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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 周雍強 | |
dc.contributor.author | Kevin Ko Shing Chang | en |
dc.contributor.author | 張可興 | zh_TW |
dc.date.accessioned | 2021-06-13T04:22:55Z | - |
dc.date.available | 2006-07-27 | |
dc.date.copyright | 2006-07-27 | |
dc.date.issued | 2006 | |
dc.date.submitted | 2006-07-22 | |
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[2] Al-Aomar, R. (2000), “Product-Mix Analysis with Discrete Event Simulation,” Proceedings of the 2000 Winter Simulation Conference, pp. 1385-1392. [3] Balasubramaniam, S., Sarwar, A. K., and Walker, D. M. H. (1997), “Yield Learning in Integrated Circuit Package Assembly,” IEEE Transactions on Components, Packaging, and Manufacturing Technology, Part C, Vol. 20, No. 2, pp. 133-141. [4] Benjaafar, S., Kim, J. S., and Vishwanadham, N. (2004), “On the Effect of Product Variety in Production-Inventory Systems,” Annals of Operations Research, Vol. 126, No. 1-4, pp. 71-101. [5] Cachon, G. P., Gao, G., and Hitt, L. (2005), “Product Variety, Inventory Management and Firm Performance,” The 2005 Manufacturing and Service Operations Management Conference. [6] Cinlar, E. (1975), Introduction to Stochastic Processes, Prentice-Hall. [7] Clark, K. B. and Wheelwright, S. C. (1992), Managing New Product and Process Development, Free Press. [8] Connors, D. P., Feigin, G. E., and Yao, D. D. (1996), “A Queueing Network Model for Semiconductor Manufacturing,” IEEE Transactions on Semiconductor Manufacturing, Vol. 9, No. 3, pp.412-427. [9] Deshmukh, A. V., Talavage, J. J., and Barash, M. M. (1998), “Complexity in Manufacturing Systems Part 1: Analysis of Static Complexity,” IIE Transactions, Vol. 30, No. 7, pp. 645-655. [10] Johnson, N. and Kotz, S. (1969), Discrete Distributions, Wiley. [11] Karlis, D. and Ntzoufras, I. (2000), “Discrete Distributions with Applications in Sports,” manuscript, Athens University of Economics and Business Greece. [12] Katti, S. K. (1960), “Moments of the Absolute Difference and Absolute Deviation of Discrete Distributions,” Annals of Statistics, Vol. 31, No. 1, pp. 78-85. [13] Keller, J. B. (1994), “A Characterization of the Poisson Distribution and the Probability of Winning a Game,” The American Statistician, Vol. 48, No. 4, pp. 294-299. [14] Kuo, W. and Kim, T. (1999), “An Overview of Manufacturing Yield and Reliability Modeling for Semiconductor Products,” Proceedings of the IEEE, Vol. 87, No. 8, pp. 1329-1344. [15] Kwon, Y. J. and Walker, D. M. H. (1995), “Yield Learning via Functional Test Data,” International Test Conference, pp. 626-635. [16] Nag, P. K., Maly, W., and Jacobs, H. J. (1997), “Simulation of Yield/Cost Learning Curves witn Y4,” IEEE Transactions on Semiconductor Manufacturing, Vol. 10, No. 2, pp. 256-266. [17] Perona, M. and Miragliotta, G. (2004), “Complexity Management and Supply Chain Performance Assessment. A Field Study and a Conceptual Framework,” International Journal of Production Economics, Vol. 90, No. 1, pp. 103-115. [18] Ross, S. (1993), Introduction to probability model, Academic Press. [19] Skellam, J.G. (1946), “The Frequency Distribution of the Difference Between Two Poisson Variates Belonging to Different Populations,” Journal of the Royal Statistical Society, Vol. 109, No. 3, pp. 296. [20] Thonemann, U. W. and Bradley, J. R. (2002), “The Effect of Product Variety on Supply-Chain Performance,” European Journal of Operational Research, Vol. 143, No. 3, pp. 548-569. [21] Yuan, L. and Kalbfleisch, J. D. (2000), “On the Bessel Distribution and Related Problems,” Annals of the Institute of Statistical Mathematics, Vol. 52, No. 3, pp. 438-447. [22] http://en.wikipedia.org/wiki/Skellam_distribution [23] 周雍強,“非等效並聯機台之生產規劃與排程”,生產排程理論與運用研討會,1999。 [24] 張毓恒,“半導體製造產品組合變異與效用評估”,國立台灣大學工業工程學研究所碩士論文,2004。 [25] 業家佑,“產品組合對平行機台工作分派效率之影響”,國立台灣大學工業工程學研究所碩士論文,2005。 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/33042 | - |
