Experimental Evaluation of Surface Roughness and Cutting Forces in Turning of 1.2379 Tool Steel: Role of Cutting Parameters and Tool Nose Radius

Öz

Machining performance in turning is governed by both cutting conditions and tool geometry. This study focuses on how cutting parameters and tool nose radius influence surface roughness and cutting forces during the machining of 1.2379 (X153CrMoV12) cold work tool steel. Two tool cutting-edge nose radius values of 0.2 mm and 0.8 mm were considered under different combinations of feed rate, cutting speed, and depth of cut. Surface roughness and cutting force data obtained from the experiments were analyzed using statistical and graphical approaches, including response surface evaluation and variance analysis. The results showed that feed rate plays a leading role in determining surface roughness, while cutting speed has a secondary influence and depth of cut remains limited in effect. Regarding the cutting forces, both feed rate and depth of cut contributed significantly, whereas cutting speed had a relatively minor impact. Similar trends were observed for both tool nose radius. Although a larger radius resulted in slightly higher cutting forces, its overall influence on machining performance was not pronounced. The findings indicate that machining behavior is predominantly controlled by cutting parameters rather than tool geometry, and appropriate parameter selection is essential for achieving improved surface quality and efficient cutting performance.

Anahtar Kelimeler

• Turning
• Cutting force
• Surface roughness
• ANOVA

1.2379 Takım Çeliğinin Tornalanmasında Yüzey Pürüzlülüğü ve Kesme Kuvvetlerinin Deneysel Değerlendirilmesi: Kesme Parametreleri ve Takım Uç Radyüsünün Rolü

Öz

Tornalama işlemlerinde kesme parametreleri ve takım geometrisi işleme performansını belirlemede kritik bir role sahiptir. Bu çalışmada 1.2379 (X153CrMoV12) soğuk işleme takım çeliğin tornalanması sırasında kesme parametreleri ve takım ucu yarıçapının yüzey pürüzlülüğü ve kesme kuvvetleri sonuçları deneysel olarak incelenmiştir. Deneyler çeşitli işleme koşulları altında iki farklı takım ucu yarıçapı (0,2 mm ve 0,8 mm) kullanılarak gerçekleştirilmiştir. Her takım ucu yarıçapı için ilerleme miktarı, kesme hızı ve kesme derinliğinin farklı kombinasyonları dikkate alınarak toplam sekiz deney yapılmıştır. Elde edilen yüzey pürüzlülüğü ve kesme kuvveti değerleri işleme parametrelerinin etkisini değerlendirmek için ana etki grafikleri, yanıt yüzey grafikleri ve varyans analizi (ANOVA) kullanılarak analiz edilmiştir. Sonuçlar ilerleme hızının yüzey pürüzlülüğünü etkileyen en etkili parametre olduğunu kesme hızının ikincil bir etkiye sahip olduğunu ve kesme derinliğinin sınırlı bir etkiye sahip olduğunu göstermiştir. Kesme kuvvetleri açısından hem ilerleme hızı hem de kesme derinliği kesme kuvvetlerini önemli ölçüde artırırken kesme hızı nispeten küçük bir etki göstermiştir. Takım ucu yarıçapları karşılaştırıldığında hem yüzey pürüzlülüğü hem de kesme kuvvetleri için benzer eğilimler gözlemlenmiştir. Daha büyük takım ucu yarıçapı ile biraz daha yüksek kesme kuvvetleri elde edilmesine rağmen takım ucu yarıçapının işleme performansı üzerindeki genel etkisinin sınırlı olduğu bulunmuştur. Bu bulgular işleme performansının öncelikle takım geometrisinden ziyade kesme parametreleri tarafından yönetildiğini ve optimum yüzey kalitesi ve kesme verimliliği elde etmek için uygun ilerleme hızı ve kesme hızının seçilmesinin şart olduğunu göstermektedir.

