Farklı tornalama koşulları altında AA7075-T6 alaşımlarının işlenebilirlik özellikleri üzerinde kaplama malzemelerinin etkileri

Öz

Talaşlı imalat, esasen talaş oluşturma ve kırma işlemidir; bu işlem sırasında iş parçasının yüzeyinin temizlenmesi ve daha pürüzsüz ve mekanik olarak uzun ömürlü bir yapı elde etmek için yeni bir yüzey oluşturulması istenir. Talaşlı imalat, her biri belirli bir amaç için uzmanlaşmış birçok işlemi içerir. En önemli işleme işlemlerinden biri tornalamadır. Tornalama, farklı işleme parametrelerine sahip çeşitli takım tezgahları, kesici takımlar ve fikstürler kullanılarak gerçekleştirilir. Bu makale, kesme hızı, ilerleme hızı ve kesici takım üzerindeki kaplama malzemeleri gibi faktörleri dikkate alarak AA7075-T6 alaşımının işlenebilirlik çalışmasına odaklanmaktadır. Bu çalışmada değerlendirilen tepki parametreleri kesme kuvvetleri, kesme sıcaklıkları ve enerji tüketimidir. Bulgulara göre, ilerleme hızı, kesme hızı ve kaplama malzemeleri sırasıyla kesme kuvvetleri, enerji tüketimi ve kesme sıcaklıkları üzerinde baskın parametreler olarak bulunmuştur. Bu makale için geliştirilen çerçeve, popüler ve geçerli işlenebilirlik göstergelerini dikkate alarak modern kaplama malzemelerini karşılaştırarak güncel literatüre katkıda bulunmayı amaçlamaktadır.

Anahtar Kelimeler

• AA7075-T6 alaşımları
• Kaplama malzemesi
• Kesme kuvvetleri
• Kesme sıcaklıkları

The Effects of Coating Materials on Machinability Characteristics of AA7075-T6 Alloys under Different Turning Conditions

Abstract

Machining is essentially a process of creating and breaking chips, during which it is desired to clean the surface of the workpiece and create a new surface to obtain a smoother and mechanically long-lasting structure. Machining involves many processes; each specialized for a specific purpose. One of the most important machining processes is turning. Turning is performed using a variety of machine tools with different machining parameters, cutting tools, and fixtures. This paper focuses on the machinability study of AA7075-T6 alloy considering the factors such as cutting speed, feed rate and coating materials on the cutting tool. The response parameters evaluated in this study is the cutting forces, cutting temperatures, energy consumption. According to the findings, feed rate, cutting speed and coating materials were found as the dominant parameters on cutting forces, energy consumption and cutting temperatures respectively. This situation is seen in the ANOVA tables that feed is the most effective parameter for cutting force with 33.05%, coating is the most effective parameter for temperature with 3.45% and cutting speed is the most effective parameter for energy consumption with 45.54%. The frame developed for this paper aims to contribute to the current literature by comparing modern coating materials considering popular and valid machinability indicators.

