COGNIMAN | COGNitive Industries for smart MANufacturing (COGNIMAN)

Summary

Glass fibre production, precision machining of large parts (e.g. wind turbines), additive manufacturing of medical implants and high-temperature metal production are manufacturing examples with processes that are difficult to automate. The main reasons for the actual labour intensive efforts in these scenarios are lack of full understanding and control over the individual manufacturing steps and the high complexity of the tasks. This has severe impacts on sustainable growth, manufacturing productivity, efficiency and flexibility due to the large amount of unpredictive waste in production and processing time.

COGNIMAN is devoted to improving these situations by developing and demonstrating a novel concept of 'digital cognitive smart manufacturing' that will shift the future design of manufacturing processes towards autonomous and predictive manufacturing with improved flexibility, safety and efficiency. This initiative will provide the means to facilitate flexible, resilient, reconfigurable, safe, sustainable, and efficient smart manufacturing by integrating key technologies. They include simulations, digital twins, advanced sensors, machine learning toolbox and cognitive robotics integrated in human-centric modular toolboxes that can be easily adapted to substitute varying manual manufacturing processes.

By tackling significant challenges, COGNIMAN will provide the means to facilitate flexible, resilient, reconfigurable, safe, sustainable, and efficient smart manufacturing by integrating simulation, models, digital twins, sensors, Artificial Intelligence (Machine Learning), data processing and analytics, robotics, and autonomous systems in a human-centric modular toolbox that can be easily adapted to new manufacturing processes and environments with the ultimate objective of boosting the European technology and manufacturing sectors competitiveness towards industrial leadership in global markets, as well as to reduce the environmental footprint of manufacturing activities.

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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101058477
https://cogniman.eu/
Start date: 01-01-2023
End date: 31-12-2026
Total budget - Public funding: 10 954 502,00 Euro - 9 484 631,00 Euro
Cordis data

Original description

Glass fibre production, precision machining of large parts (e.g. wind turbines), additive manufacturing of medical implants and high-temperature metal production are manufacturing examples with processes that are difficult to automate. The main reasons for the actual labour intensive efforts in these scenarios are lack of full understanding and control over the individual manufacturing steps and the high complexity of the tasks. This has severe impacts on sustainable growth, manufacturing productivity, efficiency and flexibility due to the large amount of unpredictive waste in production and processing time. COGNIMAN is devoted to improving these situations by developing and demonstrating a novel concept of ?digital cognitive smart manufacturing? that will shift the future design of manufacturing processes towards autonomous and predictive manufacturing with improved flexibility, safety and efficiency. This initiative will provide the means to facilitate flexible, resilient, reconfigurable, safe, sustainable, and efficient smart manufacturing by integrating key technologies. They include simulations, digital twins, advanced sensors, machine learning toolbox and cognitive robotics integrated in human-centric modular toolboxes that can be easily adapted to substitute varying manual manufacturing processes. By tackling significant challCOGNIMAN will provide the means to facilitate flexible, resilient, reconfigurable, safe, sustainable, and efficient smart manufacturing by integrating simulation, models, digital twins, sensors, Artificial Intelligence (Machine Learning), data processing and analytics, robotics, and autonomous systems in a human-centric modular toolbox that can be easily adapted to new manufacturing processes and environments with the ultimate objective of boosting the European technology and manufacturing sectors competitiveness towards industrial leadership in global markets, as well as to reduce the environmental footprint of manufacturing activities.

Status

SIGNED

Call topic

HORIZON-CL4-2021-TWIN-TRANSITION-01-01

Update Date

23-01-2023
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Comment:

The COGNIMAN consortium is committed to collaborating closely with the ISO/IEC JTC 1/SC 41 Internet of Things and Digital Twin committee & WGs

Comment:

The COGNIMAN consortium is committed to collaborating closely with the ISO/IEC JTC 1/SC 41 Internet of Things and Digital Twin committee & WGs1 , aiming to contribute to the enhancement of ongoing standards development efforts. This collaboration will leverage the insights and knowledge generated from the project, as well as the standards implemented within the DT model framework, to support and advance the committee's work on standardization in various domains. 

The ISO/IEC JTC 1/SC 41 committee, focusing on the Internet of Things (IoT) and related technologies, was formed in 2017. By 2019, it was further tasked with the standardization of Digital Twins within ISO, prompting a name update to ISO/IEC JTC 1/SC 41 Internet of Things and Digital Twin. 

This committee is organized into several working groups (WG) dedicated to different aspects of IoT and Digital Twins, such as: 

i) WG 3 - IoT Architecture, 

ii) WG 4 - IoT Interoperability, 

iii) WG 5 - IoT Applications, 

iv) WG 6 - Digital twin 

and v) WG 7 - Maritime, underwater IoT and digital twin applications. 

This effort will be coordinated with the Norwegian Electrotechnical Committee (NEK) which is a member of the International Electrotechnical Commission, IEC, which has the responsibility for developing ISO standards on DT and related applications, i.e. which contributes to ISO/IEC JTC 1/SC 41 Internet of Things and Digital Twin standards, aiming to enhance ISO standards for DT development. SINTEF Digital is an active member for the NEK and currently working on several WG to support the DT standardization activities.