A modular model to schedule predictive railway maintenance operations

This paper presents a modular model for the optimal railway maintenance scheduling problem. In particular, an innovative approach to predictive railway maintenance scheduling is applied to track maintenance, also taking into account the risk assessment, according to the ISO 55000 guidelines, and the real-time track conditions. The novelty of this approach consists of the introduction of the concept of risk in railway maintenance scheduling, thus implying that the maintenance activity priorities are based on asset criticalities, such as track degradation conditions and repair costs, and the users' unmet demand due to traffic disturbances caused by asset faults. In the paper, after a general framework description, the relevant literature is analyzed. Then, the formal problem description is given, and some experimental results are discussed, together with some indications about the future model developments.