MachineMetrics has connected to thousands of machine tools, enabling our data scientists to build algorithms that can predict quality defects and extend tool life. Machine tool operators label data using the operator interface when tool failures or quality defects occur. Our ML/AI Algorithms detect patterns from the hundreds of data items collected from each machine that can detect these problems before they occur again and stop the machine before failure occurs.
Detect when initial stress fractures are occurring in tools, and alert the operator to take them out of commission before they fail or break.
An increase in tool wear due to differences in material, environment, and cutting can be detected, allowing you to run your tools to full life every time.
When tools are compromised, they don’t do their job right. Reduce bad finishes and incomplete cuts with tool chatter detection.
Leverage high-frequency data directly from the machine control or from sensor data. Use this data as inputs to time-series or machine learning models.
Deploy and manage custom algorithms to MachineMetrics Edge devices that process and analyze at the source to detect potential failures.
When an algorithm is triggered, deliver operator actions via alerts/notifications to factory workers or automate a feed-hold that stops machines prior to equipment failure.
It's not enough just to know the problem. Predictive notifications allow the right person to take immediate action. Even better? Deploy edge applications to stop the machine automatically when algorithms detect problems.
Identify anomalous behavior that could result in machine or tool failures up to an hour before it occurs.
Predict catastrophic machine failures that cause safety issues at your plant by detecting and stopping the machine before the problems build up to this point.
Remote diagnostics and maintenance recommendations for OEMs and tooling providers to resolve issues with tools without on-site visits.
