveness of the proposed method. The results demonstrate that the proposed method is more effective than the comparative method for pricing sea foods in off-market distributions.</p>

<p>This research proposes a three-layered dynamic supply chain model using backward scheduling. The three-layered model consists of three components named Client, Manufacturer, and Supplier. The Manufacturers generate and send the orders of the parts of a product to the Supplier. The Manufacturer estimates processing times of the parts made by the Supplier and generates a production schedule by using forward scheduling. After that, the manufacturing operations in the production schedule are reallocated backward from the delivery times of products required by the Client, and the earliest starting times of the operations are determined as the required delivery times of the parts for the Supplier. The proposed model can increase the number of contracts and the profits by estimating the required delivery times of parts correctly in consideration of the lower limit of starting times of manufacturing operations in the Manufacturer. This research shows the effectiveness of the proposed model through computer simulations.</p>

&lt;p&gt;The kinematic motion deviations of the five-axis machining centers are deeply influenced by the geometric deviations of the components, such as guide-ways and bearings. A systematic design method is required for specifying suitable geometric tolerances of the guide-ways, in order to improve the kinematic motion deviations of five-axis machining centers. The objective of the present research is to establish a computer-aided design system for specifying a suitable set of the geometric tolerances of the guide-ways considering the trade-off between the requirements on the kinematic motion deviations and the ease of the manufacturing processes. A mathematical model was proposed in the previous papers to represent the standard deviations of the shape generation motions, based on the tolerance values of the guide-ways of the five-axis machining centers. A systematic method is proposed here considering the rotational table positions to determine a suitable set of the tolerance values of all the guide-ways under the constraints on the kinematic motion deviations between the tools and the workpieces. The method is applied to some design problems of the geometric tolerances of the guide-ways included in the five-axis machining centers.&lt;/p&gt;

ln cellular manufacturing systems, workers carry out the whole production activities, and the performance of workers&#039; activities changes during production processes. We are engaged in development of dynamic production management system. The previous study shows that the decrease of processing time depends on the learning level for work procedure. The purpose of this study is to predict processing times of workers in consideration of ability difference. This study proposes a method for analyzing workers&#039; heart rate variability to estimate the learning level in real time. The method determines the amount of change in processing times in response to activation level of parasympathetic nerve. Experimental results show that the proposed method is effective for prediction of processing times with consideration of personal differences.

&lt;p&gt;Currently, supply chain networks are complicated and extended to worldwide with the globalization on business. When supply chain disruptions unexpectedly occur as a result of natural disaster or industrial accidents, suppliers sustain their business continuously. Supply chain resilience has been receiving an attention for the risk management. Supply chain resilience is known as the ability of adapting to a changing environment. Thus, the collaboration among supply chain members is important for improving supply chain resilience. In this paper, we propose a rescheduling strategy in order to recover the productivity after facing unscheduled disruptions. When suppliers need to interrupt manufacturing processes due to the disruptions and products cannot satisfy a given due date, suppliers can reduce tardiness and penalty charges for delays by contracting out the delayed products to external suppliers and restore production capacity to the state before the disruption occur. Furthermore, we propose a selection rule of delayed products for outsourcing. A prototype of supply chain simulation system is developed in order to evaluate the proposed strategy. We carry out computational experiments though the developed simulation system. The experimental results demonstrate that the proposed strategy can reduce tardiness and penalty charge of suppliers and detect the most suitable selection rule for outsourcing.&lt;/p&gt;

&lt;p&gt;Nowadays, environmental issues attract people&#039;s attention. Manufacturing companies need to plan their strategies considering environment as well as economy. Closed-loop supply chains are composed of forward supply chains and reverse supply chains including remanufacturers. Remanufacturers reuse and recycle the used products. Our previous study proposed a closed loop supply chain model for remanufacturers to increase the number of reusable products and their reward by estimating suitable values of the used products. We applied the model to rechargeable batteries. A retaining value of used rechargeable battery was estimated based on the current internal resistance of battery. However, the internal resistance may be changed with different condition of charging or discharging. In this study, we propose an estimation method of batteries&#039; capacity from continuously collected data of batteries&#039; internal resistance by using the least squares method. We carry out computational experiment to evaluate the effectiveness of the proposed method from the viewpoint of remanufacturer&#039;s reward and the number of reusable products.&lt;/p&gt;

&lt;p&gt;In recent years, it is required to reduce the amount of waste since there is a growing interest in environmental issues. Hence, it is important to reuse and recycle the end-of-life products effectively. In the reusing and recycling process of products, a lot of components are disassembled and inspected to get reusable parts from the products. Thus, it is necessary to generate a suitable schedule for disassembly processes. We proposed a scheduling method using a genetic algorithm to find a suitable disassembly schedule. However, in an actual recycle factory, each product has a different condition, such as removing rust and slag, therefore an initial disassembly schedule should be improved considering the actual disassembly processes. Hence, a dynamic scheduling method is required to cope with such unforeseen changes in the actual disassembly processes. In this paper, we propose a reactive scheduling method to find an optimal disassembly schedule considering the operational situation of an actual machine. A prototype of reactive scheduling system is developed in order to verify the effectiveness of the proposed method. We carry out verification experiments though the developed scheduling system. The experimental results demonstrate that the new method is able to monitor the operational situation of an actual machine and improve a schedule.&lt;/p&gt;

Environmental issues have become a serious problem in the last decade. We have been investigating a closed-loop supply chain model for reuse of used products. This study proposes a new negotiation model for further increasing the reuse of products and, thereby, reducing the waste. A simulation system of closed-loop supply chains is developed to evaluate the effectiveness of the proposed negotiation model.

This research proposes a scheduling strategy for suppliers to constantly obtain profits in global supply chains, in case where large scale disasters occasionally occur or not. Suppliers in the previous supply chain models minimize tardiness of ordered products in order to enter into a lot of contracts and reduce penalty charges for delays. A prototype of supply chain simulation system is developed to evaluate scheduling strategies of suppliers. We evaluate several scheduling strategies, such as the minimization of both the tardiness and the flow time through computational simulation in order for suppliers to find a suitable scheduling strategy in which the suppliers can manufacture the ordered products and deliver them before the occurrence of unpredictable disasters.

Due to advance of ICT technologies and global manufacturing, the decentralized decision making of multi-tier supply chains for multiple retailers and manufacturers becomes more and more important to achieve cooperative and collaborative production in global supply chains. In such situations, game theoretical approaches for supply chain optimization to analyze coordination mechanism, leader-follower relationship, conflicts, and contracts for different manufacturing facilities are highly requested. In this paper, we address the classification of game theoretical supply chain planning models. Some of basic models and application modes are introduced.

The kinematic motion deviations of the five-axis machining centers are deeply influenced by the geometric deviations of the components, such as guide-ways and bearings. A systematic design method is required for specifying suitable geometric tolerances of the guide-ways, in order to improve the kinematic motion deviations of five-axis machining centers. The objective of the present research is to establish a computer-aided design system for specifying a suitable set of the geometric tolerances of the guide-ways considering the trade-off between the requirements on the kinematic motion deviations and the ease of the manufacturing processes. A mathematical model was proposed in the previous papers to represent the standard deviations of the shape generation motions, based on the tolerance values of the guide-ways of the five-axis machining centers. A systematic method is proposed here, by applying an optimization method, to determine a suitable set of the tolerance values of all the guide-ways under the constraints on the kinematic motion deviations between the tools and the workpieces. The method is applied to some design problems of the geometric tolerances of the guide-ways included in the five-axis machining centers.

&lt;p&gt;A systematic procedure is proposed to design the tolerance values of the components under the constraints on the kinematic motion deviations of parallel link robots. The kinematic motion deviations of parallel link robots are influenced by geometric deviation of the components, such as bearing and joints. This research focus on the geometric tolerance of the joints and bearings of the parallel link robots. The tolerance values are set smaller and smaller, the manufacturing process become more difficult and costly. It is very important to design a suitable set of tolerance values of machine products from the view point of the both the product quality and the production costs. The objective of the research is to determine the tolerance values of joints theoretically under the constraints on the kinematic motion deviations of parallel link robots by applying ISO tolerance. The proposed method provide us with theoretical way considering both the difficulty and the cost of the manufacturing process by applying ISO tolerance to objective function.&lt;/p&gt;

&lt;p&gt;In recent years, it is required to reduce the amount of waste since there is a growing interest in environmental issues. Hence, it is important to reuse and recycle the end-of-life products effectively. In the reusing and recycling process of products, a lot of components should be disassembled and inspected to get reusable parts from the products. Thus, it is necessary to carry out disassembly processes efficiently. However, it is difficult to find an optimal disassembly process since the complexity of the disassembly sequence increases with the number of parts of the products. Some studies have proposed scheduling methods using evolutionary algorithms to find a suitable disassembly schedule for a single product. However, these algorithms are considered neither the disassembly processes of multiple products nor the post processes of the disassembly processes, such as cleaning and inspecting, for reusing and recycling the parts disassembled from the products. In this paper, we propose a method using a genetic algorithm to find an optimal disassembly schedule considering both the disassembly processes of multiple products and the post processes for reusing and recycling the disassembled parts. A prototype of scheduling system is developed in order to verify the effectiveness of the proposed method. We carry out a large number of computational experiments though the developed scheduling system. The experimental results demonstrate that the new method is superior to the previous method from the viewpoint of the minimization of the whole disassembly and post-processing times.&lt;/p&gt;

&lt;p&gt;Most of the existing studies about production scheduling are carried out to find an optimum production schedule before starting production activities. However, unpredictable disturbances may occur in the actual manufacturing environment. In that case, the predetermined production schedule can&#039;t be applied to a manufacturing system. The disturbed production schedule needs to be modified for unpredictable condition changes flexibly. In the previous study, a reactive scheduling method have been proposed in order to modify the production schedule in parallel with the production activities. The proposed method uses a diffuse co-evolutionary genetic algorithm searching for the most suitable production schedule in the solution space with global scope. However, the previous method may not be able to search in the local area of the solution space. Therefore, this study adds a new method to the previous method for searching in a local area as well as a global area. The new method focuses on an idle time in a production schedule to shorten the makespan. A prototype of reactive scheduling system is developed in order to verify the effectiveness of the proposed method. Computational experiments demonstrate that the new method is superior to the previous method.&lt;/p&gt;

&lt;p&gt;Multi-agent reinforcement learning has been applied to the autonomous distributed scheduling method based on utility values in order to improve the sum of earliness and tardiness of all jobs, in the previous researches. New distributed scheduling method is proposed by using deep reinforcement learning in this research. Firstly, job selection criteria of machining centers are proposed by using Q-learning based on status s of manufacturing system and value &lt;i&gt;Q&lt;/i&gt;(&lt;i&gt;s&lt;/i&gt;, &lt;i&gt;a&lt;/i&gt;) of action a to determine utility values. Deep Q-network is one of deep reinforcement learning method. The Q-network is neural network model whose input data are status s and output data are value &lt;i&gt;Q&lt;/i&gt;(&lt;i&gt;s&lt;/i&gt;, &lt;i&gt;a&lt;/i&gt;). Deep Q-network algorithm is applied to the proposed distributed scheduling method by using Q-learning in order to estimate the value &lt;i&gt;Q&lt;/i&gt;(&lt;i&gt;s&lt;/i&gt;, &lt;i&gt;a&lt;/i&gt;) by machining center to select the suitable job for the distributed scheduling. Training of the Q-network are also carried out efficiently in the Deep Q-network algorithm.&lt;/p&gt;

&lt;p&gt;Recently，supply chain management is required to cope with unforeseen changes of client&#039;s demand for products. We have proposed a multiple-layered dynamic supply chain model in the previous researches. This enables companies to contract with an appropriate company for each product. The proposed model consists of three components named clients, manufacturers, and suppliers. The manufacturers generate and send both the orders of the parts to the suppliers and the offers of the products to the clients. In this study, we propose a new model of manufacturer which not only machines a part but also assembles several parts and produces a product for a client after machining and assembling several parts obtained from different suppliers. We extend the model in order to cope with assembly processes as well as machining processes. The manufacturers receive several orders sent from suppliers and negotiate with the suppliers to generate a suitable offer for a client through machining and assembling scheduling processes. The effectiveness of the proposed model is verified through some computational experiments from the viewpoint of the number of contracts.&lt;/p&gt;

&lt;p&gt;Environmental issues have become a serious problem in the last decade. We have been investigating a closed-loop supply chain model for reuse of used products. This study proposes a new negotiation model for further increasing the reuse of products and, thereby, reducing the waste. A simulation system of closed-loop supply chains is developed to evaluate the effectiveness of the proposed negotiation model.&lt;/p&gt;

&lt;p&gt;Due to advance of ICT technologies and global manufacturing, the decentralized decision making of multi-tier supply chains for multiple retailers and manufacturers becomes more and more important to achieve cooperative and collaborative production in global supply chains. In such situations, game theoretical approaches for supply chain optimization to analyze coordination mechanism, leader-follower relationship, conflicts, and contracts for different manufacturing facilities are highly requested. In this paper, we address the classification of game theoretical supply chain planning models. Some of basic models and application modes are introduced.&lt;/p&gt;

&lt;p&gt;This research proposes a scheduling strategy for suppliers to constantly obtain profits in global supply chains, in case where large scale disasters occasionally occur or not. Suppliers in the previous supply chain models minimize tardiness of ordered products in order to enter into a lot of contracts and reduce penalty charges for delays. A prototype of supply chain simulation system is developed to evaluate scheduling strategies of suppliers. We evaluate several scheduling strategies, such as the minimization of both the tardiness and the flow time through computational simulation in order for suppliers to find a suitable scheduling strategy in which the suppliers can manufacture the ordered products and deliver them before the occurrence of unpredictable disasters.&lt;/p&gt;

The Social Force Model introduced is to represent physical interactions and congestions among the people and the environment.The Social Force Model computes a force impact from the pedestrian&#039;s self-consciousness while the other two illustrate interaction forces from other pedestrians and the walls.The interation force consists of a pspchological force resulting from distance between each other,and a physical force inspired by counteracting body compression and sliding friction.The Social force model is applied to the autonomous distributed AGV in order to avoid the collision and achieve the effective transportation process, in this research. Simulation model is constructed based on the social force model by using multi method simulator AnyLogic.

