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BOOK 1. Qin, S. J. and J.F. MacGregor (2004). Multivariate Analysis and Monitoring of Process Data: A Latent Variable Approach. To be published. REFEREED ARCHIVAL JOURNAL PAPERS1. S.J. Qin, Gregory Cherry, Richard Good, Jin Wang, and Christopher A. Harrison (2004). Semiconductor Manufacturing Process Control and Monitoring: A Fab-wide Framework. Submitted to J. of Process Control. 2. W. Lin and S.J. Qin (2004). An Optimal Structured Residual Approach for Improved Faulty Sensor Diagnosis. To be revised for I&EC Research. 3. D. Wang, D.H. Zhou, Y.H. Jin and S. Joe Qin (2004), A strong tracking predictor for nonlinear processes with input time delay, Computers & Chemical Engineering, 28, 2523-2540. 4. Chris A. McNabb and S.J. Qin (2004). Fault Diagnosis in the Control Invariant Subspace of Closed-loop Systems, accepted in a special issue of I&EC Research in honor of W.H. Ray. 5. D. Wang, D.H. Zhou, Y.H. Jin, S.J. Qin (2004) Adaptive generic model control for a class of nonlinear time-varying processes with input time delay, J. of Process Control, 14, 517-531 6. S.J. Qin, W. Lin, and L. Ljung (2004). A Novel Subspace Identification Approach with Enforced Causal Models, revised for Automatica. 7. W. Lin, S.J. Qin, and L. Ljung (2004). A Framework for Closed-loop Subspace Identification with Innovation Estimation, submitted to Automatica, Jan., 2004. 8. Chris A. McNabb and S.J. Qin (2005). Projection Based MIMO Control Performance Monitoring - II. Measured disturbances, J. of Process Control, 15, 89-102. 9. J. Wang, Q. He, S.J. Qin, C. Bode, and M. Purdy (2004). Recursive least squares estimation for run-to-run control of shallow trench isolation, Revised for IEEE Trans. on Semi. Manufacturing, Nov. 2004. 10. R. Good and S.J. Qin (2004). On the Stability of MIMO EWMA Run-to-Run Controllers with Metrology Delay, submitted to IEEE TSM. 11. B. Huang, S.X. Ding, and S.J. Qin (2005). Closed-loop subspace identification: an orthogonal projection approach. Journal of Process Control, 15, 53-66. 12. J. Wang and S.J. Qin (2004). Combined deterministic-stochastic subspace identification under errors-in-variables, submitted to Automatica. 13. Q. He, J. Wang and S.J. Qin (2004). A New Fault Diagnosis Method Using the Fault Directions in Fisher Discriminant Analysis, accepted by AIChE Jounral. 14. In-Sik Chin, S.J. Qin, Kwang S. Lee, and Moonki Cho (2004). A Two-Stage Iterative Learning and Batch Control Technique with Independent Disturbance Rejection Capability, Automatica, 40(11), 1913-1922. 15. Y. Chu, S.J. Qin, and C. Han (2004). Fault Detection and Operation Mode Identification Based on Pattern Classification with Variable Selection, Ind. And Eng. Chem. Res., 43, 1701-1710. 16. Chris A. McNabb and S.J. Qin (2003). Projection Based MIMO Control Performance Monitoring - I. Covariance Monitoring in State Space, J. of Process Control, 13, 739-759. 17. S.J. Qin (2003). Statistical process monitoring: basics and beyond, J. Chemometrics, 17, 480-502. 18. Q. He, S.J. Qin, and A. Toprac (2003). Computationally Efficient Modeling of Wafer Temperatures in a Low Pressure Chemical Vapor Deposition Furnace, IEEE Trans. Semi. Manuf., 16(2), 342-350. 19. S.J. Qin and T.A. Badgwell (2003). A survey of industrial model predictive control technology, Control Engineering Practice, 11(7), 733-764. 20. S.J. Qin, G. Scheid, and T. Riley (2003). Adaptive run to run control and monitoring for a rapid thermal processor, JVST-B, 21(1), 301-310. 21. H. Potrykus, F. Allgower, and S.J. Qin (2002). Idempotent-Analytic Nonlinear Small Gain Theorem via Gauge Functions, submitted to Systems and Control Letters, December, 2002. 22. H. Potrykus, F. Allgower, and S.J. Qin (2002). The Characterization of an Idempotent-Analytic Nonlinear Small Gain Theorem, submitted to IEEE Trans. On Automatic Control, August, 2002. 23. H. Potrykus, F. Allgower, and S.J. Qin (2002). Applications of a Small Gain Theorem to Three Chemical Engineering Systems, submitted to Chemical Engineering Science, August, 2002. 24. Uwe Kruger and S. Joe Qin (2002). Canonical correlation partial least squares. Part II: process monitoring applications, submitted to J. of Chemometrics. July, 2002. 25. Uwe Kruger and S. Joe Qin (2002). Canonical correlation partial least squares. Part I: algorithms and analysis, submitted to J. of Chemometrics. March, 2002. 26. Chris A. McNabb and S.J. Qin (2002). Projection Based MIMO Control Performance Monitoring - III. Impact of Sensor and Actuator Faults, submitted J. of Process Control. April 2002. 27. Richard Good, J. Hahn, T. Edison, and S. J. Qin (2002). A Run-to-Run Control Approach to Drug Dosage Adjustment for Long-Term Drug Therapy, submitted to Control Engineering Practice. 28. Mirats, J.M., Cellier, F.E., Huber, R.H., and Qin, S.J. (2002). On the selection of variables for qualitative modeling of dynamic systems. Int. J. of General Systems, 31(5), pp.435-467. 29. Misra, M., S.J. Qin, H. Yue and C. Ling (2002). Multivariate process monitoring and fault identification using multi-scale PCA, Comput. Chem. Engng., 26(9), 1281-1293. 