臺灣博碩士論文加值系統

多世代產能規劃中存在許多不確定因素，例如：產品售價、需求變化、產品生命週期等，皆影響到企業的營運及獲利，因此本研究將針對目前產能規劃所面臨的不確定因素加以探討，目的為決定各規劃時期之不同世代產能，以使得整體利潤最大化。本研究與過去文獻相異之處在於需求隨產業景氣而變動，並且同時考慮產出與價格不確定。
本研究考慮多世代產能可彈性相互支援之特性，在兩種不同生命週期產品之情況下，建構動態規劃模式，並以數值迭代法(Value Iteration Algorithm)進行模式求解，決定產能規劃期限內每一期之最佳購買策略，以達成最大化利潤之目標。本研究提供一改良之求解演算法大幅減少求解時間，同時探討策略轉移曲線之存在，此曲線將系統狀態分為三區域，每一區域均有對應之最佳策略，可清楚描述產能擴張決策。

Our research studies the multi-generation capacity planning problem. Multi-generation capacity planning has become an interesting research subject, because many uncertainty factors affect the accuracy of planning. These factors include price uncertainties, demand fluctuation and uncertain product life cycle. The objective of this research is find a multi-generation capacity portfolio in each time period that is robust to demand, price, product life cycle uncertainties.
This research models the multi-generation capacity planning problem as a Markov decision processes (MDP) problem. In this MDP model, we consider two generation of manufacturing technology. The new generation capacity serves as a flexible resource that can be used to downward fulfill the deficiency of old generation capacity. The MDP model is solved by value iteration algorithm, and the solution provides a robust capacity expansion strategy for both types of capacity. The objective of this MDP model is to maximize the expected profit under demand and price uncertainties. An efficient algorithm is also developed by action elimination techniques to reduce the computation complexity of the problem. We verify our results under different types of product life cycle setting.

目錄
目錄 i
圖目錄 iii
表目錄 v
第一章、研究背景 1
1.1研究動機 1
1.2研究目的與方法 3
1.3研究步驟 6
第二章、文獻回顧 8
2.1產業背景相關文獻 8
2.2產能投資考慮因素 10
2.2.1限制式的建立 10
2.2.2產能調整成本 11
2.2.3產能規劃目標、規劃時間、折扣因素、多決策者之討論 11
2.2.4前置時間 12
2.2.5產能衰退 12
2.2.6策略性之規劃及庫存問題 13
2.2.7需求不滿足及產能短缺 13
2.2.8不確定性及預測 14
2.3產能規劃相關文獻及理論回顧 15
2.3.1確定性模式 15
2.3.2隨機性模式 17
2.3.3 需求特性 27
2.3.4產出不確定因素 28
2.3.5彈性機台之特性 28
第三章、研究方法 31
3.1研究用語定義 31
3.2問題定義與假設 31
3.3問題模式之參數與變數 33
3.4問題架構與模式 36
3.5求解數學模式之演算法 41
第四章、實驗設計與分析 43
4.1執行數值驗證所需之資訊說明 43
4.1.1範例假設說明 43
4.1.2資訊系統介紹 45
4.2範例分析 47
4.2.1範例一、彈性機台特性比較 47
4.2.2範例二、改變各參數下之投資決策 49
4.2.3範例三、景氣確定下最佳投資組合 58
4.2.4範例四、不同產品生命週期下之投資組合 63
4.3最佳產能投資組合特性 66
第五章、結論與未來研究方向 70
5.1結論 70
5.2未來研究方向 71
參考文獻 72

參考文獻
1. 陳馨宇、陳永豐與周雍強，(2007)，「不確定需求與高產能成本之寡佔產業的產能策略賽局模式」，科技管理學刊，Vol. 12, No. 2, pp. 65-92.
2. Alp, S. and T. Tan, (2008), “Tactical capacity management under capacity flexibility”, IIE Transactions, Vol. 40, pp.221–237.
