Butler, Shane and Ringwood, John and MacGearailt, Niall (2009) 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.

Download (471kB)

Abstract

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.

Item Type:	Conference or Workshop Item (Paper)
Keywords:	fault detection; neural networks; process models;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering
Item ID:	2126
Depositing User:	Professor John Ringwood
Date Deposited:	22 Sep 2010 15:40
Journal or Publication Title:	7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes
Refereed:	No
URI:
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

Repository Staff Only(login required)

Item control page

Downloads

Origin of downloads