Iraqi Journal for Mechanical and Materials Engineering (Mar 2019)

COMPARATIVE ANALYSIS ON NUMERICAL MODELLING AND EXPERIMENTS OF THE CUTTING TEMPERATURE IN MAGNETIC ABRASIVE FINISHING PROCESS

  • Dr. Ali H Kadhum

DOI
https://doi.org/10.32852/iqjfmme.v19i1.260
Journal volume & issue
Vol. 19, no. 1

Abstract

Read online

In Magnetic Abrasive Finishing (MAF) process the cutting temperature is generated from two sources, from the electromagnetic flux (electrical heat), and from magnetic abrasive brush due to the friction force (mechanical heat). The cutting temperature has significant effects upon the condition of the surface, whereas it is less studied than the other parameters. In this study, an attempt has been made to simulate and investigate the influence of cutting parameters on the cutting temperature, to improve the thermal effect by MAF process. The aims of this study was to determine the distribution of the cutting temperature in the working gap, numerically and experimentally, then compared the results. In addition, to determine the most influence parameters affecting on the cutting temperature for Brass alloy CuZn28. Two dimensional Finite Element Models (FEM) with two software’s were developed to predict the temperature by dynamic electric and magnetic field, the first was DEFORM 10.2 used to calculate the mechanical heat and the second was COMSOL5.2 used to calculate the electrical heat. Sixteen tests designed according to Taguchi matrix through the orthogonal array (OA) L16 (). There are four various parameters that, have a large impact on cutting temperature, with four levels (rotational speed (A), working time (B), current (C), and working gap (D)). The analysis of the variance (ANOVA) technique was utilized to analysis the results, by using the statistical software (MINITAB-17). From the results, it is concluded that the Numerical modeling gives a very good comparison with the values of experimental tests. The maximum difference between the numerical and experimental temperature for brass CuZn28 is less than (9%).

Keywords