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Management Suggestions for Process Control of Semiconductor Manufacturing: An Operations Research and Data Science Perspective

In: Computational Intelligence and Optimization Methods for Control Engineering

Author

Listed:
  • Marzieh Khakifirooz

    (Tecnológico de Monterrey)

  • Mahdi Fathi

    (Mississippi State University)

  • Chen Fu Chien

    (National Tsing Hua University)

  • Panos M. Pardalos

    (University of Florida)

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.

Suggested Citation

  • Marzieh Khakifirooz & Mahdi Fathi & Chen Fu Chien & Panos M. Pardalos, 2019. "Management Suggestions for Process Control of Semiconductor Manufacturing: An Operations Research and Data Science Perspective," Springer Optimization and Its Applications, in: Maude Josée Blondin & Panos M. Pardalos & Javier Sanchis Sáez (ed.), Computational Intelligence and Optimization Methods for Control Engineering, chapter 0, pages 245-274, Springer.
    • Handle: RePEc:spr:spochp:978-3-030-25446-9_11
    DOI: 10.1007/978-3-030-25446-9_11
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