M. Antoine GRALL

Ph.D. Position 


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Teaching:

Mathematics, reliability theory and maintenance modeling

• Linear algebra mathematics - undergraduate. 

• Mathematics for engineers (optimization, least square problems, linear systems, convolution, Laplace transform) - Engineering degree/undergraduate

• Systems reliability theory  - Engineering degree/graduate

• Models for reliability and maintenance - Master degree/graduate

• Maintenance modeling for deteriorating systems - PhD level

( RAMS specialization for Industrial Engineering at UTT)

Research :

Reference topic : «Dependability» - Stochastic modeling for reliability and maintenance .

Competence and interests

• Maintenance modeling: condition-based and predictive maintenance (dynamic on-line decision rules, assessment and optimisation, lifetime pronostic)

• Stochastic dégradation modeling of systems and structures : wear, gradual deterioration, stochastic processes. 

• Reliability  of complex systems: Probabilistic Safety Assessment, Common Cause Failures modeling.

Keywords :maintenance, reliability, dependability, on-line monitoring, prognosis, stochastic modeling framework. 

Topics:

• Adaptive condition-based and predictive maintenance policies
• Imperfect maintenance fro deteriorating systems
• Reliability assessment of autonomous vehicles
• Predictive  maintenance of wind turbine pitch control system
• Maintenance of deteriorating control systems
• Maintenance of a fleet of items
• Maintenance of production systems (Factory of the Future)

Main Academic duties:

2022 - : Director of the doctoral school "Science for Engineers"

2020 - 2023 : Head of the "Dependability: Reliability and Maintenance " Scientific Axis of LIST3N

2017 - 2022 : Deputy director of the doctoral school "Science for Engineers"

2006 - 2019 : Head of the "Reliability and Maintenance" Research group of LM2S

2006 - 2016: Head of ROSAS department (Operation Research, Applied Statistics, Simulation)

2003 - 2011: Responsible of the specialization "Operational safety, Risks and Environment" (RAMS) for engineers in Industrial Engineering