AI in Mechanical Engineering: Tanaro Schädler on Potentials, Limits and New Perspectives

Artificial intelligence is increasingly finding its way into mechanical engineering – including the packaging industry. In the Packaging People podcast from Packaging People and interpack, Matthias Laux talks with Tanaro Schädler, Innovation Engineer AI & Data at the Uhlmann Group, about the use of AI in pharmaceutical packaging environments, managing expectations and why openness toward new technologies is becoming increasingly important.

At the Uhlmann Group’s Future Lab, Tanaro Schädler works on integrating artificial intelligence along the value chain. He sees major potential especially in German mechanical engineering: “We are technologically leading in mechanical engineering and still have a lot of room for expansion in applying this technology.”

At the same time, he warns against extreme views on AI. On the one hand, the technology is often overestimated, for example when people fear that AI could fully automate processes and replace jobs. On the other hand, critics sometimes deny AI any real capability. “AI is not a cure-all, but it is a very capable tool,” he says.

Applications such as predictive maintenance, condition monitoring or support in PLC programming are already relevant today. At the same time, data availability plays a central role. “We cannot provide condition monitoring if we do not have data about the conditions,” Schädler explains.

He considers the interaction between generative AI models and company-specific knowledge particularly exciting. While large language models are mainly based on publicly available data, valuable know-how in mechanical engineering is often stored internally – for example in documentation or in the knowledge of experienced employees.

The pharmaceutical sector in particular is subject to strict regulatory requirements. This makes the direct use of many AI systems more difficult. “Non-deterministic systems do not always work in a fully predictable and explainable way,” says Schädler. That is why he currently sees the so-called human-in-the-loop approach as especially important: AI systems should provide recommendations that are then reviewed and evaluated by humans.

Looking to the future, Schädler expects further developments. He considers smarter and partly autonomous machines realistic in the long term. Initial developments such as predictive maintenance and autonomous error correction are already becoming visible.

As a participant in the interpack Young Talents Day, Schädler also emphasizes the importance of curiosity and openness toward new technologies. Especially in a traditional industry such as mechanical engineering, it is important to actively shape change. “Being open and curious about new possibilities is important to make this industry resilient for the future.”