OPTIMIZATION OF MACHINING PARAMETERS ON THE SURFACE ROUGHNESS OF ALUMINUM IN CNC TURNING PROCESS USING TAGUCHI METHOD

Authors

DOI:

https://doi.org/10.22441/ijimeam.v5i2.21679

Keywords:

Taguchi Method, CNC, Surface Roughness, Orthogonal Array, Aluminum Alloy 6063

Abstract

In this research, Taguchi method is employed by focusing on spindle speed, feed rate, and depth of cut to optimize the CNC turning parameters for aluminum alloy 6063. The main goal of this study is to improve the surface roughness of the material. A L9 orthogonal array is used for experimentation, and the results are subsequently analyzed using ANOVA (Analysis of Variance). A spindle speed of 1300 rpm, a feed rate of 0.5 m/min, and a depth of cut of 1.5 mm are the optimal conditions to achieve the minimum average surface roughness (Ra). The main effect plot of the signal-to-noise (S/N) ratio provides significant evidence supporting the primary research goal. Furthermore, the ANOVA table reveals that spindle speed contributes 59.71%, feed rate contributes 29.80%, while depth of cut only contributes minimally at 0.72%. Based on the research findings, spindle speed and feed rate can be adjusted to control surface roughness. Both factors are highly significant in influencing the surface roughness of the material. The prediction equation from the linear regression analysis is Ra = 1.745 – 0.001024 spindle speed + 0.3000 feed rate – 0.0233 depth of cut. A coefficient of determination or R-squared value of 0.9115 indicates that the independent variables can explain 91.15% of the variation in the dependent variable. The experimental and predicted surface roughness (Ra) values have a predicted error percentage of 2.26%.

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References

Sachin, B., Narendranath, S., & Chakradhar, D. (2018). Effect of cryogenic diamond burnishing on residual stress and microhardness of 17-4 PH stainless steel. Materials Today: Proceedings, 5(9), 18393-18399.

Rao, B. N., Banapurmath, N. R., Atgur, V., Sanjeevannavar, M. B., Sajjan, A. M., Vadlamudi, C., ... & Ayachit, N. H. (2023). Utilization of additives in biodiesel blends for improving the diesel engine performance and minimizing emissions through a modified Taguchi approach. Heliyon.

Barik, B. B., Mahanty, A., Majumder, S. D., & Goswami, A. R. (2023). Fabrication of cost-effective three-axis portable mini-CNC milling Machine. Materials Today: Proceedings.

Soejanto, I. (2009). Desain eksperimen dengan metode Taguchi. Yogyakarta: Graha Ilmu.

Hamzaçebi, C., Li, P., Pereira, P. A. R., & Navas, H. (2020). Taguchi method as a robust design tool. Quality Control-Intelligent Manufacturing, Robust Design and Charts, 1-19.

Khandey, U., & Arya, V. (2023). Optimization of multiple surface roughness characteristics of mild steel turned product using weighted principal component and Taguchi method. Materials Today: Proceedings.

Kumar, N. S., Shetty, A., Shetty, A., Ananth, K., & Shetty, H. (2012). Effect of spindle speed and feed rate on surface roughness of carbon steels in CNC turning. Procedia Engineering, 38, 691-697.

Palaniappan, S. P., Muthukumar, K., Sabariraj, R. V., Kumar, S. D., & Sathish, T. (2020). CNC turning process parameters optimization on Aluminium 6082 alloy by using Taguchi and ANOVA. Materials Today: Proceedings, 21, 1013-1021.

Das, B., Roy, S., Rai, R. N., & Saha, S. C. (2016). Application of grey fuzzy logic for the optimization of CNC milling parameters for Al–4.5% Cu–TiC MMCs with multi-performance characteristics. Engineering Science and Technology, an International Journal, 19(2), 857-865.

Benardos, P. G., & Vosniakos, G. C. (2002). Prediction of surface roughness in CNC face milling using neural networks and Taguchi's design of experiments. Robotics and Computer-Integrated Manufacturing, 18(5-6), 343-354.

Irfan, S. S., Kumar, M. V., & Rudresha, N. (2019). Optimization of machining parameters in CNC turning of EN45 by Taguchi’s orthogonal array experiments. Materials Today: Proceedings, 18, 2952-2961.

Kumar, M. V., Kumar, B. K., & Rudresha, N. (2018). Optimization of machining parameters in CNC turning of stainless steel (EN19) by Taguchi’s orthogonal array experiments. Materials Today: Proceedings, 5(5), 11395-11407.

Maneesh, K., Shan, M., Xavier, S., Vinayak, M. B., & Shafeek, M. (2023). Quality characteristic optimization in CNC turning of aluminum bronze by using Taguchi’s approach and ANOVA. Materials Today: Proceedings, 80, 620-628.

Mia, M., Dey, P. R., Hossain, M. S., Arafat, M. T., Asaduzzaman, M., Ullah, M. S., & Zobaer, S. T. (2018). Taguchi S/N based optimization of machining parameters for surface roughness, tool wear and material removal rate in hard turning under MQL cutting condition. Measurement, 122, 380-391.

Singh, R. (2021). Application of Taguchi method to optimize CNC parameters on Brass 63/37 (C27400). Materials Today: Proceedings, 45, 4424-4430.

Krishnan, B. R., & Ramesh, M. (2020). Optimization of machining process parameters in CNC turning process of IS2062 E250 Steel using coated carbide cutting tool. Materials Today: Proceedings, 21, 346-350.

Parnianifard, A. (2022). Robust Product Design: A Modern View of Quality Engineering in Manufacturing Systems.

Kesarwani, R., Ariz, M., & Kumar, N. (2017). HHO generation & its application on welding. IJSRD-International Journal for Scientific Research & Development, 5(09).

Gurugubelli, S., Chekuri, R. B. R., & Penmetsa, R. V. (2022). Experimental investigation and optimization of turning process of EN8 steel using Taguchi L9 orthogonal array. Materials Today: Proceedings, 58, 233-237.

Sahithi, V. V. D., Malayadrib, T., & Srilatha, N. (2019). Optimization of turning parameters on surface roughness based on Taguchi technique. Materials Today: Proceedings, 18, 3657-3666.

Selvaraj, D. P., & Chandramohan, P. (2010). Optimization of surface roughness of AISI 304 austenitic stainless steel in dry turning operation using Taguchi design method. Journal of engineering science and technology, 5(3), 293-301.

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Published

2023-12-27

How to Cite

1.
Putra YM, Timuda GE, Darsono N, Chollacoop N, Khaerudini DS. OPTIMIZATION OF MACHINING PARAMETERS ON THE SURFACE ROUGHNESS OF ALUMINUM IN CNC TURNING PROCESS USING TAGUCHI METHOD. Int. J. Innov. Mech. Eng. Adv. Mater [Internet]. 2023 Dec. 27 [cited 2026 Jun. 3];5(2):56-62. Available from: https://publikasi.mercubuana.ac.id/index.php/ijimeam/article/view/21679

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