Measurement System Analysis And Destructive Testing
نویسندگان
چکیده
measurement system analysis is a vital component for many quality improvement initiatives. It is important to assess the ability of a measurement system to detect meaningful differences in process variables. In many instances, it is possible to design an experiment in which the level of variation attributed to the operator, parts and the operator by part interaction effect can be assessed. This is possible when all operators have the ability to measure each part and is typically the experimental design assessed during the measure phases of the define-measureanalyze-improve-control cycle. For many measurement systems, however, the part being measured is affected in some manner. As such, you cannot assume all operators in the study can assess the same part and reasonably obtain similar results. Look at destructive testing, for example. The part characteristic such as tensile strength, impact strength or burst pressure of a vessel is measured as the part is destroyed. Once the measurement is obtained for a particular part, that part is no longer available for additional measurements with the same or different operators. There are statistical methods available to estimate the repeatability and reproducibility (R&R) components in destructive scenarios if a key, and perhaps controversial, assumption is made. The assumption is that it is possible to identify a batch of parts enough alike that it is reasonable to consider them the same part. This means the measurement characteristic of interest is identical for each part in the group—the batch is homogenous. This assumption is important because the observed within-batch variability is used to estimate the repeatability of the measurement system. If this assumption is reasonable you can consider conducting an R&R study. The homogenous batch size is an important consideration in designing and analyzing a destructive R&R study. A more traditional or crossed design and analysis may be appropriate when the batch is large enough to assign at least two parts from each batch to each operator. This is because USE A NESTED
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