초록 ▼

A method is provided, the method comprising sampling at least one parameter characteristic of processing performed on a workpiece in at least one processing step, and modeling the at least one characteristic parameter sampled using an adaptive sampling processing model, treating sampling as an integ

A method is provided, the method comprising sampling at least one parameter characteristic of processing performed on a workpiece in at least one processing step, and modeling the at least one characteristic parameter sampled using an adaptive sampling processing model, treating sampling as an integrated part of a dynamic control environment, varying the sampling based upon at least one of situational information, upstream events and requirements of run-to-run controllers. The method also comprises applying the adaptive sampling processing model to modify the processing performed in the at least one processing step.

대표청구항 ▼

What is claimed: 1. A method comprising: sampling at least one parameter characteristic of processing performed on a workpiece in at least one processing step in accordance with a sampling rate; modeling the at least one characteristic parameter sampled using an adaptive sampling processing model,

What is claimed: 1. A method comprising: sampling at least one parameter characteristic of processing performed on a workpiece in at least one processing step in accordance with a sampling rate; modeling the at least one characteristic parameter sampled using an adaptive sampling processing model, treating sampling as an integrated part of a dynamic control environment, varying the sampling rate based upon at least one of situational information, upstream events and requirements of run-to-run controllers; and applying the adaptive sampling processing model to modify the processing performed in the at least one processing step. 2. The method of claim 1, wherein sampling the at least one parameter characteristic of the processing performed on the workpiece in the processing step comprises monitoring the at least one characteristic parameter using an advanced process control (APC) system. 3. The method of claim 2, wherein monitoring the at least one characteristic parameter using the advanced process control (APC) system comprises using the advanced process control (APC) system to monitor at least one tool variable of a processing tool during the processing step. 4. The method of claim 3, wherein modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 5. The method of claim 4, wherein applying the adaptive sampling processing model to modify the processing performed in the processing step comprises tuning the at least one tuning parameter to improve the processing performed in the processing step. 6. The method of claim 2, wherein modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 7. The method of claim 6, wherein applying the adaptive sampling processing model to modify the processing performed in the processing step comprises tuning the at least one tuning parameter to improve the processing performed in the processing step. 8. The method of claim 1, wherein modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 9. The method of claim 8, wherein using the adaptive sampling processing model incorporating the at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having the at least one tuning parameter comprises using the adaptive sampling processing model incorporating at least one of a closed-loop model predictive control (MPC) controller and a closed-loop proportional-integral-derivative (PID) controller having the at least one tuning parameter. 10. The method of claim 8, wherein applying the adaptive sampling processing model to modify the processing performed in the processing step comprises tuning the at least one tuning parameter to improve the processing performed in the processing step. 11. The method of claim 1, wherein varying the sampling rate comprises at least one of increasing and decreasing the sampling rate. 12. The device of claim 1, comprising means for at least one of increasing and decreasing the sampling rate. 13. A computer-readable, program storage device, encoded with instructions that, when executed by a computer, perform a method comprising: sampling at least one parameter characteristic of processing performed on a workpiece in at least one processing step in accordance with a sampling rate; modeling the at least one characteristic parameter sampled using an adaptive sampling processing model, treating sampling as an integrated part of a dynamic control environment, varying the sampling rate based upon at least one of situational information, upstream events and requirements of run-to-run controllers; and applying the adaptive sampling processing model to modify the processing performed in the at least one processing step. 14. The device of claim 13, wherein sampling the at least one parameter characteristic of the processing performed on the workpiece in the processing step comprises monitoring the at least one characteristic parameter using an advanced process control (APC) system. 15. The device of claim 14, wherein monitoring the at least one characteristic parameter using the advanced process control (APC) system comprises using the advanced process control (APC) system to monitor at least one tool variable of a rapid thermal processing tool during the processing step. 16. The device of claim 15, wherein modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 17. The device of claim 16, wherein applying the adaptive sampling processing model to modify the processing performed in the processing step comprises tuning the at least one tuning parameter to improve the processing performed in the processing step. 18. The device of claim 14, wherein modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 19. The device of claim 18, wherein applying the adaptive sampling processing model to modify the processing performed in the processing step comprises tuning the at least one tuning parameter to improve the processing performed in the processing step. 20. The device of claim 13, wherein modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 21. The device of claim 20, wherein using the adaptive sampling processing model incorporating the at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having the at least one tuning parameter comprises using the adaptive sampling processing model incorporating at least one of a closed-loop model predictive control (MPC) controller and a closed-loop proportional-integral-derivative (PID) controller having the at least one tuning parameter. 