Translated Titles

A Study of Equipment Preventive Maintenance (EPM) with Applying Process Defective Rate for Production System





Key Words

預知性預防 ; 可靠度 ; 倒傳遞網路 ; 預防維護 ; 不良率 ; Defective Rate ; Back-Propagation Neural Network ; Prevention by Prediction ; Reliability ; Preventive Maintenance



Volume or Term/Year and Month of Publication


Academic Degree Category




Content Language


Chinese Abstract

中文摘要 本研究主要係針對具有因龐大的設備成本導致過高的維護成本之產業為研究對象,並結合可靠度(Reliability)的觀念與成本效益分析來發展一套以設備製程不良率為基礎之預防維護決策系統。 本研究所考慮的參數有:平均失效間隔時間(MTBF)、生產批量數(N)、預防維護成本(PMC)、單位產品成本(IC)以及單位產品製程時間(PT)…等,期望藉由以上參數來建構預防維護模式以制定製程不良率之上限值(P)為停機維護的閥值(Threshold Value),並利用系統模擬軟體eM-Plant的運算能力來有效執行其計算過程。另外,藉由倒傳遞網路(BPNN)之函數對應能力,建構設備之預防維護決策系統。 最後利用模擬機台生產製程之實驗資料進行數據分析,驗證本維護模式之可行性。且本研究亦驗證出預防維護決策系統具有不需等到設備失效即可預知何時該執行預防維護的能力,有效達到預知性預防(Prevention by Prediction)之特性。 關鍵詞:預防維護、可靠度、不良率、倒傳遞網路、預知性預防

English Abstract

Abstract The purpose of this research is about combining the concepts of reliability and cost-effect analysis to develop a preventive maintenance decision system based on manufacturing process defective rate for those industries with the feature of high maintenance cost for the equipments. Parameters mainly considered in this paper include: Mean Time Between Failure (MTBF), Production Lot (N), Preventive Maintenance Cost (PMC), Item Cost (IC) and Process Time per Unit (PT). We expect not only to build a preventive maintenance model by using these parameters but also to decide the upper limit of process defective rate (P). Once the process defective rate is beyond to this limit, an immediate equipment maintenance has to be carried out. During this study, we use eM-Plant to simulate the proposed model, and use back-propagation neural network to construct the decision system. In this study, data collected from the simulation process are utilized to demonstrate the feasibility of this model. The unique feature of the preventive maintenance decision system is that it can be applied to practical manufacturing process, and use its capability of prevention by prediction to detect the time to maintain in advance. Key Word:Preventive Maintenance , Reliability , Defective Rate , Back-Propagation Neural Network , Prevention by Prediction

