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| Funder | European Commission |
|---|---|
| Recipient Organization | Malardalens Universitet |
| Country | Sweden |
| Start Date | Sep 01, 2024 |
| End Date | Aug 31, 2027 |
| Duration | 1,094 days |
| Number of Grantees | 28 |
| Roles | Participant; Coordinator |
| Data Source | European Commission |
| Grant ID | 101140216 |
Thanks to the advances in information technology, modern industrial systems are becoming increasingly intelligent and autonomous;thus their requirements for, e.g., correctness, availability, traceability and reliability, are also increasing.
Monitoring, analysis anddiagnosis of such industrial systems became pivotal and fueled the development of virtualization and simulation solutions such asdigital twins.In a nutshell, digital twins are virtual representations of actual systems or processes that serve as real-time digital counterparts for,e.g., prediction, analysis, testing, and simulation.
Developing digital twins is a complex process.
On the one hand, it includesdeveloping digital twins at different levels of abstraction of the system to allow one to focus on different relevant aspects (e.g,behavioural, logical, physical).
On the other hand, it must ensure the correctness of digital twins with respect to the systemspecifications and the respective level of abstraction, and the federation enabling the communication between digital twinsconceived as exchange and resume of models.This project aims to develop a model-based framework addressing the above-mentioned challenges by i) automating the creation ofdigital twins for the simulation, monitoring and testing of functional and non-functional properties ii) continuous validating digitaltwins to meet the required properties and iii) developing a multidomain and automated digital twin toolchain for the verification andvalidation of complex industrial systems based on digital twins.
We foresee that this project will positively impact the efficiency ofsuch systems by reducing their time to value and by increasing their final quality.
Eskisehir Osmangazi Universitesi; Innovation River S.R.L.; Alstom Rail Sweden Ab; Cleanwatts Digital Sa; Universite de Rennes; Universitat Linz; Universita Degli Studi Di Teramo; Rise Research Institutes of Sweden Ab; Siemens Aktiengesellschaft Oesterreich; Instituto Superior de Engenharia Do Porto; Softeam; Deftr Teknoloji Elektronik Muhendislik Danismanlik Enerji Ve Uluslararasi Ticaret Limited Sirketi; Gran Sasso Science Institute; Institut Mines-Telecom; Fondazione Istituto Italiano Di Tecnologia; Thinglink Oy; Addiva Ab; Otokar Otomotiv Ve Savunma Sanayi As; Solidcomp Oy; Gran Sasso Tech; Leonardo - Societa Per Azioni; 3D Talo Finland Oy; Malardalens Universitet; Universitaet Innsbruck; Cnet Svenska Ab; Ita-Suomen Yliopisto; Lieberlieber Software Gmbh; Process Genius Oy
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