An Economic Design of Rectifying Double Acceptance Sampling Plans via Maxima Nomination Sampling

Q3 Mathematics Stochastics and Quality Control Pub Date : 2017-12-01 DOI:10.1515/eqc-2017-0018
M. Razmkhah, B. Sadeghpour Gildeh, J. Ahmadi
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引用次数: 2

Abstract

Abstract In industry when a lot of items is sent for inspection, double acceptance sampling plans (DASP) are considered as a way to decide on acceptance or rejection of the lot. If the lot contains items with high sensitivity, then the measuring of quality characteristics is destructive or costly. So we are looking for a method to decide that it has high performance. Using the ranked set sampling (RSS) method will make it stricter and more accurate whether or not to accept a lot. Moreover, it is affordable and will not burden extra costs on the buyer or the producer. In this paper, by using a special type of RSS, with the name of maxima nomination sampling (MNS), we design a DASP with regards to the total loss function. The results indicate that the total loss function, which is acquired by the MNS method, has lower values than the one using the simple random sampling (SRS) method.
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用最大提名抽样校正双重接受抽样方案的经济设计
摘要在工业生产中,当大量的物品被送去检验时,双重验收抽样计划(DASP)被认为是决定接受或拒绝批次的一种方法。如果该批含有高灵敏度的项目,那么质量特性的测量是破坏性的或昂贵的。因此,我们正在寻找一种方法来确定它是否具有高性能。采用排序集抽样(RSS)的方法,可以使是否接受大量的数据更加严格和准确。此外,它是负担得起的,不会给买家或生产商带来额外的成本。本文利用一种特殊的RSS,称为最大提名抽样(MNS),设计了一个关于总损失函数的DASP。结果表明,MNS方法得到的总损失函数值比简单随机抽样(SRS)方法得到的总损失函数值要小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Stochastics and Quality Control
Stochastics and Quality Control Mathematics-Discrete Mathematics and Combinatorics
CiteScore
1.10
自引率
0.00%
发文量
12
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