Multiscale Statistical Process Control of Paper Surface Profiles

References

• Bakshi, B. R. (1998). Multiscale PCA with Application to Multivariate Statistical Process Control. AIChE Journal, 44(7), 1596–1610.
   Google Scholar
• Bakshi, B. R. (1999). Multiscale Analysis and Modeling Using Wavelets. Journal of Chemometrics, 13, 415–434.
   Google Scholar
• Bernié, J. P., Pande, H., and Gratton, R. (2004). A New Wavelet-Based Instrumental Method for Measuring Print Mottle. Pulp & Paper Canada, 105(9), 24–26.
   Google Scholar
• Bharati, M. H. and MacGregor, J. F. (1998). Multivariate Image Analysis for Real-Time Process Monitoring and Control. Industrial & Engineering Chemistry Research, 37, 4715–4724.
   Google Scholar
• Bouydain, M., Colom, J. F., and Pladellorens, J. (1999). Using Wavelets to Determine Paper Formation by Light Transmission Image Analysis. Tappi Journal, 82(7), 153–158.
   Google Scholar
• Box, G. E. P., Jenkins, G. M., and Reinsel, G. C. (1994). Time Series Analysis — Forecasting and Control, 3rd edition. Prentice Hall, Upper Saddle River, NJ.
   Google Scholar
• Burrus, C. S., Gopinath, R. A., and Guo, H. (1998). Introduction to Wavelets and Wavelet Transforms — A Primer. Prentice Hall, New Jersey.
   Google Scholar
• Costa, R., Angélico, D., Saraiva, P., Reis, M., Ataíde, J., Abreu, C., and Bogas, D. (2004). Paper Superficial Waviness: Conception of a Statistical Measurement System. CAC-2004 Chemometrics in Analytical Chemistry Lisbon (Portugal).
   Google Scholar
• Dai, X. D., Motard, R. L., Joseph, B., and Silverman, D. C. (2000). Corrosion Process Monitoring Using Wavelet Analysis. Industrial & Engineering Chemistry Research, 39, 1256–1263.
   Google Scholar
• Dijkerman, R. W. and Mazumdar, R. R. (1994). Wavelet Representations of Stochastic Processes and Multiresolution Stochastic Models. IEEE Transactions on Signal Processing, 42(7), 1640–1652.
   Google Scholar
• Forseth, T. and Helle, T. (1996). Principles and Application of a Method for Assessing Detailed Paper Surface Topography. 82nd Annual Meeting, Technical Session, CPPA.
   Google Scholar
• Fourie, S. H. and de Vaal, P. (2000). Advanced Process Monitoring Using an On-Line Non-Linear Multiscale Principal Component Analysis Methodology. Computers and Chemical Engineering, 24, 755–760.
   Google Scholar
• Ganesan, R., Das, T. K., and Venkataraman, V. (2004). Wavelet Based Multiscale Process Monitoring — A Literature Review. IIE Trans. on Quality and Reliability Eng., 36(9), 787–806.
   Google Scholar
• ISO (1997). ISO 4287: 1997. Geometrical Product Specifications (GPS) — Surface texture: Profile method — terms, definitions and surface texture parameters.
   Google Scholar
• Jeong, M. K., Lu, J.-C., Huo, X., Vidakovic, B., and Chen, D. (2004). Wavelet-Based Data Reduction Techniques for Process Fault Detection, Georgia Institute of Technology, School of Industrial and Systems Engineering, Statistics Group. (Rep. nb. 11/2004).
   Google Scholar
• Jin, J. and Shi, J. (1999). Feature-Preserving Data Compression of Stamping Tonnage Information Using Wavelets. Technometrics, 41(4), 327–339.
   Google Scholar
• Jin, L. and Shi, J. (2001). Automatic Feature Extraction of Waveform Signals for In-Process Diagnostic Peformance Improvement. Journal of Intelligent Manufacturing, 12, 257–268.
   Google Scholar
• Kajanto, I., Laamanen, J., and Kainulainen, M. (1998). Paper Bulk and Surface. Paper Physics (Edited by K. Niskanen), 88–113. Fapet Oy.
   Google Scholar
• Kano, M., Nagao, K., Hasebe, S., Hashimoto, I., Ohno, H., Strauss, R., and Bakshi, B. R. (2002). Comparison of Multivariate Statistical Process Monitoring Methods with Applications to the Eastman Challenge Problem. Computers and Chemical Engineering, 26, 161–174.
   Google Scholar
• Kortschot, M. T. (1997). The Role of the Fibre in the Structural Hierarchy of Paper. The Fundamentals of Papermaking Materials — Transactions of the 11th Fundamental Research Symposium, 351–399.
   Google Scholar
• Lada, E. K., Lu, J.-C., and Wilson, J. R. (2002). A Wavelet-Based Procedure for Process Fault Detection. IEEE Transactions on Semiconductor Manufacturing, 15(1), 79–90.
