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Optimal design of a 3D-printed scaffold using intelligent evolutionary algorithms

Fabrication of three-dimensional structures has gained increasing importance in the bone tissue engineering (BTE) field. Mechanical properties and permeability are two important requirement for BTE scaffolds. The mechanical properties of the scaffolds are highly dependent on the processing parameter...

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Main Authors:	Asadi-Eydivand, M., Solati-Hashjin, M., Fathi, A., Padashi, M., Abu Osman, Noor Azuan
Format:	Article
Published:	Elsevier 2016
Subjects:	R Medicine TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery
Online Access:	http://eprints.um.edu.my/18344/ https://doi.org/10.1016/j.asoc.2015.11.011
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id	my.um.eprints.18344
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spelling	my.um.eprints.183442019-02-07T07:43:27Z http://eprints.um.edu.my/18344/ Optimal design of a 3D-printed scaffold using intelligent evolutionary algorithms Asadi-Eydivand, M. Solati-Hashjin, M. Fathi, A. Padashi, M. Abu Osman, Noor Azuan R Medicine TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery Fabrication of three-dimensional structures has gained increasing importance in the bone tissue engineering (BTE) field. Mechanical properties and permeability are two important requirement for BTE scaffolds. The mechanical properties of the scaffolds are highly dependent on the processing parameters. Layer thickness, delay time between spreading each powder layer, and printing orientation are the major factors that determine the porosity and compression strength of the 3D printed scaffold. In this study, the aggregated artificial neural network (AANN) was used to investigate the simultaneous effects of layer thickness, delay time between spreading each layer, and print orientation of porous structures on the compressive strength and porosity of scaffolds. Two optimization methods were applied to obtain the optimal 3D parameter settings for printing tiny porous structures as a real BTE problem. First, particle swarm optimization algorithm was implemented to obtain the optimum topology of the AANN. Then, Pareto front optimization was used to determine the optimal setting parameters for the fabrication of the scaffolds with required compressive strength and porosity. The results indicate the acceptable potential of the evolutionary strategies for the controlling and optimization of the 3DP process as a complicated engineering problem. Elsevier 2016 Article PeerReviewed Asadi-Eydivand, M. and Solati-Hashjin, M. and Fathi, A. and Padashi, M. and Abu Osman, Noor Azuan (2016) Optimal design of a 3D-printed scaffold using intelligent evolutionary algorithms. Applied Soft Computing, 39. pp. 36-47. ISSN 1568-4946 https://doi.org/10.1016/j.asoc.2015.11.011 doi:10.1016/j.asoc.2015.11.011
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
topic	R Medicine TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery
spellingShingle	R Medicine TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery Asadi-Eydivand, M. Solati-Hashjin, M. Fathi, A. Padashi, M. Abu Osman, Noor Azuan Optimal design of a 3D-printed scaffold using intelligent evolutionary algorithms
description	Fabrication of three-dimensional structures has gained increasing importance in the bone tissue engineering (BTE) field. Mechanical properties and permeability are two important requirement for BTE scaffolds. The mechanical properties of the scaffolds are highly dependent on the processing parameters. Layer thickness, delay time between spreading each powder layer, and printing orientation are the major factors that determine the porosity and compression strength of the 3D printed scaffold. In this study, the aggregated artificial neural network (AANN) was used to investigate the simultaneous effects of layer thickness, delay time between spreading each layer, and print orientation of porous structures on the compressive strength and porosity of scaffolds. Two optimization methods were applied to obtain the optimal 3D parameter settings for printing tiny porous structures as a real BTE problem. First, particle swarm optimization algorithm was implemented to obtain the optimum topology of the AANN. Then, Pareto front optimization was used to determine the optimal setting parameters for the fabrication of the scaffolds with required compressive strength and porosity. The results indicate the acceptable potential of the evolutionary strategies for the controlling and optimization of the 3DP process as a complicated engineering problem.
format	Article
author	Asadi-Eydivand, M. Solati-Hashjin, M. Fathi, A. Padashi, M. Abu Osman, Noor Azuan
author_facet	Asadi-Eydivand, M. Solati-Hashjin, M. Fathi, A. Padashi, M. Abu Osman, Noor Azuan
author_sort	Asadi-Eydivand, M.
title	Optimal design of a 3D-printed scaffold using intelligent evolutionary algorithms
title_short	Optimal design of a 3D-printed scaffold using intelligent evolutionary algorithms
title_full	Optimal design of a 3D-printed scaffold using intelligent evolutionary algorithms
title_fullStr	Optimal design of a 3D-printed scaffold using intelligent evolutionary algorithms
title_full_unstemmed	Optimal design of a 3D-printed scaffold using intelligent evolutionary algorithms
title_sort	optimal design of a 3d-printed scaffold using intelligent evolutionary algorithms
publisher	Elsevier
publishDate	2016
url	http://eprints.um.edu.my/18344/ https://doi.org/10.1016/j.asoc.2015.11.011
_version_	1643690679075864576
score	13.211869

Optimal design of a 3D-printed scaffold using intelligent evolutionary algorithms

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