Surface roughness optimization in ball nose milling process of c45 steel using taguchi method

69 editor@iaeme.com International Journal of Mechanical Engineering and Technology (IJMET) Volume 10, Issue 05, May 2019, pp. 69-74, Article ID: IJMET_10_05_008 Available online at ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication SURFACE ROUGHNESS OPTIMIZATION IN BALL NOSE MILLING PROCESS OF C45 STEEL USING TAGUCHI METHOD Vu Nhu Nguyet 1 Faculty of Mechanical Engineering, Thai Nguyen University of Technology, 3/2 street, Tich Luong ward, Thai Nguyen Ci

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ity, Vietnam. Do Duc Trung Faculty of Mechanical Engineering, Hanoi University of Industry, No. 298, Cau Dien Street, Bac Tu Liem district, Hanoi, Vietnam Dinh Trong Hai Faculty of Mechanical Engineering, Thai Nguyen University of Technology, 3/2 street, Tich Luong ward, Thai Nguyen City, Vietnam. ABSTRACT In this paper, Taguchi method with L16 was used to experimental research in order to present the influence of cutting parameters and feed path on the surface roughness of workpiece when machining C45 by ball nose mill. The experimental result shows the influence of above parameters on surface roughness and the value of cutting conditions and feed path to minimize the surface roughness. Keywords: Milling, Ball Nose Mill, Surface roughness, C45 Steel, Taguchi Method. Cite this Article: Vu Nhu Nguyet, Do Duc Trung and Dinh Trong Hai, Surface Roughness Optimization In Ball Nose Milling Process of C45 Steel Using Taguchi Method, International Journal of Mechanical Engineering and Technology 10(5), 2019, pp. 69-74. 1. INTRODUCTION In mechanical engineering, milling is a common method that has high productivity. Milling process by ball nose mill can be used in many cases of surface contour that has a high accuracy and productivity. In those cases, surface roughness of workpiece has the significant influence on productivity and accuracy of milling process. A research on the influence of processing parameters on surface roughness proposed the determination of the reasonable value (or optimum value) of them to get minimum surface roughness. Basim A. Khidhir and Bashir Mohamed [1] proposed the influence of velocity speed, feed rate, depth of cut and nose radius on surface roughness when machining nickel based hastelloy – 276 by response surface Surface Roughness Optimization In Ball Nose Milling Process of C45 Steel Using Taguchi Method 70 editor@iaeme.com method, experimental matrix was Box-Behnken; Duong Xuan-Truong and Tran Minh-Duc [2] presented the influence of velocity speed, feed rate and depth of cut on surface roughness when machining Inconel 718 material by response surface method. In this work, experimental matrix was central composite design. Study on the influence of velocity speed, feed rate, depth of cut and machining time on surface roughness when milling Stainless Steel (316L) was done by Ali Abbar Khleif and Mostafa Adel Abdullah [3]; Taguchi method was applied to determine the influence of cutting speed, milling direction, insert number and cutting tool material on surface roughness when machining Inconel 718 material [4]; Muataz Hazza Faizi Al-Hazza et at. [5] proposed the influence of velocity speed, feed rate and depth of cut on surface roughness when machining Hardened Steel D2 by Taguchi method; Taguchi method was applied to determine the influence of type of coolant, cutting speed and feed rate on surface roughness when dry machining in milling process of alloy special steel (20MNCR5) EN1008:2008 [6]; Proposed the influence of velocity speed, feed rate and depth of cut on surface roughness using ball nose mill by Taguchi method when machining titanium alloy Ti- 6Al-4V [7] and when machining EN 31 steel using solid carbide tool [8], and so on. This paper presents the experimental research when machining C45 steel by ball nose mill. Taguchi method with 16 points in experimental matrix (L16) was used to study the influence of parameters on surface roughness of workpiece. The four input parameters include velocity speed, feed rate, depth of cut and feed path. Finally, this work shows the optimized value of above parameters for minimum value of surface roughness. 2. EXPERIMENTAL MILLING 2.1. Experimental system The C45 hardened steel (40÷42HRC) was used, and its chemical composition is shown in Table 1. The dimensions of the experimental sample are shown in Fig.1. Table 1 Chemical composition of C45 steel C(%) Si(%) Mn(%) P(%) S(%) Cr (%) 0.42 15 0.5 0.025 0.025 0.2 The P3202-XWM25 ball nose mill was used with the diameter 8, flutes 02, helix angle 15 0 , and rake angle -14 0 as shown in Fig. 2. Milling experiments were conducted on Mazak VCS530C, as shown in Fig. 3. Mitutoyo - S3000 surface roughness tester was used, as shown in Fig 4. Each component was measured in three times. a) Dimensions of experimental sample b) Experimental sample Figure 1 Experimental Component Vu Nhu Nguyet, Do Duc Trung and Dinh Trong Hai 71 editor@iaeme.com Figure 2 Ball nose mill Figure 3 Experimental machine-tool Figure 4 Mitutoyo - S3000 surface roughness tester 2.2. Design of experiment The Taguchi method with 16 runs was used. Four