簡易檢索 / 詳目顯示

研究生: 曾信達
Tseng, Hsin-Ta
論文名稱: TFT-LCD模組廠物料採購之二階隨機規劃
Two-stage Stochastic Programming Approach for Material Planning in TFT-LCD Module Site
指導教授: 林則孟
Lin, James T.
口試委員:
學位類別: 碩士
Master
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: 2010
畢業學年度: 98
語文別: 中文
論文頁數: 112
中文關鍵詞: TFT-LCD物料採購計劃替代物料A-BOM採購比例隨機規劃
相關次數: 點閱:4下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  •   本研究將探討產品具有A-BOM(Alternative Bill-of-Material)特性之TFT-LCD(thin film transistor liquid crystal display)模組廠之物料採購計劃。A-BOM代表產品可由不只一組BOM組成,而不同家供應商提供之物料可組成不同A-BOM;模組廠的顧客會指定由不同A-BOM組成的產品,模組廠再根據顧客指定A-BOM進行生產。考量現今產業需求具有不確定性的情形下,在規劃期間內,各產品於各期有不同的預測需求分配,過去研究僅以需求預測的期望值來做物料採購規劃,但在需求丕變的環境下,無法找到一個穩健(robust)的物料採購計劃,故本研究利用二階隨機規劃(two-stage stochastic programming)手法來考慮未來需求之不確定性,以期能找到各期之最佳物料採購組合,達到較穩健的物料採購結果。
      由於模組廠在收到顧客訂單之前必須先採購物料,待顧客給予訂單後,再將採購好的原物料分配給各顧客需求,故可將採購物料視為未來不確定性事件發生前必須做的第一階段決策,當真實需求發生後將購買好的物料進行第二階段的物料分配。模組廠採購物料的目標是以實際採購比例與預先決策好之理想採購比例差距最小化,本研究同時考慮需求不確定性,除了達到理想採購比例外,盡可能讓缺貨比例與庫存比例最小化。
      本研究將以一案例驗證二階隨機規劃模型得到之物料採購計劃,將比確定性物料採購計劃穩健,面對未來需求不確定性,二階隨機規劃在目標值與風險評估績效指標上有較優異的表現。除此之外,本研究最後將設計DE(differential evolution)啟發式演算法,提供產業在面臨大型問題(large scale)的狀況下,仍可使用本研究提出之二階隨機規劃,並將此結果提供現場物管人員,做為實際規劃的一個參考建議。


    摘要 I 謝誌 II 目錄 III 圖目錄 VI 表目錄 VIII 第一章 緒論 1 1.1 研究背景與動機 1 1.2 研究目的 3 1.3 研究範圍與限制 3 1.4 研究步驟與方法 4 第二章 TFT-LCD產業模組廠區特性與問題定義 6 2.1 TFT-LCD產業與製程概述 6 2.1.1 TFT-LCD生產製程簡介-陣列製程(Array Process) 8 2.1.2 TFT-LCD生產製程簡介-組立製程(Cell Process) 10 2.1.3 TFT-LCD生產製程簡介-模組製程(Module Process) 11 2.2 模組廠區生產特性與分析 11 2.2.1關鍵物料特性與描述 12 2.2.2 A-BOM(Alternative Bill-of-Material)特性與描述 18 2.2.3採購比例(purchase ratio)特性與描述 20 2.2.4 顧客喜好度(Customer Preference)特性與描述 23 2.2.5物料相容性特性與描述 24 2.3 模組(module)廠區現行物料採購計劃方式 25 2.3.1 現況描述 25 2.3.2 物料採購過程之缺失與改善 26 2.4 問題定義與假設 27 第三章 文獻回顧 30 3.1 可替代性物料相關文獻 30 3.2 物料採購計劃相關文獻 34 3.3 隨機規劃相關文獻 39 3.4 DE啟發式演算法相關文獻 42 第四章 二階隨機規劃模式建構與案例驗證 45 4.1 二階隨機規劃方法說明與意義 45 4.2 二階隨機規劃數學模式建構 46 4.2.1 參數符號定義 46 4.2.2 數學規劃模式說明 48 4.3 範例驗證 52 4.3.1 範例情境說明 53 4.3.2 範例結果 59 4.4 Monte Carlo simulation驗證 60 4.4.1 Monte Carlo simulation方法說明 61 4.4.2 第二階段之物料分配數學模型 62 4.4.3 績效指標 66 4.4.4 驗證結果與分析 68 4.4.5 需求變異大小對規劃結果之分析 72 第五章 大型問題與啟發式演算法設計 74 5.1 實際案例情境說明 74 5.1.1 實際情境參數 75 5.1.2 複雜度比較 80 5.2 DE啟發式演算法說明 82 5.2.1 Differential Evolution模式建構 83 5.2.2 Differential Evolution參數設定 88 5.3 DE求解實際案例結果分析 92 5.3.1 實際案例求解結果 92 5.3.2 演算法效率探討 95 5.3.3 驗證結果與分析 97 第六章 結論與建議 99 6.1 結論 99 6.2 建議 100 參考文獻 101 附錄一 確定型物料採購計劃數學模式(修改自Lin et al., 2009) 106 附錄二 蒙地卡羅抽樣情境 108 附錄三 蒙地卡羅模擬結果 109 附錄四 大型問題未來需求預測值 110 附錄五 大型問題蒙地卡羅抽樣情境 111 附錄六 大型問題蒙地卡羅模擬結果 112

    1. 王凱生,“訂單滿足流程與可允諾量分配模式”, 國立清華大學工業工程與工程管理學系,碩士論文,2007。
    2. 朱曉晴,“考慮需求不確定之隨機動態產能規劃-以TFT-LCD產業為例”,國立清華大學工業工程與工程管理學系,碩士論文,2009。
    3. 林則孟,「生產計畫與管理」,華泰文化,2006。
    4. 陳子立,“TFT-LCD生產鏈物料與產能規劃之研究”,國立清華大學工業工程與工程管理學系,博士論文,2009。
    5. 張益菁,“考量需求不確定之單階多廠產能規劃問題-以TFT-LCD產業為例”,國立清華大學工業工程與工程管理學系,碩士論文,2007。
    6. 溫伊婷,“拉式多階多廠之訂單滿足問題-以TFT-LCD產業為例”,國立清華大學工業工程與工程管理學系,碩士論文,2008。
