PROCESS MODELING AND CONTROL. T.F. Edgar The Department of Chemical Engineering. The University of Texas at Austin
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1 PROCESS MODELING AND CONTROL T.F. Edgar The Department of Chemical Engineering The Uniersity of Texas at Austin What is process modeling and control Why improe the technology Process control research in our department
2 Ensure safe plant operation Meet product specifications Optimize economic performance MIMO (s. SISO) models Nonlinear (s. linear) models Stochastic ariables Large number of ariables
3 TWMCC Texas-Wisconsin Modeling and Contr ol Consortium T. F. Edgar Co-Director The Uniersity of Texas at Austin Department of Chemical Engineering Austin, Texas Tel: (512) Fax: (512) J. B. Rawlings Co-Director Uniersity of Wisconsin-Madison Department of Chemical Engineering Madison, Wisconsin Tel: (608) Fax: (608) Control System Monitoring and Diagnosis Dynamic Modeling of Chemical Processes Materials Processing Dynamic System Identification NMPC and Moing Horizon Predictions Optimization Theory and Algorithms Statistical Process Monitoring/Fault Diagnosis 3
4 TWCCC - Multiple Projects Company JBR TFE JQ Abbott Labs AMD Aspentech Chemstations Cheron Eastman ExxonMobil Emerson Proc. Mgt. Johnson Control Praxair Samsung Shell Texas Instruments Tokyo Electron Weyerhaeuser Courting Dow, Boise, Air Liquide, Bayer, Freescale, Intel, Honeywell, TOTAL, Capstone Technology, TresArk 4
5 M.S., Ph.D. Graduates ( ) Student/Superisor Destination J. Wang (JQ) Ph.D. (5/04) Auburn Uniersity E. Haseltine (JBR) Ph.D. (12/04) Vertex Pharmaceuticals R. Good (JQ) Ph.D. (8/04) AMD W. Lin (JQ) Ph.D. (5/05) Postdoc (U. Minn) P. He (JQ) Ph.D. (5/05) Tuskegee Uniersity J. Hedengren (TFE) Ph.D. (5/05) ExxonMobil W. Cho (TFE) Ph.D. (5/05) Consultant E. Hale (JQ) Ph.D. (8/05) NREL R. Chong (TFE) M.S. (8/05) AMD L. Rueda (TFE) Ph.D. (12/05) Shell S. Harrison (TFE) Ph.D. (5/06) AMD D. Castineira (TFE) Ph.D. (5/06) Shell C. Harrison (JQ) Ph.D. (5/06) Marathon Oil A. Venkat (JBR) Ph.D. (5/06) Shell K. Chamness (TFE) Ph.D. (12/06) Spansion (AMD) G. Cherry (JQ) Ph.D. (12/06) AMD 5
6 Student/Superisor M.S., Ph.D. Graduates ( ) Destination T. Farmer (TFE) Ph.D. (5/07) Capital One J. Yu (JQ) Ph.D. (5/07) Shell P. Larsen (JBR) Ph.D. (7/07) Dow E. Mastny (JBR) Ph.D. (7/07) BP Alaska M. Rajamani (JBR) Ph.D. (10/07) BP C. Schoene (JQ) Ph.D. (12/07) Multiphase Solutions Y. Cai (JQ) Ph.D. (8/08) Freescale A. Prabhu (TFE) Ph.D. (8/08) Air Liquide H. Lee (TFE) Ph.D. (8/08) Intel Y. Zhang (TFE) Ph.D. (8/08) ExxonMobil B. Bregenzer (JQ) Ph.D. (12/08) Interiewing D. Weber (TFE) Ph.D. (8/09) Shell Oil S. Abrol (TFE) Ph.D. (8/09) Interiewing B. Parkinson (TFE) M.S. (8/09) Interiewing 6
7 Edgar Group Highlights 3 PhD s graduated in papers in journals/proceedings published or in press since 1/ new students and 1 postdoc added to group in B. Gill IIT; D. French Ohio State; B. Parkinson Idaho State; K. Han Seoul N.U AEC/APC Student Paper Award (B. Parkinson) T. Edgar selected as IFAC Fellow 7
8 Ph.D Candidates Graduated in Yang Zhang (8/08): Improed Methods in Statistical and First Principles Modeling for Batch Process Control and Monitoring 2. Amogh Prabhu (8/08): Performance Monitoring of Run-to-Run Control Systems used in Semiconductor Manufacturing 3. Hyung Lee (8/08): Adanced Process Control and Optimal Sampling in Semiconductor Manufacturing 8
