A study on skip-lot sampling plan with repetitive deferred sampling plan under Bayesian perspective

Abstract

Nowadays a manufacturing industry holds some difficulties that the companies formulate innovative clarifications to the problem of rising cost of non-conforming lots. The combined quality controlling system deploys a variety of statistical process control tools to improve the efficiency of inspections. The Skip-lot sampling attends as cost effective procedure to achieve the cost of performing repeated product inspections. A powerful tool within a real-time quality controlling system, the capability to collect data towards optimizes skip-lot sampling parameters gives manufacturers the extravagance of lowering inspection expenses. A method for determining the optimal sampling plan of bayesian model is developed for attribute sampling plan towards the production weight of sample size. The sampling inspections are assumed under destructive testing. The model is suggested based on prior distribution and a cost, the optimal sampling plan is developed with minimizing the smaller sample size and acceptance number for specified attribute plan.

Keywords:

• Bayesian Attribute Plan
• Acceptable and Limiting Quality Levels
• Mathematical Relation
• Prior Distribution
• Markov-Chain Technique
• Weighted Risk