Topic Category 工學院 > 工業工程研究所
工程學 > 工程學總論
  1. 5. Charles, E. Ebeling, An Introduction To Reliability and Maintainability Engineering, McGraw-Hill, International Editions, 1997.
  2. 6. Charytoniuk, W. and M. S. Chen, “ Neural-network-based demand forecasting in aderegulated environment ”, IEEE Transactions on industry applications, Vol.36, No.3, pp.893-898, May/June 2000.
  3. 7. Dantas, A., K. Yamamoto, M. V. Lamar and Y. Yamashita, “ Neural network for travel demand forecasting using GIS and Remote Sensing ”, IEEE proceeding, pp.435-440, 2000.
  4. 9. Hornik, K., M. Stinchcombe and H White, “ Multilayer Feedforward Networks are Universal Approximators”, Neural Networks, Vol. 2, pp.359-366, 1989.
  5. 11. Johnson, Perry L., Kantner, Rob and Kikora, Marcia A., TQM Team-Building and Problem Solving, Southfield, MI: Perry Johnson, Inc., pp.1-1 ~ 10-15, 1990.
  6. 12. Kececioglu, D. and F.B. Sun, “ A general discrete-time dynamic programming model for the opportunistic replacement policy and its application to ball-bearing systems ”, Reliability Engineering and System Safety, Vol.47, pp.175-185, 1995.
  7. 13. Lam, C.T. and R.H. Yeh, “ Optimal Maintenance-Policies For Deterioration Systems Under Various Maintenance Strategies ”, IEEE Transactions on Reliability, Vol. 43, pp. 423-430, 1994.
  8. 14. Law, R., “ Back-propagation learning in improving the accuracy of neural network based tourism demand forecasting ”, Tourism Management, Vol. 21,pp. 331-340, 2000.
  9. 15. Law, R. and N. Au, “ A neural network model to forecast Japanese demand for travel to Hong Kong ”, Tourism Management, Vol. 20, pp 89-97, 1999.
  10. 17. Love, C.E. and R. Guo, “ Using proportional hazard modelling in plant maintenance ”, Quality and Reliability Engineering international, Vol. 7, pp.7-17, 1991.
  11. 19. May, G.S. and C.J. Spanos, “ Automated Malfunction Diagnosis of Semiconductor Fabrication Equipment: A Plasma Etch Application ”, IEEE Transactions on Semiconductor Manufacturing, Vol. 6, No.1, pp. 28-40, 1993.
  12. 20. McFadden, R.H., “ Developing a Database for a Reliability, Availability, and Maintainability Improvement Program for an Industrial Plant or Commercial Building ”, IEEE Transactions on Industrial Applications, Vol.26, No.4, 1990.
  13. 21. Okogbaa, G., J. Huang and R. L. Shell, “ Database Design for Predicitive Preventive Maintenance System of Automated Manufacturing System ”, Computers and Industrial Engineering, Vol. 23, No. 1-4, pp. 7-10, 1992.
  14. 25. Sim, S.H. and J. Endrenyi, “ Optimal Preventive Maintenance with Repair ”,IEEE Transactions on reliability, Vol.37, pp.92-96, 1988.
  15. 26. Su, C.T., Wu, S.C. and Chang, C.C., “Multiaction maintenance subject to action-dependent risk and stochastic failure”, European Journal of Operational Research Vol.125 pp.133-148, 2000.
  16. 27. Vaurio, J.K., “ Optimization of test and maintenance intervals based on risk and cost ”, Reliability Engineering and System Safety, Vol.49, pp.23-36, 1995.
  17. 29. Wang, K.S. and C.H.Lin, “ Replacement policy about key components of a system ”, Proceedings of the 11th Nat. Conf. Of the Chinese Society of Mechanical Engineers, Nat. Chung Hsing University, Taichung, Taiwan, ROC, pp.595-604, 1994.
  18. 30. Wildeman, R.E., R. Dekker and A.C.J.M. Smit, “ A dynamic policy for grouping maintenance activities ”, European Journal of Operation Research Vol.99, pp.530-551, 1997.
  19. 31. Wood, A.P., “ Optimal Maintenance Policies for Constantly Monitored System ”,Naval Research Logistics Vol.35, pp.461-471, 1988.