    7. Balakrishnan, A. and Geunes, J., “Requirements Planning with Substitutions: Exploiting Bill-of-Materials Flexibility in Production Planning”, Manufacturing & Service Operations Management, Vol. 2, No. 2, pp. 166–185, 2000.
    8. Basnet, C. and Leung, J. M. Y., “Inventory lot-sizing with supplier selection”, Computers & Operations Research, 32, pp.1-14, 2005.
    9. Che, Z.H. and Wang, H.S., “Supplier selection and supply quantity allocation of common and non-common parts with multiple criteria under multiple products”, Computers & Industrial Engineering, 55, pp.110-133, 2008.
    10. Chen, Z. L., Li, S. and Tirupati, D., “A scenario-based stochastic programming approach for technology and capacity planning”, Computers & Operations Research, 29, pp.781-806, 2002.
    11. Dantzig, G. B., “Linear programming under uncertainty”, Management Science, 1, pp.197-206, 1955.
    12. Das, S., Abraham, a. and Konar, A., “Metaheuristic Clustering”, Springer-Verlag Berlin Heidelberg, 2009
    13. Demirtas, E.A. and Üstün, Ö., “An integrated multiobjective decision making process for supplier selection and order allocation”, The International Journal of Management Science, Omega 36 pp.76 – 90, 2008.
    14. Demirtas, E.A. and Üstün, Ö., “Analytic network process and multi-period goal programming integration in purchasing decisions”, Computers & Industrial Engineering, 56, pp.677–690, 2009.
    15. Dolgui, A. and Prodhon, C., “Supply planning under uncertainties in MRP environments: A state of the art”, Annual Reviews in Control, 31, pp.269-279, 2007.
    16. Fan, S. K. S., Yeh, K. C. and Chuang, Y. C., “Differential evolution with Dynamic penalty function for solving constrained continuous optimization problems”.
    17. Geunes, J., “Solving large-scale requirements planning problems with component substitution options”, Computers & Industrial Engineering, 44 pp.475-491, 2003.
    18. Ghodaypour, S.H. and O’Brien, C., “A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming”, International Journal of Production Economics, 56-57, pp.199-212, 1998.
    19. Ghodaypour, S.H. and O’Brien, C., “The total cost of logistics in supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraint”, International Journal of Production Economics, 73, pp.15-27, 2001.
    20. Gupta, A. and Maranas, C. D., “A Two-Stage Modeling and Solution Framework for Multisite Midterm Planning under Demand Uncertainty ”, Ind. Eng. Chem. Res., pp.3799-3813, 2000.
    21. Gupta, A. and Maranas, C. D., “Managing demand uncertainty in supply chain planning ”, Computers and Chemical Engineering, 27, 2003
    22. Heitsch, H. and Romisch, W., “Scenario Reduction Algorithms in Stochastic Programming”, Computational Optimization and Applications, 24, pp.187-206, 2003.
    23. Higle, J. L., “Stochastic Programming: Optimization When Uncertainty Matters”, Tutorials in Operations Research, 2005.
