Joe Qin

Articles in Scholarly Journals [Incomplete List]

  1. Recent developments in multivariable controller performance monitoring?
    Journal of Process Control, vol. 17, no. 3, pp. 221–227, 2007
  2. A Curve Fitting Method for Detecting Valve Stiction in Oscillating Control Loops
    Industrial & Engineering Chemistry Research, vol. 46, no. 13, pp. 4549–4560, 2007
  3. Multiblock Principal Component Analysis Based on a Combined Index for Semiconductor Fault Detection and Diagnosis
    IEEE Transactions on Semiconductor Manufacturing, vol. 19, no. 2, pp. 159–172, 2006
  4. Semiconductor manufacturing process control and monitoring: A fab-wide framework
    Journal of Process Control, vol. 16, no. 3, pp. 179–191, 2006
  5. Closed-loop subspace identification using the parity space?
    Automatica, vol. 42, no. 2, pp. 315–320, 2006
  6. An overview of subspace identification
    Computers & Chemical Engineering, vol. 30, no. 10-12, pp. 1502–1513, 2006
  7. Fault detection and diagnosis based on modified independent component analysis
    AIChE Journal, vol. 52, no. 10, pp. 3501–3514, 2006
  8. A novel subspace identification approach with enforced causal models?
    Automatica, vol. 41, no. 12, pp. 2043–2053, 2005
  9. Projection based MIMO control performance monitoring: II??measured disturbances and setpoint changes
    Journal of Process Control, vol. 15, no. 1, pp. 89–102, 2005
  10. Industrial & Engineering Chemistry Research, vol. 44, no. 7, pp. 2117–2124, 2005
  11. Industrial & Engineering Chemistry Research, vol. 44, no. 8, pp. 2359–2368, 2005
  12. A new fault diagnosis method using fault directions in Fisher discriminant analysis
    AIChE Journal, vol. 51, no. 2, pp. 555–571, 2005
  13. Recursive Least Squares Estimation for Run-to-Run Control With Metrology Delay and Its Application to STI Etch Process
    IEEE Transactions on Semiconductor Manufacturing, vol. 18, no. 2, pp. 309–319, 2005
  14. Closed-loop subspace identification: an orthogonal projection approach
    Journal of Process Control, vol. 15, no. 1, pp. 53–66, 2005
  15. Industrial & Engineering Chemistry Research, vol. 43, no. 7, pp. 1701–1710, 2004
  16. A two-stage iterative learning control technique combined with real-time feedback for independent disturbance rejection*1
    Automatica, vol. 40, no. 11, pp. 1913–1922, 2004
  17. Adaptive generic model control for a class of nonlinear time-varying processes with input time delay
    Journal of Process Control, vol. 14, no. 5, pp. 517–531, 2004
  18. A strong tracking predictor for nonlinear processes with input time delay
    Computers & Chemical Engineering, vol. 28, no. 12, pp. 2523–2540, 2004
  19. Statistical process monitoring: basics and beyond
    Journal of Chemometrics, vol. 17, no. 8-9, pp. 480–502, 2003
  20. A survey of industrial model predictive control technology
    Control Engineering Practice, vol. 11, no. 7, pp. 733–764, 2003
  21. Computationally efficient modeling of wafer temperatures in a low-pressure chemical vapor deposition furnace
    IEEE Transactions on Semiconductor Manufacturing, vol. 16, no. 2, pp. 342–350, 2003
  22. Adaptive run-to-run control and monitoring for a rapid thermal processor
    Journal of Vacuum Science & Technology B: Microelectronics and Nanometer Structures, vol. 21, no. 1, p. 301, 2003
  23. Projection based MIMO control performance monitoring: I—covariance monitoring in state space
    Journal of Process Control, vol. 13, no. 8, pp. 739–757, 2003
  24. A new subspace identification approach based on principal component analysis
    Journal of Process Control, vol. 12, no. 8, pp. 841–855, 2002
  25. On the selection of variables for qualitative modelling of dynamical systems