30. J. Wang and S.J. Qin (2002). A new subspace identification approach based on principal component analysis, J. of Process Control, 12, pp. 841-855. 31. Li, W. and S.J. Qin (2001). Consistent dynamic PCA based on errors-in-variables subspace identification, J. of Process Control, 11(6), pp 661-678. 32. Misra, M., Kumar, S., Qin, S.J., and Seemann, D. (2001). Error based criterion for on-line wavelet data compression, J. of Process Control, 11(6), pp 717-731. 33. Yue, H. and S.J. Qin (2001). Reconstruction based fault identification using a combined index, I&EC Research, 40, 4403-4414. 34. Yue, H., S.J. Qin, J. Wiseman, and A. Toprac (2001). Plasma etching endpoint detection using multiple wavelengths for small open-area wafers, J. of Vacuum Science & Technology A, 19, 66-75. 35. Nugroho, Toto and S.J. Qin (2001). Sensor validation under feedback control of MPC, Control Engineering Practice, 9, 877-888. 36. Qin, S.J., S. Valle, and M.J. Piovoso (2001). On unifying multi-block analysis with application to decentralized process monitoring, J. Chemometrics, 15, 715-742. 37. Qin, S. J. and W. Li (2001). Detection and identification of faulty sensors in dynamic processes with maximized sensitivity, AIChE Journal, 47, 1581-1593. 38. Li, W., H. Yue, S. Valle-Cervantes, and Qin, S.J. (2000). Recursive PCA for adaptive process monitoring, J. of Process Control, 10, 471 - 486. 39. H. Yue, S.J. Qin, R. Markle, C. Nauert, and M. Gatto (2000). Fault detection of plasma etchers using optical emission spectra. IEEE Trans. on Semiconductor Manufacturing, 13, 374-385. 40. Misra, M., Kumar, S., Qin, S.J., and Seemann, D. (2000). On-line data compression and error analysis using wavelet technology, AIChE Journal, 46, 119-132. 41. Qin, S.J and R. Dunia (2000). Determining the number of principal components for best reconstruction, J. of Process Control, 10, 245-250. 42. Qin, S.J and W. Li (1999). Detection, identification and reconstruction of faulty sensors with maximized sensitivity, AIChE J., 45(9), 1963-1976. 43. Valle-Cervantes, S., W. Li, and S.J. Qin (1999). Selection of the number of principal- components: A new criterion with comparison to existing methods, I&EC Research, 38, 4389-4401. 44. R. Dunia and Qin, S.J. (1998). A subspace approach to multidimensional fault identification and reconstruction, AIChE J., 44(8), 1813-1831. 45. R. Dunia and Qin, S.J. (1998). Joint diagnosis of process and sensor faults using principal component analysis, Control Engineering Practice, vol. 6, no. 4, 457-469. 46. R. Dunia and Qin, S.J. (1998). A unified geometric approach to process and sensor fault identification and reconstruction: the unidimensional fault case, Computer and Chem. Eng., 22, 927-943. 47. Qin, S.J. (1998). Recursive PLS algorithms for adaptive data modeling, Comput. and Chem. Eng., 22, 503-514. 48. Qin, S.J. (1998). Control performance monitoring -- A review and assessment. Comput. and Chem. Eng., vol.23, 178-186. 49. Luo, R., M. Misra, Qin, S.J., R. Barton, D.M. Himmelblau (1998). Sensor fault detection via multiscale analysis and nonparametric statistical inference, Ind. Eng. Chem. Res., 37, 1024-1032. 50. Luo, R., S.J. Qin and D. Chen (1998). A new approach to closed loop autotuning for proportional-integral-derivative controllers, I&EC Research, 37, 2462-2468. 51. Qin, S.J. and Badgwell, T.J. (1997). An overview of industrial model predictive control technology, Chemical Process Control-V, edited by J.C. Kantor, C.E. Garcia and B. Carnahan, pp.232-256, Tahoe, California. 52. Qin, S.J., H. Yue and R. Dunia (1997). Self-validating inferential sensors with application to air emission monitoring, I&EC Research, vol.36, pp.1675-1685. 53. Qin, S.J., V. M. Martinez, and B. Foss (1997). An interpolating MPC strategy with application to a waste treatment plant, Comp. and Chem. Eng., vol.21, pp. S881-S886. 54. Foss, B. and Qin, S.J. (1997). Interpolating optimizing process control. Journal of Process Control, vol. 7, pp.129-138. 55. Dunia, R., Qin, S.J., Edgar, T.F., and T.J. McAvoy (1996). Identification of faulty sensors using principal component analysis, AIChE Journal, vol. 42, no. 10, pp. 2797-2811. 56. Dunia, R., Qin, S.J., Edgar, T.F., and T.J. McAvoy (1996). Use of principal component analysis for sensor fault identification. Comp. and Chem. Eng., vol. 20, pp. S713-S718. 57. Qin, S.J. and McAvoy, T.J. (1996). Nonlinear FIR modeling via a neural net PLS approach. Comp. & Chemical Engng., vol 20, 147-159. 58. Qin, S.J. & G. Borders (1994). A multi-region fuzzy controller for nonlinear process control. IEEE Transactions on Fuzzy Systems, Vol 2, No.1, pp74-81. 59. Qin, S.J. and McAvoy, T.J. (1992). Nonlinear PLS modeling using neural networks. Computers & Chemical Engineering, vol. 16, no. 4, 379-391.60. Qin, S.J., Su, H. and McAvoy, T.J. (1992). Comparison of four neural net learning methods for dynamic system identification, IEEE Transactions on Neural Networks, vol. 3, no. 1, 122-130. In Preparation61. R. Good and S.J. Qin (2004). On the Performance of MIMO EWMA Run-to-Run Controllers with Metrology Delay. To be submitted to Transations IIE. BOOK CHAPTERS 62. Badgwell, T.A. and S.J. Qin (2001). A Review of Nonlinear Model Predictive Control Applications, Chapter 1 in Non-linear Predictive Control: Theory and Practice, Institution of Electrical Engineers, edited by Basil Kouvaritakis and M. Cannon. 