期刊
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
卷 48, 期 6, 页码 629-643出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ijmachtools.2007.11.004
关键词
milling; finite element methods; transient thermo-mechanical loading; fixture; cutting parameters
The rigid body motion of the workpieces and their elastic-plastic deformations induced during high speed milling of thin-walled parts are the main root causes of part geometrical and dimensional variabilities; these are governed mainly from the choice of process plan parameters such as fixture layout design, operation sequence, selected tool path strategies and the values of cutting variables. Therefore, it becomes necessary to judge the validity of a given process plan before going into actual machining. This paper presents an overview of a comprehensive finite element method (FEM) based milling process plan verification model and associated tools, which by considering the effects of fixturing, operation sequence, tool path and cutting parameters simulates the milling process in a transient 3D virtual environment and predicts the part thin wall deflections and elastic-plastic deformations during machining. The advantages of the proposed model over previous works are: (i) Performs a computationally efficient transient thermo-mechanical coupled field milling simulation of complex prismatic parts comprising any combination of machining features like steps, slots, pockets, nested features, etc., using a feature based milling simulation approach; (ii) Predicts the workpiece non-linear behavior during machining due to its changing geometry, inelastic material properties and fixture-workpiece flexible contacts; (iii) Allows the modelling of the effects of initial residual stresses (residing inside the raw stock) on part deformations; (iv) Incorporates an integrated analytical machining load (cutting force components and average shear plane temperature) model; and (v) Provides a seamless interface to import an automatic programming tool file (APT file) generated by CAM packages like CATIA V5. The prediction accuracy of the model was validated experimentally and the obtained numerical and experimental results were found in good agreement. (C) 2007 Elsevier Ltd. All rights reserved.
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