Title :
A CVD epitaxial deposition in a vertical barrel reactor: process modeling using cluster-based fuzzy logic models
Author :
Chiou, J.C. ; Yang, J.Y.
Author_Institution :
Dept. of Electr. & Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
fDate :
11/1/1998 12:00:00 AM
Abstract :
A chemical vapor deposition (CVD) epitaxial deposition process modeling using fuzzy logic models (FLM´s) has been proposed. The process modeling algorithm consists of a cluster estimation method and backpropagation algorithm to construct a number of modeling structures from the training data. A decision rule based on the multiple correlation factor is used to obtain the optimum structure of the fuzzy model using the testing data. Upon the optimum structure being reached, the gradient-descent method is used to refer the parameters of the final fuzzy model using both training and testing data. The algorithm has been applied to a nonlinear function and a vertical chemical vapor deposition process. The results demonstrate the efficiency and effectiveness of the proposed fuzzy logic model in comparison with existing fuzzy logic models and artificial neural network models
Keywords :
backpropagation; estimation theory; fuzzy logic; identification; semiconductor process modelling; vapour phase epitaxial growth; CVD epitaxial deposition; backpropagation algorithm; chemical vapor deposition; cluster estimation method; cluster-based fuzzy logic models; decision rule; gradient-descent method; multiple correlation factor; nonlinear function; process modeling; training data; vertical CVD process; vertical barrel reactor; Backpropagation algorithms; Chemical vapor deposition; Clustering algorithms; Fuzzy logic; Inductors; Input variables; Manufacturing processes; Process control; Semiconductor process modeling; Testing;
Journal_Title :
Semiconductor Manufacturing, IEEE Transactions on
