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The AIDEAS project aims to integrate artificial intelligence (AI) into the lifecycle management of industrial equipment, thereby increasing agility, sustainability, and resilience. With Europe's machinery industry employing over 3.2 million people, technological advances are essential to maintain global competitiveness. AIDEAS addresses this need by implementing AI-based solutions in four key phases of the Industrial Equipment Life Cycle: design, manufacturing, use, and repair-reuse-recycling. These solutions optimise structural component design, simplify manufacturing processes, improve predictive maintenance, and support sustainable end-of-life strategies. To validate the developed solutions, AIDEAS has four pilots, one of which is PAMA. This pilot focused on improving accuracy, reducing material waste, and leveraging predictive maintenance to minimise operational disruptions. By integrating AI-driven optimisation into machining processes, PAMA has achieved remarkable efficiency gains, reduced downtime and increased overall equipment effectiveness. The results illustrate how Industry 4.0 principles and Smart Manufacturing techniques can contribute to more sustainable, competitive, and innovative industrial practices.

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Advancing Industrial Equipment Lifecycle Management Through AI: Insights from the PAMA Pilot

  • 会议论文

  • 发表日期：

    2026年

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  • José Ferreira,
  • Ilaria Pietrangeli,
  • Miguel Mateo-Casali,
  • Jorge Calado,
  • Laura Moya-Ruiz,
  • Fabrizio Defant,
  • Giovanni Mazzuto,
  • Ricardo Jardim-Gonçalves

摘要

The AIDEAS project aims to integrate artificial intelligence (AI) into the lifecycle management of industrial equipment, thereby increasing agility, sustainability, and resilience. With Europe's machinery industry employing over 3.2 million people, technological advances are essential to maintain global competitiveness. AIDEAS addresses this need by implementing AI-based solutions in four key phases of the Industrial Equipment Life Cycle: design, manufacturing, use, and repair-reuse-recycling. These solutions optimise structural component design, simplify manufacturing processes, improve predictive maintenance, and support sustainable end-of-life strategies. To validate the developed solutions, AIDEAS has four pilots, one of which is PAMA. This pilot focused on improving accuracy, reducing material waste, and leveraging predictive maintenance to minimise operational disruptions. By integrating AI-driven optimisation into machining processes, PAMA has achieved remarkable efficiency gains, reduced downtime and increased overall equipment effectiveness. The results illustrate how Industry 4.0 principles and Smart Manufacturing techniques can contribute to more sustainable, competitive, and innovative industrial practices.