2022/09/28 更新

写真a

イシダ コウセイ
石田 航星
所属
理工学術院 創造理工学部
職名
准教授

兼担

  • 理工学術院   大学院創造理工学研究科

学内研究所等

  • 2020年
    -
    2022年

    理工学術院総合研究所   兼任研究員

学歴

  •  
    -
    2014年

    早稲田大学   創造理工学研究科   建築学専攻  

  •  
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    2014年

    早稲田大学  

  •  
    -
    2011年

    早稲田大学   創造理工学研究科   建築学専攻  

  •  
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    2011年

    早稲田大学  

  •  
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    2009年

    早稲田大学   理工学部   建築学科  

  •  
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    2009年

    早稲田大学  

▼全件表示

学位

  • Waseda University   Doctor of Engineering

経歴

  • 2021年04月
    -
    継続中

    早稲田大学   理工学術院 創造理工学部 建築学科   准教授

  • 2018年04月
    -
    2021年03月

    早稲田大学   理工学術院創造理工学部建築学科   講師(専任)

  • 2014年04月
    -
    2018年03月

    工学院大学   建築学部建築学科   助教

  • 2012年
    -
    2014年

    早稲田大学創造理工学部建築学科 助手

所属学協会

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    日本建築学会

  •  
     
     

    Architectural Institute of Japan

 

研究分野

  • 建築計画、都市計画

研究キーワード

  • 測量

  • 作業能率

  • 情報化施工

論文

  • Evaluation of Drainage Gradient using Three-dimensional Measurement Data and Physics Engine

    Kosei Ishida

    Proceedings of the 37th International Symposium on Automation and Robotics in Construction (ISARC)     1219 - 1226  2020年10月  [査読有り]

    担当区分:筆頭著者

    DOI

  • FCIの分譲マンションへの応用及び修繕積立金残高に基づくマンションマネジメント手法の開発

    石井一輝, 村田裕嘉, 志手一哉, 石田航星

    建築生産シンポジウム論文集   35rd   245 - 252  2019年07月

  • 照明工事における作業時間に影響を与える潜在的因子の推定方法に関する研究

    石田 航星, 鳥越 順之

    日本建築学会計画系論文集   82 ( 739 ) 2361 - 2371  2017年09月  [査読有り]

     概要を見る

    &nbsp;Since many workers are involved in construction work, it is important to improve work efficiency. For this purpose, time duration and motion studies are often applied during construction work. The authors have developed methods for time and motion studies by using factor analysis. Moreover, in this paper, the authors describe analysis methods to improve work efficiency via factor analysis. The methods can be decomposed into the following seven steps:<br>&nbsp;1. Recording the tasks and activities of workers by using a camcorder<br>&nbsp;2. Observing and defining each task and activity of the workers<br>&nbsp;3. Evaluating each task and activity<br>&nbsp;4. Analyzing the task and activity times (time study)<br>&nbsp;5. Predicting the latent factors affecting task and activity times<br>&nbsp;6. Verifying the latent factor predictions via confirmatory factor analysis (CFA)<br>&nbsp;7. Analyzing the cause of work delay by using factor scores from CFA as the task and activity times<br>&nbsp;To illustrate time and motion studies by using factor analysis, we record the tasks and activities of workers. Fig. 2 shows an example of ceiling light installation work. Fig. 3 and Fig. 4 show the shape and product drawing of the luminaire, and Fig. 5 shows the office plan and layout of the luminaire employed in this study. Time to completion of the ceiling light installation work was two days with three construction workers working, as shown in Tables 1 and 2, respectively. We observed and defined the task, activities, and motions of the workers. Table 3 provides definitions for each activity and motion of ceiling light installation. The motions have been classified into 19 types, and represent a detailed analysis of work motions performed for a manual task.<br>&nbsp;Fig. 7 demonstrates the proportion of total performance duration of each installation activity. Three workers installed 49 LED luminaires. Fig. 8 and Table 4 demonstrate the proportions of activity performance duration for each worker relative to the proportional sum of duration. To analyze task and activity times, we evaluate the learning curve for installing ceiling lighting. Fig. 9 shows the task times of workers, as represented by time to complete the installation tasks. This figure shows that task time per unit decreases with increased installation task repetition.<br>&nbsp;After analyzing task and activity times, we applied factor analysis to the activity times. The purpose of this analysis was to predict the cause of work delay. First, in order to investigate the relationship between total completion time and individual activity time, we calculated the correlation between completion time and individual activity time. The results are shown in Table 4. To validate the probability distribution of task time and individual activity time, we provide histograms (Fig. 10) of the times taken to perform each task and activity.<br>&nbsp;Next, we applied exploratory factor analysis (EFA) to the six activity durations. By eigenvalue (Table 6) and parallel analysis, we determined the number of factors to be one or two. Table 7 shows the results of exploratory factor analysis. This table displays the respective loading of each variable onto each factor for the cases of one and two factors.<br>&nbsp;In the case of two factors, Factor 1 is defined as "work environment of back plate installation work, " and Factor 2 is defined as "work environment of electrical wiring." According to the results of EFA, we reevaluated the work-time relationship between each activity and the two factors F1 and F2. Next, we calculated the factor scores generated from CFA, as shown in Fig. 12, and analyzed the cause of work delay. Fig. 13 shows the relationship plot of factor scores obtained via CFA analyses, with the horizontal and vertical axes being the scores of F1 and F2, respectively.

