Selecting a quality control attribute sample:An information‐economics method

The information‐economics approach to assessing the value of information is different fromthe statistical approach. The statistical approach focuses on determining the probabilities oftype I and II errors, while the information‐economics approach focuses on maximizing theexpected monetary value of the whole process. This attitude is the basis for the models ofsequential decision processes, especially Markov decision processes (MDP) or partiallyobserved Markov decision processes (POMDP). However, as in traditional single‐samplingmodels, the sample size and sampling costs are not treated as decision variables in a cost‐effectivemanner. This paper uses a well‐known information‐economics model ‐ the InformationStructure Model ‐ to determine the optimal sample size and decision rule in QC single‐samplingproblems. The method uses rough information about the costs of types I and IIerrors and other parameters of the sampling problem. That method can be applied by decisionmakers to decide whether to use a QC sample and to determine the optimal QC plan in orderto maximize the long‐range expected monetary value of sampling gained by the firm. Analgorithm for single‐sampling plan determination is presented toward the end of the paper.Applications to double‐sampling or sequential‐sampling problems need further research. Copyright Kluwer Academic Publishers 1999