SavedAdd your journal

Journals / Journal of Advances in Manufacturing Engineering / 2026 / Volume: 7 Issue: 1

Assessment of drilling kinematic configurations and their contribution to surface roughness formation in 40HM+QT steel

Mateusz Bronis(Kielce University of Technology)0000-0003-3639-0752
Mehmet Şükrü Adin(BATMAN UNIVERSITY)0000-0002-2307-9669
Pages
—
Publication Date
2026-07-01
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results show that spindle speed is the most influential parameter (46.27% contribution to Rt variability), followed by the kinematic system (34.45%) and feed per revolution (19.28%).

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The study investigates the influence of three different drilling kinematic systems on the surface roughness (Rt) of holes machined in quenched-and-tempered 40HM (AISI 4140) steel.
📊
Key Findings & Data:The spindle speed (n), feed per revolution (fn), and drilling kinematics were evaluated using a Taguchi L27 orthogonal array supported by ANOVA and response surface methodology (RSM).
💡
Conclusion & Impact:The results show that spindle speed is the most influential parameter (46.27% contribution to Rt variability), followed by the kinematic system (34.45%) and feed per revolution (19.28%).
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Kinematics · Surface roughness · ANOVA

Abstract

The study investigates the influence of three different drilling kinematic systems on the surface roughness (Rt) of holes machined in quenched-and-tempered 40HM (AISI 4140) steel. A full experimental campaign was carried out using a CNC machining center and solid carbide internal-coolant drills. The spindle speed (n), feed per revolution (fn), and drilling kinematics were evaluated using a Taguchi L27 orthogonal array supported by ANOVA and response surface methodology (RSM). The results show that spindle speed is the most influential parameter (46.27% contribution to Rt variability), followed by the kinematic system (34.45%) and feed per revolution (19.28%). The most favorable surface roughness was obtained for the first kinematic system, combining tool rotation with an additional axial oscillation. Higher spindle speeds and a feed of 0.14 mm/rev yielded the lowest Rt values across most configurations. The findings highlight the importance of selecting an appropriate kinematic system, demonstrating that non-standard drilling kinematics can significantly enhance hole quality in heat-treated steels.

🔖

Cite This Article

Bronis, M., Adin, M. Ş. (2026). Assessment of drilling kinematic configurations and their contribution to surface roughness formation in 40HM+QT steel. Journal of Advances in Manufacturing Engineering, Volume: 7 Issue: 1. https://ajindex.com/articles/1504980

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (34)

