Abstract

AbstractThe paper focuses on the economic design of group chain sampling plans (GChSP) for the Weibull distribution using Bayesian methodology. The GChSP is a technique to accept or reject a product based on a sample from a lot. The study addresses situations where destructive testing is costly and utilizes the Bayesian approach to make informed decisions. The research outlines the methodology of developing GChSP including the stages of construction, performance evaluation, and cost estimation. The study compares the proposed plans with an existing one and demonstrates that the Bayesian approach generally yields lower costs. We will provide tables, figures, and calculations related to various aspects of the proposed plans and their comparison with existing methods.

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