Date of Award
Winter 2012
Project Type
Thesis
Program or Major
Mechanical Engineering
Degree Name
Master of Science
First Advisor
Barry Fussell
Abstract
A Smart Machining System being developed at UNH has the potential to produce high quality machined parts in minimum time. Integral to the success of this system is the ability to accurately simulate cutting forces. In this current work, a time-domain milling simulation is developed with a tool-workpiece compliance model to predict dynamic cutting forces. The simulation computes milling forces, tool deflections, and workpiece vibration (surface waviness).
The accuracy of the simulation depends on finding reliable system parameters. In this work, an end milling parameter identification method is developed using linear predictive coding (LPC) and Extended Kalman Filtering. The milling simulation model is validated by comparison of simulation and experimental forces for a variety of end milling cuts. In-cut and out-of-cut damping is shown to be significantly different, and must be considered in the simulation model. This milling force simulation is shown to predict chatter reasonably well under controlled cuts.
Recommended Citation
Koh, Min Hyong, "Identification of system parameters for end milling force simulation with tool and workpiece compliance" (2012). Master's Theses and Capstones. 761.
https://scholars.unh.edu/thesis/761