Design, Operations Management and Engineering of Systems and Services

The research carried out by our team aims to develop models, methods and algorithms to improve performance and ensure the proper operation of uncertain dynamic systems subject to extensive uncertainty and whose precise behaviour cannot be fully known in advance.

The research carried out in the team concerns the management and operation of production systems of goods and services, and aims to develop models, methods and algorithms to optimize their performance and ensure their proper operation in the event of more or less significant hazards. The studied systems are dynamic systems, subject to extensive uncertainty and whose behavior cannot be fully known a priori.

Our work is therefore characterized by taking this uncertain aspect into account. The considered uncertainties can be operational hazards (such as equipment breakdowns, for example), uncertainties about the environment (arrival of requests or arrival of products to be treated, for example), internal uncertainties (activities of occupants in a building) or even major risks (such as chemical dispersion, for example).

The systems we are interested in are production systems of physical goods (in the automotive manufacturing sector, semiconductor manufacturing or the chemical industry for example), service production systems (healthcare production, energy management in homes or for electric vehicles, industrial risks and organizational crisis management systems, etc.).

Most of the used modeling tools and the developped resolution methods are specific to discrete-event systems and operations research, deterministic or stochastic: Markov Chains, Queuing Nets, Stochastic Petri Nets, Markovian Decision Processes, Discrete-event Simulation, Set-Membership Approach.