Effect of Dressing Parameters on Material Removal Rate when Surface Grinding SKD11 Tool Steel

Abstract:

Nowadays, surface grinding is one of the most common of metal finishing methods. The efficiency of this process is affected by the so-called process parameters such as dressing feed rate (S), rough dressing depth (a_r), rough dressing times (n_r), fine dressing depth (a_f), fine dressing times (n_f), and non-feeding dressing (n_non). etc. In this paper, the optimization of dressing parameters in surface grinding SKD11 tool steel is studied. The aim of the study is to find the most appropriate value set of dressing parameters to maximize the material removal rate (MRR). In order to solve the problem, the Taguchi method is used. Based on an orthogonal array L₁₆(4⁴x2²), sixteen experiments have been conducted. By analyzing the experimental results, an optimal solution of such optimization problem has been solved, presenting the most appropriate dressing parameters as follows: a_r = 0.015 mm, n_r = 2 times, a_f = 0.005 mm, n_f = 0 times, n_non = 0 times, S = 1.6 m/min. The discovered technology mode has been applied to the real machining process and the outcome shows out a much better result in comparison with default setting modes, that the difference between the model values and the real values of the roughness average is controlled within 3.87% of the ranges.

• Periodical: Materials Science Forum (Volume 1020)
• Pages: 60-67
• DOI: https://doi.org/10.4028/www.scientific.net/MSF.1020.60
• Online since: February 2021
• Authors: Thi Hong Tran, Thanh Danh Bui, Nguyen Anh Tuan, Vu Trung Tuyen, Luu Anh Tung, Thanh Tu Nguyen, Tran Ngoc Giang, Vu Ngoc Pi*
• Keywords: Dressing Parameters, Grinding Wheel, Material Removal Rate, SKD11, Taguchi Method

References

[1] Tran T. H., Luu A. T., Nguyen Q. T., Le H. K. Hoang, T. D. Vu, Vu, N. P. (2020). A Study on Calculation of Optimum Exchanged Grinding Wheel Diameter when Surface Grinding Stainless Steel. Materials Science Forum, 977, 3–11. https://doi.org/10.4028/www.scientific.net/ msf.977.3.

DOI: 10.4028/www.scientific.net/msf.977.3

[2] Tran, T. H., Hoang, X. T., Le, H. K., Nguyen, Q. T., Nguyen, T. T., Nguyen, T. T. N., Jun, G., & Vu, N. P. (2020). A Study on Cost Optimization of External Cylindrical Grinding. Materials Science Forum, 977, 18–26. https://doi.org/10.4028/www.scientific.net/msf.977.18.

DOI: 10.4028/www.scientific.net/msf.977.18

[3] Hung, L. X., Lien, V. T., Pi, V. N., & Long, B. T. (2019). A Study on Coolant Parameters in Internal Grinding of 9CrSi Steel. Materials Science Forum, 950, 24–31. https://doi.org/10.4028/www.scientific.net/msf.950.24.

DOI: 10.4028/www.scientific.net/msf.950.24

[4] Tu, H. X., Pi, V. N., & Jun, G. (2019). A Study on Determination of Optimum Parameters for Lubrication in External Cylindrical Grinding Base on Taguchi Method. Key Engineering Materials, 796, 97–102. https://doi.org/10.4028/www.scientific.net/kem.796.97.

DOI: 10.4028/www.scientific.net/kem.796.97

[5] Le Xuan Hung, Vu Ngoc Pi, Luu Anh Tung, Hoang Xuan Tu, Gong Jun and BanhTien Long. Determination of Optimal Exchanged Grinding Wheel Diameter when Internally Grinding Alloy Tool Steel 9CrSi. In IOP Conference Series: Materials Science and Engineering. (2018). IOP Publishing.

DOI: 10.1088/1757-899x/417/1/012026

[6] Tran, T.-H., et al., Optimization of replaced grinding wheel diameter for minimum grinding cost in internal grinding. Applied Sciences, 2019. 9(7): p.1363.

DOI: 10.3390/app9071363

[7] Tran, T.-H., et al., Optimization of Replaced Grinding Wheel Diameter for Surface Grinding Based on a Cost Analysis. Metals, 2019. 9(4): p.448.

DOI: 10.3390/met9040448

[8] Hoang Xuan Tu, Gong Jun, LX Hung, LA Tung, VN Pi. Calculation of optimum exchanged grinding wheel diameter when external grinding tool steel 9CrSi. International Journal of Mechanical Engineering and Robotics Research Vol. 8, No. 1, January (2019).

DOI: 10.18178/ijmerr.8.1.59-64

[9] Tu, H.X., et al. Influence of dressing parameters on surface roughness of workpiece for grinding hardened 9XC tool steel. in IOP Conference Series: Materials Science and Engineering. 2019. IOP Publishing. https://iopscience.iop.org/article/10.1088/1757-899X/542/1/012008/pdf.

DOI: 10.1088/1757-899x/542/1/012008

[10] Ngoc-Pi Vu ., et al., Optimization of Grinding Parameters for Minimum Grinding Time When Grinding Tablet Punches by CBN Wheel on CNC Milling Machine. Appl. Sci. 2019, 9, 957;.

DOI: 10.3390/app9050957

[11] Jack Palmer et al., An experimental study of the effects of dressing parameters on the topography of grinding wheels during roller dressing. Journal of Manufacturing Processes. Volume 31, January 2018, Pages 348-355. https://doi.org/10.1016/j.jmapro.2017.11.025.

DOI: 10.1016/j.jmapro.2017.11.025

[12] Davide Matarazzoa et al., Prediction of dressing in grinding operation via neural networks. 10th CIRP Conference on Intelligent Computation in Manufacturing Engineering - CIRP ICME. Procedia CIRP 62 ( 2017) p.305 – 310.

DOI: 10.1016/j.procir.2017.03.043

[13] P. Puertoa et al., Evolution of surface roughness in grinding and its relationship with the dressing parameters and the radial wear. The Manufacturing Engineering Society International Conference, MESIC 2013. Procedia Engineering 63 (2013) p.174 – 182.

DOI: 10.1016/j.proeng.2013.08.181

[14] Chekole, N.; Deshpande, V. Review analysis on optimization of cylindrical grinding process parameters by using Taguchi technique. Ind. Eng. J. 2018, 14, 35–39.

DOI: 10.26488/iej.11.5.1066

[15] Hong-Seok Byun, Seok-Hee Lee. Design of a piston forging process using a hybrid Taguchi method and multiple criteria decision-making. Journal of Mechanical Science and Technology 31 (4) (2017).

DOI: 10.1007/s12206-017-0334-7