Improve injection moulding with recycled plastics
Join RECIPE_SBO and explore how advanced material analysis, predictive modelling and process optimisation can help you increase recycled plastic content while maintaining consistent product quality and reducing production waste.
Challenge
Manufacturers are under increasing pressure to make plastic products more sustainable by incorporating recycled materials. Reusing post-industrial and post-consumer plastics can reduce material costs and support circular production. However, maintaining consistent quality and performance when using recycled materials remains a major challenge.
Unlike virgin materials, recycled plastics often show significant variations in their properties, depending on their origin, composition and processing history. These differences can affect injection moulding behaviour and the mechanical performance of finished products, making it difficult to predict whether components will meet their quality requirements.
Today, selecting suitable recycled materials and adjusting injection moulding parameters largely relies on experience and trial-and-error. Manufacturers must continuously adapt process settings to changing material batches while ensuring product quality. This leads to longer setup times, higher scrap rates, increased energy consumption and uncertainty about final product performance.
Project Goals
In this project (RECIPE_SBO), we aim to develop a reliable methodology for producing high-quality injection-moulded products with recycled material content, helping manufacturers manage material variability and optimise production processes.
The project combines material variability analysis, advanced performance modelling and process optimisation. By identifying which material properties influence injection moulding behaviour, RECIPE will support more informed feedstock selection and reliable assessment of recycled material batches.
The project will also develop uncertainty-aware performance prediction methods to estimate how variations in material properties affect product characteristics such as stiffness and warpage. These insights will support more robust product designs and quality control decisions.
Based on material measurements and predictive models, we will investigate how to optimise recycled and virgin material combinations and automatically propose suitable injection moulding settings for different batches.
By reducing trial-and-error, improving product reliability and limiting scrap production, we aim to help manufacturers increase recycled plastic content without compromising product performance, while reducing material costs, energy consumption and production inefficiencies.
Join our research
We are looking for companies that want to participate in our research and work with us on the valorisation of the project.
Interested?
Then complete the form below.