The Effect of Internal and External MQL Methods Used for Environmentally Friendly Manufacturing on Machining Performance in Drilling AA2024 Alloys: A Comparison for ANN And Taguchi Analyzes
Abstract
Keywords
Supporting Institution
Ethical Statement
Thanks
References
- [1] Çakır, A., 2009. AA7075 and AA6013 Investigation of cutting parameter on aluminium alloys during drilling operations. Gazi University, Graduate School of Natural and Applied Sciences, Master Thesis, Ankara.
- [2] Çakır, A., 2015. Investigation of the effect of cooling conditions on cutting performance in drilling AA7075 and AA2024 aluminum materials. Gazi University, Graduate School of Natural and Applied Sciences, Ph.D. Thesis, Ankara.
- [3] Mills, B., Redford, A.H., 1983. Machinability of Engineering Materials. Applied Sci. Publishers Ltd.
- [4] Akkurt, M., 1998. Metal Cutting Methods and Machine Tools. Birsen Press, pp. 23-90.
- [5] Tonshoff, H.L., Spintig, W., Konig, W., Neises, A., 1994. Machining of holes developments in drilling technology. Annals of the CIRP, Vol. 43(2), pp. 551-561.
- [6] Ogawa, M., Inose, M., Arai, M., Saga, T., 1994. Micro drilling of 5056 wrought aluminum alloy. Journal of Japan Institute of Light Metals, Vol. 44(9), pp. 486-491. DOI: 10.2464/jilm.44.486.
- [7] Pirtini, M., Lazoglu, I., 2005. Forces and hole quality in drilling. International Journal of Machine Tools & Manufacture, Vol. 45(1), pp. 1271-1281. DOI: 10.1016/j.ijmachtools.2005.01.004.
- [8] Taşgetiren, S., Aslantaş, K., 2000. A new design of hard metal insert holder for cutting on turning. 3rd GAP Engineering Congress, pp. 150-157.
Details
Primary Language
English
Subjects
Optimization Techniques in Mechanical Engineering, Tribology, Manufacturing Processes and Technologies (Excl. Textiles)
Journal Section
Research Article
Authors
Abdullah Duran
0000-0001-6618-7275
Türkiye
Ulvi Şeker
0000-0001-6455-6858
Türkiye
Cevdet Şencan
0000-0002-7562-9896
Türkiye
Early Pub Date
January 15, 2025
Publication Date
January 23, 2025
Submission Date
January 26, 2024
Acceptance Date
May 8, 2024
Published in Issue
Year 2025 Volume: 27 Number: 79
Cited By
Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel Engines
International Journal of Automotive Science And Technology
https://doi.org/10.30939/ijastech..1896122