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以作者查詢圖書館館藏 、以作者查詢臺灣博碩士 、以作者查詢全國書目 、勘誤回報 、線上人數：30 、訪客IP：18.117.72.224
姓名 馬瑞龍(Funk, Ma-Jui Lung) 查詢紙本館藏 畢業系所 企業管理學系 論文名稱 應用X因子理論找出半導體晶圓廠中產能瓶頸區域之研究 相關論文 檔案 [Endnote RIS 格式]
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至系統瀏覽論文 ( 永不開放)
摘要(中) 在半導體產業中，資本支出相較於一般傳統製造業者及科技業者都較為龐大，而
其產品生命週期短暫、技術汰換率過高等高波動率的產業特性，也使得各大廠商不得
不被客戶要求要能夠以低成本、技術創新及能夠快速的進入市場。
本研究以應用 X 因子理論(X-Factor theory)及利特爾法則(Little′s law)找出半導體晶 圓廠中產能瓶頸區域的研究方法，將半導體晶圓廠預設十個加工工作站，假設當半導 體市場需求資訊給定的情況下，如何利用最具效率的方法找出晶圓廠區中的瓶頸工作 區域需要進行優化改善，以利在最短的時間內有效地改善在製品存貨量過多、製造時 間過於攏長、製造成本過高等問題，使生產及資本的效益最佳化。
本研究之研究模型主要利用西門子(Siemens)公司所提供的 Tecnomatix Plant Simulation 13 進行廠區模擬產生出相關的生產績效資料，根據其起始解得出的數值， 利用 SPSS 軟體進行迴歸分析找出其中影響廠區運作效率的關鍵因子，藉以初步判定出 影響廠區整體效益的關鍵瓶頸區域落於何處，最後再以驗證解與起始解比較，以驗證 此解為可行解，以利爾後找出最適之產能配置。摘要(英) The semi-conductor industry has a capital expenditure relatively higher than that of traditional manufacturers and technology industry. With industry characteristics of short product life cycles and high technical replacement rate, major companies are forced by clients to quickly enter the market with low cost and innovative techniques.
This study applies the research methods of X-Factory theory and Little’s law to find out the bottleneck area of production capacity in a semi-conductor company. With a default of ten processing work station in the semi-conductor company, if the information of demand in the semi-conductor market is fixed, how to adopt the most efficient method to find out that the bottleneck area of the semi-conductor company is in need of improvement, so as to effectively solve problems such as excessive inventory, long production time, and high production cost in the shortest possible time, therefore, maximizing the benefits of production and capital.
This research model of this study is mainly the use of Tecnomatix Plant Simulation 13 provided by Siemen to simulate relevant production performance data of the company. Based on initial numbers and by using the SPSS software for regression analysis, key factors in affecting the operating efficiency of the company are found. Initial determination is made to understand where the key bottleneck area that affects the overall benefit of the company is, and eventually make comparisons between the verified solution and starting solution so as to verify that such solution is feasible, which in turn helps find the best production capacity distribution in the future.關鍵字(中) ★ 產能規劃
★ 半導體製程
★ 瓶頸關鍵字(英) ★ Production capacity planning
★ Semi-conductor process
★ bottleneck論文目次 摘要 ..........................................................................................................................I ABSTRACT ..............................................................................................................II 誌謝 ........................................................................................................................III 目錄 ....................................................................................................................... IV 圖目錄 ................................................................................................................... VI 表目錄 .................................................................................................................. VII
第一章 緒論..............................................................................................................1 1.1 研究背景與動機...................................................................................................1 1.2 研究目的 ............................................................................................................1 1.3 研究方法與步驟 ..................................................................................................2
第二章 文獻及理論回顧 ............................................................................................ 4 2.1 半導體產業特性及管理問題...................................................................................4 2.1.1 半導體產業特性 ................................................................................................4 2.1.2 半導體製程及晶圓廠製造流程 ...........................................................................6 2.1.3 半導體生產系統的特性 ....................................................................................11 2.2 半導體工廠決策與產能模式介紹 .........................................................................13 2.2.1 數學規劃模式 .................................................................................................13 2.2.2 等候網路模式 .................................................................................................14 2.2.3 模擬模式 ........................................................................................................15 2.2.4X 因子理論 .....................................................................................................15 2.2.5 廠房效能決策 .................................................................................................17 2.2.6 回歸分析 ........................................................................................................19
