Method for Risk Assessment in Aeroengine Overhaul using a combination of Bayesian Networks and Fuzzy Logic in the context of Industry 5.0
DOI:
https://doi.org/10.14488/BJOPM.2991.2026Keywords:
Bayesian Network, Fuzzy Model, Risk Assessment, Safety Management, Aeronautic Industry, Quality ManagementAbstract
This study presents a method for identifying and managing risks in the aeronautical engine overhaul process. It emphasizes the integration of this process with the Operational Safety Management System (SMS) to enhance quality and meet regulatory requirements. The study also introduces an optimized risk prioritization process using Bayesian Belief Networks (BBN) and Fuzzy Logic. As technology evolves, it brings both advancements and new risks. In aircraft engine maintenance, effective risk identification and response are vital due to the potential catastrophic consequences of engine failure during flight. The study combines a literature review on probabilistic risk analysis with a case study of aircraft engine overhaul process, presenting a method for integrating risks from various sources into a unified model. The mathematical method, employing BBN and Fuzzy Logic, aids in prioritizing risk mitigation actions. By integrating the overhaul process with SMS using this method, aero engines operations can enhance quality and operational safety while reducing costs. The approach aligns with industry standards and regulations. In conclusion, this method offers significant potential for optimizing risk management, especially in the context of aeronautical engine maintenance. It contributes to the knowledge of process and aero engine maintenance, can aid safety professionals, and its implications can extend to various industries where safety and risk management are paramount.
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