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Bayesian two-sided group chain sampling plan for beta binomial distribution under quality regions

Waqar Hafeez (School of Quantitative Sciences, Universiti Utara Malaysia, Sintok, Malaysia)
Nazrina Aziz (School of Quantitative Sciences, Universiti Utara Malaysia, Sintok, Malaysia) (Institute of Strategic Industrial Decision Modelling (ISIDM), Universiti Utara Malaysia, Sintok, Malaysia)

International Journal of Quality & Reliability Management

ISSN: 0265-671X

Article publication date: 12 October 2021

Issue publication date: 1 November 2022

120

Abstract

Purpose

This paper introduces a Bayesian two-sided group chain sampling plan (BT-SGChSP) by using binomial distribution to estimate the average proportion of defectives. In this Bayesian approach, beta distribution is used as a suitable prior of binomial distribution. The proposed plan considers both consumer's and producer's risks. Currently, group chain sampling plans only consider the consumer's risk and do not account for the producer's risk. All existing plans are used to estimate only a single point, but this plan gives a quality region for the pre-specified values of different design parameters. In other words, instead of point wise description for the designing of sampling plan based on a range of quality by involving a novel approach called quality region.

Design/methodology/approach

The methodology is based on five phases, which are (1) operating procedure, (2) derivation of the probability of lot acceptance, (3) constructing plans for given acceptable quality level (AQL) and limiting quality level (LQL), (4) construction of quality intervals for BT-SGChSP and (5) selection of the sampling plans.

Findings

The findings show that the operating characteristic (OC) curve of BT-SGChSP is more ideal than the existing Bayesian group chain sampling plan because the quality regions for BT-SGChSP give less proportion of defectives for same consumer's and producer's risks.

Research limitations/implications

There are four limitations in this study: first is the use of binomial distribution when deriving the probability of lot acceptance. Alternatively, it can be derived by using distributions such as Poisson, weighted Poisson and weighted binomial. The second is that beta distribution is used as prior distribution. Otherwise, different prior distributions can be used like: Rayleigh, exponential and generalized exponential. The third is that we adopt mean as a quality parameter, whereas median and other quintiles can be used. Forth, this paper considers probabilistic quality region (PQR) and indifference quality region (IQR).

Practical implications

The proposed plan is an alternative of traditional group chain sampling plans that are based on only current lot information. This plan considers current lot information with preceding and succeeding lot and also considers prior information of the product.

Originality/value

This paper first time uses a tight (three acceptance criteria) and introduces a BT-SGChSP to find quality regions for both producer's and consumer's risk.

Keywords

Acknowledgements

Funding: This research was supported by the Ministry of Higher Education (MoHE) through Fundamental Research Grant Scheme (FRGS/1/2020/STG06/UUM/02/2).

Citation

Hafeez, W. and Aziz, N. (2022), "Bayesian two-sided group chain sampling plan for beta binomial distribution under quality regions", International Journal of Quality & Reliability Management, Vol. 39 No. 10, pp. 2424-2437. https://doi.org/10.1108/IJQRM-10-2020-0356

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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