RADICLE | Real-time dynamic control system for laser welding

Summary

RADICLE aims to create a real-time dynamic control system for laser welding using a combination of (application specific) sensors in combination with intelligent and predictive control technologies for in-process monitoring and control to minimize/eliminate defects for a range of materials and geometries for both aerospace, automotive and other applications. The control system will include pre- and post-welding measurement as well as in-process monitoring, control and fault prevention / fixing.

The project has 4 large, end-user partners - Rolls-Royce, Alstom, GKN and CRF (FIAT) therefore the impact of RADICLE is expected to be very large.

The overall impacts of successful implementation of the RADICLE technology through our consortium and the wider welding sectors will enable us to achieve the following impacts:

  • Increased productivity of up to 30%
  • 30% reduced energy usage
  • 30% reduced emissions
  • Eliminate the need for part scrappage or rework (up to 20%-30% of labour input)
  • Reduction or removal of the need for final NDE testing of the parts
  • Remove need for large enclosed remote welding rooms (~35% floor space reduction)
  • Increase health and safety benefits

In addition, RADICLE will contribute to the wider Europe 2020 targets, through:- Increased employment of 20-64 year-olds;- Increased R&D spending;- Reduced energy usage and greenhouse gas emissions;- Increased education, especially at third level education;

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More information & hyperlinks
Web resources: http://radiclelaser.com/
https://cordis.europa.eu/project/id/636932
Start date: 01-02-2015
End date: 31-10-2018
Total budget - Public funding: 3 793 802,00 Euro - 3 583 212,00 Euro
Cordis data

Original description

RADICLE aims to create a real-time dynamic control system for laser welding using a combination of (application specific) sensors in combination with intelligent and predictive control technologies for in-process monitoring and control to minimize/eliminate defects for a range of materials and geometries for both aerospace, automotive and other applications. The control system will include pre- and post-welding measurement as well as in-process monitoring, control and fault prevention / fixing. The project has 4 large, end-user partners - Rolls-Royce, Alstom, GKN and CRF (FIAT) therefore the impact of RADICLE is expected to be very large.

The overall impacts of successful implementation of the RADICLE technology through our consortium and the wider welding sectors will enable us to achieve the following impacts:
- Increased productivity of up to 30%, resulting in:
- 30% reduced energy usage;
- 30% reduced emissions;
- Eliminate the need for part scrappage or rework (up to 20%-30% of labour input);
- Reduction or removal of the need for final NDE testing of the parts;
- Remove need for large enclosed remote welding rooms (~35% floor space reduction);
- Increase health and safety benefits;

In addition, RADICLE will contribute to the wider Europe 2020 targets, through:
- Increased employment of 20-64 year-olds;
- Increased R&D spending;
- Reduced energy usage and greenhouse gas emissions;
- Increased education, especially at third level education;

Status

CLOSED

Call topic

FoF-01-2014

Update Date

27-10-2022
Geographical location(s)
Structured mapping
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Factories of the Future Partnership - Made in Europe Partnership

H2020 - Factories of the Future
H2020-FoF-2014
FoF-01-2014 Process optimisation of manufacturing assets
Research & Innovation Action (RIA)
Horizon 2020
H2020-EU.2. INDUSTRIAL LEADERSHIP
H2020-EU.2.1. INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies
H2020-EU.2.1.1. INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)
H2020-EU.2.1.1.0. INDUSTRIAL LEADERSHIP - ICT - Cross-cutting calls
H2020-FoF-2014
FoF-01-2014 Process optimisation of manufacturing assets
H2020-EU.2.1.5. INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Advanced manufacturing and processing
H2020-EU.2.1.5.1. Technologies for Factories of the Future
H2020-FoF-2014
FoF-01-2014 Process optimisation of manufacturing assets