Attribute gage studies assess the amount of bias and repeatability of a gage when the response is a binary attribute variable. Unlike a variable gage, an attribute gage does not give information on the quality of a part but only indicates whether a part is accepted or rejected based on a set of specified standards.

To conduct an attribute gage study, you must have part names or numbers, a unique reference value for each part, and the number of acceptances for each reference value. You should select reference values that are at nearly equidistant intervals. You must also specify either a lower or upper tolerance limit.

Minitab offers two methods to assess bias: AIAG and regression. If you use AIAG (default), you must have at least 20 trials per part and at least 6 parts greater than 0 number of acceptances and less than the maximum number of acceptances.

The minimum number of trials necessary to use the regression method is 15. However, 20 or more trials are recommended.

You are the production supervisor at an automobile company and need to ensure that all attribute measurement systems meet calibration standards. To assess the bias and repeatability of a gage that is used to accept or reject length values (in millimeters), you run 8 parts through the attribute gage. Reference values are at intervals of 0.0005 from 0.7000 to 0.7035. The system has a lower tolerance of 0.7020.

Data: Length.MTW (available in the Sample Data folder).