Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/103303
Title: Development of smart semiconductor manufacturing : operations research and data science perspectives
Authors: Khakifirooz, Marzieh
Fathi, Mahdi
Wu, Kan
Keywords: Cloud Computing
Engineering::Mechanical engineering
Cyber-physical Space
Issue Date: 2019
Source: Khakifirooz, M., Fathi, M., & Wu, K. (2019). Development of smart semiconductor manufacturing : operations research and data science perspectives. IEEE Access, 7, 108419-108430. doi:10.1109/ACCESS.2019.2933167
Series/Report no.: IEEE Access
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 important opportunities that can boost the cost reduction of productivity and improve quality in wafer fabrication are based on the simulations of actual environment in Cyber-Physical Space and integrate them with decentralized decision-making systems. However, this integration faced the industry with novel unique challenges. The stream of the data from sensors, robots, and Cyber-Physical Space can aid to make the manufacturing smart. Therefore, it would be an increased need for modeling, optimization, and simulation for 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 and data science perspective. In addition, we will discuss future research directions and new challenges for this industry.
URI: https://hdl.handle.net/10356/103303
http://hdl.handle.net/10220/49962
DOI: http://dx.doi.org/10.1109/ACCESS.2019.2933167
Rights: © 2019 IEEE. This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license*, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given.
metadata.item.grantfulltext: open
metadata.item.fulltext: With Fulltext
Appears in Collections:MAE Journal Articles

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