Multi-response Optimization of Machining Parameters in Inconel 718 End Milling Process Through RSM-MOGA

Abstract

Most of the time, thin walls may be developed during milling operations to manufacturecomplicated dies and moulds. In current high-speed machining, bending these thin wallsis expected owing to thermal expansion, making it a common source of dimensional error.Workpiece temperature (WT) with a response Machine time has been considered outputresponses. By adopting a unique technique, the response surface methodology during 2.5 Dmilling of Inconel 718, an anti-corrosive material, we could reach the best process parameterscombination for minimizing workpiece temperature. The workpiece’s temperature wasdetermined by three sets of combinations of k-type thermocouples while the surface testermeasured surface quality. Box–Behnken design has been used to conduct 26 trials to determinethe best combinations of parameters. Several process variables were examined, includingcutting speed, feed per tooth, depth of cut, and tool nose radius, and ANOVA has been usedto quantify the impact of these variables. A multi-objective genetic algorithm based on theregression model has been applied to optimize the parameters. Five structural experiments werealso conducted to verify this optimized process parameters combination, which was provenmore successful.