Sustainable polymers/Machine Learning

Student: Mahdi Pahlevan

Polymers are used for mass production industrial applications and consumer goods. Product quality and safety are mainly related to material property profile, design and manufacturing processes.

There is a general trend to use more sustainable materials either from renewable feedstock or from recycled materials. This leads to new challenges and opportunities. Monomers can form new polymers. By controlling monomers, co-monomers, configuration, chain length, molecular weight distribution, additives and shaping process parameters it is possible to manage product quality.

The use of sensor technologies and advanced materials and product testing high amounts of relevant data are generated. The generated data are often used for R&D and optimization. The possibilities for utilizing data are often limited to simple material models and statistical tools.


Project proposal

Investigate different approaches for using machine learning, neural network or other ways of utilizing big data. The data should preferable come from real industry cases. Cases should be related to material properties, manufacturing processes and product properties. Models must be verified by use of real industry cases.

Involved partnes: Aarhus University (Kim Daasbjerg), LEGO

Data, progress, and status on the project is found here.

If you’re interested in hearing more about this project, SPOMAN or want to hear about the possibilities for starting a collaboration, please contact us at