Mathematical modeling and optimization of MQL assisted end milling characteristics based on RSM and Taguchi method

By Mozammel Mia. Measurement, 2018

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Abstract This work intervenes some of the sustainability issues in machining by studying the cutting energy, surface finish and Minimum Quantity Lubrication (MQL). The concentration has been set on the mathematical modeling of the specific cutting energy (Esp) and the average surface roughness parameter (Ra) in end milling of hardened AISI 4140 steel under the use of MQL. The cutting speed, feed rate and flow rate of lubricant have been oriented by full factorial design of experiment. A detailed step-by-step study of Response Surface Methodology (RSM) has been conducted. Furthermore, the influences of variables were determined by the analysis of variance; and, a comprehensive statistical analysis was conducted by the perturbation plot, interaction effects, and 3D response surface plots. Besides the Desirability based duplex optimization in RSM, the Taguchi method has been employed for mono-objective optimization of Esp and Ra. On Esp, the cutting speed exerted prime role, whereas Ra was mostly influenced by lubricant flow rate. The obtained optimum parameters are: feed rate of 46 mm/min, cutting speed of 32 m/min and coolant flow rate of 150 mL/h. The RSM and Taguchi based models revealed compatible results, thereby justified their acceptability. Moreover, the studied statistical indicators legitimated the adequacy of these models.

Subfields: Biomedical Engineering, Electrical and Electronic Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/9d3c9188e85a979e0364a1bf14033d1fac767ca3