Anahtar Kelimeler

• Tornalama
• Kesme kuvveti
• Yüzey pürüzlülüğü
• ANOVA

Kaynakça

1. [1] N. Villarrazo, Á. Sáinz de la Maza, S. Caneda, L. Bai, O. Pereira, L.N. López de Lacalle, Effect of tool orientation on surface roughness and dimensional accuracy in ball end milling of thin-walled blades, Int. J. Adv. Manuf. Technol. 136 (2025) 383–395. https://doi.org/10.1007/s00170-024-14523-6.
2. [2] S.K. Chaubey, K. Gupta, A Review on Fabrication of Cylindrical and Rotating Parts by Thermoelectric-Erosion Based Turning Processes, Metals (Basel). 12 (2022) 1227. https://doi.org/10.3390/met12071227.
3. [3] Q. Xiao, C. Li, Y. Tang, L. Li, Meta-Reinforcement Learning of Machining Parameters for Energy-Efficient Process Control of Flexible Turning Operations, IEEE Trans. Autom. Sci. Eng. 18 (2021) 5–18. https://doi.org/10.1109/TASE.2019.2924444.
4. [4] A. Aslan, Optimization and analysis of process parameters for flank wear, cutting forces and vibration in turning of AISI 5140: A comprehensive study, Measurement 163 (2020) 107959. https://doi.org/10.1016/j.measurement.2020.107959.
5. [5] N. Aydın, H. Yurtkuran, M. Kuntoğlu, R. Binali, Statistical and experimental analysis of machining parameters and tool radius in turning of low carbon steels, Int. J. Adv. Nat.Sci. Eng. Res. 9 (2025) 92–100. https://asproceeding.com/index.php/ijanser/article/view/2836.
6. [6] A. la Monaca, J.W. Murray, Z. Liao, A. Speidel, J.A. Robles-Linares, D.A. Axinte, M.C. Hardy, A.T. Clare, Surface integrity in metal machining - Part II: Functional performance, Int. J. Mach. Tools Manuf. 164 (2021) 103718. https://doi.org/https://doi.org/10.1016/j.ijmachtools.2021.103718.
7. [7] M. Kuntoğlu, A. Aslan, H. Sağlam, D.Y. Pimenov, K. Giasin, T. Mikolajczyk, Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140, Sensors 20 (2020) 4377. https://doi.org/10.3390/s20164377.
8. [8] B. Toubhans, G. Fromentin, F. Viprey, H. Karaouni, T. Dorlin, Machinability of inconel 718 during turning: Cutting force model considering tool wear, influence on surface integrity, J. Mater. Process. Technol. 285 (2020) 116809. https://doi.org/https://doi.org/10.1016/j.jmatprotec.2020.116809.

