Particle Swarm Optimisation Prediction Model for Surface Roughness

M. M., Noor and K., Kadirgama and M. M., Rahman (2011) Particle Swarm Optimisation Prediction Model for Surface Roughness. International Journal of Physical Sciences, 6 (13). pp. 3082-3090. ISSN 1992-1950. (Published)

[img]
Preview
PDF
Particle_swarm_optimisation_prediction_model_for.pdf

Download (399kB)

Abstract

Acrylic sheet is a crystal clear (with transparency equal to optical glass), lightweight material having outstanding weather ability, high impact resistance, good chemical resistance, and excellent thermo-formability and machinability. This paper develops the artificial intelligent model using partial swarm optimization (PSO) to predict the optimum surface roughness when cutting acrylic sheets with laser beam cutting (LBC). Response surface method (RSM) was used to minimize the number of experiments. The effect of cutting speed, material thickness, gap of tip and power towards surface roughness were investigated. It was found that the surface roughness is significantly affected by the tip distance followed by the power requirement, cutting speed and material thickness. Surface roughness becomes larger when using low power, tip distance and material thickness. Combination of low cutting speed, high power, tip distance and material distance produce fine surface roughness. Some defects were found in microstructure such as burning, melting and wavy surface. The optimized parameters by PSO are cutting speed (2600 pulse/s), tip distance (9.70 mm), power (95%) and material thickness (9 mm) which produce roughness around 0.0129 µm.

Item Type: Article
Additional Information: Muhamad Mat Noor (M. M. Noor) Prof. Dr. Md Mustafizur Rahman (M. M. Rahman) Dr. Kumaran Kadirgama (K. Kadirgama)
Uncontrolled Keywords: Laser beam; Particle swarm optimization; Surface roughness, Acrylic sheet
Subjects: T Technology > TS Manufactures
Faculty/Division: Faculty of Mechanical Engineering
Depositing User: Pn. Hazlinda Abd Rahman
Date Deposited: 12 Mar 2012 05:59
Last Modified: 25 Jan 2018 04:05
URI: http://umpir.ump.edu.my/id/eprint/2228
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item