A partially observable simulation model for quality assurance policies

This paper presents a simulation model of a partially observable Markov decision process (POMDP) for quality assurance policies. The model may be used as a decision aid for evaluation and comparison of different quality policies. The decision maker must decide what quality policy to adopt: a ‘do-nothing’ policy, an appraisal policy that prevents the nonconforming products from reaching the customer, or a prevention policy that affects process performance and leads to long term improvements. The process performance is not observed directly but its effect on the quality of products is observed. The three policies are compared based on the incurred quality costs and the average outgoing quality. A case study in a fish processing plant is presented. It is shown that if costs are the only criteria for decision making then a prevention policy that leads to process improvement may not be the best policy to adopt. Money spent in this policy may never be regained. It is also shown that the merits of each quality policy depend on the actual quality level in each organization.