Networked Production with an Adaptive System
Kistler Puts Artificial Intelligence into Plastics Processing
At K 2019, the metrology experts at Kistler AG, Winterthur, Switzerland, showed how artificial intelligence will pave the way for the smart factory. ComoNeoPredict, a module of the ComoNeo process monitoring system, allows model-based prediction of the desired part quality based on the cavity pressure and temperature profiles.
The quality model provided by intelligent software is based on a neural network and provides the basis of high-precision, efficient injection molding. The network is first trained with the correlation between the sensor data of the process, recorded over a long period, and the quality features of the part. The system then continues to learn intelligently. The cavity pressure can be measured directly, indirectly or even contactlessly (with a measuring pin); the evaluation takes into account the entire curve, not only the maximum or integral. The quality feature is then displayed mathematically as a numerical value. In addition, quality-relevant process data are made available platform-independently via OPC UA for use in analyses.
According to Kistler, ComoNeo is the central module of the digital supply change, not only at a horizontal process level on the shop floor. On a vertical level, all the process data can be transferred to higher-level systems such as MES or ERP. At a process level, ComoNeo provides various functions, including a cavity-pressure-based process-monitoring system, also for multi-component injection molding (ComoNeoMerge), automated switchover to holding pressure (ComoNeoSwitch), as well as balancing of hot-runner systems in multicavity molds through individual readjustment of the nozzle temperatures (ComoNeoMultiFlow).
Kistler Instrumente AG
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