Utilizing the information theory of entropy to solve an off-line inspection problem

Abstract

This study presents an off-line inspection problem for a batch produced from a process subject to random failures and exhibiting manufacturing variations. The objective of this paper is to develop an inspection policy in which units should be inspected in a particular order to find the transition unit in the batch under a required confidence level. This study develops an algorithm to compute the expected number of inspections. This approach uses the information theory of entropy to select an un-inspected unit to be inspected, and effectively minimizes the uncertainty of the transition unit in the production batch. A numerical example illustrates the proposed off-line inspection policy, and the effects of model parameters on the expected inspection number are investigated. The numerical example in this study indicates that full inspection is required when the required confidence level is one or the process has larger manufacturing variations.

Designing a robust supply chain network against disruptions

“…There is a vast literature [e.g., 82,83,14,84,85,86,87,88,15,89,16,90] on inspection in the context of production systems and supply chains. For example, Hariga and Azaiez [15] discuss about inspection schedules mechanism for an unreliable facility where a minimal repair is carried out.…”

“…Also several ways of estimating are provided for the failure rate by Bayesian methods. Wang et al [90] investigate an off-line inspection policy for a production batch produced from an unreliable process under a required confidence level. An approach based on an information theory of entropy is developed which selects the un-inspected unit to minimize the uncertainty of the transition unit.…”