In 2020, our data science team launched a program focused on the application of high-frequency machine data for predictive maintenance with the goal of accelerating predictive analytics use cases for machine tools. Our team has recently discovered a way to collect data at 1 kHz directly from the control of CNC machines without using sensors that can immediately used as inputs to time-series or machine learning models to predict machine failures. We’re now excited to share those findings with you in what will be our first MachineMetrics Data Science Workshop!
As we continue to share both our data and data collection methodologies with the community, we’re learning key insights into how this methodology can accelerate the use cases of predictive analytics for the manufacturing industry as a whole.
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 we’ll be doing: We’ll be distributing a real dataset ahead of time to allow all participants to follow along in R/Python for real-time analysis.
Who Should Come: data scientists, managers, data science/technical directors, research scientists, and technical group heads
How To Sign Up: As this is a discussion, seats are limited to 20.