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CORDIS - Forschungsergebnisse der EU
CORDIS

Data and decentralized Artificial intelligence for a competitive and green European metallurgy industry

CORDIS bietet Links zu öffentlichen Ergebnissen und Veröffentlichungen von HORIZONT-Projekten.

Links zu Ergebnissen und Veröffentlichungen von RP7-Projekten sowie Links zu einigen Typen spezifischer Ergebnisse wie Datensätzen und Software werden dynamisch von OpenAIRE abgerufen.

Leistungen

Project Handbook (öffnet in neuem Fenster)

T1.1-T1.3. It shall describe all operational aspects of the project, project execution and management in order to provide the consortium partners with background information about specific procedures and norms to be followed during the project lifetime. Quality procedures, risk identification, management and mitigation procedures, as well as guidelines on knowledge management for information sharing, IPR protection and innovation will be here described.

Plan for impact creation, standardisation and exploitation (öffnet in neuem Fenster)

T6.1-T6.3 Report on the communication, dissemination, and standardisation. This report will include detailed plans for dissemination, communication, standardization and exploitation activities and IPR to be followed by all partners to publicise the ALCHIMA results. This deliverable will also include a preliminary Business Plan for the sustainability of the project

Use-cases preparation (öffnet in neuem Fenster)

T5.1. Report that describes the readiness of each pilot for the development and deployment activities based on T5.1.

Requirements and human-centric recommendations (öffnet in neuem Fenster)

T2.1, T2.3 This deliverable will include the stakeholders’ expectations. Also, the findings of the research with survey results and interviews provide insights and foresight recommendations for human-centric technology development and insertion.

Data Management Plan (öffnet in neuem Fenster)

T1.5. It defines the guidelines for data management in order to ensure a high level of data quality and accessibility for final users and stakeholders and to allow the application of data analytics techniques. Note: Financial and progress reporting will be provided at the end of each reporting period through the EC tool.

Federated Learning framework_version 1 (öffnet in neuem Fenster)

T3.1-T3.3 Report and prototype implementation of ALCHIMIA Federated Learning framework, Transfer Learning and domain adaptation techniques.

Veröffentlichungen

Artificial Intelligence in Steel Production: Questions of Augmentation, Optimisation and Accountability

Autoren: Dean Stroud, Rachel Hale; Martin Weinel; Luca Antonazzo; Vinicio Di Iorio
Veröffentlicht in: 2026
Herausgeber: ELGAR - Handbook of Disruptive Digital Technology

Machine Learning models to forecast defects occurrence on foundry products (öffnet in neuem Fenster)

Autoren: S. Dettori, A. Zaccara, L. Laid, I. Matino, M. Vannucci, V. Colla, G. Bontempi, L. Forlani
Veröffentlicht in: IFAC-PapersOnLine, Ausgabe 58, 2024, ISSN 2405-8963
Herausgeber: Elsevier BV
DOI: 10.1016/J.IFACOL.2024.09.300

ALCHIMIA: what it really takes to build industrial AI in European steelmaking

Autoren: David Blazquez, Irene Garcia and Barbara Fernandez
Veröffentlicht in: 2026
Herausgeber: Steel Times International

Embedding Human-Centred AI in Steelmaking: Lessons from the Alchimia Project

Autoren: Dean Stroud and Martin Weinel
Veröffentlicht in: 2026
Herausgeber: Steel Times International

Optimizing Steelmaking with Models, AI, and Federated and Continual Learning (öffnet in neuem Fenster)

Veröffentlicht in: Automaatioväylä, Ausgabe 41(1), 2025, ISSN 0784-6428
Herausgeber: Finnish Society of Automation
DOI: 10.5281/ZENODO.14741719

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