000077070 001__ 77070
000077070 005__ 20231215090948.0
000077070 0247_ $$2doi$$a10.1016/j.ejor.2018.01.042
000077070 0248_ $$2sideral$$a105926
000077070 037__ $$aART-2018-105926
000077070 041__ $$aeng
000077070 100__ $$0(orcid)0000-0002-8035-5762$$aBerrade, M.D.$$uUniversidad de Zaragoza
000077070 245__ $$aConditional inspection and maintenance of a system with two interacting components
000077070 260__ $$c2018
000077070 5060_ $$aAccess copy available to the general public$$fUnrestricted
000077070 5203_ $$aIn this paper we consider the inspection and maintenance of a two-component system with stochastic dependence. A failure of component 1 may induce the defective state in component 2 which in turn leads to its failure. A failure of component 1 and a defect in component 2 are detected by inspection. Our model considers a conditional inspection policy: when component 1 is found to have failed, inspection of component 2 is triggered. This opportunistic inspection policy is a natural one to use given this stochastic dependence between the components. The long-run cost per unit time (cost-rate) of the conditional inspection policy is determined generally. A real system that cuts rebar mesh motivates the model development. The numerical examples reveal that when the ratio of the cost of corrective system replacement, that is on failure, to the cost of preventive system replacement is large there exists a finite optimum policy in most cases. Moreover, for the studied system wherein inspections of component 2 are expensive relative to those of component 1, having a reliable indicator of the defective state in component 2 is a good strategy to avoid costly failures of component 2, particularly when its time to failure is short.
000077070 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/MTM2015-63978-P
000077070 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000077070 590__ $$a3.806$$b2018
000077070 591__ $$aOPERATIONS RESEARCH & MANAGEMENT SCIENCE$$b13 / 84 = 0.155$$c2018$$dQ1$$eT1
000077070 592__ $$a2.205$$b2018
000077070 593__ $$aComputer Science (miscellaneous)$$c2018$$dQ1
000077070 593__ $$aModeling and Simulation$$c2018$$dQ1
000077070 593__ $$aManagement Science and Operations Research$$c2018$$dQ1
000077070 593__ $$aInformation Systems and Management$$c2018$$dQ1
000077070 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000077070 700__ $$aScarf, P.A.
000077070 700__ $$aCavalcante, C.A.V.
000077070 7102_ $$12007$$2265$$aUniversidad de Zaragoza$$bDpto. Métodos Estadísticos$$cÁrea Estadís. Investig. Opera.
000077070 773__ $$g268, 2 (2018), 533-544$$pEur. J. oper. res.$$tEuropean Journal of Operational Research$$x0377-2217
000077070 8564_ $$s1730450$$uhttps://zaguan.unizar.es/record/77070/files/texto_completo.pdf$$yPostprint
000077070 8564_ $$s62766$$uhttps://zaguan.unizar.es/record/77070/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000077070 909CO $$ooai:zaguan.unizar.es:77070$$particulos$$pdriver
000077070 951__ $$a2023-12-15-08:57:32
000077070 980__ $$aARTICLE