Reference projects

Here we show a small selection of our current and successfully completed research and industrial projects.

Please note that many of our references are subject to secrecy and therefore can not be displayed.

Please do not hesitate to contact our departments directly if you can not find your task.

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  • With the BIOTRAIN project, an extensive pilot survey on the biological transformation of the industrial value chain was started under the management of Fraunhofer IPA on the 1st of November 2017. Other members of the project consortium are the Fraunhofer institutes IGB, IML, IWM, IPT and IWU. The project aims at analyzing the potential and requirements associated with implementing biological transformation, particularly regarding a sustainable economy.

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  • If machine learning methods are to be used in industry, robots will have to learn faster than before how to grasp components safely. In the Deep Grasping research project, scientists from Fraunhofer IPA and the University of Stuttgart are therefore developing a virtual learning environment. The neural networks are trained in this environment and then transferred to the real robot.

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  • FlexNote makes it easy to record defects, improvement suggestions and machine settings. The immediate communication of all relevant information to the right people reduces the number of queries. And by statistically evaluating the information gathered, weak points in machines and correlations between defects can be identified in the long term.

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  • Together with BÄR Automation GmbH, an automated guided vehicle has been developed, enabling an automotive manufacture to design his assembly processes flexibly. Consequently, cycle times and conveyors no longer determine assembly processes. Instead, automated guided vehicles (AGVs) bring car bodies from one assembly station to the next via a lifting table.

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  • The "Green Wall Robot" looks after plants in places that people find hard to reach: vertical green facades. Researchers at Fraunhofer IPA and the University of Stuttgart are currently working on a modular automated system for green facades. The aim is to do away with the need for time-consuming and expensive manual maintenance.

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  • InsideOut visualizes a real machine and its movements using real-time data. Recording the machine’s values enables processes and parameters over the last few hours to be displayed correctly, the machine’s behavior to be analyzed and any errors and problems to be identified and eliminated.  

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