Statistica Gage Linearity Overview
Measurement systems are not perfect, and the accuracy of their readouts is limited by various sources of error that cannot be controlled. These sources of error may stem from the nature of the gage itself, or they might be related to the conditions under which a gage operates. Some of these errors are deterministic and some are random in nature. Either way such sources of error result in imperfections in gage readouts that need to be taken into account in many industrial applications of Process Analysis. Statistica Gage Linearity helps you to achieve this task.
The Statistica Gage Linearity module is an implementation of techniques known as gage linearity and bias study [see AIAG (Automotive Industry Action Group manual) for more details]. The program is part of the Statistica Process Analysis module of the Industrial Statistics & Six Sigma group.
Statistica Gage Linearity helps you to determine how much of the variation in your process is actually coming from the measurement system. The determination of the sources of variation in measurement systems is particularly important in Quality Control problems, where measurements are often made with finite precision due to limited accuracy of the gage, or because of existing environmental factors that are adding further inaccuracies to gage readouts.
The program allows for the selection of Part, Master, and Measure variables. Options are also available for using aggregated data. Statistica Gage Linearity also supports the use of the estimated value of process variation, obtained from previous Gage R&R studies, and process tolerance (see AIAG) analyses, to obtain the absolute and percentage estimates of linearity and bias.
In the Gage Linearity Results dialog box, there are options for reviewing your results and producing a variety of outputs in the form of spreadsheets and graphs to further aid your analysis and draw conclusions.
See also, Statistica Gage Linearity Technical Notes and Example 5: Gage Linearity and Bias Study.