I wanted to know please if the method used for the R-R attributes test can be considered a reliable source? What is your academic (and bibliographical) basis for doing this test? ——————————————————————————————————————————————————— – I would like to know if the method used for testing the R and R attributes can be considered a reliable source? To determine the effectiveness of the go/no pledge, opt for an attribute-gage study. You select three reviewers (Bob, Tom and Sally). In the trial version, you`ll find 30 pieces that you can use. Each of these parts was measured at a variable measurement value and assessed as being transmitted (in specifications or compliant) or defective (non-compliant or not). The study has 21 compliant parts and 9 non-compliant parts. Minitab produces many more statistics in the editing of the attribute analysis, but in most cases and in the mode of use, the analysis described in this article should be sufficient. ISO/TR 14468:2010 evaluates a measurement process in which the characteristics to be measured are measured in the form of attribute data (including nominal and ordinal data). The tool used for this type of analysis is called the R-R pledge attribute. R-R is synonymous with repeatability and reproducibility.
Repeatability means that the same operator who measures the same thing must get the same reading each time with the same measuring instrument. Reproducibility means that different operators who measure the same thing, with the same measuring device, should get the same measurement value each time. Depending on the efficiency, Bob and Tom are marginal and Sally needs to be improved. The same goes for the wrong rate. The false alarm rate is acceptable to Bob and Tom, but Sally needs to be improved. On the basis of this analysis, the entire measurement system needs to be improved. The key in all measurement systems is a clear testing method and clear criteria on what to accept and what should be rejected. The steps are as follows: ISO/TR 14468:2010 provides examples of attribute agreement analysis (AAA) and deduces various results to assess the agreement between evaluators, such as agreement between evaluators. B, the agreement between the evaluators, the agreement of each expert in relation to a standard and the agreement of any expert in relation to a standard. Since the %agreement for each examiner is within the confidence interval for the other examiner, we must conclude that there is no statistically significant difference between the three examiners. This percentage indicates the overall effectiveness of the measurement system (Minitab calls it “All Appraiser vs.
Standard”). This is the percentage of time agreed by all inspectors and their agreement is in accordance with the standard. This is the second newsletter on attributes of Gage R-R Studies. As mentioned earlier last month, a measurement system sometimes has a measured value from a finite number of categories.