Blind identification of manufacturing variation patterns by combining source separation criteria

Technometrics

Volumn 50, Issue 3, 2008, Pages 332-343

  Shan, Xuemei ^a   Apley, Daniel ^a  

^a Northwestern University   (United States)

Author keywords

Blind source separation; Factor rotation; Manufacturing variation reduction; Multivariate statistical process control; Principal components analysis

Indexed keywords

BLIND IDENTIFICATIONS; BLIND SEPARATION ALGORITHMS; ESTIMATION ERRORS; FACTOR ROTATION; MANUFACTURING VARIATION REDUCTION; MANUFACTURING VARIATIONS; MULTIVARIATE STATISTICAL PROCESS CONTROL; PRINCIPAL COMPONENTS ANALYSIS; ROOT CAUSES; SOURCE SEPARATIONS; VARIATION PATTERNS;

APARTMENT HOUSES; CONTROL THEORY; INTERCONNECTION NETWORKS; ISOMERS; MANUFACTURE; MOBILE TELECOMMUNICATION SYSTEMS; MULTIVARIANT ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; SEPARATION; SIGNAL ANALYSIS; STATISTICAL PROCESS CONTROL;

BLIND SOURCE SEPARATION;

EID: 55149091340     PISSN: 00401706     EISSN: None     Source Type: Journal    
DOI: 10.1198/004017008000000316     Document Type: Article

References (27)

1. Anderson, T. W. (1963), "Asymptotic Theory for Principal Component Analysis," The Annals of Mathematical Statistics, 34, 122-148.
2. Apley, D. W., and Lee, H. Y. (2003), "Identifying Spatial Variation Patterns in Multivariate Manufacturing Processes: A Blind Source Separation Approach," Technometrics, 45, 220-234.
3. Apley, D.W., and Shi, J. (1998), "Diagnosis of Multiple Fixture Faults in Panel Assembly," ASME Journal of Manufacturing Science and Engineering, 120, 793-801.
4. (2001), "A Factor-Analysis Method for Diagnosing Variability in Multivariate Manufacturing Processes," Technometrics, 43, 84-95.
5. Auestad, B., and Tjostheim, D. (1990), "Identification of Nonlinear Time Series: First-Order Characterization and Order Determination," Biometrika, 77, 669-687.
6. Barton, R. R., and Gonzalez-Barreto, D. R. (1996), "Process-Oriented Basis Representations for Multivariate Process Diagnosis," Quality Engineering, 9, 107-118.
7. Belouchrani, A., Abed-Meraim, K., Cardoso, J. F., and Moulines, E. (1997), "A Blind Source Separation Technique Using Second-Order Statistics," IEEE Transactions in Signal Processing, 45, 434-444.
8. Bowman, A. W., and Azzalini, A. (1997), Applied Smoothing Techniques for Data Analysis: The Kernel Approach With S-PLUS Illustration, Oxford, U.K.: Clarendon Press.
9. Cardoso, J. F. (1994), "Perturbation of Joint Diagonalizers," Technical Report 94d027, Telecom Paris. (1998), "Blind Signal Separation: Statistical Principles," Proceedings of the IEEE, 86, 2009-2025.
10. Cardoso, J. F., and Souloumiac, A. (1993), "Blind Beamforming for Non- Gaussian Signals," IEE Proceedings, 140, 362-370.
11. Ceglarek, D., and Shi, J. (1996), "Fixture Failure Diagnosis for Autobody Assembly Using Pattern Recognition," ASME Journal of Engineering for Industry, 118, 55-66.
12. Cichocki, A., and Amari, S. (2002), Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications, New York: Wiley. Comon, P. (1994), "Independent Component Analysis: A New Concept?" Signal Processing, 36, 287-314.
13. Cruces-Alvarez, S. A., and Cichocki, A. (2003), "Combining Blind Source ExtractionWith Joint Approximate Diagonalization: Thin Algorithms for ICA," in Proceedings of the 4th InternationalSymposium on Independent Component Analysis and Blind Signal Separation, pp. 463-468.
14. Davis, A. W. (1977), "Asymptotic Theory for Principal Component Analysis: Non-Normal Case," Australian Journal of Statistics, 19, 206-212.
15. Ding, Y., Shi, J., and Ceglarek, D. (2002), "Diagnosability Analysis of Multi- StationManufacturing Processes," ASME Journal of Dynamic Systems, Measurement and Control, 124, 1-13.
16. Doron, E., and Yeredor, A. (2004), "Asymptotically Optimal Blind Separation of Parametric Gaussian Sources," Lecture Notes in Computer Science, 3195, 390-397.
17. Hyvarinen, A., and Oja, E. (2000), "Independent Component Analysis: Algorithms and Applications," Neural Networks, 13, 411-430.
18. Jackson, J. E. (1980), "Principal Components and Factor Analysis, Part I: Principal Components," Journal of Quality Technology, 12, 201-213.
19. (1981), "Principal Components and Factor Analysis, Part II: Additional Topics Related to Principal Components," Journal of Quality Technology, 13, 46-58.
20. Johnson, R. A., and Wichern, D. W. (1998), Applied Multivariate Statistical Analysis (4th ed.), Upper Saddle River, NJ: Prentice-Hall.
21. Koldovský, Z., Tichavský, P., and Oja, E. (2006), "Efficient Variant of Algorithm FastICA for Independent Component Analysis Attaining the Cramer- Rao Lower Bound," IEEE Transactions on Neural Networks, 17, 1265-1277.
22. Künsch, H. R. (1989), "The Jackknife and the Bootstrap for General Stationary Observations," The Annals of Statistics, 17, 1217-1241.
23. Lee, H. Y., and Apley, D. W. (2004), "Diagnosing Manufacturing Variation Using Second-Order and Fourth-Order Statistics," International Journal of Flexible Manufacturing Systems, 16, 45-64.
24. Müller, K. R., Philips, P., and Ziehe, A. (1999), %quot;JADETD: Combining Higher- Order Statistics and Temporal Information for Blind Source Separation (With Noise)," in Proceedings of the International Workshop on Independent Component Analysis and Signal Separation (ICA'99), pp. 87-92.
25. Paparoditis, E., and Politis, D. N. (2002), "The Local Bootstrap for Markov Processes," Journal of Statistical Planning and Inference, 108, 301-328.
26. Tichavský, P., and Koldovský, Z. (2004), "Optimal Pairing of Signal Components Separated by Blind Techniques," IEEE Signal Processing Letters, 11, 119-122.
27. Tichavský, P., Koldovský, Z., Doron, E., Yeredor, A., and Gomez-Herrero, G. (2006), "Blind Signal Separation by Combining Two ICA Algorithms: HOS- Based EFICA and Time Structure-Based WASOBI," in Proceedings of 14th European Signal Processing Conference (EUSIPCO), EURASIP, pp. 1-5.