Keywords

• AA7075-T6 alloys
• Coating material
• Cutting forces
• Cutting temperatures

Kaynakça

1. Asiltürk I., Neşeli S., Multi response optimisation of CNC turning parameters via Taguchi method-based response surface analysis. Measurement 45(4), 785-794, 2012.
2. Binali R., Parametric optimization of cutting force and temperature in finite element milling of AISI P20 steel. Journal of Materials and Mechatronics: A 4(1), 244-256, 2023.
3. Binali R., Coşkun M., Neşeli S., An investigation of power consumption in milling AISI P20 plastic mold steel by finite elements method. Avrupa Bilim ve Teknoloji Dergisi (34), 513-518, 2022.
4. Binali R., Korkmaz M. E., Özdemir M. T., Günay M., A Holistic Perspective on Sustainable Machining of Al6082: Synergistic Effects of Nano-Enhanced Bio-Lubricants. Machines, 13(4), 2025.
5. Binali R., Kuntoğlu M., Evaluation of Machining Parameters Affecting Cutting Forces in Dry Turning of GGG50 Ductile Cast Iron. Türk Doğa ve Fen Dergisi 12(2), 55-60, 2023.
6. Binali R., Yaldız S., Neşeli S., Finite element analysis and statistical investigation of S960ql structure steel machinability with milling method. Journal of the Brazilian Society of Mechanical Sciences and Engineering 46(5), 260, 2024.
7. Coşkun M., Çiftçi İ., Demir H., AISI P20S kalıp çeliğinin işlenebilirliğinin incelenmesi. Manufacturing Technologies and Applications, 2(2), 1-9, 2021.
8. Çakır A., Yağmur S., Kavak N., Küçüktürk G., Şeker U., The effect of minimum quantity lubrication under different parameters in the turning of AA7075 and AA2024 aluminium alloys. The International Journal of Advanced Manufacturing Technology 84(9), 2515-2521, 2016.

