EN
TR
Optimization of Vertical Machining Parameters of DIN 1.0038 Steels Using Hybrid Taguchi Based Grey-Fuzzy Algorithm in CNC Pocket Milling Process
Öz
In CNC pocket milling, surface quality, material removal rate and production time are critical parameters. However, setting the optimum parameters related to the process is problematic due to the presence of many factors. In this study, a hybrid grey-based fuzzy algorithm with a Taguchi L16 orthogonal array experimental design was used to determine the optimum results by combining factors such as cutting speed, feed rate, cutting depth and cutting path strategy. The optimum results were found as 0.36 µm surface roughness, 10 s machining time and 120 mm³/min material removal rate. These results were achieved by using 1500 rpm cutting speed, 2.0 mm/rev feed rate, 1.25 mm cutting depth and zigzag cutting path strategy. In the analysis made using the Analysis of Variance (ANOVA), it was concluded that the process was affected by feed rate, cutting depth, cutting speed and cutting path strategy, respectively.
Anahtar Kelimeler
Kaynakça
- 1. Ozturk, B. & Kara, F. (2020). Calculation and estimation of surface roughness and energy consumption in milling of 6061 alloy. Advances in Materials Science and Engineering, 2020(1), 5687951.
- 2. Traini, E., Bruno, G. & Lombardi, F. (2020). Tool condition monitoring framework for predictive maintenance: a case study on milling process. International Journal of Production Research, 59(23), 7179-7193.
- 3. Liu, Q., Chen, X., Liu, K., Cristino, V.A.M., Lo, K., Xie, Z., Guo, D., Tam, L. & Kwok, C. (2024). Influence of processing parameters on microstructure and surface hardness of hypereutectic Al-Si-Fe-Mg alloy via friction stir processing. Coatings, 14(2), 222.
- 4. Viswanathan, R., Ramesh, S., Maniraj, S. & Subburam, V. (2020). Measurement and multi-response optimization of turning parameters for magnesium alloy using hybrid combination of Taguchi-GRA-PCA technique. Measurement, 159, 107800.
- 5. Bien, D.X. (2023). Predictive modeling of surface roughness in hard turning with rotary cutting tool based on multiple regression analysis, artificial neural network, and genetic programing methods. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 238(1-2), 137-150.
- 6. Yang, H., Zheng, H. & Zhang, T. (2024). A review of artificial intelligent methods for machined surface roughness prediction. Tribology International, 199, 109935.
- 7. Gologlu, C. & Sakarya, N. (2008). The effects of cutter path strategies on surface roughness of pocket milling of 1.2738 steel based on Taguchi method. Journal of Materials Processing Technology, 206(1-3), 7-15.
- 8. Deng, C., Miao, J., Ma, Y., Wei, B. & Feng, Y. (2019). Reliability analysis of chatter stability for milling process system with uncertainties based on neural network and fourth moment method. International Journal of Production Research, 58(9), 2732-2750.
Ayrıntılar
Birincil Dil
İngilizce
Konular
Makine Mühendisliğinde Optimizasyon Teknikleri
Bölüm
Araştırma Makalesi
Yayımlanma Tarihi
25 Mart 2026
Gönderilme Tarihi
26 Mayıs 2025
Kabul Tarihi
6 Ocak 2026
Yayımlandığı Sayı
Yıl 2026 Cilt: 41 Sayı: 1
APA
Engin, K. E., Eşme, U., & Külekci, M. K. (2026). Optimization of Vertical Machining Parameters of DIN 1.0038 Steels Using Hybrid Taguchi Based Grey-Fuzzy Algorithm in CNC Pocket Milling Process. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi, 41(1), 115-128. https://doi.org/10.21605/cukurovaumfd.1706626
AMA
1.Engin KE, Eşme U, Külekci MK. Optimization of Vertical Machining Parameters of DIN 1.0038 Steels Using Hybrid Taguchi Based Grey-Fuzzy Algorithm in CNC Pocket Milling Process. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi. 2026;41(1):115-128. doi:10.21605/cukurovaumfd.1706626
Chicago
Engin, Kaan Emre, Uğur Eşme, ve Mustafa Kemal Külekci. 2026. “Optimization of Vertical Machining Parameters of DIN 1.0038 Steels Using Hybrid Taguchi Based Grey-Fuzzy Algorithm in CNC Pocket Milling Process”. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi 41 (1): 115-28. https://doi.org/10.21605/cukurovaumfd.1706626.
EndNote
Engin KE, Eşme U, Külekci MK (01 Mart 2026) Optimization of Vertical Machining Parameters of DIN 1.0038 Steels Using Hybrid Taguchi Based Grey-Fuzzy Algorithm in CNC Pocket Milling Process. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi 41 1 115–128.
IEEE
[1]K. E. Engin, U. Eşme, ve M. K. Külekci, “Optimization of Vertical Machining Parameters of DIN 1.0038 Steels Using Hybrid Taguchi Based Grey-Fuzzy Algorithm in CNC Pocket Milling Process”, Çukurova Üniversitesi Mühendislik Fakültesi Dergisi, c. 41, sy 1, ss. 115–128, Mar. 2026, doi: 10.21605/cukurovaumfd.1706626.
ISNAD
Engin, Kaan Emre - Eşme, Uğur - Külekci, Mustafa Kemal. “Optimization of Vertical Machining Parameters of DIN 1.0038 Steels Using Hybrid Taguchi Based Grey-Fuzzy Algorithm in CNC Pocket Milling Process”. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi 41/1 (01 Mart 2026): 115-128. https://doi.org/10.21605/cukurovaumfd.1706626.
JAMA
1.Engin KE, Eşme U, Külekci MK. Optimization of Vertical Machining Parameters of DIN 1.0038 Steels Using Hybrid Taguchi Based Grey-Fuzzy Algorithm in CNC Pocket Milling Process. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi. 2026;41:115–128.
MLA
Engin, Kaan Emre, vd. “Optimization of Vertical Machining Parameters of DIN 1.0038 Steels Using Hybrid Taguchi Based Grey-Fuzzy Algorithm in CNC Pocket Milling Process”. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi, c. 41, sy 1, Mart 2026, ss. 115-28, doi:10.21605/cukurovaumfd.1706626.
Vancouver
1.Kaan Emre Engin, Uğur Eşme, Mustafa Kemal Külekci. Optimization of Vertical Machining Parameters of DIN 1.0038 Steels Using Hybrid Taguchi Based Grey-Fuzzy Algorithm in CNC Pocket Milling Process. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi. 01 Mart 2026;41(1):115-28. doi:10.21605/cukurovaumfd.1706626