Supercharge Your Predictive Tooling and Quality Applications with High-Frequency Machine Data
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In 2020, MachineMetrics launched a program focused on the application of high-frequency machine data for predictive maintenance to accelerate predictive analytics use cases for machine tools. During that time they’ve developed a way to collect this data from the control of CNC machines without using sensors that can immediately be used as inputs to predict machine failures. MachineMetrics is now excited to share this methodology with you in what will be their first MachineMetrics Data Science Webinar!
Sign up now and learn how you can start leveraging high-frequency machine data to diagnose and predict various types of failures on your machines (or even stop them from happening in the first place!).
- What is high-frequency data and why it's a game-changer for predictive analytics
- How to optimize your tooling usage to reduce tooling costs
- How to detect when a tool is about to break so you can avoid downtime
Head of Data Science, MachineMetrics
Lou Zhang is Head of Data Science at MachineMetrics. Lou has extensive experience with both the manufacturing industry and with developing predictive algorithms for time-series data. Prior to MachineMetrics, Lou conducted research with NIST and AMT.