Project description
Future factories and facilities run by digital twins
The concept of digital twins has been around but the Internet of Things has enabled its cost-effective implementation. Digital twins refer to a virtual representation of a physical product or process. The EU-funded IoTwins project plans to build testbeds for digital twins in the manufacturing and facility management sectors. The digital models will integrate data from various sources such as data APIs, historical data, embedded sensors and open data. This will give manufacturers an unprecedented view into how their products are performing. In facility management, the technology will be instrumental in improving the way buildings and their systems operate and in preventing prospective problems.
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
Fields of science
- natural sciencescomputer and information sciencesinternetinternet of things
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
Programme(s)
Funding Scheme
IA - Innovation actionCoordinator
40012 Calderara Di Reno Bo
Italy
See on map
Participants (28)
08034 Barcelona
See on map
92220 BAGNEUX
See on map
Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
WS11 8JB Cannock
See on map
Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
60549 FRANKFURT AM MAIN
See on map
80686 Munchen
See on map
10623 Berlin
See on map
08028 Barcelona
See on map
40010 Bentivoglio
See on map
40126 Bologna
See on map
00044 Frascati
See on map
40033 Casalecchio Di Reno Bo
See on map
40129 Bologna Bo
See on map
Participation ended
3364 Leudelange
See on map
20870 Elgoibar
See on map
Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
20009 DONOSTIA SAN SEBASTIAN
See on map
7430 Ikast
See on map
1060 Bruxelles / Brussel
See on map
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
42015 Correggio Re
See on map
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
75013 Paris
See on map
1246 Luxembourg
See on map
Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
15122 Alessandria Al
See on map
1210 Wien
See on map
80333 Munchen
See on map
1040 Wien
See on map
92230 Gennevilliers
See on map
60304 Senlis Cedex
See on map
4942 Gurten
See on map
1040 Wien
See on map