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Digital twins implementations in the chemical industry with a focus on soda ash production: a literature review

  • Sławomir Szczeblewski ORCID logo EMAIL logo und Jacek Gębicki ORCID logo
Veröffentlicht/Copyright: 3. November 2025
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Chemical Product and Process Modeling
Aus der Zeitschrift Chemical Product and Process Modeling

Abstract

The implementation of digital twins, which serve as digital representations of physical industrial installations and their associated industrial processes, is a rapidly evolving technology aligned with the core principles of Industry 4.0 and 5.0. A digital industrial installation enables the collection of data from the real environment for the purpose of reproducing, validating, and simulating both the current and predictive behavior of physical production systems. The aim of this systematic literature review is to provide a comprehensive overview of digital twin technology in the context of the challenges and limitations associated with its implementation in the chemical industry. By employing the method of systematic literature review, the study identified areas of real implementations in the chemical industry, describing both the software applied and the types of processes optimized through the use of digital twins. The findings demonstrate that digital twins represent an innovation within the chemical domain and constitute dynamically evolving methods for process analysis.

Keywords: industry 5.0; digital twin; soda ash production; chemical engineering computing; chemical industry
Corresponding author: Sławomir Szczeblewski, Department of Process Engineering and Chemical Technology, Faculty of Chemistry, Gdansk University of Technology, G. Narutowicza Street 11/12, 80-233, Gdansk, Poland; and Soda Production Department, Qemetica Soda Polska, Fabryczna Street 4, 88-101, Inowrocław, Poland, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: Chat GPT: to improve translation.

  5. Conflict of interest: All other authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Received: 2025-07-08
Accepted: 2025-10-18
Published Online: 2025-11-03

© 2025 Walter de Gruyter GmbH, Berlin/Boston

https://doi.org/10.1515/cppm-2025-0166
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industry 5.0; digital twin; soda ash production; chemical engineering computing; chemical industry
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