This work focuses on developing the mathematical model of surface roughness (Ra) in the turning of Inconel 625 superalloy with cryogenically treated tungsten carbide inserts. The influence of cryogenic treated on the microstructure and hardness of tungsten carbide tools was also investigated for the as-received inserts and deep cryogenic treatment at − 196 °C for 12, 24, and 36 h conditions. Turning experiments have been performed according to an orthogonal array L16 with three parameters (cutting tool, feed rate, cutting speed) at different levels with a 1 mm depth of cut. The ideal cutting tool and cutting parameters were evaluated in terms of the surface roughness (Ra). Analysis of Variance has been applied to determine the percentage of each cutting factor. It has been observed that the cutting speed has a maximum with 66.28% contribution on Ra. The best optimal turning parameters are obtained as A3B3C1 according to S/N ration. The mathematical model of Ra has been developed by regression analysis. The developed model is tested with verification experiments and found to be in good agreement with the experimental results.

In this study, the drilling of an Al 6082-T6 alloy and the effects of cutting tool coating and cutting parameters on surface roughness, cutting temperature, hole diameter, circularity, and cylindrical variations was investigated. In addition, the prediction accuracy of Taguchi, artificial neural networks (ANNs), and adaptive neuro-fuzzy inference system (ANFIS) methods was compared using both experimental results and Signal/Noise (S/N) ratios derived from the experimental results. The experimental design was prepared according to Taguchi L27 orthogonal indexing. As a result, it was observed that increasing the cutting speed and feed rate increases the cutting temperature hole error, circularity error and cylindricity error. Increasing the cutting speed positively affected the surface roughness, while increasing the feed rate led to an increase in the surface roughness. The lowest surface roughness, cutting temperature, hole diameter error and hole circularity error values were measured for the uncoated cutting tool. The minimum cylindricity variation was measured for drilling with TiAlN-coated cutting tools. The optimum cutting parameters were A1B1C3 (Uncoated, 0.11 mm/rev, 200 m/min) for surface roughness, A1B1C1 (Uncoated, 0.11 mm/rev, 120 m/min) for cutting temperature, hole error, circularity error and cylindricity error. In the estimation of the output parameters with Taguchi, ANNs and ANFIS, it was observed that the estimates made by converting the experimental values into S/N ratios were more accurate than the estimates made with the experimental results. The reliability coefficient and prediction ability of the ANN model were found to be higher than Taguchi and ANFIS models in estimating the output parameters.

Bu çalışma, Eriyik Yığma Modelleme (FDM) teknolojisi kullanılarak üretilen numunelerin yüzey kalitesi ve çekme dayanımı üzerinde ABS, PLA ve PETG filamentlerin ve baskı parametrelerinin etkisini incelemektedir. Bu amaçla, Taguchi L27 dizinine göre baskı deney tasarımı yapılmıştır. Filament malzemesi, dolum oranı, katman kalınlığı, doldurma hızı ve tarama açısı baskı parametreleri iken, yüzey pürüzlülüğü ve çekme mukavemeti de baskı kalitesi göstergeleridir. Ayrıca, deneysel ölçümler sonucu elde edilen yüzey pürüzlülüğü ve çekme dayanımı değerlerini matematiksel olarak modellemek için regresyon analizi de uygulanmıştır. Bu çalışmanın sonuçları filament malzemesinin yüzey pürüzlülüğü ve çekme dayanımı üzerinde önemli bir rol oynadığını göstermektedir. ABS ve PETG filamentlere göre PLA filament de yüzey pürüzlülüğünün sırasıyla ortalama %7,23ve %54,19 oranında daha az olduğu ve ayrıca, diğer filamentlere göre PLA filament de çekme dayanımın sırasıyla ortalama %46,46 ve %34,12 oranında daha yüksek olduğu tespit edilmiştir.

In this study, the effect of mechanical properties and cutting parameters (Cp) on the machinability of AISI 5140 steel cooled at high cooling rates after hot forging was investigated. The microstructural examinations and hardness measurements of the as-received AISI 5140 steel and the workpieces cooled in the oil and polymerized water after hot forging were performed. Turning process was conducted by using a coated ceramic tool at five different cutting speeds (Vc) (120, 150, 180, 210, and 240 m/min), four different feed rates (fn) (0.04, 0.08, 0.12, and 0.16 mm/rev), and four different depths of cut (ap) (0.4, 0.6, 0.8, and 1 mm) under dry machining conditions. SEM examinations of the cutting tools were also performed. It was seen from the results that the changing microstructure and hardness values had a significant effect on cutting forces (Fc) and surface roughness (Ra) from the Cp depending on cooling rate. While the highest Fc were reached in the workpiece with the highest hardness cooled in the polymerized water after hot forging, the lowest surface roughness (Ra) was obtained in the same workpiece.

This study focuses on optimization of cutting conditions and numerical analysis of flank wear in milling of Inconel 625 superalloy using PVD AlTiN and CVD TiCN/Al2O3/TiN-coated carbide inserts. The milling experiments have been performed in CNC vertical machining centre according to Taguchi L18 orthogonal array. Finite element modelling of tool wear was performed using Deform 3D software. Analysis of variance was utilized to define the influences of the milling conditions on Vb. The results showed that the feed rate (with 41.5% contribution rate) is the most important parameter affecting Vb. The linear and quadratic regression analyses were used to estimate the results of the test. The regression analysis results showed that the estimated Vb values achieved by the quadratic regression model were more effective compared to the linear regression model. Statistical results revealed that the Taguchi method was successful to define optimum cutting parameters in the milling of Inconel 625.