    DOI CiNii J-GLOBAL

  • Investigating the accuracy of 3D models created using SfM

    石田 航星

    IAARC ISARC 2017     834 - 839  2017年06月

  • 建設会社の組織形態がBIMの導入に与える影響に関する研究

    石田 航星, 志手 一哉, 壹岐 健章

    日本建築学会計画系論文集   81 ( 726 ) 1743 - 1743  2016年08月  [査読有り]

     概要を見る

    &nbsp;Building information modeling (BIM) is an important technology in the design and construction of buildings. BIM is also used in the construction of building equipment. In recent years, construction companies have been promoting the introduction of BIM. Typically, the technologies of building construction are introduced for each department. However, BIM has been promoting technology introduction beyond departments and companies. Therefore, we analyzed the process of introducing BIM in construction companies. We also analyzed the proportion of companies that introduced BIM, process of technology introduction, and the organizational form of the construction companies.<br>&nbsp;In this study, we conducted a questionnaire survey of construction companies about BIM. Based on the questionnaire results, we performed an analysis of corporate organization as follows.<br>&nbsp;1. Analyze the relationship between the respondents of a department and technician experts by cross tabulation.<br>&nbsp;2. Classify respondents by factor analysis.<br>&nbsp;3. Discuss the motivation behind introducing BIM by covariance structure analysis.<br><br>&nbsp;The percentage of companies that have used BIM in their construction projects was approximately 32%. Moreover, 40% of the survey respondents collect BIM information. More than 50% of the respondents think that construction work using BIM is more efficient than the traditional construction work. These results mean that BIM entered a stage of popularity. On the other hand, the percentage of engineers that manipulate 3D-CAD or BIM is only approximately 23%. The occupation of the highest percentage of 3D-CAD users is construction engineers of building equipment. Architects are also a high percentage of 3D-CAD users. Then, we created a contingency table (Table 4) for the relationship between the current department and the specialized field of survey respondents. All personnel who belong to the building construction department are part of the specialized field of building construction. On the other hand, 22% of the personnel who belong to the architectural design department are part of a different specialized field of architectural design. Next, we performed an exploratory factor analysis on the questionnaire results. Maximum likelihood estimation with a promax rotation of 32 Likert scale questions was conducted on data gathered from 212 participants. The results of the promax rotation of the solution are listed in Table 8. When loadings less than 0.35 were excluded, the analysis yielded a seven-factor solution. The seven factors were labeled as follows: "Expectations of BIM (Factor 1)", "The degree of information gathering about BIM (Factor 2)", "The need for the introduction of front-loading (Factor 3)", "IT skill levels of the respondents (Factor 4)", &ldquo;Adequacy of information equipment in the belonging company (Factor 5)&rdquo;, &ldquo;Growth potential of the construction industry (Factor 6)&rdquo;, and &ldquo;Dissatisfaction with the current construction technology (Factor 7).&rdquo; Moreover, we performed a hierarchical cluster analysis by selecting three factors&mdash;Factor 2, Factor 4, and Factor 6. As a result, we classified four respondent groups. In addition, we analyzed of the motivation behind the introduction of BIM by structural equation modeling (SEM). The results of SEM analysis are shown in Fig. 12. SEM supposes that motivations behind introducing BIM are to improve productivity of the construction work.

