Brazilian Journal of Operations and Production Management | 2026
Authors: Pereira J.C.; dos Reis J.C.G.
DOI: 10.14488/BJOPM.2991.2026
Journal: Brazilian Journal of Operations and Production Management
Year: 2026
Publisher: Associacao Brasileira de Engenharia de Producao
Document Type: Article
Open Access: All Open Access; Gold Open Access
Cited by: 0
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 Safety Management System (SMS) to enhance quality and meet regulatory requirements. The study also introduces an optimized risk prioritization process using Bayesian Networks (BBN) and Fuzzy Logic (FL). 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 the aircraft engine overhaul process, presenting a method for integrating risks from various sources into a unified model. The mathematical method, employing BBN and FL, aids in prioritizing risk mitigation actions. By integrating the overhaul process with SMS using this method, aero engine 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. © 2026, Associacao Brasileira de Engenharia de Producao. All rights reserved.
Aeroengine Overhaul; Bayesian Belief Networks; Fuzzy Logic; Operati Assessment; Quality and Safety; Risk Management