In this paper, we consider the generalized inverted exponential distribution (GIED) as a life model to develop various acceptance sampling schemes for truncated life tests. We develop the repetitive acceptance sampling plan (RASP) by attributes based on truncated life test and determine the design parameters satisfying both the producer's risk (α) and consumer's risk (β) simultaneously for the specified quality levels in terms of true median life ratio to the specified life. We are also to minimize average sample number where the constraints are related to the lot acceptance probabilities at the acceptance and limiting quality levels. The performance of the proposed plan is compared with single acceptance sampling plan under the GIED. The proposed sampling plan reduces the average sample number as compare to the single acceptance sampling plan. Tables are obtained for various values of shape parameter and the results are discussed. Also, discussion about the effect of misspecification of shape parameter is explained.
In this paper, we consider a skew-generalized inverse Weibull probability distribution for repetitive acceptance sampling plans based on truncated life tests with known shape parameter. The design parameters such as sample size and acceptance numbers are evaluated by considering the median life time of the test units as a quality parameter under the constraint of two risks, known as the producer's risk and consumer's risk at a certain level. We explained the proposed method with the help of tables for different values of the known parameter. The skew-generalized inverse Weibull distribution fits better a real data set considered than the generalized inverse Weibull distribution. Comparison between the proposed plan and the single sampling plan is presented.
In this paper, the multiple deferred state repetitive acceptance sampling plan (MDSRASP) is proposed and designed for assuring a 50th percentile lifetime of the products under odds exponential log-logistic (OELL) distribution. The optimum parameters of the proposed plan are determined based on satisfying various blends of producer’s risk and consumer’s risk for definite quality levels in light of 50th percentile. The aim is to minimize the average sample number (ASN), though the constraints are connected with the lot acceptance probability at the acceptable and limiting quality levels. The efficiency of the proposed plan is compared with single sampling plan using ASN. Tables are formed to present the outcomes and comparison of the proposed plan with existing sampling plan is done in terms of ASN.
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