Parametric optimization for burnishing of AISI-E52100 steel material using multi-objective artificial bee colony algorithm

Burnishing greatly enhances surface properties such as hardness, finish, corrosion resistance, and fatigue strength. However, its complexity and unpredictable variable interactions necessitate a multi-objective optimization model. An attempt is therefore made in this work to simultaneous optimization of three burnishing process responses that include burnishing time, surface hardness and surface roughness. The correlation between process parameters of burnishing such as speed, feed, force, no. of passes and above mentioned responses is evaluated using response surface methodology (RSM) before optimization. A meta-heuristics method named as multi-objective artificial bee colony algorithm is employed to tackle multi response problem to detect optimum burnishing process parameter values to improve service life of AISI-E52100 so as to comply all functional requirements. A set of Pareto solutions thus obtained offers a handy guide to choose the most suitable parameter setting to obtain the desired quality of burnished surfaces. After burnishing, SR reduced from 0.477 µm (original) to 0.113 µm and SH improved from 170.4 HV (original) to 251.8 HV, means SR decreased by 76.31 % and SH improved by 47.77 %. This will enable to predict appropriately the effects of burnishing process to control required quality characteristics and can therefore be effectively implemented in production. • The results of optimization shows that the proposed approach has potential to replace costly, time consuming and hazardous operation like hardening in applications such as manufacturing of taps, reamers, drills, punches, shafts, die and mould parts etc. • The proposed approach can also eliminate grinding operation in many applications. • The set of Pareto optimal solutions obtained by using MO-ABC algorithm can be used as nomogram by process planners to select appropriate burnishing parameters.