Artificial Intelligence for improved PROduction efFICIEncy quality and maiNTena...
Artificial Intelligence for improved PROduction efFICIEncy quality and maiNTenance
The AI-PROFICIENT project will pave the way for integration of advanced AI technologies to manufacturing domain through an evolution from hierarchical and reactive decision making to self-learning and proactive control strategies....
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THOMAS
Mobile dual arm robotic workers with embedded cognition for...
6M€
Cerrado
Información proyecto AI-PROFICIENT
Duración del proyecto: 39 meses
Fecha Inicio: 2020-07-02
Fecha Fin: 2023-10-31
Líder del proyecto
UNIVERSITE DE LORRAINE
No se ha especificado una descripción o un objeto social para esta compañía.
TRL
4-5
Presupuesto del proyecto
5M€
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
The AI-PROFICIENT project will pave the way for integration of advanced AI technologies to manufacturing domain through an evolution from hierarchical and reactive decision making to self-learning and proactive control strategies. The proposed approach is underpinned by predictive and prescriptive AI analytics at both component and system level, by cross-fertilizing edge and platform AI, while leveraging the human knowledge and feedback for reinforcement learning (human-in-the-loop). AI-PROFICIENT aspires to bring advanced AI technologies to manufacturing and process industry, while improving the production planning and execution, and facilitating the collaboration between humans and machines. Taking the full advantage of AI capabilities and human knowledge, AI-PROFICIENT will develop proactive control strategies to improve the manufacturing process over three main vectors: production efficiency, quality and maintenance. AI-PROFICIENT will increase the positive impact of AI technology on the manufacturing process as a whole, while keeping the human in central position, assuming supervisory (human-on-the-loop) and executive (human-in-command) roles. AI-PROFICIENT intends to identify the effective means for human-machine interaction, while respecting the safety and security requirements and following the ethical principles, in order to enable: event identification and prediction, operation scenarios simulation, transparent decision and optimal control, and personalized shop-floor assistance. Such an approach will ensure that the ambitious, but realistic project targets, namely to improve production planning and execution, as well as to facilitate the human-machine collaboration, are achievable for the European manufacturing and process industry. The implementation of this novel concept will be based on the results of several recently finished European R&D projects, which will be demonstrated in two pilot sites, under different scenarios of significant economic value.