1594 KB0 KB199920252023Le, Minh-ThaiNguyen, Trung ThanhVan, An-Leštevilka:3/4letnik:69str. 155-168ISSN:0039-2480DOI:10.5545/sv-jme.2022.303COBISSID_HOST:148484355URN:URN:NBN:SI:doc-YSINFAO1enZveza strojnih inženirjev in tehnikov Slovenije etc.Strojniški vestnikaverage roughnessbayesian regularizationBayesova regularizacijafino poliranje z enim diamantomNSGA-Goptimumipovprečna hrapavostsingle diamond burnishingtrdota po Vickersuumetne nevronske mreževickers hardnessImpacts of burnishing variables on the quality indicators in a single diamond burnishing operation|Diamond burnishing is an effective solution to finish a surface. The purpose of the current work is to optimize parameter inputs, including the spindle speed (S), depth of penetration (D), feed rate (f), and diameter of tool-tip (DT) for improving the Vickers hardness (VH) and decreasing the average roughness (Ra) of a new diamond burnishing process. A set of burnishing experiments is executed under a new cooling lubrication system comprising the minimum quantity lubrication and double vortex tubes. The Bayesian regularized feed-forward neural network (BRFFNN) models of the performances are proposed in terms of the inputs. The criteria importance through the inter-criteria correlation (CRITIC) method and non-dominated sorting genetic algorithm based on the grid partitioning (NSGA-G) are applied to compute the weights of responses and find optimality. The optimal outcomes of the S, D, f, and DT were 370 rpm, 0.10 mm, 0.04 mm/rev, and 8 mm, respectively. The improvements in the Ra and VH were 40.7 % and 7.6 %, respectively, as compared to the original parameters. An effective approach combining the BRFFNN, CRITIC, and NSGA-G can be widely utilized to deal with complicated optimization problems. The optimizing results can be employed to enhance the surface properties of the burnished surfaceTEXTznanstveno časopisjejournalsSlovenian National E-content AggregatorNational and University Library of SloveniaUniverza v Ljubljani, Fakulteta za strojništvo