第三章 決策模型建置 .............................................................................................. 21 3.1 產能配置的經濟概念...........................................................................................21 3.2.1 何謂產能配置 .................................................................................................21 3.2.2 為何需要做到經濟考量 ...................................................................................22 3.2 啟始解建構 .......................................................................................................23 3.3 產能決策分析 ...................................................................................................25 3.4 最適機台配置產能瓶頸區域判定決策研究之架構 .................................................27
第四章 實例驗證 .................................................................................................... 28 4.1 模擬環境的建置.................................................................................................28 4.2 半導體工業中產能最適機台之分配......................................................................31
4.2.1 各工作站起始解機臺數量及其生產效能.............................................................31 4.2.2 迴歸分析.........................................................................................................31 4.2.3 產能驗證........................................................................................................36 4.2.4 實驗數值分析與結果 ......................................................................................38
第五章 結論與建議 ................................................................................................ 40 5.1 結論..................................................................................................................40 5.2 未來研究方位....................................................................................................40
參考文獻................................................................................................................ 42 附錄:生產績效模擬數據...........................................................................................46參考文獻 [1] Kishimoto, M., Ozawa, K., Watanabe, K., and Martin, D. (2001).” Optimized operations by extended X-factor theory including unit hours concept”, IEEE Transactions on Semiconductor Manufacturing, 14(3), pp.187-195.
[2] Ozawa, K., Wada, H., and Yamaguchi, T. (1999). “Optimum tool planning using the X- factor theory”. In Semiconductor Manufacturing Conference Proceedings, IEEE International Symposium on Semiconductor Manufacturing (ISSM), pp. 49-52.
[3] Wu, S. D., Erkoc, M., and Karabuk, S. (2005). “Managing capacity in the high-tech industry: A review of literature”, The Engineering Economists, 50(2), pp.125-158.
[4]呂麗香(2006)，「以規模經濟的觀點探討半導體晶圓廠產能規劃之研究: 一個以系統 模擬為基礎的方法」，中央大學企業管理學系學位論文，桃園，pp.1-59。
[5]陳欣瑜(2012)，「半導體製造業發展趨勢」，TTR台灣趨勢研究報告，pp.1-4。
[6]Van Zant Peter. (2014). “Microchip fabrication: a practical guide to semiconductor processing”, 6th ed. McGraw-Hill., New York.
[7]楊雲凱(2015)，「物理氣相沉積(PVD)介紹」，國家奈米元件實驗室奈米通訊， 22(4)，pp.33-35。
[8] Schropp, R. E. I., Stannowski, B., Brockhoff, A. M., Van Veenendaal, P. A. T. T., and Rath, J. K. (2000). “Hot wire CVD of heterogeneous and polycrystalline silicon semiconducting thin films for application in thin film transistors and solar cells”, Mater. Phys. Mech, 1(2), 73-82.
[9] Puma, G. L., Bono, A., Krishnaiag, d., Collin, J. G. (2008). “Prepareation of titanium dioxide photocatalyst loaded onto activated carbon support using chemical capor deposition: A review paper”, Journal of Hazardous Materials Vol. 157, Issues 2-3, 15 September 2008, pp.209-219.
[10] Dabbas, R. M., Fowler, J. W. (2003). “A new scheduling approach using combined dispatching criteria in wafer fabs”, IEEE Transactions on Semiconductor Manufacturing, 16(3), Aug. 2003, pp.501-510.
[11] Chien, C. F., and Chen, C. (2007). “Using GA and CTPN for modeling the optimization- based schedule generator of a generic production scheduling system”, International Journal of Production Research, 45(8), pp.1763–1789.
[12] Chien, C. F., Hsu, C. Y., and Chang, K. H. (2013). “Overall wafer effectiveness (OWE): A novel industry standard for semiconductor ecosystem as a whole”, Computers & Industrial Engineering, 65(1), pp.117-127.
[13] Uzsoy, R., Lee, C. Y., and Martin-Vega, L. A. (1992). “A review of production planning and scheduling models in the semiconductor industry. Part I: System characteristics, performance evaluation and production planning”, IIE Transactions, 24(4), pp.47-60.
