Numerous IFOY awards in the past are proof that STILL offers particularly efficient and robust industrial trucks and intralogistics solutions. This year, the Hamburg-based manufacturer once again impressed as a system provider in the international competition. For the implementation of the new production warehouse of Danfoss Power Electronics in Tinglev, Denmark, the logistics provider received the coveted IFOY award in the category “Integrated Warehouse Solution” during the award ceremony in Dortmund. This is the tenth time that STILL has won the title in different categories.
“The Danfoss project is an impressive example of how automated warehouses will be controlled, monitored and analysed in the future,” was the unanimous verdict of the international jury of experts. The implemented overall system contains known logistical components that are particularly forward-looking in their interaction – i.e., communication via interfaces for safety, function and optimisation using deep learning methods. The functionality of the real automated warehouse seems “exemplary” according to the jury’s verdict.
For the new Danfoss warehouse, STILL supplied a perfectly coordinated combination of three automated series industrial trucks (MX-X and EXV), including the installation of all system components. For end-to-end automation of the material flow, the series trucks are equipped with the iGo systems automation kit. Identical components, controls and interfaces create powerful AGVs. These AGVs are controlled and monitored by a transport and traffic management system. Transport orders are generated by the WMS in the SAP host and transferred to the control system. This permanently generates vast amounts of valuable data, which is used to carry out a precise analysis of the automated warehouse in a cloud.
This data is evaluated with iGo insights – a tool that filters correlations from the wealth of process information in the cloud and provides specific recommendations for action. According to the IFOY jury, it is this analysis tool in particular that provides “further outstanding customer benefits”. In addition to technical problems with individual industrial trucks, it can also identify optimisation potential for the entire system, such as “bottlenecks”. To do this, iGo insights uses the principle of machine learning.
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