Tony Schmitz Professor
How Process Damping Impacts Milling Stability
Process damping is a phenomenon that can increase milling stability at low cutting speeds and is affected by the cutting edge design.
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Applying Machine Learning for Milling to Prevent Chatter
Machine learning is used to predict system behavior based on process data. It can be used to model milling behavior and improve performance.
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Understanding Structured Light Scanning Measurements
Structured light scanning is used to create a digital twin of a manufactured part, but we must understand the measurement reproducibility to best use the data.
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Machining is More Than Geometry
While CAD/CAM software may represent machining operations as geometry, you must consider vibration effects to obtain a successful outcome.
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Using Digital Tap Testing to Measure Machining Dynamics
Tool-toolholder-spindle-machine combinations each have a unique vibration response. We can measure the response by tap testing, but we can also model it.
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Incorporating AFSD Into Hybrid Manufacturing Processes
Additive friction stir deposition (AFSD) is a new, solid-state additive manufacturing process that provides an alternative to beam-based AM processes.
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How to Evaluate Measurement Uncertainty
Manufacturing and measurement are closely coupled. An important consideration for the use of measurement results is the associated measurement uncertainty. This article describes common metrology terms and provides an example uncertainty analysis.
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Solve Worker Shortages With ACE Workforce Development
The America’s Cutting Edge (ACE) program is addressing the current shortage in trained and available workers by offering no-cost online and in-person training opportunities in CNC machining and metrology.
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The Impact of Cutting Teeth Spacing on Machining Stability
Many cutter designs are available, and variable teeth spacing (or variable pitch) cutters can be used to influence milling stability. Let’s discuss why teeth spacing affects stability.
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How Modal Testing Can Reveal Dynamic Machining Responses
Tool-holder-spindle-machine combinations each have a unique dynamic response in the same way that each person has a unique fingerprint, which can be revealed using modal testing.
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