Team cqfd

Overall Objectives
Scientific Foundations
Application Domains
New Results
Contracts and Grants with Industry
Other Grants and Activities

Section: New Results

Optimal stopping for predictive maintenance

Participants : Benoîte de Saporta, François Dufour, Huilong Zhang.

In the continuation of our work on numerical approximation of the optimal stopping problem for Piecewise deterministic Markov Processes (PDMP's), we applied our procedure on an industrial example provided by EADS-Astrium, as part of our ANR grant.

More precisely, we studied the maintenance of an aluminum metallic structure embedded in a strategic ballistic missile. It is to stored in a nuclear submarine missile launcher in peacetime and inspected with a given periodicity. These structures are made to have potentially long storage durations. They stay for random periods in different environments that characterize the conditions of use. Such environments may degrade faster or slower the corrosion protection of the structure. The requirement for security on this structure is very strong. It is thus crucial to control the evolution of the thickness loss of the structure over time, and to intervene before reaching a critical threshold.

We modeled the system by a 4-dimensional PDMP an applied and adapted our numerical procedure described in [26] to obtain path-adapted stopping rules and find optimal maintenance dates. This work was presented in the workshop Modern trends in controlled stochastic processes: theory and applications in Liverpool in July [39] , in the 34th conference on Stochastic Processes and their Applications in Osaka in september, in the conference Lamba-Mu 17 [35] and in several seminars in France and abroad. A full article on this topic is in progress.


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