9. [9] H. Demirpolat, R. Binali, A.D. Patange, S.S. Pardeshi, S. Gnanasekaran, Comparison of Tool Wear, Surface Roughness, Cutting Forces, Tool Tip Temperature, and Chip Shape during Sustainable Turning of Bearing Steel, Materials (Basel). 16 (2023). https://doi.org/10.3390/ma16124408.
10. [10] Q.N. The Ho, T.T. Do, P.S. Minh, Studying the Factors Affecting Tool Vibration and Surface Quality during Turning through 3D Cutting Simulation and Machine Learning Model, Micromachines 14 (2023) 1025. https://doi.org/10.3390/mi14051025.
11. [11] D.I. Lalwani, N.K. Mehta, P.K. Jain, Experimental investigations of cutting parameters influence on cutting forces and surface roughness in finish hard turning of MDN250 steel, J. Mater. Process. Technol. 206 (2008) 167–179. https://doi.org/https://doi.org/10.1016/j.jmatprotec.2007.12.018.
12. [12] M.E. Korkmaz, N. Yaşar, M. Günay, Numerical and experimental investigation of cutting forces in turning of Nimonic 80A superalloy, Eng. Sci. Technol. an Int. J. 23 (2020) 664–673. https://doi.org/https://doi.org/10.1016/j.jestch.2020.02.001.
13. [13] M.E. Korkmaz, M. Günay, Finite Element Modelling of Cutting Forces and Power Consumption in Turning of AISI 420 Martensitic Stainless Steel, Arab. J. Sci. Eng. 43 (2018) 4863–4870. https://doi.org/10.1007/s13369-018-3204-4.
14. [14] C.J. Rao, D.N. Rao, P. Srihari, Influence of Cutting Parameters on Cutting Force and Surface Finish in Turning Operation, Procedia Eng. 64 (2013) 1405–1415. https://doi.org/https://doi.org/10.1016/j.proeng.2013.09.222.
15. [15] T. Çetin, K. Kaya, R. Binali, H. Gündoğmuş, Finish turning of toolox 33 to improve machining parameters with different nose radius tools, Eur. Mech. Sci. 9 (2025) 234–245. https://doi.org/10.26701/ems.1724270.
16. [16] S. Dutta, S.K.R. Narala, Effect of tool nose radius in turning of novel Mg alloy, Mater. Today Proc. 38 (2021) 2675–2679. https://doi.org/https://doi.org/10.1016/j.matpr.2020.08.334.
17. [17] A. Tzotzis, C. García-Hernández, J.-L. Huertas-Talón, P. Kyratsis, Influence of the Nose Radius on the Machining Forces Induced during AISI-4140 Hard Turning: A CAD-Based and 3D FEM Approach, Micromachines 11 (2020) 798. https://doi.org/10.3390/mi11090798.
18. [18] H. Demir, M. Günay, M.E. Korkmaz, R. Çakıroğlu, Optimization of Cutting Parameters in Hard Turning of AISI H10A Steel under Minimum Quantity Lubrication, Eur. J. Eng. Nat. Sci. 3 (2019) 157–164. https://dergipark.org.tr/en/pub/ejens/article/371766.
19. [19] M.S. Surya, Optimization of machining parameters while turning AISI316 stainless steel using response surface methodology, Sci. Rep. 14 (2024) 30083. https://doi.org/10.1038/s41598-024-78657-z.
20. [20] E. Franczyk, W. Zębala, Impact of Cutting Data on Cutting Forces, Surface Roughness, and Chip Type in Order to Improve the Tool Operation Reliability in Sintered Cobalt Turning., Mater. (Basel, Switzerland) 17 (2024). https://doi.org/10.3390/ma17102210.
21. [21] B.L. Mahdi, A.H. Ali, H.K. Hussein, O.F. Abdulateef, The Influence of Cutting Parameters on the Surface Hardness in Turning of 6061 Aluminum Alloy, Eng. Technol. Appl. Sci. Res. 14 (2024) 17118–17124. https://doi.org/10.48084/etasr.8261.
22. [22] N. Praveen, S.K. N G, S. R, C.D. Prasad, H. Soni, V. G, M. Prasad, S.K. T C, U.S. Mallik, A.A. Aden, Effect of CNC Turning Parameters on MRR, Cutting Force and Surface Roughness for Ternary Shape Memory Alloys (SMAs), Results Eng. 26 (2025) 104876. https://doi.org/https://doi.org/10.1016/j.rineng.2025.104876.
23. [23] H.T. Thuong, N.H. Tan, H.Q. Khanh, N. Van Cuong, B. Van Huu, Investigating effects of cutting parameters on surface roughness machined by turning of C45 steel based on Taguchi methodology and ANOVA, CTU J. Innov. Sustain. Dev. 17 (2025) 53–58. https://doi.org/10.22144/ctujoisd.2025.007.
24. [24] M. Boy, İ. Çiftçi, M. Günay, F. Ozhan, Application of the Taguchi method to optimize the cutting conditions in hard turning of a ring bore, Mater. Tehnol. 49 (2015) 765–772. https://doi.org/10.17222/mit.2014.246.
