Sampling rules to achieve quality, maximize benefit and minimize financial loss

Abstract

Determining the proper sample size and frequency of sampling such that quality is assured while financial losses are not unnecessarily incurred is critical to an effective quality program. The main purpose of the present work is to design a fuzzy controller to adjust sample sizes and frequency of sampling according to potential fuzzy benefit/loss. A set of fuzzy rules is given where, depending on the antecedents, the sample size and/or sampling frequency may be decreased, remain static or be increased. At any given moment the proportion of defects in the sample determines the firing strength of the rules suggesting an appropriate sample size and sampling frequency. The firing strength is then modified to include an analysis of the decision maker’s belief that as sampling takes place and adjustments are being considered benefit or loss would be incorporated prior to any action or adjustment to sample size and/or frequency.