Approval Criteria for Multivariate Measurement Systems

Abstract

Standard measurement-system analysis criteria assume the gauge measures a single variable. In automotive-body manufacturing, measurement systems take data for many quality characteristics, yet manufacturers evaluate each response independently. To support using these data as a multivariate response, this paper develops multivariate extensions of gauge-approval criteria precision to tolerance ratio, percent R&R, and signal-to-noise ratio. These criteria use the volume of constant-density contours to characterize variability, the role of the standard deviation in single-variable models. This paper contains a MANOVA method using expected mean squares for estimating the variance—covariance matrices for one-factor, two-factor, and three-factor gauge studies. The paper demonstrates how to fit the MANOVA model and estimate the multivariate criteria using automotive body panel gauge-study data.

• Gauge Study
• MANOVA
• Measurement-Systems Analysis
• Multivariate Capability
• Signal-to-Noise Ratio

Additional information

Notes on contributors

Karl D. Majeske

Dr. Majeske is an Assistant Professor of Quantitative Methods Management in the School of Business Administration. His email is [email protected].