A bivariate optimal replacement policy for a cold standby repairable system with preventive repair

A bivariate optimal replacement policy for a cold standby repairable system with preventive repair

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Article ID: iaor201110704
Volume: 218
Issue: 7
Start Page Number: 3158
End Page Number: 3165
Publication Date: Dec 2011
Journal: Applied Mathematics and Computation
Authors: ,
Keywords: combinatorial optimization, simulation, decision, statistics: distributions
Abstract:

In this paper, the repair–replacement problem for a deteriorating cold standby repairable system is investigated. The system consists of two dissimilar components, in which component 1 is the main component with use priority and component 2 is a supplementary component. In order to extend the working time and economize the running cost of the system, preventive repair for component 1 is performed every time interval T, and the preventive repair is ‘as good as new’. As a supplementary component, component 2 is only used at the time that component 1 is under preventive repair or failure repair. Assumed that the failure repair of component 1 follows geometric process repair while the repair of component 2 is ‘as good as new’. A bivariate repair–replacement policy (T, N) is adopted for the system, where T is the interval length between preventive repairs, and N is the number of failures of component 1. The aim is to determine an optimal bivariate policy (T, N)* such that the average cost rate of the system is minimized. The explicit expression of the average cost rate is derived and the corresponding optimal bivariate policy can be determined analytically or numerically. Finally, a Gamma distributed example is given to illustrate the theoretical results for the proposed model.

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