Industry 4.0 communications for an assistance system, ML-based, that autonomously analyses connected production chains. Photo: IMMS.
Industry 4.0 communications for an assistance system, ML-based, that autonomously analyses connected production chains. Photo: IMMS.

Voices from industry and academia

Dr. Alexander Maier, Fraunhofer IOSB-INA

”At the Fraunhofer IOSB Industrial Automation Centre (INA) in Lemgo, NRW, Germany, we offer application knowledge for industrial automation. Smart connectivity, analysis, monitoring and user-centered design of technical systems are what we are good at. As support for their digital transformation, we provide our business partners with living labs in the form of the SmartFactoryOWL together with Lemgo Digital. We worked with IMMS as early as 2012 in this area. At that time, IMMS developed wireless networked sensors that captured data on energy use while production chains were operating, to increase manufacturing efficiency and to underpin our task of detecting and avoiding inefficient energy input-output ratios during manufacture.

Having had such good cooperative experience, we kept in touch and grew the original project concept to become AgAVE. Again we formed a perfectly complementary team, developing an assistance system which could analyse complex connected machinery automatically, to find faults quickly and reduce costs. On our side, the job was to contribute machine learning methods for local investigation of cause and effect at machine level, and, at the global level to deliver results capable of human interpretation and to generate instructions for the entire production chain.

IMMS’ job was to develop the means by which the two levels could communicate with each other as required in Industry 4.0 and to support us in the accomplishment of a practical demonstrator with fully connected sensors. Together we succeeded in demonstrating on actual plant how the assistance system learns the decision rules and discovers cause-and-effect links in separate machines and modules, finding possible root causes.

We very much appreciate not only the sound, practical engineering knowledge of the IMMS staff concerning Industry 4.0-compatible protocols and systems but also the personal contact and the constructive manner of IMMS’ collaboration. And so we shall be delighted if we can tackle upcoming subjects together.“

Dr. rer. nat. Alexander Maier, Head of Machine Learning group, Fraunhofer IOSB Industrial Automation Centre (INA). Photograph: Fraunhofer IOSB-INA.

www.iosb-ina.fraunhofer.de