Bayesian two-sided complete group chain sampling plan for poisson distribution with gamma prior

For statistical quality assurance based on the inspection of a random sample, acceptance sampling plan help to decide whether the lot should be accepted or rejected. Most traditional plans only focus on minimizing the consumer’s risk, but producer’s risk also should not be ignored in acceptance samp...

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Main Authors: Waqar Hafeez, Nazrina Aziz
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2022
Online Access:http://journalarticle.ukm.my/19763/
http://journalarticle.ukm.my/19763/1/26.pdf
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author Waqar Hafeez,
Nazrina Aziz,
author_facet Waqar Hafeez,
Nazrina Aziz,
author_sort Waqar Hafeez,
building UKM Institutional Repository
collection Online Access
description For statistical quality assurance based on the inspection of a random sample, acceptance sampling plan help to decide whether the lot should be accepted or rejected. Most traditional plans only focus on minimizing the consumer’s risk, but producer’s risk also should not be ignored in acceptance sampling plan. Therefore, this study focuses on reducing both producer’s and consumer’s risks through the quality region. This study proposes a Bayesian two-sided complete group chain sampling plan (BTSCGChSP) for the average probability of lot acceptance. The Poisson distribution with gamma as prior distribution is used to derive the average probability of lot acceptance. Next, R programing language is used to obtain the average number of defectives according to average probability of acceptance and pre-specified values of design parameters. For selected design parameters in BTSCGChSP, the acceptable quality level (AQL) associated with producer’s risk and limiting quality level (LQL) associated with consumer’s risk are considered to estimate quality regions. In this paper, four quality regions are measured: (i) probabilistic quality region (PQR), (ii) quality decision region (QDR), (iii) limiting quality region (LQR) and (iv) indifference quality region (IQR). Operating characteristic curves (OC) are used for performance comparison with existing Bayesian group chain sampling plan (BGChSP) for the same probability of lot acceptance and other design parameter values. Findings validate that BTSCGChSP provides more ideal OC curve than BGChSP for the same probability of acceptance. For quality regions with the same values of consumer’s and producer’s risks, then the BTSCGChSP region will contain fewer defectives than in the BGChSP region. Hence, the proposed plan is a better substitute for existing BGChSP.
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spelling oai:generic.eprints.org:197632022-09-19T07:10:39Z http://journalarticle.ukm.my/19763/ Bayesian two-sided complete group chain sampling plan for poisson distribution with gamma prior Waqar Hafeez, Nazrina Aziz, For statistical quality assurance based on the inspection of a random sample, acceptance sampling plan help to decide whether the lot should be accepted or rejected. Most traditional plans only focus on minimizing the consumer’s risk, but producer’s risk also should not be ignored in acceptance sampling plan. Therefore, this study focuses on reducing both producer’s and consumer’s risks through the quality region. This study proposes a Bayesian two-sided complete group chain sampling plan (BTSCGChSP) for the average probability of lot acceptance. The Poisson distribution with gamma as prior distribution is used to derive the average probability of lot acceptance. Next, R programing language is used to obtain the average number of defectives according to average probability of acceptance and pre-specified values of design parameters. For selected design parameters in BTSCGChSP, the acceptable quality level (AQL) associated with producer’s risk and limiting quality level (LQL) associated with consumer’s risk are considered to estimate quality regions. In this paper, four quality regions are measured: (i) probabilistic quality region (PQR), (ii) quality decision region (QDR), (iii) limiting quality region (LQR) and (iv) indifference quality region (IQR). Operating characteristic curves (OC) are used for performance comparison with existing Bayesian group chain sampling plan (BGChSP) for the same probability of lot acceptance and other design parameter values. Findings validate that BTSCGChSP provides more ideal OC curve than BGChSP for the same probability of acceptance. For quality regions with the same values of consumer’s and producer’s risks, then the BTSCGChSP region will contain fewer defectives than in the BGChSP region. Hence, the proposed plan is a better substitute for existing BGChSP. Penerbit Universiti Kebangsaan Malaysia 2022-06 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/19763/1/26.pdf Waqar Hafeez, and Nazrina Aziz, (2022) Bayesian two-sided complete group chain sampling plan for poisson distribution with gamma prior. Sains Malaysiana, 51 (6). pp. 1915-1926. ISSN 0126-6039 https://www.ukm.my/jsm/malay_journals/jilid51bil6_2022/KandunganJilid51Bil6_2022.html
spellingShingle Waqar Hafeez,
Nazrina Aziz,
Bayesian two-sided complete group chain sampling plan for poisson distribution with gamma prior
title Bayesian two-sided complete group chain sampling plan for poisson distribution with gamma prior
title_full Bayesian two-sided complete group chain sampling plan for poisson distribution with gamma prior
title_fullStr Bayesian two-sided complete group chain sampling plan for poisson distribution with gamma prior
title_full_unstemmed Bayesian two-sided complete group chain sampling plan for poisson distribution with gamma prior
title_short Bayesian two-sided complete group chain sampling plan for poisson distribution with gamma prior
title_sort bayesian two-sided complete group chain sampling plan for poisson distribution with gamma prior
url http://journalarticle.ukm.my/19763/
http://journalarticle.ukm.my/19763/
http://journalarticle.ukm.my/19763/1/26.pdf