From the first instances of data recording to Al applications

More so than almost any other issue, digitalisation in production stands for technological change and gives rise to news and trends, including at EMO Hannover 2025. All this, despite the fact that digitalisation of machine tools is hardly a new topic. It began with the first computer numerical control (CNC) system in the 1960s. That actually makes it older than the world's leading trade fair for production technology which celebrates its 50th anniversary this year. Whether it is Industry 4.0, the Internet of Things or AI that are causing a stir among experts – one question is ever present: How can companies find the easiest and most economically sensible path to digitalisation?

- Author: Cornelia Gewiehs

"It is always a good idea for companies to first gain an overview of which applications are relevant for them," explains Dr. Markus Heering, Executive Director at EMO organiser VDW (German Machine Tool Builder's Association). According to him, one of the first and most important steps for any factory is to create transparency in production through targeted recording and exchange of data.

Data recording and networking made easy the benefits to be gained from this data are apparent when taking a look at the digital solutions offered by many machine manufacturers. Machines themselves are complex mechatronic systems which are now fully digitalised. This takes centre stage when building a self-contained data space (private cloud, intranet) that is limited to the relevant company. Open, standardised data interfaces are required to ensure that new machine tools as well as existing tools, machines from different manufacturers and even robots can communicate with each other and exchange data in production. The global initiative umati (universal machine technology interface) will once again demonstrate the benefits of standardised machine networking at EMO Hannover 2025.

The most important insight is that evaluating large quantities of data makes it possible to optimise production processes, identify errors early on and utilise resources more efficiently. This increases competitiveness on the global market significantly.

CURRENT APPLICATIONS AND TRENDS