9907-167

The capabilities of the 9907-167 provide the basis for machine builders and manufacturers to improve machine performance, 9907-167 through predictive maintenance, process self-optimization and autonomous detection of process anomalies. Through machine learning, automation controllers can learn the required algorithms from process data. With this alternative approach, ML models can be trained and then used to provide solutions. This is designed to help open up possibilities in areas including predictive maintenance and process control, anomaly detection, collaborative robots (cobots), automated quality control and machine optimization. Models to be learned are trained in an ML framework such as MATLAB or TensorFlow and then imported into the TwinCAT runtime via the Open Neural Network Exchange Format (ONNX), a standardized data exchange format for describing trained models.

9907-167 Features:
Higher performance and efficiency thanks to a powerful 520MHz XScale 32-bit RISC processor.
Dual USB host ports are compatible with peripheral devices such as mice, keyboards, printers and USB disks.
An on-board standard SD card slot and USB host port can be used for uploading/downloading applications, and recipe data from/to the panel as well as historical data can be stored on the card.
A 3.5 mm audio port is available for speakers, and some models support a dual-channel video input interface.
RJ45 Ethernet interface and optional CANopen, Profibus and MPI interfaces are available.