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<p>The industrial production of printed products is an energy- and material-intensive process that is influenced by various parameters and variables such as production speeds, machine settings, and environmental conditions. This article describes how organizations can utilize this data to tap into hidden sustainability potentials through Artificial Intelligence (AI). A&#xa0;case study in the printing industry is used to demonstrate how the expertise of a&#xa0;printing machine manufacturer, a&#xa0;data analytics provider, and a&#xa0;printing plant can be pooled along the value chain to develop AI-based smart services in an interdisciplinary consortium that contribute to a&#xa0;simultaneous increase in economic and ecological sustainability. This article presents the results of a&#xa0;four-phase process model that was developed and applied as part of the publicly funded consortium research project “Artificial intelligence and data analytics in smart services for a&#xa0;sustainable printing industry”. Objectives, activities, and results are presented for each phase and illustrated using specific case examples. Based on this, five overarching recommendations for action are formulated to demonstrate to incumbent firms, using the printing industry as an example, that collaboration in an interdisciplinary consortium can be a&#xa0;promising approach to unlocking sustainability potentials through AI.</p>

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Erschließung von Nachhaltigkeitspotenzialen mittels Künstlicher Intelligenz: Einblicke aus einem Konsortialforschungsprojekt in der Druckindustrie

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月19日

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  • Björn Häckel,
  • Simon Meierhöfer,
  • Melina Müller,
  • Anna Maria Oberländer,
  • Selina Süzeroğlu,
  • Tim Werner,
  • Stefanie Wiedemann

摘要

The industrial production of printed products is an energy- and material-intensive process that is influenced by various parameters and variables such as production speeds, machine settings, and environmental conditions. This article describes how organizations can utilize this data to tap into hidden sustainability potentials through Artificial Intelligence (AI). A case study in the printing industry is used to demonstrate how the expertise of a printing machine manufacturer, a data analytics provider, and a printing plant can be pooled along the value chain to develop AI-based smart services in an interdisciplinary consortium that contribute to a simultaneous increase in economic and ecological sustainability. This article presents the results of a four-phase process model that was developed and applied as part of the publicly funded consortium research project “Artificial intelligence and data analytics in smart services for a sustainable printing industry”. Objectives, activities, and results are presented for each phase and illustrated using specific case examples. Based on this, five overarching recommendations for action are formulated to demonstrate to incumbent firms, using the printing industry as an example, that collaboration in an interdisciplinary consortium can be a promising approach to unlocking sustainability potentials through AI.