Exploring
Tomorrow

Through pioneering research projects with strong partners from science and industry, ABF continuously expands its product portfolio – for the solutions of tomorrow.

AI in Intralogistics: A true game-changer.

In our NextBase research project, we are investigating how Artificial Intelligence (AI) and Machine Learning can make existing intralogistics systems smarter and more efficient – without additional hardware investments. The goal is to enhance the performance of existing facilities through data-driven optimizations, thereby achieving sustainable efficiency gains. Together with RISC Software GmbH, we were able to implement two practical use cases in the first project year, demonstrating how AI-based optimization potential can be utilized in real-world applications.

Use Case 1

Increasing Crane Efficiency through Intelligent Coordination

In a warehouse system where two cranes operate on the same rail, AI-based optimization is used to efficiently coordinate their movements.
The system learns from real operational data and continuously adjusts travel paths. This identifies faster and safer task sequences. A direct comparison between rule-based and AI-optimized crane control shows an improvement of 24.6% in the simulation.

Increased Throughput, Higher Efficiency – with the Same Hardware.

Use Case 2

Intelligent Stacking for Long Goods Warehouses

When storing long goods, data-driven simulations are used to avoid unnecessary re-storage.
The AI continuously analyzes historical inbound and outbound storage data and learns how to optimize stack compositions to flexibly adapt to changing material mixes.

In cooperation with

What's next for NextBase

After demonstrating how Artificial Intelligence (AI) can significantly increase efficiency in intralogistics, the NextBase project is now taking the next step: We are bringing intelligence directly into Manufacturing.
In the second year of research, we are expanding our AI-based methods into two new, forward-looking areas of Manufacturing – with the goal of making production processes more flexible, efficient, and data-driven.

Use Case 1

Fine Planning - Smart Production Planning

In complex Manufacturing environments, a single planning decision can influence the entire process chain.
Our new AI-supported detailed planning methods learn from real production data to intelligently balance workloads, optimize order sequences, and dynamically adapt production plans.
The result: Faster processes, greater flexibility, and more resilient production.