Forward-thinking plastic processing system boosts injection molding efficiency

A new, intelligent process system that combines real-time shape data with machine learning software promises to increase plastic manufacturing efficiency by up to 30%.

Germany’s Netzsch Process Intelligence’s SensXPERT technology analyzes material behavior using in-mold sensors that enable dynamic, adaptive production by reacting to material deviations, the company says. Customers can connect sensXPERT to existing production and control systems with standard interfaces or use it as a cloud-based service.

At the heart of the sensXPERT manufacturing solution is the edge device, which evaluates hardware and software to create models that capture the smallest deviations in the material and process. The resulting algorithms simulate, predict and analyze material behavior on individual machines. Important parameters such as glass transition temperature, pressure and curing requirements “train” these process models, which are continuously refined.

The technology has already proven successful in manufacturing composite wheels and aircraft wing components, the company noted.

Image courtesy of NETZSCH Process Intelligence
SensXPERT offers a real-time window on plastic processing parameters for quality assurance.

“Stakeholders of Industry 4.0 need real-time answers to what is happening in their manufacturing processes,” says Cornelia Beyer, Managing Director and CEO of sensXPERT. “Our unique approach unlocks the potential of fully data-driven productivity, delivering immediate quality and efficiency benefits to our customers in the plastics processing industry.”

SensXPERT technology works with a wide range of materials and methods – including thermosets, thermoplastics and elastomers, as well as injection, compression and transfer molding or thermoforming, vacuum infusion and autoclave curing. A web app allows users to access the system remotely.

SensXPERT will be exhibited October 19-26 at Netzsch Process Intelligence booth C36 in Hall 12 at K 2022 in Düsseldorf, Germany.

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