Foundation Models for the Process Industry: Challenges and Opportunities

With the emergence of general foundational models, such as Chat Generative Pre-trained Transformer (ChatGPT), researchers have shown considerable interest in the potential applications of foundation models in the process industry. This paper provides a comprehensive overview of the challenges and opportunities presented by the use of foundation models in the process industry, including the frameworks, core applications, and future prospects. First, this paper proposes a framework for foundation models for the process industry. Second, it summarizes the key capabilities of industrial foundation models and their practical applications. Finally, it highlights future research directions and identifies unresolved open issues related to the use of foundation models in the process industry.

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Publication Details

Journal
Engineering
Published
2025-03-29
DOI
https://doi.org/10.1016/j.eng.2025.03.023
Citations
14
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
Field-Weighted Citation Impact
16.03

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article

Foundation Models for the Process Industry: Challenges and Opportunities

Lei Ren, Keke Huang, Haiteng Wang, Lihui Wang et al.
14 citations
Engineering
Reservoir Engineering and Simulation Methods
16.03
article

Foundation Models for the Process Industry: Challenges and Opportunities

Lei Ren, Keke Huang, Haiteng Wang, Lihui Wang, Yuqing Wang, Bohu Li
article en
14 citations

Abstract

With the emergence of general foundational models, such as Chat Generative Pre-trained Transformer (ChatGPT), researchers have shown considerable interest in the potential applications of foundation models in the process industry. This paper provides a comprehensive overview of the challenges and opportunities presented by the use of foundation models in the process industry, including the frameworks, core applications, and future prospects. First, this paper proposes a framework for foundation models for the process industry. Second, it summarizes the key capabilities of industrial foundation models and their practical applications. Finally, it highlights future research directions and identifies unresolved open issues related to the use of foundation models in the process industry.

EngineeringVol. 52
Central South University (CN), Beihang University (CN), KTH Royal Institute of Technology (SE)
National Natural Science Foundation of China
Openalex Percentile: Top 1%
Reservoir Engineering and Simulation Methods
16.03
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