In this paper we study the optimal number of independent classifications on each produced unit when there are two types of classification errors: the type I error where a product is classified as non-conform when actually it is conform, and the type II error where a product is classified as conform when actually it isn't. We develop an economic model to minimize the total expected cost as a function of the classification errors and the cost of each classification.
control of attributes; misclassification; total expected cost
