Improving FEM model of low immersion milling process using multi-objective optimization of tool elastic support dynamic properties

Improving FEM model of low immersion milling process using multi-objective optimization of tool... The accurate prediction of tool displacement on elastic support is always considered a crucial problem in metal cutting process simulation. Static and dynamic properties of a machine tool structure which are the function of boundary conditions of a tool-tool holder, modal parameters of an end mill, and interface of cutting edge with a workpiece can affect the displacement of the end mill. In this paper, the receptance coupling substructure analysis (RCSA) and multi-objective optimization algorithm, NSGA-II, are combined to determine the elastic support properties. The investigated effective parameters include the tool-tool holder contact length, clamping torque, and the tool length ratio to diameter. In order to evaluate the accuracy of results and simulate the low immersion end milling process, a novel FEM model is created in which the constant stiffness and damping have a linear relationship along the elastic support. The frequency response function-obtained FEM models have good accordance with experimental data. Using this model and linking the FEM model with MATLAB software, cutting forces and tool displacements are simulated. The accuracy of the suggested method is evaluated by simulating two case studies based on different cutting conditions. Comparison between simulation and experimental results indicates that the suggested model can precisely predict the cutting force and tool displacement. The proposed model can be used to simulate the milling processes for various tool boundary conditions in forced and free vibration states, and the consumed time for simulation of process is significantly reduced. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The International Journal of Advanced Manufacturing Technology Springer Journals

Improving FEM model of low immersion milling process using multi-objective optimization of tool elastic support dynamic properties

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Publisher
Springer London
Copyright
Copyright © 2017 by Springer-Verlag London
Subject
Engineering; Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design
ISSN
0268-3768
eISSN
1433-3015
D.O.I.
10.1007/s00170-017-0261-x
Publisher site
See Article on Publisher Site

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