The Use of the Taguchi-Grey Based to Optimize High Speed End Milling with Multiple Performance Characteristics

Abstract

This paper presents a new approach for the optimization of the high speed machining (HSM) process with multiple performance characteristics based on the orthogonal array with the grey relational analysis has been studied. Optimal machining parameters can then be determined by the grey relational grade as the performance index. In this study, the machining parameters such as cutting speed, feed rate and axial depth of cut are optimized under the multiple performance characteristics including, tool life, surface roughness, and material removal rate(MMR). As shown experimental results, machining performance in the HSM process can be improved effectively through this approach.

Multi-Objective Optimization of in Precision Turn-Boring Parameters for AA7050-T7451 with Multiple Performance Characteristics

“…Kant and Sangwan [10] using grey relational analysis to find the optimum values of machining parameters to achieve the minimum power consumption and surface roughness. Hwang et al [11] investigated and optimized the high speed end milling of SKD61 Tool Steel using Taguchi methods with grey relational analysis. Recently, this method attracts more and more widely applied on mechanical machining and tribological engineering, including drilling [12][13][14], turning [15][16] As mentioned above, The GRA is an effective approach to solve the multi-objective optimization.…”