Title :
Real time plasma etch process modeling by neural networks
Author :
Si, Jennie ; Tseng, Yuan-Ling ; Clayton, Mike ; Felker, Steve ; Yoo, Bob ; Martinez, Jim ; Durham, Jim ; Dang, Kim
Author_Institution :
Motorola Inc., Mesa, AZ, USA
Abstract :
We address the problem of control relevant process modeling from production data for the N-well reactive ion etching processed by LAM Rainbow Etchers. Due to physical constraints we consider building an empirical neural network model using one lot of data which usually contains 24 wafers. Using the existence result of feedforward networks as universal approximators, we experimentally developed different network structures as models of the etching process under investigation. Our results are built upon extensive simulations on different lots of the process. The same modeling idea is also extended to use the network model to predict the end point detection signal prior for the processing of one wafer
Keywords :
digital simulation; discrete time systems; feedforward neural nets; function approximation; nonlinear dynamical systems; process control; recurrent neural nets; sputter etching; LAM Rainbow Etchers; N-well reactive ion etching; control relevant process modeling; empirical neural network model; end point detection signal prior; feedforward networks; physical constraints; real time plasma etch process modeling; universal approximators; Buildings; Etching; Neural networks; Plasma applications; Predictive models; Process control; Production; Semiconductor device modeling; Signal detection; Signal processing;
Conference_Titel :
Emerging Technologies and Factory Automation Proceedings, 1997. ETFA '97., 1997 6th International Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
0-7803-4192-9
DOI :
10.1109/ETFA.1997.616294