Virtual Five-Axis Milling of Free-Form Surface-Part I: Process Modeling

Li Qiang Zhang; Ye Cui Yan

doi:10.4028/www.scientific.net/AMM.29-32.424

Paper Titles

Research on Coupled Water Hammer in Hydraulic Pipe System
p.401

The Resistance-Heated Furnace Temperature Control Based on CMAC-Fuzzy Immune PID Control
p.407

Numerical Simulation of Oscillating Flows over a Circular Cylinder
p.414

Level Set Based Mesh Model Simplification
p.420

Virtual Five-Axis Milling of Free-Form Surface-Part I: Process Modeling
p.424

Virtual Five-Axis Milling of Free-Form Surface-Part II: Feed Optimization
p.430

The Identification of the Natural Frequency of Rolling Bearing Rotor System Based on Combined Genetic Neural Network
p.436

A New Design Method for Waste Gas Efflux Self-Sucking Device Based on the Isentropic Gas Flow Theory
p.442

Time Domain Identification of Distributed Dynamic Load of Rotating Timoshenko Beam Based on Orthogonal Polynomial
p.448

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 29-32Virtual Five-Axis Milling of Free-Form...

Virtual Five-Axis Milling of Free-Form Surface-Part I: Process Modeling

Abstract:

In free-form surface machining, it is essential to optimize the feedrate in order to improve the machining efficiency. This work is the first of a two part paper on cutting force prediction and feedrate optimization for five-axis milling. Conservative cutting parameters have been mostly used since there was a lack of physical models and optimization tools. Part and tool deflections under high cutting forces may result in poor part quality. The extracted cutter workpiece engagements are used as input to a force prediction model. The predicted cutting forces are shown to be in reasonable agreement with those collection during a roughing operation on a dual blades part.