OPTIMIZATION ANALYSIS OF MULTIPLE PERFORMANCE CHARACTERISTICS IN ENDMILL FOR HIGH-SPEED MACHINING
Currently applications of the high-speed milling have achieved distinguished developments. Also the manufacturing technology is regarded as one of key technologies for mechanical industry in coming ten years. The major application fields include the aerospace, automobile, mold industry and outer casing of 3C products. Because ultra-high precision can be realized by the high speed milling, workpiece may be directly processed to required dimensional precision, and the production cost and time would be obviously reduced. Therefore it is worth to research the involved topic about applications of the high speed milling for the molding tool steel processing. Recently, the grey-relational analysis has been widely applied in the optimal design of cutting parameters with multiple performance characteristics. In this study, a grey relational analysis is integrated with Taguchi method to determine the cutting parameters for optimizing the high-speed end milling with multiple performance characteristics. The major characteristics indexes for evaluating cutting performance are tool life and metal removal rate. And the corresponding cutting parameters are high-speed end milling, surface roughness of end-mill, spindle speed, feed per tooth, axial and radial cutting depth. In this study, the L18 orthogonal arrays were introduced for experimental arrangements. Larger-thebetter was used as a quality characteristic to evaluate the experimental results. Finally, by grey relational analysis coupled with major component analysis, the optimal cutting parameters have been analyzed for rough cutting processes and high-speed end milling on SKD61 tool steel. Moreover, the major component analysis is utilized to estimate for the weighting values corresponding to various performance characteristics so that their relative importance can be properly and objectively described. The experiment results demonstrate that the optimal combination of cutting parameters can be effectively acquired by grey relational analysis coupled with major component analysis.
High-speed end milling Grey relational analysis Major component analysis Optimization.
Yung-Cheng Wang Chi-Hsiang Chen Bean-Yin Lee
Institute of Mechanical Engineering, National Yunlin University of Science & Technology, 123 Univers Institute of Mechanical and Electro-Mechanical Engineering, National Formosa University, No. 64,Wunh Department of Mechanical and Computer-Aided Engineering, National Formosa University, No. 64, Wunhua
国际会议
上海
英文
1-6
2009-08-02（万方平台首次上网日期，不代表论文的发表时间）