Designing of Optimal Required Sample Sizes for Double Acceptance Sampling Plans under the Zero-Inflated Defective Data
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Creator Wimonmas Bamrungsetthapong
Title Designing of Optimal Required Sample Sizes for Double Acceptance Sampling Plans under the Zero-Inflated Defective Data
Contributor Pramote Charongrattanasakul
Publisher King Mongkut's Institute of Technology Ladkrabang
Publication Year 2564
Journal Title Current Applied Science and Technology
Journal Vol. 21
Journal No. 2
Page no. 227-239
Keyword double acceptance sampling plan, zero-inflated poisson distribution, probability of extra zeros, probability of acceptance sampling plan, Genetic Algorithm, multi-objective optimization
URL Website https://www.tci-thaijo.org/index.php/cast
Website title https://www.tci-thaijo.org/index.php
ISSN 2586-9396
Abstract This research proposes an optimal double acceptance sampling plan (DSP) for manufacturing that is affected by zero-inflated data. Suppose that the number of defective items for sample inspection is considered to be under Zero-inflated Poisson (ZIP) distribution. A multi-objective optimization using Genetic Algorithm is applied to calculate the optimal parameters (?n_1,n_2,c?_1,c_2 )^* of the proposed DSP, which is concerned with maximizing the probability of acceptance sampling plan(P_a ) and minimizing the total cost of inspection(TC) and the average number of samples(ASN)simultaneously. The optimal solution was focused on the design of the required sample sizes (n_1,n_2 ) based on three different scenarios. The results showed that the first sample and the second sample should be equal (n_1=n_2 ). Moreover, it was found that the probability of extra zeros (?) under the ZIP distribution affects the required sample sizes and the performance of the proposed DSP. Illustrations for selecting the optimal parameters of the proposed DSP are also provided. Real data with excess zero is used to illustrate the application of the proposed DSP.
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