Bachelor-/ Master Thesis: »Machine learning pipeline for polymer 3D printing«

Webseite Fraunhofer Institute for Production Technology IPT

The Fraunhofer-Gesellschaft (www.fraunhofer.com) currently operates 75 institutes and research institutions throughout Germany and is the world’s leading applied research organization. Around 29,000 employees work with an annual research budget of 2.8 billion euros.

A prerequisite for the use of Machine Learning (ML) and Artificial Intelligence (AI) is the integration of data from different data sources and their preparation for the subsequent selection of suitable algorithms. The activities for data interlinkage and data preprocessing are complex and time-consuming, but significantly determine the performance of a developed model. How production data is integrated and prepared depends strongly on the use case and therefore represents a central challenge. For an industrial use case from polymer 3D printing, a pipeline for data linking and data preprocessing with subsequent modelling is to be developed within the scope of the thesis. The focus will be on modularity and transferability of the results to similar processes.

What you will do

  • Familiarization with the state of the art for data integration and preparation as well as polymer 3D printing
  • Development of a pipeline for interlinkage and pre-processing of production data from a 3D printing process
  • Initial training of an ML model
  • Software implementation of the developed pipeline
  • Evaluation and documentation of the results

What you bring to the table

  • You are studying mechanical engineering, computer science, industrial engineering or a comparable subject
  • Initial experience in the field of data science is an advantage
  • A high degree of initiative and team spirit
  • Very good language skills in English

What you can expect

  • Interdisciplinary research field at the interface between data science and 3D printing
  • Opportunity of collaboration in an industry-oriented research project and in a dedicated team
  • Alignment of thesis with individual interests possible

Questions according to this position will be answered by:
Henrik Heymann M.Sc.
Research assistant production quality
Phone: +49 241 8904-478

Um dich für diesen Job zu bewerben, besuche bitte jobs.fraunhofer.de.