63. Qin, S.J. and T.A. Badgwell (2000). An overview of nonlinear model predictive control applications. In Nonlinear Model Predictive Control, edited by F. Allgower and A. Zheng, Birkhauser, SWITZERLAND. 64. Frank Allgower, Tom Badgwell, S.J. Qin, James Rawlings, and Steven Wright (1999). Nonlinear Predictive Control and Moving Horizon Estimation -- An Introductory Overview. In Advances in Control, edited by Paul M. Frank, Springer. 65. Qin, S.J. (1997). Neural networks for intelligent sensors and control -- Practical issues and some solutions. In Neural Systems Control, Chapter 8, pp. 213-234, edited by Omid Omidvar and David L. Elliott, Academic Press. OTHER ARTICLES 1. Qin, S.J. (1998). University/industry consortia in industrial process control. Control Systems Magazine, IEEE, February, 65-66. 2. Qin, S.J. (1996). University-industry consortia in industrial process control. News Notes on Industrial Process Control, CSS, IEEE, June. REFEREED CONFERENCE PAPERS 1. Weilu Lin, S. Joe Qin and Lennart Ljung (2005). Comparisons of Subspace Identification Methods for Systems Operating on Closed-loop, submitted to IFAC Congress, Prague, Czech 2. Kwang Soon Lee, Insik Chin, Moonki Cho, and S. Joe Qin (2005). State Space Model-based Two-Stage Iterative Learning Control with Real-time Feedback, submitted to IFAC Congress, Prague, Czech 3. Weilu Lin, S. Joe Qin, and Lennart Ljung (2004). On Consistency of Closed-loop Subspace Identification with Innovation Estimation. Accepted by 2004 Conf. on Decision and Control, Dec. 2004, Bahamas. 4. Christopher Harrison, Richard Good, Daniel Kadosh, and S. Joe Qin (2004). A Multi-Step Supervisory Control Strategy for Semiconductor Device Manufacturing. Accepted by 2004 Conf. on Decision and Control, Dec. 2004, Bahamas. 5. S.J. Qin, Gregory Cherry, Richard Good, Jin Wang, and Christopher A. Harrison (2004). Control and Monitoring of Semiconductor Manufacturing Processes: Challenges and Opportunities. Keynote at IFAC DYCOPS-7, July 4-7, Boston, MA. 6. E.T. Hale and S.J. Qin (2004). Multi-parametric nonlinear programming and the evaluation of implicit optimization model adequacy. IFAC DYCOPS-7, July 4-7, Boston, MA. 7. J. Wang and S.J. Qin (2004). Errors-in-variables subspace identification using the parity space. IFAC DYCOPS-7, July 4-7, Boston, MA. 8. Christopher Harrison, S. Joe Qin (2004). Closed-loop Time Delay Estimation of SISO Processes for Control Performance Monitoring. IFAC DYCOPS-7, July 4-7, Boston, MA. 9. B. Huang, S.X. Ding, and S.J. Qin (2004). Closed-loop subspace identification: an orthogonal projection approach. IFAC DYCOPS-7, July 4-7, Boston, MA. 10. Christopher A. Harrison, Richard Good, Daniel Kadosh, S. Joe Qin (2003). Multi-Step Supervisory Control of Flash Memory Device Production via a Simple First-Principles Model, Best Student Paper Award, AEC/APC Symposium XV, September, 2003, Colorado Spring, Denver. 11. S.J. Qin and L. Ljung (2003). Closed-loop subspace identification with innovation estimation, IFAC Symposium on System Identification, August 2003, Rotterdam, Netherlands. 12. S.J. Qin and L. Ljung (2003). Parallel QR Implementation of Subspace Identification with Parsimonious Models, IFAC Symposium on System Identification, August 2003, Rotterdam, Netherlands. 13. U. Kruger and S.J. Qin (2003). Canonical Correlation Partial Least Squares, IFAC Symposium on System Identification, August 2003. 14. S.J. Qin and C.A. McNabb (2003). A Subspace Approach to MIMO Control Performance Monitoring and Diagnosis, IFAC Symposium on ADCHEM, June 18-20, 2003, Hong Kong. 15. In-Sik Chin, S.J. Qin, Kwang S. Lee, and Moonki Cho (2003). Combined Stochastic Real-time and Run-to-run Control Technique with Independent Tuning in a Stochastic Framework, IFAC Symposium on ADCHEM, June 18-20, 2003, Hong Kong. 16. Y.H. Chu, J.H. Kim, S.J. Moon, I.S. Kang, S.J. Qin, and C. Han (2003). Control of gasholder level by trend prediction based on time-series analysis and process heuristics, IFAC Symposium on ADCHEM, June 18-20, 2003, Hong Kong. 17. Potrykus H.G., Allgower F., Qin S.J. (2003). The character of an idempotent-analytic nonlinear small gain theorem. In Proc. of Positive Systems, LECTURE NOTES IN CONTROL AND INFORMATION SCIENCES, 294: 361-368, SPRINGER-VERLAG BERLIN, Germany. 