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研究生： 蕭維承
Hsiao, David W.
論文名稱： 以代理人為核心之工程資產管理維修鏈整合研究
A Study of Agent-based Maintenance Chain Integration for Engineering Asset Management
指導教授： 張瑞芬
Chang, Amy J. Trappey
馬林
Ma, Lin
口試委員:
學位類別： 博士
Doctor
系所名稱： 工學院 - 工業工程與工程管理學系
Department of Industrial Engineering and Engineering Management
論文出版年： 2008
畢業學年度： 97
語文別： 英文
論文頁數： 106
中文關鍵詞： 工程資產管理 、維修鏈整合 、統一建模語言 、多代理人系統 、斐氏圖
外文關鍵詞： Engineering Asset Management, Maintenance Chain Integration, Unified Modeling Language, Multi-Agent System, Petri-Net
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    • 工程資產所包含之流程與功能具備有分散環境且協同作業之特性，然目前之工程資產管理仍高度仰賴自我維護之經驗法則以及週期性維修保養，此等維修保養模式無法避免突發事件之發生，進而造成人員之傷害以及機台效能之損失。再者，為提高顧客於維修服務上之滿意度，維修之效率以及專業諮詢之重要性亦日益增高。為了提高整體維修鏈之效率，本研究擬導入服務中心進行維修鏈之整合。於新的整合維修鏈中，服務中心擁有專業工程資產症狀診斷與生命週期預測能力，因此可提供具高度參考價值之維修決策依據。藉此專業能力，進行維修需求以及維修提供之整合。並藉由整體產業鏈之合作，預先探討與預測總體維修相關備件需求，藉由彼此之存貨互調，協助整體維修鏈以較低之庫存量達到高度之服務水準。於研究步驟上，本研究將藉由斐氏圖 (Petri-net) 之運用協助分析瓶頸作業，以及效率面較低之構面，並針對此等作業以及構面，進行分析，作為後續新商業模式之改善重點。此外，統一建模語言 (Unified Modeling Language, UML) 搭配斐氏圖運用於 Prometheus 代理人設計流程，將更可視覺化以及合理化代理人系統之設計。最後進行代理人系統之分析設計與實做，並進行前後模式之比較。
    本研究之價值在於提出工程資產整合維修鏈模式，並導入代理人技術使整合模式可以順暢運行。此外，於代理人系統分析設計步驟上，結合 Prometheus 設計流程方法論，搭配圖形化分析工具斐氏圖，以及統一建模語言進行系統之設計，將可有效溝通與串接管理部門與工程部門之間對於多代理人系統之設計構想。

    Engineering asset management (EAM) process is a broad discipline and the EAM functions and processes are characterized by its distributed nature. However, engineering asset nowadays mostly relies on self-maintained experiential rule-bases and periodic maintenance, which is lacking a collaborative engineering approach. To enrich the maintenance efficiency and customer relationship, this research proposes collaborative environment integrated by service center with good diagnosis and prognosis expertise. The collaborative maintenance chain jointly combines asset operation sites (i.e., maintenance demanders), service center (i.e., maintenance coordinator), system provider, first tier collaborators (i.e., maintenance providers), and maintenance part suppliers. Meanwhile, to realize the automation of communication and negotiation among organizations, multi-agent system (MAS) technique is applied. With agent-based collaborative environment, the entire service level of engineering asset maintenance chain is increased. Moreover, during the MAS design processes, this research combines Prometheus MAS modeling methodology with Petri-net modeling methodology and unified modeling language (UML) to visualize and rationalize the design processes of MAS.
    The major contributions of this research contain developing a Petri-net enabled Prometheus multi-agent system (MAS) modeling methodology and construct an agent-based maintenance chain framework for integrated engineering asset management.

    中文摘要 I ABSTRACT II TABLE of CONTENTS III LIST of FIGURES VI LIST of TABLES X 1. INTRODUCTION 1 1.1. Research Motivation 1 1.2. Research Objectives and Research Scope 2 1.2.1. Research objectives 2 1.2.2. Research scope 3 1.3. Phrase Definitions and Assumptions 4 1.4. Case Description 5 1.4.1. As-is practice 5 1.4.2. To-be practice 6 1.5. Thesis Organization 7 2. LITERATURE REVIEW 8 2.1. Engineering Asset Management 8 2.2. Multi-Agent System (MAS) 10 2.2.1. Agent definition and characteristics 11 2.2.2. Agent communication language 12 2.2.3. Agent-based engineering asset management 16 2.3. Multi-Agent System Modeling Methodology 20 2.3.1. Gaia methodology 21 2.3.2. ROADMAP methodology 24 2.3.3. Tropos methodology 25 2.3.4. MaSE methodology 27 2.3.5. PASSI methodology 29 2.3.6. Prometheus methodology 31 2.3.7. Summary of the MAS modeling methodology 33 3. SYSTEM METHODOLOGY 35 3.1. Process Modeling and Analysis 35 3.1.1. Petri-net 35 3.1.2. Petri-net models of current maintenance chain 36 3.1.3. Analysis of current maintenance chain 38 3.2. Information System Modeling Using UML 40 3.3. Agent System Modeling Methodology 41 3.3.1. Requirement analysis 42 3.3.2. Architectural design 44 3.3.3. Detailed design 46 3.4. Modeling Methodology Comparison 48 4. SYSTEM ANALYSIS AND DESIGN 50 4.1. Requirement Analysis 51 4.2. Architectural Design 52 4.2.1. Agent identification 52 4.2.2. Agent relationship 55 4.2.3. System architecture 61 4.3. Detailed Design 62 4.3.1. Agent overview 62 4.3.2. Conversation design 63 4.3.3. Ontology and data schema 74 5. SYSTEM IMPLEMENTATION AND EVALUATION 76 5.1. Case Description 76 5.2. System Implementation 79 5.3. Evaluations and Comparisons 89 5.3.1. Simulation procedures 90 5.3.2. As-is practice simulation modeling 92 5.3.3. To-be practice simulation modeling 95 5.3.4. Evaluation results and analysis 97 6. CONCLUSIONS AND CONTRIBUTIONS 99 REFERENCES 101

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