Cooperation formats

We research, develop and implement AI basics and applications for the fields of manufacturing engineering, logistics and automation. Our project formats range from compact studies on specific issues to long-term strategic cooperations. Our institute also holds lectures, training courses and workshops.

In addition to the standard project formats, Fraunhofer IPA offers the following formats that are specifically tailored to the requirements of AI applications:

© Fraunhofer IPA

If you are interested in a cooperation with us, please get in touch with our contact partners. All project formats are based on industry-funded contract research. Thanks to funding by the Baden-Württemberg Ministry of Economics, Labor and Housing, Fraunhofer IPA has already been able to analyze around 90 industrial AI applications with their Quick Checks. You have the possibility to inform yourself about the public results from the Quick Checks (German version) as well as current funding measures (German version) in order to order a Quick Check for your application idea directly at Fraunhofer IPA.

  • Are you interested in AI technologies, but do not yet know whether and how you can use them profitably in your company?

    By transforming business processes into data-driven questions, we develop use cases with you and prioritize them according to benefit and effort. This provides you with a qualified expert assessment of the potential for process improvements or product and service innovations through AI applications.

    Scope: 2 to 3 workshops

  • Do you have the application data, but not the necessary experience in handling large volumes of data or data analysis tools to analyze the data in depth?

    With the help of our experts, you can quickly review data and analyze and identify potential applications.

    Scope: 2 to 3 days

  • Do you already have an idea of how you want to use AI technologies in your company and are now looking for dedicated professionals to help you implement them?

    This format is designed for conducting feasibility studies, which are indispensable when it comes to automating processes and sequences. They minimize the risks associated with technical developments and give you the security you need to help you make decisions about upcoming investments. We find out whether your production problem can be solved with machine learning. You can implement your AI application idea together with the experts from Fraunhofer IPA in a field study.

    Scope: 10 to 15 days

    Here you will find some examples of Quick Checks that have already been successfully carried out.

  • Would you like to implement your ideas and test them via a prototype?

    The results of the feasibility study from the Quick Check form the basis of a so-called Exploring Project. In the project, an implementation strategy is worked out within about three months and an initial prototype solution is developed. In a further step, these strategies are explored in transfer analyses and scaled if appropriate.

    Scope: 3 to 4 months

    Here you will find some examples of Exploring Projects.

  • Do you want to innovate and are looking for a partner to collaborate with you on long-term development work? Do you want the market and your staff to see you as an innovation driver?

    The Enterprise Lab is a long-term collaboration in which several aspects are investigated in parallel. Findings from current research are transferred directly into practice. You can work methodically on strategic AI topics outside your own corporate structures. We focus on the potential of adding value in the future.

  • Would you like to close gaps in your knowledge on AI or find out about new trends identified by research?

    In our seminars, you gain a sound technical insight and are taught concrete transfer concepts and methodical guidelines.

    Webinars offered by Fraunhofer IPA

Cooperations with Fraunhofer IPA offer you:

  • Comprehensive process knowledge on manufacturing, machine vision and material processing, which is essential in order to apply machine learning methods successfully.

  • Large-scale laboratories for experimental feasibility studies on machine learning concepts in robotics, quality assurance, process optimization, environmental detection and cleanroom technology.

  • A powerful IT infrastructure, including high-performance computers, to design, train or test machine learning concepts.

  • An excellent cooperation network in regional and international fundamental research on the topics of machine learning and artificial intelligence.

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