18. Q. He, S.J. Qin, A. Toprac, and J. Campbell (2003). Computationally Efficient Modeling of Wafer Temperatures in an LPCVD Furnace, presented at SPIE Conference, Feb. 28, 2002, San Jose, CA. 19. G. Cherry, R. Good, and S.J. Qin (2002). Semiconductor Process Monitoring and Fault Detection with Recursive Multiway PCA Based on a Combined Index, Best Student Paper Award, AEC/APC XIV Symposium, September, 2002, Salt Lake City, Utah. 20. E.T. Hale and S.J. Qin (2002). Subspace model predictive control and a case study, American Control Conf., May 8–10, Anchorage, AK. 21. Richard Good and S. J. Qin (2002). Stability analysis of double EWMA run-to-run controller with metrology delay, American Control Conf., May 8–10, Anchorage, AK. 22. S. J. Qin, Glen Scheid and T. Riley (2002). Adaptive run-to-run control for intermittent batch operations. Accepted by American Control Conf., May 8–10, Anchorage, AK. 23. Richard Good, J. Hahn, T. Edison, and S. J. Qin (2002). Drug dosage adjustment via run-to-run control. Accepted by American Control Conf., May 8–10, Anchorage, AK. 24. J. Wang and S. Joe Qin (2001). Principal component analysis for errors-in-variables subspace identification, Proc. of the 40th IEEE Conf. On Decision and Control, 3936-3941, December 4-7, Orlando, FL. 25. K. Chamness, G. Cherry, R. Good, and S.J. Qin (2001). A Comparison of R2R Control Algorithms for the CMP with Measurement Delays, Best Student Paper Award, AEC/APC XIII Symposium, October, 2001, Banff, Canada. 26. S. Valle, S.J. Qin, M. Piovoso, M. Bachmann, and N. Mandakoro (2001). Extracting fault subspaces for fault identification of a polyester film process. Proc. Of American Control Conf., 4466-4471, June 25-27, Arlington, VA. 27. U. Kruger, X. Wang, Q. Chen, and S.J. Qin (2001). An alternative PLS algorithm for the monitoring of industrial process. Proc. Of American Control Conf., 4455-4459, June 25-27, Arlington, VA. 28. Pranatyasto, T. and S.J. Qin (2000). Model predictive control of FCC units with integrated sensor validation and process fault diagnosis. Proc of ADCHEM 2000, 569 - 574, June 14-16, 2000, Pisa, ITALY. 29. Qin, S.J., W. Li and H. Yue (1999). Recursive PCA for adaptive process monitoring. IFAC Congress '99, July 5-9, 1999, Beijing, China. 30. Misra, M., S. Kumar, S.J. Qin, and R.S. Seemann (1999). Adaptive error based thresholding for on-line wavelet compression, IFAC Congress '99, July 5-9, 1999, Beijing, China. 31. Pasadyn, A. and Qin, S.J (1999). Closed-loop and open-loop identification of an industrial reactor, American Control Conf., June 2-4, 1999, San Diego, CA. 32. Qin, S.J and W. Li (1999). Detection, identification and reconstruction of faulty sensors with maximized sensitivity, American Control Conf., June 2-4, 1999, San Diego, CA. 33. Luo, R., S.J. Qin and D. Chen (1998). A new approach to closed loop autotuning for PID controllers, Porc. of American Contr. Conf., June 21-23, 1998, Philadelphia, PA. 34. Qin, S.J and R. Dunia (1998). Determining the number of principal components for best reconstruction, Proc. of the 5-th IFAC Symposium on Dynamics and Control of Process Systems, 359-364, June 8-10, 1998, Corfu, Greece. 35. Yi Cheng, S.J. Qin, T.F. Edgar, M.J. Gatto, and C. Nauert (1997). Modeling of OES data to estimate etch rate for etching equipment, SPIE Proceedings, vol. 3213, pp. 108-118. 36. Dunia, R., Qin, S.J., and Edgar, T.F. (1997). A unified approach to process and sensor fault identification using PCA. Proceedings of the 2nd China/US Conference on Chemical Engineering, May 19-22, 1997, Beijing, China. 37. R. Dunia and Qin, S.J. (1997). Multidimensional fault diagnosis using a subspace approach. American Control Conference’97, June 4-6, 1997, Albuquerque, New Mexico. 38. Qin, S.J., H. Yue and R. Dunia (1997). A self-validating inferential sensor for emission monitoring. American Control Conference’97, June 4-6, 1997, Albuquerque, New Mexico. 39. Dunia, R., Qin, S.J., Edgar, T.F., and T.J. McAvoy (1996). Sensor fault identification and reconstruction using principal component analysis, Proceedings of IFAC Congress’96, vol. N, pp. 259-264, June 30 - July 5, 1996, San Francisco. 40. Hayes, R. and Qin, S.J. (1995). Experience using a neural network to model polymer molecular weight, Advanced Instrum. Control, 50, pp. 927-932. 41. Dunia, R., Qin, S.J., & Edgar, T.F. (1995). Multivariable process monitoring using nonlinear PLS approach. Proc. 1995, American Control Conference. June 21-23, 1995, Seattle, WA. 42. Qin, S.J. (1994). Auto-tuned fuzzy logic control. Proc. of American Control Conference. June 29-July 1, 1994, Baltimore. 43. Qin, S.J. (1994). Fuzzy logic control -- A tutorial. Presented at 1994 ISA Conference. October 23-27, 1994, Anaheim, CA. 44. Qin, S.J. (1994). Fuzzy logic enhances process control. ISA ACOS, 1994. 45. Qin, S.J. (1993). Partial least squares regression for recursive system identification, Proc. of the 32nd IEEE Conference on Decision and Control, Vol. 3: 2617-2622, December 15-17, 1993, San Antonio, TX. 46. Qin, S.J. & G. Borders (1993). A multi-region fuzzy controller for controlling processes with nonlinear gains, Proc. of IEEE Int. Symposium on Intelligent Control, 445-450, August 25-27, 1993, Chicago. 47. Qin, S.J. (1993). A statistical perspective of neural networks for process modeling and control, Proc. of IEEE Int. Symposium on Intelligent Control, 599-604, August 25-27, 1993, Chicago. 48. Qin, S.J. & Rajagopal, B. (1993). Combining statistics and expert systems with neural networks for empirical process modeling, Proc. of ISA Conference, 1711-1720, October, 1993, Chicago. 