Industrial AI In Plastics Processing – When Skilled Workers Are in Short Supply

Production systems are becoming increasingly complex, while skilled workers are becoming increasingly scarce. For many companies in plastics processing, this is already a reality. Industrial AI addresses this challenge directly: it is gaining importance across industry because it enables knowledge, processes and decisions to be scaled. Using Reifenhäuser NEXT as an example, we show how Industrial AI can be integrated into day-to-day production in a practical way.

Production systems in plastics processing are becoming more networked and data-intensive. At the same time, the shortage of skilled labour is becoming increasingly acute. Experienced machine operators are difficult to find, onboarding times are increasing, and valuable know-how is lost through staff turnover. For many companies, this results in a double pressure: rising demands on productivity, quality and efficiency combined with a declining availability of experienced personnel.

In everyday production, this is reflected, among other things, in:

• a high dependency on individual specialists
• longer downtime when problems occur
• fluctuating results during shift or staff changes
• increased effort required for training and onboarding

Conventional automation can help stabilise processes, but it cannot replace the implicit knowledge of experienced operators. Industrial AI therefore shifts from being a future topic to a concrete response to a structural challenge – not as a replacement for people, but as a tool for scaling knowledge and decision-making in daily production.

Industrial AI is often compared with well-known AI applications from the consumer space. However, very different requirements and objectives apply when it comes to plastics processing:

How these differences play out in practice is explained by Marcel Perrevort, Chief Sales Officer of the Reifenhäuser Group, in an interview at K 2025:

How Industrial AI can be integrated into everyday production was demonstrated by the Reifenhäuser Group at K 2025 with the launch of Reifenhäuser NEXT. The new business unit bundles AI-based assistance systems, digital learning offerings and data-driven applications into an integrated ecosystem.

The aim is to support producers in:

• increasing productivity, quality and OEE
• reducing dependence on highly qualified personnel

The portfolio is structured around three closely interlinked components.

Studies already indicate that the targeted use of AI in industrial production offers considerable potential. What is crucial, however, is a solution that is precisely tailored to existing processes. This is exactly what the modular approach of Reifenhäuser NEXT enables.

Industrial AI is not a response to the shortage of skilled labour in the sense of reducing headcount. It is a tool for democratising knowledge, experience and decision-making – and thus for safeguarding productivity and quality in the long term.