氏名　MUHAMAD ARIFPIN BIN MANSOR
学位の種類　博士（工学）
学位記番号　博甲第568号
学位授与の日付　平成22年12月31日
学位論文題目　Development of Performance Measurement Methods for Production Maintenance Activities in Manufacturing Systems　（製造システムにおける生産保全活動のパフォーマンス測定法の開発）
論文審査委員
　主査　教授　大里　有生
　副査　教授　淺井　達雄
　副査　教授　山田　耕一
　副査　准教授　五島　洋行
　副査　准教授　志田　敬介

• 論文目次
• 論文要旨
• 論文審査の結果の要旨

［平成22（2010）年度博士論文題名一覧］ ［博士論文題名一覧］に戻る．

Contents　Page
Abstract　p.i
Contents　p.v
List of Figures　p.ix
List of Tables　p.x
Acronyms　p.xii

Chapter 1.　Introduction
　1.1　Introduction to the Reseach　p.1
　1.2　Problems Statements　p.4
　1.2.1　Problem 1 - Data management
　1.2.2　Problem 2 - Measurement the performance of production maintenance activities by consideration all inputs and outputs
　1.2.3　Problem 3 - Collaboration measurement between the elements that are working toegther
　1.3　Aim and objectives　p.6
　1.4　Research approach　p.7
　1.5　Scope of the dissertation　p.10
　1.6　Thesis overview　p.11
Chapter 2.　Literature Review
　2.1　Performance Measurement　p.12
　2.1.1　Performance Measurement Tools
　2.1.2　Performance Measurement in Maintenance
　2.2　Knowledge Measurement　p.21
　2.2.1　Example of Knowledge Management
　2.3　Types of Maintenance　p.23
　2.4　Total Productive Maintenance　p.25
　2.4.1　Compact Total Productive Maintenance
　2.5　Overall Equipment Effectiveness （OEE）　p.32
　2.6　Conclusion　p.34
Chapter 3.　Data Management for Maintenance Activities
　3.1　Introduction　p.35
　3.2　Determining Input and Output for Maintenance Activities　p.36
　3.3　Framework of Dimensional Model Design for Maintenance's Data Marts　p.40
　3.4　Knowledge Measurement in Maintenance　p.43
　3.5　Discussions and Conclusion　p.45
Chapter 4.　Performance Measurement of Maintenance
　4.1　Introduction　p.47
　4.2　DEA Model for Maintenance Performance Measurement　p.48
　4.2.1　Simple model for maintenance
　4.3　Maintenance Performance of Malaysia's Automotive Sector: A Case Study　p.54
　4.4　Discussions and Conclusion　p.64
Chapter 5.　Collaboration Measurement in Maintenance
　5.1　Introduction　p.65
　5.2　Measurement of Coalition of OEE Using Shapley Value　p.66
　5.2.1　An Illustrative Example
　5.2.2　A Case Study
　5.3　The Concept of Moving Coalition Analysis and Its Transpose　p.74
　5.3.1　Moving Coalition Analysis
　5.3.2　Transpose Moving Coalition Analysis
　5.4　Collaboration Measurement in OEE Using MCA and T-MC: A Case Study　p.84
　5.4.1　A Case Study for MCA
　5.4.2　A Case Study for T-MCA
　5.5　Discussions and Conclusion　p.91
Chapter 6.　Concluding Remarks and Future Research
　6.1　Concluding Remarks　p.94
　6.2　Originalities of Dissertation　p.95
　6.3　Limitation of the Proposed Method　p.96
　6.4　Future Research　p.97
List of Authur's Publications　p.99
References　p.101
Appendix 1　Major Input for Maintenance　p.111
Appendix 2　Major Output for Maintenance　p.112
Appendix 3　Attributes for Each Table in Maintenance Data Mart　p.114
Appendix 4　DEA CCR Model　p.118
Appendix 5　DEA Window Analysis　p.123

　With each passing year, the importance of maintenance continues to grow. This is due to rapid advancements in technology and customer demands. The trend toward automation has forced managers to pay more attention to maintenance. However, the general attitude toward maintenance is, “It costs what it costs.” Equipment has typically been fixed when it broke down without considering costs, time consumed, or other elements in the repair process. This, however, detracts from the efficiency and effectiveness of an organization. Thus, the proper management of maintenance system plays an important role in an organization`s success an survivability.

　A scientific approach is necessary to make maintenance activities more efficient and cost-effective. Simultaneously, it is necessary to monitor the efficiency of the activities regularly because previously performed maintenance activities are influential in the current circumstance as well as in following periods. For example, in production maintenance, poor past maintenance activities will cause frequent failures in the future.