49. Qin, S.J. and McAvoy, T.J. (1992). Process control through neural computing, Preprints of Congress Interkama'92, October 5-10, 1992, Duseldorf, Germany. 50. Qin, S.J. and McAvoy, T.J. (1992). A data-based process modeling approach and its applications, Proceedings of the 3rd IFAC DYCORD+ Symposium, pp. 321-326, April 26-29, 1992, College Park, Maryland. PRESENTATIONS WITH REFEREED ABSTRACTS 51. K. Onodera, M. Ogawa, and S.J. Qin (2004). A comparative study of several closed-loop MIMO identification methods with industrial data. AIChE Annual Meeting, Austin, TX, November 7-14, 2004 52. P. He and S.J. Qin (2004). Multivariate Visualization in Data Analysis for Process Operations. AIChE Annual Meeting, Austin, TX, November 7-14, 2004 53. J. Wang and S.J. Qin (2004). Stochastic Fault Detection Algorithms Using Second Order Statistics. AIChE Annual Meeting, poster, Austin, TX, November 7-14, 2004 54. C. Harrison and S.J. Qin (2004). A STRAIGHTFORWARD FEEDBACK-INVARIANT APPROACH TO CLOSED-LOOP TIME DELAY ESTIMATION OF SISO PROCESSES. AIChE Annual Meeting, poster, Austin, TX, November 7-14, 2004 55. P. He, J. Wang and S.J. Qin (2003). Fault Diagnosis Using Fault Directions in Fisher Discriminant Analysis. AIChE Annual Meeting, paper 453f, San Francisco, CA, November 16-21, 2003 56. R. Good and S.J. Qin (2003). Stability Analysis of a MIMO Double-EWMA Run-to-Run Controller with Metrology Delay. AIChE Annual Meeting, paper 176e, San Francisco, CA, November 16-21, 2003 57. Richard Good and S. Joe Qin (2003), A Supervisory Control Methodology for Semiconductor Device Manufacturing, AEC/APC Symposium XV, September, 2003, Colorado Spring, Denver. 58. T.A. Badgwell and S.J. Qin (2003). A Survey of Industrial Model Predictive Control Technology, to be presented at AIChE Spring Meeting, New Orleans, April 2, 2003. 59. C.A. McNabb, A.P. Swanda, and S.J. Qin (2002), control performance monitoring of a wood waste power boiler, presented at the 52nd Canadian Chemical Engineering Conference, Vancouver , BC, Oct.20-23, 2002. 60. S.J. Qin, J. Wang, and L. Ljung (2002). [255c] - Subspace Identification Methods Using Parsimonious Model Formulation, AIChE Annual Meeting, Indianapolis, November, 2002. 61. Chris McNabb and S.J. Qin (2002). [254d] – Plant-wide MIMO Control Performance Diagnosis via Subspace Projections, AIChE Annual Meeting, Indianapolis, November, 2002. 62. Greg Cherry, Rick Good, and S.J. Qin (2002). [261b] - Semiconductor Process Monitoring and Fault Detection with Recursive Multiway PCA Based on a Combined Index, AIChE Annual Meeting, Indianapolis, November, 2002. 63. Q. He, A. Toprac, and S.J. Qin (2002). [261e] - A New Thermal Model for the Hot-wall Low Pressure Chemical Vapor Deposition, AIChE Annual Meeting, Indianapolis, November, 2002. 64. M. Misra and S.J. Qin (2002). [271e] - On-line Wavelet Data Compression Using Adaptive Error Based Thresholding Criterion, AIChE Annual Meeting, Indianapolis, November, 2002. 65. J. Wang and S. Joe Qin (2001). SIMPCA: Subspace identification method via PCA. [Paper 279b], presented at AIChE Annual Meeting 2001, November 4-9, 2001, Reno, NV. 66. C.A.R McNabb and S. Joe Qin (2001). MIMO control performance monitoring based on subspace projections. [Paper 282b], presented at AIChE Annual Meeting 2001, November 4-9, 2001, Reno, NV. 67. Qin, S.J., S. Valle and M. Piovoso (2000). Analysis of multi-block PCA and PLS for fault detection and identification. AIChE Annual Meeting 2000, November, 2000, Los Angeles, CA. 68. W. Li and S.J. Qin (2000). Subspace identification models for dynamic sensor fault detection and diagnosis. AIChE Annual Meeting 2000, November, 2000, Los Angeles, CA. 69. J. Wang and S.J. Qin (2000). A new subspace identification approach based on principal component analysis. AIChE Annual Meeting 2000, November, 2000, Los Angeles, CA. 70. Yue, H. and S.J. Qin (2000). A wavelength selection method and its application in endpoint detection and fault detection. AEC/APC Symposium 2000, September 23-28, 2000, Tahoe, CA. 71. Scheid, G., S.J. Qin and T. Riley (1999). Run to Run Optimization, Monitoring, and Control on a Rapid Thermal Processor. Presented at AIChE Annual Meeting, Dallas, TX. 72. Yue, H., S.J. Qin, A. Toprac, and J. Wiseman (1999). Monitoring of Plasma Etching Processes Using High Resolution Optical Emission Spectroscopy. Presented at AIChE Annual Meeting, November 1-5, 1999, Dallas, TX. 73. McNabb, C. and S.J. Qin (1999). Block Decentralized MPC Control of a Kamyr Digester. Presented at AIChE Annual Meeting, November 1-5, 1999, Dallas, TX. 74. Misra, M., S.J. Qin, H. Yue and C. Ling (1999). Multivariate Sensor Data Validation and Compression Using Multi-scale PCA. Presented at AIChE Annual Meeting, November 1-5, 1999, Dallas, TX. 75. Valle-Cervantes, S. and S.J. Qin (1998). Determining the number of principal components. AIChE Annual Meeting, Nov. 16-20, 1998, Miami, FL. 76. Misra, M., S. Kumar, S.J. Qin, and R.S. Seemann (1998). A New Recursive On-line Technique for Wavelet Based Data Compression. AIChE Annual Meeting, November 16-20, 1998, Miami, FL. 77. Yue, H. and S. Joe Qin (1998). Fault Reconstruction and Subspace Control for Industrial Processes. AIChE Annual Meeting, November 16-20, 1998, Miami, FL. 78. S. Joe Qin, W. Li and H. Yue (1998). Adaptive process monitoring. FACSS Conf., October 11-15, 1998, Austin, TX. 79. Cheng, Y., R. Markle, S.J. Qin, T.F. Edgar, M. Gatto, and C. Nauert (1997). Modeling of OES data to estimate etch rate for etching equipment. Invited paper, SPIE’s 1997 Symposium on Microelectronic Manufacturing, October 1-2, 1997, Austin, TX. 80. Luo, R., M. Misra, S.J. Qin, R. Barton and D. M. Himmelblau (1997). Fault detection via multiscale analysis and nonparametric statistical inference. Presented at AIChE Annual Meeting, November, 1997, Los Angeles. 