Recycled materials enter the line. Intelligence controls the outcome.
Extrusion is where recycled and sustainable plastic formulations become industrial materials. But recycled polymers, bio-based inputs, fillers, and fibres bring variability into the process.
If the extrusion line cannot adapt, downstream part quality suffers.
Simularge is developing a physics-based digital twin for extrusion within the EcoPlast Horizon Europe project, in collaboration with Eurotec and Ford Otosan.
Eurotec will produce recycled and sustainable engineering plastic compounds for Ford automotive part production. Simularge’s digital twin will support the extrusion process by monitoring and controlling the impact of compositional variation in the input material.
The goal is clear: make recycled-content compounds predictable enough for demanding automotive applications.
The digital twin will support:
Twin-screw extrusion process optimisation
Better control of raw material variability
Plastic material property prediction
Faster material qualification
Reduced process losses
Lower waste and scrap
More reliable supply of recycled-content compounds
EcoPlast sets measurable targets for the manufacturing layer:
Digital twin prediction accuracy: >90%
Digital twin response time: <15 seconds
Scrap rate: ≤1%
Process optimisation error rate: <1%
Waste target: <5%
Efficiency improvement target: ≥10%
Simularge can help evaluate how real-time process prediction could improve product consistency, reduce waste, and support more stable production.
Contact us to assess how a physics-based digital twin can optimize your extrusion process under changing material, temperature, and line-speed conditions.
References:
SIMULARGE
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BEKO
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Ready to get started ?
If this challenge sounds familiar, let’s discuss how Simularge’s physics-based digital twin technology can be applied to your production environment.
