Professor Hopmann, why does the plastics industry need its own AI network?

Hopmann: Because the challenges that companies face in the field of artificial intelligence are very specific – both in terms of data and production processes. Many companies know that AI offers potential – but they are faced with the question: Where should I start? Will it pay off? What data do I actually need? This is exactly where our network comes in. We create space for exchange, impart knowledge and develop viable approaches together with the industry.

Who is the network intended for? Who should feel addressed?

Hopmann: Our offering is aimed at all players along the value chain – from material manufacturers, machine builders and processors to product developers and those responsible for digitalization. Access for small and medium-sized companies, which often do not have their own data science teams, is particularly important to us, and if you want to know how AI can be used practically and economically, you’ve come to the right place.

What questions do companies typically bring with them when they approach you?

Hopmann: The spectrum is broad. Many people ask themselves: Does it even pay off? How long does it take until I see an ROI? Others want to know how they can get started with their current data situation or how much personnel effort is required. It gets particularly exciting when we work together on use cases – for example, how product developments can be accelerated or how processes can be automated without having to turn the entire production process upside down.

AI often sounds abstract. How concrete is the network?

Hopmann: Very specific. We talk about real challenges – such as how visual quality controls can be automated, how anomalies can be detected at an early stage and how production data can be used to make predictions. We also bring research into play: for example, how simulations and real process data can be combined. And we help to implement the first steps – from pilot projects to the introduction of an AI tool in everyday life.

What do you say to companies that think: “We don’t have the capacity for that”?

Hopmann: We often hear that – and that’s exactly why the network is there. We offer entry points with manageable effort, structure topics and make knowledge accessible. It doesn’t always have to be the big digitalisation project. A clearly defined use case is often enough to create real added value. And we accompany companies on this path – with technical know-how, but also with an understanding of economic realities.

What is your wish for the future of the network?

Hopmann: I would like us to work together with the industry to show how AI can be used responsibly, pragmatically and effectively. And that we are not only making processes more efficient, but also creating new areas of innovation – for products, for business models and for the next generation of plastics engineers.