Development of surface roughness model in turning process of 3X13 steel using TiAlN coated carbide insert
Surface roughness that is one of the most important parameters is used to evaluate the quality of a machining process. Improving the accuracy of the surface roughness model will contribute to ensure an accurate assessment of the machining quality. This study aims to improve the accuracy of the surface roughness model in a machnining process. In this study, Johnson and Box-Cox transformations were successfully applied to improve the accuracy of surface roughness model when turning 3X13 steel using TiAlN insert. Four input parameters that were used in experimental process were cutting velocity, feed rate, depth of cut, and insert-nose radius. The experimental matrix was designed using Central Composite Design (CCD) with 29 experiments. By analyzing the experimental data, the influence of input parameters on surface roughness was investigated. A quadratic model was built to explain the relationship of surface roughness and the input parameters. Box-Cox and Johnson transformations were applied to develop two new models of surface roughness. The accuracy of three surface roughness models showed that the surface roughness model using Johnson transformation had the highest accuracy. The second one model of surface roughness is the model using Box-Cox transformation. And surface roughness model without transformation had the smallest accuracy. Using the Johnson transformation, the determination coefficient of surface roughness model increased from 80.43 % to 84.09 %, and mean absolute error reduced from 19.94 % to 16.64 %. Johnson and Box-Cox transformations could be applied to improve the acuaracy of the surface roughness prediction in turning process of 3X13 steel and can be extended with other materials and other machining processes
Kumar, N., Kumar, P. (2016). Influence of machining parameters on surface roughness and dry friction. Engineering Solid Mechanics, 109–116. doi: https://doi.org/10.5267/j.esm.2016.3.001
Bala Raju, J., Leela Krishna, J., Tejomurthy, P. (2013). Effect and optimization of machining parameters on cutting force and surface finish in turning of mild steel and aluminum. International Journal of Research in Engineering and Technology, 02 (11), 135–141. doi: https://doi.org/10.15623/ijret.2013.0211021
Yacov, S., Gurpreet, S. (2013). Determining the Influence of Various Cutting Parameters on Surface Roughness during Wet CNC Turning of AISI 1040 Medium Carbon Steel. IOSR Journal of Mechanical and Civil Engineering, 7 (2), 63–72. doi: https://doi.org/10.9790/1684-0726372
Rao, C. J., Rao, D. N., Srihari, P. (2013). Influence of Cutting Parameters on Cutting Force and Surface Finish in Turning Operation. Procedia Engineering, 64, 1405–1415. doi: https://doi.org/10.1016/j.proeng.2013.09.222
Struzikiewicz, G., Sioma, A. (2020). Evaluation of Surface Roughness and Defect Formation after The Machining of Sintered Aluminum Alloy AlSi10Mg. Materials, 13 (7), 1662. doi: https://doi.org/10.3390/ma13071662
Mia, M., Bashir, M. A., Dhar, N. R. (2016). Effects of Cutting Parameters and Machining Environments on Surface Roughness in Hard Turning using Design of Experiment. AIP Conference Proceedings, 1754. doi: https://doi.org/10.1063/1.4958453
Aleksandrovich, R. V., Siamak, G. (2014). The Effect of Tool Construction and Cutting Parameters on Surface Roughness and Vibration in Turning of AISI 1045 Steel Using Taguchi Method. Modern Mechanical Engineering, 04 (01), 8–18. doi: https://doi.org/10.4236/mme.2014.41002
Saini, S., Ahuja, I. S., Sharma, V. S. (2012). Influence of cutting parameters on tool wear and surface roughness in hard turning of AISI H11 tool steel using ceramic tools. International Journal of Precision Engineering and Manufacturing, 13 (8), 1295–1302. doi: https://doi.org/10.1007/s12541-012-0172-6
Dejan, T., Velibor, M. (2012). Modelling and Optimization of the Surface Roughness in the Dry Turning of the Cold Rolled Alloyed Steel Using Regression Analysis. Journal of the Brazilian Society of Mechanical Sciences and Engineering. XXXIV (1), 41–48.
Yousefi, S., Zohoor, M. (2019). Effect of cutting parameters on the dimensional accuracy and surface finish in the hard turning of MDN250 steel with cubic boron nitride tool, for developing a knowledged base expert system. International Journal of Mechanical and Materials Engineering, 14 (1). doi: https://doi.org/10.1186/s40712-018-0097-7
Yusuf, M., Anuar, K., Ismail, N. B., Sulaiman, S. (2011). Influence of Cutting Parameters on Surface Roughness for Wet and Dry Turning Process. Key Engineering Materials, 471-472, 233–238. doi: https://doi.org/10.4028/www.scientific.net/kem.471-472.233
Lazarević, D., Madić, M., Janković, P., Lazarević, A. (2012). Cutting Parameters Optimization for Surface Roughness in Turning Operation of Polyethylene (PE) Using Taguchi Method. Tribology in Industry, 34 (2), 68–73. Available at: http://www.tribology.rs/journals/2012/2012-2/3.pdf
Senthil Kumar, K., Senthilkumaar, J. S., Srinivasan, A. (2013). Reducing surface roughness by optimising the turning parameters. The South African Journal of Industrial Engineering, 24 (2), 78. doi: https://doi.org/10.7166/24-2-593
Akkuş, H., Yaka, H. (2021). Experimental and statistical investigation of the effect of cutting parameters on surface roughness, vibration and energy consumption in machining of titanium 6Al-4V ELI (grade 5) alloy. Measurement, 167, 108465. doi: https://doi.org/10.1016/j.measurement.2020.108465
Angela, D., Daniel, V. (1999). Design and Analysis of Experiments. Springer, 742. doi: https://doi.org/10.1007/b97673
Nguyen, V. D., Nguyen, D. B. (2011). Design of experiment techniques. Science and technics publishing House, Hanoi.
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