Maintenance cost optimisation in critical single-component systems: A technician’s training approach based on a joint learning–forgetting and fuzzy maintenance quality model

Abstract

Effective maintenance in critical systems is crucial to ensure their operability and safety. Maintenance technicians play an important role in achieving the safety and reliability objectives of critical system components. However, the role of the technical team in maintenance quality is often overlooked. Our study addresses this knowledge gap by developing a methodology to optimise the training scheduling of maintenance technicians in single-component systems, focusing on a learn-and-forget approach. Our main objective is to improve maintenance efficiency by mitigating the negative impact of technician expertise level. To this end, we implemented a simulation-based optimisation, modelling the evolution of technician experience and its influence on maintenance costs. As a case study, we used an urban aerial passenger ropeway system, demonstrating that proper training of technical staff can significantly reduce both corrective and preventive maintenance costs. Our methodology identified three strategic areas for training technical staff throughout the system lifecycle. The results highlight the importance of investing in the training scheduling of technical equipment in critical systems and suggest that an appropriate training strategy can improve operational efficiency and reduce maintenance costs. In conclusion, our research underlines the need to actively consider the human factor in the maintenance of critical systems to ensure their optimal performance and long-term safety.