Automated Robotic Assembly Using a Vibratory Work Table: Optimal Tuning of Vibrators Based on the Taguchi Method

The goal of this paper is to perform complex assembly tasks, using a robot assisted by a multi-axis vibrator that reduces friction and avoids jamming. An experimentbased approach using the Taguchi Method is applied to the tuning of the vibrator. The vibrators are tuned so that effects of friction and stick-slip can be minimized. Using actual assembly data and an experimental analysis method, called Taguchi analysis, we obtain optimal settings for the vibrator through an iterative procedlure. The use of Taguchi Method is a new learning technique. The Taguchi Method has brought the true meaning of automation to reality by eliminating human intervention in operating the control console. A minimum number of tests or experiments are designed and conducted at each iteration, and the process is repeated until final results reach a satisfactory level. To evaluate performance, we use the root mean square of reaction force and moment during assembly, which indicates the magnitude of stick-slip and the effect of friction. The basic technique, a prototype system, and experimental results are presented in this paper. After we have proven the concept of using Taguchi Method as a new learning method, we then apply it, to two dimensional cable connector assembly. The experimental setup and results are also presented. Haruhiko Asada Thesis Supervisor: Haruhiko Asada Professor Mechanical Engineering, MIT