Multi Responses Optimization of Plastic Injection Moulding Through Simulation Using MOLDEX3D

Authors

  • Syidatul Akma Sulaiman Pengajian Kejuruteraan Mekanikal, UiTM Cawangan Johor, Kampus Pasir Gudang, 81750 Masai, Johor, Malaysia
  • Nurul Hayati Abdul Halim School of Mechanical Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia.
  • Wan Mohamad Alif Mohd Roslan School of Mechanical Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia
  • Izdihar Tharazi School of Mechanical Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia
  • Farrahshaida Mohd Salleh School of Mechanical Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia.
  • Mohamad Firhan Morni School of Mechanical Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia

DOI:

https://doi.org/10.37934/araset.64.3.5968

Keywords:

Injection Moulding, Optimization, Design Expert, ANOVA, MOLDEX3D

Abstract

Process parameters in plastic injection moulding such as filling time, packing time, injection speed and cooling time are generally determined by a trial-and error method through the experiments. Trial and error method is cost and time consuming. Therefore, finding the optimal and best process parameter becomes the most crucial and important issue in injection moulding process. Thus, multi-response optimization of plastic injection moulding using MOLDEX3D simulation software is an alternative approach to determine the optimal process parameter. Three factors which are cooling time (10-20s), packing time (2-7s), and filling time (2-5ss) were controlled at 2 levels and the experiment were designed by using Full Factorial method of Design Expert that entail eight sets of process parameters. Subsequently, results obtained from the simulation works were thoroughly analysed by using Analysis of Variance (ANOVA). Result shows the cooling time is the most significant control factor which contributes to 83.7% and 100% on warpage and cycle time respectively. While for the filling time, the influence contribution is 92.56% on the volumetric shrinkage. Optimized process parameters were selected at packing time at 7 s, filling time at 5s and cooling time at 12.190s to achieve 25.690s of cycle time for producing a plastic card holder. For validation, the selected optimum process parameter was assigned to a plastic injection moulding machine and managed to produce a plastic card holder with better quality which suitable for small and medium scale production.

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Author Biographies

Syidatul Akma Sulaiman, Pengajian Kejuruteraan Mekanikal, UiTM Cawangan Johor, Kampus Pasir Gudang, 81750 Masai, Johor, Malaysia

syidatul_akma7091@uitm.edu.my

Nurul Hayati Abdul Halim , School of Mechanical Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia.

hayatihalim@uitm.edu.my

Wan Mohamad Alif Mohd Roslan, School of Mechanical Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia

alifroslan@gmail.com.my

Izdihar Tharazi , School of Mechanical Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia

izdihar92@uitm.edu.my

Farrahshaida Mohd Salleh , School of Mechanical Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia.

fshaida@uitm.edu.my

Mohamad Firhan Morni , School of Mechanical Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia

firhan@uitm.edu.my

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Published

2025-03-15

How to Cite

Sulaiman, S. A., Abdul Halim , N. H., Mohd Roslan, W. M. A., Tharazi , I., Mohd Salleh , F., & Morni , M. F. (2025). Multi Responses Optimization of Plastic Injection Moulding Through Simulation Using MOLDEX3D. Journal of Advanced Research in Applied Sciences and Engineering Technology, 64(3), 59–68. https://doi.org/10.37934/araset.64.3.5968

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