Stabilizing Fluctuations in Recycled Material Processing Using AI

At Fakuma 2026, ARBURG will introduce the Hopper AI tool from plus10, which is integrated into the Gestica control system: The self-learning software analyzes quality-relevant process data in real time and automatically suggests appropriate parameter adjustments to the machine operator to prevent scrap from occurring in the first place. On display at ARBURG in Hall A3, Booth A3-3101.

Injection molding machines provide more data than ever before, yet scrap remains the most costly unsolved problem for many processors. Based on a survey of over 100 plastics processors, plus10 CEO Felix Georg Müller and Dr. Stefan Kruppa (kundu X) show where the real problem lies: not so much in a lack of data as in a lack of the ability to take action. Their solution: Process data becomes process intelligence when the system offers concrete recommendations for action instead of just providing yet another dashboard.

At TechXellence 2026 in the U.S., plus10, together with ARBURG, demonstrated the Hopper AI solution—fully integrated into GESTICA—live on an injection molding machine. The software detects the risk of scrap in real time and automatically recommends appropriate process parameters to reduce scrap and optimize production.