   Google Scholar
• Ljung, L. (1999). System Identification — Theory for the User, 2nd edition. Prentice Hall, Upper Saddle River, NJ.
   Google Scholar
• MacGregor, M. A. (2001). Some Impacts of Paper Making on Paper Structure. Paper Technology, 42(3), 30–44.
   Google Scholar
• Mallat, S. (1989). A Theory for Multiresolution Signal Decomposition: The Wavelet Representation. IEEE Transaction on Pattern Analysis and Machine Intelligence, 11(7), 674–693.
   Google Scholar
• Mallat, S. (1998). A Wavelet Tour of Signal Processing. Academic Press, San Diego.
   Google Scholar
• Martin, E. B. and Morris, A. J. (1996). Non-Parametric Confidence Bounds for Process Performance Monitoring Charts. Journal of Process Control, 6(6), 349–358.
   Google Scholar
• Misra, M., Yue, H. H., Qin, S. J., and Ling, C. (2002). Multivariate Process Monitoring and Fault Diagnosis by Multi-Scale PCA. Computers and Chemical Engineering, 26, 1281–1293.
   Google Scholar
• Montgomery, D. C. (2001). Introduction to Statistical Quality Control, 4th edition. Wiley, New York.
   Google Scholar
• Nomikos, P. and MacGregor, J. F. (1995). Multivariate SPC Charts for Monitoring Batch Processes. Technometrics, 37(1), 41–59.
   Google Scholar
• Nomikos, P. and MacGregor, J. F. (1995). Multi-Way Partial Least Squares in Monitoring Batch Processes. Chemometrics and Intelligent Laboratory Systems, 30, 97–108.
   Google Scholar
• Nordström, J.-E. P., Lindberg, S., and Lundström, A. (2002). Human Perception and Optical Measurement of HSWO Waviness. IPGAC (International Printing & Graphic Arts Conference) Bordeaux, France.
   Google Scholar
• Rioul, O. and Vetterli, M. (1991). Wavelets and Signal Processing. IEEE Signal Processing Magazine, 8(4), 14–38.
   Google Scholar
• Sahni, N. S., Aastveit, A. H., and Naes, T. (2005). In-Line Process and Product Control Using Spectroscopy and Multivariate Calibration. Journal of Quality Technology, 37(1), 1–20.
   Google Scholar
• Sander, M. (1991). A Practical Guide to the Assessment of Surface Texture. Feinprüf Perthen GmbH, Göttingen.
   Google Scholar
• Shao, R., Jia, F., Martin, E. B., and Morris, A. J. (1999). Wavelets and Non-Linear Principal Components Analysis for Process Monitoring. Control Engineering Practice, 7, 865–879.
   Google Scholar
• Silverman, B. W. (1986). Density Estimation for Statistics and Data Analysis. Chapman and Hall, London.
   Google Scholar
• Sze, D. H. and Waech, T. G. (1997). Paper Waviness and Finer Alignement Streaks in Paper Forming. CPPA Annual Technical Meeting Proceedings Montréal, Canada.
   Google Scholar
• Top, S. and Bakshi, B. R. (1998). Improved Statistical Process Control Using Wavelets. Foundation of Computer Aided Process Operations FOCAPO 98, 332–337.
   Google Scholar
• Trygg, J., Kettaneh-Wold, N., and Wallbäcks, L. (2001). 2D Wavelet Analysis and Compression of On-Line Industrial Process Data. Journal of Chemometrics, 15, 299–319.
   Google Scholar
• Van Eperen, R. H. (1991). Paper Properties and Testing Procedures, 3rd edition. Vol. 7, Pulp and Paper Manufacture. The Joint Textbook Committee of The Paper Industry, Atlanta.
   Google Scholar
• Vetterli, M. and Kovačevic, J. (1995). Wavelets and Subband Coding. Prentice Hall, New Jersey.
   Google Scholar
• Wågberg, P. and Johansson, P.-Å. (2002). Characterization of Paper Surfaces Using Optical Profilometry. In Handbook of Physical Testing of Paper, 2nd ed. (Edited by J. Borch, M. B. Lyne, R. E. Mark, and C. C. Habeger, Jr.), Marcel Dekker.
   Google Scholar
• Westerhuis, J. A., Kourti, T., and MacGregor, J. F. (1999). Comparing Alternative Approaches for Multivariate Statistical Analysis of Batch Process Data. Journal of Chemometrics, 13, 397–413.
   Google Scholar
• Woodall, W. H., Spitzner, D. J., Montgomery, D. C., and Gupta, S. (2004). Using Control Charts to Monitor Process and Product Quality Profiles. Journal of Quality Technology, 36(3), 309–320.
   Google Scholar
• Zhao, Z., Jin, Y., and Wang, J. (2000). Application of Wavelet Transform to Process Operating Region Recognition. Journal of Chemical Engineering of Japan, 33(6), 823–831.
   Google Scholar