View : 875 Download: 0

Full metadata record

DC Field Value Language
dc.contributor.author차지환*
dc.date.accessioned2021-02-25T16:31:54Z-
dc.date.available2021-02-25T16:31:54Z-
dc.date.issued2021*
dc.identifier.issn0266-4763*
dc.identifier.issn1360-0532*
dc.identifier.otherOAK-28851*
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/257186-
dc.description.abstractUntil now, in the literature, a variety of acceptance reliability sampling plans have been developed based on different life test plans. In most of the reliability sampling plans, the decision procedures to accept or reject the corresponding lot are developed based on the lifetimes of the items observed on tests, or the number of failures observed during a pre-specified testing time. However, frequently, the items are subject to degradation phenomena and, in these cases, the observed degradation level of the item can be used as a decision statistic. In this paper, we develop a variables acceptance sampling plan based on the information on the degradation process of the items, assuming that the degradation process follows the inverse Gaussian process. It is shown that the developed sampling plan improves the reliability performance of the items conditional on the acceptance in the test and that the lifetimes of items after the reliability sampling test are stochastically larger than those before the test. A study comparing the proposed degradation-based sampling plan with the conventional sampling plan which is based on a life test is also performed.*
dc.languageEnglish*
dc.publisherTAYLOR &amp*
dc.publisherFRANCIS LTD*
dc.subjectVariables sampling plan*
dc.subjectdegradation test*
dc.subjectinverse Gaussian process*
dc.subjectmixture distribution*
dc.subjectstochastic ordering*
dc.titleVariables acceptance reliability sampling plan for items subject to inverse Gaussian degradation process*
dc.typeArticle*
dc.relation.issue3*
dc.relation.volume48*
dc.relation.indexSCIE*
dc.relation.indexSCOPUS*
dc.relation.startpage393*
dc.relation.lastpage409*
dc.relation.journaltitleJOURNAL OF APPLIED STATISTICS*
dc.identifier.doi10.1080/02664763.2020.1723505*
dc.identifier.wosidWOS:000513275600001*
dc.identifier.scopusid2-s2.0-85079218229*
dc.author.googleCha, Ji Hwan*
dc.author.googleBadia, F. G.*
dc.contributor.scopusid차지환(7202455739)*
dc.date.modifydate20231123095848*
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

BROWSE