Artificial intelligence (AI) will play a central role in the logistics of the future, especially when it comes to the self-optimization of processes. However, AI algorithms can also play an important role in seemingly trivial tasks, for example when it comes to optimally loading a truck with packages of different sizes and shapes.
Schnellecke promotes the use of artificial intelligence (AI) under the working title Schnellecke iX+ai, for example for real-time simulations to predict critical events.
Simulation models determine results about the dynamic behavior of a system for given parameters. Due to the often not fully visible relationship between result variables and parameters of a logistics system, manual optimization is difficult or only possible for the
observed application case without any claim to general validity.
With the digital twin, the field of simulation is experiencing a new boost in significance. The nearly identical digital representation of a system under observation enables the learning, further learning, and re-learning of AI-supported algorithms in the event of changes in the logistics environment with correspondingly comprehensive data input. Only in this way will the entire system be able to actively and quickly adapt from its own substance to sudden and unforeseeable changes
Self-controlling material flow
Ultimately, Schnellecke iX+ai has the vision of a material flow that controls itself independently and is highly robust against disruptions and unforeseeable changes. But it will be some time before this happens, because other stations in a supply chain, including customers, transporters and suppliers, have to be included in the system.
The first partial successes, such as the manufacturer-independent control system for AGVs – TransportControl, can already be reported. The use of intelligent algorithms and integration through universal interfaces to the intralogistics systems alone will make the processes more effective and leaner.