  20. 參考文獻
  21. 英文部分:
  22. 1. Aven, T. and R. Dekker, “ A useful framework for optimal replacement models ”, Reliability Engineering and System Safety, Vol.58, No.2, pp.61-67, 1997.
  23. 2. Benjamin, S.B. and W.J. Fabrycky, Systems Engineering and Analysis, Prentice Hall, Inc., 1998.
  24. 3. Bullema, J. E., C. J. G. Hehl, C. Klomp and B. R. P. Nederhand, “ Total Productive Maintenance : Towards Development of a Pro-active Maintenance Concept ”, Technical Report, Philips, 1994.
  25. 4. Chang, Y.C., H.C. Cheng and W.F. Wu, “ Reliability centered maintenance policy ”, Proceeding of The Second symposium on Reliability and Maintainability, Chungli, Taiwan, ROC, pp.223-230, 1997.
  26. 8. Goetsch, David L. and Davis, Stanley B., Introduction to Total Quality, 2/E ,Prentice-Hall, Inc., New Jersey, 1997.
  27. 10. Ishikawa, Kaoru, Guide to Quality Control, Asian Productivity Organization, Tokyo, pp.24-26, 1976.
  28. 16. Legat, V., A.H.Zaludora, V. Cervenka and V. Jurca, “ Contribution to optimization of preventive replacement ”, Reliability Engineering and System Safety, Vol.51, No.3, pp.259-266, 1996.
  29. 18. Marteel, D., D. Menexiadis and R. Soenen, “ Maintenance Knowledge Base Design Methodogy and Building of an Integrated Preventive Maintenance System( IPMAS) ”, Knowledge Based Hybrid Systems (B-11), Edited by E. Mezgar and P.Bertok, Published by Elsevier Science Publishers B. V., pp. 251-260, 1993.
  30. 22. Pintelonm, L.M. and L.F. Gelders, “ Maintenance management decision making ”,European Journal of Operation Research, Vol. 58, pp.301-307, 1992.
  31. 23. Pintelonm, L.M. and L. N. Wassenhove, “ A Maintenance Management Tool ”, OMEGA Int.J.of Mgmt Sci., Vol. 18, No. 1, pp. 59-70, 1990.
  32. 24. Scherkenbach, William W., “ Deming’s Road to Continual Improvement ”, Knoxville, TN: SPC Press, Inc, pp.63-66, 1991.
  33. 28. Walton, Mary, “ The Deming Management Method ”, The Putnam Publishing Group, New York, pp.98-119, 1986.
  34. 32. Yurtsver, T. and M. Comerford, “ Equipment Management System (EMS)”, IEEE/SEMI Advanced Semiconductor Manufacturing Conference, 1995.
  35. 中文部分:
  36. 1. 汪益譯,Rafael Aguayo 原著,品管大師戴明博士,聯經出版社,1997年5 月。
  37. 2. 林恬宇, 設備維護系統設計-維護策略與週期之訂定,中原大學工業工程研究所碩士論文,1996年7月。
  38. 3. 施育仁,半導體後段製程生產設備維修決策支援系統之研究,國立台北科技大學生產系統工程與管理研究所碩士論文,2001年7月。
  39. 4. 紀冠安,考慮成本與可靠度之不完全預防維護模型,朝陽科技大學工業工程與管理學系碩士論文,2001年7月。
  40. 5. 陳家明等著,系統模擬eM-Plant(SiMPLE++)操作與實務,華泰書局,2001年。
  41. 6. 許隆昌,設備保養之失效模式與效應分析,中華大學工業工程與管理研究所碩士論文,2001年6月。
  42. 7. 程鈞尉,生產系統中最佳維修策略之制定與推導,國立成功大學統計學研究所碩士論文,1998年6月。
  43. 8. 彭鴻霖,可靠度技術手冊,中原大學工業工程研究所講義,中壢,2003年。
  44. 9. 葉怡成,類神經網路模式應用與實作,儒林圖書,1999年。
  45. 10. 黃以宏,以類神經構建半導體廠生產績效預策模式,國立交通大學工業工程與管理學系碩士論文,1997年6月。
  46. 11. 鄭達才,設備維護管理,中國生產力中心,2000年5 月。
  47. 12. 蔡有藤,系統預防維護作業之研究,國立中央大學機械工程研究所博士論文,1999年6月。
  48. 13. 藤本俊原著,豐田式管理實踐,劉天祥譯,中國生產力中心,1997年。
  49. 14. 羅哲生,半導體製造設備全面維護管理系統下之故障預測模式,國立清華大學工業工程研究所碩士論文,1997年6月。
Times Cited
  1. 林昌誠(2008)。基於支持向量迴歸及支持向量資料描述 之半導體CVD 製程虛擬量測研究。中原大學機械工程研究所學位論文。2008。1-157。 
  2. 施靜如(2008)。整合預防維護與插單於流線型雙機台之重排程探討。中原大學工業工程研究所學位論文。2008。1-100。 
  3. 陳穎仁(2008)。應用馬可夫決策過程於維護策略研究 -以太康導航系統為例。中原大學工業工程研究所學位論文。2008。1-87。 
  4. 許晉榮(2009)。基於模糊支持向量迴歸之半導體CVD製程厚度預測。中原大學機械工程研究所學位論文。2009。1-91。 
  5. 張君實(2007)。延遲完工懲罰成本最小化之流線型 雙機生產排程與預防維護計畫之整合。中原大學工業工程研究所學位論文。2007。1-83。 
  6. 郭晉源(2007)。晶圓測試廠維護策略對生產績效影響之研究。清華大學工業工程與工程管理學系學位論文。2007。1-117。
  7. 邱惠筠(2007)。多組件系統之機會性置換策略。元智大學工業工程與管理學系學位論文。2007。1-48。
  8. 周大鈞(2010)。應用德爾菲法及分析網路程序法於半導體分析晶片缺點因子改善製程良率之研究。虎尾科技大學工業工程與管理研究所學位論文。2010。1-67。
  9. 謝宗翰(2013)。網通產業導入設備資產管理系統之個案研究探討。臺北科技大學管理學院工業工程與管理EMBA專班學位論文。2013。1-119。