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  • Küçük Resim
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    Milling Inconel 718 workpiece with cryogenically treated and untreated cutting tools
    (SpringerLink, 2021-07-17) Gürbüz, Hüseyin; Baday, Şehmus
    Although Inconel 718 is an important material for modern aircraft and aerospace, it is a kind material, which is known to have low machinability. Especially, while these types of materials are machined, high cutting temperatures, BUE on cutting tool, high cutting forces, and work hardening occur. Therefore, in recent years, instead of producing new cutting tools that can withstand these difficult conditions, cryogenic process, which is a heat treatment method to increase the wear resistance and hardness of the cutting tool, has been applied. In this experimental study, feed force, surface roughness, vibration, cutting tool wear, hardness, and abrasive wear values that occurred as a result of milling of Inconel 718 material by means of cryogenically treated and untreated cutting tools were investigated. Three different cutting speeds (35-45-55 m/min) and three different feed rates (0.02- 0.03-0.04 mm/tooth) at constant depth of cut (0.2 mm) were used as cutting parameters in the experiments. As a result of the experiments, lower feed forces, surface roughness, vibration, and cutting tool wear were obtained with cryogenically treated cutting tools. As the feed rate and cutting speed were increased, it was seen that surface roughness, vibration, and feed force values increased. At the end of the experiments, it was established that there was a significant relation between vibration and surface roughness. However, there appeared an inverse proportion between abrasive wear and hardness values. While BUE did not occur during cryogenically treated cutting tools, it was observed that BUE occurred in cutting tools which were not cryogenically treated. Also, in this study, the statistical validity of the experimental values was tested with the help of secondorder equations and analyses of variance (ANOVA). R2 values obtained as 99.14%, 99.76%, and 97.98% for vibration, surface roughness, and feed force values were modeled statistically with the help of second-order equations, respectively.
  • Küçük Resim
    Öğe
    Modelling of effects of various chip breaker forms on surface roughness in turning operations by utilizing artificial neural networks
    (Gazi Üniversitesi, 2016-03-01) Gürbüz, Hüseyin; Baday, Şehmus; Sözen, Adnan
    In this study, the effects of different chip breaker forms and cutting parameters on the surface roughness on machined surfaces were investigated experimentally in turning of AISI 1050 steel; and values of surface roughness obtained from experiments were determined with empirical equations using artificial neural networks. The utilizing of ANN was offered to determine the surface roughness depending on chip breaker forms and cutting parameters of AISI 1050 steel. The back propagation learning algorithm and fermi transfer function were used in artificial neural network. Experimental measurements data were employed as training and test data in order to train the neural network created. The best fitting training data set was attained with ten neurons in two hidden layers 6 of which were at first hidden layer and 4 of which were at second hidden layer, making it possible to predict surface roughness with precision at least as good as that of the experimental error over the entire experimental range. After network training, R2 value was found as 0.978, and average error as 0.018%. When the results of mathematical modelling are examined, the computed surface roughness is observed to be apparently within acceptable values
  • Küçük Resim
    Öğe
    Investigation of effects of different cutting and machining parameters on surface roughness and main cutting forces via response surface method
    (European Journal of Technique (EJT), 2020-12-30) Gürbüz, Hüseyin; Gönülaçar, Yunus Emre
    In this study, the effects of cutting speed, feed rate and minimum quantity lubrication (MQL), frequently employed in machining applications, on main cutting force (Fc) and average surface roughness (Ra), resulting from turning AISI 4140, were investigated. For this purpose, analyses for Fc and Ra were performed utilizing Box-Behnken model. By using experimental parameters, the efficiency and the changes of the parameters on Fc and Ra were examined with the help of 13 experiments. In addition, the effectiveness of design models was investigated by creating different design models. The high success rate modelling for Fc and Ra was realized with 99% success as a result of analyses conducted according to Box-Behnken methods (BoxBehnken, Box-Behnken-Stepwise, Box-Behnken-Backward and BoxBehnken-Forward). The most effective parameter on Fc and Ra was found to be the feed rate according to analysis of variance (ANOVA). It was demonstrated that the estimations on the created Box-Behnken model were quite successful on the data initially entered into the system; and that R2 values obtained for Fc and Ra were 0.999 and 0.996, respectively. It was determined that optimum parameters for Fc were feed rate 0.25 mm/rev, cutting speed 125 m/min and cutting condition MQL2 ml/min, while they were feed rate 0.25 mm/rev, cutting speed 125 m/min and cutting condition MQL1 ml/min for Ra.
