self-X Artificial Intelligence for European Process Industry digital transformation

Informazioni relative al progetto

s-X-AIPI

ID dell’accordo di sovvenzione: 101058715

DOI

10.3030/101058715

Progetto chiuso

Data della firma CE 18 Maggio 2022

Data di avvio 1 Maggio 2022

Data di completamento 30 Aprile 2025

Finanziato da

• Digital, Industry and Space

Costo totale

€ 5 986 540,00

Contributo UE

€ 5 351 440,00

Coordinato da

FUNDACION CARTIF
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

Other (5)

Autonomic managers for Data in Motion and Humans support in AI solutions-final version

Final version to be provided at month 30 Design about the Autonomic managers in charge of coordinate different self-X AI components of use cases to integrate appropriately the flow of “New RAW data” from industrial data sources and the human support according to self-X abilities available (configuration, optimization and healing). Initial version to be provided at month 18

Education and Training Program and Results

Document explaining the impact of the training program ensuring the toolkit’s evolution after project’s end, learn resources, will cover: lectures, seminars, workshops, conferences, in house training and on-line materials

Autonomic managers for Data in Motion and Humans support in AI solutions-initial version

Initial version to be provided at month 18 Design about the Autonomic managers in charge of coordinate different self-X AI components of use cases to integrate appropriately the flow of “New RAW data” from industrial data sources and the human support according to self-X abilities available (configuration, optimization and healing). Initial version to be provided at month 18

s-X-AIPI open-source toolset-v2

Second version of open source algorithms, data sources and example of applications usage to create new self-X AI applications.

s-X-AIPI open-source toolset-v1

First version of open source algorithms, data sources and example of applications usage to create new self-X AI applications.

Documents, reports (11)

AI for Process Industry Reference Architecture and implementation

Preliminary design of the Reference Architecture based on existing standards (FIWARE, RAMI4.0, IDSA, Apache) and requirements from use cases to implement self-X AI applications in those use cases.

Validation report for Data in Motion and human support in IT/OT use case's infrastructures

The s-X-AIPI “New RAW Data” integration will be validated in all scenarios and feedbacks will be collected for improving performance, tuning and bug fixing of the different self-X AI appications in the use cases.

Report on the standardization landscape and applicable standards

Report on the standards affected and related with project's environment and technologies.

General s-X-AIPI technology requirements validation report

Report of the methodology which will allow to validate (assumptions, designs, implementations and deployments) the different components developed in WP4

Guidelines for trustworthy AI in process industry

Update EC guidelines for a trustworthy AI based on experiences from project and use cases in particular, adaptation of guideline to process industries.

Scenarios and Requirements for self-X AI adoption in Process Industry

Analysis of the industrial Scenarios and the preliminar design of the requirements from use cases of the project for adoption in Process Industry of self-X or autonomic AI.

Report on the contribution to standardization-final version

Report about how the selected results of the project will contribute to standardization activities and how the partners will be involved in such activities. Final version to be provided at month 36

AI Maturity Model for Process Industry

AI Maturity Model customized for the process industry to carry out an initial barrier analysis, based on the experiences of use cases.

Report on the contribution to standardization-intermediate version

Report about how the selected results of the project will contribute to standardization activities and how the partners will be involved in such activities. Intermediate version to be provided at month 18

s-X-AIPI solutions impact evaluation on use cases

Evalutaion of the impact in use cases of their performance improvements across different KPIs as a consecuence of use of self-X AI applications.

Report on the contribution to standardization-initial version

Report about how the selected results of the project will contribute to standardization activities and how the partners will be involved in such activities. Initial version to be provided at month 9

Demonstrators, pilots, prototypes (1)

Assessment of collaborative self-X AI solutions performance based on training data-sets

Assessment of the models according to each specific of use case requirements and foreseen self-X abilities and enable the learning of the models that reflect usual behaviour of the system with the information available in this stage of the project.

Data Management Plan (2)

Data management plan-initial version

Initial Data Management Plan for the S-X-AIPI project. This plan will ensure that all research data generated during is findable, accessible, interoperable and reusable (FAIR). It will include a set of guidelines and templates for an apprpriate description of the generated data sets.

Data management plan-final version

Final Data Management Plan for the S-X-AIPI project. This plan will ensure that all research data generated during is findable, accessible, interoperable and reusable (FAIR). It will include a set of guidelines and templates for an apprpriate description of the generated data sets.

Pubblicazioni

Other (2)

selfX: An open-source R package with autonomic abilities for data mining

Autori: M Galende; A Corral; A Reñones
Pubblicato in: Open Research Europe, 2024
Editore: Open Research Europe
DOI: 10.12688/OPENRESEUROPE.18070.1

Timeseries on IIoT Platforms: Requirements and Survey for Digital Twins in Process Industry

Autori: Nölle, Christoph; Kannisto, Petri
Pubblicato in: 2023
Editore: arXiv
DOI: 10.48550/arxiv.2310.03761

Conference proceedings (1)

An AI-Driven User-Centric Framework reinforced by Autonomic Computing: A case study in the Aluminium sector

Autori: Angosto Artigues, Ramon; Coto, Andrea Gregores; Torrez Herrera, Jonathan Josue; Tomás, Fernando Lou; Verardi, Sabrina; Marzano, Mattia Giuseppe; Martínez, Andrea Fernández
Pubblicato in: Proceedings of the 12th International Conference on Human Interaction & Emerging Technologies (IHIET 2024), Numero AHFE (2024) International Conference, vol -1, 2024
Editore: AHFE International
DOI: 10.54941/AHFE1005478

Peer reviewed articles (2)

Resilient, Adaptive Industrial Self-X AI Pipeline with External AI Services: A Case Study on Electric Steelmaking

Autori: Petri Kannisto; Zeinab Kargar; Gorka Alvarez; Bernd Kleimt; Asier Arteaga
Pubblicato in: Processes, 2024, ISSN 2227-9717
Editore: MDPI
DOI: 10.3390/PR12122877

A reference architecture to implement Self-X capability in an industrial software architecture

Autori: Walter Quadrini;Francesco Alessandro Cuzzola; Luca Fumagal; Marco Taisch; Gabriele De Luca; Marta Calderaro;Mattia Giuseppe Marzano; Angelo Marguglio
Pubblicato in: Procedia Computer Science, 2024, ISSN 1877-0509
Editore: Elsevier
DOI: 10.1016/j.procs.2024.01.044