Multi-Response Optimization of Magnetic Abrasive Flow Finishing Process on Aluminum (6061-T6) Using Utility Concept Embedded Firefly’s Algorithm

Abstract

Surface finish is the most desired properties of any sophisticated machinery parts for its proper functioning and long endurance. The surface finish must be in the order of micrometer to nanometer for most of the machinery parts. The nontraditional surface finish processes prepare these parts; in these processes, the uses of electromagnet play a vital role in the surface finishing mechanism. Magnetic abrasive flow finishing (MAFF) is such a hybrid process, which gives a combined effect of abrasive flow finishing (AFF) and magnetic abrasive finishing (MAF). In this method, a pair of electromagnets are attached to the AFF setup. By using electromagnet in the AFF process, it enhanced material removal and surface finishing. The main process parameters selected in the MAFF process were magnetic flux density, number of cycles, percentage abrasive content, piston speed, and corresponding responses selected were material removal, percentage improvement in surface finish. In this research paper, the responses were optimized by a combination of utility theory and meta-heuristic firefly’s algorithm. The utility theory based-firefly algorithm’s predicted global optimum parameters set, which was more suitable for reducing the finishing time and required surface finish. The confirmatory test validated this optimized parameter set and it was revealed that the meta-heuristic firefly algorithm embedded with utility theory had given optimized results in the MAFF process.