    DOI CiNii J-GLOBAL

  • Construction Progress Management and Interior Work Analysis Using Kinect 3D Image Sensors

    石田 航星

    IAARC ISARC 2016     314 - 322  2016年07月

  • 繰返し工程に関する工程計画手法の開発:ネットワーク図の表現と日程計算

    嘉納 成男, 石田 航星

    日本建築学会計画系論文集   81 ( 723 ) 1195 - 1205  2016年  [査読有り]

     概要を見る

    &nbsp;1. Introduction<br>&nbsp;Although PERT/CPM method is recognized as an inevitable method for planning and scheduling in building construction projects, it has been applied to less construction projects as a planning and scheduling method, as it is not suitable for repetitive activities such as multi-floor buildings and large apartment houses with many dwellings. The authors proposed a new graphical representation which is based on the conventional network diagram and scheduling method for a building project with repetitive activities.<br><br>&nbsp;2. Previous Research Works<br>&nbsp;The authors reviewed the previous works, and pointed out that many research works on planning and scheduling for repetitive activities have been done, but that those research works modeled the repetitive activities using non-network diagrams. Furthermore, there has been no research work which has established the planning and scheduling method using network diagrams for repetitive activities.<br><br>&nbsp;3. Basic Concept of Network Diagram and Scheduling Method for Repetitive Activities<br>&nbsp;The authors proposed the network diagram which shows only the precedence relations among activities in common work zones. And the authors defined those relations in the table of activity data as well as in the table of work zone data. Moreover, the authors introduced the concept of &ldquo;work tickets&rdquo; as a work instruction for each work zone.<br>&nbsp;To calculate the schedule dates, the authors utilized the concept of the flow of work tickets along the precedence arrows in network diagrams. The time when the work ticket has entered into an activity and the time when it has left from the activity could correspond respectively to the start date and finish date.<br><br>&nbsp;4. Network Diagram and Scheduling Method for Sophisticated Repetitive Activities<br>&nbsp;To apply this method to sophisticated projects with repetitive activities, the authors developed the algorisms to handle the flow of &ldquo;work tickets&rdquo; in network diagrams so that the following conditions could be included in repetitive activities.<br>&nbsp;(1)Work zones which include activities of different contents and different durations<br>&nbsp;(2)Precedence relations between activities in different work zones<br>&nbsp;(3)Precedence relations to activities from activities in several work zones<br>&nbsp;(4)Restrictions which prohibit more than two simultaneous activities in a specific area<br><br>&nbsp;5. Verification of the Usefulness of the Scheduling Method<br>&nbsp;The authors applied this method to plan and schedule a four-story apartment house with 32 dwellings, so as to verify the usefulness to represent the sophisticated precedence relations among many work zones by using network diagrams and to calculate the earliest date and the latest date of each activity in the construction project. As the result of the verification, the authors successfully represented the repetitive activities as network diagrams, and correctly calculated the schedule date of each activity.<br><br>&nbsp;6. Conclusion<br>&nbsp;The authors summarized the feasible conditions of repetitive activities to which the method in this paper is able to be applied, and clarified this method would become more important as a planning and scheduling method, because the building construction project are required to be more efficient by applying repetitive activities in the project.