25. [25] T. He, W. Chen, Z. Liu, Z. Gong, S. Du, Y. Zhang, The Impact of Surface Roughness on the Friction and Wear Performance of GCr15 Bearing Steel, Lubricants 13 (2025) 187. https://doi.org/10.3390/lubricants13040187.
26. [26] K. Bouacha, M.A. Yallese, T. Mabrouki, J.-F. Rigal, Statistical analysis of surface roughness and cutting forces using response surface methodology in hard turning of AISI 52100 bearing steel with CBN tool, Int. J. Refract. Met. Hard Mater. 28 (2010) 349–361. https://doi.org/https://doi.org/10.1016/j.ijrmhm.2009.11.011.
27. [27] M. ÖZDEMİR, Yüzey pürüzlülüğü üzerinde kesme parametrelerinin etki oranlarının Yüzey Yanıt Yöntemi kullanarak Analizi, Gazi Üniversitesi Fen Bilim. Derg. Part C Tasarım ve Teknol. 7 (2019) 639–648. https://doi.org/10.29109/gujsc.595722.
28. [28] E. Salur, N. Okcu, M.E. Korkmaz, K. Kaya, R. Binali, S.B. Çetinkal, Effect of Cooling/Lubrication Conditions on Machining Performance: An Experimental Investigation of 1040 Steel Under Dry, MQL, and Nano-MQL Environments, Materials (Basel). 18 (2025) 4063. https://doi.org/10.3390/ma18174063.
29. [29] K.Y. Çamlı, R. Demirsöz, M. Boy, M.E. Korkmaz, N. Yaşar, K. Giasin, D.Y. Pimenov, Performance of MQL and Nano-MQL Lubrication in Machining ER7 Steel for Train Wheel Applications, Lubricants 10 (2022) 48. https://doi.org/10.3390/lubricants10040048.
30. [30] R. Binali, M.E. Korkmaz, M.T. Özdemir, M. Günay, A Holistic Perspective on Sustainable Machining of Al6082: Synergistic Effects of Nano-Enhanced Bio-Lubricants, Machines 13 (2025) 293. https://doi.org/10.3390/machines13040293.
31. [31] İ. Asiltürk, H. Akkuş, Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method, Measurement 44 (2011) 1697–1704. https://doi.org/https://doi.org/10.1016/j.measurement.2011.07.003.
32. [32] S. Mane, R.B. Patil, A. Roy, P. Shah, R. Sekhar, Analysis of the Surface Quality Characteristics in Hard Turning Under a Minimal Cutting Fluid Environment, Appl. Mech. 6 (2025) 5. https://doi.org/10.3390/applmech6010005.
33. [33] Sweta Baruah, James B Mann, Srinivasan Chandrasekar, Balkrishna C Rao, On the effects of tool nose radius in alleviating parasitic mechanisms for cutting of aluminum alloy, Adv. Mech. Eng. 17 (2025) 16878132251328056. https://doi.org/10.1177/16878132251328057.
34. [34] E. Kuram, N. Ucuncu, Toolox 44 Çeliğinin Tornalanmasında Kesme Hızının, İlerlemenin ve Kesici Uç Burun Radyüsünün Takım Aşınmasına ve Yüzey Pürüzlülüğüne Etkileri, Gazi Üniversitesi Fen Bilim. Derg. Part C Tasarım ve Teknol. 12 (2024) 1006–1017. https://doi.org/10.29109/gujsc.1530456.
35. [35] X. Jing, R. Lv, Y. Chen, Y. Tian, H. Li, Modelling and experimental analysis of the effects of run out, minimum chip thickness and elastic recovery on the cutting force in micro-end-milling, Int. J. Mech. Sci. 176 (2020) 105540. https://doi.org/https://doi.org/10.1016/j.ijmecsci.2020.105540.
36. [36] H. Yurtkuran, M. Günay, Analyzing the Effects of Cutting Parameters on Machinability Criteria in Milling of 17-4PH Stainless Steel under Dry Environment TT - 17-4PH Paslanmaz Çeliğin Kuru Ortamda Frezelenmesinde Kesme Parametrelerinin İşlenebilirlik Kriterlerine Etkilerinin Ara, Manuf. Technol. Appl. 3 (2022) 8–19. https://doi.org/10.52795/mateca.1181213.
37. [37] R. BİNALİ, Parametric Optimization of Cutting Force and Temperature in Finite Element Milling of AISI P20 Steel, J. Mater. Mechatronics A 4 (2023) 244–256. https://doi.org/10.55546/jmm.1257453.
38. [38] N. YAŞAR, Sertleştirilmiş X40CrMoV5-1 Çeliğinin Tornalanmasında Kesme Kuvvetinin Deneysel ve Nümerik Olarak İncelenmesi, Gazi Üniversitesi Fen Bilim. Derg. Part C Tasarım ve Teknol. 6 (2018) 765–773. https://doi.org/10.29109/gujsc.385823.
39. [39] M. Reznicek, C. Horava, M. Ovsik, Evaluation of Cutting Forces and Roughness During Machining of Spherical Surfaces with Barrel Cutters, Materials (Basel). 18 (2025) 3630. https://doi.org/10.3390/ma18153630.
40. [40] M.E. Korkmaz, M.K. Gupta, Z. Li, G.M. Krolczyk, M. Kuntoğlu, R. Binali, N. Yaşar, D.Y. Pimenov, Indirect monitoring of machining characteristics via advanced sensor systems: a critical review, Springer London, 2022. https://doi.org/10.1007/s00170-022-09286-x.