Optimization of the dependability and performance measures of a generic model for multi-state deteriorating systems under maintenance

V.P. Koutras, S. Malefaki and A.N. Platis

Reliability Engineering and System Safety, 2017, vol. 166, issue C, 73-86

Abstract: In this paper, a general model for multi-state deteriorating systems with condition based preventive maintenance is introduced and analyzed extensively. The system experiences various levels of deterioration and at each stage, an inspection is carried out at constant time intervals in order to identify what kind of preventive maintenance, the system should undergo. When the system fails, despite preventive maintenance, a repair procedure is carried out and the system is restored to its initial fully operational state. The proposed model incorporates also imperfect maintenance, either minimal or major, failed maintenance and sudden failures that may occur mostly due to external factors at any deterioration state as well. Moreover, the sojourn times are assumed to be generally distributed. The main dependability and performance measures of the proposed model are computed while the corresponding transient measures are estimated using Monte Carlo simulation. Our endmost aim is to distinguish inspection and consequently maintenance policies that optimize multi-state deteriorating system's dependability and/or performance. Additionally, multi-objective optimization problems are formulated and solve in order to distinguish preventive maintenance policies that optimize simultaneously both the dependability and performance measures.

Keywords: Multi-state systems; Condition-based maintenance; Semi-Markov process; Availability; Operational cost; Dependability and performance optimization (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:166:y:2017:i:c:p:73-86

DOI: 10.1016/j.ress.2017.01.002

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