In order to realize the efficient manufacturing thorough intensive manufacturing processes, 5-axis machine tools attract a wide attention. New scheduling systems are proposed by using 3DCAM aimed at high production efficiency for 5-axis machine tools, in this research. The scheduling systems consist of 3axis and 5axis CNC machine tools, 3DCAD database, Customized 3DCAM corresponding to types of machine tools, and the jobs. The proposed scheduling systems carry out following 3 steps. The individual machine tools refer the 3DCAD database to obtain the 3DCAD data of jobs which can be carried out next machining process in the first step. 3DCAM creates the NC data and estimates processing time of all jobs in second step. The individual machine tools and jobs carry out the autonomous distributed scheduling process in order to minimize the make-span in third step.

A new planning method is proposed to invest manufacturing equipment based on asset management in order to cope with fluctuations in demand for manufacturing systems, in this research. Some portfolios are set to consider candidates of the equipment investment. Returns and risks of the individual portfolios are required to select the best portfolio in the invest planning based on the asset management. The returns and the risks of the portfolios are obtained by using the returns and the risks of the investment of the individual manufacturing equipment. The returns and risks of the investment of the individual manufacturing equipment are calculated based on the averages and the variances of profit for the cases where the individual manufacturing equipment are invested under assumptions that candidate production plans and their probabilities are obtained.

A new investment planning method is proposed to determine purchase of suitable production equipment considering demand fluctuations by using portfolio for manufacturing systems consisted of CNC machine tools and jobs in this research. The portfolios are set to consider candidates of the purchasing production equipment for investment. Returns and risks considering demand fluctuations of the individual portfolios are required to select the best portfolio in the proposed investment planning method. The returns and the risks of the portfolios are calculated by using the returns and the risks of the purchasing individual production equipment for investment under assumptions that candidate production plans and probabilities that production plans correspond to demand have already been obtained. Profit of the manufacturing system is estimated in the cases where the production plans are carried out by using the purchased production equipment and existing that in order to calculate the returns and the risks of the purchasing individual production equipment.

The Social force Model is introduced to represent physical interactions and congestions among the people and the environment. It introduces a quite general framework in which the details of the collision avoiding behaviour can be expressed through a function depending on the relative and absolute positions and velocities of the pedestrians. Even in its simplest formulation that uses only information about positions, the model describes correctly many qualitative features of pedestrian behaviour. The Social force Model is applied to the autonomous distributed AGV in order to analyze motion of them and to achieve the effective transportation process, in this research. Simulation model is constructed based on the Social force Model by using multi method simulator AnyLogic.

Dynamic scheduling methods are required to cope with unforeseen changes in the actual manufacturing environment. We have proposed a reactive scheduling method using a genetic algorithm in the previous researches. The proposed method modifies an initial production schedule, in case where unexpected changes occur in manufacturing systems in the progress of manufacturing processes. Previous study proposed a reactive scheduling method by using a diffuse co-evolutionary genetic algorithm in order to modify an initial production schedule by changing three decision variables, such as loading sequences, machining sequences, and job allocation to machine tools. In this study, we investigate the performance improvement of the existing reactive scheduling method from the viewpoint of minimization of make-span. There are two points to be improved in the genetic algorithm. First, we change the coding method of both machining sequences and job allocation to machine tools to find an optimum solution from a wider range of search space than the previous method. Second, we provide an individual selection method to escape from a local optimum solution. A prototype of reactive scheduling system is developed in order to verify the effectiveness of the proposed method. Computational experiments demonstrate that the new method is superior to the previous method.

A new planning method is proposed to invest manufacturing equipments based on asset management in order to cope with fluctuations in demand for manufacturing systems, in this research. Some portfolios are set to consider candidates of the equipment investment. Returns and risks of the individual portfolios are required to select the best portfolio in the invest planning based on the asset management. The returns and the risks of the portfolios are obtained by using the returns and the risks of the investment of the individual manufacturing equipment. The returns and risks of the investment of the individual manufacturing equipment are calculated based on the averages and the variances of loads of manufacturing equipments under assumptions that candidate production plans and their probabilities are obtained.

A systematic method has been proposed, in previous paper, to allocate human operators to machine tools and to determine machining schedules considering statistical distributions of machining times. It was assumed that the processing times executed by the human operators are represented by random variables according to normal distributions, in the previous paper. However, normal distribution cannot express distributions of machining time enough e.g. case that probabilities of delay are larger than that of earliness. A new method is proposed, in this paper, to assign human operators to machine tools and to determine machining schedules considering statistical distributions of processing times under the assumption that the processing times executed by the human operators are represented by random variables according to beta distributions.

著者らは，従来の固定的なサプライチェーンに対して，複数のサプライチェーンを契約ごとに組み替える動的サプライチェーンの研究を進めてきた．近年では，環境問題への意識が高まり,リユース・リサイクルを取り入れることが社会全体から求められている．本研究では，需要の変動を考慮して，製品の廃棄を抑制することで，リユース率を向上させる能動的な交渉モデルを提案するとともに，シミュレーションにより，その評価を行う．

サプライチェーンに甚大な被害を与える，予測できない大規模災害に対して，災害による被害を低減するためのリスクマネジメントが注目されている．そこで，本研究は，低頻度かつ大規模な災害に対して，製造企業が，自身の利益を確保するための頑健な生産スケジューリング手法を提案する．さらに，既存の2階層サプライチェーンシミュレーションシステムを用いて，計算機実験を行うことで，その有効性を検証する．

The objective of this study is to propose a work instruction system for workers to understand the assembly processes quickly and reduce their assembly times of products without repeating same assembly processes. According to the learning curve of workers, it is important that the assembly time should be reduced from the first time the workers assemble the products in order to increase the productivity of cellular manufacturing systems. This study firstly analyzes the learning processes of workers and develops a work instruction system for assembly cells.

The objective of the present research is to establish mathematical models representing kinematic motion deviations of 5-Axis machining centers. A systematic procedure is proposed to estimate kinematic motion deviations of linear tables and rotary tables based on geometric deviations of guide-ways. A model is developed by combining both the models of the linear table and the rotary table and applied to the analysis of the 5-axis machining centers.

A simulation model is proposed in the paper to estimate and to verify the geometry deviations of the machined surfaces in the machining processes of CNC machining centers and single point tools. The model proposed here represents the boring processes based on both the shape generation motions and the cutting tool geometries. The individual motions are mathematically described by 4 by 4 transformation matrices including the kinematic motion deviations. Emphasis is given to the modeling and analysis of the machining process of the single point tools.

A new method is proposed, in this paper, to assign human operators to machine tools and to determine machining schedules considering statistical distributions of processing times. The proposed method consists of following three steps. The human operators are assigned to machine tools by using 0-1 integer programming, in order to minimize a total of standard deviations of processing times, in the first step. Some feasible machining schedules are determined for the individual machine tools by using a set of dispatching rules, in the second step. The statistical distributions of the makespans are calculated for the individual scheduling results by applying Clark's formula in order to select the machining schedule which minimizes the estimated maximum value of the makespan, in the third step.

A systematic method has been proposed, in previous paper, to allocate human operators to machine tools and to determine machining schedules considering statistical distributions of machining times. It was assumed that the processing times executed by the human operators are represented by random variables according to normal distributions, in the previous paper. However, normal distribution cannot express distributions of machining time enough e.g. case that probabilities of delay are larger than that of earliness. A new method is proposed, in this paper, to assign human operators to machine tools and to determine machining schedules considering statistical distributions of processing times under the assumption that the processing times executed by the human operators are represented by random variables according to beta distributions.

A new systematic method is proposed to invest manufacturing equipments in order to cope with fluctuations in demand, in this research. Conventional researches have been carried out to propose the methods for the equipment investment considering the fluctuations in demand. However, the risks of the equipment investment are not discussed in the conventional researches. Returns and risks are defined based on averages and variances in economic science. The returns and the risks for the equipment investment are defined based on the averages and the variances of loads of manufacturing equipments under assumptions that candidate production plans and their probabilities are set to cope with the fluctuations in demand, in this research.

Multi-agent reinforcement learning have been applied to the autonomous distributed scheduling method in order to improve the objective functions of individual job agents and resource agents, in the previous researches. New distributed scheduling method is proposed to improve the sum of earliness and tardiness of all job agents by applying multi-agent reinforcement learning to resource agents, in this research. The resource agents learn the selection criteria of job agents for next machining operation based on the status of manufacturing systems. Some case studies have been carried out to verify the effectiveness of the proposed method.

This research proposes a new reactive scheduling method using co-evolutionary genetic algorithms for machining and assembly processes in a manufacturing system. Reactive scheduling is a technique of improving a disturbed initial production schedule due to some changes, such as delays of manufacturing processes, occurred in a manufacturing system. Co-evolutionary genetic algorithms are extended in this research to deal with the modification of production schedules including not only machining processes but also assembly processes. A prototype of reactive scheduling system is developed in order to verify the effectiveness of the proposed method through some computational experiments.

Cellular manufacturing systems are well known as flexible and reliable manufacturing systems for assembly processes. A suitable control method is required for the cellular manufacturing systems to keep the production capacity in the case where unforeseen changes, such as delay of assembly processes, occur during the progress of assembly processes. This research proposes a new method for dynamic production management in the cellular manufacturing systems. When delays of assembly processes occur in the cellular manufacturing systems, delayed production schedules are modified in real-time by changing initial task allocations for workers and loading sequences of the allocated tasks in order to minimize the maximum tardiness of products. The method also allocates various tasks for untrained workers in order to enhance workers&#039; capabilities and productivities in the case where the cellular manufacturing systems still have enough production capacities for minimizing the maximum tardiness. A prototype of task reallocation and rescheduling system is developed to evaluate the effectiveness of the proposed method.

This research proposes a closed-loop supply chain model which represents not only traditional forward supply chains for the generation of products but also reverse supply chains for the reuse of used products. The proposed model consists of four model components, these are clients, manufacturers, suppliers, and remanufacturers. Remanufacturers receive used products from clients and provide reusable parts to manufacturers. These model components modify their production schedules and negotiate with each other in order to determine suitable prices and delivery times of ordered products. Remanufacturers send orders for used products to clients and stimulate discarding the products, in order to control the balance of demand and supply of reusable parts. A prototype of simulation system for closed-loop supply chains was developed to verify the effectiveness of the proposed closed-loop supply chain model.

FMSの主な構成要素であるMCは，多数の工具を配備することにより柔軟性の高い加工を行うことが可能である．ただし，工具のコストや工具マガジン容量の制約のため，加工に必要な工具をすべてのMC に配備できるとは限らない．そこで，FMSを効率良く運用するには，工具を適切にMC に割り当てることが重要になる．本研究では，負荷平準化と搬送効率の両方を考慮した工具配分手法を提案する．

現在，食に対する安全性と安定供給が重要となっている．そこで，植物工場が注目されている．しかし，植物工場で生産される野菜は，生産コストが一般の野菜に比べて高くなる事が問題である．そこで，リーフレタスの完全制御型植物工場をモデル化し生産コスト分析を行い，その問題点を分析する．さらに，植物工場を運営する上で重要な市場価格を予測するシステムを開発し，予測価格に基づいて植物工場の運用を行う手法を検討する．

本研究では工作機械のうち，5 軸マシニングセンタに着目し，その構成要素において幾何学的偏差を含むモデルを作成した．その上で，構成要素の幾何学的偏差が一定である時，2種類の回転テーブルの回転量の違いが工作物に対する工具の位置と姿勢に与える影響を解析する．

近年，二酸化炭素排出量に対する規制が厳しくなっている．製造企業には，サプライチェーン全体の二酸化炭素排出量の低減が求められる一方で，経済的な衰退が危惧されている．そこで，本研究では，企業が利益を損なうことなく，輸送工程における二酸化炭素排出量を削減することができるように，生産スケジュールと輸送スケジュールを改善する手法を提案する．さらに，計算機実験により，その有効性を検証する．

A new tool allocation method is proposed, in this paper, to consider both load balancing and optimization of transportation based on mathematical programming. The proposed tool allocation method consists of two steps. In the first step, the individual tools are divided into tool sets based on the integer programming, in order to balance the total machining time by using the individual tool sets and reduce the number of transportation. In the second step, the individual tool sets are assigned to the MCs based on the quadratic assignment problem, in order to minimize the transportation distance of jobs. Some case studies have been carried out to verify the effectiveness of the proposed method.

This paper deals with an education planning method of human operators considering production plans. The human operators carry out the machining operations by using manual machine tools based on their skills in the target manufacturing systems. The individual human operators can obtain the new skills to operate the machine tools by receiving the trainings. New education planning method is proposed based on the integer programming in this research. The integer programming determines the suitable numbers of training and that of machining operations executed by human operators for productions.

著者らは，これまでに，共進化遺伝的アルゴリズムを用いて，部品の加工工程と投入順序を改善するリアクティブスケジューリング手法を提案した．本研究では，部品の加工工程と組立工程を含むスケジューリング問題に適用するため，既存の手法を拡張して，階層型の遺伝子構造を有する共進化遺伝的アルゴリズムを提案する．さらに，リアクティブスケジューリングシステムを開発し，計算機実験を行うことで，その有効性を検証する．

セル生産は，製品の品種や量の変化に対応できる柔軟な生産方式として注目されている．本研究では，セル生産において，作業の遅延が発生した場合に，納期遅れの最小化と作業者の技能の向上を考慮した多目的ハイブリッド遺伝的アルゴリズムを用いて，セルへの作業配分と作業順序を動的に改善する手法を提案する．さらに，提案手法に基づき，動的生産管理システムのプロトタイプを開発して，計算機実験を行い，その有効性を検証する．

Our previous researches proposed a dynamic supply chain model, which consists of model components such as suppliers, manufacturers, and clients. The model provided a systematic method to determine suitable prices and delivery times of ordered products based on both scheduling processes and negotiation processes among the model components. This research proposes an order selection method using parallel scheduling for suppliers to select a suitable order in a number of orders sent from lower model components in dynamic supply chains. Some heuristic rules are also proposed as other selection methods for suitable orders in the research. The scheduling based selection method is compared with the rule based selection methods though some computational experiments in order to evaluate the effectiveness of the proposed methods. © 2011 The Japan Society of Mechanical Engineers.

