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Generative design of a 6-axis quadcopter drone for weight optimization

Unmanned aerial vehicles (UAVs), known as drones, can be remotely operated using embedded technology and software-controlled flight plans. A six-axis drone's main problem is that its significant weight limits how much it can be used. As a result, the flexibility and endurance of the drone'...

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Main Authors:	Md Ghazaly, Mariam, Kueh, Tze Jun
Format:	Article
Language:	English
Published:	UTHM Publisher 2023
Online Access:	http://eprints.utem.edu.my/id/eprint/27366/2/0108618122023525.PDF http://eprints.utem.edu.my/id/eprint/27366/ https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/10935
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spelling	my.utem.eprints.273662024-07-04T11:22:28Z http://eprints.utem.edu.my/id/eprint/27366/ Generative design of a 6-axis quadcopter drone for weight optimization Md Ghazaly, Mariam Kueh, Tze Jun Unmanned aerial vehicles (UAVs), known as drones, can be remotely operated using embedded technology and software-controlled flight plans. A six-axis drone's main problem is that its significant weight limits how much it can be used. As a result, the flexibility and endurance of the drone's design are necessary for excellent performance during altitude displacement. In order to create a body frame for the quadcopter, the project intends to solve the weight optimization problem via generative design. The three main steps of the optimization attempts utilizing generative design procedures are (a) abstraction, (b) initialization, and (c) interpretation. These are accomplished by employing the five generative design processes. The stress analysis and the generative design process were used to confirm that the generative design technique will help reduce the drone's weight. The drone using three (3) generative designs, was set to a total weight of less than 1kg. The results show that Generative Design 2 shows good optimization as follows, (a) 50.00% of parts of assembly optimized from eight parts to four parts, (b) 54.09% of the weight of the body frame optimized from 1.1565kg to 0.531kg, (c) 36.17% of the height of the body frame optimized from 94mm to 60mm, (d) 45.44% of stress analysis increased from 3.457MPa to 5.028MPa, (e) 83.00% reduction of displacement elongation from 3.918mm to 0.666mm and (f) 61.25% of production time optimized from 40 hours to 15.5 hours. UTHM Publisher 2023-08 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/27366/2/0108618122023525.PDF Md Ghazaly, Mariam and Kueh, Tze Jun (2023) Generative design of a 6-axis quadcopter drone for weight optimization. International Journal of Integrated Engineering, 14 (4). pp. 100-111. ISSN 2229-838X https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/10935 10.30880/IJIE.2023.15.04.009
institution	Universiti Teknikal Malaysia Melaka
building	UTEM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknikal Malaysia Melaka
content_source	UTEM Institutional Repository
url_provider	http://eprints.utem.edu.my/
language	English
description	Unmanned aerial vehicles (UAVs), known as drones, can be remotely operated using embedded technology and software-controlled flight plans. A six-axis drone's main problem is that its significant weight limits how much it can be used. As a result, the flexibility and endurance of the drone's design are necessary for excellent performance during altitude displacement. In order to create a body frame for the quadcopter, the project intends to solve the weight optimization problem via generative design. The three main steps of the optimization attempts utilizing generative design procedures are (a) abstraction, (b) initialization, and (c) interpretation. These are accomplished by employing the five generative design processes. The stress analysis and the generative design process were used to confirm that the generative design technique will help reduce the drone's weight. The drone using three (3) generative designs, was set to a total weight of less than 1kg. The results show that Generative Design 2 shows good optimization as follows, (a) 50.00% of parts of assembly optimized from eight parts to four parts, (b) 54.09% of the weight of the body frame optimized from 1.1565kg to 0.531kg, (c) 36.17% of the height of the body frame optimized from 94mm to 60mm, (d) 45.44% of stress analysis increased from 3.457MPa to 5.028MPa, (e) 83.00% reduction of displacement elongation from 3.918mm to 0.666mm and (f) 61.25% of production time optimized from 40 hours to 15.5 hours.
format	Article
author	Md Ghazaly, Mariam Kueh, Tze Jun
spellingShingle	Md Ghazaly, Mariam Kueh, Tze Jun Generative design of a 6-axis quadcopter drone for weight optimization
author_facet	Md Ghazaly, Mariam Kueh, Tze Jun
author_sort	Md Ghazaly, Mariam
title	Generative design of a 6-axis quadcopter drone for weight optimization
title_short	Generative design of a 6-axis quadcopter drone for weight optimization
title_full	Generative design of a 6-axis quadcopter drone for weight optimization
title_fullStr	Generative design of a 6-axis quadcopter drone for weight optimization
title_full_unstemmed	Generative design of a 6-axis quadcopter drone for weight optimization
title_sort	generative design of a 6-axis quadcopter drone for weight optimization
publisher	UTHM Publisher
publishDate	2023
url	http://eprints.utem.edu.my/id/eprint/27366/2/0108618122023525.PDF http://eprints.utem.edu.my/id/eprint/27366/ https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/10935
_version_	1804070315664343040
score	13.211869

Generative design of a 6-axis quadcopter drone for weight optimization

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