Selected Problems of Effectiveness and Quality in the Dry Rough Milling of Magnesium Alloy AZ91D Using End Mills with Different Helix Angles
DOI:
https://doi.org/10.24425/mper.2025.156148Abstract
From the point of view of production and manufacturing processes, issues related to surface quality and machining efficiency are very important. This paper presents the results of a study investigating selected problems of quality and efficiency in dry rough milling. Roughness parameters 2D and 3D were analysed. Additionally, 3D surface topography maps and Abbott– Firestone curves were generated. Carbide end mills with different helix angles were used in the study. Experiments were conducted on AZ91D magnesium alloy specimens. The machining process was conducted using high-speed machining parameters. The results showed that the surface roughness of the AZ91D alloy depended to a great extent on the tool geometry and applied machining parameters. Moreover, ANOVA statistical analysis and post-hoc tests (Tukey) were performed to assess the differences between individual groups of the specimens. Additionally, an artificial neural network (ANN) model was developed to predict the Ra parameter, and the results demonstrated its high predictive accuracy (R = 0.966).References
Adhikari, R., Bolar, G., Shanmugam, R., & Koklu, U. (2023). Machinability and surface integrity investigation during helical hole milling in AZ31 magnesium alloy. International Journal of Lightweight Materials and Manufacture, 6 (2), 149–164. DOI: 10.1016/J.IJLMM.2022.09.006
Ahmed, F., Ahmad, F., Abbassi, F., Kumaran, S.T., & Mabrouki, T. (2023). Investigation of machining quality indicators and effect of tool geometry parameters during the machining of difficult-tomachine metal. Results in Materials, 20, 100487. DOI: 10.1016/J.RINMA.2023.100487
Bari, P., Kilic, Z.M., & Law, M. (2023). Rapid stability analysis of variable pitch and helix end mills using a non-iterative multi-frequency solution. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 237 (13), 2109–2118.
Biruk-Urban, K., Józwik, J., & Bere, P. (2022). Cutting Forces and 3D Surface Analysis of CFRP Milling. Advances in Science and Technology. Research Journal, 16 (2), 206–215. DOI: 10.12913/22998624/147338
Chen, Y., Sun, R., Gao, Y., & Leopold, J. (2017). A nested-ANN prediction model for surface roughness considering the effects of cutting forces and tool vibrations. Measurement, 98, 25–34. DOI: 10.1016/J.MEASUREMENT.2016.11.027
Dijmărescu, M.R., Abaza, B.F., Voiculescu, I., Dijmărescu, M.C., & Ciocan, I. (2021). Surface Roughness Analysis and Prediction with an Artificial Neural Network Model for Dry Milling of Co–Cr Biomedical Alloys. Materials, 14 (21), 6361. DOI: 10.3390/MA14216361
El-Shenawy, E.H., & Farahat, A.I.Z. (2023). Surface quality and dry sliding wear behavior of AZ61Mg alloy using Abbott firestone technique. Scientific Reports 2023, 13 (1), 1–18. DOI: 10.1038/s41598-023-39413-x
Ercetin, A., Aslantaş, K., Özgün, Ö., Perçin, M., &Chandrashekarappa, M.P.G. (2023). Optimization of Machining Parameters to Minimize Cutting Forces and Surface Roughness in Micro-Milling of Mg13Sn Alloy. Micromachines, 14 (8), 1590. DOI: 10.3390/MI14081590
Gziut, O., Kuczmaszewski, J., & Zagórski, I. (2015). Surface quality assessment following high performance cutting of AZ91HP magnesium alloy. Management and Production Engineering Review, 6 (1), 4–9. DOI: 10.1515/MPER-2015-0001
Hu, X., Qiao, H., Yang, M., & Zhang, Y. (2022). Research on Milling Characteristics of Titanium Alloy TC4 with Variable Helical End Milling Cutter. Machines, 10 (7), 537. DOI: 10.3390/MACHINES10070537
Jouini, N.;, Ruslan, M.;, Ghani, J. A.;, Haron, C., Murad, M.N., Jouini, N., Shahfizal, M., Ruslan, M., Ghani, J.A., & Hassan, C. (2023). Sustainable High-Speed Milling of Magnesium Alloy AZ91D in Dry and Cryogenic Conditions. Sustainability, 15 (4), 3760. DOI: 10.3390/SU15043760
Kanan, M., Zahoor, S., Habib, M.S., Ehsan, S., Rehman, M., Shahzaib, M., Khan, S.A., Ali, H., Abusaq, Z., & Hamdan, A. (2023). Analysis of Carbon Footprints and Surface Quality in Green Cutting Environments for the Milling of AZ31 Magnesium Alloy. Sustainability, 15 (7), 6301. DOI: 10.3390/SU15076301