既存の研究では，生産活動中に発生した作業の遅延に対して，生産工程の順序制約を考慮しながら，生産スケジュールを改善する，共進化遺伝的アルゴリズムを用いたリアクティブスケジューリング手法を提案した．本研究では，既存の手法を拡張し，順序制約の数が増加しても，生産スケジュールの改善率が低下しにくい，リアクティブスケジューリング手法を開発する．さらに，計算機実験を行い，その有効性を検証する．

Previous researches provided a two-layered supply chain model consisting of a set of clients and suppliers. This research proposes a new model representing multi-layered dynamic supply chains and a negotiation process among multi-layered organizations. The organizations in the middle-layers generate both orders of parts for suppliers and offers of products for clients. Production schedules in the middle-layers continue to be modified after sending orders to suppliers. Suppliers simultaneously generate and modify sets of production schedules for individual orders to find the most profitable order of all. The effectiveness of the model and the negotiation process is evaluated through computational experiments.

A new scheduling method is proposed, in this paper, to consider the statistical distribution of processing time of human operators. The proposed scheduling method consists of two steps. In the first step, the machining schedules are determined for the individual machine tools based on average processing time. In the second step, the candidate human operators are assigned to the individual machine tools taking into consideration of the statistical distribution of the processing time which are represented by normal distributions. The scheduling system is also developed to carry out the proposed scheduling method by using processing time database.

This paper deals with an education planning method of human operator considering production schedules. The human operators carry out the machining operations by using manual machine tools based on their skills in the target manufacturing systems. The individual human operators can obtain the new skills to operate the machine tools by receiving the trainings. New education planning method is formulated based on the goal programming in this research. The proposed education planning method determine the suitable number of operations for making products and receiving training in order to keep the regular working hours and to maximize the priorities. The priorities represent the indices of the required skills according to the production schedules.

This research proposes a three-layered dynamic supply chain model consisting of suppliers, manufacturers, and clients as a minimum model for multi-layered dynamic supply chains. Each organization can change the configurations of supply chains by selecting the most profitable order. This research provides a cooperative negotiation process among the three-layered organizations. A prototype of simulation system was developed to evaluate the effectiveness of the three-layered model. The experimental results showed that the manufactures and the suppliers entered into more contracts and obtained more profits, and the clients obtained ordered products at lower prices than required prices of the initial orders, by continuing to modify the production schedules of the manufacturers after sending the orders to the suppliers.

New operator allocation method is proposed, in this paper, to consider the statistical distribution of machining time executed by human operators. The proposed operator allocation method consists of two steps. In the first step, the candidate human operators are allocated to the individual machine tools based on 0-1 programming problem which minimizes the summation of standard deviation of machining time for all the machining operations. In the second step, the machining schedules are determined for the individual machine tools by using dispatching rules. Monte Carlo simulations are carried out in order to estimate the standard deviation of make span of machining schedule obtained by the proposed operator allocation method.

Cellular manufacturing systems are well known as flexible manufacturing systems for assembly processes. Single workers carry out all assembly processes of products in the cellular manufacturing systems. The cellular manufacturing systems are required to cope with dynamic changes of product mix and production volumes. The workers are not able to be trained by repeating same assembly processes. This research proposes a work support method for the workers to shorten assembly times of products without a repeat of training. Based on the analysis of learning curve effects for workers, a prototype of work support system is developed and applied to some experiments.

筆者らは，これまでに自律分散型生産システムにおけるスケジューリング手法の研究として，マルチエージェント強化学習の適用について検討している．本報告では，納期ずれ和の最小化を目的として，リソースがジョブを適切に選択するための判断基準を学習する手法について提案する．

A new tool allocation method is proposed, in this paper, to consider both the load balancing among the machining centers (MCs) and the transportation time of jobs between the MCs. The proposed tool allocation method consists of two steps. In the first step, the individual tools are assigned to the tool sets based on the integer programming, in order to balance the load among the tool sets. In the second step, the individual tool sets are assigned to the MCs based on the quadratic assignment problem, in order to minimize the transportation time of jobs. Some case studies have been carried out to verify the effectiveness of the proposed method.

既存の研究では，二階層の動的サプライチェーンにおいて，サプライヤが，輸送制約を考慮して，生産スケジュールを改善し，クライアントと交渉を繰り返すことで，適切な納期と価格を決定する手法を提案した．本研究では，輸送時の二酸化炭素排出量の削減を考慮して，適切な納期と価格を決定するために，二階層動的サプライチェーンの輸送モデルの拡張を行う．さらに，シミュレーションシステムを開発し，その有効性を検証する．

In the scheduling problems of the manufacturing systems with human operators, it is not easy to consider variation of machining time which are different from operator to operator. New scheduling method is proposed, in this paper, to consider the statistical distribution of machining time executed by human operators. It is assumed that the machining time executed by human operators are obtained by normal distribution. The proposed scheduling method consists of two steps. In the first step, the sequences of machining operations are determined for the individual machining tools by using utility value based method. In the second step, the candidate human operators are allocated to the individual machining tools taking into consideration of the statistical distribution of the machining time of the individual human operators. The scheduling system is also developed to carry out the proposed scheduling method by using machining time database. Some case studies have been carried out to verify the effectiveness of the proposed method.

Supply chain should be continuously designed and redesigned in order to dynamically configure suitable clients and suppliers in multiple supply chains. Previous researches proposed a dynamic configuration method of two-layered supply chains consisting of a set of clients and suppliers. The proposed method provided suitable delivery times and prices of products by the negotiation between clients and suppliers and by the modification of existing production schedules of suppliers. This research proposes a new model of two-layered dynamic supply chains considering transportation constraint. The new model provides a method for the suppliers to estimate delivery times and prices of products based on not only production schedules but also transportation plans that include constraints about shipping times and loading capacities for transportation. A prototype of dynamic supply chain simulation system was developed and some computational experiments were carried out in order to verify the effectiveness of the new model. The experimental results showed that the prototype system obtained a set of suitable shipping times and loading capacities.

This research proposes a new model representing multi-layered dynamic supply chains and a new negotiation process among components. The proposed model consists of three components named clients, manufacturers, and suppliers. The manufacturers generate and send both the orders of the parts to the suppliers and the offers of the products to the clients. The manufacturers continue to modify their production schedules after sending their orders of the parts to the suppliers, in order to improve their schedules to manufacture the ordered products. Therefore, the manufacturers are able to satisfy the requirements on the delivery time of the ordered products, even if the possible delivery time from suppliers does not satisfy the required delivery time from the manufacturers. The effectiveness of the proposed model and negotiation processes is verified through some computational experiments from the viewpoint of profits.

In the scheduling problems of the manufacturing systems with human operators, it is not easy to consider variation of machining time which are different from operator to operator. New scheduling method is proposed, in this paper, to consider the statistical distribution of machining time executed by human operators. It is assumed that the machining time executed by human operators are obtained by normal distribution. The proposed scheduling method consists of two steps. In the first step, the sequences of machining operations are determined for the individual machining tools by using utility value based method. In the second step, the candidate human operators are allocated to the individual machining tools taking into consideration of the statistical distribution of the machining time of the individual human operators. The scheduling system is also developed to carry out the proposed scheduling method by using machining time database. Some case studies have been carried out to verify the effectiveness of the proposed method.

This research proposes a new model representing multi-layered dynamic supply chains and a new negotiation process among components. The proposed model consists of three components named clients, manufacturers, and suppliers. The manufacturers generate and send both the orders of the parts to the suppliers and the offers of the products to the clients. The manufacturers continue to modify their production schedules after sending their orders of the parts to the suppliers, in order to improve their schedules to manufacture the ordered products. Therefore, the manufacturers are able to satisfy the requirements on the delivery time of the ordered products, even if the possible delivery time from suppliers does not satisfy the required delivery time from the manufacturers. The effectiveness of the proposed model and negotiation processes is verified through some computational experiments from the viewpoint of profits.

Supply chain should be continuously designed and redesigned in order to dynamically configure suitable clients and suppliers in multiple supply chains. Previous researches proposed a dynamic configuration method of two-layered supply chains consisting of a set of clients and suppliers. The proposed method provided suitable delivery times and prices of products by the negotiation between clients and suppliers and by the modification of existing production schedules of suppliers. This research proposes a new model of two-layered dynamic supply chains considering transportation constraint. The new model provides a method for the suppliers to estimate delivery times and prices of products based on not only production schedules but also transportation plans that include constraints about shipping times and loading capacities for transportation. A prototype of dynamic supply chain simulation system was developed and some computational experiments were carried out in order to verify the effectiveness of the new model. The experimental results showed that the prototype system obtained a set of suitable shipping times and loading capacities.

Machine tools are recognized as key components of manufacturing systems, and product quality and cost mainly depend on performances of the machine tools. Much progress has been made in the machine tool technologies, aimed at improving the performances of the machine tools from various viewpoints, such as accuracy, reliability, productivity, and flexibility. The machining accuracy is one of the most important characteristics of the machine tools. From the viewpoints of the design and the manufacturing of the machine tools and their components, one of the important issues is to clarify the relationships between the kinematic motion deviations of the machine tools and the geometric tolerances of the components, such as the guide ways and the bearings. The objective of the present research is to establish mathematical models representing the kinematic motion deviations of the machine tools, on the basis of the geometric tolerances of the components, and to apply the models to theoretical analysis of the kinematic motion deviations of the machine tool components.

Cellular manufacturing systems are well known as flexible and reliable manufacturing systems for assembly processes. A suitable control method is required for the cellular manufacturing systems to keep the production capacity in the case where unforeseen changes, such as delays of assembly processes, occur during the progress of assembly processes. This research proposes a new method for dynamic production management in the cellular manufacturing systems. When delays of assembly processes occur in the cellular manufacturing systems, delayed production schedules are modified in real-time by changing initial task allocations for workers and orders of the allocated tasks in order to minimize the total tardiness of products. The proposed method considers learning levels of workers in the task allocation processes. The method allocates various tasks for untrained workers in order to enhance workers&#039; capabilities and productivities in the case where the total tardiness is less than zero and the cellular manufacturing systems still have enough production capacities. A prototype of reallocation supporting system is developed to evaluate the effectiveness of the proposed method.

This paper deals with a work scheduling method considering preferences of human operators. The human operators indicate the weights of preference for their holidays, in the proposed scheduling method. The machining skills of human operators are also considered to generate the work schedule. The proposed work scheduling method is formulated by integer programming problem. Its objective function is to maximize the number of holidays which correspond to requests of human operators. And its constraints are number of holidays which are determined by the labor standards act, and the number of human operators which can carry out the machining processes from the view point of their skills.

Important activities in manufacturing such as R&amp;D, design, production management, production engineering, and manufacturing operation need advanced skills formed as results of a number of practices and thinking. We name these skills manufacturing phronesis. Manufacturing phronesis in Japanese industry has been decreasing while it is a key resource for competitive products. This paper reports the present state of manufacturing phronesis in Japanese manufacturers based on the analysis of questionnaire survey and interviews to engineers.

本研究では，作業者を構成要素の一つとする自律分散型生産システムのリアルタイムスケジューリング手法について検討している．これまでに作業者のモチベーションを高めることを目的として，作業者の希望を考慮したスケジューリング手法を提案した．本報告では，生産プロセスの進捗状況に応じて，作業者の希望を優先または抑制することができる作業者の希望と生産効率を考慮したリアルタイムスケジューリング手法について提案する．

これまでに提案した二階層動的サプライチェーンモデルは，サプライヤが生産スケジュールを改善し，クライアントと交渉を繰り返すことで，適切な納期と価格を決定する．しかし，生産スケジュールの変更により，契約済みのオーダに納期遅れが発生し，それがクライアントの信頼を損なう場合が考えられる．そこで，本論文では，特定のオーダの納期遅れを抑制する方法を提案し，納期遵守が利益に与える影響を計算機実験により評価する．

近年，派遣法改正などの問題から，作業者を多能工にするための技能教育に注目が高まっている．作業者に技能教育を行う場合，教育を行う作業者および習得させる技能の種類を適切に決定するための教育計画が重要となる．本研究では，加工ショップを対象として，生産計画を所与とする場合に，整数計画法を用いることにより教育計画を最適に決定する手法について提案する．また，生産シミュレーションを実行し，その有効性を検証する．

本研究では，作業の遅延など，あらかじめ予測することができない製造環境の変化に対し，共進化遺伝的アルゴリズムの手法を用いて，加工対象物の加工順序，および加工機械における加工対象物の投入順序を逐次変更することで，動的に生産スケジュールを改善するリアクティブスケジューリング手法を提案した．本稿では，加工対象物の加工順序に制約がある場合を考慮した提案手法の拡張を行うとともに，計算機実験を行い，拡張した手法の有効性を検証する．

Machine tools are recognized as key components of manufacturing systems, and product quality and cost mainly depend on performances of the machine tools. Much progress has been made in the machine tool technologies, aimed at improving the performances of the machine tools from various viewpoints, such as accuracy, reliability, productivity, and flexibility. The machining accuracy is one of the most important characteristics of the machine tools. From the viewpoints of the design and the manufacturing of the machine tools and their components, one of the important issues is to clarify the relationships between the kinematic motion deviations of the machine tools and the geometric tolerances of the components, such as the guide ways and the bearings. The objective of the present research is to establish mathematical models representing the kinematic motion deviations of the machine tools, on the basis of the geometric tolerances of the components, and to apply the models to theoretical analysis of the kinematic motion deviations of the machine tool components.

Rapid changes of market demands and pressures of competition require manufacturers to maintain highly flexible manufacturing systems to cope with a complex manufacturing environment. This paper deals with development of an agent-based architecture of dynamic systems for incremental process planning in the manufacturing systems. In consideration of alternative manufacturing processes and machine tools, the process plans and the schedules of the manufacturing resources are generated incrementally and dynamically. A negotiation protocol is discussed, in this paper, to generate suitable process plans for the target products real-timely and dynamically, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks discussed in the previous paper, and the suitable process plans are searched and generated to cope with both the dynamic changes of the product specifications and the disturbances of the manufacturing resources. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans in the dynamic manufacturing environment. &lt;br&gt;

Recently, new distributed architectures of manufacturing systems are proposed, aiming at realizing more flexible control structures of the manufacturing systems. Many researches have been carried out to deal with the distributed architectures for planning and control of the manufacturing systems. However, the human operators have not yet been discussed for the autonomous components of the distributed manufacturing systems. A real-time scheduling method is proposed, in this research, to select suitable combinations of the human operators, the resources and the jobs for the manufacturing processes. The proposed scheduling method consists of following three steps. In the first step, the human operators select their favorite manufacturing processes which they will carry out in the next time period, based on their preferences. In the second step, the machine tools and the jobs select suitable combinations for the next machining processes. In the third step, the automated guided vehicles and the jobs select suitable combinations for the next transportation processes. The second and third steps are carried out by using the utility value based method and the dispatching rule-based method proposed in the previous researches. Some case studies have been carried out to verify the effectiveness of the proposed method.&lt;br&gt;

This research deals with a two-layered dynamic supply chain model representing decision-making processes of individual clients and suppliers, and also negotiation processes among all clients and suppliers. In the model, suitable prices and delivery times are determined through both the scheduling processes of the individual suppliers and the negotiation processes among the clients and the suppliers. Dynamic production scheduling processes of the suppliers are newly considered in the model to deal with the trade-off between the prices and the delively times. The effectiveness of the proposed model is verified through computational experiments from the viewpoints of the profits of the suppliers.

