NDLI: Steady-state availability analysis of repairable mechanical systems with opportunistic maintenance by using Semi-Markov process

Content Provider	Springer Nature Link
Author	Kumar, Girish Jain, Vipul Gandhi, O. P.
Copyright Year	2014
Abstract	In this paper, a methodology for analysis of steady-state availability of repairable mechanical systems with opportunistic maintenance is presented, which is based on Semi-Markov process (SMP). SMP models; combining corrective maintenance with the opportunistic maintenance are proposed. The opportunistic maintenance is based on the condition of the component. An analytical framework is suggested for the solution of the SMP models. System steady-state availability is evaluated and compared in three cases of corrective maintenance; perfect, minimal and imperfect repairs; with and without opportunistic maintenance. The benefits of opportunistic maintenance are quantified in terms of the increased system availability. The proposed methodology is useful for maintenance engineers in implementing appropriate maintenance policy. The methodology is also helpful to designers to target a desired value of the system availability for the type and level of repair. The proposed methodology is demonstrated for a system, consisting of a centrifugal pump and the transmission unit in a series configuration.
Starting Page	664
Ending Page	678
Page Count	15
File Format	PDF
ISSN	09756809
Journal	International Journal of System Assurance Engineering and Management
Volume Number	5
Issue Number	4
e-ISSN	09764348
Language	English
Publisher	Springer India
Publisher Date	2014-02-14
Publisher Place	India
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Opportunistic maintenance Semi-Markov process (SMP) System availability Degraded states Repairable mechanical systems Quality Control, Reliability, Safety and Risk Engineering Economics, Organization, Logistics, Marketing
Content Type	Text
Resource Type	Article
Subject	Strategy and Management Safety, Risk, Reliability and Quality

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