000069942 001__ 69942 000069942 005__ 20190709135509.0 000069942 0247_ $$2doi$$a10.1016/j.ress.2017.04.006 000069942 0248_ $$2sideral$$a101874 000069942 037__ $$aART-2017-101874 000069942 041__ $$aeng 000069942 100__ $$0(orcid)0000-0002-8035-5762$$aBerrade, M. D.$$uUniversidad de Zaragoza 000069942 245__ $$aA study of postponed replacement in a delay time model 000069942 260__ $$c2017 000069942 5060_ $$aAccess copy available to the general public$$fUnrestricted 000069942 5203_ $$aWe develop a delay time model for a one component system with postponed replacement to analyze situations in which maintenance might not be executed immediately upon discovery of a defect in the system. Reasons for postponement are numerous: to avoid production disruption or unnecessary or ineffective replacement; to prepare for replacement; to extend component life; to wait for an opportunity. This paper explores conditions that make postponement cost-effective. We are interested in modelling the reality in which a maintainer either prioritizes functional continuity or is not confident of the inspection test indicating a defective state. In some cases more frequent inspection and a longer time limit for postponement are recommended to take advantage of maintenance opportunities, characterized by their low cost, arising after a positive inspection. However, when the cost of failure increases, a significant reduction in the time limit of postponement interval is observed. The examples reveal that both the time to defect arrival and delay time have a significant effect upon the cost-effectiveness of maintenance at the limit of postponement. Also, more simply, we find that opportunities must occur frequently enough and inspection should be a high quality procedure to risk postponement. 000069942 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/MTM2015-63978-P 000069942 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/ 000069942 590__ $$a4.139$$b2017 000069942 591__ $$aOPERATIONS RESEARCH & MANAGEMENT SCIENCE$$b6 / 83 = 0.072$$c2017$$dQ1$$eT1 000069942 591__ $$aENGINEERING, INDUSTRIAL$$b5 / 47 = 0.106$$c2017$$dQ1$$eT1 000069942 592__ $$a1.665$$b2017 000069942 593__ $$aApplied Mathematics$$c2017$$dQ1 000069942 593__ $$aSafety, Risk, Reliability and Quality$$c2017$$dQ1 000069942 593__ $$aIndustrial and Manufacturing Engineering$$c2017$$dQ1 000069942 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion 000069942 700__ $$aScarf, P. A. 000069942 700__ $$aCavalcante, C.A.V. 000069942 7102_ $$12007$$2265$$aUniversidad de Zaragoza$$bDpto. Métodos Estadísticos$$cÁrea Estadís. Investig. Opera. 000069942 773__ $$g168 (2017), 70-79$$pReliab. eng. syst. saf.$$tRELIABILITY ENGINEERING & SYSTEM SAFETY$$x0951-8320 000069942 8564_ $$s471438$$uhttps://zaguan.unizar.es/record/69942/files/texto_completo.pdf$$yPostprint 000069942 8564_ $$s69359$$uhttps://zaguan.unizar.es/record/69942/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint 000069942 909CO $$ooai:zaguan.unizar.es:69942$$particulos$$pdriver 000069942 951__ $$a2019-07-09-11:50:38 000069942 980__ $$aARTICLE