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

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 analyzes the pallet manufacturing process using a novel 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 goal is to show how sensors that monitor machine operation and technical state 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. Additionally, using sensors for monitoring the condition of key mechanical components enable condition-based maintenance (CBM). 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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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-04
DOI
https://doi.org/10.5281/zenodo.13938409
Primary Topic
Assisted Reproductive Technology and Twin Pregnancy
Type
article
Field-Weighted Citation Impact
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article

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

Zenodo (CERN European Organization for Nuclear Research)
Assisted Reproductive Technology and Twin Pregnancy
article

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

article en

Abstract

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 analyzes the pallet manufacturing process using a novel 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 goal is to show how sensors that monitor machine operation and technical state 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. Additionally, using sensors for monitoring the condition of key mechanical components enable condition-based maintenance (CBM). 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.

Zenodo (CERN European Organization for Nuclear Research)
University of Hradec Králové (CZ)
Industry, innovation and infrastructure
Openalex Percentile: Top 43%
Assisted Reproductive Technology and Twin Pregnancy
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