SAY GOODBYE TO SCRAPPED PARTS.
Supercharge your predictive analytics with high-frequency machine data. Diagnose, predict, and avoid failures with unprecedented visibility into the condition of your tooling with no sensors required.
Understanding why issues have occured on machines in the past has been a notoriously difficult task. While low-frequency data can accomplish condition-based monitoring, Trying to do condition-based monitoring on say, spindle load, requires higher fidelity.
Collecting high frequency data from the control delivers unprecedented visibility and fidelity into the health and condition of the machine, enabling diagnoses that were once impossible.
Pushing cutting tools too hard leads to high tooling costs and frequent downtime for changeovers. Not pushing machines may reduce tooling costs at the expense of throughput.
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. This causes problems like bad finishes and incomplete cuts on parts that must then be scrapped once they make it to QA.
Reduce these issues with tool chatter detection. Predict when parts go out of spec before they need to be scrapped or when parts will soon become out of spec.
Expensive tools that snap when they become over-stressed, breaking not only that tool but even those further down the line.
Detect when initial stress fractures are occurring in tools, and alert the operator to take them out of commission before it gets worse.
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Join hundreds of Manufacturing organizations across the globe that use MachineMetrics software to collect, monitor, analyze, and take action on their manufacturing equipment data.
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