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Tool Run-Out in Micro-Milling: Development of an Analytical Model Based on Cutting Force Signal Analysis
Andrea Abeni1, Cristian Cappellini2, Greta Seneci1
1Dipartimento di Ingegneria Meccanica ed Industriale, Università degli Studi di Brescia, via Branze, 38, 25123 Brescia (BS), Italy.
Micromachines
|March 28, 2024
Summary
This study introduces a novel analytical method for calibrating micro-machining tool run-out models using cutting force signals, eliminating the need for time-consuming geometric measurements in biomedical device fabrication.
Area of Science:
- Manufacturing Engineering
- Materials Science
- Biomedical Engineering
Background:
- Micro-machining is crucial for fabricating precise biomedical devices.
- Transitioning to micro-scale machining presents challenges, including tool run-out.
- Tool run-out is difficult to measure experimentally and complicates process optimization.
Purpose of the Study:
- To develop a new analytical method for describing tool run-out in micro-machining.
- To calibrate micro-machining model parameters using cutting force signal analysis.
- To eliminate the need for dimensional measurements in run-out prediction.
Main Methods:
- Developed a novel analytical model for tool run-out.
- Utilized cutting force signal elaboration for model parameter calibration.
- Tested the procedure on micro-machined additively manufactured AlSi10Mg specimens.
Main Results:
- Successfully calibrated micro-machining model parameters without dimensional measurements.
- Demonstrated a new method for analyzing tool run-out based on force signals.
- Validated the approach on additively manufactured materials.
Conclusions:
- The developed analytical strategy offers a promising, mathematically robust approach to tool run-out analysis.
- This method significantly reduces the time and complexity associated with run-out prediction.
- Further research can expand upon this foundation for advanced micro-machining applications.
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