規則式專家系統求解多廠區半導體工業生產計劃問題

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：29

、訪客IP：52.15.163.239

姓名

何宗穎(Tsung-Ying Ho) 查詢紙本館藏

畢業系所

企業管理學系

論文名稱

規則式專家系統求解多廠區半導體工業生產計劃問題

相關論文

★ 企業流程為核心的食品產業運籌體系規劃:低溫物流部份	★ 以企業流程方法規劃整體飛航後勤維修體系之研究
★ 成衣產業導入ERP運籌管理方案之個案研究	★ 光電產業試產基地之生產最佳化模式：以光投影機為例
★ TFT LCD產業獲利因素之探討	★ 科技事業進行合併/讓售之決策過程與成效之個案探討
★ 企業治理、風險及遵循解決方案導入之個案研究-以職責分離資訊系統為例	★ 品質機能展開與多準則決策於設備開發應用
★ ERP導入品質因素對IFRS轉換專案之影響	★ ERP投資金額對服務品質及導入後IT治理目標之分析
★ ERP 導入問題對專案的影響	★ IFRS轉換對員工退休金計畫影響
★ IFRS轉換問題對IFRS效益的影響	★ 電子產業新產品開發參考模式之發展
★ 應用資料科學方法提昇國防裝備可靠度之研究－以防空系統為例	★ 企業資訊方案行銷歷程之探討-以MES為例

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 ( 永不開放)

摘要(中)

半導體製造是為高度資本與知識密集之產業，而半導體最終產品之生命週期大幅縮短，廠商無不希望保持產能利用率同時維持既定的生產週期，如期交貨以滿足市場瞬息萬變之需求。企業資源規劃系統 (Enterprise resource planning system) 應用在半導體工業來整合協調各個部門的資訊外，基於ERP系統之限制，我們更需要一個決策模型，來協助管理者達成生產與銷售協同之目標，以提昇顧客滿意度以及獲利。現有之規劃系統僅考量了原物料需求滿足生產所需之情況，並未考量到生產產能限制、多個廠區、工作中心之指派問題，也無法進行生產規劃模擬，或者考量其他生產限制進行規劃調整，因此相關的調整生產規劃之邏輯仍需要一套模型或者系統。學者提出先進規劃系統 (Advanced planning system) 之概念，將可針對生產規劃問題之結構模組化，並可以套用相對應的資訊軟體，與ERP系統的資訊整合來解決上述之問題。

本研究提出了一套以APS為架構之生產規劃模型，考量半導體製造前、後製程產能限制、生產產能、良率、生產週期時間、交期限制來解決上述的問題。在管理者進行總體規劃時，能夠納入考量整個供應鏈之能力，以維持較低之庫存，降低公司資金積壓造成之營運風險。本研究採用數值驗證，驗證模型與規則式專家系統演算法之可行性，並與最佳化軟體Lingo之規劃結果進行比較，證實本研究提出之模型與解法能夠維持較低之庫存，具有一定的求解品質。本研究最後針對模型與解法考量不周之處進行說明，期待能使未來之研究更臻完善，使半導體產業之管理者能夠提升管理績效。

關鍵字 : 生產計劃、產銷協同、供應鏈管理。

摘要(英)

Semiconductor manufacture is an industry consisting of high capital and knowledge. Maintaining high utilization rate is persuaded by companies. Meanwhile, companies are eager to meet due date constraint. Enterprise resource planning (ERP) system is utilized in the semiconductor manufacture industry to integrate information. Owing to the system limitation, decision models are needed to achieve the balance of sales and operation. However, the existed ERP system has encountered certain drawbacks. We divided the problems into two parts. First, the system ignored not only the production limitation but multi plants、multi work center dispatch problem and so on. Second, it could neither stimulate the production plan nor adjust it. Stadtler (2005) stated the concept of advanced planning system (APS) had exhibited an architecture based on the principles of hierarchical planning. The main focus is on supporting the material flow amidst a supply chain and is related to business functions: procurement, production, transport and distribution as well as sales.

