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KraussMaffei is Advancing Digital Research and Teaching in the Field of Injection Moulding

KraussMaffei is Advancing Digital Research and Teaching in the Field of Injection Moulding

  • Friday, 11th January 2019
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  • Reading time: about 2 minutes

By providing a new injection moulding machine from the all-electric PX series, KraussMaffei is supporting the Chair of Engineering Design and Plastics Machinery at the ipe of the University of Duisburg-Essen.

The PX 120-380 features complete digital equipment including the DataXplorer. The shared goal is to develop new systems and applications and to use the acquired data as a basis for giving product and process quality a sustainable boost.

The all-electric PX 120-380 injection moulding machine with a clamping force of 1,200 kN is part of a fully automated production cell along with linear robot and conveyor. This makes it possible to run processes in a way that resembles those in the real-life industry more closely than previously. “The production cell measures up to the state of the art of technology in every respect and enables us to merge research and practical applications in digitalisation – not least thanks to the cell’s complete digital equipment,” explains Prof. ReinhardSchiffers, Chair of the Department of Engineering Design and Plastics Machinery (KKM) at the University of Duisburg-Essen.

The overall digital package for the PX 120 includes, for example, the DataXplorer from KraussMaffei. The DataXplorer is an analysis tool that gives you a nearly ‘microscopic’ view of the process. This makes it possible to react to unclear fault patterns. Depending on the machine’s equipment, the DataXplorer displays up to 500 high-resolution signal paths, visualises these signal paths and makes them available for evaluation. These can be standard signals of the machine or special signals such as the mould cavity pressure.

The joint research and development efforts at ipe are focused on applications and services that closely resemble their real-world counterparts, as well as virtual assistance systems in the areas of autonomous process control, condition monitoring and predictive maintenance. This applies to both the basics and ideas relating to specific products. Additional focal points include IoT (Internet of Things) platforms, digital infrastructures and standards for connecting machines to higher-level systems or peripherals. Another goal is to collaborate on the development of new data analytics applications so that raw data can be turned into valuable information.


Image provided by KraussMaffei


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