  1. Kowalska, N., Błasiak, S., Skrzyniarz, M., Szczygieł, P., Szot, W., & Rudnik, M. (2025). Evaluation of surface roughness reduction in TPU 95A samples using ferromagnetic liquid machining. Materials, 18, Article 4939. [CrossRef]
  2. Bronis, M., Miko, E., Nowakowski, L., & Bartoszuk, M. (2022). A study of the kinematics system in drilling Inconel 718 for improving hole quality in the aviation and space industries. Materials, 15, Article 5500. [CrossRef]
  3. Bronis, M., Miko, E., & Nowakowski, L. (2021). Influence of the kinematic system on the geometrical and dimensional accuracy of holes in drilling. Materials, 14, Article 4568. [CrossRef]
  4. Szot, W., Rudnik, M., Szczygieł, P., & Kowalska, N. (2025). Evaluation of tensile stress relaxation of selective laser sintering of PA2200 material using the Maxwell–Wiechert model. Acta Mechanica et Automatica, 19, 292–299. [CrossRef]
  5. Bronis, M., Krawczyk, B., & Legutko, S. (2024). Effect of choice of drilling kinematic system on cylindricity deviation, roundness deviation, diameter error and surface roughness of holes in brass alloy. Processes, 12, Article 220. [CrossRef]
  6. Sutopo, Wijanarka, B. S., Wibowo, A. E., Arifin, A., & Wu, Y.-R. (2025). Cutting performance of various CNC drilling cycles at diverse cutting speeds concerning hole dimension error, surface roughness, and cutting time. International Journal of Machining and Machinability of Materials, 27, 224–250. [CrossRef] [7] Nowakowski, L., Rolek, J., Błasiak, S., & Skrzyniarz, M. (2024). The influence of insert mounting errors on the surface roughness of 1.0503 steel in face milling. Materials, 17, Article 6144. [CrossRef]
  7. Nowakowski, L., Bartoszuk, M., Skrzyniarz, M., Błasiak, S., & Vasileva, D. (2022). Influence of the milling conditions of aluminium alloy 2017A on the surface roughness. Materials, 15, Article 3626. [CrossRef]
  8. Nowakowski, L., Bronis, M., Błasiak, S., & Skrzyniarz, M. (2025). A method for determining the minimum thickness of the cut layer in precision milling. Materials, 18, Article 189. [CrossRef]
  9. Özcan, D., Özsoy, N., Turgut, Y. Z., & Özsoy, M. (2025). Effects of tool geometry on cutting performance in CW511L brass drilling. Materials Testing, 68(1), 96–111. [CrossRef] [11] Biswas, S., Saikat, C. S., Sristi, N. A., & Zaman, P. B. (2025). A review of the role of modeling and optimization methods in machining Ni–Cr super-alloys. Journal of Manufacturing and Materials Processing, 9, Article 289. [CrossRef]
  10. Bronis, M., Miko, E., & Nowakowski, L. (2021). Analyzing the effects of the kinematic system on the quality of holes drilled in 42CrMo4 + QT steel. Materials, 14, Article 4046. [CrossRef]
  11. Balaji, M., Venkata Rao, K., Mohan Rao, N., & Murthy, B. S. N. (2018). Optimization of drilling parameters for drilling of Ti-6Al-4V based on surface roughness, flank wear and drill vibration. Measurement, 114, 332–339. [CrossRef]
  12. Kumar, D., & Sing, K. K. (2017). Experimental analysis of delamination, thrust force and surface roughness on drilling of glass fibre reinforced polymer composites material using different drills. Materials Today: Proceedings, 4, 7618–7627. [CrossRef]
  13. Kilickap, E., Huseyinoglu, M., & Yardimeden, A. (2011). Optimization of drilling parameters on surface roughness in drilling of AISI 1045 using response surface methodology and genetic algorithm. International Journal of Advanced Manufacturing Technology, 52, 79–88. [CrossRef]
  14. Aized, T., & Amjad, M. (2013). Quality improvement of deep-hole drilling process of AISI D2. International Journal of Advanced Manufacturing Technology, 69, 2493–2503. [CrossRef]
  15. Ravindranath, V. M., Shiva Shankar, G. S., Basavarajappa, S., & Suresh, R. (2017). Optimization of Al/B4C and Al/B4C/Gr MMC drilling using Taguchi approach. Materials Today: Proceedings, 4, 11181–11187. [CrossRef]
  16. Vipin, Kant, S., & Jawalkar, C. S. (2018). Parametric modeling in drilling of die steels using Taguchi method based response surface analysis. Materials Today: Proceedings, 5, 4531–4540. [CrossRef]
