Project description
A hybrid solution for Europe’s manufacturers
The world of manufacturing is moving away from paper drawings, 2D specs, the huge plants and long assembly lines. Today’s processes in the industry are becoming digitised. Complicated designs are handed down to the shop floors on special USB flash drives or tablets. Digital twins exist to mirror the objects being built. The EU-funded COGNITWIN project will investigate how today’s plants can learn from historical data and adapt. It will partner with numerous industries and research groups from around Europe to create a platform that includes a sensor network for monitoring and collecting data from various plant processes. The platform will include IoT, Big Data, AI, smart sensors as well as automatic learning and communication technologies.
Objective
"While the concept of digitalisation and Industry 4.0 is making rapid inroads into the European manufacturing sector, there are several aspects that can be still incorporated into the system which can strengthen the goal of optimal process operations. One such aspect to the digitalisation vision is the ""cognitive element"", where the process plants can learn from historical data and adapt to changes in the process while also being able to predict unwanted events in the operation before they happen. Through this project, COGNITWIN (Cognitive digital Twin), we aim to add the cognitive element to the existing process control systems and thus enabling their capability to self-organise and offer solutions to unpredicted behaviours.
To achieve the objectives of the project, we have partnered with six industries and seven research groups from seven European nations, each of whom will bring their expertise in data analytics and pattern recognition which are going to be at the heart of the COGNITWIN solution platform. The set-up of the platform includes a sensor network that will continuously monitor and collect data from various plant processes and assets which will be stored at a database. This data will be used to develop a digital twin of the process and will also be used to develop models with cognitive capability for self-learning and predictive maintenance which will lead towards optimal plant operations.
The project builds on ideas and technologies that have been validated in controlled environments (TRL 5) to arrive at prototype demonstrations in operational environments (TRL 7). The COGNITWIN project results will be implemented to our industrial partner's processes to demonstrate the transition from TRL 5 to TRL 7.
TRL – Technology Readiness Level
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Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering control systems
- natural sciences computer and information sciences databases
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors smart sensors
- natural sciences computer and information sciences artificial intelligence pattern recognition
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.2.1.5. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Advanced manufacturing and processing
MAIN PROGRAMME
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H2020-EU.2.1.5.3. - Sustainable, resource-efficient and low-carbon technologies in energy-intensive process industries
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
IA - Innovation action
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-NMBP-ST-IND-2018-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
7034 Trondheim
Norway
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.