Reliability parameter estimation of repairable systems with imperfect maintenance, repair and overhaul
Purpose: Industries generally require good maintenance, repair and overhaul (MRO) facilities. Maintenance activities at MRO cover the normal scheduled check-ups known as scheduled preventive maintenance (SPM) whereas an overhaul reviews and rejuvenates the complete system at a scheduled time. The literature is reasonably stocked with reliability modelling of repairable systems considering both the corrective maintenance (CM) and SPM as imperfect. However, in all these situations the overhaul is modelled as perfect repair. Thus, the purpose of this research paper is to develop a mathematical model for the estimation of reliability parameters considering the complete MRO as imperfect. Design/methodology/approach: The paper proposes arithmetic reduction of age (Kijima I) based virtual age model to estimate reliability parameters by considering the complete MRO as imperfect and provides the likelihood and log-likelihood functions for parameter estimation of the proposed model and also presents the various extensions of the proposed model. Findings: For analysis, two real-time data sets of two components, i.e. turbostarter and plunger pump are considered. The analysis mainly focuses on intensity function and availability of components. The availability analysis of the components directly affects the cost analysis. It is very important to analyze the realistic trend of availability, and the comparative analysis shows that the assumption of perfect overhaul overestimates and minimal overhaul underestimates the performance of the components whereas assumption of imperfect overhaul portraits more sensible deteriorating and availability trend of the components. Originality/value: The proposed methodology in this paper is a novice and not available in the literature.
Year of publication: |
2020
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Authors: | Sharma, Garima ; Rai, Rajiv Nandan |
Published in: |
International Journal of Quality & Reliability Management. - Emerald, ISSN 0265-671X, ZDB-ID 1466792-7. - Vol. 38.2020, 4 (19.08.), p. 892-907
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Publisher: |
Emerald |
Saved in:
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