Data and METAdata for advanced digitalization of manuFACTURING industrial lines

Información del proyecto

MetaFacturing

Identificador del acuerdo de subvención: 101091635

DOI

10.3030/101091635

Proyecto cerrado

Fecha de la firma de la CE 29 Noviembre 2022

Fecha de inicio 1 Enero 2023

Fecha de finalización 31 Diciembre 2025

Financiado con arreglo a

• Digital, Industry and Space

Coste total

€ 5 768 142,75

Aportación de la UE

€ 4 997 759,13

Coordinado por

KATHOLIEKE UNIVERSITEIT LEUVEN
Belgium

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Documents, reports (7)

AI and hybrid models for industrial ML

A document outlining the methodology for setting up AI and hybrid (AI+first principle) models in the context of industrial problems, focussing on reliability and scalability.

Continuum thermal material identification approach

A document outlining the DT based material identification approach. This document will both contain the theory, as well as guidelines and overview of the software setup to perform this identification.

Measures to guarantee valuable validation results

A report outlining the main KPI which will be considered for the MetaFacturing developments, as well as their target values to yield economic viability.

CHADA testing documentation

This document outlines how the various testing procedures, identification methods and obtained parameters for the materials can be converted into description files consistent with the CHADA standard.

Definition of integrated data consolidation

A document outlining the formatting requirements for the various data (streams) to guarantee inter-operability of the developed (sub)systems.

Operational, functional and usability requirements

A report to outline the various requirements for the MetaFacturing developments. This document will be updated as the development and validation continues and a final version is scheduled for M26.

Schedule and integration concept

A detailed deployment plan for the developed (and under development) MetaFacturing toolchain on the two industrial scale use cases.

Demonstrators, pilots, prototypes (1)

Final Requirements Update

A report on the requirements of effective MetaFacturing system, starting from the lesson learned on the serial production use cases.

Data Management Plan (1)

Project manag. handbook, quality plan and DMP

A document outlining the project management approach, as well as a data-management plan to ensure an efficient and safe exchange of data and models between the project and external partners.

Publicaciones

Peer reviewed articles (2)

Innovative Data Models: Transforming Material Process Design and Optimization

Autores: Amir M. Horr; Matthias Hartmann; Fabio Haunreiter
Publicado en: Metals, 2025, ISSN 2075-4701
Editor: MDPI
DOI: 10.3390/MET15080873

Insights on Weld Quality using Unsupervised Learning: Clustering of MIG/MAG Process Signals

Autores: Evans Doe Ocansey, Hannes Hinterbichler, Roxana-Maria Holom, Michael Araz
Publicado en: IOP Conference Series: Materials Science and Engineering, Edición 1315, 2024, ISSN 1757-8981
Editor: IOP Publishing
DOI: 10.1088/1757-899X/1315/1/012003

Book chapters (4)

Industrial Artificial Intelligence

Autores: Roxana Holom, Evans Doe Ocansey, Paul Heinzlreiter, Sandra Wartner
Publicado en: ISBN 978-3-200-09843-5
Editor: ÖWGP Österreichische Wissenschaftliche Gesellschaft für Produktionstechnik

Declarative Programming Approaches for Robust Anomaly Detection in HPDC Process Data

Autores: Tomasz Piotr Michno, Roxana-Maria Holom, Sebastian Schmalzer, Pauline Meyer-Heye, Giulia Scampone, Elias Riegler, Matthias Hartmann, Urban Repanšek, Nejc Košir, Peter Šifrer
Publicado en: Lecture Notes in Networks and Systems, Distributed Computing and Artificial Intelligence, Special Sessions I, 22nd International Conference, 2026, ISSN 2367-3389
Editor: Springer Nature Switzerland
DOI: 10.1007/978-3-032-05745-7_4

Towards a Zero-Defect in Welding: An Exploration of Factors to Improve the Training Data for Image Classification

Autores: Negin Javanbakhtghahfarokhi, Angel J. Lopez, Jorge Rodríguez-Echeverría, Sidharta Gautama
Publicado en: Lecture Notes in Networks and Systems, Intelligent Systems and Applications, 2024
Editor: Springer Nature Switzerland
DOI: 10.1007/978-3-031-66329-1_30

Data Quality Strategies in Gas Metal Arc Welding Production for Machine Learning Applications

Autores: Jorge Rodríguez-Echeverría, Evans Doe Ocansey, Roxana-Maria Holom, Tomasz Piotr Michno, Hannes Hinterbichler, Pauline Meyer-Heye, José Neves, Martin Schnall, Matthias Hartmann, Sidharta Gautama
Publicado en: Lecture Notes in Networks and Systems, Distributed Computing and Artificial Intelligence, Special Sessions I, 21st International Conference, 2025
Editor: Springer Nature Switzerland
DOI: 10.20944/PREPRINTS202503.1190.V1

Conference proceedings (3)

Data Models for Casting Processes – Performances, Validations and Challenges

Autores: A M Horr, R Gómez Vázquez, D Blacher
Publicado en: IOP Conference Series: Materials Science and Engineering, Edición 1315, 2024, ISSN 1757-8981
Editor: IOP Publishing
DOI: 10.1088/1757-899X/1315/1/012001

A physics-based welding digital twin for predicting temperature profiles under varying input parameters

Autores: Talha Saleh, Frank Naets
Publicado en: 19th CIRP Conference on Intelligent Computation in Manufacturing Engineering - CIRP ICME '25, Procedia CIRP, 2026, ISSN 2212-8271
Editor: Elsevier

Porosity Classification in High Pressure Die Casting using Thermal Images and Sensor Data Fusion via Fuzzy Cognitive Maps

Autores: Tomasz Michno, Roxana Holom, Sebastian Schmalzer, Giulia Scampone, Elias Riegler, Matthias Hartmann, Urban Repanšek, Nejc Košir, Peter Šifrer, Katarzyna Poczęta
Publicado en: 2026
Editor: SCITEPRESS

Other (1)

Automated Execution of Data Pipelines based on Configuration Files.

Autores: Károly Bósa; Paul Heinzlreiter
Publicado en: Open Research Europe, 2025
Editor: European Commission
DOI: 10.12688/OPENRESEUROPE.21019.1