Bayesian Acceptance Sampling for Textile Quality Systems
topic
Bayesian sampling plans incorporate prior information about supplier quality history into the sampling decision framework through conjugate beta-binomial models, updating the posterior lot quality distribution after each inspection and adjusting required sample sizes and acceptance numbers based on accumulated supplier quality evidence rather than treating each lot independently.
Role
Enables adaptive inspection intensity that formally incorporates supplier quality track record into sampling plan parameters, providing a statistically rigorous framework for sampling reduction decisions that goes beyond the rule-based switching procedures of ISO 2859 by quantifying the posterior probability of lot conformance given both current sample results and historical supplier performance.