Butler, Shane W. and Ringwood, John V. and MacGearailt, Niall
Prediction of Vacuum Pump Degradation
in Semiconductor Processing.
In: SAFEPROCESS'09, 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, June 30 - July 3 2009, Barcelona.
This paper addresses the issue of vacuum pump degradation in semiconductor
manufacturing. The ability to identify the current level of vacuum pump degradation and
predict the Remaining-Useful-Life (RUL) of a dry vacuum pump would allow manufacturers
to schedule pump swaps at convenient times, and reduce the instances of unexpected pump
failures, which can incur significant costs. In this paper, artificial neural networks are used to
model the current level of pump degradation using pump process data as inputs, and a double-
exponential smoothing prediction method is employed to estimate the RUL of the pump.We also
demonstrate the benefit of incorporating process data, from the upstream processing chamber,
in the development of a solution.
Conference or Workshop Item
||fault detection; neural networks; process models;
||Faculty of Science and Engineering > Electronic Engineering
Professor John Ringwood
||22 Sep 2010 15:40
|Journal or Publication Title:
||7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes
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