透過您的圖書館登入
IP:3.142.196.27
  • 學位論文

半導體製造之先進製程產能的建置時點模型

A Model of Capacity Deployment Timing for Advanced Processes of Semiconductor Manufacturing

指導教授 : 周雍強

摘要


高科技產業的技術測試與產品需求有很高的不確定性,而先進製程技術更迭迅速、建廠的前置時間長,使得製程測試壓力很大,此外產能的投資成本往往很高,更加深了企業在規劃先進製程技術產能投資的困難度,產能建置過早會造成設備閒置,建置太晚則會喪失商機,所以產能建置時點是高科技製造企業的重要決策。 本文的主要目的是探討半導體先進製程產能的建置規劃方法,本文首先建構包含良率改善的隨機模型在內的系統動態模型,其次,依據系統動態關係,建立一個設備閒置與商機損失的經濟分析模式,最後,產能就緒的最佳時點經由數學優化產生並以投資績效指標,提出一個產能擴充的應有態度。 本研究的主要貢獻為成孕H良率改善的隨機模型計算測試期時間長度的機率分佈,提供企業明確的先進製程產能投資時點的決策方法,並結合產能擴充計劃與投資績效指標,客觀地提出產能擴充的合理態度。未來的高科技產業將會有很多的不確定性,本文提出的方法將有助於分析風險與制訂對策。

並列摘要


Technology development and product demand in high-tech industries are full of uncertainties. Since building a factory requires long lead-time and manufacturing capacity incurs high cost, capacity deployment timing is an important decision in the uncertain environment of technology development and the volatile market. The objective of this paper is to propose a method of capacity deployment timing for advanced process technology of semiconductor manufacturing in order to decrease the capacity idle costs and the losing business chance costs. A dynamic system model based on a stochastic model of yield improvement is first presented. And then, establish an economic analysis model considering over-capacity and under-capacity costs. Finally, illustrations are given to show how to optimize capacity deployment timing with this model. The contribution of this paper is to offer successfully the distribution of time length of development, present the method of capacity deployment timing decision, and verify its optimization. Besides, the editor also presents a proper attitude to capacity increment when the demand condition is uncertain. Because of the high uncertainties that high-tech industry will face in the future, the research results will help those firms in that industry to make better risk and strategy analyses.

參考文獻


2. Balasubramaniam, S., Abul K. Sarwar and D. M. H. Walker, , “Yield Learning in Integrated Circuit Package Assembly,” IEEE Transactions on components, packaging, and manufacturing technology, part C, Vol.20, No.2, April 1997.
3. Baldi, L., “Industry roadmaps: The challenge of complexity,” Microelectronic Engineering 34, 1996, p. 9-26
4. Benavides, D.L., James R. Duley and Blake E. Johnson, “As Good as it Gets: Optimal Fab Design and Development,” IEEE Transactions on Semiconductor Manufacturing, Vol.12, No.3, 281-287, 1999
5. Cassandras, C. G.., and Yu-Chi Ho, “Yield Learning and Production Planning for Semiconductor Manufacturing Systems,” Network Dynamics, Inc., 128 Wheeler Road, Burlington, MA01803, 385-390, 1994.
6. Clarke, F. H., Darrough M.N., and Heineke J.M., “Optimal Pricing Policy in the Presence of Experience Effects,” Journal of Business 55, 517-530, 1982.

被引用紀錄


陳永豐(2006)。半導體製造之產能規劃的實質選擇權法之應用〔碩士論文,國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2006.01518

延伸閱讀