Optimal Design for Compliant Mechanism Flexure Hinges: Bridge-Type

Compliant mechanisms’ design aims to create a larger workspace and simple structural shapes because these mechanical systems usually have small dimensions, reduced friction, and less bending. From that request, we designed optimal bridge-type compliant mechanism flexure hinges with a high magnificat...

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Autores principales:	Chia-Nan Wang, Fu-Chiang Yang, Van Thanh Tien Nguyen, Quoc Manh Nguyen, Ngoc Thai Huynh, Thanh Thuong Huynh
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	optimization design compliant mechanism grey-based Taguchi method artificial neural network Mechanical engineering and machinery TJ1-1570
Acceso en línea:	https://doaj.org/article/a87ca0b28cc1402d98af46424a9e1484
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spelling	oai:doaj.org-article:a87ca0b28cc1402d98af46424a9e14842021-11-25T18:22:57ZOptimal Design for Compliant Mechanism Flexure Hinges: Bridge-Type10.3390/mi121113042072-666Xhttps://doaj.org/article/a87ca0b28cc1402d98af46424a9e14842021-10-01T00:00:00Zhttps://www.mdpi.com/2072-666X/12/11/1304https://doaj.org/toc/2072-666XCompliant mechanisms’ design aims to create a larger workspace and simple structural shapes because these mechanical systems usually have small dimensions, reduced friction, and less bending. From that request, we designed optimal bridge-type compliant mechanism flexure hinges with a high magnification ratio, low stress by using a flexure joint, and especially no friction and no bending. This joint was designed with optimal dimensions for the studied mechanism by using the method of grey relational analysis (GRA), which is based on the Taguchi method (TM), and finite element analysis (FEA). Grey relational grade (GRG) has been estimated by an artificial neural network (ANN). The optimal values were in good agreement with the predicted value of the Taguchi method and regression analysis. The finite element analysis, signal-to-noise analysis, surface plot, and analysis of variance demonstrated that the design dimensions significantly affected the equivalent stress and displacement. The optimal values of displacement were also verified by the experiment. The outcomes were in good agreement with a deviation lower than 6%. Specifically, the displacement amplification ratio was obtained as 65.36 times compared with initial design.Chia-Nan WangFu-Chiang YangVan Thanh Tien NguyenQuoc Manh NguyenNgoc Thai HuynhThanh Thuong HuynhMDPI AGarticleoptimization designcompliant mechanismgrey-based Taguchi methodartificial neural networkMechanical engineering and machineryTJ1-1570ENMicromachines, Vol 12, Iss 1304, p 1304 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	optimization design compliant mechanism grey-based Taguchi method artificial neural network Mechanical engineering and machinery TJ1-1570
spellingShingle	optimization design compliant mechanism grey-based Taguchi method artificial neural network Mechanical engineering and machinery TJ1-1570 Chia-Nan Wang Fu-Chiang Yang Van Thanh Tien Nguyen Quoc Manh Nguyen Ngoc Thai Huynh Thanh Thuong Huynh Optimal Design for Compliant Mechanism Flexure Hinges: Bridge-Type
description	Compliant mechanisms’ design aims to create a larger workspace and simple structural shapes because these mechanical systems usually have small dimensions, reduced friction, and less bending. From that request, we designed optimal bridge-type compliant mechanism flexure hinges with a high magnification ratio, low stress by using a flexure joint, and especially no friction and no bending. This joint was designed with optimal dimensions for the studied mechanism by using the method of grey relational analysis (GRA), which is based on the Taguchi method (TM), and finite element analysis (FEA). Grey relational grade (GRG) has been estimated by an artificial neural network (ANN). The optimal values were in good agreement with the predicted value of the Taguchi method and regression analysis. The finite element analysis, signal-to-noise analysis, surface plot, and analysis of variance demonstrated that the design dimensions significantly affected the equivalent stress and displacement. The optimal values of displacement were also verified by the experiment. The outcomes were in good agreement with a deviation lower than 6%. Specifically, the displacement amplification ratio was obtained as 65.36 times compared with initial design.
format	article
author	Chia-Nan Wang Fu-Chiang Yang Van Thanh Tien Nguyen Quoc Manh Nguyen Ngoc Thai Huynh Thanh Thuong Huynh
author_facet	Chia-Nan Wang Fu-Chiang Yang Van Thanh Tien Nguyen Quoc Manh Nguyen Ngoc Thai Huynh Thanh Thuong Huynh
author_sort	Chia-Nan Wang
title	Optimal Design for Compliant Mechanism Flexure Hinges: Bridge-Type
title_short	Optimal Design for Compliant Mechanism Flexure Hinges: Bridge-Type
title_full	Optimal Design for Compliant Mechanism Flexure Hinges: Bridge-Type
title_fullStr	Optimal Design for Compliant Mechanism Flexure Hinges: Bridge-Type
title_full_unstemmed	Optimal Design for Compliant Mechanism Flexure Hinges: Bridge-Type
title_sort	optimal design for compliant mechanism flexure hinges: bridge-type
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/a87ca0b28cc1402d98af46424a9e1484
work_keys_str_mv	AT chiananwang optimaldesignforcompliantmechanismflexurehingesbridgetype AT fuchiangyang optimaldesignforcompliantmechanismflexurehingesbridgetype AT vanthanhtiennguyen optimaldesignforcompliantmechanismflexurehingesbridgetype AT quocmanhnguyen optimaldesignforcompliantmechanismflexurehingesbridgetype AT ngocthaihuynh optimaldesignforcompliantmechanismflexurehingesbridgetype AT thanhthuonghuynh optimaldesignforcompliantmechanismflexurehingesbridgetype
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Optimal Design for Compliant Mechanism Flexure Hinges: Bridge-Type

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