Multi‐agent system for the reactive fleet maintenance support planning of a fleet of mobile cyber–physical systems

Abstract

Improving the availability and reliability of a fleet of mobile cyber-physical systems as well as the ability to adapt the maintenance planning decisions when facing unexpected events at the fleet level is a major stake faced by the manufacturers and the operators. In the context of this study, the authors propose a reactive multi-agent system model for the fleet maintenance planning of mobile cyber-physical systems. For that purpose, the ANEMONA multi-agent design methodology is used. In this methodology, the agents are modelled and then their organisational and interaction views are described. Numerical experiments are carried out in static and dynamic contexts. In a static context, the proposed multi-agent system is compared with a mathematical programming model to validate the effectiveness of the former in satisfying the fleet's availability and reliability expectations. In a dynamic context, simulated perturbations are used to illustrate the reactivity of the proposed multiagent system. Lastly, an application to rail transport for the maintenance of a fleet of trains at Bombardier Transportation France is proposed. For that purpose, the proposed multi-agent system is integrated in the model layer of a decision support system named 'MainFleet' which is currently under development.

Evaluation of the Transitions Potential to Cyber-Physical Production System of Heavy Industries in Turkey With a Novel Decision-Making Approach Based on Bonferroni Function

“…Therefore, the obtained results by applying this approach may not be realistic and reliable. Mbuli (2019) evaluated the applicability of the CPS in the railway industry without using any MCDM approach. This study is valuable for the railway industry, but it is limited, as it did not provide an opportunity to compare industries and focus on a single industry.…”