Karmiris-Obratański, P., Karkalos, N.E., Kudelski, R., & Markopoulos, A. P. (2022). Experimental study on the effect of the cooling method on surface topography and workpiece integrity during trochoidal end milling of Incoloy 800. Tribology International, 176, 107899. DOI: 10.1016/J.TRIBOINT.2022.107899
Kaviarasan, V., Venkatesan, R., & Natarajan, E. (2019). Prediction of surface quality and optimization of process parameters in drilling of Delrin using neural network. Progress in Rubber, Plastics and Recycling Technology, 35 (3), 149-169. DOI: 10.1177/1477760619855078
Khawaja, A.H., Jahanzaib, M., &Cheema, T.A. (2020). High-speed machining parametric optimization of 15CDV6 HSLA steel under minimum quantity and flood lubrication. Advances in Production Engineering And Management, 15 (4), 403–415. DOI: 10.14743/APEM2020.4.374
Kramar, D., & Cica, D.J. (2021). Modeling and optimization of finish diamond turning of spherical surfaces based on response surface methodology and cuckoo search algorithm. Advances in Production Engineering And Management, 16 (3), 326-334. DOI: 10.14743/APEM2021.3.403
Krzyzak, A., Kosicka, E., Borowiec, M., & Szczepaniak, R. (2020). Selected Tribological Properties and Vibrations in the Base Resonance Zone of the Polymer Composite Used in the Aviation Industry. Materials, 13 (6), 1364. DOI: 10.3390/MA13061364
Kuczmaszewski, J., Pieśko, P., & Zawada-Michałowska, M. (2016). Surface roughness of thin-walled components made of aluminium alloy EN AW-2024 following different milling strategies. Advances in Science and Technology. Research Journal, 10 (30), 150–158. DOI: 10.12913/22998624/62515
Kulisz, M., Zagórski, I., & Józwik, J. (2022a). 2D Geometric Surface Structure ANN Modeling after Milling of the AZ91D Magnesium Alloy. Advances in Science and Technology. Research Journal, 16 (2), 131–140. DOI: 10.12913/22998624/146765
Kulisz, M., Zagórski, I., Józwik, J., & Korpysa, J. (2022b). Research, Modelling and Prediction of the Influence of Technological Parameters on the Selected 3D Roughness Parameters, as Well as Temperature, Shape and Geometry of Chips in Milling AZ91D Alloy. Materials, 15 (12), 4277. DOI: 10.3390/MA15124277
Kumar, R., Katyal, P., & Kumar, K. (2023). Effect of End Milling Process Parameters and Corrosion Behaviour of ZE41A Magnesium Alloy using Taguchi Based GRA. Biointerface Research in Applied Chemistry, 13 (3), 214. DOI: 10.33263/BRIAC133.214
Lisowicz, J., Habrat, W., & Krupa, K. (2022). Influence of Minimum Quantity Lubrication Using VegetableBased Cutting Fluids on Surface Topography and Cutting Forces in Finish Turning of Ti-6Al-4V. Advances in Science and Technology. Research Journal, 16 (1), 95–103. DOI: 10.12913/22998624/143289
Marakini, V., Pai, S.P., Bhat, U.K., Thakur, D.S., & Achar, B.P. (2022). High-speed face milling of AZ91 Mg alloy: Surface integrity investigations. International Journal of Lightweight Materials and Manufacture, 5 (4), 528–542. DOI: 10.1016/J.IJLMM. 2022.06.006
Matuszak, J. (2023). Analysis of Geometric Surface Structure and Surface Layer Microhardness of Ti6Al4V Titanium Alloy after Vibratory Shot Peening. Materials, 16 (21), 6983. DOI: 10.3390/MA16216983
Matuszak, J., Kłonica, M., Zagórski, I. (2019). Effect of brushing conditions on axial forces in ceramic brush surface treatment. 2019 IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2019 – Proceedings, 2019, 644–648, 8869605
Niemczewska-Wójcik, M., & Madej, M. (2023). Surface Topography and Tribological Properties of Cutting Tool Coatings. Advances in Science and Technology. Research Journal, 17 (6), 39–48. DOI: 10.12913/22998624/173214
Sangwan, K.S., Saxena, S., & Kant, G. (2015). Optimization of Machining Parameters to Minimize Surface Roughness using Integrated ANN-GA Approach. Procedia CIRP, 29, 305–310. DOI: 10.1016/J.PROCIR. 2015.02.002
Savkovic, B., Kovac, P., Rodic, D., Strbac, B., & Klancnik, S. (2020). Comparison of artificial neural network, fuzzy logic and genetic algorithm for cutting temperature and surface roughness prediction during the face milling process. Advances in Production Engineering And Management, 15 (2), 137–150. DOI: 10.14743/APEM2020.2.354
