Using dynamic life cycle assessment to evaluate the effects of industry digitalization: A steel case study.

Decarbonization of steelmaking has stagnated while it has a considerable share of global greenhouse gas emissions and a growing demand. Digitalization is seen as a viable option to reduce emissions and costs of the sector in the near term and life cycle assessment (LCA) as a comprehensive framework...

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Publicado en:Journal of Industrial Ecology Vol. 28; no. 4; pp. 942 - 953
Autores principales: Astudillo, Miguel F., Krämer, Kai, Arteaga, Asier
Formato: Artículo
Publicado: Springer Nature Aug2024
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Aug2024
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      pub: Springer Nature
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        10.1111/jiec.13510
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        atl: Using dynamic life cycle assessment to evaluate the effects of industry digitalization: A steel case study.
      aug:
        au:
          Astudillo, Miguel F.
          Krämer, Kai
          Arteaga, Asier
        affil:
          2.‐0 LCA Consultants, Barcelona, Spain
          Deutsches Forschungszentrum für Künstliche Intelligenz, Saarbrücken, Germany
          I+D, Sidenor, Basauri, Spain
      su:
        Industrial ecology
        Global warming
        Greenhouse gases
        Optimization algorithms
        Product life cycle assessment
      sug:
        subj:
          Industrial ecology
          Global warming
          Greenhouse gases
          Optimization algorithms
          Product life cycle assessment
      keyword:
        CPS
        digitalization
        industrial ecology
        industry 4.0
        LCA
        steel
        CPS
        digitalization
        industrial ecology
        industry 4.0
        LCA
        steel
      ab: Decarbonization of steelmaking has stagnated while it has a considerable share of global greenhouse gas emissions and a growing demand. Digitalization is seen as a viable option to reduce emissions and costs of the sector in the near term and life cycle assessment (LCA) as a comprehensive framework to evaluate changes in production practices. In this study, we analyze the potential impact of using optimization algorithms to improve the operation of a steelmaking plant in Spain. Specifically, we study the potential effects of optimizing the sequence in which steel is produced to minimize losses during casting. The global warming (GW) impacts and economic costs are quantified using a dynamic LCA model, considering uncertainty and temporal variability using an open‐source LCA framework. The results indicate, on average, modest savings in costs and are inconclusive regarding GW emissions. Most of the cost savings come from a reduction in the use of additives and electricity, which are wasted when the steel is scrapped during casting. The methodological framework has proven useful in quantifying and interpreting the potential effects of digitalization. The implemented solution, tested in an industrial setting, allows an automated evaluation of production at the plant using the LCA model, facilitating the use of sustainability criteria in decision‐making.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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