Test uncertainty ratio (TUR) and test uncertainty
Analytics
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Abstract
Measurement uncertainty is a natural parameter that can be used to characterize any measure¬ment process. Continually increasing demands of higher and higher dimensional accuracy in manufactured components places similar demands on the field of dimensional measurement, as manufacturers strive for lower uncertainty associated with the results of measurement. Complete elimination of uncertainty in manufacturing and measurement is not the intent of this research, as only the reduction of uncertainty is possible, and the reduction of uncertainty comes at a cost. Given that similar manufacturing and measurement equipment is available across industries, it is often the case that the better one can estimate these uncertainties, the greater the competitive advantage as money to reduce uncertainty - thereby improving quality - can be used in the most effective way. The objective of this research is to analyze the impact of two different kinds of uncertainty - the "Test Uncertainty Ratio" and "Test Uncertainty" - for both manufacturers of measurement equipment and their customers. This impact influenced both by their understanding of what the uncertainty represents, as well as their ability to characterize this uncertainty. Measuring equipment often has a stated 'accuracy' within which it can be expected to perform. However, some complex measurements performed with this equipment have additional uncertainty contributors, and the resulting measurement is less accurate (i.e. has a greater uncertainty) than the instrument's stated performance. The Test Uncertainty Ratio (TUR) for a measuring process is one of a family of metrics that relate the tolerance for a measurand to the uncertainty present in performing that measurement. This ratio is used in industry to describe the measurement capability of a system or process, but often is not based on a realistic estimation of the uncertainty present. This research clarifies the uncertainty contributors for the calculation of this metric, and experimentally validates different estimation techniques. It is common to perform a test of the instrument on an artifact with known dimensions, when buying and selling metrology tools. The errors obtained during this test are used to evaluate the instrument, but the errors will reflect not only instrument deficiencies, but also improper use of the instrument, and incomplete knowledge of the test artifact. The contributors to the errors in this type of test that are not associated with the instrument itself have been lumped into a term called Test Uncertainty. This is a new concept, and is receiving much attention in both the accreditation of metrology laboratories and in national and international standards writing bodies. This research in the area of test uncertainty develops a consistent way of considering test uncertainty and its influence in the evaluation of measuring instruments. Experimental results support the method of decomposing uncertainty contributors into those that do and do not affect the test uncertainty.