Acceptance Sampling Plans based on Percentiles of Exponentiated Inverse Kumaraswamy Distribution

M. R. Reddy, B. S. Rao, K. Rosaiah
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Abstract

Objectives: To prepare the percentile-based acceptance sampling plans for the Exponentiated Inverse Kumaraswamy Distribution (EIKD) at a specific truncation time to inspect the defective lots corresponding to the desired acceptance level. Methods: The failure probability value is estimated using the cumulative probability function F(.) at time ‘t’ which is converted in terms of the scale parameter σ as 100th percentile using quantile function. The minimum size of the sample, Operating Characteristic (OC) and the minimum ratios are calculated for a required levels of consumer’s as well as producer’s risk. Findings: The percentile-based sampling plans are obtained through the minimal size of the sample ‘n’ under a truncated life test with a target acceptance number c in a manner that the proportion of accepting a lot which is not good (consumer’s risk) would not be more than . These values are calculated at The function of probability of acceptance for variations in the quality of a lot (OC function) L(p) of the sample plan are evaluated for the acceptance values of c=1 and c=5. The minimum ratio values are calculated for the acceptability of the lot with producers’ risk of using the sampling plan. Novelty: The modernity of this study is the designing of the acceptance sampling plans to a non-normal data using an asymmetrical distribution that has all three shape parameters. Also, the monitor of the implementation and suitability of statistical quality control and process control aspects using Exponentiated Inverse Kumaraswamy Distribution when compared to other asymmetrical distributions which has at least one scale parameter. Keywords: Sampling plans, Consumer's risk, Operating characteristics function, Truncated life tests, Producer's risk
基于幂级数反库马拉斯瓦米分布百分位数的验收抽样计划
目标:为指数化反库马拉斯瓦米分布 (EIKD) 制定基于百分位数的验收抽样计划,在特定的截断时间检查与所需验收水平相对应的缺陷批次。方法:使用累积概率函数 F(.)估算时间 "t "处的故障概率值,并使用量化函数将其转换为规模参数 σ,即 100 百分位数。根据消费者和生产者的风险水平要求,计算出样本的最小规模、运行特征(OC)和最小比率。研究结果基于百分位数的抽样计划是在目标接受数 c 的截断寿命测试下,通过最小样本量 "n "获得的,其方式是接受不合格批次的比例(消费者风险)不超过 。 在接受值 c=1 和 c=5 时,对抽样计划中批次质量变化的接受概率函数(OC 函数)L(p) 进行了评估。计算出使用该抽样计划的批次可接受性与生产商风险的最小比率值。新颖性:本研究的新颖性在于利用具有所有三个形状参数的非对称分布,为非正态数据设计验收抽样计划。此外,与其他至少有一个尺度参数的非对称分布相比,使用指数化反库马拉斯瓦米分布对统计质量控制和过程控制方面的实施和适用性进行了监测。关键词抽样计划、消费者风险、运行特征函数、截断寿命试验、生产者风险
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