22. The device of claim 20, wherein applying the adaptive sampling processing model to modify the processing performed in the processing step comprises tuning the at least one tuning parameter to improve the processing performed in the processing step. 23. The computer-readable, program storage device of claim 13, encoded with instructions that, when executed by a computer, perform a method comprising at least one of increasing and decreasing the sampling rate. 24. A computer programmed to perform a method comprising: sampling at least one parameter characteristic of processing performed on a workpiece in at least one processing step in accordance with a sampling rate; modeling the at least one characteristic parameter sampled using an adaptive sampling processing model, treating sampling as an integrated part of a dynamic control environment, varying the sampling rate based upon at least one of situational information, upstream events and requirements of run-to-run controllers; and applying the adaptive sampling processing model to modify the processing performed in the at least one processing step. 25. The computer of claim 24, wherein sampling the at least one parameter characteristic of the processing performed on the workpiece in the processing step comprises monitoring the at least one characteristic parameter using an advanced process control (APC) system. 26. The computer of claim 25, wherein monitoring the at least one characteristic parameter using the advanced process control (APC) system comprises using the advanced process control (APC) system to monitor at least one tool variable of a rapid thermal processing tool during the processing step. 27. The computer of claim 26, wherein modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 28. The computer of claim 27, wherein applying the adaptive sampling processing model to modify the processing performed in the processing step comprises tuning the at least one tuning parameter to improve the processing performed in the processing step. 29. The computer of claim 25, wherein modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 30. The computer of claim 29, wherein applying the adaptive sampling processing model to modify the processing performed in the processing step comprises tuning the at least one tuning parameter to improve the processing performed in the processing step. 31. The computer of claim 24, wherein modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 32. The computer of claim 31, wherein using the adaptive sampling processing model incorporating the at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having the at least one tuning parameter comprises using the adaptive sampling processing model incorporating at least one of a closed-loop model predictive control (MPC) controller and a closed-loop proportional-integral-derivative (PID) controller having the at least one tuning parameter. 33. The computer of claim 31, wherein applying the adaptive sampling processing model to modify the processing performed in the processing step comprises tuning the at least one tuning parameter to improve the processing performed in the processing step. 34. The computer of claim 24, programmed to perform a method comprising at least one of increasing and decreasing the sampling rate. 35. A method comprising: sampling at least one parameter characteristic of processing performed on a workpiece in at least one processing step in accordance with a sampling rate; modeling the at least one characteristic parameter sampled using an adaptive sampling processing model, treating sampling as an integrated part of a dynamic control environment, varying the sampling rate based upon at least one of situational information comprising at least one of an amount of variation in recent data and a rate of change in the variation in the recent data, upstream events comprising at least one of maintenance in a process upstream and changes in the process upstream, and requirements of run-to-run controllers attempting to identify control model parameters; and applying the adaptive sampling processing model to modify the processing performed in the at least one processing step. 36. The method of claim 35, wherein sampling the at least one parameter characteristic of the processing performed on the workpiece in the processing step comprises monitoring the at least one characteristic parameter using an advanced process control (APC) system. 37. The method of claim 26, wherein monitoring the at least one characteristic parameter using the advanced process control (APC) system comprises using the advanced process control (APC) system to monitor at least one tool variable of a rapid thermal processing tool during the processing step. 38. The method of claim 37, wherein modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 39. The method of claim 38, wherein applying the adaptive sampling processing model to modify the processing performed in the processing step comprises tuning the at least one tuning parameter to improve the processing performed in the processing step. 40. The method of claim 36, wherein modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 41. The method of claim 40, wherein applying the adaptive sampling processing model to modify the processing performed in the processing step comprises tuning the at least one tuning parameter to improve the processing performed in the processing step. 42. The method of claim 35, wherein modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 43. The method of claim 42, wherein using the adaptive sampling processing model incorporating the at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having the at least one tuning parameter comprises using the adaptive sampling processing model incorporating at least one of a closed-loop model predictive control (MPC) controller and a closed-loop proportional-integral-derivative (PID) controller having the at least one tuning parameter. 