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<p>In the evolving automotive industry, sustainability and environmental responsibility are increasingly prioritized. Automotive paint shops are essential in this highly automated sector, using specialized equipment and materials to improve vehicle aesthetics and durability. Robust risk management is critical in this context, where the process is often complicated by uncertainty that stems from subjective human evaluations. To address this, we develop a Multi-Criteria Decision-Making tool implemented in flexible Python code to enhance risk management in the sector. This tool builds on the Fuzzy DEcision MAking Trial and Evaluation Laboratory (Fuzzy DEMATEL) method, addressing the unique requirements of each business context and enriching the risk management process by incorporating input from multiple experts. The code automatically identifies the most influential risks, selects effective and sustainable strategies, formalizes comprehensive risk management procedures, and prioritizes targeted interventions. Our approach enhances visual clarity by graphically illustrating the relationships among the most influential risks, supporting more informed decision-making. At the same time, a versatile validation procedure is offered in various input scenarios, confirming the reliability of the developed code that is ready to be applied in various industrial sectors.</p>

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Advanced risk management software for multi-criteria decision-making in uncertain scenarios

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月25日

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  • Silvia Carpitella,
  • Fortunato Carpitella,
  • Antonella Certa,
  • Bruno Brentan,
  • Joaquín Izquierdo

摘要

In the evolving automotive industry, sustainability and environmental responsibility are increasingly prioritized. Automotive paint shops are essential in this highly automated sector, using specialized equipment and materials to improve vehicle aesthetics and durability. Robust risk management is critical in this context, where the process is often complicated by uncertainty that stems from subjective human evaluations. To address this, we develop a Multi-Criteria Decision-Making tool implemented in flexible Python code to enhance risk management in the sector. This tool builds on the Fuzzy DEcision MAking Trial and Evaluation Laboratory (Fuzzy DEMATEL) method, addressing the unique requirements of each business context and enriching the risk management process by incorporating input from multiple experts. The code automatically identifies the most influential risks, selects effective and sustainable strategies, formalizes comprehensive risk management procedures, and prioritizes targeted interventions. Our approach enhances visual clarity by graphically illustrating the relationships among the most influential risks, supporting more informed decision-making. At the same time, a versatile validation procedure is offered in various input scenarios, confirming the reliability of the developed code that is ready to be applied in various industrial sectors.