The automotive industry faces huge challenges in the production context. The high complexity and the high level of automation need to be handled without suffering from unplanned downtimes such as short stops, technical disturbances or machine breakdowns as well as subsequent troubleshooting.
Operational excellence is required at every factory to remain competitive which means, knowledge about machine behaviour and technology needs to be available and provided to every operator in every plant around the clock whenever needed.
Lastly, the current technology change leads to higher requirements in cost efficiency, flexibility and productivity.
Shannon®, the Real-time Solution Recommender, provides situational problem-solving proposals for employees responsible for automotive production lines to reduce downtimes during breakdowns and short stops. The tool thus forms a continuously effective optimization loop based on high-frequency machine controller data. Shannon® makes expert knowledge about problems and their solutions explicitly available to the entire staff worldwide at the right moment in a mobile app.
Fully automated production line for car cabin air filters consisting of 21 processes with initial efficiency rate of 79% – 92% depending on individual product type and shift.
Detection and quantification of optimization potential regarding short stops, breakdowns and related scrap. Based on that generation of situational counter-actions to reduce troubleshooting efforts.
for high frequency data collection of all legacy machine controllers
the real-time solution recommender
"After a short training phase of Shannon® it was applied to one of our fully automated productions lines. The real-time transparency on error behaviour, associated scrap per cause and situational problem-solving proposals during operations helps us a lot to limit losses to a minimum around the clock!"
Vice President Global Operations, Freudenberg Filtration Technologies SE & Co. KG
Darwin, the intelligent machine benchmark, learns a virtual ideal process on the basis of high-frequency PLC data from several machines and thus provides a target value how fast each machine could be and how to get there. Darwin continuously generates specific recommendations for reducing the cycle time for each machine. Thanks to early warnings, maintenance departments are empowered by Darwin to avoid breakdowns before they happen.
Darwin as intelligent machine benchmark focuses on cyclic automotive production processes, e.g. injection moulding, deep drawing, extrusion or metal stamping.