A Multivariate Statistical Approach to Metrology

[+] Author and Article Information
T. R. Kurfess

The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332

D. L Banks, L. J. Wolfson

Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213

J. Manuf. Sci. Eng 118(4), 652-657 (Nov 01, 1996) (6 pages) doi:10.1115/1.2831081 History: Received November 01, 1994; Revised November 01, 1995; Online January 17, 2008


This paper presents an approach to metrology that allows one to set a confidence level on geometric parameters using multivariate statistical techniques. Furthermore, the analysis incorporates deviations from nominal geometry that are expected from various manufacturing and measurement processes to reduce the size of the multidimensional confidence interval.

Copyright © 1996 by The American Society of Mechanical Engineers
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