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Proposing a maturity model for assessing Artificial Intelligence and Big data in the process industry

Author

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  • Rosanna Fornasiero
  • Lorenz Kiebler
  • Mohammadtaghi Falsafi
  • Saskia Sardesai

Abstract

Among digital technologies, Artificial Intelligence (AI) and Big Data (BD) have proven capability to support different processes, mainly in discrete manufacturing. Despite a number of AI and BD solutions and applications, no comprehensive assessment of their implementation is available for the Process Industry (i.e. cement, chemical and steel) and it is getting urgent to take into consideration specific operations. Grounding on literature and focus group interaction, this paper contributes to answering this gap by proposing a maturity model (MM) for AI and BD and assessing the current status of the application of these solutions in the process industry. Based on MMs available in the literature, a set of dimensions for the process industry has been identified and contextualised for assessing the level of maturity for AI and BD solutions. Results from applying the MM to a sample of European companies reveal that operations are supported by a relatively high level of maturity of AI and BD implementation with differences in the specific dimensions and operations where it is still necessary to invest. The MM can be used by companies both to self-assess and to benchmark with companies from the same or other sectors.

Suggested Citation

  • Rosanna Fornasiero & Lorenz Kiebler & Mohammadtaghi Falsafi & Saskia Sardesai, 2025. "Proposing a maturity model for assessing Artificial Intelligence and Big data in the process industry," International Journal of Production Research, Taylor & Francis Journals, vol. 63(4), pages 1235-1255, February.
    • Handle: RePEc:taf:tprsxx:v:63:y:2025:i:4:p:1235-1255
    DOI: 10.1080/00207543.2024.2372840
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