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Computing Optimization of a Parallel Structure-Based Monolithic Gripper for Manipulation Using Weight Method-Based Grey Relational Analysis

Computing Optimization of a Parallel Structure-Based Monolithic Gripper for Manipulation Using Weight Method-Based Grey Relational Analysis
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Author(s): Ngoc Le Chau (Faculty of Mechanical Engineering, Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam), Nhat Linh Ho (Koei Vietnam Company Limited, Ho Chi Minh City, Vietnam), Tran The Vinh Chung (Faculty of Mechanical Engineering, Ly Tu Trong College of Ho Chi Minh City, Ho Chi Minh City, Vietnam), Shyh-Chour Huang (Department of Mechanical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan) and Thanh-Phong Dao (Division of Computational Mechatronics, Institute for Computational Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam & Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam)
Copyright: 2021
Volume: 12
Issue: 3
Pages: 36
Source title: International Journal of Ambient Computing and Intelligence (IJACI)
Editor(s)-in-Chief: Nilanjan Dey (JIS University, Kolkata, India)
DOI: 10.4018/IJACI.2021070103

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Abstract

This study proposes an integration of the weight method and grey relational analysis to optimize a monolithic gripper. This gripper is desired for use in the assembling industry of cylindrical parts with diameters from 500 µm to 800 µm. The weight factor for each response is calculated accurately. Response surface methodology and Taguchi method are utilized to build an experiment matrix, and grey relational analysis is utilized to predict optimal results. The results found that the predicted displacement value is 0.5699 µm, and the predicted frequency value is 780.9 Hz. Compared to the initial design, the quality of responses is improved by 7.53% for the natural frequency and 35.29% for the output displacement. The error between the predicted result and the verified result is 1.15% for the natural frequency and 16.62% for the output displacement, respectively. It implies that the proposed method has a statistical accuracy.

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