FDM Parameters Optimization for Improving Tensile Strength using Response Surface Methodology and Particle Swarm Optimization

Authors

  • Mohamad Ezral Baharudin Faculty of Mechanical Engineering & Technology, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
  • Mohd Sazli Saad Faculty of Mechanical Engineering & Technology, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
  • Mohd Zakimi Zakaria Faculty of Mechanical Engineering & Technology, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
  • Azuwir Mohd Nor Faculty of Mechanical Engineering & Technology, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
  • Mat Hussin Ab Talib Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia

DOI:

https://doi.org/10.37934/araset.38.2.112128

Keywords:

Additive Manufacturing (AM), Fused Deposition Modelling (FDM), Particle Swarm Optimisation (PSO), Response Surface Methodology (RSM), tensile strength

Abstract

Fused deposition modelling (FDM) is a popular 3D printing technique that uses a thermoplastic filament as the build material. In FDM 3D printing, tensile strength can be an issue because the layers of the object are built on top of each other, and if the layers do not adhere properly, the object can be weak and prone to breaking. Typically, this problem is caused by incorrect parameter settings. Hence, this study was then carried out to analyse and improve the printing quality in term of tensile strength of the printed part using the response surface methodology (RSM) and the particle swarm optimization (PSO) method. The effect of four input parameters such as layer height, printing speed, infill density, and print temperature was examined on the tensile strength of polylactic acid (PLA) standard samples ASTM D638-IV. The experimental design was performed using face-centred central composite designs (FCCD). The experimental data were statistically analysed to form a regression model of the tensile strength. This model was used to approximate the actual process. The optimization was performed using desirability analysis from RSM and PSO to search for the optimal parameter for maximum tensile strength. Experimental results showed that PSO outperformed RSM with a 1.52 % reduction in tensile strength. The maximum tensile strength obtained from PSO was about 39.069 MPa with the optimal process parameters of layer height of 0.30 mm, printing speed of 30.17 m/s, infill density of 79.72 %, and print temperature of 205.92 °C.

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Author Biographies

Mohamad Ezral Baharudin, Faculty of Mechanical Engineering & Technology, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia

mezral@unimap.edu.my

Mohd Sazli Saad, Faculty of Mechanical Engineering & Technology, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia

sazlisaad@unimap.edu.my

Mohd Zakimi Zakaria, Faculty of Mechanical Engineering & Technology, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia

zakimizakaria@unimap.edu.my

Azuwir Mohd Nor, Faculty of Mechanical Engineering & Technology, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia

azuwir@unimap.edu.my

Mat Hussin Ab Talib, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia

mathussin@utm.my

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Published

2024-01-30

How to Cite

Baharudin, M. E., Saad, M. S., Zakaria, M. Z., Mohd Nor, A., & Ab Talib, M. H. (2024). FDM Parameters Optimization for Improving Tensile Strength using Response Surface Methodology and Particle Swarm Optimization. Journal of Advanced Research in Applied Sciences and Engineering Technology, 38(2), 112–128. https://doi.org/10.37934/araset.38.2.112128

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