The recent information technologies provide us with global and fast communication among the different organizations, such as raw material suppliers, parts suppliers and assembly manufacturers. Each organization requires a strategy for finding suitable business partners for every order and for entering into proper contracts with the partners, in order to make a profit and to survive in dynamic supply chains. The proposed model provided suitable delivery times and prices of products by the negotiation between the clients and the suppliers and by the modification of the existing production schedules of the suppliers using the genetic algorithm. This research proposes a new negotiation protocol for the supplier to select a suitable order from a lot of orders using parallel and distributed scheduling. Some computational experiments were carried out in order to evaluate the effectiveness of the new negotiation protocol.

This paper deals with a facility layout method with feedback of execution data. The components of target manufacturing systems are machining tools, jobs and AGVs. The machining tools have the alternatives which can carry out the same machining operations of the individual jobs. Therefore the individual jobs have the alternative machining sequences. In the target manufacturing system, the machining sequences are determined by the real-time scheduling which is carried out after the facility layout have determined. The proposed facility layout method estimates the amount of jobs which is machined by the individual machining sequences, based on the execution data which have been carried out in the manufacturing system. The proposed method generates the suitable layout based on the integer programming problem by using estimated amount of jobs.

This research proposes new method for a dynamic production management in cellular manufacturing systems. When unforeseen changes, such as delays of manufacturing processes decrease of the number of workers, occur in the manufacturing systems, the predetermined production schedule is dynamically modified, in order to minimize the tardiness of products. All the tasks are reallocated to the individual workers real-timely by using evolutionary computation algorithm, and the execution sequences of the reallocated tasks are determined by using a heuristic rule. A learning curve effect is considered in this research in generation of a suitable production schedule. A prototype of dynamic production management system is developed based on the proposed method, and the effectiveness of the proposed method is verified through some computational experiments.

This research proposes a new model representing multi-layered dynamic supply chains and a new negotiation process among components in the model. The proposed model consists of three components named clients, manufacturers, and suppliers. The manufacturers generate and send both the orders of the parts to the suppliers and the offers of the products to the clients. The manufacturers continue to modify their production schedules after sending their orders of the parts to the suppliers, in order to improve their schedules to contract the ordered products. Therefore, the manufacturers are able to satisfy the requirements of the ordered products, even if the suppliers do not satisfy the requirement from the manufacturers. The effectiveness of the proposed model is verified through some computational experiments from the viewpoint of contract completion.

New scheduling method is proposed in this paper, to consider the statistical distribution of machining time executed by human operators. The proposed scheduling method consists of two steps. In the first step, the sequences of jobs are determined for the individual machining tools based on dispatching rules. In the second step, the allocations of human operators to the individual machining tools are determined by considering the statistical deviations of the machining time. The scheduling system is also developed to carry out the proposed scheduling method by using machining time data base. The machining time data base generate the statistical deviations of the machining time obtained by the simulation of machining process.

人間の作業において前腕のひねりを伴う動作を解析するためのモデルを検討する．本報告では，前腕における２本の骨格構造（橈骨と尺骨）CTスキャナーを用いて計測し，その計測データに基づき橈骨と尺骨の相対回転運動を考慮したモデルを提案する．

工作機械における工具と工作物間の形状創成運動の幾何学的な偏差を表現するモデルを構築し，運動偏差の解析を行う．特に，本報告では，案内面および軸受け面の３次元的な幾何偏差に基づいて，回転テーブルの運動偏差を解析する手法を提案する．

本研究では，加工フロアにおいて手動工作機械を用いて加工作業を行う作業者の勤務スケジューリングについて検討する．本研究の特徴として，作業者の休日に対する希望を考慮してスケジューリングを行う．そのため，作業者が希望する休日と実際の休日が一致する日数の最大化を目的関数，制約条件を労働基準法で定められた勤務日数および要求生産量を満たすための各日の作業者数とし，整数計画問題として勤務スケジュールを作成する．

本研究では，自律分散型生産システムにおいて，自律的な構成要素として作業者を考慮し，作業者がやる気，意欲を持って生産プロセスを実行することができる人に優しい自律分散型生産システムの開発を目的として，作業者の希望を考慮したリアルタイムスケジューリング手法を提案する．提案するリアルタイムスケジューリング手法は，作業者，自動化設備および工作物が自律的に意思決定を行なうとともに協調しながら次に実行する生産プロセスを決定することができる．提案手法において，作業者は，ヒューマンインタフェースを用いて自身の希望に基づいて次に実行する生産プロセスを決定する．リアルタイムスケジューリングのケーススタディを行い，特にCNC工作機械が故障した場合に，作業者がボトルネックとなる加工プロセスを実行することにより総処理時間を短くすることができることを示す．

２階層の動的サプライチェーン問題では，サプライヤが生産スケジュールを改善しながら，クライアントと交渉を繰り返すことで，適切な納期と価格を決定する手法を提案した．本論文では，一定間隔で製品の輸送を繰り返す輸送制約を追加する．輸送機器の最大積載量を満たさない無駄を最小化するとともに，製品の重み付き納期遅れ和を最小化する二目的最適化遺伝的アルゴリズムを用いて，適切な納期と価格を算出する手法を提案する．

系列の解体や情報ネットワークの普及にともない，近年，物品調達の取引先を契約ごとに組み替える動的サプライチェーンの研究が注目されている．著者らは，これまでに，サプライヤとクラアントで構成される2階層の動的サプライチェーンモデルを提案し，サプライヤが，既存の生産スケジュールを変更しながら，クライアントと交渉を繰り返すことで，受注製品の納期と価格を決定する手法を提案した．また，前田らは，クライアントからの複数のオーダに対して，複数のスケジューリングを同時に行うことで，自身にとって適切なオーダを選択し，交渉を行う手法を提案した．本研究では，分散計算機環境において，並列にスケジューリングを行い，現行の生産スケジュールに最も適切なオーダを選択する並列分散スケジューリングシステムを開発する．さらに，2階層の動的サプライチェーンモデルのシミュレーションシステムを用いて，その有効性を検討する．

This paper deals with a real-time scheduling system of the holonic manufacturing systems (HMS). In the previous papers, real-time scheduling processes have been proposed based on the utility values of the candidate holons. A simulation based procedure has also been implemented to estimate the future status of HMS and to determine the utility values based on the estimated future status. However, it was assumed that the simulation models for estimation include the model representing the decision criteria of all the holons. A new simulation based real-time scheduling method is proposed, in the present paper, to improve the estimation process, which enable all the holons to estimate the future status of the HMS without decision criteria of other holons. An estimation process is developed for the individual job holons and resource holons to estimate the future status of HMS through the simulation. Some case studies of the real-time scheduling are carried out to verify the effectiveness of the proposed method. It is shown, through case studies, that the proposed methods are effective to improve the objective function values of the individual holons.

This paper deals with a real-time scheduling system of the holonic manufacturing systems (HMS). In the previous papers, real-time scheduling processes have been proposed based on the utility values of the candidate holons. A simulation based procedure has also been implemented to estimate the future status of HMS and to determine the utility values based on the estimated future status. However, it was assumed that the simulation models for estimation include the model representing the decision criteria of all the holons. A new simulation based real-time scheduling method is proposed, in the present paper, to improve the estimation process, which enable all the holons to estimate the future status of the HMS without decision criteria of other holons. An estimation process is developed for the individual job holons and resource holons to estimate the future status of HMS through the simulation. Some case studies of the real-time scheduling are carried out to verify the effectiveness of the proposed method. It is shown, through case studies, that the proposed methods are effective to improve the objective function values of the individual holons.

The objective of the research is to establish mathematical models representing the kinematic motion deviations of the machine tools on the basis of the geometric tolerances of the components, and to apply the models to theoretical analysis of the kinematic motion deviations of the machine tools. Mathematical models are proposed to represent the kinematic motion deviations of the linear tables of the machine tools. The proposed models give the relationships between the geometric tolerances of the guide-ways of the components and the kinematic motion deviations of the linear tables. The models of the linear tables are combined to represent the whole machine tools to represent the positional deviations of the tools against the workpieces. The developed models are applied to the analysis of the kinematic motion deviations of the machine tools, aiming at clarifying the effects of the geometric deviations of the components on the kinematic motion deviations between the tools and the workpieces.

This paper deals with a multi-agent architecture of an integrated and dynamic system for process planning and scheduling for multi jobs. A negotiation protocol is discussed, in this paper, to generate the process plans and the schedules of the manufacturing resources and the individual jobs, dynamically and incrementally, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks discussed in the previous paper, and the suitable process plans and schedules are searched and generated to cope with both the dynamic status and the disturbances of the manufacturing systems.

A predetermined production schedule may be often disturbed, due to unscheduled disruptions, such as delays of manufacturing operations and failures in manufacturing equipment. A genetic algorithm based reactive scheduling method was proposed in the previous research, in order to modify and improve a disturbed initial production schedule without suspending the progress of manufacturing process. This paper deals with a new reactive scheduling method, which changes both loading sequences of jobs on each resource and machining sequences of each job simultaneously by using a co-evolutionary genetic algorithm. A prototype of integrated reactive scheduling system was developed to evaluate the effectiveness of the proposed method through some computational experiments.

Recently, new distributed architectures of manufacturing systems are proposed, aiming at realizing more flexible control structures of the manufacturing systems. However, the human operators have not yet been discussed for the autonomous components of the distributed manufacturing systems. A real-time scheduling method is proposed, in this research, to select suitable combinations of the human operators, the resources and the jobs for the manufacturing processes. The proposed scheduling method consists of following three steps. In the first step, the human operators select their favorite manufacturing processes which they will carry out in the next time period, based on their preferences. In the second step, the machine tools and the jobs select suitable combinations for the next machining processes. In the third step, the automated guided vehicles and the jobs select suitable combinations for the next transportation processes.

This research proposes a dynamic task reallocation method for cellular manufacturing systems. When unforeseen changes, such as delays of assembly processes, occur in the manufacturing systems, the predetermined initial task allocation is dynamically modified, in order to minimize the total tardiness of products. All the tasks are reallocated to the individual workers real-timely by using genetic algorithm, and the execution sequences of the reallocated tasks are determined by using a heuristic rule, called as EDD. A learning curve effect is considered in this research in generation of a suitable production schedule. A prototype of reallocation supporting system is developed based on the proposed method, and the effectiveness of the proposed method is verified through some computational experiments.

The objective of the research is to establish mathematical models representing the kinematic motion deviations of the machine tools on the basis of the geometric tolerances of the components, and to apply the models to theoretical analysis of the kinematic motion deviations of the machine tools. Mathematical models are proposed to represent the kinematic motion deviations of the linear tables of the machine tools. The proposed models give the relationships between the geometric tolerances of the guide-ways of the components and the kinematic motion deviations of the linear tables. The models of the linear tables are combined to represent the whole machine tools to represent the positional deviations of the tools against the workpieces. The developed models are applied to the analysis of the kinematic motion deviations of the machine tools, aiming at clarifying the effects of the geometric deviations of the components on the kinematic motion deviations between the tools and the workpieces.

従来のスケジューリング問題に関する研究では，各生産設備における作業時間は確定値として取り扱われている．しかし，実際の生産システムにおける作業時間は，ばらつきを含んでいる．本研究では，作業時間のばらつきを正規分布と仮定して，スケジュール結果を示すガントチャート上で，各作業の終了時刻のばらつきを近似する手法を提案する．さらに，作業時間のばらつきが異なる作業者を適切な工作機械に割り付ける方法を提案する．

The objective of the present research is to develop systematic methods for planning and analysis of the geometric tolerances of the three-dimensional machine products. The tolerance zones of the geometric features have been investigated, in the previous paper, based on the definitions of the geometric tolerances, and the parameters have been defined to describe the statistical deviations of the geometric features within the tolerance zones. Mathematical methods are discussed, in the present paper, to estimate the statistical deviations of the positions and the orientations of the geometric features, based on the deviation parameters and the relationships between the datum features and the target features. In particular, emphasis is given to the analysis of the statistical deviations of the geometric features under the MMC (maximum material conditions), which specifies the interaction between the dimensional tolerances and the geometric tolerances. The proposed method is applied to the analysis of the deviations of the geometric features, to which both the dimensional tolerances and the geometric tolerances are required.

The objective of the present research is to develop systematic methods for planning and analysis of the geometric tolerances of the three-dimensional machine products. The tolerance zones of the geometric features have been investigated, in the previous paper, based on the definitions of the geometric tolerances, and the parameters have been defined to describe the statistical deviations of the geometric features within the tolerance zones. Mathematical methods are discussed, in the present paper, to estimate the statistical deviations of the positions and the orientations of the geometric features, based on the deviation parameters and the relationships between the datum features and the target features. In particular, emphasis is given to the analysis of the statistical deviations of the geometric features under the MMC (maximum material conditions), which specifies the interaction between the dimensional tolerances and the geometric tolerances. The proposed method is applied to the analysis of the deviations of the geometric features, to which both the dimensional tolerances and the geometric tolerances are required.

This research proposes a reallocation method of workers in a cellular manufacturing system. When the delays of manufacturing processes occur in the manufacturing system, the workers move from one working area to another working area based on a reallocation plan of workers, in order to minimize the maximum tardiness of products without interrupting the manufacturing processes. The reallocation plan modifies the initial allocation of workers and the initial production schedule by using genetic algorithm. A prototype of reallocation supporting system is developed based on the proposed method, and the effectiveness of the proposed method is verified through some computational experiments.

Recently, new distributed architectures of manufacturing systems are proposed, aiming at realizing more flexible control structures of the manufacturing systems. Many researches have been carried out to discus distributed architectures for planning and control of the systems. However, the labor has not been considered enough for the components of the manufacturing system based on distributed architecture, in the previous researches. In this research, the function of labor is discussed, and real-time scheduling process based on decision making by labor is proposed. The interface between the labor and the real-time scheduling system is also proposed.

