Off-line programming system of industrial robot for spraying manufacturing optimization

Artificial teaching used of traditional industrial robots in manufacturing severely restrict the improvement of the productivity, and offline programming technique is regarded as the key technology to solve this problem. In this paper, the paint robot is studied on the following modules, including importing and preprocessing of CAD workpiece model, spraying process modeling, spray path planning, trajectory optimization and adjustment, spraying process simulation and performance analysis, and spraying robot trajectory generation, which is based on deep analysis of the basic characteristics of spray manufacturing systems. A set of core technologies and algorithms with a high degree of automation, optimization and flexibility have formed, which realizes offline simulation and performance evaluation for complex spraying tasks, so as to achieve the purpose of optimizing spray effect, improving the efficiency of spraying operations and save spraying costs. Simulation and spraying experimental results show the effectiveness and practicality of offline programming system developed in this paper.