parameters are velocity speed vc, feed rate ft, depth of cut t and feed method Fm. Experimental matrix is shown in Table 2. Surface Roughness Optimization In Ball Nose Milling Process of C45 Steel Using Taguchi Method 72 editor@iaeme.com Table 2 Experimental design matrix Run v (m/min) f (mm/tooth) t (mm) Fm Ra (m) 1 80 0.1 0.16 zigzag 0.36 2 80 0.2 0.25 zig 0.33 3 80 0.3 0.35 zig with contour 0.36 4 80 0.4 0.45 Follow periphery 0.79 5 100 0.1 0.25 zig with contour 0.34 6 100 0.2 0.16 Follow periphery 0.47 7 100 0.3 0.45 zigzag 0.97 8 100 0.4 0.35 zig 0.67 9 150 0.1 0.35 Follow periphery 0.45 10 150 0.2 0.45 zig with contour 0.45 11 150 0.3 0.16 zig 0.24 12 150 0.4 0.25 zigzag 0.54 13 180 0.1 0.45 zig 0.27 14 180 0.2 0.35 zigzag 0.78 15 180 0.3 0.25 Follow periphery 0.77 16 180 0.4 0.16 zig with contour 0.16 3. RESULTS The surface roughness is taken by the average values of three consecutive measurements, as shown in Table 2. From results in Table 2, experimental data was analysed by Minitab 16. The results are shown in Table 3, Fig.5 and Fig.6. Table 3 Experimental data analysis Run v (m/min) f (mm/tooth) t (mm) Fm Ra (m) MEAN 1 80 0.1 0.16 zigzag 0.36 0.3607 2 80 0.2 0.25 zig 0.33 0.3300 3 80 0.3 0.35 zig with contour 0.36 0.3643 4 80 0.4 0.45 Follow periphery 0.79 0.7870 5 100 0.1 0.25 zig with contour 0.34 0.3377 6 100 0.2 0.16 Follow periphery 0.47 0.4733 7 100 0.3 0.45 zigzag 0.97 0.9730 8 100 0.4 0.35 zig 0.67 0.6697 9 150 0.1 0.35 Follow periphery 0.45 0.4493 10 150 0.2 0.45 zig with contour 0.45 0.4457 11 150 0.3 0.16 zig 0.24 0.2400 12 150 0.4 0.25 zigzag 0.54 0.5433 13 180 0.1 0.45 zig 0.27 0.2667 14 180 0.2 0.35 zigzag 0.78 0.7773 15 180 0.3 0.25 Follow periphery 0.77 0.7653 16 180 0.4 0.16 zig with contour 0.16 0.1600 Vu Nhu Nguyet, Do Duc Trung and Dinh Trong Hai 73 editor@iaeme.com Figure 5 Influence of parameters on surface roughness Figure 6 Main effect plot for S/N ratio Fig.5. shows that the feed path has the biggest influence on surface roughness, the following parameters are depth of cut, feed rate and velocity speed respectively. Fig.6. shows that the optimized value of velocity speed, feed rate, depth of cut are 150(m/min), 0.3(mm/tooth), 0.45(mm) respectively, and feed path is zigzag. This is optimization condition for minimum value of surface roughness. 4. CONCLUSION This paper presents the study on the influence of cutting parameters and feed path on the surface roughness when machining C45 steel by ball nose mill using Taguchi method. The influence of investigated parameters on the surface roughness was proposed. Also, this work is shown the value of above cutting parameter and feed path for minimizing the value of surface roughness. ACKNOWLEDGEMENTS The work described in this paper was supported by Ha Noi university of Industry (https://www.haui.edu.vn/vn) and Thai Nguyen university of Technology ( Surface Roughness Optimization In Ball Nose Milling Process of C45 Steel Using Taguchi Method 74 editor@iaeme.com REFEREENCES [1] Basim A. Khidhir and Bashir Mohamed, (2011), Analyzing the effect of cutting parameters on surface roughness and tool wear when machining nickel based hastelloy - 276, IOP Conf. Series: Materials Science and Engineering 17, doi:10.1088/1757- 899X/17/1/012043. [2] Duong Xuan-Truong and Tran Minh-Duc, (2013), Effect of cutting condition on tool wear and surface roughness during maching of Inconel 718, International Journal of Advanced Engineering Technology, pp.108-112. [3] Ali Abbar Khleif and Mostafa Adel Abdullah, (2016), Effect of Cutting Parameters on Wear and Surface Roughness of Stainless Steel (316L) Using Milling Process, Al-Nahrain University, College of Engineering Journal (NUCEJ) Vol.91 No.2, 6192 pp.286-292. [4] Ali Riza Motorcu, Abdil Kus, Rıdvan Arslan, Yücel Tekin, Rıdvan Ezentaş, (2013),Evaluation of tool life - tool wear in milling of inconel 718 superalloy and the investigation of effects of cutting parameters on surface roughness with Taguchi method, Tehnički vjesnik 20, 5, pp.765-774. [5] Muataz Hazza Faizi Al-Hazza, Nur Asmawiyah bt Ibrahim , Erry T. Y. Adesta, Ahsan Ali Khan and Atiah Bt. Abdullah Sidek, (2017), Surface Roughness Optimization Using Taguchi Method of High Speed End Milling For Hardened Steel D2, International Conference on Mechanical, Automotive and Aerospace Engineering, doi:10.1088/1757- 899X/184/1/012047. [6] M.Paranthaman, (2017), Optimization of Surface Roughness Using Taguchi Method for Dry Machining In Milling Process of Alloy Special Steel (20MNCR5) EN1008:2008, IOSR Journal of Mechanical and Civil Engineering, Volume 14, Issue 4 Ver. V (Jul. - Aug), pp.08-12. [7] W. Mersni, M. Boujelbene, S. Ben Salem, A-S. Alghamdi, (2018), Optimization of the surface roughness in ball end milling of titanium alloy Ti-6Al-4V using the Taguchi Method, 2nd International Conference on Materials Manufacturing and Design Engineering, Procedia Manufacturing 20, pp. 271-276. [8] Shadab anwar, Saleem uz zaman khan, Optimization of end milling parameters for improving surface roughness using Taguchi method, (2016), International Journal of Mechanical And Production Engineering, Volume- 4, Issue-8, pp.6-9.

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