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Abstract
The process loss index was developed for providing a unitless measure of process performance by considering the proximity of the target value. It is defined as the ratio of the expected quadratic loss to the square of half the specification width. Using
for measuring process performance, it also provides an uncontaminated separation between information concerning the process relative off-target loss and the process relative inconsistency loss. Most studies on measuring process loss index are based on crisp estimates involving precise output process measurements. However, measurements of product quality sometimes cannot be precisely recorded or collected. By combining randomness and fuzziness in assessing process capability, this study provides a triangular-shaped fuzzy number for the estimation of
. The fuzzy upper confidence bound, derived by extension principle, can be used for estimating the maximum process loss. Finally, the decision rule for fuzzy hypothesis testing is presented and illustrated with an example for assessing process loss in the fuzzy environment.