Summary
Fibre reinforced materials components (e.g. glass/carbon-fibre-reinforced plastics) have recently emerged as a mechanically viable, cheaper and cleaner alternative to load-bearing metal parts – becoming a multi-billion market expected to be worth over $135bn by 2021. Their mechanical strength depends on the local fibre orientation, which needs to be aligned with the main loading directions. Fibre-reinforced part design workflows typically involve many iterations with test castings and associated labour-intensive manual 2D experimental validation of fibre distribution/orientation to optimize the injection moulding parameters to reach the desired design specification. Thus, proper 3D tools for fibre orientation characterization are lacking and would greatly reduce the time required to go subsequently from initial design to final tested FRP components.
Current characterization methods are limited to destructive testing of fibre-reinforced parts, from which fibre orientation and distribution can only be observed in very small regions. This primarily stems from the fact that existing methods (e.g. microCT) need to resolve individual fibres to then infer structural information. In opposition, Xnovo’s disruptive imaging technology - FibreScanner3D - directly probes previously inaccessible structural data, encoding fibre direction and distribution over entire parts. This will greatly facilitate design optimization workflows and is expected to reduce by a factor of 2 the number of design iterations and the time required to go from initial design to the final fully optimized component.
The potential of our disruptive imaging technology is soundly supported by the strong industrial endorsement and thus the successful implementation of the present project will represent a significant business opportunity for Xnovo, opening a significant revenue stream for our SME and creating at least 15 new direct jobs in the first 5 years of commercialization.
Current characterization methods are limited to destructive testing of fibre-reinforced parts, from which fibre orientation and distribution can only be observed in very small regions. This primarily stems from the fact that existing methods (e.g. microCT) need to resolve individual fibres to then infer structural information. In opposition, Xnovo’s disruptive imaging technology - FibreScanner3D - directly probes previously inaccessible structural data, encoding fibre direction and distribution over entire parts. This will greatly facilitate design optimization workflows and is expected to reduce by a factor of 2 the number of design iterations and the time required to go from initial design to the final fully optimized component.
The potential of our disruptive imaging technology is soundly supported by the strong industrial endorsement and thus the successful implementation of the present project will represent a significant business opportunity for Xnovo, opening a significant revenue stream for our SME and creating at least 15 new direct jobs in the first 5 years of commercialization.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/827964 |
| Start date: | 01-09-2018 |
| End date: | 31-01-2019 |
| Total budget - Public funding: | 71 429,00 Euro - 50 000,00 Euro |
Cordis data
Original description
Fibre reinforced materials components (e.g. glass/carbon-fibre-reinforced plastics) have recently emerged as a mechanically viable, cheaper and cleaner alternative to load-bearing metal parts – becoming a multi-billion market expected to be worth over $135bn by 2021. Their mechanical strength depends on the local fibre orientation, which needs to be aligned with the main loading directions. Fibre-reinforced part design workflows typically involve many iterations with test castings and associated labour-intensive manual 2D experimental validation of fibre distribution/orientation to optimize the injection moulding parameters to reach the desired design specification. Thus, proper 3D tools for fibre orientation characterization are lacking and would greatly reduce the time required to go subsequently from initial design to final tested FRP components.Current characterization methods are limited to destructive testing of fibre-reinforced parts, from which fibre orientation and distribution can only be observed in very small regions. This primarily stems from the fact that existing methods (e.g. microCT) need to resolve individual fibres to then infer structural information. In opposition, Xnovo’s disruptive imaging technology - FibreScanner3D - directly probes previously inaccessible structural data, encoding fibre direction and distribution over entire parts. This will greatly facilitate design optimization workflows and is expected to reduce by a factor of 2 the number of design iterations and the time required to go from initial design to the final fully optimized component.
The potential of our disruptive imaging technology is soundly supported by the strong industrial endorsement and thus the successful implementation of the present project will represent a significant business opportunity for Xnovo, opening a significant revenue stream for our SME and creating at least 15 new direct jobs in the first 5 years of commercialization.
Status
CLOSEDCall topic
EIC-SMEInst-2018-2020Update Date
27-10-2022
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