    International Journal of General Systems, vol. 31, no. 5, pp. 435–467, 2002
  26. Multivariate process monitoring and fault diagnosis by multi-scale PCA
    Computers & Chemical Engineering, vol. 26, no. 9, pp. 1281–1293, 2002
  27. On unifying multiblock analysis with application to decentralized process monitoring
    Journal of Chemometrics, vol. 15, no. 9, pp. 715–742, 2001
  28. Detection and identification of faulty sensors in dynamic processes
    AIChE Journal, vol. 47, no. 7, pp. 1581–1593, 2001
  29. Sensor validation and process fault diagnosis for FCC units under MPC feedback
    Control Engineering Practice, vol. 9, no. 8, pp. 877–888, 2001
  30. Consistent dynamic PCA based on errors-in-variables subspace identification
    Journal of Process Control, vol. 11, no. 6, pp. 661–678, 2001
  31. Error based criterion for on-line wavelet data compression
    Journal of Process Control, vol. 11, no. 6, pp. 717–731, 2001
  32. Plasma etching endpoint detection using multiple wavelengths for small open-area wafers
    Journal of Vacuum Science & Technology A: Vacuum, Surfaces, and Films, vol. 19, no. 1, p. 66, 2001
  33. Determining the number of principal components for best reconstruction
    Journal of Process Control, vol. 10, no. 2-3, pp. 245–250, 2000
  34. Recursive PCA for adaptive process monitoring
    Journal of Process Control, vol. 10, no. 5, pp. 471–486, 2000
  35. Fault detection of plasma etchers using optical emission spectra
    IEEE Transactions on Semiconductor Manufacturing, vol. 13, no. 3, pp. 374–385, 2000
  36. On-line data compression and error analysis using wavelet technology
    AIChE Journal, vol. 46, no. 1, pp. 119–132, 2000
  37. Industrial & Engineering Chemistry Research, vol. 38, no. 11, pp. 4389–4401, 1999
  38. Industrial & Engineering Chemistry Research, vol. 37, no. 3, pp. 1024–1032, 1998
  39. Joint diagnosis of process and sensor faults using principal component analysis
    Control Engineering Practice, vol. 6, no. 4, pp. 457–469, 1998
  40. Subspace approach to multidimensional fault identification and reconstruction
    AIChE Journal, vol. 44, no. 8, pp. 1813–1831, 1998
  41. Control performance monitoring -- a review and assessment
    Computers & Chemical Engineering, vol. 23, no. 2, pp. 173–186, 1998
  42. Industrial & Engineering Chemistry Research, vol. 37, no. 6, pp. 2462–2468, 1998
  43. A unified geometric approach to process and sensor fault identification and reconstruction: the unidimensional fault case
    Computers & Chemical Engineering, vol. 22, no. 7-8, pp. 927–943, 1998
  44. Recursive PLS algorithms for adaptive data modeling
    Computers & Chemical Engineering, vol. 22, no. 4-5, pp. 503–514, 1998
  45. An Interpolating Model Predictive Control Strategy with Application to a Waste Treatment Plant
    Computers & Chemical Engineering, vol. 21, no. 1-2, pp. S881–S886, 1997
  46. Interpolating optimizing process control
    Journal of Process Control, vol. 7, no. 2, pp. 129–138, 1997
  47. Industrial & Engineering Chemistry Research, vol. 36, no. 5, pp. 1675–1685, 1997
  48. Nonlinear FIR modeling via a neural net PLS approach
    Computers & Chemical Engineering, vol. 20, no. 2, pp. 147–159, 1996
  49. Identification of faulty sensors using principal component analysis
    AIChE Journal, vol. 42, no. 10, pp. 2797–2812, 1996
  50. Use of principal component analysis for sensor fault identification
    Computers & Chemical Engineering, vol. 20, pp. S713–S718, 1996
  51. A multiregion fuzzy logic controller for nonlinear process control
    IEEE Transactions on Fuzzy Systems, vol. 2, no. 1, pp. 74–81, 1994
  52. Nonlinear PLS modeling using neural networks
    Computers & Chemical Engineering, vol. 16, no. 4, pp. 379–391, 1992