Logistics / AI logistics

Artificial Intelligence Is Entering Logistics

AI is gradually making its way into everyday work in logistics, where it helps reduce unnecessary manual work and speed up the processing of the data needed.

In logistics specifically, AI helps process large volumes of data, find important information within it, flag deviations and automate tasks that previously required manual work. At Škoda Auto, this approach is reflected, for example, in the AI DISPO and AI SAP Assistant projects, as well as in a number of smaller applications (see the box Other AI and Digitalisation Solutions).

AI DISPO

One of the main projects in logistics is AI DISPO. Its aim is to create a system that can propose an optimal order of materials from suppliers, the so-called ideal call-off. To make decisions, the system works with a range of logistics data. It takes into account current production needs, stock levels, materials in transit, packaging rules and information about lorries. The result is better coverage of production needs, more efficient use of transport capacity and stock levels kept within set limits. Time savings are important too. Routine tasks that currently take up part of dispatchers' working time are taken over by the system. Employees can therefore focus more on situations where their experience and decision-making skills are needed.

AI DISPO is also continuing to develop. The team is working on incorporating additional data sources and new functionalities. One of these will be intelligent notifications. The system will be able to flag possible delivery problems or deviations from the plan before they affect production.

AI SAP Assistant

Another area where AI can save time is working with information. The new AI SAP Assistant tool, for example, allows users to obtain data from SAP and other sources through a natural dialogue. Instead of going through several systems and searching for information in documentation, the user simply asks a question. The assistant works not only with data from SAP but also with internal documentation and guides. The solution is built on Microsoft Azure cloud technologies.

"The purpose of using these two new tools is not to replace the knowledge of specialists. On the contrary, AI is meant to take over mainly time-consuming searching and work with information. This allows experts to devote more time to actually solving tasks and making decisions," says Mojmír Barák, coordinator of the PLS/2 – Digitalization Projects and Strategy department.

What Do All the Projects Have in Common?

The point is not to add AI to logistics just because it is a current technology. The shared goal of the individual solutions is to remove unnecessary manual work, get to the needed information faster and use data where it helps with decision-making.

"AI in logistics doesn't have to mean a big revolution overnight. It's often a seemingly small change, an automatic notification, faster retrieval of information or document processing. But such tasks can add up and save employees a considerable amount of time," adds M. Barák.