NDLI: Maintenance decision-making using a continuous-state partially observable semi-Markov decision process

Content Provider	IEEE Xplore Digital Library
Author	Yifan Zhou Lin Ma Mathew, J. Yong Sun Wolff, R.
Copyright Year	2010
Description	Author affiliation: CRC of Integrated Engineering Asset Management (CIEAM), School of Engineering Systems, Queensland University of Technology, Brisbane, Australia (Yifan Zhou; Lin Ma; Mathew, J.; Yong Sun) \|\| School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia (Wolff, R.)
Abstract	Due to the limitation of current condition monitoring technologies, the actual health state of an asset may not be revealed accurately by health inspections. A maintenance strategy ignoring this uncertainty of health state can cause additional costs or downtime. The partially observable Markov decision process (POMDP) is a commonly used approach to derive optimal maintenance strategies when the health inspection is imperfect. However, the existing applications of the POMDP to maintenance decision-making largely adopt the discrete time and state assumptions. The discrete-time assumption requires the health state transitions and maintenance activities only happen at discrete epochs, which cannot model the failure time accurately and is not cost-effective. The discrete health states, on the other hand, may not be elaborate enough to improve the effectiveness of maintenance. To address these limitations, this paper proposes a partially observable semi-Markov decision process (POSMDP) which is continuous in time and states. A Monte Carlo-based density projection method is adopted to convert the POSMDP to a complete observable semi-Markov decision process (SMDP). The converted SMDP is then solved by the policy iteration. At the end of this paper, a simulation study is performed to evaluate the performance of the POSMDP. The result shows that the maintenance strategy derived by the POSMDP is more cost-effective than another two maintenance strategies derived by approximate methods, when regular inspection intervals are adopted. The simulation study also shows that the maintenance cost can be further reduced by developing maintenance strategies with state-dependent maintenance intervals using the POSMDP.
Starting Page	1
Ending Page	8
File Size	1563259
Page Count	8
File Format	PDF
ISBN	9781424447565
e-ISBN	9781424447589
DOI	10.1109/PHM.2010.5413427
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-01-12
Publisher Place	Macao
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Decision making Maintenance decision-making State space model Partially observable semi-Markov decision process
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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