XPM- workshop on Industrial AI 2023

Hôtel de La Poste – Antsiranana, Diego Suarez 201, Madagascar 28 – 29 November, 2023

E2AI-2023

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This workshop aims to bring together researchers and practitioners from the industry as well as academics seeking to conduct applied maintenance research to present their latest achievements and innovations in the field of industrial AI for the development of advanced techniques in reliability, maintainability and supportability, and this in the context of Industry 4.0 and Industry 5.0.

The widespread application of artificial intelligence (AI) and information technology (IT) in industry is growing and diversifying. Industrial artificial intelligence (IAI) integrates IT with operational technologies (OT) and engineering technologies (ET) to achieve operational excellence through improved analytics in the operation and maintenance of industrial assets.

This workshop will provide an overview of the opportunities and challenges of implementing AI in industries, as well as future developments, with particular reference to the operation and maintenance of industrial assets. It will be a leading European forum for the dissemination of original AI research, with a focus on applications as well as new algorithms and systems.

Contributions describing applications of AI techniques to real-world problems, interdisciplinary research involving artificial intelligence, experimental and/or theoretical studies providing new insights into the design of AI systems, and papers describing the development of new analytical frameworks that advance practical machine learning methods are particularly encouraged.

The workshop will include oral and poster presentations and will leave a lot of room for exchange and discussion between participants.

Auteur : Lala RAJAOARISOA

Dr. Lala Rajaoarisoa is currently an Assistant Professor at the Institut Mines-Télécom Nord Europe. He received his M.Sc. degree and PhD in Automatic and Computer Sciences, both at the University of Aix-Marseille, France in 2005 and 2009. His research interests are the development of data-driven tools and methods for the observation and control of large-scale distributed systems. Develop predictive models and controllers to assess system behavior and optimize its performance. This development includes the analysis of intrinsic properties such as stability, observability, identifiability and controllability. He is involved in research activities dedicated to the optimization of energy efficiency of building systems and the control and management of hydraulic systems with more than 80 papers published in refereed journals and conferences.

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