Title :
Feedforward learning applied to RTP of semiconductor wafers
Author :
Tao, K. Mike ; Kosut, Robert L. ; Ekblad, Mark ; Aral, Gurcan
Author_Institution :
Integrated Syst. Inc., Santa Clara, CA, USA
Abstract :
Our recent algorithmic results (1994) in feedforward learning control (LC) are applied to the control of semiconductor wafer temperature in a rapid thermal processing (RTP) reactor. Although the first attempt is experimental in nature, the results are very encouraging and deserve serious consideration. Applying this LC approach has resulted in a speed-up of a well-tuned feedback loop by a factor of 8 which amounts to more than 20 seconds saving in one processing step-quite significant for RTP. Additionally, the experiment has demonstrated the applicability of the LC theory in a real-world manufacturing setting. Many repetitive manufacturing tasks are potential applications of this LC procedure
Keywords :
feedback; feedforward; integrated circuit manufacture; intelligent control; learning systems; process control; rapid thermal processing; semiconductor device manufacture; temperature control; feedback loop; feedforward learning control; manufacturing; rapid thermal processing; semiconductor wafers; temperature control; Contracts; Control systems; Delay effects; Inductors; Manufacturing processes; Robust control; Stability; State feedback; Steady-state; Temperature control;
Conference_Titel :
Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on
Conference_Location :
Lake Buena Vista, FL
Print_ISBN :
0-7803-1968-0
DOI :
10.1109/CDC.1994.410927