    DOI CiNii J-GLOBAL

  • 建築工事における3 次元スキャナの活用

    石田 航星

    開発工学   35 ( 1 ) 9 - 12  2015年

     概要を見る

    In this paper, the author describes a method of pre-cut components in finishing the interior works using 3D laser scanner.<br>In addition, the author describes the drywall panel layout optimization method which consists of the following two steps: first, to generate possible alternative patterns of drywall panel layout in a wall; second, for each alternative pattern, to find out the best combination of panel parts to be cut from a panel of standard size.

    DOI CiNii

  • 鉄筋コンクリート建築物におけるライフサイクル・マネジメントのための3次元計測技術に関する研究―3次元レーザースキャナーによる構造躯体の検査手法―

    石田航星

    コンクリート構造物の補修,補強,アップグレード論文報告集   14   587 - 594  2014年10月  [査読有り]

    J-GLOBAL

  • A Study on Measuring of Reinforced-Concrete Structure by 3D Laser Scanner and Making Design of Precut Interior Finishing Components with Polygon Model

    Kosei Ishida, Naruo Kano, Takeshi Igarashi

    30th International Symposium on Automation and Robotics in Construction(ISARC 2013)    2013年

  • 内装部材のプレカット化のための3次元レーザースキャナーを用いた計測と生産設計の手法に関する研究

    石田 航星, 嘉納 成男, 五十嵐 健, 藤井 裕彦, 大澤 雄司, 酒本 晋太郎, 冨田 裕行

    日本建築学会計画系論文集   78 ( 688 ) 1355 - 1363  2013年  [査読有り]

     概要を見る

    In this paper, the authors describe a method of pre-cut components in finishing the interior works using 3D laser scanner.<br> To implement the pre-cut is required for the following three methods. Firstly, the authors develop the benchmark system for matching three coordinate system ― existing building, point clouds and 3D CAD. Secondly, the authors develop the method of automatically seeking the couple of the targets for transforming the coordinates. Thirdly, the authors develop the design method by polygon model.<br> The authors scanned the reinforced concrete building and then applied those methods using 3D laser scanner.

    DOI CiNii J-GLOBAL

  • 内装間仕切壁におけるボード材の割付図と加工図の最適化に関する研究

    石田 航星, 嘉納 成男, 五十嵐 健

    日本建築学会計画系論文集   78 ( 692 ) 2173 - 2180  2013年  [査読有り]

     概要を見る

    This study is aimed at developing methods to optimize the material yield of drywall panels. In this paper, the authors describe the drywall panel layout optimization method which consists of the following two steps: first, to generate possible alternative patterns of drywall panel layout in a wall; second, for each alternative pattern, to find out the best combination of panel parts to be cut from a panel of standard size.<br> The authors applied this method to minimize the cost of drywall using plaster board (1820&times;910mm, 1820&times;606mm, 2000&times;1000mm, 2420&times;910mm).

    DOI CiNii J-GLOBAL

  • 3次元レーザースキャナーによるコンクリート躯体の計測とその形状解析

    嘉納 成男, 石田 航星

    コンクリート工学 = Concrete journal   50 ( 9 ) 856 - 862  2012年09月  [査読有り]

    DOI CiNii J-GLOBAL

  • Shape Recognition with Point Clouds in Rebars

    IAARC ISARC 2012  

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Misc

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受賞

  • 第31回建築生産シンポジウム若手研究者優秀発表賞

    2015年07月   日本建築学会  

    受賞者: 石田 航星

  • 第30回建築生産シンポジウム若手研究者優秀発表賞

    2014年08月   日本建築学会  

    受賞者: 石田 航星

  • 2013年度小野梓記念賞受賞者(学術賞)

    2013年  

  • ISARC Best Paper Award 2012

    2012年  

  • ISARC Best Paper Award 2012

    2012年  

講演・口頭発表等

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特定課題研究

  • 仮想空間における建築工事の再現手法に関する研究

    2018年  

     概要を見る

    建築工事は、クレーンやバックホウなどの工事機械と建材の運搬、加工、取付けを行う作業者の2つの主体により実行される。この2つの主体の再現に加えて、工事を行う敷地、仮設構造物、作業に使う資機材、そして建築物そのものを再現することで仮想世界に工事現場を再現し、工事手順の適切性を評価するシミュレーション環境が実現可能になる。本研究においては、工事機械を仮想空間上に再現することを中心に研究を実施した。具体的には工事用のクレーンによる工事手順の再現やバックホウを用いた掘削工事の仮想空間における再現手法に関する研究を実施した。

