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Proceedings Paper

Fault detection and predictive maintenance program using SEMY Statistical Machine Control (SMC)
Author(s): Tammie Ogasawara; Brian Izzio
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Paper Abstract

This presentation describes the introduction of a fault detection and predictive maintenance strategy into the Diffusion area of a semiconductor manufacturing facility. The goal of the fault detection and predictive maintenance strategy is to maximize tool availability for production while minimizing the risk to product. The predictive maintenance methods allow the user to increase the elapsed time between maintenance activities while minimizing the risk of unexpected equipment failure. The predictive maintenance methods are based on the use of a statistically based fault detection system. The selected equipment parameters are monitored throughout the run for drift beyond established threshold limits. Fault detection is reported directly to a maintenance planning and scheduling application which in turn sends a message to the operating personnel. An option is available which will inhibit the use of the tool until the maintenance activity has been completed. A major part of this project was the identification of equipment parameters for monitoring, the statistical methods used in the analysis and the determination of the threshold values at which t originate a maintenance activity. The decision process leading to the definition of these factors is discussed.

Paper Details

Date Published: 23 August 2000
PDF: 6 pages
Proc. SPIE 4182, Process Control and Diagnostics, (23 August 2000); doi: 10.1117/12.410101
Show Author Affiliations
Tammie Ogasawara, Motorola (United States)
Brian Izzio, Motorola (United States)


Published in SPIE Proceedings Vol. 4182:
Process Control and Diagnostics
Michael L. Miller; Kaihan A. Ashtiani, Editor(s)

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