E-Modeling and Evolution of Nanolubricant Coupled Machining Parameters Using Statistical Tool

Abstract

Optimization is an essential action to select the effective input parameters for the responses obtained from machining. In this work, the combination of six sigma techniques and grey relational optimization are used for the corresponding input parameters, namely, spindle speed, feed rate, and drill diameter. The responses recorded are torque, thrust force, surface roughness, temperature, and ovality. Smaller the better response is preferred for all the output responses. Taguchi design of L27 array is preferred, and based on 27 combinations of input parameters, output responses are recorded. The thrust force and torque values are obtained in the graphical form during drilling process by the vertical machining center. After the drilling process the surface roughness of the hole is measured using profilometer. The probe in the profilometer is moved along the surface of the hole and the corresponding surface roughness values are noted for twenty-seven holes. The roundness of the hole is measured using a profile projector. The roundness of the hole is expanding due to the heat generated during the machining process. The expanded diameter of the hole is measured along the vertical and horizontal axes using the projector. Six sigma techniques are used to analyze the input parameters such as spindle speed, feed rate, and drill diameter. The optimization technique is used to determine the optimized parameters.