This paper deals with a real-time scheduling system of the Holonic Manufacturing Systems (HMSs). In the previous papers, real-time scheduling processes based on the utility values have been proposed and applied to the HMSs. A simulation based procedure has also been implemented to estimate the future status of HMSs and to determine the utility values aiming at improving scheduling method. However, it was assumed that only one holon in the HMSs carries out the estimation, in the previous research, for the ease of the estimation process. A simulation based real-time scheduling method is newly proposed, in the paper, to improve the estimation process which enable all the holons to estimate the future status of the HMS. Some case studies of the real-time scheduling are carried out to verify the effectiveness of the proposed method.

Uncertainties of operation time of manufacturing operations are not considered in the conventional scheduling problems, however the operation time may have some uncertainty and distributions for the case of the manual operations and the long distance transportations. An approximation method is proposed in the paper to estimate the distributions of the finish time of all the operations in the scheduling results, based on the mean values and the standard deviations of the operation time.

本研究では，多階層の動的サプライチェーンを表現するための基本構成要素として，３階層の動的サプライチェーンモデルを提案し，各企業が自身の生産スケジュールを改善しながら，交渉を進めることで，協調的に契約を成立させる手法を提案する．さらに，動的サプライチェーンのシミュレーションシステムを開発し，計算機実験を行うことで，本手法の有効性を検証する．

This research deals with the three layered supply chain model which consist of material company, assembly company and client. The supply chain model based on the reactive scheduling and inventory management is proposed in order to decide the suitable price and due-date.

Uncertainties of operation time in manufacturing processes are not considered in the conventional scheduling problems, however the operation time may have some uncertainty and distributions for the case of the manual operations and the long distance transportations. An approximation method is proposed in the paper to estimate the distributions of the finish time of all the operations in the scheduling results, based on the mean values and the standard deviations of the operation time.

This paper deals with a Holonic Manufacturing Systems (HMS) for machining process. The labors are newly considered for the components of the HMS. Real-time scheduling process based on decision of labor is proposed in this paper.

本研究ではこれまでに，一対のサプライヤとクライアントが，生産スケジュールを改善しながら交渉を繰り返すことで，オーダの納期と価格を決定する動的サプライチェーンモデルを提案した．本報では，複数のクライアントからのオーダに対して，機会損失を起こさないように，サプライヤが複数の生産スケジューリングを並列に実行し，適切なオファ（Offer）を生成する手法を提案する．さらに，シミュレーションシステムを用いて，その有効性を検証する．

This paper deals with a real-time scheduling system of HMSs (Holonic Manufacturing Systems). A scheduling process based on the utility values have been proposed and applied to the realtime scheduling problems of the HMSs in the previous report. It was shown that the proposed methods generate suitable schedules from the view point of the objective functions of the individual holons in the HMSs. A new real-time scheduling method is proposed, in the paper, to consider both the objective functions of the individual holons and the whole HMSs. In this method, all the pareto optimal combinations of the resource holons and the job holons are generated based on the objective function values of the individual holons. Following this, a most suitable combination is selected from the pareto optimal ones, based on the objective functions of the whole HMSs, such as total make span and total tardiness. It is shown, through case studies, that the proposed method is effective to improve the production schedules from the viewpoint of the objective functions of the whole HMSs in comparison with the previous method.

This paper deals with a real-time scheduling system of HMSs (Holonic Manufacturing Systems). A scheduling process based on the utility values have been proposed and applied to the realtime scheduling problems of the HMSs in the previous report. It was shown that the proposed methods generate suitable schedules from the view point of the objective functions of the individual holons in the HMSs. A new real-time scheduling method is proposed, in the paper, to consider both the objective functions of the individual holons and the whole HMSs. In this method, all the pareto optimal combinations of the resource holons and the job holons are generated based on the objective function values of the individual holons. Following this, a most suitable combination is selected from the pareto optimal ones, based on the objective functions of the whole HMSs, such as total make span and total tardiness. It is shown, through case studies, that the proposed method is effective to improve the production schedules from the viewpoint of the objective functions of the whole HMSs in comparison with the previous method.

New architectures of manufacturing systems have been proposed aiming at realizing more flexible control structures of manufacturing systems, which can cope with dynamic changes in volume and variety of products, and also with unscheduled disruptions. They are so called as autonomous distributed manufacturing systems, random manufacturing systems, biological manufacturing systems, and holonic manufacturing systems. The objective of the present research is to develop an integrated process planning and scheduling system, which is applicable to the holonic manufacturing systems (HMS). A basic architecture and systematic methods are proposed to determine suitable sequences of machining equipment needed to manufacture the products and suitable production schedules for the machining equipment in the HMS. Procedures are developed to select suitable sequences of machining equipment for individual products, and to determine suitable production schendules of machining equipment based on the process plans of the products.

New architectures of manufacturing systems have been proposed aiming at realizing more flexible control structures of manufacturing systems, which can cope with dynamic changes in volume and variety of products, and also with unscheduled disruptions. They are so called as autonomous distributed manufacturing systems, random manufacturing systems, biological manufacturing systems, and holonic manufacturing systems. The objective of the present research is to develop an integrated process planning and scheduling system, which is applicable to the holonic manufacturing systems (HMS). A basic architecture and systematic methods are proposed to determine suitable sequences of machining equipment needed to manufacture the products and suitable production schedules for the machining equipment in the HMS. Procedures are developed to select suitable sequences of machining equipment for individual products, and to determine suitable production schendules of machining equipment based on the process plans of the products.

This paper deals with a real-time scheduling system of HMS (Holonic Manufacturing System). Simulation based procedures have been proposed and implemented to estimate the future status of HMS and to determine the utility values, in the previous paper. The objective of this research is to improve the estimation procedure of the future status of HMS. A neural network model is proposed to represent the decision criteria of the utility values of the job holons and the resource holons. The neural network model proposed here is used by the job holons and the resource holons, in order that a holon estimates the future status of the HMS for selecting its suitable utility values in the real-time scheduling process. Some case studies are carried out for verifying the effectiveness of the proposed model.

This paper deals with a real-time scheduling method of the Holonic Manufacturing Systems (HMSs). A real-time scheduling process based on the utility values have been proposed and applied to the HMSs in the previous report. The holons in the HMSs are divided into two classes based on their roles in the manufacturing processes. They are, automatic machine tool holons which transform the jobs, and job holons which are transformed by the automatic machine tool from the blank materials to the final products. AGV holons and labor holons in the HMSs are newly considered in this report AGV holons transport the jobs ; labor holons transport the jobs and also transform the jobs.

Manufacturing systems are required to change the manufacturing performance, such as manufacturing volume and cycle time, since consumer&#039;s needs change continuously. A new flexible manufacturing system called cellular manufacturing systems was proposed in order to satisfy this requirement. Cellular manufacturing systems need a suitable control method to change the manufacturing performance in case of unforeseen changes, such as delays of manufacturing processes. This research proposes a dynamic reallocation method of workers in cellular manufacturing systems by using Genetic Algorithm. This method provides new allocations of workers dynamically in order to minimize the maximum tardiness of jobs in consideration of learning of workers. A prototype of reallocation support system was developed to evaluate the effectiveness of the proposed method.

This paper deals with a real-time scheduling system of the Holonic Manufacturing Systems (HMSs). In the previous papers, real-time scheduling processes based on the utility values have been proposed and applied to the HMSs. A simulation based procedure has also been implemented to estimate the future status of HMSs and to determine the utility values aiming at improving scheduling method. However, it was assumed that only one holon in the HMSs carries out the estimation, in the previous research, for the ease of the estimation process. A simulation based real-time scheduling method is newly proposed, in the paper, to improve the objective function values by estimating the future status of HMSs by all the holons. Some case studies of the real-time scheduling are carried out to verify the effectiveness of the proposed method.

This paper deals with a real-time scheduling system of the Holonic Manufacturing Systems (HMSs). In the previous papers, real-time scheduling method based on the utility values have been proposed and applied to the HMSs. In this method, individual job holons and resource holons determine the utility values for the next machining operation based on their own decision criteria. Reinforcement learning is applied to the job holons, in the paper, in order to make the suitable decision criteria for determination of utility values. Some case studies of the real-time scheduling are carried out to verify the effectiveness of the proposed method.

Uncertainties of operation time in manufacturing processes are not considered in the conventional scheduling problems, however the operation time may have some uncertainty and distributions for the case of the manual operations and the long distance transportations. An approximation method is proposed in the paper to estimate the distributions of the finish time of all the operations in the scheduling results, based on the mean values and the standard deviations of the operation time.

This paper deals with a real-time scheduling system of HMS (Holonic Manufacturing System). Simulation based procedures have been proposed and implemented to estimate the future status of HMS and to determine the utility values, in the previous paper. The objective of this research is to improve the estimation procedure of the future status of HMS. A neural network model is proposed to represent the decision criteria of the utility values of the job holons and the resource holons. The neural network model proposed here is used by the job holons and the resource holons, in order that a holon estimates the future status of the HMS for selecting its suitable utility values in the real-time scheduling process. Some case studies are carried out for verifying the effectiveness of the proposed model.

Supply chain should be continuously designed and redesigned in order to dynamically configure suitable clients and suppliers in multiple supply chains. The previous research proposed a dynamic configuration method of supply chains. The proposed method provides suitable delivery time and prices of products by the negotiation between clients and suppliers and by the modification of the existing production schedules of suppliers. The actual delivery time of some products is later than the contracted delivery time in the modification process of the production schedule. The clients permit the delays of actual delivery time by accepting the penalty cost for the delays. However, the supplier loses the credibility with the clients in the actual supply chain. This research evaluates the credibility of suppliers from the viewpoint of the delay of actual delivery time. Some computational experiments are carried out by using a prototype of supply chain simulation system in order to evaluate the effectiveness of the proposed method from the viewpoint of the credibility of suppliers.

This research deals with a dynamic supply chain model, which represents the decision-making process of a set of clients and suppliers. The suitable prices and delivery time are determined through the iteration of the negotiation process among the clients and the suppliers and the modification process of the production schedule. It is impossible for the suppliers to simultaneously generate suitable prices and delivery time of two or more new products in the decision-making process. This research improves the dynamic supply chain model in order to generate suitable offers for multiple orders from two or more clients.

著者らはこれまでに，サプライヤが生産スケジュールを改善しながらクライアントと交渉を行うことで，新規オーダの納期と価格を決定する動的サプライチェーンモデルを提案した．本報では，そのモデルに基づき，動的サプライチェーンシミュレーションシステムのプロトタイプを開発し，２階層の動的サプライチェーンモデルを用いた計算機実験を行うことで，サプライヤの利益，およびクライアントの納期と価格の観点から，提案したモデルの有効性を検証する．

Unscheduled disruptions often occur in the actual manufacturing systems, and an initial production schedule may not satisfy the constraints due to the disruptions. A reactive scheduling method based on Genetic Algorithm (GA) was, therefore, proposed to improve the disturbed production schedule in the previous research. This research deals with a new crossover method to improve the performance of the GA based reactive scheduling process for the tardiness minimization problems and the total flow time minimization problems. The multi&amp;ndash;objective reactive scheduling method is also proposed based on the improved reactive scheduling method in this research. The combination of the dominance of genes is discussed for the multi&amp;ndash;objective reactive scheduling problems of the tardiness minimization and the total flow time minimization. A prototype of reactive scheduling system is developed to evaluate the effectiveness of the proposed method.

Unscheduled disruptions often occur in the actual manufacturing systems. A systematic scheduling method is therefore required to modify and improve the initial production schedule in order to cope with the unexpected disturbances. The previous researches proposed the Genetic Algorithm based reactive scheduling method that improves the initial production schedule without interrupting the manufacturing processes. This research proposes a new crossover method based on the dominance of gene in order to modify the production schedule faster than the previous method.

Dimensional tolerances and geometric tolerances of three-dimensional product shapes are very important for manufacturing process control and quality control of mechanical products. The objective of the present research is to develop systematic methods for planning and analysis of the geometric tolerances of the three-dimensional mechanical products. The tolerance zones of the geometric features have been investigated, in the previous paper, based on the definitions of the geometric tolerances, and the parameters have been defined to describe the deviations of the geometric features within the tolerance zones. Mathematical methods are discussed, in the present paper, to estimate the statistical deviations of the positions and the orientations of the geometric features, based on the deviation parameters and the relationships between the datum features and the target features. In particular, emphasis is given to the analysis of the statistical deviations of the geometric features under the MMC (Maximum Material Conditions), which specifies the interaction between the dimensional tolerances and the geometric tolerances. The proposed method is applied to the analysis of the deviations of the geometric features, to which both the dimensional tolerances and the geometric tolerances are required.

This paper deals with a real-time scheduling system of HMS (Holonic Manufacturing System). Simulation based procedures have been proposed and implemented to estimate the future status of HMS and to determine the effectiveness values, in the previous paper. The objective of this research is to improve the estimation procedure of the future status of HMS. A neural network model is proposed to represent the evaluation criteria of the effectiveness values of the job holons and the resource holons. The neural network model proposed here is used by the job holons and the resource holons, in order that a holon estimates the future status of the HMS for selecting its suitable effectiveness values in the real-time scheduling process. Some case studies are carried out for verifying the effectiveness of the proposed model.

A systematic scheduling method is required to modify the predetermined production schedules in order to cope with unforeseen changes in manufacturing systems. The objective of the present research is to propose a scheduling method based on GA (Genetic Algorithm) for modifying delayed production schedules due to the additional jobs, reactively. A prototype of reactive scheduling system is developed and applied to scheduling problems. The effectiveness of the proposed method is verified through the numerical expreriments of the reactive scheduling problems.

A systematic scheduling method is required to modify the predetermined production schedules in order to cope with unforeseen changes in manufacturing systems. The objective of the present research is to propose a scheduling method based on GA (Genetic Algorithm) for modifying delayed production schedules due to the additional jobs, reactively. A prototype of reactive scheduling system is developed and applied to scheduling problems. The effectiveness of the proposed method is verified through the numerical expreriments of the reactive scheduling problems.

The objective of the present research is to develop a systematic method for planning and analysis of kinematic motion deviations of machine tools based on geometric tolerances of three-dimensional components. This paper deals with the modeling and analysis of the geometric deviations of the toleranced components. The tolerance zones of the geometric features of the components are investigated and classified based on the definitions of the geometric tolerances. The parameters are defined to describe the deviations of the geometric features within the tolerance zones. An analytical method is proposed to estimate the statistic deviations of the positions and the orientations of the geometric features, based on the deviation parameters and the relationships between the datum features and the toleranced features.

