Design Optimization of the Robot Manipulator Based on Global Performance Indices Using the Grey-based Taguchi Method

This paper presents the procedure and the results of the multi-objective optimization for designing a seven-degree-of-freedom (7DOF) robot manipulator that has higher global performance, which pertains to the global conditioning and structural length indices. The Taguchi method was used to reduce the time for analyzing the global performance of the robot manipulator. Grey relational analysis was done to deal with the multiple performances of the manipulator by converting multiple responses into a single response with a Grey relational grade. Analysis of variance (ANOVA) was done to analyze the effect of the link parameters on the performance of the robot manipulator, and to find which link parameter affects the performance of the robot manipulator. The results of the optimization of the prototype robot manipulator are presented herein.