3. Barahona, F., S. Bermon, O. Gunluk and S. Hood, (2005), “Robust capacity planning in semiconductor manufacturing”, Naval Research Logistics, Vol.52, pp. 459–468.
4. Bassok, Y., R. Anupindi and R. Akella, (1999), “Single-Period Multiproduct Inventory Models with Substitution”, Operations Research, Vol. 47, No. 4. (Jul. - Aug.), pp. 632-642.
5. Bean, J. C., J. L. Higle and R. L. Smith., (1992), ”Capacity expansion under stochastic demands”, Operations Research, Vol. 40, pp. 210–216.
6. Bermon, S. and S. J. Hood, (1999), “Capacity optimization planning system (caps)”, Interfaces, Vol. 29, No. 5, pp. 31–51.
7. Bernstein, F. and G. A. DeCroix, (2002), “Decentralized pricing and capacity decisions in a multitier system with modular assembly”, Technical report, Fuqua, Duke University, NC.
8. Bish, E. K. and Q. Wang, (2004), “Optimal Investment Strategies for Flexible Resources, Considering Pricing and Correlated Demands”, Operations Research, Vol. 52, No. 6, November–December, pp. 954–964.
9. Bish, E. K. and R. Suwandechochai, (2005), “Impact of Demand Substitution/Complementarity and Price/Quantity Postponement on the Optimal Capacity of the Flexible Resource”, Proceedings of the 2005 MSOM Conference.
10. Boyaci, T. and O. Ozer, ”Information Acquisition for Capacity Planning via Pricing and Advance Selling: When to Stop and Act?”, Working paper.
11. Burnetas, A. and S. Gilbert, (2001), ”Future capacity procurements under unknown demand and increasing cost”, Management Science, Vol. 47, pp. 979–992.
12. Cachon G. P., (1999), “Managing Supply Chain Demand Variability with Scheduled Ordering Policies”, Management Science, Vol. 45, No. 6. Jun., pp. 843-856.
13. Cachon, G. P. and M. Lariviere, (2001), ”Contracting to assure supply: how to share demand forecasts in a supply chain”, Management Science, Vol. 47, No. 5, pp. 629-646.
14. Cakanyildirim, M. and R. O. Roundy, (2002), ”Optimal capacity expansion and contraction under demand uncertainty”, Technical report, University of Texas at Dallas, Dallas, TX.
15. Cakanyildirim, M. and R. O. Roundy, (2002), “Optimal Capacity Expansion Strategies under Demand Uncertainty “, Technical Report 1250 SORIE Cornell University 14853 NY.
16. Cantamessa, M. and C. Valentini, (2000), “Planning and managing manufacturing capacity when demand is subject to diffusion effects”, International Journal of Production Economics, Vol. 66, pp. 227-240.
17. Catay, B., S. S. Erenguc, and A. J. Vakharia, (2003), “Tool capacity planning in semiconductor manufacturing”, Computers and Operations Research, Vol. 30, No. 9, pp. 1349–1366.
18. Chand, S., T. McClurg and J. Ward, (2000), “A model for parallel machine replacement with capacity expansion”, European Journal of Operational Research, Vol. 121, pp. 519-531.
19. Chand, S., V. N. Hsu and S. Sethi., (2002), “Forecast, solution, and rolling horizons in Harvard operations management problems: A classified bibliography”, Manufacturing Service Operations Management, Vol. 4, No. 1, pp. 25–43.
20. Chen, F., (2000), ”Salesforce incentives, market information, and production inventory planning”, Working paper, Columbia Business School.
21. Chen, F., (2002), ”Information Sharing and Supply Chain Coordination”, Graduate School of Business Columbia University New York, NY 10027 January.
22. Chen, F. and J. S. Song, (2001), “Optimal policies for multi-echelon inventory problems with Markov-modulated demand”, Operations Research, Vol. 49, No. 2, pp. 226-234.