44. The method of claim 42, wherein applying the adaptive sampling processing model to modify the processing performed in the processing step comprises tuning the at least one tuning parameter to improve the processing performed in the processing step. 45. The method of claim 35, wherein varying the sampling rate comprises at least one of increasing and decreasing the sampling rate. 46. A system comprising: a tool for sampling at least one parameter characteristic of processing performed on a workpiece in at least one processing step in accordance with a sampling rate; a computer for modeling the at least one characteristic parameter sampled using an adaptive sampling processing model, treating sampling as an integrated part of a dynamic control environment, varying the sampling rate based upon at least one of situational information, upstream events and requirements of run-to-run controllers; and a controller for applying the adaptive sampling processing model to modify the processing performed in the at least one processing step. 47. The system of claim 46, wherein the tool for sampling the at least one parameter characteristic of the processing performed on the workpiece in the at least one processing step comprises a monitor for monitoring the at least one characteristic parameter using an advanced process control (APC) system. 48. The system of claim 47, wherein the advanced process control (APC) system monitors at least one tool variable of at least one processing tool during the at least one processing step. 49. The system of claim 48, wherein the computer modeling the at least one characteristic parameter measured uses an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 50. The system of claim 49, wherein the controller applying the adaptive sampling processing model to modify the processing performed in the at least one processing step tunes the at least one tuning parameter to improve the processing performed in the at least one processing step. 51. The system of claim 47, wherein the computer modeling the at least one characteristic parameter sampled uses an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 52. The system of claim 51, wherein the controller applying the adaptive sampling processing model to modify the processing performed in the at least one processing step tunes the at least one tuning parameter to improve the processing performed in the at least one processing step. 53. The system of claim 46, wherein the computer modeling the at least one characteristic parameter sampled uses an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 54. The system of claim 53, wherein the computer uses the adaptive sampling processing model incorporating at least one of a closed-loop model predictive control (MPC) controller and a closed-loop proportional-integral-derivative (PID) controller having the at least one tuning parameter. 55. The system of claim 53, wherein the controller applying the adaptive sampling processing model to modify the processing performed in the at least one processing step tunes the at least one tuning parameter to improve the processing performed in the at least one processing step. 56. The system of claim 46, wherein the computer performs at least one of increasing and decreasing the sampling rate. 57. A device comprising: means for sampling at least one parameter characteristic of processing performed on a workpiece in at least one processing step in accordance with a sampling rate; means for modeling the at least one characteristic parameter sampled using an adaptive sampling processing model, treating sampling as an integrated part of a dynamic control environment, varying the sampling rate based upon at least one of situational information, upstream events and requirements of run-to-run controllers; and means for applying the adaptive sampling processing model to modify the processing performed in the at least one processing step. 58. The device of claim 57, wherein the means for sampling the at least one parameter characteristic of the processing performed on the workpiece in the at least one processing step comprises means for monitoring the at least one characteristic parameter using an advanced process control (APC) system. 59. The device of claim 58, wherein the means for monitoring the at least one characteristic parameter using the advanced process control (APC) system comprises using the advanced process control (APC) system to monitor at least one tool variable of at least one processing tool during the at least one processing step. 60. The device of claim 59, wherein the means for modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises means for using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 61. The device of claim 60, wherein the means for applying the adaptive sampling processing model to modify the processing performed in the at least one processing step comprises means for tuning the at least one tuning parameter to improve the processing performed in the at least one processing step. 62. The device of claim 58, wherein the means for modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises means for using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 63. The device of claim 62, wherein the means for applying the adaptive sampling processing model to modify the processing performed in the at least one processing step comprises means for tuning the at least one tuning parameter to improve the processing performed in the at least one processing step. 64. The device of claim 57, wherein the means for modeling the at least one characteristic parameter sampled using the adaptive sampling processing model comprises means for using an adaptive sampling processing model incorporating at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having at least one tuning parameter. 65. The device of claim 64, wherein the means for using the adaptive sampling processing model incorporating the at least one of a model predictive control (MPC) controller and a proportional-integral-derivative (PID) controller having the at least one tuning parameter comprises the means for using the adaptive sampling processing model incorporating at least one of a closed-loop model predictive control (MPC) controller and a closed-loop proportional-integral-derivative (PID) controller having the at least one tuning parameter. 66. The device of claim 64, wherein the means for applying the adaptive sampling processing model to modify the processing performed in the at least one processing step comprises means for tuning the at least one tuning parameter to improve the processing performed in the at least one processing step.