  • モーションキャプチャーによる建材の検査結果の3次元CADへの記録手法に関する研究

    2013年  

     概要を見る

    作業者の姿勢や移動をモーションキャプチャーにより3次元的に計測できるKinectセンサーを用いて、建築工事における作業者の姿勢と移動経路の記録と分析を行う研究を実施した。KinectはRGBによる動画と計測対象の3次元形状を示す点群データと作業者の作業姿勢を示す骨格情報を取得できる。Kinectセンサーによる計測では動画として撮影できる範囲においてしか計測を行えないが、本研究では点群データにより示す球ターゲットの位置を取得し、複数台のKinectセンサーにより取得した骨格情報を同一の座標系に統合する手法を考案した。また、複数台のKinectにより取得した作業者の移動経路や姿勢を記録した骨格情報には多くのノイズが含まれるため、ノイズを除去する手法を考案した。Kinectは、骨格情報として、頭や腰、膝、つま先、肩、肘、手先などの位置の3次元座標を最大で毎秒30回程度取得できる。複数個所から取得した骨格情報を同一の座標系に変換したのち、各骨格情報の計測時刻に基づいて骨格情報を並べなおす。続いて、各計測データには数cmの誤差を含むため、移動平均法により前0.5秒分と後0.5秒分の計測データを平均することで骨格情報の移動データを円滑化した上で、前後に取得した骨格情報の位置と大幅にずれているデータを除外し、ノイズの可能性の高い骨格情報を除去した。 作業者の骨格情報の円滑化を実施した後、作業者の移動と姿勢に基づく作業分析を行う。現場作業者の作業は、「取付」、「加工」、「運搬」、「計測(検査)」などに分類でき、建築工事における多くの作業はこれらの行為の繰り返しにより行われる。作業者の作業状態を骨格情報により認識するために、まずは移動速度により判断し、2次的な基準として作業者の位置に基づいて求めた。この手法を検査員にも適用し、作業員の位置と移動速度、姿勢により、検査を実施している状態か、移動中かを認識する手法について研究を実施した。

 

現在担当している科目

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担当経験のある科目(授業)

  • 設計製図Ⅲb

    早稲田大学  

  • 建築生産マネジメント特論

    早稲田大学  

  • 建築施工法1

    早稲田大学  

  • 建築工学実験D

    早稲田大学  

  • 建築生産マネジメント

    早稲田大学  

  • 建築生産システム演習

    早稲田大学  

  • 建築生産システム

    早稲田大学  

  • 建築情報処理1

    工学院大学  

  • 構法設計

    工学院大学  

  • 構法計画

    工学院大学  

  • 建築構法

    工学院大学  

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委員歴

  • 2020年04月
    -
    継続中

    日本建築学会  建築社会システム本委員会

  • 2017年12月
    -
    2019年11月

    日本建築学会  社会の信頼に応える建築の設計者・施工者の選定方式を検討するタスク・フォース

  • 2017年10月
    -
    2018年03月

    建築設備技術者協会  建築設備運用の最適化に向けた建築設備技術者の新たな業務展開に関する調査委員会

  • 2017年10月
    -
     

    建築コスト管理システム研究所  建築コスト管理研究会

  • 2017年04月
    -
     

    日本建築学会  グローバル人材育成委員会

  • 2016年07月
    -
     

    日本建築学会関東支部  建築生産専門研究委員会

  • 2016年04月
    -
     

    日本建築学会  施工BIM小委員会

  • 2015年04月
    -
    2016年03月

    日本建築学会  建築生産BIM小委員会

  • 2015年04月
    -
     

    日本建築学会  各部構法小委員会

  • 2015年04月
    -
     

    日本建築学会  コストマネジメント小委員会

▼全件表示