Optimisation of Surface Roughness in 3D Printing Using the Bees Algorithm

Kamaruddin, Shafie and Ridzuan, Arman Hilmi and Sukindar, Nor Aiman (2024) Optimisation of Surface Roughness in 3D Printing Using the Bees Algorithm. In: Intelligent Engineering Optimisation with the Bees Algorithm. Springer, pp. 197-207. ISBN 978-3-031-64935-6

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Abstract

Additive manufacturing (AM) is renowned for its capability to produce parts that are low-cost and have less manufacturing time. One of the main challenges in this additive manufacturing technology is selecting proper input process parameters to achieve good quality of the 3D printed model. The focus of this study is to determine the optimum input parameter of the 3D printer using the Bees Algorithm (BA). This study uses the Bees Algorithm to predict the best combination parameters to optimise the surface roughness of parts printed by a fused deposition modelling (FDM) machine. The predicted results are compared with the experimental 3D model sample and previous findings of other optimisation methods. Comparative analysis between predicted and actual surface roughness measurements showed good agreement with differences of less than 2%, indicating a significant prediction method. The result also shows that the Bees Algorithm found a better combination of parameters compared to other algorithms. This research provides another alternative optimisation approach for industries that utilise 3D printing.

Item Type:	Book Chapter
Uncontrolled Keywords:	Additive manufacturing, Bees Algorithm, Intelligent optimisation
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ1125 Machine shops and machine shop practice
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Manufacturing and Materials Engineering
Depositing User:	Dr. Shafie Kamaruddin
Date Deposited:	12 Dec 2024 12:12
Last Modified:	12 Dec 2024 12:12
URI:	http://irep.iium.edu.my/id/eprint/116094

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