Jim To perform an R&R measurement for a destructive measurement system, you need to make a critical assumption. You should assume that you are able to identify a batch of parts where the parts are so close to each other that you can reasonably consider the parts in the batch to be “equal”. They think the lot is homogeneous. If you measure part of the plot for the same property, you will get the same result in the perfect world. Measurement Systems Analysis (MSA) is critical to the success of any data analysis. If you can`t rely on the tool you use to take action, why bother collecting data first? It would be like trying to lose weight while relying on a scale that doesn`t work. It also contains variability within the batch. This applies to destructive testing, whether you use cross-references or nested R&R promises. In MSA studies for continuous measurements (e.B.B.B weight, length, volume) by non-destructive testing, each part can be measured repeatedly. In this case, we can use cross-payment studies. However, sometimes we need to perform an MSA where the test required for the measurement destroys the object or physically changes the property to be measured. Examples include shock testing and chemical analysis. Imagine frozen chickens thrown on airplane windshields or test the force needed to open a bag of chips.

So what analysis do we use if the test is destructive? Of course, as with many questions that arise in statistics, the answer is: “It all depends.” Aiden, I have the same problem. I have information about the destructive R&R and R attribute, but nothing that combines it. Suppose you run an R&R Gage study with 3 operators, where each operator measures each part twice. This requires 3×2 = 6 measurements per piece. Suppose you can get at least 6 samples for your destructive test that are similar enough to be considered the same part. Even though the 6 samples are really not the same piece, as long as they are similar enough to be considered the same piece, you can use a cross-over Gage study, just as they would for a non-destructive test. Based on these results, reviewers are very close to the 0.75 mark, indicating good to excellent approval. A measure of the match between appraisers can be found using Cohen`s kappa value.

This compares two examiners who measure the same parts. Kappa can range from 1 to -1. A kappa value of 1 represents a perfect match between the two reviewers. A kappa score of -1 represents a perfect disagreement between the two evaluators. A kappa value of 0 indicates that the match represents the expected match at random. Therefore, kappa values close to 1 are desired. In MSA studies for continuous measurements (e.B weight, length, volume) by means of non-destructive testing, each part can be measured repeatedly. In this case, we can use cross-gauge studies.

However, sometimes we need to perform an MSA where the test required for the measurement destroys the object or physically changes the property to be measured. Examples include impact testing and chemical analysis. Imagine frozen chickens being thrown at airplane windshields or testing the force needed to open a bag of chips. Aidan, I have a similar problem where I work. Unfortunately, after being a professor specializing in MSA at Arizona State Univ., there doesn`t seem to be any work at this point that has combined both destructive gauges and R&R attributes. Jim To determine the effectiveness of The Go/No-Gauge, opt for an R&R study with attribute counters. You choose three critics (Bob, Tom and Sally). You will find 30 coins that you can use in the trial version.

Each of these parts was measured using a variable gauge and rated as successful (in specifications) or failed (external specification). Can anyone comment on how to perform a Gage R&R destructive attribute and its method of analysis? Thank you. Help. Another article (Landis, J.R. and Koch, G. G. (1977) “The measurement of observer agreement for categorical data” in Biometrics. Vol. 33, pp. 159-174) provides the following interpretation of kappa: Sometimes a measurement system has a measured value that comes from a finite number of categories. The simplest of these is a go/no go counter. This counter simply tells you if the part exists or breaks down.

There are only two possible outcomes. Other attribute measurement systems may have several categories, para. B example very good, good, bad and very bad. In this bulletin, we will use the simple go/no-go level to understand how an attribute counter R&R study works. This is the first in a series of newsletters on R&R studies on feature labeling and focuses on comparing evaluators. In this edition: “A general rule is that kappa values greater than 0.75 indicate a good to excellent match (with a maximum kappa = 1); Scores above 0.40 indicate a bad match. You have selected a go/no go gauge attribute to use. This counter simply indicates if the part complies with the specifications. It does not tell you how close the result is to the nominal; only that it is in the specifications. Next month, we will continue the newsletters on R&R studies on attribute counters. We will use the reference column in the data above – the “true” value of the part and see how each reviewer compares to the reference. .