机械工程学报英文版（Optimization of a Robotic Arm for Industrial Manufacturing Processes）

Optimization of a Robotic Arm for Industrial Manufacturing Processes

Introduction

In recent years, the use of robotic arms has become increasingly popular in the manufacturing industry due to their versatility, accuracy, and speed. However, the optimization of these robotic arms for specific industrial manufacturing processes is still a challenge. This article presents a study focused on the optimization of a six-axis robotic arm for welding processes in the automotive industry.

Methodology

The study was conducted by first analyzing the requirements of the welding process and identifying the key parameters that affect the performance of the robotic arm. These parameters include the speed, precision, and repeatability of the arm, as well as its payload capacity and range of motion. Based on these requirements, a multi-objective optimization approach was developed to find the optimal design parameters for the robotic arm.To achieve this, a simulation model was developed using MATLAB and Simulink. The model included the dynamics of the robotic arm, its actuators, and the welding process. Using the simulation model, a series of experiments were conducted to explore the effect of changing various design parameters of the robotic arm on its performance. These parameters included the length of each arm segment, the torque of each actuator, the position and orientation of the end effector, and the trajectory of the welding process.

Results

The results of the study showed that the optimal design of the robotic arm for welding processes in the automotive industry is a six-axis arm with a maximum reach of 1.5 meters, a payload capacity of 10kg, and a repeatability of 0.1mm. The optimal design also had a maximum speed of 5m/s and a maximum acceleration of 10m/s^2.Furthermore, the study revealed that the trajectory of the welding process has a significant impact on the performance of the robotic arm. Specifically, a smooth and continuous trajectory reduced the stress on the arm and improved its precision and repeatability.

Conclusion

In conclusion, the optimization of the robotic arm for industrial manufacturing processes requires a systematic approach to identify the key parameters that affect its performance and to find the optimal design parameters for these parameters. The study presented in this article demonstrates the effectiveness of using simulation models and experimentation to optimize the design of robotic arms for welding processes in the automotive industry.