This research provides a production planning model which integrates front-end and back-end production plan based on the capacity. The whole capacity of supply chain can be considered by managers when making aggregate level planning. Moreover, companies can maintain lower inventory level, and also avoid the operation risk of backlog holding cost. Besides, this research offers numerical experiment to verify the model and Rule-based expert algorithm. We compare the result that we got from algorithm and the one out of optimization software Lingo. At last, we found out that two methods have their advantages respectively. Using the optimization software can reach the lower inventory level, whilst our algorithm is able to gain feasible solution. In the end of the research, we illustrate the points which we did not take into consideration. Nevertheless, in future researches, thinking over and solving all the problems to make the model and algorithm more practical are necessary jobs to do.

Key words : Production planning, Sales and operation planning, Supply chain management.

關鍵字(中)

★ 生產計劃
★ 產銷協同
★ 供應鏈管理

關鍵字(英)

★ Production planning
★ Sales and operation planning
★ Supply chain management

論文目次

摘要i

ABSTRACTii

誌謝iii

目錄iv

圖目錄vi

表目錄vii

第一章緒論1
1.1 研究動機與目的1
1.2 研究方法與步驟2

第二章半導體工業簡介與問題分析3
2.1半導體工業供應鏈3
2.2半導體工業供應鏈整合與協調5
2.3半導體工業製造流程8
2.4半導體工業問題分析10
2.5半導體工業生產與銷售協同14

第三章模型建立21
3.1 架構21
3.2 發展23
3.3 模型24
3.3.1 前製程模型26
3.3.2 後製程模型29
3.4 解法32
3.4.1 規則式專家系統36
3.4.2 解法步驟40
3.4.3 情境因子與規則建立43
3.4.4 調整解法47

第四章數值驗證53
4.1 資料輸入53
4.2 數值驗證58
4.3 交叉比較69

第五章結論與建議75
5.1 結論75
5.2 研究限制76
5.3 未來研究方向76

參考文獻77

參考文獻

1.Bang, J. Y. and Kim, Y. D., “Hierarchical production planning for semiconductor wafer fabrication based on linear programming and discrete-event simulation”, IEEE Transactions on Automation Science and Engineering, Vol. 7 (2), pp. 326-336, 2010.

2.Beamon, B. M., “Supply chain design analysis: Models and methods”, International Journal of Production Economics, Vol. 55 (3), pp. 281-294, 1988.

3.Bhatnagar, R., Chandra, P. and Goyal, S. K., “Models for multi-plant coordination”, European Journal of Operational Research, Vol. 67 (2), pp. 141-160, 1993.

4.Chiang, D., Guo, R. S., Chen, A., Cheng, M. T. and Chen, C. B., “Optimal supply chain configurations in semiconductor manufacturing”, International Journal of Production Research, Vol. 45 (3), pp. 631-651, 2007.

5.DiazMadronero, M., Mula, J. and Peidro, D., “A review of discrete-time optimization models for tactical production planning”, International Journal of Production Research, Vol. 52 (17), pp. 5171-5205, 2014.

6.Gupta, A., Maranas, C. D. and McDonald, C. M., “Mid-term supply chain planning under demand uncertainty: Customer demand satisfaction and inventory management”, Computers and Chemical Engineering, Vol. 24 (12), pp. 2613-2621, 2000.

7.Gupta, A. and Maranas, C. D., “Managing demand uncertainty in supply chain planning”, Computers and Chemical Engineering, Vol. 27 (3), pp. 1219-1227, 2003.

8.Gupta, J. N. D., Ruiz, R., Fowler, J. W. and Mason, S. J., “Operational planning and control of semiconductor wafer production”, Production Planning and Control, Vol. 17 (7), pp. 639-647, 2006.

9.Horiguchi, K., Raghavan, N., Uzsoy, R. and Venkateswaran, S., “Finite-capacity production planning algorithms for a semiconductor wafer fabrication facility”, International Journal of Production Research, Vol. 39 (5), pp. 825–842, 2001.

10.Kang, H. Y., “A multi-criteria decision-making approach for capacity allocation problem in semiconductor fabrication”, International Journal of Production Research, Vol. 49 (19), pp. 5893-5916, 2011.

11.Kantardzic, M., “Data mining: Concepts, models, methods, and algorithms”, 2nd edition, Wiley, New Jersey, 2011.

12.Kazemi-Zanjani, M., Nourelfath, M. and Ait-Kadi, D., “A multi-stage stochastic programming approach for production planning with uncertainty in the quality of raw materials and demand”, International Journal of Production Research, Vol. 48 (22), pp. 4701-4723, 2010.

