IDF – Institute for Data-optimised Manufacturing

  1. Kempten University of Applied Sciences
  2. Research
  3. Research institutes
  4. IDF – Institute for Data-optimised Manufacturing

IDF – Institute for Data-optimised Manufacturing

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:

  • Developing machine-oriented sensor technology for capturing process-specific parameters and real-time data;
  • Developing an infrastructure to transfer and store data in suitable database structures with scalable cloud solutions;
  • Tool tracking to record machining processes and the specific tools involved – enabling precise predictions of tool life and optimising resource efficiency in production;
  • Addressing the hitherto neglected issue of the optimal use of cooling lubricants;
  • Developing suitable business models to convert optimised manufacturing processes into tangible customer benefits.

Our team

With the aim of accelerating the transfer of innovations into operational practice, our team of engineers and computer scientists with bachelor’s or master’s degrees adopts an interdisciplinary approach to working in the fields of research mentioned above.

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)

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)

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)

Practical semester

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

Gottlieb-Daimler-Strasse 4
87600 Kaufbeuren


The sensor data generated in machining is analysed using a combination of conventional analytical tools and fast Fourier transformation and AI methods such as artificial neural networks. (Animation: Kempten UAS)

Research Priority Area and research projects