Degradation modeling and monitoring of machines using operation-specific hidden Markov models

Cholette, Michael E. & Djurdjanovic, Dragan (2014) Degradation modeling and monitoring of machines using operation-specific hidden Markov models. IIE Transactions, 46(10), pp. 1107-1123.

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Abstract

In this paper, a novel data-driven approach to monitoring of systems operating under variable operating conditions is described. The method is based on characterizing the degradation process via a set of operation-specific hidden Markov models (HMMs), whose hidden states represent the unobservable degradation states of the monitored system while its observable symbols represent the sensor readings. Using the HMM framework, modeling, identification and monitoring methods are detailed that allow one to identify a HMM of degradation for each operation from mixed-operation data and perform operation-specific monitoring of the system. Using a large data set provided by a major manufacturer, the new methods are applied to a semiconductor manufacturing process running multiple operations in a production environment.

Impact and interest:

6 citations in Scopus
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6 citations in Web of Science®

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19 since deposited on 18 Jul 2014
4 in the past twelve months

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ID Code: 73999
Item Type: Journal Article
Refereed: Yes
DOI: 10.1080/0740817X.2014.905734
ISSN: 1545-8830
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MECHANICAL ENGINEERING (091300) > Automation and Control Engineering (091302)
Divisions: Current > Schools > School of Chemistry, Physics & Mechanical Engineering
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 Taylor & Francis
Deposited On: 18 Jul 2014 01:53
Last Modified: 04 Jan 2016 15:43

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