Particle swarm optimization for achieving the minimum profile error in honing process

Gears are among the most important mechanical components of the modern industry. The topography of the gears’ tooth flank has an intricate and complex form and requires great finishing and quality. Commonly, traditional grinding processes are applied to finishing gear profile. However, the use of honing process has grown in recent years to provide the best finishing in industrial products. In this study, the honing process was improved applying a particle swarm optimization. Pinions of steering systems were used as work pieces to testify the optimization technique. The input parameters were the spindle speed, feed rate in X direction, feed rate in Z direction, oscillation time, and spark out time. The experimental measures were compared with simulation tests using the responses total profile deviation (fα), total helix deviation (fβ), and total cumulative pitch deviation (fp). The results showed that profile error was minimized, and the quality was improved based a set of strategies that were held simultaneously in the input parameters.