We present a pull system that uses a new approach to facilitate material control and scheduling in a disassembly environment and is called the multi Kanban system for disassembly (MKSD). Within the MKSD is an approach to optimize operation and mitigate supply chain risk factors as well. We also compare the performance of MKSD to its "push" counterpart. Various scenarios are explored using a case example. For the scenarios, the assumptions, input data and results are presented. The study clearly demonstrates the effectiveness of the multi Kanban system over the push system. (C) 2012 Elsevier B.V. All rights reserved.

Offering a well-designed reverse supply chain programme can significantly improve the ability of any organisation to differentiate itself, and even to take market share away, from its competitors. Reverse supply chain considerations should be a part of an organisation's corporate strategy. From a macro-level perspective, value propositions of reverse supply chains in for an organisation, and/or the industry in which the organisation operates, include considerations for both strategies (to reuse, repair, refurbish, remanufacture, retrieve parts or cannibalise components, recycle, scrap, redesign returned products, etc.) and effective operations (to handle and sort returns by value and ease of remanufacture) to sustain and even enhance organisational competency. In this article, we examine the role of sorting used products before disassembly for parts retrieval and remanufacturing under stochastic variability based on customer demand using a Markov decision process. We address a problem of managing costs in a remanufacturing environment with stochastically variable demand and model it for two types of used parts. Each part type is assumed to have varying quality and acquisition costs. The cost function includes manufacturing, holding and backlog costs components. We compute optimal purchase policy that maximises the expected average profit per period. Using a case example from photocopier industry, numerical analysis is performed to study the implications of various holding cost for two parts on optimal purchase policy in remanufacturing environments.

Under stochastic demand and deterministic processing times, we discussed a single-stage JIT production system with the production-ordering and supplier kanbans and derived a probability generating function (p.g.f.) of the stationary distributions of the backlogged demand. In this paper, we extend the system to supply chain management (SCM) in JIT environment with two kinds of kanbans under stochastic demand, deterministic processing times and withdrawals with lead time. These conditions are more realistic than the previous papers. We develop an algorithm for the exact performance evaluation of the SCM such as the stationary distributions of the inventory level, production quantities and total backlogged demand in each stage, using discrete-time Markov process. Optimal numbers of two kinds of kanbans in the system are determined by minimizing a general total cost function. Numerical examples are given to show the efficiency of the proposed approach. (c) 2008 Elsevier B.V. All rights reserved.

This paper proposes a new approach to environmental-performance evaluation (EPE) with consideration for multiple types of environmental management systems (EMSs) for establishing a Plan-Do-Check-Act ( PDCA) management cycle in the system. First, we summarize the background of the environmentally conscious society and manufacturing. Then, ISO14001 is explained as one of the useful approaches in realizing the environmental conscious management system. Finally, we suggest the new approach to EPE using data-envelop analysis (DEA). In this approach, we determine the input and output factors to obtain the performances of each EMS and compare the performances of the same type of companies using DEA. The result is used as information to maintain the continuous improvement in the system.

An optimal control problem of a remanufacturing system under stochastic demand is studied. The system is formulated by a Markov decision process, which is a class of stochastic sequential processes in which the reward and transition probability depend only on the current state of the system and the current action. The models have gained recognition in such diverse fields as engineering, economics, communications, etc. Each model consists of states, actions, rewards and transition probabilities. The paper considers two types of inventories: the actual product inventory in a factory and the virtual inventory used by a customer. The state of the remanufacturing system is defined by both inventory levels. One can obtain the optimal production policy that minimizes the expected average cost per period. The paper also considers some scenarios under various conditions and shows the example of controlling the remanufacturing system.

Industry has mass-produced and consumed resources to optimize only by the criteria of economical efficiencies. Most products are produced without any environmental considerations being enough. Exhaustion of resources happened with mass production, so that waste sites are overflowing. In this paper, we summarize the actions of the manufacturing industry in the Recycling-based Society. We develop a remanufacturing system in which the products are collected from the customers. In this paper, we calculate the average cost per period. We investigate cost factors using design of experiment and discuss their effects on the remanufactoring system.

