生產機台是半導體，TFT-LCD，太陽能等產業中非常重要的一環。若該生產機台內之任一個模組發生故障 (如：壓力器、加熱器等), 將可能導致與其相關之機台設備功能異常或停擺，造成隨之而來的重大損失。而半導體機台結構如此複雜，目前並無一個系統化且有效的管理方式來直接讓使用者即時掌握整個機台的健康狀況。參考目視化生產管理中的看板系統中即時傳送與層層傳送資料的概念，本論文將針對結構複雜的機台，發展出一即時監控的電子看板及系統架構 (Intelligent Predictive Maintenance (IPM) Framework), 讓結構複雜機台之健康狀況能系統化地呈現給使用者以達到即時監控的目標。最後並以實際生產中之資料驗證架構的可行性

Process tools are an essential part for semiconductor manufacturing, TFT-LCD, and solar-cell industries. When a module of a process tool (ex. pressure gauge, heater, etc.) breaks down, it would result in abnormal function(s) and may cause serious damage. Nevertheless, the structure of a process tool is rather complicated. At present, there is no systematic and feasible approaches to monitor the health status of a process tool, which could be obvious at a glance of users. In this paper, a real-time monitoring dashboard and Intelligent Predictive Maintenance (IPM) framework are proposed. By utilizing the concept of visual management, users can learn the health status of a process tool systematically to reach the goal of real-time monitoring the process tool. Finally, real data of a practical process tool are applied to validate the feasibility of the IPM framework.

參考文獻
[1] ISMI Predictive and Preventive Maintenance Equipment Implementation Guidelines Technology Transfer #08064934A-ENG International SEMATECH Manufacturing Initiative August 30, 2008.
[2] 羅文雄, 蔡榮輝, 鄭岫盈 「半導體製造技術」，滄海書局，2011.
[3] SEMI E120-1104, Specification for the Common Equipment Model (CEM), U.S.A., 2004.
[4] 林進旺 「目視管理操作技巧」，憲業企管顧問有限公司，2008.
[5] V. T. Tran, B.-S. Yang, "An Intelligent Condition-Based Maintenance Platform for Rotating Machinery," Expert Systems with Applications, vol. 39, pp. 2977–2988, February 2012.
[6] T. Han, B.-S. Yang, "Development of an E-maintenance System Integrating Advanced Techniques," Computers in Industry, vol. 57, pp. 569-580, August 2006.
[7] L. Liao , J. Lee, "Design of a Reconfigurable Prognostics Platform for Machine Tools," Expert Systems with Applications, vol. 37, pp. 240–252, January 2010.
[8] V. T. Tran, B.-S. Yang, "An Intelligent Condition-Based Maintenance Platform for Rotating Machinery," Expert Systems with Applications, vol. 39, pp. 2977–2988, February 2012.
[9] Y.-S. Hsieh, F.-T. Cheng, H.-C. Huang, C.-R. Wang, S.-C. Wang, and H.-C. Yang, “VM-based Baseline Predictive Maintenance Scheme,” IEEE Transactions on Semiconductor Manufacturing, vol. 26, no. 1, pp. 132-144, February 2013.
[10] SEMI E132-0305, Specification for Equipment Client Authentication and Authorization (A&A), U.S.A., 2005.
[11] SEMI E125-0305, Specification for Equipment Self Description (ESD), U.S.A., 2005.
[12] SEMI E134-0305, Specification for Data Collection Management (DCM), U.S.A., 2005.
[13] F.-T. Cheng, G.-W. Huang, C.-H. Chen, and M.-H. Hung, "A Generic Embedded Device for Retrieving and Transmitting Information of Various Customized Applications," in Proc. 2004 IEEE International Conference on Robotics and Automation, New Orleans, Louisiana, U.S.A., pp. 978-983, April 2004.
[14] W.-M. Wu, F.-T. Cheng and F.-W. Kong, “A Dynamic-Moving-Window Scheme for Virtual-Metrology Model Refreshing,” IEEE Transactions on Semiconductor Manufacturing, vol. 25, pp. 238-246, May 2012.
[15] C.-F. Chen, Y.-S. Hsieh, F.-T. Cheng, H.-C. Huang, and S.-C. Wang, “Automatic Baseline-Sample-Selection Scheme for Baseline Predictive Maintenance,” Proc. of the 2013 IEEE International Conference on Automation Science and Engineering (CASE 2013), Madison, Wisconsin, USA, pp. 189-194, August 17-21, 2013.
[16] D. H. Stamatis, Failure Mode Effect Analysis: FMEA From Theory to Execution, 2d ed. Milwaukee: ASQ Quality Press, 2003.
[17] B. Anderson, T. Fagerhaug, Root Cause Analysis Simplified Tools and Techniques, 2d ed. Milwaukee: ASQ Quality Press, 2006.