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研究生： 阮鴻福
Hong-Phuc Nguyen
論文名稱： 在技術創新下的產能規劃與資源分配之研究
CAPACITY PLANNING AND RESOURCE ALLOCATION UNDER TECHNOLOGICAL INNOVATIONS
指導教授： 王孔政
Kung-Jeng Wang
口試委員: 曹譽鐘
Yu-Chung Tsao
孔光源
Ky Koung
學位類別： 碩士
Master
系所名稱： 管理學院 - 工業管理系
Department of Industrial Management
論文出版年： 2014
畢業學年度： 102
語文別： 中文
論文頁數： 51
中文關鍵詞： 產能規劃 、技術採用 、動態規劃
外文關鍵詞： Capacity planning, equipment replacement, technological change, dynamic programming
相關次數： 點閱：261  下載：3 
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  •  上一筆

    • 在高資本密集的高科技產業裡，技術投資與產能規劃的決策是非常重要的。在現今高競爭的市場裡，這些產業的決策者面臨許多不確定因素，影響著企業的長期獲利與市占率，例如技術的突破與不確定的需求。本研究的目的是協助決策者了解在技術不斷發展的環境中，(一)如何擬定技術投資的策略 (二)滿足客戶需求所需要的資源數量。本研究發展出一套最佳化模型，用以算出最佳利潤以及產能分配的規劃，包含特定技術被保留的最佳期數。另外，本研究也利用動態規劃決定最佳技術之採用，進一步發展出最佳生命週期的模型。實驗結果顯示，最佳解可在數分鐘內求得。

    Technology investment, capacity planning and resource allocation decisions are crucial and capital intensive in high-tech industries. In today’s competitive market, decision-makers in such industries are facing many uncertain factors such as technology breakthroughs and varied demands, which strongly affect the company’s profit and market share for a long run. The purpose of this study is to support the decision-makers to figure out solutions regarding (i) the technology investment policy and (ii) levels of resources required to satisfy customers’ demands along the planning periods under the technological development environment. In this study, an optimization model is developed to obtain the optimal profit and capacity and resources allocation plan associated with number of periods a given technology is kept. Then, an economic life model, represented as a stochastic dynamic programming mode, is adopted in order to determine the best technology adoption policy. Experiment results indicate that near optimal solution can be achieved. However, the computational load is sensitive with the increase of the problem size due to the increasing number of sub-problem.

    摘要 ii Abstract iii Table of contents iv List of figures v List of tables vi Chapter 1 Introduction 1 1.1 Research motivations 1 1.2 Research objectives 2 1.3 Research framework 2 1.4 Organization of dissertation 3 Chapter 2 Literature Review 4 2.1 Technology replacement approaches 4 2.2 Capacity planning and resource allocation 7 2.3 Benchmark solving methods 8 2.4 Summary 10 Chapter 3 Problem Formulation 11 3.1 Problem description 11 3.2 Stochastic dynamic programming model 12 3.3 Capacity planning and resource allocation 18 3.4 Solving procedure 22 3.5 Solution approach for the capacity planning and resource allocation problem 23 Chapter 4 Numerical Example 27 4.1 Solving a specific case 27 4.2 Sensitivity analysis regarding large-scaled problem 33 Chapter 5 Conclusion 36 5.1 Conclusion 36 5.2 Future work 37 References 38 Appendix: Input Data 42

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