Vibration Analysis and Stability Prediction of CNC end-milling
This Master's Thesis investigates the process of stability prediction for milling process.
Stability prediction for a given tool-workpiece combination can maximize material
removal rate while maintaining vibrational stability. Milling is modelled as a
time-delayed system with single degree of freedom. Temporal Finite Element Analysis
& Spectral Element Analysis algorithms have been prepared to solve those. TFEA
algorithm is then customized for milling process to prepare stability charts for a given
The algorithm is verified by experimental means. A compliant system is designed
and manufactured for cutting tests. Impact modal tests are performed to extract
modal parameters, which are used to produce stability charts. Milling test passes are
done on the workpiece for various combinations of spindle speeds and depths of cut.
Real-time workpiece displacement and spindle speed data is used to identify stability
of the cuts. These are then analyzed and compared with stability predictions.
The findings of this work indicate considerable agreement of theory with experiment.
TFEA algorithm was able to predict stability accurately for low spindle
speeds. They also suggest the need to consider dynamics of the cutting tool and to
model a second degree of freedom for more accurate predictions.
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
Rights for Collection: Masters Theses