A new policy for designing acceptance sampling plan based on Bayesian inference in the presence of inspection errors

Nezhad, Mohammad Saber Fallah; Saredorahi, Faeze Zahmatkesh

doi:10.1080/03610926.2017.1390130

Cited by 6 publications

(2 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fallahnezhad and Babadi [9] developed acceptance sampling plan in the presence of inspection error using the decision tree approach." "Following Moskowitz and Tang [4], Fallahnezhad and Saredorahi [10] proposed a Bayesian acceptance sampling plan on the basis of smallest proportion of a lot which should be inspected in the presence of inspection error. Gonzalez and Palomo [11] derived Bayesian acceptance sampling plans for the number of defect to minimize the expected total cost (ETC) of quality.…”

Section: Introductionmentioning

confidence: 99%

Robustness of Shape Parameter for Erlang and Weibull Bayesian Acceptance Sampling Plans

Bibi,

Ali,

Shah

2022

Scientia Iranica

View full text Add to dashboard Cite

This article assesses the robustness of shape parameter for Bayesian acceptance sampling plans assuming Erlang and Weibull distributions. In particular, the prior information on the parameter is combined assuming different loss functions to derive different sampling plans. The cost model for the group sampling plans is studied by satisfying the constraints of producer's and consumer's risks for the Weibull sampling. The single sampling plan is compared with the group sampling plan and the results suggest that the group sampling plan performs better than the single sampling in terms of cost. It is noticed that the shape parameters of Erlang and Weibull distributions are not robust as claimed in the literature. "

show abstract

Section: Introductionmentioning

confidence: 99%

Robustness of Shape Parameter for Erlang and Weibull Bayesian Acceptance Sampling Plans

Bibi,

Ali,

Shah

2022

Scientia Iranica

View full text Add to dashboard Cite

show abstract

“…Mahdy and Ahmed [15] provide acceptance sampling plans for generalized inverse Weibull, skew-generalized inverse Weibull, and compound inverse Rayleigh distributions under truncated lifetime experiment to decide about the acceptance or rejection of the submitted lots. Fallahnezhad and Saredorahi [16] use the Bayesian approach to develop a new acceptance sampling plan by examining the minimum proportion of the lot having inspection errors. Some recent contributions of developing acceptance sampling plans by using different methodologies, selecting different quality characteristics, and objective functions following different distributions, are also stated.…”

Section: Introductionmentioning

confidence: 99%

Acceptance sampling plan using new truncated Weibull-X family based on run lengths of conforming items

2020

View full text Add to dashboard Cite

In this paper, we develop two acceptance sampling plans where the lifetimes of the products follow Weibull Exponential and Weibull Lomax distributions both belonging to the new truncated Weibull-X family of distributions based on run lengths of the conforming items.The model parameters are estimated by using the maximum likelihood method contrary to the existing plans where authors have been selecting arbitrary values of the parameters. The efficiency of the proposed plan is established by comparing it with the existing plan based on the average number of inspected items. A real example of failure rates of a piece of electronic equipment operating in a specific mode is presented to illustrate the proposed plans for industrial use.

show abstract

Designing acceptance single sampling plans: An optimization‐based approach under generalized beta distribution

Facchinetti

Osmetti

Magagnoli

2022

Appl Stoch Models Bus & Ind

View full text Add to dashboard Cite

The availability of information that suppliers possess about the production process, as well as about the technical and economic consequences for customers, encourages the development and application of acceptance sampling plans that follow economic criteria, such as the Bayesian ones proposed in the literature. The combination of prior knowledge described by the prior distribution and empirical knowledge based on the sample leads to the decision to accept or reject the lot under inspection. The main purpose of this study was to derive acceptance sampling plans for attributes based on a prior generalized beta distribution following the economic criterion to minimize the expected total cost of quality. Specifically, a procedure is proposed to define the optimal sampling plan based on the technical characteristics of the production process and the costs inherent in the quality of the product. After the methodological aspects are described in detail, an extensive simulation study is reported that demonstrates how the optimal plan changes according to the main parameters, providing guidance for practitioners.

show abstract

A new policy for designing acceptance sampling plan based on Bayesian inference in the presence of inspection errors

Cited by 6 publications

References 28 publications

Robustness of Shape Parameter for Erlang and Weibull Bayesian Acceptance Sampling Plans

Robustness of Shape Parameter for Erlang and Weibull Bayesian Acceptance Sampling Plans

Acceptance sampling plan using new truncated Weibull-X family based on run lengths of conforming items

Designing acceptance single sampling plans: An optimization‐based approach under generalized beta distribution

Contact Info

Product

Resources

About