  Smart Manufacturing refers to optimization techniques that are implemented in
production operations by utilizing advanced analytics approaches. With the
widespread increase in deploying Industrial Internet of Things (IIoT) sensors
in manufacturing processes, there is a progressive need for optimal and
effective approaches to data management. Embracing Machine Learning and
Artificial Intelligence to take advantage of manufacturing data can lead to
efficient and intelligent automation. In this paper, we conduct a comprehensive
analysis based on Evolutionary Computing and Deep Learning algorithms toward
making semiconductor manufacturing smart. We propose a dynamic algorithm for
gaining useful insights about semiconductor manufacturing processes and to
address various challenges. We elaborate on the utilization of a Genetic
Algorithm and Neural Network to propose an intelligent feature selection
algorithm. Our objective is to provide an advanced solution for controlling
manufacturing processes and to gain perspective on various dimensions that
enable manufacturers to access effective predictive technologies.