Sur, G., Motorcu, A.R., &Nohutçu, S. (2022). Single and multi-objective optimization for cutting force and surface roughness in peripheral milling of Ti6Al4V using fixed and variable helix angle tools. Journal of Manufacturing Processes, 80, 529–545. DOI: 10.1016/J.JMAPRO.2022.06.016
Tomov, M., Gecevska, V., &Vasileska, E. (2022). Modelling of multiple surface roughness parameters during hard turning: A comparative study between the kinematical-geometrical copying approach and the design of experiments method (DOE). Advances in Production Engineering And Management, 17 (1), 75–88. DOI: 10.14743/APEM2022.1.422
Varatharajulu, M., Duraiselvam, M., Krishna Pradeep, G.V., & Jagadeesh, B. (2023). Tool temperature thermographic study on end milling magnesium AZ31 using carbide tool. Materials Chemistry and Physics, 295, 127077. DOI: 10.1016/J.MATCHEMPHYS.2022.127077
Vukelic, D., Simunovic, K., Kanovic, Z., Saric, T., Doroslovacki, K., Prica, M., & Simunovic, G. (2022). Modelling surface roughness in finish turning as a function of cutting tool geometry using the response surface method, Gaussian process regression and decision tree regression. Advances in Production Engineering And Management, 17(3), 367–380. DOI: 10.14743/APEM2022.3.442
Wang, C., Chen, C., Huang, Z., Zhao, J., & Yang, E. (2023). Influence of milling parameters on machining performances and surface quality of ZK61M magnesium alloy. International Journal of Advanced Manufacturing Technology, 128 (11–12), 4777–4789. DOI: 10.1007/S00170-023-12241-Z/FIGURES/14
Xue, K., Chen, P., Liu, W., Zou, B., Li, L., Chen, W., Wang, X., & Xu, Z. (2023). Geometric Structures for Sialon Ceramic Solid End Mills and Its Performance in High-Speed Milling of Nickel-Based Superalloys. Coatings, 13 (9), 1483. DOI: 10.3390/COATINGS13091483
Zagórski, I. (2024a). Surface Roughness of Magnesium Alloy AZ91D after Rough Milling Using Carbide End Mills with Different Rake Angle. 2024 IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2024 – Proceeding, 57–62. DOI: 10.1109/METROAEROSPACE61015.2024.10591602
Zagórski, I. (2023). Safety in Rough Milling of Magnesium Alloys Using Tools with Variable Cutting Edge Geometry. Advances in Science and Technology. Research Journal, 17 (2), 181–191. DOI: 10.12913/ 22998624/159637
Zagórski, I. (2024b). Surface Roughness Evaluation of AZ31B Magnesium Alloy After Rough Milling Using Tools with Different Geometries. Strojniški Vestnik – Journal of Mechanical Engineering, 70 (7–8), 355–368. DOI: 10.5545/SV-JME.2023.885
Zagórski, I., & Korpysa, J. (2020). Surface Quality Assessment after Milling AZ91D Magnesium Alloy Using PCD Tool. Materials, 13 (3), 617. DOI: 10.3390/ma13030617
Zagórski, I., Kulisz, M., & Szczepaniak, A. (2024). Roughness Parameters with Statistical Analysis and Modelling Using Artificial Neural Networks After Finish Milling of Magnesium Alloys with Different Edge Helix Angle Tools. StrojniskiVestnik/Journal of Mechanical Engineering, 70 (1–2), 27–41. DOI: 10.5545/SV-JME.2023.596
Zagórski, I., Szczepaniak, A., Kulisz, M., & Korpysa, J. (2022). Influence of the Tool Cutting Edge Helix Angle on the Surface Roughness after Finish Milling of Magnesium Alloys. Materials, 15 (9), 3184. DOI: 10.3390/MA15093184
Zawada-Michałowska, M., Kuczmaszewski, J., & Pieśko, P. (2020). Pre-Machining of Rolled Plates as an Element of Minimising the Post-Machining Deformations. Materials, 13 (21), 4777. DOI: 10.3390/MA13214777
Zawada-Michałowska, M., Kuczmaszewski, J., & Pieśko, P. (2022). Effect of the Geometry of Thin-Walled Aluminium Alloy Elements on Their Deformations after Milling. Materials, 15(24), 9049. DOI: 10.3390/ MA15249049
Zawada-Michałowska, M., Pieśko, P., & Legutko, S. (2023). Effect of the Cutting Tool on the Quality of a Machined Composite Part. Manufacturing Technology, 23 (6), 870–879. DOI: 10.21062/MFT.2023.107
Zhang, P., Huang, Y., Wang, R., & Ohashi, K. (2023). Study of Machined Surface Quality of AZ31B Magnesium Alloy by End Milling. Metals, 13 (10), 1712. DOI: 10.3390/MET13101712