The continuous growth in consumer waste in recent years has seriously threatened the environment. Environmentally conscious manufacturing and product recovery has become an obligation to the environment and to society. Many countries are contemplating regulations that force manufacturers to take back used products from consumers so that the components and materials retrieved from the products may be reused and/or recycled. We focus on a product recovery system in a remanufacturing system. Product recovery aims to minimize the amount of waste sent to landfills by recovering materials and parts from old or outdated products by means of recycling and remanufacturing. It should be considered when designing and managing the manufacturing systems. We propose a new analytical approach to evaluating the product recovery system with stochastic variability. This model applies the traditional inventory theory to the production/ inventory management with consideration for disposal and return. The system is formulated by a discrete time Markov chain. It is composed of the states denoted by the number of the inventory, the transition probabilities between states and the costs associated with the transitions. Using the Markov analysis, we can calculate the total expected average cost per period exactly. Numerical examples are given to show the property of the management system and optimize the product recovery system.

We consider a production system in a general cofifiguration with a new control strategy: the push policy for the part sending and the kanban mechanism for the work-in-process (WIP). The production system is composed of many stations (or workshops) such as an entry station, a set of workstations, a central station, and an exit station. This type of system is modeled as an open queueing network (OQN) in a general configuration with a Markov-type part sending policy and a machine no blocking (MNB) mechanism. The most important performance measures of the production system are the total throughput of the workstations and the total blocking flow of blocked parts sent from the workstations to the central station. This paper discusses an optimization problem with multiple objectives: allocate kanbans to the workstations so as to simultaneously maximize the total throughput and minimize the total blocking flow. Based on a semi-open decomposition approach, several useful properties of the system are characterized. These properties are used to develop a marginal algorithm for the optimization problem. Moreover, a dynamic simulation approach is devised as a tool for evaluating the quality of the solutions obtained by the algorithm. Numerical experiments are provided demonstrate the efficiency of the algorithm through the simulation approach.

We consider a production system comprising multiple stations (or workshops) such as an entry station, a set of work stations, a central station, and an exit station, which are arranged in a general configuration. A worker (or a vehicle tool) is assigned to each station, who sends a part from the station to the destination station according to the required process path of the part. Any part is allowed to visit a work station more than once if its process path requires. We propose a new control strategy with the push policy for instructing each worker to send a part and the kanban mechanism for controlling the work-in-process (WIP) in each work station. As all work stations have limited local buffers, the central station is used for storing blocked parts temporarily. Such a production system is modeled as an open queueing network in a general configuration with a Markovian part sending policy and a machine no blocking mechanism. The queueing network is analytically characterized. Some important performance measures are compared with other control strategies. A semi-open decomposition approach is applied to the queueing network for computing the blocking probabilities when parts arrive at the work stations. An algorithm is developed based on the semi-open decomposition approach. Numerical experiments show the quality of the solutions obtained by the algorithm as well as a property of a performance measure. (C) 2001 John Wiley & Sons, Inc.

We consider a production system in a general configuration with a new control strategy: the push mechanism for the part transport and the kanban technique for the work-in-process (WIP). The production system is composed of many stations such as an entrance station, a set of work stations, a central station, and an exit station, that are arranged in a general configuration. The push mechanism is followed for transporting a part from a station to a destination station. The kanban technique is adopted for controlling the WIP in a work station. The production system is modeled by a closed queuing network in a general configuration with a Markov part sending mechanism and a machine no blocking (MNB) technique. An optimal part sending policy that maximizes the expected system throughput is formulated into a long run average semi-Markov decision process. Three solution approaches are developed for obtaining optimal or suboptimal solutions. Numerical examples are given to evaluate the quality of the solutions obtained by the solution approaches.

A management information system (MIS) is one of the important systems to control materials and information harmoniously. The previous design approaches dealt with it qualitatively. Therefore, it was impossible to smooth the office works in the management system. In this paper, we design the MIS using a stochastic Petri net (SPN). First, we describe a typical MIS and explain the concept of SPN. Next, we construct the MIS as the SPN model and obtain the total expected sojourn time of documents in each section. Finally, we propose the design for the MIS with consideration for the smoothing of the office works. (C) 1999 Elsevier Science B.V. All rights reserved.

The production-ordering and withdrawal kanbans are used in a Just-in-Time (JIT) production system. In particular, a withdrawal kanban used for a vendor is called a supplier kanban. This paper deals with the JIT production system with the production-ordering and supplier kanbans under stochastic demand. A necessary and sufficient condition, called a stability condition, is derived under which the JIT production system has a stationary distribution of the backlogged demand. An algorithm is devised for determining optimal numbers of two kinds of kanbans that minimize an expected average cost per period. In other words, it determines optimal values of the safety stocks included in the popular formulas for computing the numbers of kanbans. Numerical results are given to show its efficiency.