{"id":148603,"date":"2024-03-25T16:59:12","date_gmt":"2024-03-25T15:59:12","guid":{"rendered":"https:\/\/eurecat.org\/?post_type=avada_portfolio&p=148603"},"modified":"2024-03-25T17:01:15","modified_gmt":"2024-03-25T16:01:15","slug":"amp-ai","status":"publish","type":"avada_portfolio","link":"https:\/\/eurecat.org\/en\/portfolio-items\/amp-ai\/","title":{"rendered":"AMP-AI"},"content":{"rendered":"

\"AMP-AI<\/p>\n<\/div>

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Autonomous manufacturing process with artificial intelligence.<\/strong><\/p>\n

The AMP-AI<\/strong> project drives a solution that allows small and medium-sized industries to optimize online manufacturing processes using artificial intelligence (AI)<\/strong> and increase their efficiency, reducing energy consumption and raw material waste.<\/p>\n

AMP-AI’s solution is based on a new methodology or pipeline of machine learning (ML) algorithms <\/strong>that run iteratively within the cycle time of the production process, combining optimal autonomous control agents and process modeling through AI-based surrogate models.<\/p>\n

This solution requires a smaller volume of experimental data<\/strong> to create AI models of the process and optimal autonomous control of production, adapting to any kind of machine and model of any manufacturer.<\/p>\n

AMP-AI helps many industries that do not optimize industrial processes online because acquiring all the solutions they would need is too expensive. This leads to the waste of raw materials and also greater energy consumption by having to repeat the manufacture of defective parts.<\/p>\n

In this sense, the initiative represents a step forward with respect to current solutions, which are based on mathematical models and which work for a specific process and a specific machine. They are models that approximate the reality of the process, but are limited by the mathematical equations they use and cannot describe effects not foreseen in the model itself.<\/p>\n

Eurecat leads the AMP-AI project through its Applied Artificial Intelligence<\/a> Unit, responsible for developing new AI models for industrial process modeling and the development of optimal autonomous control agents.<\/p>\n<\/div>

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General details<\/h3><\/span>
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Project<\/strong><\/p>\n

AMP-AI \u2013 Autonomous Manufacturing Process with Artificial Intelligence<\/p>\n

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Project reference<\/strong><\/p>\n

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2023 PROD 0011<\/p>\n<\/div>\n

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Programme and call for tender<\/strong><\/p>\n

Project funded by the AGAUR-PROD program: Call for Knowledge Industry for the year 2023 Modality B. Product<\/p>\n<\/div>

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Related SDG<\/strong><\/p>\n

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<\/i><\/i><\/span>9. Industry, innovation and infrastructure<\/span><\/a><\/h4><\/div>
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Optimization through artificial intelligence of manufacturing processes for many small and medium-sized industries that currently cannot have the human resources necessary to continuously optimize them.<\/p>\n<\/div><\/div><\/div>

<\/i><\/i><\/span>12. Responsible production and consumption<\/span><\/a><\/h4><\/div>
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Optimization of manufacturing processes in many more industrial plants. Promotion of a more responsible production that allows the saving of raw materials, the reduction of energy consumption, the reduction of stoppages in the production lines, etc.<\/p>\n

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