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Designing Bayesian Two-Sided Group Chain Sampling Plan for Gamma Prior Distribution

Computer Systems Science & Engineering 2023年第2期44卷 1069-1079页

作者： Waqar Hafeez nazrina aziz School of Quantitative of Sciences Universiti Utara MalaysiaSintok06010Malaysia Institute of Strategic Industrial Decision Modelling(ISIDM) Universiti Utara MalaysiaSintok06010Malaysia

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 *** an alternative to traditional sampling plans,it is possible to use Baye-sian approaches using previous knowledge on process *** study pre-sents a Bayesian two-sided group chain sampling plan(BTSGChSP)by using various combinations of design *** BTSGChSP,inspection is based on preceding as well as succeeding *** function is used to derive the probability of lot acceptance based on defective and non-defective *** distribution is considered as a suitable prior for Poisson *** quality regions are found,namely:(i)quality decision region(QDR),(ii)probabil-istic quality region(PQR),(iii)limiting quality region(LQR)and(iv)indifference quality region(IQR).Producer’s risk and consumer’s risk are considered to esti-mate the quality regions,where acceptable quality level(AQL)is associated with producer’s risk and limiting quality level(LQL)is associated with consumer’s ***,AQL and LQL are used in the selection of design parameters for *** values based on all possible combinations of design parameters for BTSGChSP are presented and inﬂection points’values are ***ﬁnding exposes that BTSGChSP is a better substitute for the existing plan for industrial practitioners.

关键词： Bayesian acceptance sampling poisson distribution gamma distribution producer’s risk consumer’s risk

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Bayesian Group Chain Sampling Plan for Poisson Distribution with Gamma Prior

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Computers, Materials & Continua 2022年第2期70卷 3891-3902页

作者： Waqar Hafeez nazrina aziz Zakiyah Zain Nur Azulia Kamarudin School of Quantitative Sciences Universiti Utara MalaysiaUUM Sintok06010KedahMalaysia Institute of Strategic Industrial Decision Modelling(ISIDM) Universiti Utara MalaysiaUUM Sintok06010KedahMalaysia

Acceptance sampling is a statistical quality control technique that consists of procedures for sentencing one or more incoming lots of finished *** or rejection is based on the inspection of sampled products drawn randomly from the *** theory of previous acceptance sampling was built upon the assumption that the process from which the lots are produced is stable and the process fraction nonconforming is a *** variability is inevitable due to random fluctuations,which may inadvertently lead to quality *** an alternative to traditional sampling plans,Bayesian approach can be used by considering prior information of the *** different combinations of design parameters,this study introduces a Bayesian group chain sampling plan(BGChSP).For the first time in group chain sampling plan,the probability of lot acceptance is derived by using Poisson distribution to estimate an average number of *** distribution is used as a prior distribution with Poisson *** into account both consumer’s and producer’s risks,this research considers two quality regions namely,probabilistic quality region(PQR)and indifference quality region(IQR).By minimizing consumer’s and producer’s risks,BGChSP can be used to minimize the average number of defective products in industry.

关键词： Bayesian acceptance sampling gamma produce risk consumer risk

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Designing Bayesian New Group Chain Sampling Plan For Quality Regions

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Computers, Materials & Continua 2022年第2期70卷 4185-4198页

作者： Waqar Hafeez nazrina aziz Zakiyah Zain Nur Azulia Kamarudin School of Quantitative of Sciences Universiti Utara MalaysiaSintok06010Malaysia Institute of Strategic Industrial Decision Modelling(ISIDM) Universiti Utara MalaysiaSintok06010Malaysia

Acceptance sampling is a well-established statistical technique in quality *** sampling is used to decide,acceptance or rejection of a lot based on the inspection of its random *** concur that the Bayesian approach is the best approach to make a correct decision,when historical knowledge is *** paper suggests a Bayesian new group chain sampling plan(BNGChSP)to estimate average probability of *** distribution function is used to differentiate between defective and non-defective *** distribution is considered as a suitable prior *** is completed for the estimation of the average proportion of *** study includes four quality regions namely:(i)probabilistic quality region(PQR),(ii)quality decision region(QDR),(iii)limiting quality region(LQR),and(iv)indifference quality region(IQR).The estimated values for the BNGChSPare tabulated and the inflection point values are derived,based on different combinations of design parameters including both consumer’s and producer’s *** comparison with the existing plan,the operating characteristic curves expose that BNGChSP is a better substitute for industrial practitioners.

关键词： Binomial beta distribution consumer’s risk producer’s risk quality region

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