Multi-response optimization of the roller burnishing process in terms of energy consumption and product quality

The burnishing process is an efficient finishing operation which is widely used to enhance the surface properties of the machined components. The published works mainly focused on the parameters optimization of the burnishing process in which objective functions are relative to burnished surface qualities. Because of natural resource exhaustion and the rising energy prices, the reduction in energy consumption is an urgent demand in the manufacturing industry. This paper presented an efficient optimization to simultaneously decrease energy consumption as well as the mean roughness depth and improve the Brinell hardness for the burnished surface of H13 steel. The burnishing speed, feed rate, depth of penetration, and the number of rollers were the input parameters. The burnishing processes were carried out on a CNC milling machine. The mathematical relations between inputs and outputs were developed using the radius basis function models. The multi-objective particle swarm optimization and the technique for order of preference by similarity to ideal solution were used to generate the Pareto fronts and to determine the best solution. The results show that energy consumption and surface roughness are reduced by 39.50% and 7.83%, respectively. The Brinell hardness is improved by 29.61% compared to the initial values. The radial basis function models can be effectively used to render the approximations and to predict the response's values. The proposed method can be considered as a sufficient approach for modeling and optimizing the burnishing process. (C) 2019 Elsevier Ltd. All rights reserved.