Design of Multiple Deferred State Repetitive Group Sampling Plans for Life Tests based on Generalized Gamma Distribution

IF 1.3 4区 工程技术 Q4 ENGINEERING, INDUSTRIAL Quality Engineering Pub Date : 2022-09-07 DOI:10.1080/08982112.2022.2118063
K. Sathya Narayana Sharma
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引用次数: 1

Abstract

Abstract Reliability sampling plans is a procedure to determine the acceptance or non-acceptance of the lot(s) of finished products by performing tests on the sampled items. Lifetime of individual items is a quality characteristic that can be treated as a continuous random variable and can be modeled by an appropriate continuous probability distribution. In this article, Multiple Deferred State Repetitive Group Sampling (MDSRGS) Plans for life tests under hybrid censoring with a provision to draw a random sample and to admit a maximum of one failure in the sample is formulated assuming that the lifetime random variable follows a Generalized Gamma (GG) distribution. A methodical procedure for the selection of the plan parameters using mean life criterion with the desired discrimination protecting the interests of the producer and the consumer in terms of the acceptable mean life and unacceptable mean life is evolved.
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基于广义伽玛分布的多延迟状态重复组寿命试验抽样方案设计
摘要可靠性抽样计划是通过对抽样项目进行测试来确定批次成品的验收或不验收的程序。单个物品的寿命是一种质量特征,它可以看作是一个连续的随机变量,可以用一个适当的连续概率分布来建模。在本文中,假设寿命随机变量服从广义伽玛(GG)分布,制定了混合审查下的寿命试验计划,该计划规定抽取随机样本并允许样本中最多有一个失效。在可接受的平均寿命和不可接受的平均寿命方面,提出了一种选择计划参数的有系统的程序,以保护生产者和消费者的利益。
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来源期刊
Quality Engineering
Quality Engineering ENGINEERING, INDUSTRIAL-STATISTICS & PROBABILITY
CiteScore
3.90
自引率
10.00%
发文量
52
审稿时长
>12 weeks
期刊介绍: Quality Engineering aims to promote a rich exchange among the quality engineering community by publishing papers that describe new engineering methods ready for immediate industrial application or examples of techniques uniquely employed. You are invited to submit manuscripts and application experiences that explore: Experimental engineering design and analysis Measurement system analysis in engineering Engineering process modelling Product and process optimization in engineering Quality control and process monitoring in engineering Engineering regression Reliability in engineering Response surface methodology in engineering Robust engineering parameter design Six Sigma method enhancement in engineering Statistical engineering Engineering test and evaluation techniques.
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