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.
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.
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|Item Type:||Journal Article|
|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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