81. R. Dunia and Qin, S.J. (1997). Multidimensional fault detectability, identifiability, and reconstructability. Presented at AIChE Annual Meeting, November, 1997, Los Angeles. 82. Qin, S.J., H. Yue, R. Markle, C. Nauert, and M. Gatto (1997). Fault detection and classification of plasma etchers via optical spectroscopy analysis. Presented at AIChE Annual Meeting, November 16-21, 1997, Los Angeles, CA. 83. Dunia, R. and Qin, S.J. (1996). Fault detection and identification using principal component subspace models. Presented at AIChE Annual Meeting, November 10-15, 1996, Chicago. 84. Cheng, Y., Qin, S.J., and Edgar, T.F. (1996). Multi-PCA modeling for an etching process monitoring. Presented at AIChE Annual Meeting, November 10-15, 1996, Chicago. 85. Foss, B. and Qin, S.J. (1996). Nonlinear optimization-based control via interpolation. Presented at AIChE Annual Meeting, November 10-15, 1996, Chicago. 86. Lu, Z.J. and S. J. Qin (1996). A range control algorithm for model predictive control and unit optimization. Poster presented at AIChE Annual Meeting, November 10-15, 1996, Chicago. 87. Qin, S.J. (1993). A recursive PLS algorithm for system identification, AIChE Annual Meeting, November 7-12, 1993, St. Louis. 88. Qin, S.J. and McAvoy, T.J. (1992). Building nonlinear FIR models via a neural net PLS approach for long-term prediction. AIChE Annual Meeting, November 1-6, 1992, Miami. 89. Qin, S.J. and McAvoy, T.J. (1991). Neural net PLS approach to dynamic modeling: method and application. AIChE Annual Meeting, November, 1991, Los Angeles. PLENARY/KEYNOTE/INVITED PRESENTATIONS 1. Control Performance Monitoring: Theoretical Advancement and Practical Issues. Plenary Talk at the Annual Process Control Meeting of China, July 31 - Aug., 2004, Changchun, China 2. Control and Monitoring of Semiconductor Manufacturing Processes: Challenges and Opportunities, Invited Keynote to be presented at the 2004 IFAC DYCOPS-7 Symposium, Boston, MA, July 5-7. 3. APC in Semiconductor Manufacturing. Invited Panel Presentation and Discussions, Intel APC Submit, March 8 – 9, 2004, Rio Rancho, NM. 4. Statistical Process Monitoring: Basics and Beyond. Plenary Talk at the Annual Process Control Meeting of China, Aug. 16 – 17, 2003, Zhangjiajie, Hunan, China. 5. Process Monitoring for Feedback Systems. Gordon Research Conference on Statistics in Chemistry and Chemical Engineering, Invited Speaker, July 27-August 1, 2003, Mount Holyoke College, MA. 6. Process Chemometric Techniques and Applications, Plenary Talk, Advances in Process Analytics and Control Technology 2003 Conference (APACT 03), April 28-30, 2003, York, UK. 7. Statistical Process Monitoring: A Tutorial. Invited Keynote. AIChE Spring Meeting, New Orleans, LA, April 2, 2003. 8. Fault Detection and Diagnosis in Dynamic Processes with Maximal Sensitivity. Invited Talk at Louisiana Workshop on Systems Safety. Sponsored by NASA and Louisiana Board of Regents, Baton Rouge, LA, Feb. 28, 2003. 9. Process Systems Engineering in Microelectronics Manufacturing. Keynote, PSE-Asia, Taipei, Taiwan, December 4-6, 2002 10. Invited Speaker, AspenWorld 2002, October 27-31, 2002, Washington, D.C. 11. From Chemical Process Control to Semiconductor Manufacturing Control. Keynote, AEC/APC XIV Symposium, September 8-13, 2002. 12. Process Chemometrics, Invited Talk, International Chemometrics Research Meeting, Veldhoven, Netherlands, May 27-30, 2002 13. Subspace Approaches to Dynamic Modeling and Fault Diagnosis, Second Chemical Engineering Conference for Collaborative Research in Eastern Mediterranean, Ankara, Turkey, May 20 –24, 2001. 14. Fault Detection and Classification Theory for the User --- Tutorial. Presented at AEC/APC Symposium XII, September 23-28, 2000, Tahoe, CA. 15. Advanced Sensor Validation Methods, AspenWorld 2000, Orlando Florida, February 6-9, 2000 16. Nonlinear Predictive Control and Moving Horizon Estimation -- An Introductory Overview. An invited minicourse presented at 1999 European Control Conference, August 31 - September 3, Karlsruhe, Germany, with Frank Allgower, James Rawlings, Steven Wright, and Tom Badgwell. 17. An Overview of Nonlinear MPC Applications, Invited Plenary Keynote at the Workshop on Nonlinear Model Predictive Control - Assessment and Future Direction. Ascona, Switzerland, June 2 - 6, 1998. 18. Control Performance Monitoring - An Assessment, Invited talk at the NSF/NIST Vision 2020 Workshop on Process Measurement and Control, New Orleans, March 6-8, 1998. 