Manufacturing systems are required to change the manufacturing performance, such as manufacturing volume and cycle time, since consumer&#039;s needs change continuously. A new flexible manufacturing system called cellular manufacturing systems was proposed in order to satisfy this requirement. Cellular manufacturing systems need a suitable control method to change the manufacturing performance in case of unforeseen changes, such as delays of manufacturing processes. This research proposes a dynamic reallocation method of workers in cellular manufacturing systems by using Genetic Algorithm. This method provides new allocations of workers dynamically in order to minimize the tardiness of jobs. A prototype of reallocation support system was developed to evaluate the effectiveness of the proposed method.

This paper deals with a real-time scheduling method of HMS (Holonic Manufacturing System). A real-time scheduling process based on the estimation of future status of the HMS have been proposed and applied to the real-time scheduling problems of the HMS in the previous report. Only one holon estimates the future status of HMS to determine the next machining schedule by using a simulation, in the previous method. New systematic methods for the individual holons are proposed, in the paper, to make all the holons determine the next machining schedules based on the future status of HMS estimated by simulaton, aiming at improving the previous methods. The effectiveness of the proposed methods are verified through the case studies.

A systematic scheduling method is required to modify the predetermined production schedules in order to cope with unforeseen changes in manufacturing systems. The objective of the present research is to propose a scheduling method based on GA (Genetic Algorithm) for modifying delayed production schedules due to the additional jobs, reactively. A prototype of reactive scheduling system is developed and applied to scheduling problems. The effectiveness of the proposed method is verified through the numerical experiments of the reactive scheduling problems.

A reactive scheduling method based on GA (Genetic Algorithm) was proposed in the previous research. The method can improve the delayed production schedules by unscheduled changes, without interrupting the progress of the manufacturing process. This research improves the reactive scheduling method for multi-objective problems by using multi-objective GA.

Since consumer&#039;s needs dynamically change, manufacturing systems are required for changing manufacturing performance, such as manufacturing volume and cycle time, continuously. A new flexible manufacturing system called cellular manufacturing systems are proposed in order to satisfy this requirement. Cellular manufacturing systems need a suitable control method to change the manufacturing performance in case of unforeseen changes, such as delays of manufacturing processes. This research proposes a dynamic reallocation method of workers in cellular manufacturing systems. This method dynamically provides an allocation of workers in order to minimize the tardiness of jobs. A prototype of reallocation support system was developed to evaluate the effectiveness of the proposed method.

The objective of the present research is to develop a systematic method for planning and analysis of kinematic motion deviations of machine tools based on geometric tolerances of three-dimensional components. This paper deals with the modeling and analysis of the geometric deviations of the toleranced components. The tolerance zones of the geometric features of the components are investigated and classified based on the definitions of the geometric tolerances. The parameters are defined to describe the deviations of the geometric features within the tolerance zones. An analytical method is proposed to estimate the statistic deviations of the positions and the orientations of the geometric features, based on the deviation parameters and the relationships between the datum features and the toleranced features.

This research deals with a dynamic supply chain model, which represents the decision&amp;ndash;making and communication process among the clients and the suppliers of the products. The suitable prices and delivery dates are determined through the iteration of the negotiation process among the clients and the suppliers. The high priority products on the delivery dates are manufactured more quickly than the low priority products on the delivery date through the modification process of the production schedule. On the other hand, the low priority products come down in the prices by receiving the reward from the clients ordering the high priority products. The suppliers get a chance to accept a lot of orders and become profitable by improving the production schedule.

Supply chain should be continuously designed and redesigned in order to dynamically configure suitable clients and suppliers in multiple supply chains. This research proposes a configuration method for dynamic configuration of supply chains. The proposed method provides suitable due-dates and prices of products by the negotiation between clients and suppliers and by the modification of the existing production schedules of suppliers. A prototype system of supply chain simulation was developed and some computational experiments were carried out in order to evaluate the effectiveness of the proposed method from the viewpoint of the profit and the customer satisfaction.

本研究では，これまでリアクティブスケジューリングに遺伝的アルゴリズムを適用してきた．リアクティブスケジューリングでは生産活動と並行して生産スケジュールの変更を行うため，迅速に解を求める必要がある．そこで，本研究では，スケジューリングの目的関数に応じた下界値を定義し，その値に基づいて目的を満たさない遺伝子のみを交叉させることにより，効率的に探索を行うことができる交叉法を提案する．また，提案する交叉法を適用したリアクティブスケジューリングシステムのプロトタイプを開発し，計算機実験を行うことにより本研究の有効性を検証する．

近年，複数の顧客・企業間におけるサプライチェーンの形成に関する研究が必要とされており，適切な取引先を逐次組み替える動的サプライチェーン（Dynamic Supply Chain，以下ではDSCと呼ぶ）の研究が行われている．DSCでは，サプライヤの利益を最大化するとともに，クライアントの顧客満足度を最大化する適切な契約手法が必要である．本研究では，納期に対するクライアントの要求の度合いとサプライヤの生産性をリアルタイムに考慮した適切な価格の決定手法を提案する．まず，受注型生産を対象として，クライアントとサプライヤの交渉により，生産スケジュールを考慮して価格を決定する価格モデルを提案する．次に，生産スケジュールの変更およびクライアントとサプライヤ間の交渉の繰返しにより，納期と価格を決定するプロセスを提案する．さらに，複数のクライアントとサプライヤによるDSCシミュレーションシステムのプロトタイプを開発し，簡単な例を用いて，本手法の有効性を検証する．

This paper deals with a real-time scheduling system of HMS (Holonic Manufacturing System). A decision making process based on the effectiveness values have been proposed and applied to the real-time scheduling problems of the HMS in the previous report. New systematic methods for the individual holons are proposed, in the paper, to determine the effectiveness values based on the estimation of the future HMS status, aiming at improving the previous methods. Simulation based procedures are newly developed and implemented to estimate the future HMS status and to determine the effectiveness values. The effectiveness of the proposed methods are verified through the case studies.

This paper deals with a real-time scheduling system of HMS (Holonic Manufacturing System). A decision making process based on the effectiveness values have been proposed and applied to the real-time scheduling problems of the HMS in the previous report. New systematic methods for the individual holons are proposed, in the paper, to determine the effectiveness values based on the estimation of the future HMS status, aiming at improving the previous methods. Simulation based procedures are newly developed and implemented to estimate the future HMS status and to determine the effectiveness values. The effectiveness of the proposed methods are verified through the case studies.

New architectures of manufacturing systems have been proposed aiming at realizing more flexible control structures of manufacturing systems which can cope with dynamic changes in volume and variety of products. They are so called as holonic manufacturing systems, autonomous distributed manufacturing systems, random manufacturing systems and biological manufacturing systems. The objective of the present research is to develop an integrated process planning and scheduling system which is applicable to the holonic manufacturing systems. In the previous paper, a systematic method is proposed to select suitable sequences of machining equipment, by applying the genetic algorithm (GA) and the dynamic programming (DP) methods. The method is extended, in the present paper, to consider the production schedules of the machining equipment.

New architectures of manufacturing systems have been proposed aiming at realizing more flexible control structures of manufacturing systems which can cope with dynamic changes in volume and variety of products. They are so called as holonic manufacturing systems, autonomous distributed manufacturing systems, random manufacturing systems and biological manufacturing systems. The objective of the present research is to develop an integrated process planning and scheduling system which is applicable to the holonic manufacturing systems. In the previous paper, a systematic method is proposed to select suitable sequences of machining equipment, by applying the genetic algorithm (GA) and the dynamic programming (DP) methods. The method is extended, in the present paper, to consider the production schedules of the machining equipment.

Unscheduled disruptions often occur in the actual manufacturing systems, and an initial production schedule may not satisfy the constraints due to the disruptions. A reactive scheduling method based on Genetic Algorithm (GA) was, therefore, proposed to improve the disturbed production schedule in the previous research. This research deals with improvement of the reactive scheduling method for consideration of setup operations. Setup operations are modeled, and the previous reactive scheduling method is modified to generate suitable production schedules that contain setup operations.

This paper deals with a real-time scheduling system of HMS (Holonic Manufacturing System). A decision making process based on the effectiveness values have been proposed and applied to the real-time scheduling problems of the HMS in the previous report. New systematic methods for the individual holons are proposed, in the paper, to determine the effectiveness values based on the estimation of the future HMS status, aiming at improving the previous methods. The effectiveness of the proposed methods are verified through the case studies.

Unscheduled disruptions often occur in the actual manufacturing systems, and an initial production schedule may not satisfy the constraints due to the disruptions. A reactive scheduling method based on Genetic Algorithm (GA) was, therefore, proposed to improve the disturbed production schedule in the previous research. This research deals with improvement of the reactive scheduling method for tardiness minimization problems. A new crossover method is proposed to generate more suitable individuals in the reactive scheduling process than the previous crossover method. A prototype of reactive scheduling system was developed to evaluate the effectiveness of the proposed method.

Much emphasis has been given to minimize the time not only for design and manufacturing of products but also for development of production lines, in order to deliver products to market as soon as possible. However, planning, design and evaluation processes of production lines are very complicated, and individual engineers carry out the production lines&#039; design based on their own experiences. It is now eagerly required to establish systematic methods and support tools, in order to support re-design of the production lines. The objective of this research is to propose a re-design method for production lines by using the technique of numerical analysis

This paper deals with a real time scheduling system of a holonic manufacturing system for machining process. The holonic manufacturing system was proposed aiming at realizing more flexible and robust control structures of the manufacturing systems which can cope with the variety of the products and the unscheduled disruptions, such as status changes of equipment and input of high priority jobs. New systematic methods for the individual holons are proposed in the paper, to determine the effectiveness values based on estimation of system status.

In the research, a reactive scheduling method based on GA (Genetic Algorithm) is proposed to modify the delayed production schedules. The proposed method modifies the predetermined production schedules from the viewpoint of tardiness, when unforeseen delays of manufacturing processes occur in the manufacturing systems. The proposed method modifies in consideration of alternative resources. Effectiveness of the proposed reactive scheduling method is verified through several computational experiments in terms of the optimization of the production schedules.

This paper deals with a real time scheduling system of HMS (Holonic Manufacturing System). A decision making process based on the effectiveness values have been proposed and applied to the real-time scheduling problems of the HMS in the previous report. New systematic methods for the individual holons are proposed, in the paper, to determine the effectiveness values based on the estimation of the future HMS status, aiming at improving the previous methods. Simulation based procedures are newly developed and implemented to estimate the future HMS status and to determine the effectiveness values. The effectiveness of the proposed methods are verified through the case studies.

著者らは,多重のサプライチェーンの中で企業が継続して利益を得るための戦略の構築を目標としている.本研究では,まず1顧客1企業間における企業間契約について検討した.ここでは,GAを用いたリアクティブスケジューリング手法を拡張して,生産スケジュールの変更と交渉により,受注生産における適切な納期と価格を算出する方法を提案した.さらに,プロトタイプシステムを開発し,簡単な例を適用した.

本研究では,生産活動中に生じる作業の遅延や特急ジョブの追加などの外乱に対して遺伝的アルゴリズムを用いたリアクティブスケジューリング手法を提案してきた.これまでの研究では,総処理時間があらかじめ定めた基準を満たさなくなる場合に,生産活動を中断することなくスケジュールを改善する手法を提案した.本研究では,複数の目的関数を同時に改善することができるように拡張を行う.

本研究ではこれまでに,ホロニック生産システムにおける効用値に基づくリアルタイムスケジューリング手法を提案した.しかしこの手法では,個々のホロンが自身の目的関数に基づいて適切な加工プロセスを決定することができるが,システム全体の目的関数を考慮することはできない.そこで本研究では,個々のホロンとシステム全体の目的関数の最適化を同時に考慮することができる新しいリアルタイムスケジューリング手法を提案する.

生産活動中に処理時間の遅延やジョブの追加が発生した場合，迅速にスケジュールを変更する必要がある．本研究では，遺伝的アルゴリズムにより，初期スケジュールにおいて作業が開始していないオペレーションの処理順序を適切に変更することにより，迅速にスケジュールを変更するリアクティブスケジューリング手法を提案する．

A systematic method is eagerly required to modify the predetermined production schedules in order to cope with unforeseen changes in manufacturing systems, such as delays of manufacturing processes. The objective of the present research is to propose a scheduling method based on GA (Genetic Algorithm) for modifying delayed production schedules reactively. A prototype of reactive scheduling system is developed and applied to scheduling problems. The effectiveness of the proposed method is verified through the comparison of the experimental results of the reactive scheduling with the ones of the rule-based real-time scheduling.

A systematic method is eagerly required to modify the predetermined production schedules in order to cope with unforeseen changes in manufacturing systems, such as delays of manufacturing processes. The objective of the present research is to propose a scheduling method based on GA (Genetic Algorithm) for modifying delayed production schedules reactively. A prototype of reactive scheduling system is developed and applied to scheduling problems. The effectiveness of the proposed method is verified through the comparison of the experimental results of the reactive scheduling with the ones of the rule-based real-time scheduling.

This paper deals with a real time scheduling system of a holonic manufacturing system for machining process. The holonic manufacturing system was proposed by HMS cooperative research project aiming at realizing more flexible and robust control structures of the manufacturing systems which can cope with the changes of the product volume and variety and the unscheduled disruptions, such as status changes of equipment and input of high priority jobs. Decision-making procedures of individual holons are discussed in the paper to establish a real time scheduling of the holonic manufacturing systems. Systematic procedures are proposed for coordination process among holons based on effectiveness values of the individual holons. The effectiveness values are evaluated by the individual holons referring to their own objective functions.

This paper deals with a real time scheduling system of a holonic manufacturing system for machining process. The holonic manufacturing system was proposed by HMS cooperative research project aiming at realizing more flexible and robust control structures of the manufacturing systems which can cope with the changes of the product volume and variety and the unscheduled disruptions, such as status changes of equipment and input of high priority jobs. Decision-making procedures of individual holons are discussed in the paper to establish a real time scheduling of the holonic manufacturing systems. Systematic procedures are proposed for coordination process among holons based on effectiveness values of the individual holons. The effectiveness values are evaluated by the individual holons referring to their own objective functions.

Design processes of production lines are very complicated, and individual manufacturing engineers carry out production line design based on their own experiences. It is now eagerly required to establish systematic methods and supporting tools, in order to support all the design processes of the production lines. The objective of the research is to establish systematic methods and computerized support systems for the design processes of production lines by using numerical analysis.

