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IoTwins SIGNED

Distributed Digital Twins for industrial SMEs: a big-data platform

Total Cost €

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EC-Contrib. €

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Partnership

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Project "IoTwins" data sheet

The following table provides information about the project.

Coordinator
BONFIGLIOLI RIDUTTORI SPA 

Organization address
address: VIA GIOVANNI XXIII 7 A
city: CALDERARA DI RENO BO
postcode: 40012
website: www.bonfiglioli.com

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Italy [IT]
 Total cost 20˙029˙818 €
 EC max contribution 16˙422˙552 € (82%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2018-3
 Funding Scheme IA
 Starting year 2019
 Duration (year-month-day) from 2019-09-01   to  2022-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    BONFIGLIOLI RIDUTTORI SPA IT (CALDERARA DI RENO BO) coordinator 1˙360˙712.00
2    ISTITUTO NAZIONALE DI FISICA NUCLEARE IT (FRASCATI) participant 1˙308˙500.00
3    ALMA MATER STUDIORUM - UNIVERSITA DI BOLOGNA IT (BOLOGNA) participant 1˙140˙686.00
4    BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION ES (BARCELONA) participant 1˙082˙625.00
5    ESI GROUP FR (PARIS) participant 959˙175.00
6    FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V. DE (MUNCHEN) participant 910˙125.00
7    FUTBOL CLUB BARCELONA ASOCIACION ES (BARCELONA) participant 876˙875.00
8    GCL INTERNATIONAL LU (LUXEMBOURG) participant 859˙643.00
9    SIEMENS AKTIENGESELLSCHAFT DE (MUNCHEN) participant 789˙812.00
10    TTTECH COMPUTERTECHNIK AG AT (WIEN) participant 705˙862.00
11    CINECA CONSORZIO INTERUNIVERSITARIO IT (CASALECCHIO DI RENO BO) participant 674˙875.00
12    KK WIND SOLUTIONS AS DK (IKAST) participant 606˙764.00
13    CENTRE TECHNIQUE DES INDUSTRIES MECANIQUES FR (SENLIS CEDEX) participant 582˙785.00
14    FILL GESELLSCHAFT MBH AT (GURTEN) participant 563˙447.00
15    MARPOSS SOCIETA PER AZIONI IT (BENTIVOGLIO) participant 531˙475.00
16    TECHNISCHE UNIVERSITAT BERLIN DE (BERLIN) participant 530˙125.00
17    SIEMENS AKTIENGESELLSCHAFT OESTERREICH AT (WIEN) participant 506˙450.00
18    ECOLE NATIONALE SUPERIEURE D'ARTS ET METIERS FR (PARIS) participant 499˙000.00
19    ETXE-TAR, S.A. ES (ELGOIBAR) participant 475˙912.00
20    THALES SIX GTS FRANCE SAS FR (GENNEVILLIERS) participant 443˙625.00
21    ART-ER-SOCIETA CONSORTILE PER AZIONI IT (BOLOGNA BO) participant 400˙000.00
22    BEWARRANT BE (BRUXELLES) participant 307˙300.00
23    WAVESTONE LUXEMBOURG SA LU (LEUDELANGE) participant 306˙775.00
24    ASTER - SOCIETA CONSORTILE PER AZIONI IT (BOLOGNA) participant 0.00

Map

 Project objective

The IOTWINS project will deliver large-scale industrial test-beds leveraging and combining data related to the manufacturing and facility management optimization domains, coming from diverse sources, such as data APIs, historical data, embedded sensors, and Open Data sources. The goal is to build a reference architecture for the development and deployment of distributed and edge-enabled digital twins of production plants and processes. Digital Twins collect data from manufacturing, maintenance, operations, facilities and operating environments, and use them to create a model of each specific asset, system, or process. These models are then used to detect and diagnose anomalies, to determine an optimal set of actions that maximize key performance metrics. IOTWINS proposes a hierarchical organization of digital twins modeling manufacturing production plants and facility management deployment environments at increasing accuracy levels: • IoT twins: featuring lightweight models of specific components performing big-data stream processing and local control for quality management operations (low latency and high reliability); • Edge twins: deployed at plant gateways and/or at emerging Multi-access Edge Computing nodes, providing higher level control knobs and orchestrating IoT sensors and actuators in a production locality, thus fostering local optimizations and interoperability; • Cloud twins: performing time-consuming and typically off-line parallel simulation and deep-learning, feeding the edge twin with pre-elaborated predictive models to be efficiently executed in the premises of the production plant for monitoring/control/tuning purposes

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "IOTWINS" project.

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The information about "IOTWINS" are provided by the European Opendata Portal: CORDIS opendata.

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