  • Küçük Resim
    Öğe
    Effect of MQL flow rate on machinability of AISI 4140 steel
    (Taylor & Francis, 2020-06-27) Gürbüz, Hüseyin; Gönülaçar, Yunus Emre; Baday, Şehmus
    Many studies were performed about the influence of minimum quantity lubrication (MQL) technique on cutting performance in the literature, but there is no paper examining the effect of different MQL flow rates and cutting parameters on machinability of AISI 4140 material as a whole. In this study, the effects of different MQL flow rates and cutting parameters on surface roughness, main cutting force and cutting tool flank wear (VB), with great importance among the machinability criteria, and forming as a result of the machining of AISI 4140, were revealed. At the end of the experiments, it was determined that rise of flow rate affected main cutting forces positively to a certain extent; yet, it exhibited no significant effect on surface roughness, but reduced VB. Also, it was observed that both main cutting force and surface roughness increased with the increase of feed, while generally decreased with the increase of cutting speed. It was seen that flank wear was positively affected by the increase in flow rate; and this decreased with the increase in flow rate. R2 values obtained as 99.8% and 99.9% for main cutting forces and surface roughness values modeled statistically with the help of quadratic equations, respectively.
  • Küçük Resim Yok
    Öğe
    Optimization and evaluation of dry and minimum quantity lubricating methods on machinability of AISI 4140 using Taguchi design and ANOVA
    (SAGE Journals, 2020-07-05) Gürbüz, Hüseyin; Gönülaçar, Yunus Emre
    In this work, it is aimed to study the effects of dry machining and minimum quantity lubrication application on machinability in turning AISI 4140 steel by utilizing different cutting parameters. Also, this study contains effects and optimization of cutting conditions (dry and minimum quantity lubricating), feed rate, and cutting speed on surface roughness (Ra) and main cutting forces (Fc) determined by employing the Taguchi method. At the end of experiments, it was established that compared to dry machining operations, minimum quantity lubricating significantly reduced cutting tool wear, while Fc and Ra decreased in general. Analyses of variance, regression analysis, signal-to-noise ratio, and orthogonal array were employed to analyze the effects and contributions of independent variables on dependent variables. The optimum levels of the dependent variables for reducing Fc and Ra using signal-to-noise rates were established. According to signal-to-noise ratios, minimum quantity lubricating had a more important effect on Fc and Ra than dry machining. The optimal conditions for Fc and Ra were at 0.16 mm/rev feed rate, 125 m/min cutting speed at minimum quantity lubricating. Analysis of variance results demonstrated that the feed rate is the most influential independent variable on Fc (93.976 %) and Ra (89.352 %). Validation test results exhibited that the Taguchi method and regression analysis were highly achieved methods in the optimization of independent variables for dependent variables. Taguchi optimization technique and regression analysis obtained from Fc (R2Tag. = 0.972 and R2Rag. = 0.997) and Ra (R2Tag. = 0.985 and R2Rag. = 0.996) measurements match really well with the experimental data
  • Küçük Resim Yok
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  • Küçük Resim
    Öğe
    Investigation of effects of cutting insert rake face forms on surface integrity
    (SpringerLink, 2017-06) Gürbüz, Hüseyin; Şeker, Ulvi; Kafkas, Fırat
    In this study, the effects of cutting insert rake face forms and cutting parameters on the surface integrity in machining of AISI 316 L steel were investigated experimentally. The cutting forces occur during chip removal, surface roughness values on the machined surfaces with residual stresses on machined workpiece were measured, and metallurgical structure (microhardness and microstructural variations) of the surface layers formed as a result of machining were evaluated. The surface integrity was evaluated in terms of surface roughness, residual stress, microhardness, and microstructure analysis. In experiments, the best surface integrity results were obtained by cutting tools having QM form, and the worst surface integrity results were obtained by cutting tools having MR form. Under all these cutting conditions, it was observed that the surface integrity worsened when depth of cut and cutting feed were increased; however, the surface integrity improved when cutting speed was increased. In terms of cutting parameters, the best surface integrity was obtained with cutting speed 200 m/min, cutting feed 0.1 mm/rev, and depth of cut 1.25 mm; on the other hand, the worst surface integrity was obtained with cutting speed 125 m/min, cutting feed 0.3 mm/rev, and depth of cut 2.5 mm.
  • Küçük Resim Yok
    Öğe
    Estimation of surface roughness and cutting speed in CNC WEDM by artificial neural network that employed trainable activation function
    (SAGE Journals, 2021-02-01) Gürbüz, Hüseyin
    Activation functions are the most significant properties of artificial neural networks (ANN) because these functions are directly related with the ability of ANN in learning or modelling a system or a function. Furthermore, another reason for the significance of the fact that determination of optimal activation function in ANN is its relationship with success level. In this experimental study, the effects of different types of wire electrodes, cooling techniques and workpiece materials on surface roughness (Ra) and cutting speed (Vc) in wire electrical discharge machining (WEDM) were investigated by using trainable activation functions (AFt) and modelling them in ANNs. So far, a number of methods have been performed according to the data set in order to optimally predict Ra and Vc results. Among these methods, randomized ANN with AFt was found to be the best one for robust prediction according to RMSE values. While the value was 0.280 for Vc, it was 0.2104 for Ra. Optimum activation functions in Ra and Vc were found at first and third degree trainable functions, respectively.