Our mission: Operational business intelligence in the field of smart factories
The IDF – Institute for Data-optimised Manufacturing (originally founded as the Technology Transfer Centre (TTC) for Process Data-optimised Manufacturing – Kaufbeuren) investigates research and development issues in the field of machining.
We consider the entire value creation process using machining tools – from the manufacture of the machines themselves through to the moment when production takes place on them. We work together with partners in industry on devising practical solutions to problems and on creating innovations.
The IDF is spearheaded by professors in the Faculties of Computer Science and Mechanical Engineering and employs research assistants with degrees in the relevant disciplines, supported by students working on projects and degree dissertations.
Objectives and research areas
At the IDF – Institute for Data-Optimised Manufacturing, we are constructing an applications centre with a real-life “glass series production plant” for machining. Our work focuses on the topics of process data-optimised manufacturing and Industry 4.0 – i.e. the digitalisation of industrial production. Our industrial partners at various points along the value chain can further develop and network their solutions in joint projects with the IDF.
We work on designing and implementing prototypes for an end-to-end operational business intelligence solution for the machining industry, i.e. “smart factory”. A selection of pilot projects in the field of machining technology provide ideas and serve as a practical testing ground.
In order to achieve process data-optimised machining production across the entire breadth of this field, we are pursuing many sub-projects within the four inter-related fields of activity.
The main pillars of the Institute for Data-optimised Manufacturing are:
Vacancies for student assistants
Wanted! Student assistant in Computer Science (potential deployment areas: data processing, data science and machine learning, simulation, IT infrastructure, e.g. Docker/Kubernetes or server administration). If you would be interested in this role, please contact christian.dorer(at)hs-kempten.de.
Wanted! Student assistant in Mechanical Engineering (potential deployment areas: Conducting experiments, measuring workpieces and tools (e.g. tool wear, surface quality), FEM simulations. If you would be interested in this role, please contact benedikt.mueller(at)hs-kempten.de.
Opportunities for bachelor’s/master’s theses
Possible topics include Data Science in Industry 4.0; Developing algorithms for evaluating and utilising sensor data in AI models; Machine/deep/reinforcement learning in machining; Knowledge graphs and Bayesian networks; Uncertainty quantification in neural networks; Digital twins and RAMI 4.0 in manufacturing. If you are interested, please contact frank.schirmeier(at)hs-kempten.de.
Practical semester in the field of Data Science
Practical semester in Mechanical Engineering
We also appreciate speculative application applications!
Professor Frank Schirmeier, Dr. rer. nat.
Tel. +49 (0)8341 9667-112
Professor Andreas Rupp, Dr.-Ing.
Tel. +49 (0)831 2523-241 or -101
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