Multi-response optimization of machining factors in pocket milling of AISI304 using grey relational analysis

Abstract

Abstract Pocket milling finds applications in ship building and aerospace industries. To cut the required profile of the pocket on the material various tool trajectories may be used. Surface roughness is one of the quality parameters to accept products at the same time production time must be reduced to reduce the production cost. This shows the need of selecting the best parameters machining parameters to get good surface finish with less production time. Tool trajectories also play a vital role in pocket generation and production time. In the current study, first, optimum machining parameters are identified for AISI304 using Taguchi L9 Orthogonal Array and Grey Relational Analysis. Experiments are done with Speed (S), Feed (F) and Stepover (SO) as the influencing parameters. Secondly, suitable tool path is to be identified to improve the surface quality (SR) and Material Removal Rate (MRR). Two tool paths viz, follow periphery and zigzag are used to generate pockets. For each tool trajectory, from the obtained results, Grey Relational Grade is calculated. The combination of parameters with highest Grey Relational Grade is identified as the optimal parameters. Confirmation experiments indicate that predicted responses are closer to the optimal values.