13.Kishimoto, M., Ozawa, K., Watanabe, K. and Martin, D., “Optimized operations by extended X-Factor theory including unit hours concept”, IEEE Transactions on Semiconductor Manufacturing, Vol. 14 (3), pp. 187-195, 2001.

14.Kusiak, A., “Intelligent manufacturing systems ”, 1st edition, Prentice Hall, New Jersey, 1990.

15.Lee, Y. H., Jeong, C. S. and Moon, C., “Advanced planning and scheduling with outsourcing in manufacturing supply chain”, Computers and Industrial Engineering, Vol. 43 (1), pp. 351-374, 2002.

16.Lowe, J. J. and Mason, S. J., “Integrated semiconductor supply chain production planning”, IEEE Transactions on Semiconductor Manufacturing, Vol. 29 (2), pp. 116-126, 2016.

17.Luger, G. F. and Stubblefield, W. A., “Artificial intelligence : Structures and strategies for complex problem solving ”, 3rd edition, Addison Wesley Longman, Boston, 1998.

18.Mallik, S. and Harker, P.T., “Coordinating supply chains with competition : Capacity allocation in semiconductor manufacturing”, European Journal of Operational Research, 159 (2), Vol. pp. 330-347, 2004.

19.Nagendra, P. B. and Das, S. K., “Finite capacity scheduling method for MRP with lot size restrictions”, International Journal of Production Research, Vol. 39 (8), pp. 1603-1623, 2001.

20.Nassimbeni, G., “ International sourcing: Empirical evidence from a sample of Italian firms”, International Journal of Production Economics, Vol. 103 (2), pp. 694-706, 2006.

21.Pontrandolfo, P. and Okogbaa, O. G., “Global manufacturing : A review and a framework for planning in a global corporation”, International Journal of Production Research, Vol. 37 (1), pp. 1-19, 1999.

22.Rastogi, A. P., Fowler, J. W., Matthew Carlyle, W., Araz, O. M., Maltz, A. and Buke, B., “Supply network capacity planning for semiconductor manufacturing with uncertain demand and correlation in demand considerations”, International Journal of Production Economics, Vol. 134 (2), pp. 322-332, 2011.

23.Shapiro, J. F., “Modeling the supply chain”, 2nd edition, South-Western Educational Publishing, Kentucky, 2006.

24.Shi, J., Zhang, G. and Sha, J., “Optimal production planning for a multi-product closed loop system with uncertain demand and return”, Computers and Operations Research, Vol. 38 (3), pp. 641-650, 2011.

25.Simatupang, T.M. and Sridharan, R., “The collaborative supply chain”, The International Journal Logistics Management, Vol. 13 (1), pp. 15-29, 2011.

26.Simchi-Levi, D., Kaminsky, P. and Simchi-Levi, E., “Designing and managing the supply chain: Concepts, strategies and case studies ”, 2nd edition, McGraw-Hill, New York, 2003.

27.Stadtler, H., “Supply chain management and advanced planning-basics, overview and challenges”, European Journal of Operational Research, Vol. 163 (3), pp. 575-588, 2005.

28.Stadtler, H., Kilger, C. and Meyr, H., “Supply chain management and advanced planning : Concepts, models, software, and case studies”, 5th edition, Springer, Berlin, 2015.

29.Stray, J., Fowler, J. W., Carlyle, W. M. and Rastogi, A. P., “Enterprise-wide semiconductor manufacturing resource planning”, IEEE Transactions on Semiconductor Manufacturing, Vol. 19 (2), pp. 259-268, 2006.

30.Uzsoy, R., Lee, C. Y. and Martin-Vega, L.A., “A review of production planning and scheduling models in the semiconductor industry, Part II: Shop flow control”, IIE Transactions, Vol.26 (5), pp. 44-55, 1994.

31.Xiao, H., “Introduction to semiconductor manufacturing technology”, 2nd edition, Prentice Hall, New Jersey, 2000.

32.Zhang, G., Shang, J. and Li, W., “Collaborative production planning of supply chain under price and demand uncertainty”, European Journal of Operational Research, Vol. 215(3), pp. 590-603, 2011.

指導教授

呂俊德(Jun-Der Leu)

審核日期

2017-1-11

推文