Zyfra, Finnish-Russian industrial digitalization leader, has developed predictive analytics solution powered by machine learning to enhance the capabilities of metalworking machines by detecting anomalies in technological process and identifying their possible cause.
ZyfraPdA solution analyses the real-time data from CNC machines, alerts users whenever an anomaly emerges, and indicates the possible cause while giving recommendations for further actions. The system classifies a range of anomalies like tool quality, operator error in case of incorrect operating modes selection and machine failure.
“Manufacturers of large-dimensioned products made of expensive materials face a detect defection problem. Defects are caused by many factors such as the quality of the cutting tools, technological faults, equipment wear, etc. There is a need for an intelligent system which will take into account all the necessary information from equipment monitoring systems, evaluate the impact of this information on defects and help operators and technologists to make decisions,” said Alexander Smolensky, Business Development Director, Zyfra.
For more details visit: https://www.zyfra.com/
