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The Role of Big Dat...
The Role of Big Data in Industrial (Bio)chemical Process Operations
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- Udugama, Isuru A. (author)
- Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Kongens Lyngby, 2800, Denmark
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- Gargalo, Carina L. (author)
- Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Kongens Lyngby, 2800, Denmark
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- Yamashita, Yoshiyuki (author)
- Department of Chemical Engineering, Tokyo University of Agriculture and Technology, Koganei, Tokyo, 184-9599, Japan
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- Taube, Michael A. (author)
- S&D Consulting, Inc., Houston, Texas 77006, United States
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- Palazoglu, Ahmet (author)
- Department of Chemical Engineering, University of California, Davis, California 95616, United States
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- Young, Brent R. (author)
- Industrial Information and Control Centre, Department of Chemical & Materials Engineering, The University of Auckland, Auckland, 1010, New Zealand
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- Gernaey, Krist V. (author)
- Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Kongens Lyngby, 2800, Denmark
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- Kulahci, Murat (author)
- Luleå tekniska universitet,Industriell Ekonomi,Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, 2800, Denmark
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- Bayer, Christoph (author)
- Department of Process Engineering, TH Nürnberg, Nürnberg, 90489, Germany
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(creator_code:org_t)
- 2020-08-03
- 2020
- English.
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In: Industrial & Engineering Chemistry Research. - : American Chemical Society (ACS). - 0888-5885 .- 1520-5045. ; 59:34, s. 15283-15297
- Related links:
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https://backend.orbi...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- With the emergence of Industry 4.0 and Big Data initiatives, there is a renewed interest in leveraging the vast amounts of data collected in (bio)chemical processes to improve their operations. The objective of this article is to provide a perspective of the current status of Big-Data-based process control methodologies and the most effective path to further embed these methodologies in the control of (bio)chemical processes. Therefore, this article provides an overview of operational requirements, the availability and the nature of data, and the role of the control structure hierarchy in (bio)chemical processes and how they constrain this endeavor. The current state of the seemingly competing methodologies of statistical process monitoring and (engineering) process control is examined together with hybrid methodologies that are attempting to combine tools and techniques that belong to either camp. The technical and economic considerations of a deeper integration between the two approaches is then explored, and a path forward is proposed.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Tillförlitlighets- och kvalitetsteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Reliability and Maintenance (hsv//eng)
Keyword
- Kvalitetsteknik och logistik
- Quality technology and logistics
Publication and Content Type
- ref (subject category)
- art (subject category)
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