An energy-saving optimization method for robot laser welding systems based on multi-objective metaheuristic algorithms

Abstract

Reducing the energy consumption of robot manufacturing systems has become one of the increasingly important issues in industry. However, for robot manufacturing systems, the traditional optimization method with energy consumption as the objective function always suffers from low efficiency. In view of this, a novel energy-saving optimization method is proposed for robot laser welding systems based on the multi-objective optimization in this paper. This method deconstructs the energy consumption objective into three computationally inexpensive feature objectives and uses these three feature objectives as the objective functions of optimization, thus significantly improving the optimization efficiency. And a comprehensive optimization model of robot laser welding systems, which simultaneously considers three factors: the layout pose of workpieces, the posture of laser tools, and the inverse kinematics solution of robots, is established by utilizing a task energy characteristic model based on the time-scaling method. Furthermore, an integrated optimization process based on the NSGA-II algorithm is presented. A case study is described in detail. The results of the case study demonstrate that the proposed optimization method leads to a remarkable increase of over 95 % in optimization efficiency, that three factors exhibit interdependence, and that the integrated optimization of these factors yields superior results compared to optimizing them individually. In the case study, at a 95 % confidence level, the optimization scheme reduces the energy consumption of idle motion by 34.91 % and the total energy consumption by 7.29 %, compared to the original scheme.