Multi-objective optimization of ultrasonic-assisted magnetic abrasive finishing process

Ultrasonic-assisted magnetic abrasive finishing (UAMAF) is an advanced abrasive finishing process that finishes a workpiece surface effectually when compared to a traditional magnetic abrasive finishing process in the order of nanometer. A change of surface roughness and material removal rate are two important factors determining the efficacy of the process. These two factors affect the surface quality and production time and, thereby, a total production cost. The finishing performed at higher material removal rates leads to a loss in shape/form accuracy of the surface. At the same time, increasing the rate of change of surface roughness increases loss of material. For an optimized finishing process, a compromise has to be made between the change of surface roughness and the material removal (loss). In this work, a multi-objective optimization technique based on genetic algorithm is used to optimize the finishing parameters in the UAMAF processes. A fuzzy-set-based strategy for a higher level decision is also discussed. The results of the optimization based on a mathematical model of the process are validated with the experimental results and are found to be in compliance.