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

Informazioni relative al progetto

ALCHIMIA

ID dell’accordo di sovvenzione: 101070046

DOI

10.3030/101070046

Progetto chiuso

Data della firma CE 13 Giugno 2022

Data di avvio 1 Settembre 2022

Data di completamento 30 Novembre 2025

Finanziato da

• Digital, Industry and Space

Costo totale

€ 3 182 500,00

Contributo UE

€ 2 576 987,50

Coordinato da

ATOS IT SOLUTIONS AND SERVICES IBERIA SL
Spain

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Documents, reports (4)

Project Handbook

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

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

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

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 (1)

Data Management Plan

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.

Other (1)

Federated Learning framework_version 1

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

Pubblicazioni

Conference proceedings (1)

Machine Learning models to forecast defects occurrence on foundry products

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

Other (1)

Optimizing Steelmaking with Models, AI, and Federated and Continual Learning

Pubblicato in: Automaatioväylä, Numero 41(1), 2025, ISSN 0784-6428
Editore: Finnish Society of Automation
DOI: 10.5281/ZENODO.14741719