Analysis of tool wear and surface roughness in high-speed milling process of aluminum alloy Al6061
Abstract
In this study, the influence of cutting parameters and machining time on the tool wear and surface roughness was investigated in high-speed milling process of Al6061 using face carbide inserts. Taguchi experimental matrix (L9) was chosen to design and conduct the experimental research with three input parameters (feed rate, cutting speed, and axial depth of cut). Tool wear (VB) and surface roughness (Ra) after different machining strokes (after 10, 30, and 50 machining strokes) were selected as the output parameters. In almost cases of high-speed face milling process, the most significant factor that influenced on the tool wear was cutting speed (84.94 % after 10 machining strokes, 52.13 % after 30 machining strokes, and 68.58 % after 50 machining strokes), and the most significant factors that influenced on the surface roughness were depth of cut and feed rate (70.54 % after 10 machining strokes, 43.28 % after 30 machining strokes, and 30.97 % after 50 machining strokes for depth of cut. And 22.01 % after 10 machining strokes, 44.39 % after 30 machining strokes, and 66.58 % after 50 machining strokes for feed rate). Linear regression was the most suitable regression of VB and Ra with the determination coefficients (R2) from 88.00 % to 91.99 % for VB, and from 90.24 % to 96.84 % for Ra. These regression models were successfully verified by comparison between predicted and measured results of VB and Ra. Besides, the relationship of VB, Ra, and different machining strokes was also investigated and evaluated. Tool wear, surface roughness models, and their relationship that were found in this study can be used to improve the surface quality and reduce the tool wear in the high-speed face milling of aluminum alloy Al6061
Downloads
References
Nguyen, N.-T., Tien, D. H., Trung, D. D. (2020). Multi-Objective Optimization when Surface Grinding the 3X13 Steel by Combining the General Reduced Gradient Algorithm and Harmonic Mean Method. Advances in Science, Technology and Engineering Systems Journal, 5 (5), 395–400. doi: https://doi.org/10.25046/aj050550
Eckstein, M., Vrabeľ, M., Maňková, I. (2016). Tool Wear and Surface Roughness Evolution in Hole Making Process of Inconel 718. Materials Science Forum, 862, 11–17. doi: https://doi.org/10.4028/www.scientific.net/msf.862.11
Gürgen, S., Tali, D., Kushan, M. C. (2019). An Investigation on Surface Roughness and Tool Wear in Turning Operation of Inconel 718. Journal of Aerospace Technology and Management. doi: https://doi.org/10.5028/jatm.v11.1030
Behera, B. C., Alemayehu, H., Ghosh, S., Rao, P. V. (2017). A comparative study of recent lubri-coolant strategies for turning of Ni-based superalloy. Journal of Manufacturing Processes, 30, 541–552. doi: https://doi.org/10.1016/j.jmapro.2017.10.027
Laghari, R. A., Li, J., Xie, Z., Wang, S. (2018). Modeling and Optimization of Tool Wear and Surface Roughness in Turning of Al/SiCp Using Response Surface Methodology. 3D Research, 9 (4). doi: https://doi.org/10.1007/s13319-018-0199-2
Nguyen, N. T., Do, D. T. (2020). Modeling and Improvement of the Surface Roughness Model in Hole Turning Process 3x13 Stainless Steel by Using Johnson Transformation. International Journal of Mechanical and Production Engineering Research and Development (IJMPERD), 10 (3), 12097–12110. Available at: http://paper.researchbib.com/view/paper/260700
Kilickap, E., Yardimeden, A., Çelik, Y. H. (2017). Mathematical Modelling and Optimization of Cutting Force, Tool Wear and Surface Roughness by Using Artificial Neural Network and Response Surface Methodology in Milling of Ti-6242S. Applied Sciences, 7 (10), 1064. doi: https://doi.org/10.3390/app7101064
Li, Y., Zheng, G., Zhang, X., Cheng, X., Yang, X., Xu, R. (2019). Cutting force, tool wear and surface roughness in high-speed milling of high-strength steel with coated tools. Journal of Mechanical Science and Technology, 33 (11), 5393–5398. doi: https://doi.org/10.1007/s12206-019-1033-3
Molla Ramezani, N., Rasti, A., Sadeghi, M. H., Jabbaripour, B., Rezaei Hajideh, M. (2016). Experimental study of tool wear and surface roughness on high speed helical milling in D2 steel. Modares Mechanical Engineering, 15 (13), 198–202. Available at: https://mme.modares.ac.ir/article-15-8858-en.html
Nguyen, N.-T. (2020). A Study on Influence of Milling Types and Cutting Conditions on Surface Roughness in Milling of Aluminum Alloy Al6061-T6. Universal Journal of Mechanical Engineering, 8 (4), 183–190. doi: https://doi.org/10.13189/ujme.2020.080403
