Simultaneous optimization of burrs size and surface finish when milling 6061-T6 aluminium alloy

Taguchi-based optimization has been successfully applied in industrial applications. Some of these applications have more than one response to study. Most of reported applications of Taguchi method deal with single objective optimization, while multiple responses optimization has received relatively less attentions. The main objective of this article is to propose new modifications to application of Taguchi method by proposing fitness mapping function (ψ) and Desirability index (Di) for correct selection of process parameters setting levels that can be used for multiple responses optimization. The proposed method is verified by simultaneous minimization of surface roughness and burrs thickness during slot milling of 6061-T6 aluminium alloy. It was found that surface roughness and burrs size can be optimized by selecting appropriate setting levels of process parameters. According to experimental results, feed per tooth has the major influence on variation of burr size and surface roughness, while cutting speed has shown less significant effect as compared to other cutting parameters used.

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