Karriere am WZL



am Forschungsbereich Technologie der Fertigungsverfahren, Abteilung Zerspantechnologie, Research Group Product and Process Monitoring

The intelligent tool holder: Industry 4.0 for process monitoring in milling

With the emergence of Industry 4.0 and the Internet of Production, new solutions to cost-efficiently monitor processes is gaining importance strongly. Together with our industry partners, we develop a sensatory tool holder with in-built strain gauges that send out the data via radio. This data can be used to monitor the milling process, for example to determine the real-time process conditions or monitor tool wear.

In this Master Thesis, you become part of our research team and develop on the models which are used by the system. We are currently working on a new method to estimate the real-time engagement situation (width of cut ae, engagement angle) out of the process signals. This is done via a MATLAB tool, supported by an Artificial Neural Network (ANN). The following picture shows the signals we used.

The signals for different widths of cut share a common curve of data points. The various graphs 'enter' and 'leave' this curve at different points. We use this cuve for the ae estimation.

You do not necessarily have to be skilled in MATLAB, as we have two students in our team who are very proficient in it. However, this thesis provides a possibility to learn MATLAB, or increase your already existing skills, if you want it. You should be a team player, have curiosity for Data Science, Process Signals or machinging processes, and speak either English or German fluently.

We offer a strong support and very good supervision of your thesis, a motivated team of skilled students and research assistants and lots of fun beside the work. Also, a challenging task, work in a promising topic with brilliant perspectives. And cookies ;-)
  • Student of Maschinenbau/Engineering, Informatics/IT or Physics
  • Curiosity for Data Science, Process Monitoring or production science
  • Ability to work in a team, share results and lern+teach from+to others
  • Speak English or German fluently

Zeitaufwand: 40,00 Arbeitsstunden

Sven Goetz, M.Sc. RWTH
Cluster Produktionstechnik 3B 232
Tel.: 0241-80-27466
Mail: S.Goetz@wzl.rwth-aachen.de