축차 샘플링을 기반으로 한 one-shot devices의 신뢰성 입증 시험
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 전종선 | - |
dc.contributor.author | 안선응 | - |
dc.date.accessioned | 2021-06-22T15:45:21Z | - |
dc.date.available | 2021-06-22T15:45:21Z | - |
dc.date.issued | 2016-11 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/12230 | - |
dc.description.abstract | This paper describes the Bayesian approach for reliability demonstration test based on the sequential samples from the one-shot devices. The Bayesian approach involves the technical method about how to combine the prior distribution and the likelihood function to produce the posterior distribution. In this paper, the binomial distribution is adopted as a likelihood function for the one-shot devices. The relationship between the beta-binomial distribution and the Polya’s urn model is explained and is used to make a decision about whether to accept or reject the population of the one-shot devices by one by one then in terms of the faulty goods. A numerical example is also given. | - |
dc.format.extent | 5 | - |
dc.language | 한국어 | - |
dc.language.iso | KOR | - |
dc.publisher | 한국산업경영시스템학회 | - |
dc.title | 축차 샘플링을 기반으로 한 one-shot devices의 신뢰성 입증 시험 | - |
dc.title.alternative | Reliability Demonstration Test for the One-Shot Devices Based on the Sequential Sampling | - |
dc.type | Article | - |
dc.publisher.location | 대한민국 | - |
dc.identifier.bibliographicCitation | 한국산업경영시스템학회 2016년 추계학술대회 논문집, pp 80 - 84 | - |
dc.citation.title | 한국산업경영시스템학회 2016년 추계학술대회 논문집 | - |
dc.citation.startPage | 80 | - |
dc.citation.endPage | 84 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | domestic | - |
dc.subject.keywordAuthor | Bayesian approach | - |
dc.subject.keywordAuthor | sequential sampling | - |
dc.subject.keywordAuthor | beta-binomial distribution | - |
dc.subject.keywordAuthor | one-shot devices | - |
dc.subject.keywordAuthor | reliability demonstration test | - |
dc.subject.keywordAuthor | Polya’s urn model | - |
dc.identifier.url | https://db.koreascholar.com/Article/Detail/353380 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.