    24. Ho, W., Xu, X. and Dey, P. K., “Multi-criteria decision making approaches for supplier evaluation and selection: A literature review”, European Journal of Operational Research, 202, pp.16-24, 2010.
    25. Hung, Y. F. and Wang, Q.Z. “A new formulation technique for alternative material planning-An approach for semiconductor bin allocation planning”, Computers & Industrial Engineering, Volume 32, Issue 2, pp.281-297, 1997.
    26. Jadidi, O., Hong, T.S., Firouzi, F. and Yusuff, R. B. M., “A Special discount Strategy for Supplier Selection and Order Allocation”, IEEE, 2008.
    27. Lang, J. C. and Domschke, W., “Efficient reformulations for dynamic lot-sizing problems with product substitution”, Springer-Verlag, 2008.
    28. Leung, S. C. H., Wu, Y. and Lai, K. K., “Multi-site aggregate production planning with multiple objectives: a goal programming approach” , Production Planning and Control, Vol. 14, pp.425-436, 2003.
    29. Liao, T.W. and Daftardar, S., “Model based optimisation of friction stir welding processes”, Science and Technology of Welding & Joining, Volume 14, Number 5, pp. 426-435, 2009.
    30. Lin, J. T., Chen, T. L. and Lin, Y. T., “Critical material planning for TFT-LCD production industry”, International Journal of Production Economics, 122, pp.639-655, 2009.
    31. Lyon, P., Milne, R. J., Orzell, R. and Rice, R., “Matching Assets with Demand in Supply Chain Management at IBM Microelectronics”, Interfaces, 31, pp.108-124, 2001.
    32. Miller, A. C. and Rice, T. R., “Discrete Approximations of probability Distributions”, Management Science, Vol.29, no.3, pp.352-362, 1983.
    33. Mula, J., Poler, R., Garcia-Sabater, J. P. and Lario, F. C., “Models for production planning under uncertainty: A review”, International Journal of Production Economics, 103, pp.271-285, 2006.
    34. Ozgen, D., Onut, S., Gulsun, B. and Tuzkaya, U. R., “A two-phase possibilistic linear programming methodology for multi-objective supplier evaluation and order allocation problems”, Information Sciences, 178, pp.485-500, 2008.
    35. Sanayei, A., Mousavi, S. F., Abdi, M. R. and Mohaghar, A., “An integrated group decision-making process for supplier selection and order allocation using multi-attribute utility theory and linear programming”, Journal of The Franklin Institute, 345, pp.731-747, 2008.
    36. Sen, S. and Higle, J. L., “An Introductory Tutorial on Stochastic Linear Programming Models”, Interfaces, 29, 2, pp.33-61, 1999.
    37. Tam, M. C. Y. and Tummala V. M. R., “An application of the AHP in vendor selection of a telecommunications system”, The International Journal of Management Science, Omega 29 pp.171-182, 2001.
    38. Ting, S. C. and Cho, D. I., “An integrated approach for supplier selection and purchasing decisions”, Supply Chain Management: An International Journal, Vol. 13, No. 2, pp.116-127, 2008.
    39. Üstün, Ö. and Demirtas, E.A., “An integrated multi-objective decision-making process for multi-period lot-sizing with supplier selection”, The International Journal of Management Science, Omega 36 pp.509-521, 2008.
    40. Wei, C. C., Chien, C. F. and Wang, M. J., “An AHP-based approach to ERP system selection”, International Journal of Production Economics, 96, pp. 47-62, 2005.
    41. Wu, C. H., Lin, J. T. and Wu, H. H., “Robust production and transportation planning in thin film transistor-liquid crystal display (TFT-LCD) industry under demand and price uncertainties”, International Journal of Production Research, 1-24, 2009.
    42. Wu, J. Z. and Chien, C. F., “Modelling strategic semiconductor assembly outsourcing decisions based on empirical settings”, OR Spectrum, 30, pp.401-430, 2008.
    43. Yu, J. R. and Tsai, C. C., “A decision framework for supplier rating and purchase allocation: A case in the semiconductor industry”, Computers & Industrial Engineering, 55 pp.634-646, 2008.
    44. Zhang, G. and Ma, L., “Optimal acquisition policy with quantity discounts and uncertain demands”, International Journal of Production Research, Vol. 47, No. 9, pp.2409-2425, 2009.
    45. Display Search, http://www.displaysearch.com

    無法下載圖示 全文公開日期 本全文未授權公開 (校內網路)
    全文公開日期 本全文未授權公開 (校外網路)
    全文公開日期 本全文未授權公開 (國家圖書館:臺灣博碩士論文系統)
    QR CODE