Optimal maintenance policies for a safety‐critical system and its deteriorating sensor

We consider the integrated problem of optimally maintaining an imperfect, deteriorating sensor and the safety‐critical system it monitors. The sensor's costless observations of the binary state of the system become less informative over time. A costly full inspection may be conducted to perfect...

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Bibliographic Details
Published inNaval research logistics Vol. 64; no. 5; pp. 399 - 417
Main Authors van Oosterom, Chiel, Maillart, Lisa M., Kharoufeh, Jeffrey P.
Format Journal Article
LanguageEnglish
Published New York Wiley Subscription Services, Inc 01.08.2017
Subjects
Costs
Inspection
Logistics
maintenance optimization
Markov analysis
Markov chains
Optimization
partially observable Markov decision process
Policies
Safety critical
Scheduling
sensor deterioration
Sensors
threshold policy
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Summary:We consider the integrated problem of optimally maintaining an imperfect, deteriorating sensor and the safety‐critical system it monitors. The sensor's costless observations of the binary state of the system become less informative over time. A costly full inspection may be conducted to perfectly discern the state of the system, after which the system is replaced if it is in the out‐of‐control state. In addition, a full inspection provides the opportunity to replace the sensor. We formulate the problem of adaptively scheduling full inspections and sensor replacements using a partially observable Markov decision process (POMDP) model. The objective is to minimize the total expected discounted costs associated with system operation, full inspection, system replacement, and sensor replacement. We show that the optimal policy has a threshold structure and demonstrate the value of coordinating system and sensor maintenance via numerical examples. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 399–417, 2017
ISSN:0894-069X
1520-6750
DOI:10.1002/nav.21763