This paper deals with a real time scheduling system of a holonic manufacturing system for machining process. The holonic manufacturing system was proposed by HMS cooperative research project aiming at realizing more flexible and robust control structures of the manufacturing systems which can cope with the changes of the product volume and variety and the unscheduled disruptions, such as status changes of equipment and input of high priority jobs. Decision-making procedures of individual holons are discussed in the paper to establish a real time scheduling of the holonic manufacturing systems. Systematic procedures are proposed for coordination process among holons based on effectiveness values of the individual holons. The effectiveness values are evaluated by the individual holons referring to their own objective functions.

ホロニック生産システムにおけるリアルタイムスケジューリングでは，生産システム内に存在する構成要素であるホロンが，実際に生産を行いつつ意思決定を行い，その結果としてスケジュールが作成される．本研究ではこれまでに，ホロンが効用値に基づいて意思決定を行う，意思決定プロセスを提案した．本報告では，ホロンが将来の生産システムの状態を予測して，その情報を用いて効用値を算出する方法について基礎的な検討を行う．

これまでに著者らは，加工作業の遅延に対し，生産開始前に作成した生産スケジュールを，遺伝的アルゴリズムを用いて，適切な生産スケジュールに変更するリアクティブスケジューリング手法を提案した．本報告では，これを拡張して，加工中に発生した不良によるジョブの再投入や，オーダの不規則な追加に対して，リアクティブスケジューリングを行う方法を提案する．さらに，プロトタイプシステムを開発し，簡単な例題に適用する．

ホロニック生産システムにおけるリアルタイムスケジューリングでは，生産システム内に存在する構成要素であるホロンが，実際に生産を行いつつ意思決定を行い，スケジュールを作成する．本研究ではこれまでに，ホロンが効用値に基づいて意思決定を行う意思決定プロセスを提案した．本報告では，ホロンがシミュレーションを行い，将来の目的関数の値を予測して，自身の意思決定を行う方法を提案する．

生産活動中に特急ジョブが発生した場合，迅速に初期スケジュールを変更する必要がある．本研究では，遺伝的アルゴリズムを用いて初期スケジュールを適切に改善するリアクティブスケジューリング手法を提案する．本報では，分岐限界法に基づき，初期スケジュールの総加工時間に影響を与えない時間区間にジョブを追加することにで，遺伝的アルゴリズムの初期個体群を生成する手法を提案する．

本研究では，既存の生産ラインの設計プロセスに関する情報を利用することにより，要求仕様を満たさない生産ラインを迅速に再設計することを目的としている．本報では，最小の変更量で要求仕様を満たす生産ラインへ再設計するために，設計プロセスの入出力情報に対して，感度解析とニュートンラプソン法を用い，変更すべき生産ラインの複数の属性値とその変更量を特定する方法を提案する．

Recently, new architectures of manufacturing systems have been proposed to realize flexible control structures of manufacturing systems, which can cope with dynamic changes in volume and variety of products and also unforeseen disruptions, such as malfunctions of manufacturing resources and interruptions by high priority jobs. They are so called as autonomous distributed manufacturing system, biological manufacturing system and holonic manufacturing system. Rule-based scheduling methods have been proposed and applied to the real-time production scheduling problems of the HMS (Holonic Manufacturing System) in the previous report. However, there are still remaining problems from the viewpoint for the improvement of the objective functions of the individual holons.
A new simulation system is proposed in the present paper to verify the real-time scheduling process in the HMS. New procedures are also proposed to select the production schedules, aimed at generating effective production schedules in real-time. The proposed methods enable the individual holons to select suitable machining operations to be carried out in the next time period.

Recently, new architectures of manufacturing systems have been proposed to realize flexible control structures of manufacturing systems, which can cope with dynamic changes in volume and variety of products and also unforeseen disruptions, such as malfunctions of manufacturing resources and interruptions by high priority jobs. They are so called as autonomous distributed manufacturing system, biological manufacturing system and holonic manufacturing system. Rule-based scheduling methods have been proposed and applied to the real-time production scheduling problems of the HMS (Holonic Manufacturing System) in the previous report. However, there are still remaining problems from the viewpoint for the improvement of the objective functions of the individual holons.
A new simulation system is proposed in the present paper to verify the real-time scheduling process in the HMS. New procedures are also proposed to select the production schedules, aimed at generating effective production schedules in real-time. The proposed methods enable the individual holons to select suitable machining operations to be carried out in the next time period.

Manufacturing system engineering process (MSE process) is investigated to establish a systematic and computerized support system for planning, design and evaluation processes of the manufacturing systems. A description method is proposed to describe the MSE process. The proposed method is applied to description of the MSE process for the automotive parts manufacturing system. According to the analysis of the description, a prototype of a computerized support system is developed for MSE processes in order to support the manufacturing engineering processes.

Manufacturing system engineering process (MSE process) is investigated to establish a systematic and computerized support system for planning, design and evaluation processes of the manufacturing systems. A description method is proposed to describe the MSE process. The proposed method is applied to description of the MSE process for the automotive parts manufacturing system. According to the analysis of the description, a prototype of a computerized support system is developed for MSE processes in order to support the manufacturing engineering processes.

This paper deals with a real time scheduling system of a holonic manufacturing system for machining process. The holonic manufacturing system was proposed by HMS cooperative research project aiming at realizing more flexible control structures of the manufacturing systems which can cope with the variety of the products and the unscheduled disruption, such as status changes of equipment and input of high priority jobs. Decision-making procedures of individual holons are discussed in the paper to establish a decision making process based on effectiveness for the holonic real time scheduling systems.

Much emphasis has been given to minimize the time not only for design and manufacturing of products but also for development of production lines, in order to deliver products to market as soon as possible. However, planning, design and evaluation processes of production lines are very complicated, and individual engineers carry out the production lines&#039; design based on their own experiences. It is now eagerly required to establish systematic methods and support tools, in order to support all the engineering processes for the planning, design, evaluation and redesign of the production lines. The objective of the research is to establish systematic methods and computerized support systems based on cluster analysis, in order to deal with the redesign of the existing production lines.

In the research, a reactive scheduling method based on GA (Genetic Algorithm) is proposed to modify the delayed production schedules. The proposed method modifies the predetermined production schedules reactively without interrupting the progresses of the manufacturing processes, when unforeseen delays of manufacturing processes are occurred in the manufacturing systems. A reactive scheduling method for multi-layered manufacturing systems is also proposed in order to modify the production schedules of all the layers concurrently and to keep the consistency among the production schedules of all the layers in the manufacturing systems. Effectiveness of the proposed reactive scheduling method is verified through several computational experiments in terms of the optimization of the production schedules and the computation time of the modification processes in the multi-layered manufacturing systems.

This paper deals with real-time scheduling system in a holonic manufacturing system for machining process. The holonic manufacturing system was proposed by HMS cooperative research project aiming at realizing more flexible control structures of the manufacturing system which can cope with the variety of the products and the unscheduled disruptions, such as status changes of equipment and input of high priority jobs. Decision making processes of Holons are newly proposed here to satisfy not only flexibility but also optimality of real-time scheduling in HMS.

This paper deals with a real time scheduling system of a holonic manufacturing system for machining process. The holonic manufacturing system was proposed by HMS cooperative research project aiming at realizing more flexible control structures of the manufacturing systems which can cope with the variety of the products and the unscheduled disruptions, such as status changes of equipment and input of high priority jobs. Decision making procedures of individual holons are discussed in the paper to establish a decision making process based on utilities for the holonic real time scheduling systems.

Much emphasis has been given to minimize the time not only for design and manufacturing of products but also for development of manufacturing lines, in order to deliver products to market as soon as possible. However, planning, design and evaluation processes of manufacturing lines are very complicated, and individual engineers carry out the manufacturing lines&#039; design based on their own experiences. It is now eagerly required to establish systematic methods and support tools, in order to support all the engineering processes for the planning, design, evaluation and redesign of the manufacturing lines. The objective of the research is to establish systematic methods and computerized support systems for manufacturing lines&#039; design based on cluster analysis and sensitivity analysis.

Planning, design and evaluation processes of manufacturing systems are very complicated, and individual manufacturing engineers carry out manufacturing system design based on their own experiences. It is now eagerly required to establish systematic methods and supporting tools, in order to support all the engineering processes for the planning, design and evaluation of the manufacturing systems. The objective of the research is to describe and analyze the actual manufacturing system engineering (MSE) processes in order to establish systematic methods and computerized support systems for the MSE processes.

This paper deals with a real time scheduling system of a holonic manufacturing system for machining process. The holonic manufacturing system was proposed aiming at realizing more flexible and robust control structures of the manufacturing systems which can cope with the variety of the products and the unscheduled disruptions, such as status changes of equipment and input of high priority jobs. Decision making procedures of individual holons are discussed in the paper to establish a real-time scheduling method, and an emulation system for evaluation of real-time scheduling process.

生産活動中に発生した予測できない変化により，あらかじめ作成した生産スケジュール通りに生産活動を行えなくなった場合，即座に初期スケジュールを変更し，納期を満たす生産スケジュールを迅速に求める必要がある．これまでに著者らは，加工時間の遅延に対応することができる，遺伝的アルゴリズムを用いたリアクティブスケジューリング手法を提案した．本研究ではこれを拡張し，生産活動中に生産ラインへジョブが追加された場合においても，生産スケジュールを迅速に改善することができる手法を提案する．またリアクティブスケジューリングシステムのプロトタイプを開発し，本手法の有効性を検証する．

This paper deals with a simulation system of a holonic manufacturing system for machining process. The holonic manufacturing system was proposed by HMS cooperative research project aiming at realizing more flexible control structures of the manufacturing system which can cope with the variety of the products and the unscheduled disruptions, such as status changes of equipment and input of high priority jobs. A real-time scheduling procedure is applied to the simulation of the machining processes. A user interface system is developed in the study in order to provide the manufacturirrg engineers with a method to change the status of the equipment and the jobs. The simulation system is applied to verify the adaptability of the holonic manufacturing system to the addition of the high priority jobs and the status changes of the equipment.

Production scheduling tasks are in general carried out hierarchically and concurrently, such as scheduling for manufacturing systems, for factories and for shops, by different persons and/or organizations. Therefore, a systematic procedure is eagerly required to change the schedules and to keep the consistency among the hierarchical scheduling tasks, when some unforeseen disruptions occur in the manufacturing systems. A rescheduling method is proposed to change the schedules and to keep the consistency among the schedules of the large manufacturing systems. A prototype of distributed reactive scheduling system for large manufacturing systems is developed and applied to the consistency management problems in the rescheduling tasks.

This paper deals with a simulation system for holonic manufacturing systems. The holonic manufacturing system was proposed by HMS cooperative research project aiming at realizing more flexible control structures of the manufacturing system which can cope with the variety of the products and the unscheduled disruptions, such as break down of equipment and input of high priority jobs. A real-time scheduling procedure is implemented in the holonic manufacturing system simulation. A user interface system is developed in the study to provide the manufacturing engineers with interactive methods to change the status of the equipment and the jobs. The simulation system is applied to the holonic manufacturing system simulation for adding the high priority jobs and for changing the equipment status.

Production scheduling tasks are carried out hierarchically and concurrently, such as production scheduling for manufacturing systems, for factories and for shops, by different persons and/or organizations. Therefore, a systematic procedure is eagerly required to change the production schedules and to keep the consistency among the hierarchical scheduling tasks, when some unforeseen disruptions occur in the manufacturing systems. A rescheduling method is proposed to change the production schedules and to keep the consistency among the production schedules of the hierarchical and decentralized manufacturing systems. A prototype of distributed reactive scheduling system for the hierarchical and decentralized manufacturing systems is developed and applied to the consistency management problems in the rescheduling tasks.

This paper deals with a real time scheduling system of a holonic manufacturing system for machining process. The holonic manufacturing system was proposed by HMS cooperative research project aiming at realizing more flexible control structures of the manufacturing systems which can cope with the variety of the products and the unscheduled disruptions, such as status changes of equipment and input of high priority jobs. Decision making procedures of individual holons are discussed in the paper to establish a framework for the holonic real time scheduling systems.

Production scheduling tasks are in general carried out hierarchically and concurrently, such as scheduling for manufacturing systems, for factories and for shops, by different persons and/or organizations. Therefore, a systematic procedure is eagerly required to change the schedules and to keep the consistency among the hierarchical scheduling tasks, when some unforeseen disruptions occur in the manufacturing systems. The objectives of the research are to establish a systematic method for supporting the rescheduling tasks and for keeping the consistency among the various layers of schedules of the hierarchical and decentralized manufacturing systems. Models for hierarchical production schedules are proposed, and rescheduling procedures are also developed based on the models. A rescheduling method is proposed to change the schedules and to keep the consistency among the schedules. A prototype of hierarchical and concurrent rescheduling system is developed and applied to the consistency management problems in the rescheduling tasks. © 2001, The Japan Society of Mechanical Engineers. All rights reserved.

Production scheduling tasks are in general carried out hierarchically and concurrently, such as scheduling for manufacturing systems, for factories and for shops, by different persons and/or organizations. Therefore, a systematic procedure is eagerly required to change the schedules and to keep the consistency among the hierarchical scheduling tasks, when some unforeseen disruptions occur in the manufacturing systems. The objectives of the research are to establish a systematic method for supporting the rescheduling tasks and for keeping the consistency among the various layers of schedules of the hierarchical and decentralized manufacturing systems. Models for hierarchical production schedules are proposed, and rescheduling procedures are also developed based on the models. A rescheduling method is proposed to change the schedules and to keep the consistency among the schedules. A prototype of hierarchical and concurrent rescheduling system is developed and applied to the consistency management problems in the rescheduling tasks. © 2001, The Japan Society of Mechanical Engineers. All rights reserved.

Production scheduling tasks are in general carried out hierarchically and concurrently, such as scheduling for manufacturing systems, for factories and for shops, by different persons and/or organizations. Therefore, a systematic procedure is eagerly required to change the schedules and to keep the consistency among the hierarchical scheduling tasks, when some unforeseen disruptions occur in the manufacturing systems. The objectives of the research are to establish a systematic method for supporting the rescheduling tasks and for keeping the consistency among the various layers of schedules of the hierarchical and decentralized manufacturing systems. Models for hierarchical production schedules are proposed, and rescheduling procedures are also developed based on the models. A rescheduling method is proposed to change the schedules and to keep the consistency among the schedules. A prototype of hierarchical and concurrent rescheduling system is developed and applied to the consistency management problems in the rescheduling tasks. © 2001, The Japan Society of Mechanical Engineers. All rights reserved.

