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In the era of Industry 4.0, there is a strong focus on automation, advanced smart technologies, and addressing emerging issues related to sustainability and efficient process management. This paper presents a new approach that integrates traditional risk analysis methods, such as Failure Mode and Effects Analysis (FMEA), with the Critical Path Method (CPM) and Business Process Model and Notation (BPMN). The contribution of this method is presented using a selected sample manufacturing process, namely pallet manufacturing. The goal is to show how sensors that monitor machine operation improve process optimisation and manufacturing system sustainability and function. Utilizing the hybrid FMEA-CPM approach and modelling the production line in BPMN allowed for a comprehensive examination of each activity. This analysis was compared with the outcomes obtained both with and without sensor integration. Sensor data were used for quality control at critical stages of the manufacturing process, reducing the risk of errors in the final product. The results show an over 80% reduction in risk (measured by RPN) and more than 80% improvement in process efficiency, significantly improving decision-making and risk management. This approach offers valuable insights into how incorporating modern technologies in Industry 4.0 can enhance the administration and control of complex production systems, thus improving efficiency and sustainability.

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Risk Management and Process Optimization in Industry 4.0: Integrating Sensors with Critical Path and FMEA

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Hana Tomaskova,
  • Andrea Zvackova,
  • Patrik Urbanik,
  • Dominik Palla

摘要

In the era of Industry 4.0, there is a strong focus on automation, advanced smart technologies, and addressing emerging issues related to sustainability and efficient process management. This paper presents a new approach that integrates traditional risk analysis methods, such as Failure Mode and Effects Analysis (FMEA), with the Critical Path Method (CPM) and Business Process Model and Notation (BPMN). The contribution of this method is presented using a selected sample manufacturing process, namely pallet manufacturing. The goal is to show how sensors that monitor machine operation improve process optimisation and manufacturing system sustainability and function. Utilizing the hybrid FMEA-CPM approach and modelling the production line in BPMN allowed for a comprehensive examination of each activity. This analysis was compared with the outcomes obtained both with and without sensor integration. Sensor data were used for quality control at critical stages of the manufacturing process, reducing the risk of errors in the final product. The results show an over 80% reduction in risk (measured by RPN) and more than 80% improvement in process efficiency, significantly improving decision-making and risk management. This approach offers valuable insights into how incorporating modern technologies in Industry 4.0 can enhance the administration and control of complex production systems, thus improving efficiency and sustainability.