Comparison of statistical and neural-fuzzy approaches to process control applications

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.