dc.description.abstract | 半導體晶圓專業製造廠的生產環境特徵為在同一個製造系統內必須同時處理數十種不同的IC產品,需求來源分散而多元。產品多樣性的提高將影響系統的實體複雜度,一方面強化了生產彈性增加產業競爭力,另一方面也使得系統必須承擔一定程度的生產效率損失。
本研究以隨機過程的機率模型假設產品組合的分配,來適切實際環境的隨機性與動態性,討論在不同的情境與限制下,產品組合機率的分布與變化,以建立一個多樣性與效率關係的分析架構。本文首先討論個別產品需求、產品總量需求、受限於總量條件下的組合狀態、組合差異與組合絕對差異等情境與限制,這些產品組合狀態的分布情形能幫助分析產品多樣性的動態與隨機情形。其次,本文建立了一個較為直觀,但可以廣泛運用在不同生產單元之產品組合與生產績效的關係模式,提供各個生產階層在從事生產控制功能時一個有效的決策工具。以設定轉換發生的期望機率來衡量產品多樣性對效率損失的影響程度,並選擇產品需求率的變異係數作為判斷產品組合比例均勻程度的指標。本研究工作發現在產品種類數增多的情形下,生產效率的損失程度也會跟著上升,但幅度會愈來愈小;而產品組合越均勻的情形下,設定轉換所造成的效率損失會越大。在生產規劃的決策上,本文亦推導了在生產批量增加的情形下,對效率損失的降低程度。本文最後提供了關係模式的應用,包括平行機台組在滿足各產品產能匹配的限制下,最佳化生產效率的損失,並且分析了高優先權的產品比例對製造系統的效率影響,以及利用各種組合狀態的分配情形來衡量製造系統的平準化程度。 | zh_TW |
dc.description.abstract | Most manufacturing systems have to face multiple sources of product demands. In this situation, tradeoffs between efficiency and flexibility are important decisions. Efficiency means that a manufacturing system can produce mass quantity of products on time with minimum production costs. Flexibility means that product variety is high in order to satisfy high level of customization. Product variety includes two main factors. One is the number of product types and the other is product mixes. In this work, the effects of product variety on the manufacturing system operation are studied. In this thesis, a stochastic and probability model for product mixes is first presented. It is then applied to three cases of production control of parallel machine systems: FCFS, time bucket, and batch queue. The efficiency loss is measured by the setup changeover. The relationship between variety and efficiency is then derived. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T04:22:55Z (GMT). No. of bitstreams: 1 ntu-95-R93546021-1.pdf: 791033 bytes, checksum: 6fc46353c25b773997dc746ad0b6a2ad (MD5) Previous issue date: 2006 | en |
dc.description.tableofcontents | 中文摘要 III
英文摘要 IV 圖目錄 VII 表目錄 IX 第一章 緒論 1 1.1 研究背景與動機 2 1.2 問題描述 3 1.2.1 產品多樣性 3 1.2.2 多產品產能規劃 5 1.3 研究目的 7 1.4 研究構想 8 1.5 論文架構 10 第二章 文獻回顧與探討 11 2.1 系統複雜度 11 2.2 產品多樣性 14 2.3 良率學習 18 第三章 產品組合狀態的機率分析 24 3.1 產品組合的概述 24 3.2 兩種產品之組合狀態的機率分配 26 3.2.1 總量的機率分配 28 3.2.2 受限於總量條件之組合狀態的機率分配 29 3.2.3 組合狀態比值的機率分配 32 3.2.4 組合狀態差異的機率分配 34 3.2.5 組合狀態絕對差異的機率分配 35 3.3 多種產品之組合狀態的機率分配 36 第四章 產品多樣性與生產效率之關係模式 40 4.1 不同製造系統下之關係模式 40 4.1.1 先到達先服務下之關係模式 41 4.1.2 規劃時格下之關係模式 44 4.1.3 生產批量下之關係模式 48 4.2 設定轉換次數的機率分配 51 4.3 關係模式結果分析 54 4.3.1 產品種類數對設定轉換之影響關係 55 4.3.2 產品組合比例對設定轉換之影響關係 56 4.3.3 時間比例對效率損失比率之影響關係 60 4.3.4 生產批量對設定轉換之影響關係 62 4.4 產品多樣性的生產規劃 63 4.4.1 機台分派問題的應用 63 4.4.2 優先權產品的規劃問題 65 4.4.3 系統平準化的衡量指標 67 第五章 結論與未來展望 68 5.1 結論 68 5.2 未來研究建議 69 參考文獻 70 | |
dc.language.iso | zh-TW | |
dc.title | 產品多樣性對製造系統生產效率之影響模式 | zh_TW |
dc.title | Evaluating the Effect of Product Variety on the Efficiency of Manufacturing Systems | en |
dc.type | Thesis | |
dc.date.schoolyear | 94-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 吳文方,謝淑華 | |
dc.subject.keyword | 產品多樣性,產品組合,隨機過程,機率分配, | zh_TW |
dc.subject.keyword | Product Variety,Product Mixes,Variety-efficiency Relationship, | en |
dc.relation.page | 72 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2006-07-23 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 工業工程學研究所 | zh_TW |
顯示於系所單位: | 工業工程學研究所 |
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