Publications

Abstract :

In this work, the MAF set-up is fixed on a vertical milling machine, and experiments are performed for optimizing the process parameters using central composite design (CCD) based on response surface methodology (RSM). From these experiments, output responses like percentage improvement in surface roughness (%ΔRa) and the material removal rate (MRR) are measured. An airgap is maintained in the range of 1.5-2 mm at a voltage of 10-20 V. A series of 62 experiments are conducted using selected process parameters at different levels. A grey based fuzzy algorithm is used to optimize the multi-response characteristics. The grey fuzzy reasoning grade (GFRG) is used to identify the optimal process parameters. From the results, the highest GFRG value is obtained at a voltage of 15 V with a corresponding rotational speed, machining gap, mesh number and mixing ratio of 750 rpm, 1.75 mm, 800 and 1: 2, respectively. In addition, analysis of variance (ANOVA) is used to identify the percentage contribution of each parameter in the MAF process, and the same is verified through experimentation. Optical microscopic images confirm that the surface finish of SS310s has been improved using the MAF process.