The Importance of Measurement Uncertainty Analysis on Statistical Quality Control

Abstract

AbstractStatistical Quality Control tools require data about the process quality, which is obtained through measurement systems. These measurement systems have error components involved in their measurements, and even when they are studied and corrected, uncertainty remains on the final measurement value, generating doubt on how well this result represents the quantity measured. Imprecise measurement can seriously affect quality-oriented companies because of the risks involved in making wrong decisions based on process control tools. Consequently, the measurement uncertainty effect on these tools needs to be carefully investigated. The present study aims to provide an overview of the measurement uncertainty consideration in control charts, process capability indices, and conformance testing and to emphasize its importance in these statistical quality assurance strategies. It was found that large values of measurement uncertainty tend to distance the actual process capability values from the observed ones. In control charts analysis, new critical limits must be calculated to consider measurement uncertainties. Moreover, setting suitably the test uncertainty ratio reduces the out-of-control risks related to measurement uncertainty. Since few studies explore this context, some suggestions to motivate future studies are also provided.KeywordsStatistical quality controlMeasurement uncertaintyProcess control