A Factor-Analysis Method for Diagnosing Variability in Mulitvariate Manufacturing Processes

In many modern manufacturing processes, large quantities of multivariate process-measurement data are available through automated in-process sensing. This article presents a statistical technique for extracting and interpreting information from the data for the purpose of diagnosing root causes of process variability. The method is related to principal components analysis and factor analysis but makes more explicit use of a model describing the relationship between process faults and process variability. Statistical properties of the diagnostic method are discussed, and illustrative examples from autobody assembly are provided.

[1]  D. Lawley.  TESTS OF SIGNIFICANCE FOR THE LATENT ROOTS OF COVARIANCE AND CORRELATION MATRICES , 1956 .

[2]  David E. Tyler.  Asymptotic Inference for Eigenvectors , 1981 .

[3]  Yu Wang,et al.  Manufactured Part Modeling for Characterization of Geometric Variations of Automotive Spaceframe Extrusions , 1998 .

[4]  Faryar Etesami,et al.  Tolerance verification through manufactured part modeling , 1988 .

[5]  J. Edward Jackson,et al.  Principal Components and Factor Analysis: Part I - Principal Components , 1980 .

[6]  H. Akaike.  Factor analysis and AIC , 1987 .

[7]  Roderick P. McDonald,et al.  Factor Analysis and Related Methods , 1985 .

[8]  Charles W. Champ,et al.  Assessment of Multivariate Process Control Techniques , 1997 .

[9]  Douglas C. Montgomery,et al.  A review of multivariate control charts , 1995 .

[10]  Darek Ceglarek,et al.  Fixture Failure Diagnosis for Autobody Assembly Using Pattern Recognition , 1996 .

[11]  J. Rissanen,et al.  Modeling By Shortest Data Description* , 1978, Autom..

[12]  William S. Peters,et al.  Principal Components and Factor Analysis , 1987 .

[13]  Fred L. Hulting.  [Statistical Issues in Geometric Feature Inspection Using Coordinate Measuring Machines]: Discussion , 1997 .

[14]  Thomas Kailath,et al.  Detection of signals by information theoretic criteria , 1985, IEEE Trans. Acoust. Speech Signal Process..

[15]  Robert C. Kohberger,et al.  Cluster Analysis (3rd ed.) , 1994 .

[16]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .

[17]  H. Akaike.  Autoregressive model fitting for control , 1971 .

[18]  I. Jolliffe.  Principal Component Analysis and Factor Analysis , 1986 .

[19]  T. W. Anderson.  ASYMPTOTIC THEORY FOR PRINCIPAL COMPONENT ANALYSIS , 1963 .

[20]  J. E. Jackson.  Principal Components and Factor Analysis: Part II - Additional Topics Related to Principal Components , 1981 .

[21]  Alexander Basilevsky,et al.  Statistical Factor Analysis and Related Methods , 1994 .

[22]  Daniel W. Apley,et al.  Diagnosis of Multiple Fixture Faults in Panel Assembly , 1996, Manufacturing Science and Engineering.

[23]  Brian Everitt,et al.  Cluster analysis , 1974 .

[24]  G. Schwarz.  Estimating the Dimension of a Model , 1978 .