DocumentCode :
2516482
Title :
Comparison of statistical and neural-fuzzy approaches to process control applications
Author :
Vaidhyanathan, Balasubramanian ; Li, Hua Harry ; Sun, Shan
Author_Institution :
Texas Tech. Univ., Lubbock, TX, USA
fYear :
1996
fDate :
14-16 Oct 1996
Firstpage :
467
Abstract :
During the past few years, we have been witnessing the increasing use of artificial neural network and fuzzy logic approaches to semiconductor equipment and manufacturing process control. However, there is a lack of objective evaluation of these new techniques to the existing statistically based, or PID control techniques. In this paper, we would like to review, survey, and perform comparisons of the effectiveness of these proposed techniques. We first will address the attractive features of each technique, their design procedures, applicability to various different control problems, and their limitations. Then, we will propose a general guideline for practioners and design engineers to select an appropriate design technique. We will also address the major theoretical challenges in this field
Keywords :
fuzzy control; neurocontrollers; process control; semiconductor device manufacture; three-term control; PID control; artificial neural network; fuzzy logic; process control; semiconductor manufacturing; statistical control; Artificial neural networks; Electronic mail; Fuzzy logic; Guidelines; Manufacturing processes; Neural networks; Neurons; Process control; Sun; Three-term control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics Manufacturing Technology Symposium, 1996., Nineteenth IEEE/CPMT
Conference_Location :
Austin, TX
ISSN :
1089-8190
Print_ISBN :
0-7803-3642-9
Type :
conf
DOI :
10.1109/IEMT.1996.559789
Filename :
559789
Link To Document :
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