The aim is to use AI-supported software based on large language models to support the manufacturer-neutral planning of logistics systems. This approach comprises a guided dialogue that carries out individual planning steps and calculations and ultimately leads to the selection of the optimum system. For Klinkhammer's logistics planners, this offers the advantage of automating routine activities such as cycle time or cubature calculations. The system can be selected on the basis of defined requirements such as stored goods, order data, performance, temperature or processes. This also makes economic considerations such as estimating costs more efficient.
For Klinkhammer customers, this offers the advantage of speeding up routine calculations and comparisons and significantly reducing planning times. The time gained can be invested in a differentiated consideration of detailed aspects or in comparing variants. This is because new insights often arise during the planning process that can lead to a change in planning. AI increases the flexibility to react to this. However, the effort required to implement an AI-based system should not be underestimated. Digitalised descriptions of all technical systems from a wide range of manufacturers must be available. The language models must be regularly fed with this information. The user then receives a text or voice interface to enter their requirements. Klinkhammer is also testing similar AI methods in other areas of the company, such as the servicing of logistics systems.
Klinkhammer will be providing information about its research and developments in AI-based planning support at LogiMAT in Hall 1, Stand D50. Here, visitors will have the opportunity to exchange ideas with experts from the industry.
