Evaluation of Parameters Affecting Magnetic Abrasive Finishing (MAF) of Superalloy Inconel 718

Abstract

Superalloys generally are among the materials with poor machinability. The removal of metal contaminations, stains, and oxides can positively affect their performance. Magnetic Abrasive Finishing (MAF) is a method which uses a magnetic field to control the material removal. As another advantage, this method can be used to polish materials such assuperalloys which have high strength and special conditions. In this paper, we investigated the magnetic abrasive finishing of nickel-base superalloy Inconel 718. Since the process is highly influenced by several effective parameters, in this study we evaluated the effects of some of these parameters such as percentage of abrasive particles, gap, rotational speed, feed rate, and the relationship between size of abrasive particles and the reduction of average surface roughness. Using Minitab software package the experiments were designed based on a statistical method. Response surface method was used as the design of the experiment. The regression equation governing the process was extracted through the assessment of effective parameters and analysis of variance. In addition, the optimum conditions of MAF were also extracted. Analysis of the outputs of MAF process experiments on IN718 revealed that gap, weight percent of abrasive particles, feed rate, rotational speed, and size of abrasive particles were the factors that affected the level of changes in surface roughness. The distance between the magnet and the work piece surface, i.e. the gap, is the most important parameter which affects the changes in surface roughness. The surface roughness can decrease up to 62% through setting up the process at its optimum state i.e. in a rotational speed of 1453 rpm, feed rate of 10 mm/min, percentage of abrasive particles equal to 17.87%, size of particles equal to #1200, and gap size of 1 mm. There is a discrepancy of 13% between this prediction and the predicted value by the regression model. With mounting a magnet with a different pole beneath the work piece, magnetic flux density increases up to 35%.