Conference
Online predictive maintenance approach for semiconductor equipment
Abstract
In this paper, an online predictive maintenance approach is proposed for monitoring health of semiconductor equipment. It includes two phases, the first is online prediction of the health indicator and the second phase is the classification of the indicator to one of the health states for making maintenance decisions. Kernel recursive least square (KRLS) algorithm is used for online prediction which is computational efficient. The health states …
Authors
Luo M; Xu Z; Chan HL; Alavi M
Pagination
pp. 3662-3667
Publication Date
November 2013
DOI
10.1109/IECON.2013.6699718
Conference proceedings
IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society