[14] Stevenson, W. J. (1999). “Production/operations management (6th eds)”, Boston: Irwin.
[15] Bermon, S., and Hood, S.J. (1999). “Capacity optimization planning system (CAPS)”, Interfaces, 29(5), pp.31-51.
[16] Chou, Y. C., and Hong, L. H. (2000). “A methodology for product mix planning in semiconductor foundry manufacturing”, IEEE Transactions on Semiconductor Manufacturing, 13(3), pp.278-285.
[17] Bretthauer, K. M. (1995). “Capacity planning in networks of queues with manufacturing application”, Mathl. Comput. Modeling, 21(12), pp.35-46.
[18] Brown, S. M., Hanschke, T., Meents, I., Wheeler, B. R., Zisgen, H. (2010). “Queueing Model Improves IBM′s Semiconductor Capacity and Lead-Time Management”, Interfaces, 40(5), pp.397-407.
[19] Li, N., Jiang, Z., Liu, G., and Zhang, Z. (2012). “Analysis of quality-caused re-entrance
electrical test system in semiconductor manufacturing by Markov method”, International
Journal of Production Research, 50(12), pp.3486-3497.
[20] Dengiz, B., İç, Y. T., and Belgin, O. (2016). “A meta-model based simulation optimization using hybrid simulation-analytical modeling to increase the productivity in automotive industry”, Mathematics and Computers in Simulation, 120, pp.120-128.
[21] Huang, C. W., and Lin, J. T. (2016). “A pre-dispatching vehicle method for a diffusion area in a 300 mm wafer fab”, Journal of Industrial and Production Engineering, 33(8), pp.579-591.
[22] Martin, D. P. (1996). “How the Tool Characteristics Affect the Cycle Time and Capacity of a Semiconductor Manufacturing Line”.
[23] Martin, D. P. (1997). “How the law of unanticipated consequences can nullify the theory of constraints: The case for balanced capacity in a semiconductor manufacturing line”,
In Advanced Semiconductor Manufacturing Conference and Workshop, 1997. IEEE/SEMI, pp. 380-385.
[24] Delp, D., Si, J., and Fowler, J. W. (2006). “The development of the complete X-factor contribution measurement for improving cycle time and cycle time variability”, IEEE Transactions on Semiconductor Manufacturing, 19(3), pp.352-362.
[25] Nakajima, S. (1988). “Introduction to TPM: Total Productive Maintenance. (Translation)”, Productivity Press, Inc., 1988., pp.129.
[26] Huang, S. H., Dismukes, J. P., Shi, J., Su, Q. I., Razzak, M. A., Bodhale, R., & Robinson, D. E. (2003). “Manufacturing productivity improvement using effectiveness metrics and simulation analysis”, International Journal of Production Research, 41(3), pp.513-527.
[27] De Ron, A. J., & Rooda, J. E. (2006). “OEE and equipment effectiveness: an evaluation”, International Journal of Production Research, 44(23), pp.4987-5003. [28] 林惠玲、陳正蒼(2012)。應用統計學。臺北市:雙葉書廊。
[29] Melhem, M., Ananou, B., Ouladsine, M., & Pinaton, J. (2016). “Regression Methods for Predicting the Product’s Quality in the Semiconductor Manufacturing Process”, IFAC- PapersOnLine, 49(12), pp.83-88.
[30] 何應欽(2015)，作業管理。台北市:滄海書局(William J. Stevenson, 2014).
[31] Karabuk, S., & Wu, S. D. (2003). “Coordinating strategic capacity planning in the semiconductor industry”, Operations Research, 51(6), pp.839-849.
[32] Pindyck, R. S., & Rubinfeld, D. L. (2001). “Microeconomics 5 th”.
[33] Anderson(2001).“Kanban: successful evolutionary change for your technology business. Blue Hole Press”.
[34]Fowler, J. W., Park, S., MacKulak, G. T., and Shunk, D. L. (2001). “Efficient cycle time-throughput curve generation using a fixed sample size procedure”, International Journal of Production Research, 39(12), 2595-2613. [35]余業鑫(2003)，「以生產力為觀點的半導體晶圓廠產能規劃方法」，清華大學工業 工程與工程管理學系學位論文，新竹，pp.1-82。指導教授 呂俊德(Jun-Der Leu) 審核日期 2018-7-16 推文 plurk
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