19. An Overview of Model Predictive Control Technology, co-presented with Tom Badgwell, CPC-V, Tahoe, CA, January, 1996. 20. Building Intelligent Sensors with Neural Networks, Keynote at Fisher-Rosemount Systems Advanced Control Seminar, Birmingham, UK, November, 1995. 21. Building Intelligent Sensors with Neural Networks. Keynote at Monsanto PCI Meeting, St. Louis, May, 1995. INVITED SEMINAR PRESENTATIONS 1. Update on APC and FDC in Semiconductor Manufacturing, Seminar presented at Taiwan Semiconductor Manufacturing Company, Hsinchu, Taiwan, Oct. 8, 2004. 2. Integrated Systems Engineering for Semiconductor Manufacturing, Seminar in the Distinguished Seminar Series, Microelectronics Research Center, University of Texas at Austin, June 14, 2004 3. Systems Engineering Approach to Semiconductor Manufacturing, Seminar at Department of Chemical and Biological Engineering, University of Wisconsin, April 13, 2004 4. Process Integrity under Feedback Control and Optimization, Seminar at Department of Chemical Engineering, Queens University, March 17, 2004 5. Statistical Process Monitoring: Basics and Beyond, Seminar presented at Department of Chemical Engineering, National Taiwan University, Oct. 2, 2003. 6. Advanced Process Control in Semiconductor Processing – An Emerging Area in Process Control, Seminar presented at Taiwan Semiconductor Manufacturing Company, Hsinchu, Taiwan, Sept. 29, 2003. 7. Process Monitoring and Diagnosis Using Multi-block Analysis, Seminar presented at Department of Life Sciences, University of Amsterdam, August 25, 2003. 8. Subspace Approaches to Dynamic Model Identification and Fault Diagnosis, Seminar presented at Department of Automation, Tsinghua University, August 14, 2003. 9. Process Sensor Integrity under Feedback Control and Optimization, Seminar at Department of Chemical Engineering, University of Wisconsin, Nov. 26, 2002 10. Process Identification for Control, Seminar at National Instruments, Austin, TX, September 14, 2002 11. Subspace Approach to Fault Identification via Reconstruction. Seminar at the Department of Electrical Engineering, Linkoping University, March 19, 2002. 12. Overview of Industrial Model Predictive Control. Seminar at Chinese Academy of Sciences, Institute of Automation, Beijing, January 29, 2002. 13. Advanced Process Control in Semiconductor Processing – An Emerging Area in Process Control, Seminar presented at Department of Automation, Tsinghua University, January 28, 2002. 14. Advanced Process Control in Semiconductor Processing. Seminar presented at Mitsubishi Chemical, Tsukuba, Japan, January 24, 2002. 15. Overview of Research in Process Monitoring and Control. Seminar presented at Mitsubishi Chemical, Mitsushima, Japan, January 22, 2002. 16. Subspace Approaches to Dynamic Model Identification and Fault Diagnosis. Seminar at The Institute of Systems Theory, University of Stuttgart, November 21, 2001. 17. Overview of Subspace Approaches to Fault Detection and Diagnosis. Seminar presented at Department of Chemical Engineering, McMaster University, November 13, 2001. 18. Overview of Industrial Model Predictive Control. Seminar at the Department of Electrical Engineering, Linkoping University, October 25, 2001. 19. Overview of Industrial Model Predictive Control. Seminar at Network for Process Intelligence, Mid-Sweden University, October 24, 2001. 20. Overview of Industrial Model Predictive Control. Seminar at the Department of Signals, Sensors and Systems, Royal Institute of Technology, October 22, 2001. 21. Subspace Approaches to Dynamic Model Identification and Fault Diagnosis. Seminar at the Department of Electrical Engineering, Linkoping University, October 16, 2001. 22. Subspace Approaches to Dynamic Modeling and Fault Diagnosis. Seminar at the Department of Chemical Engineering, University of Alberta, October 5, 2001. 23. Industrial Model Predictive Control: An Updated Overview. Seminar presented at McMaster Automatic Control Consortium, McMaster University, May 17, 2001. 24. Subspace Approaches to Dynamic Modeling and Fault Diagnosis. Seminar at the Department of Chemical Engineering, Louisiana State University, April 6, 2001. 25. Fault Detection and Process Monitoring. Seminar at Weyerhaeuser Technology Center, Seattle, WA, March 30, 2001. 26. On-line data compression and validation using wavelets. Seminar at Weyerhaeuser Technology Center, Seattle, WA, March 29, 2001. 27. Process Monitoring and Control: An Evolving Game. Seminar at the Department of Chemical Engineering, University of California at Santa Barbara, March 1, 2001. 28. Subspace Model Identification and Its Applications in Process Control. Presented at Weyerhaeuser Technology Center, Seattle, WA, September 8, 2000. 29. Process Monitoring and Controller Performance Assessment: Are They Separable Tasks? Presented at Weyerhaeuser Technology Center, Seattle, WA, September 7, 2000. 30. Industrial MPC Applications -- An Updated Review. Presented at Norwegian Institute of Technology, April 12, 2000. 