It is impossible to imagine logistics without tugger trains – they are already in use on many company and factory premises. They are mainly used for production supply and disposal.
Tugger trains are complex systems whose planning and development have received a lot of attention in recent years – together with the Technical University of Munich, the MuCRoute project started in January 2019. Within the framework of the project, the tugger train system is to be further technically refined and optimised.
The aim of this cooperation between Würzburg-based Flexus AG and the Chair of Materials Handling Material Flow Logistics at the Technical University of Munich is to comprehensively facilitate problem handling in the use of tugger trains. This forward-looking project is funded by the Bavarian State Ministry for Economic Affairs, Regional Development and Energy.
Route train control of Flexus AG
The “FLX-TLS Transport / Forklift Control System” of Flexus AG already contains a tugger traincontrol system that is directly integrated into SAP ®ERP. The “FLX-TLS” transport control system optimises the control and coordination of tugger trains in material supply and disposal.
The optimisation and control algorithms shorten the transport routes for material supply by calculating the most sensible routes in advance. Past-based data and the actual distance between the destinations are used to plan the departure and time routes. Through the joint project with the Technical University of Munich, the route train control for SAP will be ®further refined and adapted to the needs of the customers.
Innovative and forward-looking technologies
In the future, the route train will also react to negative influences and external events (e.g. obstacles on the way). The new add-on is intended to identify known faults and suggest remedial measures or solutions, as well as to record as yet unknown faults. For this purpose, a comprehensive analysis of the components and influencing variables of a tugger train system is first defined and thus a catalogue of requirements is developed.
Key figures play a decisive role: already known key figures are included in the calculation and new key figures are defined. The data set is then examined for content and mathematical correlations.
The validation of the results is carried out on the basis of historical data templates and test deployments in already existing tugger train systems. By using the SAP add-on, users will be able to filter and display individually required information in the future. The end user benefits from the different views, according to the needs, as well as the self-learning algorithm, which documents the causes of errors and shows corresponding solution strategies.