Nguyen, T., Park, K.-H., Wang, X., Olortegui-Yume, J., Wong, T., Schrock, D. et. al. (2015). The Genesis of Tool Wear in Machining. Volume 15: Advances in Multidisciplinary Engineering. doi: https://doi.org/10.1115/imece2015-52531
Wang, R., Wang, B., Barber, G., Gu, J., Schall, J. D. (2019). Models for Prediction of Surface Roughness in a Face Milling Process Using Triangular Inserts. Lubricants, 7 (1), 9. doi: https://doi.org/10.3390/lubricants7010009
Coppini, N. L., Diniz, A. E., Lacerda, F. S., Bonandi, M., Baptista, E. A. (2018). Internal turning of sintered carbide parts: tool wear and surface roughness evaluation. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 40 (4). doi: https://doi.org/10.1007/s40430-018-1139-z
Hoang, D. T., Nguyen, N.-T., Tran, Q. D., Nguyen, T. V. (2019). Cutting Forces and Surface Roughness in Face-Milling of SKD61 Hard Steel. Strojniški Vestnik - Journal of Mechanical Engineering, 65 (6), 375–385. doi: https://doi.org/10.5545/sv-jme.2019.6057
Jeyakumar, S., Marimuthu, K., Ramachandran, T. (2013). Prediction of cutting force, tool wear and surface roughness of Al6061/SiC composite for end milling operations using RSM. Journal of Mechanical Science and Technology, 27 (9), 2813–2822. doi: https://doi.org/10.1007/s12206-013-0729-z
Kundor, N. F., Awang, N. W., Berahim, N. (2016). Tool Wear and Surface Roughness in Machining AISI D2 Tool Steel. Indian Journal of Science and Technology, 9 (18). doi: https://doi.org/10.17485/ijst/2016/v9i18/88731
Said, M. S., Ghani, J. A., Che Haron, C. H., Yusoff, S., Selamat, M. A., Othman, R. (2013). Tool Wear and Surface Roughness when Machining AlSi/AlN Metal Matrix Composite Using Uncoated Carbide Cutting Tool. Materials Science Forum, 773-774, 409–413. doi: https://doi.org/10.4028/www.scientific.net/msf.773-774.409
Ali, S. M., Dhar, N. R. (2010). Modeling of tool wear and surface roughness under MQL condition-a neural approach. Canadian Journal on Artificial Intelligence, Machine Learning & Pattern Recognition, 1 (2), 7–25.
Junaid Mir, M., Wani, M. F. (2018). Modelling and analysis of tool wear and surface roughness in hard turning of AISI D2 steel using response surface methodology. International Journal of Industrial Engineering Computations, 9, 63–74. doi: https://doi.org/10.5267/j.ijiec.2017.4.004
Trang, L. N., Tran, X.-T., Hai, N. T., Nguyen, N.-T. (2020). An investigation and analysis of surface roughness and tool wear in dry pocket milling of Aluminum alloy Al7075. International Journal of Mechanical and Production Engineering Research and Development (IJMPERD), 10 (2), 1307–1320. Available at: http://www.tjprc.org/publishpapers/2-67-1587533979-126IJMPERDAPR2020126.pdf
Asiltürk, İ., Akkuş, H. (2011). Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method. Measurement, 44 (9), 1697–1704. doi: https://doi.org/10.1016/j.measurement.2011.07.003
Suresh, R., Basavarajappa, S., Samuel, G. L. (2012). Some studies on hard turning of AISI 4340 steel using multilayer coated carbide tool. Measurement, 45 (7), 1872–1884. doi: https://doi.org/10.1016/j.measurement.2012.03.024
Yıldırım, Ç. V., Kıvak, T., Erzincanlı, F. (2019). Tool wear and surface roughness analysis in milling with ceramic tools of Waspaloy: a comparison of machining performance with different cooling methods. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 41 (2). doi: https://doi.org/10.1007/s40430-019-1582-5
Lumley, R. (Ed.) (2011). Fundamentals of aluminium metallurgy: production, processing and applications. Elsevier. doi: https://doi.org/10.1533/9780857090256
Lezanski, P., Shaw, M. C. (1990). Tool Face Temperatures in High Speed Milling. Journal of Engineering for Industry, 112 (2), 132–135. doi: https://doi.org/10.1115/1.2899555
Copyright (c) 2021 Nhu-Tung Nguyen, Dung Hoang Tien, Nguyen Tien Tung, Nguyen Duc Luan
This work is licensed under a Creative Commons Attribution 4.0 International License.
Our journal abides by the Creative Commons CC BY copyright rights and permissions for open access journals.
Authors, who are published in this journal, agree to the following conditions:
1. The authors reserve the right to authorship of the work and pass the first publication right of this work to the journal under the terms of a Creative Commons CC BY, which allows others to freely distribute the published research with the obligatory reference to the authors of the original work and the first publication of the work in this journal.
2. The authors have the right to conclude separate supplement agreements that relate to non-exclusive work distribution in the form in which it has been published by the journal (for example, to upload the work to the online storage of the journal or publish it as part of a monograph), provided that the reference to the first publication of the work in this journal is included.