系統識別號 U0026-2708202014273200
論文名稱(中文) 發展客戶為中心的主生產計劃以減少庫存
論文名稱(英文) A Customer-Focused Master Production Schedule to Reduce Inventory
校院名稱 成功大學
系所名稱(中) 工業與資訊管理學系
系所名稱(英) Department of Industrial and Information Management
學年度 108
學期 2
出版年 109
研究生(中文) 卡媞曼
研究生(英文) Atikah Karimah
學號 R36077014
學位類別 碩士
語文別 英文
論文頁數 91頁
口試委員 指導教授-呂執中
中文關鍵字 功能性紡織產業  以顧客為中心  主生產計劃  庫存 
英文關鍵字 technical textile industry  costumer-focus  master production schedule  inventory 
中文摘要 根據世界貿易組織(WTO)的報告,全球紡織業織整體生產額正從2000年的198(十億美元)增長到2017年的497(十億美元),這使得紡織業仍為有前途的市場。然而,經營紡織業也是一個挑戰,必須具有持續、靈活和快速反應客戶的創新能力。一般而言,訂單來自預測訂單或確認訂單。但是,即使最好的預測也可能會出錯,如果生產過多,則可能是庫存,但如果過低,則可能導致產品缺貨。此外,紡織業是一個競爭激烈的市場,一些主要品牌客戶可能會在沒有理由的情況下不履行其訂單並取消訂單,這會給供應商的庫存和生產計劃帶來麻煩,但是訂單可能太大而無法拒絕。鑑於這一難題,本研究提出了一個架構,該架構可根據客戶優先等級將主生產計劃與MTO生產策略整合,以減少庫存。架構中第一個模組是客戶排名模組(CRM),它將應用TOPSIS方法,第二個模組是訂單履行模組(OFM),它是本研究開發的演算法。架構建置後,使用Microsoft Visual Basic和Microsoft Excel來模擬這些模組,以確認其效益。
英文摘要 Based on the report of World Trade Organization (WTO), the gross value of the global textile industry was increasing from 198 (billion US$) in 2000 to 497 (billion US$) in 2017. Textile industry is still a quite promising market in the future. Nevertheless, the textile industry needs to be sustained, flexible, and quick response to customers. In general, orders come from the customer’s forecast or customer’s confirmed order. However, forecast is always incorrect. If it is too much, it can be inventory, but if it is not enough, it can leads to stock out. Moreover, the textile industry is very competitive and some major brand customers may not be committed to their orders and cancel their orders without reasons. This behavior could cause trouble in regarding inventory and production planning of the suppliers, yet the orders might be too big to refuse. In view of this dilemma, this work proposes a framework to integrate a master production schedule with MTO production strategy, based on customer priority, for possible inventory reduction. The first module is the Customer Ranking Module (CRM) which will use TOPSIS methodology and the second is the Order Fulfilment Module (OFM) which is a developed algorithm. This framework would be verified by using a simulation approach using Microsoft Visual Basic and Microsoft Excel.
This work would identify a case in functional textile industry to verify the effectiveness of the proposed framework. The customers are classified as the first priority, second priority customers, and the third priority. Various scenarios would be designed to evaluate the effectiveness of the proposed framework. Based on the numerical results of the case study, it is found out that the inventory reduction could range from 58% to 78%. The developed framework would be considered to be deployed to other companies for inventory reduction.
論文目次 Abstract in Chinese i
Abstract ii
Acknowledgements iii
Table of Contents ix
List of Tables xi
Table of Figures xii
1.1 Background and Motivations 1
1.2 Research Objectives 4
1.3 Research Scope 5
1.4 Research Process 5
2.1 Supply Chain Management (SCM) 8
2.1.1 Definition and Decision Phase in SCM 8
2.1.2 Customer Satisfaction 10 Customer Focus 10 Inventory 11
2.2 Master Production Scheduling (MPS) 12
2.2.1 Definition and Function 12
2.2.2 MPS Input and Output 13
2.2.3 The Importance of Master Production Integration 14
2.3 Textile Industry 15
2.3.1 Definition and Processes 15 Fiber Blend 17 Spinning 18 Weaving 19 Dyeing, Printing, and Finishing 20
2.3.2 Production Management System of Textile Industry 20
2.3.3 Challenges of Textile Industry 21
2.4 Simulation 23
2.4.1 Definition 23
2.4.2 Advantages and Disadvantages 24
2.4.3 Visual Basic with Application 25
3.1 Proposed Framework for the integrated Master Production Schedule 27
3.2 Proposed Algorithms 29
3.3.1 Customer Ranking Module (CRM) 31
3.3.2 Order Fulfilment Module (OFM) 34
3.3 Simulation 39
4.1 Case Company Background 40
4.2 Data Collection 44
4.2.1 Customer’s score for each criteria 44
4.2.2 Bill of Material 46
4.2.3 Demand Table 47
4.2.4 Processing time, waiting and transport time 49
4.2.5 Lead time 50
4.3 Customer Ranking 50
4.4 Scenarios 53
4.5 Results 54
4.4.1 Scenario 1 (First Come First Serve-FCFS) 54
4.4.2 Scenario 2 (75% Committed Customers – 25% Uncommitted Customers) 55
4.4.3 Scenario 2 (50% Committed Customers – 50% Uncommitted Customers) 56
4.4.4 Scenario 3 (25% Committed Customers – 75% Uncommitted Customers) 57
4.4.5 Results Summary and Statistical Analysis 58
4.6 Managerial Implication 60
5.1 Conclusions 62
5.2 Future Research Directions 64
Appendix A: VBA Excel Coding 70
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