Fraunhofer-Institut für Produktionstechnologie IPT

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.

Your tasks

  • Familiarization with the state of the art for data integration and preparation as well as polymer 3D
  • 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

Our requirements

  • 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

Your benefits
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

Notice: You can write your project work or thesis with us immediately and in direct cooperation with
the Chair of Metrology and Quality Management. According to the guidelines of the RWTH Aachen
University, the internship is preferably to be completed at a manufacturing company and can only take
place with us in exceptional cases.

We look forward to receiving your application
Henrik Heymann, M. Sc.
Fraunhofer-Institut für Produktionstechnologie IPT
Steinbachstraße 17, 52074 Aachen

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