Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 차지환 | * |
dc.date.accessioned | 2016-08-28T12:08:10Z | - |
dc.date.available | 2016-08-28T12:08:10Z | - |
dc.date.issued | 2011 | * |
dc.identifier.issn | 0377-2217 | * |
dc.identifier.other | OAK-7277 | * |
dc.identifier.uri | https://dspace.ewha.ac.kr/handle/2015.oak/221358 | - |
dc.description.abstract | Burn-in is a widely used engineering method of elimination of defective items before they are shipped to customers or put into field operation. Under the assumption that a population is described by the decreasing or bathtub-shaped failure rate functions, various optimal burn-in problems have been intensively studied in the literature. In this paper, we consider a new model and assume that a population is composed of stochastically ordered subpopulations described by their own performance quality measures. It turns out that this setting can justify burn-in even in situations when it is not justified in the framework of conventional approaches. For instance, it is shown that it can be reasonable to perform burn-in even when the failure rate function that describes the heterogeneous population of items increases and this is one of the main and important findings of our study. © 2010 Elsevier B.V. All rights reserved. | * |
dc.language | English | * |
dc.title | Burn-in and the performance quality measures in heterogeneous populations | * |
dc.type | Article | * |
dc.relation.issue | 2 | * |
dc.relation.volume | 210 | * |
dc.relation.index | SCIE | * |
dc.relation.index | SCOPUS | * |
dc.relation.startpage | 273 | * |
dc.relation.lastpage | 280 | * |
dc.relation.journaltitle | European Journal of Operational Research | * |
dc.identifier.doi | 10.1016/j.ejor.2010.09.019 | * |
dc.identifier.wosid | WOS:000286853300015 | * |
dc.identifier.scopusid | 2-s2.0-78650416758 | * |
dc.author.google | Cha J.H. | * |
dc.author.google | Finkelstein M. | * |
dc.contributor.scopusid | 차지환(7202455739) | * |
dc.date.modifydate | 20231123095848 | * |