31. Dynamic Fault Detection and Identification with Maximized Sensitivity. Presented at Norwegian Institute of Technology, April 10, 2000. 32. Sensor and Process Fault Detection and Identification. Seminar at Department of Chemical Engineering, Kyoto University, June 29, 1999. 33. Between Open-loop and Closed-loop Control: Process Monitoring. Seminar at the Department of Chemical Engineering, Purdue University, April 1, 1999. 34. Sensor and Process Fault Detection and Identification. Seminar at the Department of Chemical Engineering, University of Maryland, March 18, 1999. 35. Sensor and Process Fault Detection and Identification. Seminar at the Central Research of DuPont, Wilmington, DE, March 19, 1999. 36. Fault Detection and Diagnosis, Seminar presented at ALCOA Technical Center, Nov. 1997. 37. Subspace Approach to Fault Detection and Diagnosis. Aerospace Engineering Department, UT-Austin, October 14, 1997. 38. A Geometric Approach to Fault Detection and Diagnosis. Seminar presented at the Department of Chemical Engineering, University of California at Santa Barbara, April 11, 1997. 39. Chemical Process Modeling, Monitoring, and Control, seminar presented at 3M, Austin, June, 1996 40. Multivariable Predictive Control Technology. Monsanto PCI Meeting, St. Louis, May 1996. 41. Sensor Validation. Neural Net Club Meeting at the University of Maryland, College Park, September, 1995. 42. Partial Least Squares for System Identification. Dept. of Chem. Eng., University of Texas, March, 1995. 43. Partial Least Squares for System Identification. Dept. of Chem. Eng., University of Houston, February, 1995. 44. Fuzzy Logic Uses in Process Control. Monsanto PCI Meeting, St. Louis, December, 1994. 45. Auto-tuned Fuzzy Control. TMCC Meeting at University of Texas at Austin. September, 1994. 46. Integrating Statistics with Neural Networks. Dept. of Chem. Eng., University of Newcastle upon Tyne, UK, June, 1992. 47. Neural Net PLS Approach to Soft Sensors. Engineering Dept. at Mobil Research and Development, Princeton, January, 1992. 48. Combining PCA and PLS with Neural Networks. Neural Network Technology Center at Du Pont, Wilmington, July 1991. SHORT COURSES 1. Applications of Run to Run Control and Fault Detection in Semiconductor Manufacturing. Short course presented at AEC/APC Symposium, Sept. 18, 2004, Denver, CO, with Tom Edgar. 2. Advanced Process and Equipment Control in Semiconductor Manufacturing. Short course presented at ITRI Taiwan, September 30- Oct. 1, 2003, Hsinchu, Taiwan. 3. Model Predictive Control and Monitoring. Four-day short-course presented at the Mid-Sweden University, Sweden, May, 2003. 4. Statistical Process Monitoring and Fault Diagnosis. Four-day short-course presented at the Mid-Sweden University, Sweden, May 21-24, 2002. 5. Run to Run Control and Fault Detection. Short course presented to Applied Materials, October 5-6, 2000, Salt Lake City, UT, with Tom Edgar and J. Campbell. 6. Run to Run Control and Fault Detection. Short course presented at AEC/APC Symposium XII, September 23-28, 2000, Tahoe, CA, with Tom Edgar and J. Campbell. 7. Multivariate Statistical Process Monitoring. Four-day seminar presented at the XVIII Chemical Engineering Seminar at the Instituto Tecnologico de Celaya, Mexico, January, 1998. 8. Advanced Process Monitoring and Control. Two-week course presented at Tsinghua University, Beijing, China, August 10-21, 1998. 9. Advanced Process Modeling and Control Courses, AMD, Inc., November, 1995; February, 1996; May, 1996; June, 1997. US PATENTS/DISCLOSURES1. Cherry, G., R. Good, and S.J. Qin (2003). Adaptive process monitoring with model updates based on selected events or constraints. U.S. patent pending. 2003 2. Wang, J., R. Chong, C. Bode, S.J. Qin, and A. Pasadyn (2002). Applying self-adaptive filter to a drifting process. U.S. patent pending. 2002 3. Qin, S.J. and John Guiver (2002). Sensor validation apparatus and method. US. Patent No. 6,356,857. March 12, 2002 4. Qin, S.J. (2001). Method and Apparatus for Fuzzy Logic Control with Automatic Tuning. US Patent No. 6,330,484, December 11, 2001. 5. Scheid, G., T. Riley, Q. Wang, M. Miller, and S.J. Qin (2001). Lot-to-lot rapid thermal processing (RTP) preheat optimization. U.S. Patent 6,268,270, July 31, 2001. 6. Misra, M., Kumar, S., Qin, S.J., and Seemann, D. (2001). Recursive on-line wavelet data compression technique for use in data storage and communications. US Patent 6,215,907, April 10, 2001. 7. R. Luo, S.J. Qin and D. Chen (2000). System and method for closed loop autotuning of PID controllers. US Patent 6,081,751, June 27, 2000. 8. Qin, S.J. and G. Borders (2000). Multi-region Fuzzy Logic Control Systems with Auxiliary Variables. US Patent 6,041,320, March 21, 2000. 9. Qin, S. J., M. Ott, and W. Wojsznis (1998). Method of Adapting and Applying Control Parameters in Non-linear Process Controllers. US Patent 5,748,467. May 5, 1998. 10. Qin, S. J., R. Dunia, and R. Hayes (1997). Method and Apparatus for Detecting and Identifying Faulty Sensors in a Process. US Patent No. 5,680,409. October 21, 1997.
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