Smart Molding International 4-2022

46 smart_molding international 4/2022 sensors N ETZSCH Process Intelligence, a co r po rate vent u re o f NETZSCH Group (Germany), has announced the l aunch of sensXPERT, a technology business de- signed to deliver significant produc- tivity and quality benefits to proces- sors in the plastics industry through data-driven manufacturing solutions. The integrated approach builds on the Group’s 50+ years of know-how in the fields of material science and sensor technology. sensXPERT combines real-time material data from the mold with advanced machine learning software to analyze the material behavior. The sma r t t e chno l og y enab l e s continuous process optimization for up to 30 percent increase in production efficiency. Its technological advanced in-mold sensors provide real-time insights and transparency to react to material deviations and eliminate scrap. While allowing a dynamic and adaptive production, thus maximizing throughput, sensXPERT ensures direct in-process quality control of each single molded part. “There is a growing need for digital technology solutions in the plastics processing industry to meet the challenges of tighter cost control, total quality assurance and enhanced sustainability,” says Dr. Alexander Chaloupka, Managing Director & CTO for sensXPERT. “By using the artificial intelligence of our machine learning software to evaluate critical material, machine and process data, we help our customers optimize their manufacturing efficiency in real time, eliminating the need for time and labor consuming retroactive adjustments.” At t he hea r t o f s en s XPERT ’s manufacturing solutions, an Edge Device integrates the hardware and software for machine learning models designed to capture even the slightest deviation of material and process parameters. Based on measuring data collected from high-precision in- mold sensors, smart machine learning algorithms are applied to simulate, predict and analyze the actual material behavior on each individual machine. The learning models are trained with key parameters, including standard material and experimental data, such as glass transition temperature, pressure and required degree of curing, and are then continuously fine- tuned depending on the in-situ data measured over time. Developed by NETZSCH Process Intelligence, sensXPERT, combines real-time material data from the mold with advanced machine learning software to analyze the material behavior. The smart technology enables continuous process optimization for up to 30 percent increase in production efficiency. Its technological advanced in-mold sensors provide real-time insights and transparency to react to material deviations and eliminate scrap. Continuous process optimization Picture: NETZSCH Group