PREDICTIVE MAINTENANCE: MEET YOUR NEW BEST FRIEND.
Supercharge your predictive analytics applications with high-frequency machine data to diagnose, predict, and avoid failures on your manufacturing equipment. No sensors required.
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.
Accelerate your data science team’s predictive analytics with data immediately usable as inputs to time-series or machine learning models. Use tools such as Spark, R, and Python to develop algorithms that detect these failures. Deploy and manage your custom algorithms to analyze data at the edge that send alerts to factory workers or stop machines prior to equipment failure.
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.
THE MACHINEMETRICS DIFFERENCE.
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