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

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

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Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	Generative design, Weight optimization, 6-Axis quadcopter drone
Divisions:	Faculty of Electrical Engineering
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	04 Jul 2024 11:22
Last Modified:	04 Jul 2024 11:22
URI:	http://eprints.utem.edu.my/id/eprint/27366
Statistic Details:	View Download Statistic

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