European Commission logo
español español
CORDIS - Resultados de investigaciones de la UE
CORDIS

Artificial Intelligence and Big Data CSA for Process Industry Users, Business Development and Exploitation

Descripción del proyecto

Un plan de acción en materia de inteligencia artificial y datos masivos para las industrias transformadoras de Europa

Los sectores europeos del consorcio SPIRE (cemento, cerámica, productos químicos, ingeniería, minerales y menas, metales no ferrosos, acero y agua) están avanzando rápidamente al adoptar tecnologías de inteligencia artificial (IA) y datos masivos. El proyecto AI-CUBE, financiado con fondos europeos, concretará un plan de acción en materia de IA y el uso de datos masivos para las industrias transformadoras. Diseñará y validará el plan de acción consolidado y garantizará la viabilidad de la solución y los beneficios para la comunidad industrial europea. Además, proporcionará una descripción general de la aplicación actual de algoritmos de IA y datos masivos al identificar sinergias aprovechables entre sectores. A partir de este enfoque, el proyecto desarrollará una matriz conceptual tridimensional basada en tecnologías de IA y datos masivos, áreas de aplicación y sectores del consorcio SPIRE.

Objetivo

AI-CUBE seeks to enhance the understanding of different digital technologies related to artificial intelligence (AI) and big data (BD) applied in process industries for all the SPIRE industrial sectors. At the start of the project in September 2020 there were eight SPIRE industrial sectors considered, namely: cement, ceramics, chemicals, engineering, minerals and ores, non-ferrous metals, steel and water. At the start of 2021, also pulp & paper and refineries were added – which were then considered and integrated into the list of sectors being analysed through the project. Therefore, a close collaboration with industry is mandatory to achieve in-depth insights into possible application areas of AI for processes, technology, sensor applicability and assessment of their level of penetration.
The overall project approach is based on the development of a 3-dimensional conceptual matrix based on:
1) AI and BD technologies
2) Application areas (activities and industrial processes)
3) SPIRE sectors
AI-CUBE’s main goal is to define a roadmap in AI and the use of BD for the process industry and their maturity level across the industrial sectors, including guidelines for implementation. Industrial stakeholders and associations will validate the consolidated roadmap ensuring solution feasibility and benefits for the European industrial community. A crosslinked vision over process industry sectors shall facilitate cooperation and boost technologies deployment at their full potential. An in-depth consultation with industry (association, representatives, companies) will provide an overview of current AI and BD algorithms application, identifying exploitable synergies among sectors. A deep study of the application areas in planning and operations within other industrial sectors facilitates a gap analysis, propitiating knowledge sharing among processes and sectors.
A Multi-Actor Multi-Criteria analysis will obtain a widely supported and consensus-based action plan for industrial consultation. This will allow the inclusion of a broad stakeholder community representing the main industry actors throughout all the SPIRE sectors, with which the project consortium has strong connections that will support sector integration and stakeholders’ engagement.

Palabras clave

Convocatoria de propuestas

H2020-NMBP-ST-IND-2018-2020

Consulte otros proyectos de esta convocatoria

Convocatoria de subcontratación

H2020-NMBP-ST-IND-2020-singlestage

Régimen de financiación

CSA - Coordination and support action

Coordinador

CIAOTECH Srl
Aportación neta de la UEn
€ 176 875,00
Dirección
VIA PALESTRINA 25
00189 Roma
Italia

Ver en el mapa

Región
Centro (IT) Lazio Roma
Tipo de actividad
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Enlaces
Coste total
€ 176 875,00

Participantes (4)