臺灣博碩士論文加值系統

80年代的初期 CMMS (Computerized Maintenance Management) 電腦化設備維修管理資料系統有詳述如何建置設備維修管理系統的方法，企業建置個別的維修管理系統。此後 SAP/CRM 以其完善的客戶管理，進一步整合物流及財務支援系統，逐漸成為主流維修管理系統。
資訊系統是企業流程管理 (Business Process Management)之骨幹，而流程建置是攸關系統成敗之關鍵。以半導體的主要設備供應商為例，大多廠商已採用SAP/CRM (customer relation module) 維修系統。設備商利用此系統來記錄相關的維修服務，連結 CRM有關的客戶、維修及物料主檔，記錄每一筆的工單耗費的資源如工時、物料及工作內容，作為後續的請款(Billing)作業的依據。在後端的資料分析，使用BI、HANA、Power BI，提供企業活動的效能分析如營收管理、成本管控及資源的分配效率、缺工缺料改善等等，進而作為決策管理中不可獲缺之工具。
本研究目的在探討根本原因分析法(Root Cause Analysis)及設備維修關鍵指標，建立 SAP/CRM的維修輔助系統，改善半導體供應商在採用 SAP/CRM 在 Knowledge capture 時所面臨之結構問題以及資訊收集的流程，將CRM 維修資料的有效再利用，減少重工、減少人力及物料的浪廢，進而運用PHM的觀念將有限資源作有效的分配，在未來的 AI 人工智慧運用於半導體設備維修建立基礎。

In decades, the SAP /CRM (Customer Relation Module) dominates the primary customer service systems. CRM connects the customer, service and material module data, collects all direct/indirect workforce and material usage. It's an excellent for the billing process. Furthermore, the post-data analysis as BI (Business Intelligence) or HANA provides a tremendous advantage in efficiency improve, resource and cost management for the decision making in the enterprise operation.
The process setup is the key success factor in the enterprise operation. In this paper, we will study how to utilize RCA (Root Cause Analysis) with CMMS and PHM concepts to build the AKCS Auxiliary Knowledge Capture System and coordinate with SAP/CRM System. Apply the ARIS (Architecture of Integrated Information System) build-in the process. The AKCS vs. SAP/CRM will also be practical work in Industrious 4.0 and Artificial Intelligence to the next generation

Table of content
摘要 i
Abstract ii
誌謝 iii
Table of content iv
List of figure vi
List of table viii
Chapter 1 Introduction 1
1-1 Research background and motivation 1
1-2 Research objective and methodology 3
1-3 Research range 6
1-4 Research framework and process 6
Chapter 2 Literature Review 8
2.1 CMMS (Computerized Maintenance Management) 8
2.2 Predictive maintenance 12
2.3 Multiple Decision Criteria Analysis in Maintenance Policy setup and IT Framework 18
2.3.1 AHP Analytic Hierarchy Process 19
2.3.2 MCDA analysis and IT framework support 24
Chapter 3 Methodology 27
3.1 Root Cause Analysis method 27
3.1.1 Cause-and-effect diagram (CED) 27
3.1.2 Interrelationship Diagram (ID) 29
3.1.3 Current Reality Tree (CRT) 30
3.2 Overall Equipment Effectiveness or Efficiency OEE 34
Chapter 4 Case study – AKCS Auxiliary Knowledge Capture system 39
4.1 SAP/CRM maintenance module in CRT model analysis 39
4.1.1 CRT analysis – Current Reality Tree 40
4.1.2 CRT analysis – CRT analysis – Solution 42
4.1.3 CRT analysis – future tree for knowledge capture 43
4.2 ACKS - Knowledge capture system 44
4.2.1 ACKS - Knowledge code methodology 45
4.2.2 ACKS – Action Plan 01-99 codes methodology 49
4.2.3 ACKS – RCA code methodology 52
4.3 Build AKCS Auxiliary knowledge capture system per ARIS 55
4.4 OEE improvement with AKCS 57
4.5 AKCS Data Analysis 58
Chapter 5 Conclusion and future research 60
Reference 62

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