An Optimal Study of a Gripper Compliant Mechanism Based on Fuzzy-Taguchi Method

Author:

Dao Thanh Phong1,Huang Shyh Chour2

Affiliation:

1. National Kaohsiung University of Applied Sciences

2. National Kaohsiung University of Applied Sciences Kaohsiung

Abstract

In this paper, a gripper mechanism with two flexible elements for grasping the objects was investigated. In general, to achieve the good the flexibility and the life strength, the flexible hinges often offer the highest elastic energy store while the lowest stress concentration is also required simultaneously. Therefore, to handle this multi-objective optimization problem, this study used the fuzzy logic based Taguchi method. The two input parameters, namely a vertical force and a horizontal force that primarily influence the displacement and the stress. These were controlled with regard to two-objective functions as the torque of torsional spring and the stress. In addition, formulating two-objective functions was based on the procedure of a pseudo-rigid-body model (PRBM) and the principle of virtual work. The results found that a vertical force of 0.5 lb and a horizontal force of 0.4 lb are favorable parameters for a suggested gripper. Using ANOVA, the results also revealed that a vertical force is the most significant parameter with highest F value of 1.188.

Publisher

Trans Tech Publications, Ltd.

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Optimization of a Fin Ray Effect Gripper using Taguchi Design;2023 IEEE 15th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM);2023-11-19

2. Analyzing the performances of evolutionary multi-objective optimizers on design optimization of robot gripper configurations;TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES;2021-01-27

3. Analysis and optimization of a micro-displacement sensor for compliant microgripper;Microsystem Technologies;2017-03-29

4. Analysis and Design Optimization of a Robotic Gripper Using Multiobjective Genetic Algorithm;IEEE Transactions on Systems, Man, and Cybernetics: Systems;2016-01

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