Integrating Precision Gaging into Production Gage Maintenance
Victor Kane, Associate Professor
Kennesaw State University
Department of Statistics and Analytical Sciences
MD 1103, Rm. 3025
Kennesaw, GA 30144
E-mail: vkane@kennesaw.edu
Phone: 678 595-5872
Category of Talk: Applications
Abstract
Two analysis procedures are presented for using precision gages to evaluate production gage accuracy performance. These methods will facilitate precision gage operators in conducting many Gage Management System responsibilities. The first troubleshooting application uses precision gaging in a modified Gage Repeatability and Reproducibility (R&R) study on suspect production gages. This GARR method extends the usual statistical analysis of variance model to include production gage bias as well as R&R. All statistical measures of production gage performance are obtained and tested in a new single study analysis format. The GARR analysis also assess the new concept of variable gage bias, which can arise from part datum variation. Operators of portable precision gages can use GARR to evaluate floor gaging issues with a single study. It is desirable that these key team personnel be aware of new production gage troubleshooting methods.
Precision gaging operators are also involved in maintaining production gages within a facility. This activity often must address a large number of gages for calibration issues. The presented modified GARR approach provides a low resource method for combined R&R assessment, which can also include bias assessment using precision gaging results. After establishing production gage calibration performance, it is possible to use precision gage and production gage measurements of production parts to establish gage operational accuracy that impacts the final customer. This screening methodology ideally applied using portable metrology can supplement calibration activities by using bias measurements from production parts. Simulation studies are presented that show the modified GARR screening reliably identifies problem production gages.
References
Kane, Victor, (2016), Low Resource Gage Screening, Quality Management Journal, 23, pp. 6-18.
Kane, Victor, (2014), Gage Triage Analysis for MSA Studies, Six Sigma Forum Magazine, 13, pp. 5-17.
