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.
| Web resources: |
https://cordis.europa.eu/project/id/957391
https://ai-proficient.eu/ |
| Start date: | 01-11-2020 |
| End date: | 31-10-2023 |
| Total budget - Public funding: | 5 467 698,00 Euro - 5 467 698,00 Euro |
| Twitter: | @AiProficient |
Original description
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.Status
SIGNEDCall topic
ICT-38-2020Update Date
27-10-2022
This report also describes the experience with the HS Booster service support.
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)
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| UNIVERSITE DE LORRAINE (UL) (Coรถrdinator)
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| Athens Technology Center SA
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| CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE (CNRS)
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| CONTINENTAL FRANCE SNC
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| Fundaciรณn Tekniker
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| IBERMATICA SA (IBER)
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| INEOS MANUFACTURING BELGIUM BV
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| INEOS MANUFACTURING DEUTSCHLAND GMBH
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| INEOS SERVICES BELGIUM (INE)
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| INOS HELLAS AE EFARMOGES PLIROFORIKIS AUTOMATISMOU ROMBO
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| INSTITUT MIHAJLO PUPIN (IMP)
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| TEKNOLOGIAN TUTKIMUSKESKUS VTT OY
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| TENFORCE BVBA (TENFORCE)