23. Christie, R. M. E. and S. D. Wu, (2002), “Semiconductor capacity planning: Stochastic modeling and computational studies”, IIE Transactions, Vol. 34, No. 2, pp. 131–144.
24. Chu, W., (1992), ”Demand signaling and screening in channels of distribution”, Marketing Science, Vol. 11, No. 4, pp. 327-347.
25. Dangl, T., (1999), “Investment and capacity choice under uncertain demand”, European Journal of Operational Research, Vol. 117, pp. 415–428.
26. Daniel, P. C., G. E. Feigin and D. D. Yao, (1996), ”A Queueing Network Model For Semiconductor Manufacturing”, IEEE Transactions on Semiconductor Manufacturing , Vol. 9, No. 3.
27. Desai, P. S. and K. Srinivasan, (1995), “Demand signaling under unobservable effort in franchising: Linear and nonlinear price contracts”, Management Science, Vol. 41, No. 10, pp. 1608-1623.
28. Duenyas, I., W. J. Hopp and Y. Bassok, (1997), “Production Quotas As Bounds on Interplant JIT Contracts”, Management Science, Vol. 43, No. 10, Oct., pp. 1372-1386.
29. Eberly, J. C. and J. A. Van Mieghem, (1997), ”Multi-factor dynamic investment under uncertainty”, Journal of Economic Theory, Vol. 75, No. 2, pp. 345–387.
30. ElMaraghy, H. A., (2006), “Flexible and reconfigurable manufacturing systems paradigms”, International Journal of Flexible Manufacturing Systems, Vol. 17, pp. 261–276.
31. Fine, C. H. and R. M. Freund, (1990), “Optimal investment in product flexible manufacturing capacity”, Management Science, Vol. 36, No. 4, pp. 449–466.
32. Ellram, L. and C. Billington, (2001), “Purchasing leverage considerations in the outsourcing decision”, European Journal of Purchasing & Supply Management, Vol. 7, pp. 15-27.
33. Emmerinl, R. H. M., E. T. Verhoef, P. Nijkamp and P. Rietveld, (1998), “Information Effects in Transport with Stochastic Capacity and Uncertainty Costs”, International Economic Review, Vol. 39, No. 1, Feb., pp. 89-110.
34. Gaucherand, F. E., S. Bhatnagar, M. C. Fu, Y. He and S. I. Marcus, (1999), ”A Markov Decision Process Model for Capacity Expansion and Allocation”, Proceedings of the 38’Conference on Decision & Control Phoenix, Arizona USA December.
35. Goyal, M. and S. Netessine, (2005), “Capacity Investment and the Interplay between Volume Flexibility and Product Flexibility”, The Wharton School University of Pennsylvania Philadelphia PA-19104.
36. Groote, X. de, (1994), “The Flexibility of Production Processes: A General Framework”, Management Science, Vol. 40, No. 7, Jul., pp. 933-945.
37. Gullu, R., E. Onol and N. Erkip, (1997), ”Analysis of a deterministic demand production/inventory system under nonstationary supply uncertainty”, IIE Transactions, Vol. 29, pp. 703-709.
38. Hood, S. J., S. Bermon and F. Barahona, (2003), “Capacity planning under demand uncertainty for semiconductor manufacturing”, IEEE Transactions on Semiconductor Manufacturing, Vol. 16, No. 2, pp. 273–280.
39. Hopp, W., P. Jones and J. Zydiak, (1993), ”A further note on parallel machine replacement“, Naval Research Logistics, Vol. 40, pp. 575-579.
40. Hopp, W. J., M. L. Spearman, S. Chayet, K. L. Donohue and E. S. Gel, (2002), “Using an optimized queueing network model to support wafer fab design”, IIE Transactions, Vol. 34, No. 2, pp. 119–130.
41. Hu, S. J., (2005), “Paradigms of manufacturing a panel discussion”, 3rd Conference on Reconfigurable Manufacturing, Ann Arbor, Michigan, USA.
