The fabrication of special products places particular demands on production, especially in order to meet specific customer requirements. Thus, components must be manufactured in high quantities but also in small batch sizes. This is realized by a heterogeneous machine pool for the complete machining of components.
A fundamental disadvantage of heterogeneous machine pools is the varying integration of the machines into a communication network, which is increasingly based on IIoT. This means that end-to-end process optimization across the entire machine pool is not possible. Furthermore, investments in new machines and/or changes in the machinery can only be made in isolation per machine. The effects on the overall process cannot be predicted.
The aim of TwinMap is to develop a digital twin for heterogeneous machine pools for overall process optimization in component manufacturing. First analyses show that cost optimizations of > 10 % are possible. The project results are relevant for automotive companies with cycle time optimized production as well as SME contract manufacturers with small batch sizes.
