Deep learning applications have been thriving over the last decade in many different
domains, including computer vision and natural language understanding. The drivers for the …

This paper presents a model for optimising fleet maintenance management with a particular
application to train rolling stock fleets. The proposed model produces a joint schedule for …

The rolling stock maintenance scheduling problem addressed here involves scheduling a
set of cyclical preventive maintenance activities while considering resource capacity and …

In the automotive industry, multiple predictive maintenance units run behind the scenes in
every production process to support significant product development, particularly among …

While the progress of predictive maintenance has been rising in various application fields
and several feasibility studies and prototypes have been developed, the operational …

The optimization of fleet maintenance management is of utmost importance to ensure the
efficient and reliable operation of asset fleets. Traditional maintenance strategies are often …

In this paper, we propose a study of the decision horizon duration for rolling stock mission
assignment and maintenance planning in a prognostics and health management (PHM) …

We study the solution of the rolling stock rotation problem with predictive maintenance
(RSRP-PdM) by an iterative refinement approach that is based on a state-expanded event …

We consider the rolling stock rotation planning problem with predictive maintenance (RSRP-
PdM), where a timetable given by a set of trips must be operated by a fleet of vehicles. Here …

With the emergence of prognostics and health management (PHM) methodology,
companies are trying to fully exploit the data sources they have to build models for their …