Paper Info
Title
Designing Bayesian Two-Sided Group Chain Sampling Plan for Gamma Prior Distribution
Abstract
Acceptance sampling is used to decide either the whole lot will be accepted or rejected, based on inspection of randomly sampled items from the same lot. As an alternative to traditional sampling plans, it is possible to use Bayesian approaches using previous knowledge on process variation. This study presents a Bayesian two-sided group chain sampling plan (BTSGChSP) by using various combinations of design parameters. In BTSGChSP, inspection is based on preceding as well as succeeding lots. Poisson function is used to derive the probability of lot acceptance based on defective and non-defective products. Gamma distribution is considered as a suitable prior for Poisson distribution. Four quality regions are found, namely: (i) quality decision region (QDR), (ii) probabilistic quality region (PQR), (iii) limiting quality region (LQR) and (iv) indifference quality region (IQR). Producer's risk and consumer's risk are considered to estimate the quality regions, where acceptable quality level (AQL) is associated with producer's risk and limiting quality level (LQL) is associated with consumer's risk. Moreover, AQL and LQL are used in the selection of design parameters for BTSGChSP. The values based on all possible combinations of design parameters for BTSGChSP are presented and inflection points' values are found. The finding exposes that BTSGChSP is a better substitute for the existing plan for industrial practitioners.
Year
DOI
Venue
2023
10.32604/csse.2023.022047
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
Keywords
DocType
Volume
Bayesian acceptance sampling, poisson distribution, gamma distribution, producer's risk, consumer's risk
Journal
44
Issue
ISSN
Citations 
2
0267-6192
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Waqar Hafeez100.34
Nazrina Aziz200.34