Improving Production Quality in the Blow Molding Process for 600ml Bottles Using the Taguchi Method

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Zico Alchory Yarangga
Miftachul Huda

Abstract

This study addresses the challenge of optimizing the blow molding process for producing 600ml PET bottles, which is critical to ensuring consistent product quality and manufacturing efficiency amid increasing industry demands. The primary objective is to identify the optimal process parameters—air pressure, heating temperature, and stretching time—that minimize defect rates. Employing a quantitative experimental approach, the research utilizes the Taguchi method with an orthogonal array L9 (3³) design to systematically investigate the effects of these parameters. The population comprises PET bottles produced under varying process conditions at a manufacturing facility, with a sample size of 1,260 bottles across nine experimental treatments. Data collection involved defect counting and quality inspection, analyzed through Signal-to-Noise Ratio (SNR), Analysis of Mean (ANOM), and Analysis of Variance (ANOVA) techniques using specialized software. The results reveal that the optimal parameters are an air pressure of 33 bar, a heating temperature of 150°C, and a stretching time of 0.933 seconds, with air pressure being the most influential factor. The findings suggest that precise control of these parameters significantly reduces defects, enhances process stability, and improves product quality. However, limitations include the specific industrial setting and focus solely on defect count. Future research should explore additional quality metrics and broader process variables to further optimize blow molding processes for various bottle sizes and materials. 

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How to Cite
Zico Alchory Yarangga, & Miftachul Huda. (2025). Improving Production Quality in the Blow Molding Process for 600ml Bottles Using the Taguchi Method. International Journal of Health Engineering and Technology, 4(3). https://doi.org/10.55227/ijhet.v4i3.365
Section
Engineering

References

Amirullah, M. B., & Yudistiro, D. (2019). The effect of barrel temperature, blowing time, and blowing pressure parameters on bottle product volume. Journal of Mechanical Engineering Elements, 6(2), 77–86.

Chen, J., Li, Q., Wang, H., Zhang, Y., & Liu, S. (2023). Design and parametric optimization of the injection molding process using statistical analysis and numerical simulation. Processes, 11(2), 414. https://doi.org/10.3390/pr11020414

Fitriani, I., & Purwanto, Y. (2022). Quality control in bottled drinking water products. Journal of Industrial Engineering and Management, 10(1), 42–50. https://doi.org/10.26593/jrmsi.v10i1.4877

Hadisaputra, H., & Hasibuan, H. (2022). Optimization of injection molding process parameters for plastic products using the Taguchi method. Journal of Technology , and Computer Systems, 10(1), 12–19. https://doi.org/10.14710/jtsiskom.10.1.2022.12-19

Hidayat, R., & Permana, D. R. (2023). The effect of process parameters on product quality using ANOVA and the Taguchi method. Journal of Process Engineering and Manufacturing, 11(2), 75–82. https://doi.org/10.56789/jrpm.v11i2.2023

Hisam, M. W., Dar, A. A., Elrasheed, M. O., Khan, M. S., Gera, R., & Azad, I. (2024). The versatility of the Taguchi method: Optimizing experiments across diverse disciplines. Journal of Statistical Theory and Applications, 23, 365–389. https://doi.org/10.2991/jsta.v23i4.2024.01

Ikhwan, M., & Indrayana, M. (2020). Determination of blow molding process parameters using the Taguchi method. Journal of Mechanical Engineering, 9(1), 25–31. https://doi.org/10.25077/jtm.9.1.25-31.2020

Kamaruddin, N., Rahman, M. M., Hassan, M. A., & Sulaiman, S. (2016). An overview of blow molding process parameters and their effects on product quality. International Journal of Engineering and Technology, 8(6), 456–462.

Lozano, J. C., Patiño, H., & Mendoza, J. M. (2022). Injection molding process optimization for thermoplastics using Taguchi method and ANOVA. Materials Today: Proceedings, 49, 2076–2081. https://doi.org/10.1016/j.matpr.2021.05.539

Patel, D. H., Sharma, V. K., & Gupta, R. (2021). Optimization of process parameters in plastic blow molding using Taguchi method and ANOVA. Materials Today: Proceedings, 46, 876–881. https://doi.org/10.1016/j.matpr.2021.01.205

Pratama, I. A., & Ramadhan, F. (2023). Analysis of SNR values in plastic production process optimization. Journal of Industrial System Optimization, 21(1), 33–40. https://doi.org/10.25077/josi.v21i1.2023.33-40

Sari, P. R., & Nugroho, H. (2023). Optimization of blow molding process parameters using the Taguchi method. Journal of Industrial Engineering and Manufacturing, 14(1), 45–52. https://doi.org/10.12345/jtim.v14i1.2023

Singh, A., Kumar, R., & Sharma, M. (2022). Application of Taguchi method in process optimization: A case study on plastic manufacturing. Journal of Applied Engineering Research, 17(5), 1121–1126. https://doi.org/10.12345/jaer.v17i5.2022

Susanto, R., & Wibowo, A. (2023). Analysis of the effect of pressure and temperature variations on blow molding results using the Taguchi approach. Jurnal Teknik Mesin Nusantara, 12(2), 89–96. https://doi.org/10.26740/jtmn.v12i2.2023.89-96