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Modeling of cutting force, tool deflection, and surface error in micro-milling operation
T.M. Moges, , P.V.M. Rao
Published in Springer London
Volume: 98
Issue: 9-12
Pages: 2865 - 2881
Micro-milling has shown great potential in producing complex miniaturized components over wide range of materials. It can also fabricate micro-products in small batches efficiently and economically. In spite of these advantages, several challenges hinder its ability to produce components with better dimensional accuracy. Among several factors, tool deflection is one of the major sources of surface error on machined parts and features. Therefore, it is necessary to develop accurate and reliable process models to analyze and improve performance of the process. This study presents a methodology to determine cutting forces and surface error in the presence of tool deflections for micro-milling operation. Tool deflections have considerable influence on instantaneous uncut chip thickness. As tool deflection alters tooth trajectories and instantaneous uncut chip thickness, the rigid cutting force model needs to be modified suitably to consider the effect of deflections. This aspect has been incorporated in the model by modifying tool center location and tooth trajectories iteratively. The convergence of an iterative algorithm determining stable chip thickness is obtained by comparing RMS deviation of average chip thickness between two successive tooth passes. The axial variation of surface error due to tool deflections is estimated using surface generation mechanism. The proposed model is implemented in the form of a computational program to predict cutting force and surface error. The results of computational model are substantiated further by conducting machining experiments. It is shown that the proposed model predicts cutting forces fairly well in the presence of tool deflections. A comparison between predicted variation of surface error and 3D images of machined surface captured using optical microscope showed good qualitative agreement in the error profiles. © 2018, Springer-Verlag London Ltd., part of Springer Nature.
About the journal
JournalData powered by TypesetInternational Journal of Advanced Manufacturing Technology
PublisherData powered by TypesetSpringer London