  17. Aamir, M., Tolouei-Rad, M., Giasin, K., & Vafadar, A. (2020). Machinability of Al2024, Al6061, and Al5083 alloys using multi-hole simultaneous drilling approach. Journal of Materials Research and Technology, 9, 10991–11002. [CrossRef]
  18. Angelone, R., Caggiano, A., Improta, I., Nele, L., & Teti, R. (2020). Roughness of composite materials: Characterization of hole quality in drilling of Al/CFRP stacks. Procedia CIRP, 88, 473–478. [CrossRef]
  19. Khanna, N., Agrawal, C., Gupta, M. K., & Song, Q. (2020). Tool wear and hole quality evaluation in cryogenic drilling of Inconel 718 superalloy. Tribology International, 143, Article 106084. [CrossRef]
  20. Biermann, D., Heilmann, M., & Kirschner, M. (2011). Analysis of the influence of tool geometry on surface integrity in single-lip deep hole drilling with small diameters. Procedia Engineering, 19, 16–21. [CrossRef]
  21. Wegert, R., Guski, V., Schmauder, S., & Möhring, H.-C. (2020). Effects on surface and peripheral zone during single lip deep hole drilling. Procedia CIRP, 87, 113–118. [CrossRef]
  22. Siddique, M. Z., Faraz, M. I., Butt, S. I., Khan, R., Petru, J., Jaffery, S. H. I., Khan, M. A., & Tahir, A. M. (2023). Parametric analysis of tool wear, surface roughness and energy consumption during turning of Inconel 718 under dry, wet and MQL conditions. Machines, 11, Article 1008. [CrossRef]
  23. Gowda, B. M. U., Ravindra, H. V., Prakash, G. V. N., Nishanth, P., & Ugrasen, G. (2015). Optimization of process parameters in drilling of epoxy Si3N4 composite material. Materials Today: Proceedings, 2, 2852–2861. [CrossRef]
  24. Prakash, S., Mercy, J. L., Salugu, M. K., & Vineeth, K. S. M. (2015). Optimization of drilling characteristics using grey relational analysis (GRA) in medium density fiber board (MDF). Materials Today: Proceedings, 2, 1541–1551. [CrossRef]
  25. Sharman, A. R. C., Amarasinghe, A., & Ridgway, K. (2008). Tool life and surface integrity aspects when drilling and hole making in Inconel 718. Journal of Materials Processing Technology, 200, 424–432. [CrossRef]
  26. Neo, D. W. K., Liu, K., & Kumar, A. S. (2020). High throughput deep-hole drilling of Inconel 718 using PCBN gun drill. Journal of Manufacturing Processes, 57, 302–311. [CrossRef]
  27. Karabulut, Y., & Kaynak, Y. (2020). Drilling process and resulting surface properties of Inconel 718 alloy fabricated by selective laser melting additive manufacturing. Procedia CIRP, 87, 355–359. [CrossRef]
  28. Shah, P., Bhat, P., & Khanna, N. (2021). Life cycle assessment of drilling Inconel 718 using cryogenic cutting fluids while considering sustainability parameters. Sustainable Energy Technologies and Assessments, 43, Article 100950. [CrossRef]
  29. Dedeakayoğulları, H., Kaçal, A., & Keser, K. (2022). Modeling and prediction of surface roughness at the drilling of SLM-Ti6Al4V parts manufactured with pre-hole with optimized ANN and ANFIS. Measurement, 203, Article 112029. [CrossRef]
  30. Dedeakayoğulları, H., & Kaçal, A. (2022). Experimental investigation of hole quality in drilling of additive manufacturing Ti6Al4V parts produced by hole features. Journal of Manufacturing Processes, 79, 745–758. [CrossRef]
  31. Güldibi, A., Köklü, U., & Koçar, O., Kocaman, E., & Morkavuk, S. (2024). The effects of aging process after solution heat treatment on drilling machinability of Corrax steel. Experimental Techniques, 48, 239–257. [CrossRef]
  32. Baysal, E., Koçar, O., & Kahrıman, F., & Köklü, U. (2025). Investigation of microstructure, hardness, corrosion and machinability properties of commercially pure aluminum alloyed with rare-earth elements. International Journal of Metalcasting, Preprint. doi: 10.1007/s40962-025-01655-y [CrossRef]
  33. Callister, W. D., & Rethwisch, D. G. (2014). Materials science and engineering: An introduction (9th ed.). Wiley.
  34. Nguyen, V. H., Le, T. T., Nguyen, A. T., Hoang, X. T., Nguyen, N. T., & Nguyen, N. K. (2025). Optimization of milling conditions for AISI 4140 steel using an integrated machine learning–multi objective optimization–multi criteria decision making framework. Measurement, 242, Article 115837. [CrossRef]