Fault detection and predictive maintenance program using SEMY Statistical Machine Control (SMC)

Tammie Ogasawara; Brian Izzio

doi:10.1117/12.410101

23 August 2000 Fault detection and predictive maintenance program using SEMY Statistical Machine Control (SMC)

Tammie Ogasawara, Brian Izzio

Proceedings Volume 4182, Process Control and Diagnostics; (2000) https://doi.org/10.1117/12.410101
Event: Microelectronic Manufacturing, 2000, Santa Clara, CA, United States

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.

Citation Download Citation

Tammie Ogasawara and Brian Izzio "Fault detection and predictive maintenance program using SEMY Statistical Machine Control (SMC)", Proc. SPIE 4182, Process Control and Diagnostics, (23 August 2000); https://doi.org/10.1117/12.410101

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