Predictive Maintenance through Condition Monitoring at Diffusion Equipment of a Solar Cell Manufacturing Environment

Article Preview

Abstract:

This paper analyzes failures at diffusion equipments in a solar cell manufacturing. The history was gathered and analyze. This paper starts with prioritizing the frequent failures through Pareto Analysis and starts to discuss potential method to reduce its failure. The Root Cause Analysis with probability ratio was created by the team and they had identified potential Condition Monitoring. This diffusion equipment stores most parameter and process readings that makes the automatic Condition Monitoring possible. The Condition Monitoring on one of the parameter readings was implemented and it has shown a high reduction in that equipment failures.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 476-478)

Pages:

655-660

Citation:

Online since:

February 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Junhong Zhou, Xiang Li, Anton J.R. Andernroomer, Hao Zeng, Kiah Mok Goh, Yoke San Wong and Geok Soon Hong (2005). Intelligent Prediction Monitoring System for Predictive Maintenance in Manufacturing. Industrial Electronics Society, 2005. IECON 2005. 31st Annual Conference of IEEE Page 2314 - 2319 .

DOI: 10.1109/iecon.2005.1569264

Google Scholar

[2] Clesson T. Emoto, Rudy Tamayo, and Gary R. Hoffman, Senior Member IEEE (2006). Implementation of a Predictive Maintenance System. Transmission and Distribution Conference and Exhibition, 2005/2006 IEEE PES Page 57 - 61 .

DOI: 10.1109/tdc.2006.1668454

Google Scholar

[3] Joe, C.Y. Tang, (2006).CLP Experience on Condition Monitoring and Condition Based Maintenance. Advances in Power System Control, Operation and Management (APSCOM 2009), 8th International Conference Page 1 - 7 .

DOI: 10.1049/cp.2009.1747

Google Scholar

[4] H.M. Hashemian, Senior Member, IEEE (2010). State-of-the-Art Predictive Maintenance Techniques. IEEE Transaction on Instrumentation and Measurement. Volume 60, Issue 1, Page 226 - 236.

DOI: 10.1109/tim.2010.2047662

Google Scholar

[5] J-P Gerval, G. Morel, C Querre (1994) . Behavior modelling and vibrations analysis applied to predictive maintenance : differential approaches leading to the same conclusion. OCEANS '94. 'Oceans Engineering for Today's Technology and Tomorrow's Preservation.' Proceedings IEEE. Vol 1, Page 544-546.

DOI: 10.1109/oceans.1994.363840

Google Scholar

[6] Andrew K.S. Jardine (2002). Optimizing Condition Based Maintenance Decision. Reliability and Maintainability Symposium, 2002. Proceedings. Annual IEEE CONFERENCES. Page 90-97.

DOI: 10.1109/rams.2002.981625

Google Scholar