Computational Intelligence and Optimization Methods for Control Engineering

Abstract

With advances in information and telecommunication technologies and data-enabled decision-making, smart manufacturing can be an essential component of sustainable development. In the era of the smart world, semiconductor industry is one of the few global industries that are in a growth mode to smartness, due to worldwide demand. The promising significant opportunities to reduce cost, boost productivity, and improve quality in wafer manufacturing is based on the integration or combination of simulated replicas of actual equipment, Cyber-Physical Systems (CPS) and regionalized or decentralized decision-making into a smart factory. However, this integration also presents the industry with novel unique challenges. The stream of the data from sensors, robots, and CPS can aid to make the manufacturing smart. Therefore, it would be an increased need for modeling, optimization, and simulation to the value delivery from manufacturing data. This paper aims to review the success story of smart manufacturing in semiconductor industry with the focus on data-enabled decision-making and optimization applications based on “Operations Research” (OR) and “Data Science” (DS) perspective. In addition, we will discuss future research directions and new challenges to this industry.