9 Yang Zhang First Principles Modeling - Proposed new algorithm for dynamic DOE (P-optimal) - Successfully tested on simulated industrial processes - Getting data from industrial Broadley- James Statistical Modeling - Proposed new PCA-based algorithm for data synchronization and on-line monitoring - Algorithm package is being commercialized by Emerson - On-site software Lubrizol, Broadley-James 9
10 Amogh Prabhu Deeloped performance monitoring methodology for run-to-run EWMA controllers, alidated on industrial data Missing data estimation performed using data reconstruction for processing monitoring New method for state estimation for high mix semiconductor manufacturing facilities PID controller optimization for nonlinear processes 10
11 Hyung Lee Dynamic sampling methodology depends on the characteristics of the process and disturbances - When the process has little ariation, dynamic sampling has little effect but does not degrade the control performance The online dynamic sampling algorithm was extended for high-mix manufacturing Using integrated scatterometry with W2W FB control can correct for ariations of an etch chamber oer time within a lot Constrained multiariable control in etch is required to achiee better manufacturing performance with more CVs (CD, sidewall angle, uniformity) 11
12 Edgar Group Project Areas Multiariable Control/Estimation Semiconductor Manufacturing Monitoring and Control Optimization of Petroleum Reseroir Production Flue Gas CO 2 Remoal Strategies (Modeling, Control, Optimization) Model-based Fault Detection Diabetes Closed-loop Control 12
13 Multiariable Control and Estimation D. French Wireless feedback control (Emerson Process Management) D. Thiele Model predictie control performance enhancements from dynamic state feedback update (Emerson Process Management) J. Lee (postdoc) Various topics in multiariable control (e.g., multiloop PI controller design, interaction analysis) S. Abrol Use of ISAT in operating training simulators (Chemstations) I. Castillo Fundamental model-based fault detection (Roberto Rocca Fellowship) B. Spiey On-line estimation using fundamental models (NSF IGERT, joint with John Ekerdt) 13
14 Semiconductor Manufacturing Modeling/Control New student Trade-offs between performance and measurement (AMD) New student Control loop performance monitoring (Texas Instruments) B. Parkinson Optimization of plasma etch processing (Tokyo Electron) K. Baek Sensor selection and ealuation for plasma etching (Samsung) K. Han Run to run control (Korean Goernment postdoctoral fellowship) B. Gill soft sensors in etch processes (Texas Instruments) 14
15 Other Projects D. Weber Petroleum reseroir production optimization (Joint with Larry Lake Oil Company Consortium) S. Ziaii CO 2 absorption process modeling and control/power plant energy integration (Joint with Gary Rochelle U.S. DOE and UT Carbon Management Consortium) New student Dynamic modeling of blood glucose in Type 2 diabetes 15
16 Recent Publications/Presentations Multiariate Statistical Process Control by Yang Zhang and T.F. Edgar; Chapter 8 in New Directions in Bioprocess Modeling and Control by G. McMillan and M. Boudreau (ISA) Performance Assessment of Run-to-Run EWMA Controllers, IEEE Trans. Semiconductor Manufacturing, Vol. 20(4), (2007) Run-to-Run Control and State Estimation in High-Mix Semiconductor Manufacturing Annual Reiews in Control, Vol. 31, pp (2007) Keynote Presentation at AdConip Conference (Jasper, Alberta): Process Control Batch to the Future 16
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