At Chinaplas 2026 in Shanghai, the ENGEL Group presented six production solutions from the automotive, packaging, medical and technical moulding sectors in live operation. A foammelt application in technical moulding showed how material usage, component weight and unit costs can be reduced through physical foaming. In addition, ENGEL presented inject AI as a dedicated focus, with which digital assistance systems are specifically extended with AI-based functions. Both approaches contribute to stabilising processes, reducing scrap and improving the cost efficiency of series production.
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| Image 1: The WINTEC t-win 6500 two-platen injection moulding machine with integrated viper 20 linear robot enables the cost-efficient production of large-volume components at short cycle times. |
foammelt reduces material usage and component weight in interior applications
A further exhibit in the field of technical moulding was a production solution with a WINTEC t-win 6500 two-platen injection moulding machine with 6,500 kN clamping force. The production of a mini refrigerator housing using foammelt wass presented. This application shows that complex white goods components can be produced more lightly and cost-effectively with physical foaming without compromising design. The use of foammelt reduces cycle time, weight and material consumption, thereby sustainably lowering unit costs. In physical foaming, material savings of up to 40% are possible depending on the application.
foammelt operates with nitrogen or carbon dioxide, which is introduced into the polymer melt. The MuCell screw geometry optimised for foammelt distributes the gas evenly, resulting in a fine cell structure in the mould. The result is a lighter component with simultaneously high dimensional stability and stiffness. In the application shown at Chinaplas, a PP compound with 20% long glass fibre was processed. The part weight was 493 g, the cycle time 62 seconds.
The t-win from WINTEC is characterised by its robust two-platen design for applications with large moulds and high clamping forces. Short-stroke pressure cushions enable short cycle times, while synchronous locking and the servo-hydraulic drive operate quickly and energy-efficiently. High energy efficiency, a compact footprint and optimised maintenance accessibility reduce total operating costs and lead to a fast return on investment.
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| Image 2: The mini refrigerator housing produced using MuCell shows how material usage and component weight can be reduced through physical foaming while maintaining stable component quality. |
With iQ weight control, viscosity fluctuations are automatically compensated within the same shot in this exhibit. This made it possible to reduce scrap in this application by 37%.
The injection moulding cells from WINTEC are equipped with the intuitively operated C3 control. It supports clear process control with high performance. In addition, the new viper 20 linear robot is fully integrated into the control, handles the parts and relieves the operating personnel. The close integration of robot and machine within one control system increases production stability and reduces cycle times through the optimisation of motion sequences.
Increased system availability and lower costs through AI-based assistance systems
With inject AI, ENGEL specifically extends its established iQ assistance systems with AI-based functions and further develops the proven inject 4.0 platform into a connected and learning production environment. This was demonstrated in the expert corner at the exhibition stand. Already today, solutions such as iQ weight control, iQ clamp control, iQ flow control, iQ melt control and iQ motion control intervene directly in the process and automatically optimise quality- and efficiency-relevant parameters. For example, iQ weight control compensates for fluctuations in material viscosity in real time and ensures consistent component quality. iQ clamp control dynamically adjusts the clamping force and thus reduces mould stress and energy consumption. iQ flow control stabilises temperature control, while iQ melt control monitors plasticising and detects process deviations at an early stage.
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| Image 3: inject AI improves process stability, reduces scrap, lowers production costs and increases system availability through AI-based process optimisation. |
For processors, this results in a comprehensive support system that not only stabilises processes but also continuously optimises them. The iQ process observer uses AI to analyse more than 1,000 process parameters simultaneously, detects deviations at an early stage and derives specific recommendations for action. This is complemented by the ENGEL Virtual Assistant, which makes system-specific knowledge immediately available, as well as by AI-based applications such as the part finder for the rapid identification of spare parts via photo. Overall, this improves the cost efficiency of production through reduced scrap, higher system availability and more efficient use of machine and personnel resources.
The ENGEL Group: Broad technological spectrum from technical moulding to inject AI
At Chinaplas 2026, the ENGEL Group presented a broad spectrum of production solutions for different requirements in injection moulding production. These included applications from the automotive, packaging, medical and technical moulding sectors as well as digital solutions for further optimisation of production. In the field of technical moulding, it becomes clear how even large-volume and demanding components can be manufactured cost-efficiently. With inject AI, ENGEL at the same time set a dedicated focus on the path towards a more connected, learning and operationally efficient production.
For processors, this results in a clear benefit: production processes can be controlled more stably, scrap and costs can be reduced, and machine and personnel resources can be used more efficiently. Visitors to the ENGEL Group stand therefore gained not only insight into individual machines and applications, but also into a broad spectrum of solutions for cost-efficient and future-proof series production.
All images: ENGEL
