Cited by 358Fault Detection and Control SystemsImpact of AI and Big Data on Business and SocietyDigital Transformation in Industry

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Advances and opportunities in machine learning for process data analytics

Qin, S. Joe, Chiang, Leo H.·2019·Computers & Chemical Engineering

DOI 10.1016/j.compchemeng.2019.04.003

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Abstract

Abstract In this paper we introduce the current thrust of development in machine learning and artificial intelligence, fueled by advances in statistical learning theory over the last 20 years and commercial successes by leading big data companies. Then we discuss the characteristics of process manufacturing systems and briefly review the data analytics research and development in the last three decades. We give three attributes for process data analytics to make machine learning techniques applicable in the process industries. Next we provide a perspective on the currently active topics in machine learning that could be opportunities for process data analytics research and development. Finally we address the importance of a data analytics culture. Issues discussed range from technology development to workforce education and from government initiatives to curriculum enhancement.

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Authors: Qin, S. J., & Chiang, L. H.
Affiliations: University of Southern California (US)
Dow Chemical (United States) (US)
Corresponding author: Qin, S. Joe
ORCID: Qin, S. Joe
Chiang, Leo H.
Venue: Computers & Chemical Engineering
Publisher: Elsevier BV
Published: 2019-07
Volume: 126
Pages: 465-473
ISSN: 0098-1354 (ISSN-L)
DOI: 10.1016/j.compchemeng.2019.04.003
OpenAlex: W2941089296
Semantic Scholar: 36cfd68da9e0c521c8b09ecf9ca48e0dbf24cc19
Cited by: 351
References: 88
Citations by year: 2026: 21 · 2025: 39 · 2024: 52 · 2023: 75 · 2022: 58 · 2021: 53 · 2020: 39 · 2019: 14
FWCI: 22.71
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: Computers & Chemical Engineering (publishedVersion)
Funders: University of Southern California
Topics: Physical Sciences › Engineering › Control and Systems Engineering › Fault Detection and Control Systems
Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
Keywords: machine learning, process manufacturing, statistical learning theory, big data, workforce education, curriculum development, government initiatives, chemical process industry

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Advances and opportunities in machine learning for process data analytics

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