文章基本信息

标题：A Two-stage Group Sampling Plan Based on Truncated Life Tests for an Odd Generalized Exponential Log-logistic Distribution
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作者：D. C. U. Sivakumar ; G. Srinivasa Rao ; K. Rosaiah 等
期刊名称：Current Journal of Applied Science and Technology
印刷版ISSN：2457-1024
出版年度：2019
卷号：35
期号：4
页码：1-14
DOI：10.9734/cjast/2019/v35i430191
语种：English
出版社：Sciencedomain International
摘要：In this article, a time truncated life test based on two-stage group acceptance sampling plan is proposed for lifetime of an item follows odd generalized exponential log-logistic distribution (OGELLD). The ability about the lot acceptance can be made in the first or second stage according to the number of failures from each group. The optimal parameters for the proposed plan are determined such that both producer’s as well as consumer’s risks are contented simultaneously for the specified unreliability when group size and test duration are specified. The efficiency of the proposed sampling plan is evaluated in terms of average sample number with the existing sampling plan. The results are explained with the help of industrial example. Using exploratory data analysis and then goodness-of-fit, we show a rough indication of the goodness of fit for our model by plotting the superimposed for the data shows that the OGELLD is a good fit and also it is emphasized with Q-Q plot, displayed in Fig. 1. We observed from the tables / results that the number of groups required decrease as the group size increases from and also the ASN increases marginally, sample size decreases as the group size increases, which indicates that a larger group size may be more economical and it reduces the experimental time and cost. We proposed two-stage group acceptance sampling plan, since it performs much better in terms of the average sample number (ASN) and the operating characteristics than in single-stage group acceptance sampling plan. The advantage of two stage group sampling plan is that it reduces the average sample number (ASN) as compared to the GASP.
关键词：Odd Generalized Exponential Log-logistic Distribution (OGELLD);average sample number;producer’s and consumer’s risk