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研究生:曹偉杰
研究生(外文):Vijay Shekhar Jha
論文名稱:KnowledgemanagementcentricintelligentsystemwithmodifiedAPQP:AcasestudyforapotentialsolutionforthefuturechallengesofSemiconductorindustry
論文名稱(外文):Knowledge management centric intelligent system with modified APQP : A case study for a potential solution for the future challenges of Semiconductor industry
指導教授:王孔政王孔政引用關係
指導教授(外文):Wang Kung-Jeng
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:工業管理系
學門:商業及管理學門
學類:其他商業及管理學類
論文種類:學術論文
畢業學年度:96
語文別:英文
論文頁數:71
中文關鍵詞:知識管理品質管理半導體工業
外文關鍵詞:Knowledge ManagementAPQPAgentsSemiconductor manufacturing services Industry
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Future challenges posed to semiconductor manufacturing service companies’ demand for a system framework that uses organizational knowledge intelligently in the era of information and competitiveness. We propose a framework that integrates agent based knowledge management (KM) intelligence and advance product quality planning (APQP) features to develop a systematic framework that responds to such challenges efficiently. Agent based knowledge management system (ABKMS) with APQP concept works just fine for any semiconductor manufacturing services organization. A case study of such an organization reflects how ABKMS successfully leverages intelligent agents to seek significant inroads into process knowledge repository to recommend a solution for decision making while following customized APQP process in delivering semiconductor manufacturing services. This system has the characteristics as intelligent, flexible, simple, and automatic etc.
Future challenges posed to semiconductor manufacturing service companies’ demand for a system framework that uses organizational knowledge intelligently in the era of information and competitiveness. We propose a framework that integrates agent based knowledge management (KM) intelligence and advance product quality planning (APQP) features to develop a systematic framework that responds to such challenges efficiently. Agent based knowledge management system (ABKMS) with APQP concept works just fine for any semiconductor manufacturing services organization. A case study of such an organization reflects how ABKMS successfully leverages intelligent agents to seek significant inroads into process knowledge repository to recommend a solution for decision making while following customized APQP process in delivering semiconductor manufacturing services. This system has the characteristics as intelligent, flexible, simple, and automatic etc.
Table of Contents
CHAIRPERSON OF SUPERVISORY COMMITTEE 1
TABLE OF FIGURES & TABLES 6
CHAPTER 1. RESEARCH BACKGROUND 7
1.1 CHALLENGES FOR THE FUTURE OF SEMICONDUCTOR MANUFACTURING SERVICES COMPANY 10
CHAPTER 2. LITERATURE SURVEY 18
2.1 RESEARCH CHALLENGES FOR ABKMS 18
2.2 ENTERPRISE MODELING 21
2.3 CRITERIA FOR EVALUATING ENTERPRISE MODELS 29
2.4 COMPARISON OF MODELING APPROACHES 31
2.5 OBJECT-ORIENTED APPROACH 33
2.5.1 Unified Modeling Language (UML) 34
2.5.2 UML characteristics 34
2.5.3 Transfer a description into software implementation 37
2. 6 SUMMARY 37
CHAPTER 3. THE PROPOSED AGENT BASED KNOWLEDGE MANAGEMENT SYSTEMS (ABKMS) FRAMEWORK 39
3.1 THE CHARACTERISTICS OF COMPONENTS OF ABKMS 42
3.2 ADVANCE QUALITY PLANNING PROCESS- APQP 44
3.2.1. INTELLIGENT TECHNOLOGY QUALITY PLANNING (ITQP) 48
3.2.3. INTELLIGENT MATERIAL QUALITY PLANNING (IMQP) 51
3.2.4. INTELLIGENT VENDOR QUALITY PLANNING (IVQP) 55
3.2.5 INTELLIGENT EQUIPMENT/TOOLS QUALITY PLANNING (IETQP) 58
CHAPTER 4. ABKMS SYSTEM IMPLEMENTATION & ASSESSMENT 61
4.1 ABKMS IMPLEMENTATION 62
4.1.1 Existing Infrastructure and planning 62
4.1.2 Aligning KM and Business Strategy 64
4.1.3: Knowledge Management System Analysis, Design, and Development 65
4.2 SYSTEM REQUIREMENTS 67
4.3 IMPLEMENTATION OF APQP SYSTEM 70
4.3.1. APQP Development Planning Phase 70
4.3.2. APQP Prototype phase 70
4.3.3. Pilot Run 71
4.3.4. Quality run 71
4.4 MIDDLEWARE ARCHITECTURE OVERVIEW 72
4.4.1 Elasticity of architecture 75
4.5 CULTURAL ASSESSMENT AND KNOWLEDGE AUDITING 77
4.5.1 Incentives to Participate 77
4.5.2Eliminating Disincentives 77
4.5.3 Rewards and Compensation 77
4.6 METRICS FOR PERFORMANCE EVALUATION 77
4.7. ASSESSMENT OF SYSTEM 78
CHAPTER 5. CONCLUSION 82
REFERENCES 83
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