3 new OMRON technical papers published

We are pleased to introduce you that 3 new papers have been published on the web.

Prediction of the Characteristics of Flame Retardant Coagent for Polyester Using Deep Learning Technology and Evaluation of the Retardancy
IMAIZUMI Toyohiro / OTANI Osamu
Using deep learning technology, we searched for an alternative flame retardant coagent to antimony trioxide,which is a flame-retardant aid for polyester resins. Specifically, a deep learning model for physical property prediction was constructed based on the flame retardancy mechanism, and candidate materials were predicted and extracted. ...

Study of Analysis Method for Conducted Noise Caused by High Frequency Leakage Current for Servo Drive Systems
HAMANA Kentaro / TOKUSAKI Hiroyuki / UEMATSU Takeshi
The declining working population and the energy saving of production sites for decarbonization have become major social issues. Toward this end, methods to effectively utilize the regenerative power of motors have been proposed, and DC powering of servo drives is expected to achieve this. ...

Custom Mechanics to Realize Virtualization of Whole Facility Using Physical Simulation
In recent years, rapidly changing market needs has led to a trend of shorter product lifecycles. To keep up with such market trends, it is necessary to shorten the launch time for production facilities. We introduced virtualization technology in our FA integrated development environment, Sysmac Studio, which enabled debugging without physical machines using a 3D simulation. ...

We look forward to reading these papers.