KI4KI Understanding and using artificial intelligence for the plastics industry
© IKVHow can artificial intelligence (AI) and digitalisation methods make a concrete contribution to increasing efficiency in the plastics industry? As part of KI4KI – Artificial Intelligence for the Plastics Industry, we are networking players along the entire plastics industry value chain.
Together, we develop viable and practical strategies to successfully introduce and use AI molds – individually, scalably and sustainably
We want to achieve this together
Recognising and harnessing potential: Identifying relevant AI applications and digitalisation opportunities for plastics processing companies.
Build competence: Enabling professionals to actively use and further develop AI methods.
Create transfer: Support in the concrete use of AI molds in the company – from needs analysis to implementation.
Ensuring competitiveness: efficiency gains and innovative strength through data-based decisions and automated processes.
Become part of KI4KI!
Together we make AI applicable: Through KI4KI, we are putting digitalization and artificial intelligence into practice – along the entire plastics value chain.
The network is aimed at players along the entire plastics value chain:
- Material manufacturer
- Machine and plant manufacturers
- Processors and compounders
- Toolmakers
- Product developers and designers
- IT and digitization managers
- SMEs with a desire for a practical introduction to the world of AI
Contact us for more information, e.g. at K 2025
Mauritius Schmitz
Digitalisation
KI4KI and Brainbridge at K 2025
How can artificial intelligence be used in the plastics industry? With the AI4KI project, the IKV is demonstrating how AI can make processes more efficient and enable new innovations along the entire value chain.
One of the first tangible results is MVP Brainbridge.Knowledge powered by IKV, which we will be presenting at K 2025. Visitors will be able to try out live how the IKV’s extensive research literature can be structured and accessed in a targeted manner with the help of an AI-based search. This example clearly demonstrates the potential of the technology: if complex research content can be made easily and intuitively accessible, the same applies to corporate knowledge – from technical documentation to experience reports from projects.
Brainbridge.Knowledge powered by IKV thus opens up new possibilities for digital knowledge transfer:
- Knowledge remains available across generations of employees
- Onboarding and offboarding processes are made easier
- Project documentation and experience can be accessed at any time
In the long term, the platform is to be established as a common umbrella for the plastics industry. IKV funding companies could use Brainbridge.Knowledge powered by IKV in the future to make internal know-how as easily accessible as research literature.
Experience how data becomes knowledge – and knowledge becomes added value – at K 2025. AI4KI and Brainbridge will demonstrate how digitalisation can be approached holistically in the plastics industry: AI improves processes and makes knowledge available within the company. Discover both approaches at K 2025 – interactively and practically. Visit us at stand C16 in hall 14!
“Using artificial intelligence doesn’t have to be a major project”
Interview with Prof. Christian Hopmann
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.
