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Growing Science » International Journal of Industrial Engineering Computations » Optimization of Bayesian repetitive group sampling plan for quality determination in Pharmaceutical products and related materials

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International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 13 Issue 1 pp. 31-42 , 2022

Optimization of Bayesian repetitive group sampling plan for quality determination in Pharmaceutical products and related materials Pages 31-42 Right click to download the paper Download PDF

Authors: Velappan Kaviyarasu, Palanisamy Sivakumar

DOI: 10.5267/j.ijiec.2021.9.001

Keywords: Repetitive Group Sampling plan, Bayesian Approach, Zero Inflated Poisson distribution, Producer and Consumers risk, Quality Assuranc

Abstract: Sampling plans are extensively used in pharmaceutical industries to test drugs or other related materials to ensure that they are safe and consistent. A sampling plan can help to determine the quality of products, to monitor the goodness of materials and to validate the yields whether it is free from defects or not. If the manufacturing process is precisely aligned, the occurrence of defects will be an unusual occasion and will result in an excess number of zeros (no defects) during the sampling inspection. The Zero Inflated Poisson (ZIP) distribution is studied for the given scenario, which helps the management to take a precise decision about the lot and it can certainly reduce the error rate than the regular Poisson model. The Bayesian methodology is a more appropriate statistical procedure for reaching a good decision if the previous knowledge is available concerning the production process. This article proposed a new design of the Bayesian Repetitive Group Sampling plan based on Zero Inflated Poisson distribution for the quality assurance in pharmaceutical products and related materials. This plan is studied through the Gamma-Zero Inflated Poisson (G-ZIP) model to safeguard both the producer and consumer by minimizing the Average Sample Number. Necessary tables and figures are constructed for the selection of optimal plan parameters and suitable illustrations are provided that are applicable for pharmaceutical industries.

How to cite this paper
Kaviyarasu, V & Sivakumar, P. (2022). Optimization of Bayesian repetitive group sampling plan for quality determination in Pharmaceutical products and related materials.International Journal of Industrial Engineering Computations , 13(1), 31-42.

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Journal: International Journal of Industrial Engineering Computations | Year: 2022 | Volume: 13 | Issue: 1 | Views: 1578 | Reviews: 0

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