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Artificial Intelligence for improved PROduction efFICIEncy, quality and maiNTenance

Project description

Using AI technology to improve manufacturing

The manufacturing and process industry can benefit from artificial intelligence (AI) technologies. By combining human knowledge with AI capabilities, the EU-funded AI-PROFICIENT project will develop proactive control strategies to improve manufacturing processes in terms of production efficiency, quality and maintenance. The overall goal is to increase the positive impact of AI technology on the manufacturing process as a whole, while keeping the human in a central position, assuming supervisory (human-on-the-loop) and executive (human-in-command) roles. By identifying the effective means for human-machine interaction, the project will assist Europe’s manufacturing and process industry to improve production planning and execution.

Objective

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.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

RIA - Research and Innovation action

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-ICT-2018-20

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Coordinator

UNIVERSITE DE LORRAINE
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 662 500,00
Address
COURS LEOPOLD 34
54052 Nancy Cedex
France

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Region
Grand Est Lorraine Meurthe-et-Moselle
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 730 000,00

Participants (12)

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