　The aim of this study is to propose a measurement method that can measure equipment performance in aggregate. This includes the efficiency of resource used in maintenance activities against its outcomes and the collaboration between several factors in achieving the outcomes. Overall Equipment Effectiveness （OEE） is an index often used in maintenance management to indicate how effective a machine runs. However, OEE lacks some important points. It does not consider input information and only certain output information is considered in calculating the OEE. Thus, we propose a general model of Data Envelopment Analysis （DEA） that can take into account all considerable inputs and outputs, and thus addresses deficiencies in current measurement method. This also results in improved comprehensive results to benchmark maintenance activities.

　The model suggested that the appropriate inputs （causes） are man, machine, money, training, and time, or “3M2T” and the outputs （effects） are production, quality, cost, delivery, safety, morale, and time, or “PQCDSMT”. Man, machine and money are typical inputs for production system.
Training is an important activity in developing knowledge for employees and time plays a role in minimizing the inputs. Meanwhile, “PQCDSM” is the common measurement index for Total Productive Maintenance （TPM）. TPM is a typical Japanese production method that is directly involved with maintenance management and has a strong direct and indirect relationship with manufacturing performance.

　We also develop a new method to evaluate the collaboration among the elements that are working together and that have their own contribution to achieve a common goal. Moving Coalition Analysis （MCA） is a method to measure performance trends of a coalition over time. It uses the Shapley value to calculate the marginal contribution of each period in a sub-coalition formed by several periods or players. A coalition is divided into several sub-coalitions there each sub-coalition should consist of three or more players. A sub-coalition drops one of its members and picks up a new member to form the next sub-coalition and move horizontally where the X-axis is the player and the Y-axis is the contributor. For Transpose moving Coalition Analysis （T-MCA）, we transpose the position of the player and the contributor where players are located in the Y-axis and contributors in the X-axis. Then the sub-coalitions are created vertically.

　Without proper data, the efficiency and effectiveness of an entire organization cannot be easily assessed and it would take a certain period to manage and identify the necessary data if the data were not managed well. Therefore, data management can also speed up the processes for measuring the efficiency and effectiveness of an entire organization. A data mart design for maintenance activities was proposed for this purpose.

　The dimensions tables and facts tables of this data mart were developed based on the key performance indicators for an organization as identified by the study to 44 companies and divisions that applied TPM in Japan, literature study from books and journals, and site visits to several automotive related factories in Malaysia.

　Hence, this study provides a new measurement method to measure the performance of maintenance activities and the guidelines to manage the data that related to maintenance. This information is helpful in making effective managerial decisions, especially when involving the input and output.

　本論文は、「Development of Performance measurement Methods for Production Maintenance Activities in Manufacturing Systems （製造システムにおける生産保全活動のパフォーマンス測定法の開発）」と題し、6章より構成されている。

　第1章「序論」では、本研究の背景と意義について述べ、製造システムにおける生産設備管理の適正化と生産効率の最大化を目的として、生産効率の向上をもたらす総合的生産保全活動のパフォーマンス（業務性能）を定量的に測定する方法や評価技術に関する課題を整理し、課題解決のための方法論を示し、本研究の目的と範囲を述べている。

　第2章「先行研究の概観」では、企業経営における業務のパフォーマンス測定（業務性能評価）に関する従来の方法を概観するとともに、生産効率を極限までたかめるための全社的設備管理における生産保全活動の効率化に関する従来の取り組みを紹介し、全社的生産保全活動の総合的評価法を開発する必要性について述べている。

　第3章「生産保全活動のためのデータ管理」では。生産保全活動のパフォーマンス（業務性能）を測定する上で必要とする生産保全データベースとそれに基づく生産保全知識管理システムを構築し、パフォーマンス測定の実現を可能にする生産保全データ管理システムを提案している。

　第4章「生産保全のパフォーマンス測定」では、製造システムにおける設備効率を評価する指標としてある既存の総合設備効率指標が生産保全活動を総合的に評価する指標として不十分であることに着目し、他入力・他出力間の総合効率を包絡分析法により評価するパフォーマンス測定法を新たに開発し、実際の企業における実データを用いてその妥当性を検証している。

　第5章「生産保全における連携活動の性能測定」では、生産保全に関わる事業体・組織内の各部署間の連携活動及び生産保全活動の時系列変化における各機関・時刻間の連携性並びに生産保全への各部署の貢献度評価を可能にする測定法を開発し、実際問題としての生産保全管理問題への適用においてその有効性を明らかにしている。

　第6章「結論」では、本論文の各章で得られた結論を概括的に述べるとともに、今後の課題と展望について述べている。

　以上のように、本論文の成果により、従来は計測困難であった総合的生産保全活動の業務性能測定法が確立され、生産効率の最大化を目指す生産設備の適正管理及び効率性向上に大きく貢献するものと考えられる。
よって、本論文は工学上及び工業上貢献するところが大きく、博士（工学）の学位論文として十分な価値を有するものと認める。