This paper deals with a real-time scheduling system of a holonic manufacturing system. Holonic manufacturing system is proposed aiming at realizing more flexible control structures of the manufacturing system which can cope with the variety of the products and the unscheduled disruptions such as breakdown of equipment. An object-oriented modeling method is adopted to represent holonic components of the manufacturing system including workpieces and manufacturing equipment. We develop an object-oriented real-time scheduling system for a holonic manufacturing system. In this system the holonic components can carry out the decision-making referring to the status of the manufacturing system at the same time, and resolve conflicts.

Production scheduling takes are carried out hierarchically and concurrently, such as scheduling for manufacturing systems, for factories and for shops, by different persons and/or preanizations. Therefore, a systematic procedure is eagerly required to change the schedules and to keep the consistency among the hierarchical scheduling tasks, when some unforeseen disruptions occur in the manufacturing systems. The objective of the research are to establish a systematic method for supporting the rescheduling tasks and for keeping the consistency among the various layers of schedules of the hierarchical and decentralized manufacturing systems. A rescheduling method is proposed to change the schedules and to keep the consistency among the schedules. A prototype of hierarchical and concurrent rescheduling system is developed and applied to the consistency management problems in the rescheduling tasks.

Planning, design and evaluations processes of manufacturing system are very complicated, and individual engineers carry out the manufacturing system design based on their own experiences. It is now eagerly required to support all the engineering processes for planning, design and evaluation on the manufacturing systems with computers. The objective of the present research is to develop computerized system to support manufacturing system engineering (MSE). Models of MSE processes are proposed, and the actual MSE processes are described and analyzed by using of systematic description methods. A prototype of computer aided support system is developed and applied to case studies.

Planning, design and evaluation processes of manufacturing systems are very complicated, and individual manufacturing engineers carry out manufacturing system design based on their own experiences. It is now eagerly required to establish systematic methods and supporting tools, in order to support all the engineering processes for the planning, design and evaluation of the manufacturing systems. The objective of the research is to establish systematic methods and computerized support systems for the manufacturing system engineering (MSE) processes.

This paper deals with a real-time scheduling system for holonic manufacturing systems. An object-oriented simulation model is adopted to develop a simulation model of a holonic machining system. A mechanism is implemented to the simulation system in order to carry holonic out real-time scheduling for the holonic machining system.

In design and planning of manufacturing systems, a wide variety of models representing the manufacturing systems are required for simulation and verification from various viewpoints. These models are concurrently developed and applied to various application fields, therefore, a computerized support system is needed for concurrent development and consistency management of the various manufacturing system models. The objective of the research is to develop an object-oriented model repository aiming at supporting concurrent development and consistency management of the various manufacturing system models for production planning. Contents and structures of manufacturing system models are discussed from the viewpoint of the concurrent and hierarchical production planning problems. Model components and their relations to be stored in the model repository are proposed. A prototype of a model repository is developed and applied to the production planning problems.

Computer-integrated manufacturing (CIM) draws upon many important areas of manufacturing automation, such as CAD, CAM and MRP. It is not necessarily the sum of these compooents but the linking of them into an interoperable system that satisfies the various strategies and objectives of the CIM systems. The objective of the present research is to develop a formal modelling method in order to realize concurrent development and integration of the various CIM models. A model architecture of the CIM is discussed to establish systematic and logical criteria for classifying the CIM models. A computer-aided method is also proposed based on the model architecture in order to examine the consistency among a set of CIM models which are designed to represent the various aspects of the CIM system being analyzed.

The present research deals with the modeling and analysis of the geometric deviations of the toleranced components. The tolerance zones of the geometric features of the components are investigated and classified based on the definitions of the geometric tolerances. The parameters are defined to describe the deviations of the geometric features within the tolerance zones. An analytical method is proposed to estimate the statistic deviations of the positions and the orientations of the geometric features, based on the deviation parameters and the relationships between the datum features and the toleranced features.

Previous researches provided a reactive scheduling method based on a genetic algorithm. The existing method was able to modify and optimize disturbed initial production schedules without interrupting the progress of manufacturing processes. This research proposes a multi-objective reactive scheduling method based on a co-evolutionary approach, and develops a prototype system of reactive scheduling in order to evaluate the effectiveness of the proposed method.

(1)Modeling of distributed manufacturing systems
A model has been proposed to represent autonomous distributed manufacturing systems of machine products. In the model, all the components and the decision-making units are represented by applying agent modeling methods.
(2)Description of uncertainty of manufacturing processes
Uncertainty of manufacturing processes was discussed from the viewpoint of the distribution of the operation time, and a description method was proposed to represent the manufacturing operation time according to the normal distribution.
(3)Simulation model of distributed manufacturing systems
A simulation model was proposed to simulate the distributed decision-making processes of the manufacturing system components and the progress of the manufacturing processes. The manufacturing operation time is represented by both the mean values and the standard deviations to give the uncertainty.
(4)Scheduling system considering uncertainty
A rule-based production scheduling method was developed to generate a suitable production schedules taking into consideration of the distributions of the manufacturing operation time.
(5)Production planning considering uncertainty
A rule-based production planning method was also developed to generate a suitable production plans taking into consideration of the distributions of the manufacturing operation time.
(6)Verification of proposed method
The proposed methods have been verified by applying the simulation system.

The results of the research project are summarized in the followings.
(1)Basic Architecture of Autonomous Distributed Manufacturing Systems
A basic architecture of the distributed manufacturing systems is discussed from the viewpoint of production planning, process planning and resource planning of the machine products. Systematic procedures are proposed in the distributed decision-making environment, in order to generate suitable plans based on the volumes and the varieties of the products to be manufactured in the manufacturing systems. Communication interfaces among the decision-making units are also discussed for the information exchange among the autonomous decision-making units.
(2)Development of Production Planning, Process Planning and Resource Planning Systems
Autonomous distributed systems are developed, based on the basic architecture proposed in (1), to carry out the production planning, process planning and resource planning of the manufacturing systems. In the research projects, a real-time scheduling system is proposed to generate the production schedules real-timely, based on the process plans of the products to be manufactured. This system provides us a systematic method to generate a suitable production schedules when executing the manufacturing processes. An integrated process planning and scheduling system is also developed to generate both the process plans and the production schedules in the planning phase.
(3)Development of Simulation System and Verification of Autonomous Distributed Manufacturing System
A simulation system is developed, by applying the multi-agent programming method, in order to simulate the process planning and the scheduling process of the manufacturing systems. Some case studies have been carried out to verify the effectiveness of the proposed systems, by applying the developed simulation system. It was shown, through case studies, that the proposed systems are effective from the viewpoint of the integration of the production planning, the process planning and the resource planning for the autonomous distributed manufacturing systems.

平成14年度は,生産開始後に発生した加工設備の作業の遅延に対して,生産開始前に作成した生産スケジュールを,遺伝的アルゴリズムを用いて,適切な生産スケジュールに変更するリアクティブスケジューリング手法を提案し,リアクティブスケジューリングシステムのプロトタイプを開発した.
平成15年度は,工場層やライン層など,階層の異なる複数のリアクティブスケジューリングシステム間で,生産スケジュールの整合性を管理しながら,同時かつ並列に生産スケジュールを改善するコンカレントプロセスを提案した.さらに,オブジェクト指向言語SmalltalkとCORBAを用いて,階層の異なるリアクティブスケジューリングシステムをネットワーク上の2つのコンピュータに実装し,階層分散型リアクティブスケジューリングシステムのプロトタイプを開発した.
これまでに開発した手法は,単一目的のスケジューリング問題しか扱うことができなかった.そこで,平成16年度は,複数の目的関数を同時に考慮することができるように,従来のリアクティブスケジューリング手法の拡張を行った.この手法は,新たな加工作業が開始するまでの間は,Goldbergのランキング法に基づいて個体を選好するとともに,新たな加工作業が開始する時点においては,重みパラメータ法を用いて個体を選好する.これにより,生産活動と並行して,生産スケジュールを改善することができる.次に,既存のリアクティブスケジューリングシステムを拡張して,多目的リアクティブスケジューリングシステムのプロトタイプを開発し,総処理時間最小化と納期遅れ和最小化の二目的のスケジューリング問題に適用することで,提案した手法の有効性を検証した.

(1) Development of CAM system for plate parts.
A CAM system has been developed to generate NC data for drilling and reaming processes of the plates of the injection molds and the die-casting dies, based on the input information about the CAD data of the plates given in the IGES and/or DXF formats. The machining technology data for the drilling and the reaming processes are investigated and stored in the machining technology database. The database gives the relationships between the geometric and technological information about the holes to be machined and the machining information about the machining processes, such as the tools, the cutting conditions and the cutter location data.
(2) Development of distributed scheduling system for HMS
An object-oriented modeling technique is adopted to represent the holonic components of the manufacturing systems including workpieces and manufacturing resources. An object-oriented simulation system is developed to represent and to simulate real-time scheduling processes in the holonic manufacturing system. A set of simulation is carried our to verify the decision rules for the real-time scheduling from the viewpoint of the total make-span and the adaptability to the failure of the manufacturing resources.
(3) Verifications of the developed system.
The systems developed in the research have been verified from the viewpoint of both the process planning and scheduling in the holonic manufacturing systems

あらかじめ作成されたスケジュールに,機械の故障などの予期できない変更が生じた場合,階層分散型生産システムの全構成要素のスケジュール間で整合性を保持しながら,最上位階層の全体の納期を満たすように,迅速にスケジュールを変更(リスケジューリング)しなければならない.本研究では,階層分散型生産システムのスケジュール間の整合性を保持しながら,全体の納期を満たすように,全ての階層で同時並列にリスケジューリングを行うスケジューリングシステムを開発した.結果を以下にまとめる.
コンカレントにスケジューリングを実行するアルゴリズムを提案した.
1.リスケジューリング・アルゴリズムの提案
処理の遅れ等の問題が生じた際,階層の異なる複数の生産スケジュールにおいて,同時にリスケジューリングを検討し,その結果を重ね合せることで,問題を解消するアルゴリズムとして,コンカレント・リスケジューリング手法を提案した.
2.プログラムモジュールの開発
平成11年度に作成した情報変換プロトコルと,上記1.で提案したアルゴリズムに基づき,オブジェクト指向プログラミング言語Smalltalkを用いてプログラムモジュールを開発した.このプログラムモジュールは,CORBAに準拠して,異なる階層のスケジュール間で情報をリアルタイムに授受するとともに,コンカレント・リスケジューリングを実行することができる.
3.コンカレント・リスケジューリングの試行
平成11年度に作成したGAおよびジョンソン法のスケジューリングモジュールと,上記3.で作成したプログラムモジュールを結合し,階層分散スケジューリングシステムを開発した.このシステムを用いて,スケジューリングのコンカレント化および,リスケジューリングの協調を試行し,本手法の有効性を検証した.

The results of the research project are summarized in the followings.
(1) A basic architecture of holonic manufacturing systems (HMS) was discussed from the viewpoint of the autonomous decision-making and cooperation of the holonic components (holons). In particular, cooperative scheduling methodologies were investigated to establish a holonic scheduling system of the HMS.
(2) Simulation models of the holons were proposed by applying the object-oriented modeling method. The models represent the decision-making processes and the machining processes of all the holons imt the HMS.
(3) An object oriented simulation system has been developed, aimed at verifying the scheduling algorithms of the HMS.The simulation model consists of a set of object representing the machining equipment holons and the workpiece holons.
(4) A cooperative and hierarchical scheduling method was proposed based on the Genetic Algorithms. The proposed method determines suitable machining schedules of the individual machining holons referring to the pre-determined machining sequences of the workpieces to be machined.
(5) A prototype of the cooperative and hierarchical scheduling system has been developed by using Smalltalk, and applied to the scheduling problems of the hierarchical manufacturing systems.
(6) A holonic process planning system was proposed to determine suitable process plans for the workpiece holons based on the machining information about the machining features included in the workpiece holons.
(7) An optimization method was proposed by applying both the Genetic Algorithm and Dynamic Programming method, in order to select suitable machining sequences and suitable sequences of machining equipment. The proposed method can select suitable sequences of the machining equipment considering the machining schedules of the equipment. The method provides the workpiece holons with a systematic decision-making method to plan a suitable machining processes based on both the machining features and the machining schedules.
(8) The proposed methods me verified by applying the simulation system of the HMS, and it was shown through the case studies that the proposed methods are effective to establish the autonomous and cooperative decision-making system in the HMS.

The objective of the present research is to establish systematic methods for design and management of an autonomous distributed manufacturing system which consists of a set of autonomous manufacturing equipment and workpieces. The results of the research are summarized as follows ;
1. Architecture of autonomous distributed manufacturing system
Autonomous functions of individual components of the manufacturing system are discussed and analyzed from the viewpoint of decision making, communication and control functions. It was clarified, through the analysis, that the cooperation between the autonomous manufacturing equipment and the autonomous workpieces play a key role in the design and management of the autonomous distributed manufacturing systems.
2. Development of simulation systems of the autonomous distributed manufacturing systems
Simulation systems have been developed based on the object oriented model in order to represent the cooperative function among the autonomous elements in the manufacturing systems and to simulate autonomous controls of the manufacturing systems. Two types of simulation systems have been developed for both the batch type production of mechanical products and the line type production of the composite parts for air crafts.
3. Application to autonomous real-time scheduling
Real-time scheduling systems have been developed based on the models proposed 2. It was clarified, through the simulations, that the autonomous real-time scheduling methods are effective to determine suitable schedules for the individual equipment and workpieces in the manufacturing systems.

本研究課題では，製品から複数の部品を分解する順序だけでなく，分解した部品の洗浄や検査などの後処理工程の順序までを包括的に考慮したスケジュールの動的最適化手法を提案した．本研究では，進化型計算アルゴリズムにおいて，部品の分解順序を木構造で表す遺伝子モデルを用いた．また，後処理工程の順序は，部品に施す後処理工程の数だけ部品名を1列に並べた遺伝子モデルで表現した．これら2種類の個体群の最適な組み合わせを求めながら，各個体の進化プロセスを進めることで，より適切なスケジュールを探索する方法を示した．さらに，パソコン上にスケジューリングシステムを実装し，計算機実験を行うことで，その有効性を検証した．