Improvement of surface flatness in face milling based on 3-D holographic laser metrology

This paper presents two approaches to improve the flatness of face milled surface based on 3-D holographic laser measurement. The first approach, cutting depth compensation method, generates a compensation cutting profile that is ideally a mirror image of the surface profile from a straight cutting path. The surface profile describes the machined surface along the feed direction and is extracted using surface decomposition technique developed in this study. Issues of back-cutting and gouging, which limit the applicability of this approach, are also addressed. The second prescribed approach is the feed rate optimization method. In this technique, the tool feed rate is altered to match the axial force on the cutter with the local compliance of the workpiece. This is performed with the aim of reducing force-induced distortion. Experiments using aluminum workpieces and 50.8 mm diameter face mill demonstrate that the surface flatness can be reduced from 32 to 7 μm with the cutting depth compensation method. With the optimized feed rate, the flatness can be reduced by 19 μm with the same cycle time as that of the original constant feed rate.

[1]  A. R. Williams,et al.  Residual stresses in aluminum castings , 2007 .

[2]  Shreyes N. Melkote,et al.  Iterative Fixture Layout and Clamping Force Optimization Using the Genetic Algorithm , 2000, Manufacturing Engineering.

[3]  Berend Denkena,et al.  Machining induced residual stress in structural aluminum parts , 2008, Prod. Eng..

[4]  Jun Ni,et al.  Laser Interferometry Hologram Registration for Three-Dimensional Precision Measurements , 2006 .

[5]  M. J. Narasimha,et al.  On the Computation of the Discrete Cosine Transform , 1978, IEEE Trans. Commun..

[6]  E. C. De Meter,et al.  Min-Max Load Model for Optimizing Machining Fixture Performance , 1995 .

[7]  Michael R. Hill,et al.  Residual stress, stress relief, and inhomogeneity in aluminum plate , 2002 .

[8]  M. Estrems,et al.  A study of back cutting surface finish from tool errors and machine tool deviations during face milling , 2008 .

[9]  Shreyes N. Melkote,et al.  Determination of minimum clamping forces for dynamically stable fixturing , 2006 .

[10]  J. Heikkala.  Determining of cutting-force components in face milling , 1995 .

[11]  M. H. Sadeghi,et al.  Feed rate optimization for 3-axis ball-end milling of sculptured surfaces , 2007 .

[12]  John S. Agapiou,et al.  Metal Cutting Theory and Practice , 1996 .

[13]  Necmettin Kaya,et al.  Machining fixture locating and clamping position optimization using genetic algorithms , 2006, Comput. Ind..

[14]  Ying Huang,et al.  Improvement of flatness error in milling plate-shaped workpiece by application of side-clamping force , 2000 .

[15]  Ying Huang,et al.  Optimization of fixture design with consideration of thermal deformation in face milling , 2001 .

[16]  Chong Nam Chu,et al.  Feed-Rate Optimization of Ball End Milling Considering Local Shape Features , 1997 .

[17]  Jianbin Xue,et al.  Deformation control through fixture layout design and clamping force optimization , 2008 .

[18]  Andrew Y. C. Nee,et al.  An intelligent fixture with a dynamic clamping scheme , 2000 .

[19]  Edward C. De Meter,et al.  Fast support layout optimization , 1998 .

[20]  B. E. Alaca,et al.  Analytical modelling of residual stresses in machining , 2007 .

[21]  Chia-Hsiang Menq,et al.  Integrated planning for precision machining of complex surfaces. Part 1: Cutting-path and feedrate optimization , 1997 .

[22]  Dong-Woo Cho,et al.  Feed rate scheduling model considering transverse rupture strength of a tool for 3D ball-end milling , 2004 .

[23]  I. Korkut,et al.  The influence of feed rate and cutting speed on the cutting forces, surface roughness and tool–chip contact length during face milling , 2007 .