Master Thesis - Machine Learning for Quality Assessment in 3D Printing (m/f/d)

Topic

Additive manufacturing (AM) processes, also called 3D Printing, allow producing geometrically complex structures that are not feasible with conventional manufacturing methods. However, obtaining reliable quality of printed components is crucial. Although quality assessments can be made through conventional data analysis today, the process is often cumbersome. Developing new machine learning (ML) analyses for evaluating component quality based on production and sensor data is therefore highly beneficial. This thesis aims to explore the use of machine learning approaches for assessing the AM process and the resulting component quality.

What you will do

• Research on suitable machine learning approaches for quality data analysis (e.g., Random Forest and Support Vector Machine)
• Testing of the selected ML approach on existing data set
• Evaluation of the results and recommendation of most suitable ML-approaches

What is in for you

• Interesting topic with high industrial relevance
• Flexible working hours and remote work
• Financial support through a working student contract possible

What we are looking for

• Independent and structured work style
• Programming skills and self-initiative
• Proficient in German and English

How to apply

If you are interested, send us a brief email with your motivation and a self-description. We then arrange an initial virtual meeting.