AIDEAS

AI Driven industrial Equipment product life cycle boosting Agility, Sustainability and resilience
Project ID
Funding Organization:
Funding Programme:
HORIZON-CL4-2021-TWIN-TRANSITION-01
Funding Instrument:
HORIZON-IA
Start Date:
01/10/2022
Duration:
36 months
Total Budget:
6,610,338 EUR
ITI Budget:
675,100 EUR
Scientific Responsible:

AIDEAS will develop AI technologies for supporting the entire lifecycle (design, manufacturing, use, and repair/reuse/recycle) of industrial equipment as a strategic instrument to improve sustainability, agility and resilience of the European machinery manufacturing companies. AIDEAS will deploy 4 integrated Suites:

1) Design: AI technologies, integrated with CAD/CAM/CAE systems, for optimising the design of industrial equipment structural components, mechanisms and control components;

2) Manufacturing: AI technologies for industrial equipment purchased components selection and procurement, manufactured parts processes optimisation, operations sequencing, quality control and customisation;

3) Use: AI technologies with added value for the industrial equipment user, providing enhanced support for installation and initial calibration, production, quality assurance and predictive maintenance for working on optimal conditions;

4) Repair-Reuse-Recycle: AI technologies for extending the useful life of machines through prescriptive maintenance (repair), facilitating a second life for machines through a smart retrofitting (reuse) and identification of the most sustainable end-of-life (recycle). The AIDEAS Solutions will be demonstrated in 4 Pilots of machinery manufacturers that provide industrial equipment to different industrial sectors: metal, stone, plastic and food.

ITI-CERTH is the coordinator of the AIDEAS project, is leading the development of the machine passport and will support the development of data communication protocols, standards, and interfaces for smart trustful data storing, sharing and exchange between different AIDEAS Suites. ITI is responsible for providing real-time large-scale knowledge management algorithms that exploit robust and explainable AI techniques) to provide the rationale for any derived decision making process, to apply early analysis on manufacturing data aiming to discover critical latent insights about the entire machine life cycle, and to reveal causal relationships among data variables.

Consortium

ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXIS (CERTH), Greece
UNIVERSITAT POLITECNICA DE VALENCIA (UPV), Spain
UNINOVA-INSTITUTO DE DESENVOLVIMENTO DE NOVAS TECHNOLOGIAS-ASSOCIACAO (UNINOVA), Portugal
IKERLAN S.COOP (IKERLAN), Spain
TAMPEREEN KORKEAKOULUSAATIO SR (TAU), Finland
UNIVERSITA POLITECNICA DELLE MARCHE (UNIVPM), Italy
INSTITUTO TECHNOLOGICO DE INFORMATICA (ITI), Spain
CE.S.I. CENTRO STUDI INDUSTRIALI SRL (CESI), Italy
IANUS SIMULATION GMBH (IANUS), Germany
XLAB RAZVOJ PROGRAMSKE OPREME IN SVETOVANJE DOO (XLAB), Slovenia
FUNDINGBOX ACCELERATOR SP ZOO (FBA), Poland
DIN DEUTSCHES INSTITUT FUER NORMUNG EV (DIN), Germany
PAMA SPA (Pama), Italy
D2 TECHNOLOGY – MAQUINAS E EQUIPAMENTOS INDUSTRIAIS LDA (D2TECH), Portugal
BBM MASCHINENBAU UND VERTRIEBS GMBH (BBM), Germany
MULTISCAN TECHNOLOGIES SL (MULTISCAN), Spain

Contact

Dr. Stefanos Vrochidis
(Scientific Responsible)
Building A - Office 1.4

Information Technologies Institute
Centre of Research & Technology - Hellas
6th km Harilaou - Thermis, 57001, Thermi - Thessaloniki
Tel.: +30 2311 257754
Fax: +30 2310 474128
Email: stefanos@iti.gr

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