Machine learning is becoming increasingly important at the interface between logistics and IT. Already in the past, different challenges in logistics could be solved using machine learning methods. In order to identify and leverage the potential of machine learning in the future as well, an application-oriented view is central. In addition to a large number of research activities, the subject area of machine learning must also be incorporated into teaching in an application-oriented manner. This has been taken up in the “Machine Learning” clan of the Center of Excellence Logistics and IT: In the winter semester 2020, a cross-faculty specialized laboratory on the topic of machine learning in production and logistics will be offered by Jun.-Prof. Dr. Anne Meyer (Faculty of Mechanical Engineering) and Prof. Dr. Markus Pauly (Faculty of Statistics). Within the lab, students from different courses of study (industrial engineering, logistics, statistics and data science) solve problems in production and logistics with machine learning methods in interdisciplinary small groups. In the process, the students learn about tools for the use of machine learning methods, independently develop concepts for data processing pipelines in logistics and implement them as prototypes. At the end of the lab there is a »challenge« in which the best group is selected.
Contact persons are Jun.-Prof. Dr. Anne Meyer from the Chair of Corporate Logistics, e-mail: firstname.lastname@example.org- dortmund.de, and Prof. Dr. Markus Pauly from the Faculty of Statistics at TU Dortmund University, e-mail: email@example.com.