42. Hu, X., I. Duenyas and R. Kapuscinski, (2004), “Advance Demand Information and Safety Capacity as a Hedge Against Demand and Capacity Uncertainty”, University of Michigan Business School May 8.
43. Huh, W. T. , R. O. Roundy and M. Cakanyildirim, (2006), “A General Strategic Capacity Planning Model under Demand Uncertainty”, Naval Research Logistics, Vol. 53, pp. 137–150.
44. Iwata, Y., K. Taji and H. Tamura, (2003), “Multi-objective capacity planning for semiconductor manufacturing”, Production Planning & Control, Vol. 14, No. 3, pp. 244–254.
45. Karabuk, S. and S. D. Wu, (2002), “Decentralizing semiconductor capacity planning via internal market coordination”, IIE Transactions, Vol. 34, pp. 743–759.
46. Kim, B., (2003), “Dynamic outsourcing to contract manufacturers with different capabilities of reducing the supply cost”, International Journal of Production Economics, Vol. 86, pp. 63–80.
47. Kleindorfer, P. R. and D. J. Wu, (2003), “Integrating long and short term contracting via business-to-business exchanges for capital-intensive industries”, Management Science, Vol. 49, No. 11, pp. 1597–1615.
48. Lee, H. L., (1996), “Input Control for Serial Production Lines Consisting of Processing and Assembly Operations with Random Yields”, Operations Research, Vol. 44, No. 3. (May - Jun.), pp. 464-468.
49. Li, H. and S. C. Graves, (2007), ”Pricing Decisions during Inter-generational Product Transition”, MIT.edu, working paper, October, 34.
50. Li, S., D. Tirupati, (1994), ”Dynamic capacity expansion problem with multiple products: Technology selection and timing of capacity additions”, Operations Research, Vol. 42, No. 5, pp. 958–976.
51. Luss, H., (1982), ”Operations research and capacity expansion problems: A survey”, Operations Research, Vol. 30, pp. 907–947.
52. Mallik, S. and P. T. Harker, (2004), “Coordinating supply chains with competition: Capacity allocation in semiconductor manufacturing”, European Journal of Operational Research, Vol. 159, pp. 330–347.
53. Maranas, C. D. and A. Gupta and C. M. McDonald, (2000), “Midterm Supply Chain Planning Under Demand Uncertainty: Customer Demand Satisfaction and Inventory Management”, Computers and Chemical Engineering, Vol. 24, pp. 2613–2621.
54. Marathe, R. R. and S. M. Ryan, (2006), “Capacity expansion under a service level constraint for uncertain demand with lead times”, Iowa State University, Ames, IA 50011.
55. McClurg, T. and S. Chand, (2002), “A Parallel Machine Replacement Model”, Naval Research Logistics, Vol. 49.
56. Meixell, M. J. and S. D. Wu, (2001), “Scenario Analysis of Demand in a Technology Market Using Leading Indicators”, IEEE Transactions on Semiconductor Manufacturing, Vol. 14, No. 1.
57. Mohebbi, E., F. Choobineha and A. Pattanayakb, (2007), “Capacity-driven vs. demand-driven material procurement Systems”, International Journal of Production Economics, Vol. 107, pp. 451–466.
58. Murto, P., E. Nasakkala and J. Keppo, (2004), “Timing of investments in oligopoly under uncertainty: A framework for numerical analysis”, European Journal of Operational Research, Vol. 157, No. 2, pp. 486–500.
59. Narongwanich, W., I. Duenyas and J. R. Birge, (2002), “Optimal portfolio of reconfigurable and dedicated capacity under uncertainty”, Technical report, University of Michigan, MI.
60. Netessine, S., G. Dobson and R. A. Shumsky, (2002), ”Flexible service capacity: Optimal investment and the impact of demand correlation”, Operations Research, Vol. 50, No. 2, pp. 375–388.
