NFFP7-DYMA:System for dynamic matching of aviation maintenance capabilities and tactical needs using machine learning and big data



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Maintenance and support systems need the ability to intelligently interact with other systems in networks organisational structures and include smart sensors, AI, big-data analysis, diagnostics, forecasting and reasoning systems. The project explores the combination of AI, machine learning and big-data technology, to match tactical needs with maintenance resources including decission suport and autonomeous behaviour. A proof-of-concept demo is also developed.

Concepts feasability and technology maturity are  developed for application within  operation, maintenance and logistics support domain using hybrid AI. The SoS approach, the modular and flexible properties of the concept and adapted technologies, also implies that the results are highly suitable for application in other domains, e.g. transport, mining and dynamic industrial system.

Luleå University of Technology Academic
Saab Industrial

Peter Funk, Professor

Room: U1-126
Phone: +46-21-103153