2019 Award Winners
Award-winning project: Kyana – Predictive maintenance with a digital twin
Project partners: Koenig & Bauer Coding GmbH, Veitshöchheim | Steinbeis Research Center Design and Systems, Würzburg
The convergence of artificial intelligence, digitally enhanced imaging and novel interaction models enables innovative product enhancements that can be of particular benefit in the areas of training, monitoring and maintenance. Systems that continuously self-monitor reduce the number of on-site service calls, ensure greater availability and can therefore be operated much more cost-effectively.
In collaboration with Koenig & Bauer Coding GmbH, the Steinbeis Research Centre for Design and Systems in Würzburg developed the digital extension ‘Kyana’ for the ‘alphaJET’ marking system. Such continuous inkjet printers enable products to be coded with variable data directly on the production line at the highest speed and with the utmost precision. Kyana is an AI-based software solution that communicates via voice control and uses augmented reality to convey the complex inner workings of the printing system in a clear and interactive manner. As an intelligent assistant, Kyana will in future take on a wide range of tasks. In addition to training and operation, she independently explains maintenance processes and service procedures and identifies impending wear and tear and material consumption at an early stage. At the same time, as the system is used, it learns to analyse all external influences in order to use the insights gained to ensure consistently high print quality and maximum availability.
Augmented reality gives Kyana its spatial presence. This enhanced visual perception allows for a deeper understanding of the hardware and how it works. The digital overlays provide a precise view inside the printer and, in combination with voice output, facilitate maintenance work or repairs. In addition, the AI extension also allows for the integration of ‘virtual hands’, which, in the event of remote maintenance support, enable assistance to be provided on a digital twin. Ideally, this will enable potential faults to be rectified more quickly in future and prevent long, costly journeys by service personnel.
The potential of this application, which has been awarded the Steinbeis Foundation’s Transfer Price – the Löhn Prize – is enormous, as the analysis of the data collected holds valuable resources for future applications. The trusting collaboration between the two project partners provides an ideal foundation for this.