9. Çiftçi İ., The influence of cutting tool coating and cutting speed on cutting forces and surface roughness in machining of austenitic stainless steels. Journal of the Faculty of Engineering and Architecture of Gazi University 20(2), 205-209, 2005.
10. Demir H., Ulas H., Binali R., Investigation of the effects on surface roughness and tool wear in the toolox44 material. Technol Appl Sci, 13, 19-28, 2018.
11. Demirpolat H., Evaluation of the turning parameters of AISI 5115 steel in dry and MQL cutting environments with the use of a coated carbide cutting insert: An experimental study. Journal of Materials and Mechatronics: A 5(1), 168-182, 2024.
12. Ginting A., Skein R., Cuaca D., Masyithah Z., The characteristics of CVD-and PVD-coated carbide tools in hard turning of AISI 4340. Measurement 129, 548-557, 2018.
13. Gupta K. M., Ramdev K., Dharmateja S., Sivarajan S., Cutting characteristics of PVD coated cutting tools. Materials Today: Proceedings 5(5), 11260-11267, 2018.
14. Gupta M. K., Korkmaz M. E., Yılmaz H., Şirin Ş., Ross N. S., Jamil M., Królczyk G.M., Sharma V. S., Real-time monitoring and measurement of energy characteristics in sustainable machining of titanium alloys. Measurement 224, 113937, 2024.
15. Hamıd M. W. H., Özlü B., Ulaş H. B., Demir H., Prediction of cutting parameters and reduction of output parameters using machine learning in milling of Inconel 718 alloy. Scientific Reports 15(1), 33309, 2025.
16. Hao G., Liu Z., Liang X., Zhao J., Influences of TiAlN coating on cutting temperature during orthogonal machining H13 hardened steel. Coatings 9(6), 355, 2019.
17. Karagöz C., Özlü B., Ulaş H. B., Demir H., RSM ANN and ANFIS based analysis of machining conditions and cutting parameters in sustainable milling of AISI 316 Ti alloy. Multidiscipline Modeling in Materials and Structures 1-28, 2025.
18. Kaya K., Çetin T., Binali R., Gündoğmuş H., Finish turning of toolox 33 to improve machining parameters with different nose radius tools. European Mechanical Science 9(3), 234-245, 2025.
19. Korkmaz M. E., Gupta M. K., A state of the art on simulation and modelling methods in machining: future prospects and challenges. Archives of Computational Methods in Engineering 30(1), 161-189, 2023.
20. Korkmaz M. E., Gupta M. K., Kuntoğlu M., Patange A. D., Ross N. S., Yılmaz H., Chauhan S., Vashishtha G., Prediction and classification of tool wear and its state in sustainable machining of Bohler steel with different machine learning models. Measurement 223, 113825, 2023.
21. Korkmaz M. E., Günay M., Experimental and statistical analysis on machinability of Nimonic80A superalloy with PVD coated carbide. Sigma Journal of Engineering and Natural Sciences 36(4), 1141-1152, 2018.
22. Kul B. S., Yamaner A. S., A Comparative Evaluation of Dry-MQL Turning Applications for AISI 5115 Steel. Manufacturing Technologies and Applications, 6(1), 23-32, 2025.
23. Kumar P., Chauhan S. R., Pruncu, C. I., Gupta, M. K., Pimenov, D. Y., Mia, M., Gill, H. S., Influence of different grades of CBN inserts on cutting force and surface roughness of AISI H13 die tool steel during hard turning operation. Materials, 12(1), 177, 2019.
24. Kuntoğlu M., Acar O., Gupta M. K., Sağlam H., Sarikaya M., Giasin K., Pimenov D. Y., Parametric optimization for cutting forces and material removal rate in the turning of AISI 5140. Machines 9(5), 90, 2021.
25. Kuntoğlu M., Aslan A., AISI 5140 Çeliğinin tornalanması esnasında yaklaşma açısı ve kesme parametrelerinin işlenebilirliğe etkisinin incelenmesi. Politeknik Dergisi, 1-1, 2021.
26. Kuntoğlu M., Aslan A., Pimenov D. Y., Usca Ü. A., Salur E., Gupta M. K., Mikolajczyk T., Giasin K., Kapłonek W., Sharma S., A review of indirect tool condition monitoring systems and decision-making methods in turning: Critical analysis and trends. Sensors 21(1), 108, 2020.
27. Kuntoğlu M., Binali R., Makhesana M., Characterizing Machining Indicators with Machine Learning Models Under Cellulose Nanocrystal and Graphene-Based Nanofluid Conditions. Arabian Journal for Science and Engineering 1-17, 2025.
28. Makhesana M. A., Patel K. M., Bagga P. J., Evaluation of surface roughness, tool wear and chip morphology during machining of nickel-based alloy under sustainable hybrid nanofluid-MQL strategy. Lubricants 10(11), 315, 2022.
29. Makhesana M. A., Patel K. M., Krolczyk G. M., Danish M., Singla A. K., Khanna N., Influence of MoS2 and graphite-reinforced nanofluid-MQL on surface roughness, tool wear, cutting temperature and microhardness in machining of Inconel 625. CIRP Journal of Manufacturing Science and Technology 41, 225-238, 2023.
30. Özdemir C., Özlü B., Demir H., Performance Analysis of Process Parameters and Drill Geometry in Drilling AA 6061-T6 Alloy, Journal of Polytechnic 27(5), 2043-2059, 2024.
31. Özlü B., Ulaş H. B., Kara F., Investigation of the effects of cutting tool coatings and machining conditions on cutting force, specific energy consumption, surface roughness, cutting temperature, and tool wear in the milling of Ti6Al4V alloy. Lubricants 13(8), 363, 2025.
32. Pehlivan F., Improvement of machining vibrational stabilization for a CNC lathe in turning of 420 hardened steels by MQL and cryogenic method. Journal of Materials and Mechatronics: A 3(2), 290-299, 2022.
33. Sahoo P., Patra K., Singh V. K., Gupta M. K., Song Q., Mia M., Pimenov D. Y., Influences of TiAlN coating and limiting angles of flutes on prediction of cutting forces and dynamic stability in micro milling of die steel (P-20). Journal of Materials Processing Technology 278, 116500, 2020.
34. Sarıkaya M., Gupta M. K., Tomaz I., Krolczyk G. M., Khanna N., Karabulut Ş., Prakash C., Buddhi D., Resource savings by sustainability assessment and energy modelling methods in mechanical machining process: A critical review. Journal of Cleaner Production, 370, 133403, 2022.
35. Turan İ., Özlü B., Ulaş H. B., Demir H., Prediction and Modelling with Taguchi, ANN and ANFIS of Optimum Machining Parameters in Drilling of Al 6082-T6 Alloy. Journal of Manufacturing and Materials Processing 9(3), 92, 2025.