Investigation and Optimization of MQL System Parameters in the Roller-Burnishing Process of Hardened Steel

In the current study, internal burnishing process under minimum quantity lubrication (MQL) condition has been optimized to decrease cylindricity (CYL) and circularity (CIC) of burnished hole, while surface roughness (SR) is predefined as a constraint. The optimizing inputs are diameter spray nozzle (D), elevation angle (A), lubricant (Q), pressure value compressed air (P). artificial neural network (ANN) models performances proposed optimise inputs. grey relational analysis (GRA) utilized compute weight each response. Optimal values MQL system parameters technological objectives selected with aid an evolution algorithm (vibration communication particle swarm optimization (VCPSO) algorithm). results indicated that optimal outcomes D, A, Q, P 1.5 mm, 50 deg, 140 ml/h, 0.6 MPa, respectively. Furthermore, CYL, CIC, SR were decreased by 53.14 %, 57.83 72.97 respectively, at solution. Finally, obtained expected be significant solution support machine operator in selecting improve hole quality MQL-assisted process.