Study of measurement process capability with non-normal data distributions

Abstract

The study of capability of measurement processes is becoming a common practice within Quality Management Systems. Actually, “Gauge R&R study” techniques are currently largely widespread. In general, most of the tools described in the scientific literature, prescribed by the international standards and/or implemented in practical applications are based on the normality assumption of data distributions. This work discusses some alternative approaches for “gauge R&R study” when non-normal data distributions are involved. In order to clarify the impact of this problem in practical applications, the techniques considered in the present paper are analyzed through computer simulation of real case studies in the field of dimensional tolerancing.