61. Netessine, S. and N. Rudi, (2003), ”Centralized and competitive inventory models with demand substitution”, Operations Research, Vol. 51, No. 2, pp. 329–335.
62. Paraskevopoulos, D., E. Karakitsos and B. Rustem, (1991), ”Robust capacity planning under uncertainty”, Management Science, Vol. 37, No. 7, pp. 787–800.
63. Pinder, J. P, (1995), ”An Approximation of a Markov Decision Process for Resource Planning”, The Journal of the Operational Research Society, Vol. 46, No. 7, pp. 819-830.
64. Rajagopalan, S., (1998), “Capacity Expansion and Equipment Replacement: A Unified Approach”, Operations Research, Vol. 46, No. 6, pp. 846-857.
65. Rajagopalan, S., (1992), ”Deterministic Capacity Expansion under Deterioration”, Management Science, Vol. 38, No. 4. , pp. 525-539.
66. Rajagopalan, S., M. R. Singh and T. E. Morton, (1998), “Capacity Expansion and Replacement in Growing Markets with Uncertain Technological Breakthroughs”, Management Science, Vol. 44, No. 1, pp. 12-30.
67. Rajagopalan, S. and J. M. Swaminathan, (2001), ”A coordinated production planning model with capacity expansion and inventory management”, Management Science, Vol. 47, No. 11, pp. 1562–1580.
68. Sethi, S. and F. Cheng, (1997), ”Optimality of (s,S) policies in inventory models with Markovian demand”, Operations Research, Vol. 45, pp. 931-939.
69. Song, J. S. and P. Zipkin, (1993), ”Inventory control in a fluctuating demand environment”, Operations Research, Vol. 41, pp. 351-370.
70. Swaminathan, J. M., (2000), “Tool capacity planning for semiconductor fabrication facilities under demand uncertainty”, European Journal of Operational Research, Vol. 120, No. 3, pp. 545–558.
71. .Tan, B. and S. B. Gershwing, (2004), “Production and Subcontracting Strategies for Manufacturers with Limited Capacity and Volatile Demand”, Annals of Operations Research, Vol. 125, pp. 205–232.
72. Tan, B., (2004), “Subcontractingwith availability guarantees: production control and capacity decisions”, IIE Transactions, Vol. 36, pp. 711–724.
73. Uribe, A. M., J. K. Cochran and D. L. Shunk, (2003), “Two-stage simulation optimization for agile manufacturing capacity Planning”, International Journal of Production Research, Vol. 41, No. 6, pp. 1181–1197.
74. Van Mieghem, J. A., (1998), ”Investment strategies for flexible resources”, Management Science, Vol. 44, No. 8, pp. 1071–1078.
75. Van Mieghem, J.A.,(2003),“Capacity management, investment, and hedging: Review and recent developments,” Manufacturing and Service Operations Management, Vol. 5, No. 4, pp. 269–302.
76. Wang, Y. and Y. Gerchak, (2000), “Input control in a batch production system with lead times, due dates and random yields”, European Journal of Operational Research, Vol. 126, pp. 371-385.
77. Wu, S. D., B. Aytac, R. T. Berger and C. A. Armbruster, (2006), “Managing Short Life-Cycle Technology Products for Agere Systems”, Interfaces, Vol. 36, No. 3, pp. 234–247.
78. Wu, S. D., M. Erkoc and S. Karabuk, (2005), “Managing Capacity in The High-Tech Industry: A Review of Literature”, The Engineering Economist, Vol. 50, pp. 125–158.
79. Yano, C. A. and H. L. Lee, (1995), “Lot Sizing with Random Yields: A Review”, Operations Research, Vol. 43, No. 2, pp. 311-334.
80. Zhang, F., R. Roundy, M. Cakanyildirim and W. T. Huh, (2004), “Optimal capacity expansion for multi-product, multi-machine manufacturing systems with stochastic demand”, IIE Transactions, Vol. 36, No. 1, pp. 23–37.