Hasan Gökkaya

Comparison of regression and artificial neural network models for surface roughness prediction with the cutting parameters in CNC turning

Surface roughness, an indicator of surface quality, is one of the most specified customer requirements in machining of parts. In this study, the experimental results corresponding to the effects of different insert nose radii of cutting tools (0.4, 0.8, 1.2 mm), various depth of cuts (0.75, 1.25, 1.75, 2.25, 2.75 mm), and different feedrates (100, 130, 160, 190, 220 mm/min) on the surface quality of the AISI 1030 steel workpieces have been investigated using multiple regression analysis and artificial neural networks (ANN). Regression analysis and neural network-based models used for the prediction of surface roughness were compared for various cutting conditions in turning. The data set obtained from the measurements of surface roughness was employed to and tests the neural network model. The trained neural network models were used in predicting surface roughness for cutting conditions. A comparison of neural network models with regression model was carried out. Coefficient of determination was 0.98 in multiple regression model. The scaled conjugate gradient (SCG) model with 9 neurons in hidden layer has produced absolute fraction of variance (R2) values of 0.999 for the training data, and 0.998 for the test data. Predictive neural network model showed better predictions than various regression models for surface roughness. However, both methods can be used for the prediction of surface roughness in turning.

Optimization of Abrasive Water Jet Turning Parameters for Machining of Low Density Polyethylene Material Based on Experimental Design Method

Abstract Studies to improve the machining of engineering materials have great importance for mechanical systems. Abrasive water-jet turning (AWJT) is a new and effective process for increasing machinability of engineering materials by providing temperature free cutting conditions, high surface quality and having no tool wear problem. In this study, AWJT of low density polyethylene (LDPE) material were investigated in terms of average surface roughness (ASR) and material removal rate (MRR) values and process parameters were optimized by experimental design method. The primary objectives of the study are to investigate AWJT process and system parameters to enhance machinability of LDPE material and to determine optimal processing parameters. Nozzle feed rate (5, 25 and 45 mm/min), abrasive flow rate (50, 200 and 350 g/min) and spindle speed (1 000, 1 500 and 2 500 min−1) were analyzed as process parameters. Taguchi L27 orthogonal full factorial design, optimization box and analysis of variance (Anova) were used for the experimentation and results analysis. Experimental results show that, AWJT process is more efficient in the machining of LPDE material than the conventional machining methods by increasing surface quality and MRR parameters. Minimum ASR and maximum MRR were obtained 1.67 μm and 14 072.02 mm3/min respectively; at optimum parameters of 5 mm/min nozzle feed rate, 350 g/min abrasive flow rate and 2 500 min−1 spindle speed.

Effect of abrasive water jet turning process parameters on surface roughness and material removal rate of AISI 1050 steel

Abstract The purpose of this study was to optimize and determine the most important abrasive water jet turning (AWJT) operational parameters, such as nozzle diameter (0.75 and 1.3 mm), nozzle feed rate (5, 25 and 45min−1), stand-off distance (2, 10 and 18 mm), abrasive flow rate (50, 150 and 350 g × min−1), and spindle speed (500, 1500 and 2500 min−1), regarding machining efficiency parameters, namely, average surface roughness Ra (µm) and material removal rate (mm3 × min−1), using AISI 1050 steel workpieces machined by abrasive water jet turning. Taguchi L18(21 × 34) orthogonal experimental design was used for the experimental design. Adequacy of the predicted linear regression model equations was tested using the method of ANOVA. These model equations were used to optimize the operational parameters of the surface roughness and material removal rate. Machinability charts, indicating the optimum processes with respect to the surface roughness and material removal rate for AISI 1050 steel workpieces, were developed and presented in this study. As a result of experimental studies, it is seen that nozzle feed rate proved to have the most significant impact on surface roughness by 48.7 %. Abrasive flow rate proved to have the most significant impact on material removal rate by 84.6 %. Using a nozzle diameter of 0.75 mm, the average surface roughness was improved while material removal rate decreased.

Mechanical and physical properties of hybrid reinforced (Al/B4C/Ni(K)Gr) composite materials produced by hot pressing

Abstract In this study, the mechanical and physical properties of hybrid reinforced (Al/B4C/Ni(K)Gr) metal matrix composite (MMC) materials were investigated. The MMC materials were produced using the powder metallurgy (PM) production method of hot pressing (HP). The aluminum alloy Alumix 13 was used as matrix material and boron carbide (B4C) and nickel-coated graphite (Ni(K)Gr) as reinforcement elements. The microstructural characteristics, hardness, 3-point bending strength and density values of the produced hybrid reinforced MMC materials were determined. The reinforcement element B4C was kept at constant concentration of 8 wt.-%. Four different MMC materials were produced with the addition of 0, 3, 5 and 7 wt.-% Ni(K)Gr in the B4C. From the SEM images of the MMC materials produced by the HP technique, it was observed that the reinforcement element exhibited a uniform distribution. Moreover, the particles showed an approach to each other depending on the particle size and the amount (wt.-%) of the reinforcement element. With increasing graphite content in the structure density, hardness and 3-point bending test values decreased.

The Effect of Process Parameters on Machining Volume and Depth Of Cut In Turning Operation Of AISI 1040 Steel With Abrasive Water Jet

Bu çalışmada, AISI 1040 çeliğinin aşındırıcı su jeti ile tornalanması esnasında işleme parametrelerinin kaldırılan talaş hacmime ve kesme derinliğine etkisi araştırılmıştır. Yapılan çalışmada deney sayısının en az olması için literatürde yapılmış olan çalışmalar göz önüne alınmış ve ön deneyler sonucu elde edilen tecrübelerle en uygun işleme parametre değerleriyle deneyler gerçekleştirilmiştir. Deneysel çalışmalarda pompa basıncı (350 MPa), aşındırıcı boyutu (Garnet formunda ve boyutu 80 mesh) ve nozul çapı (1.2 mm) sabit tutulmuştur. Ø 30 ve 240 mm ebatlarında 1040 çeliği, dört farklı aşındırıcı akış oranı (50, 150, 250 ve 350 gr/dak.), nozul mesafesi (2, 5, 8 ve 11 mm), nozul ilerleme miktarı (5, 15, 25 ve 35 mm/dak.) ve torna aynası deviri (25, 50, 75 ve 100 dev/dak.) işleme parametreleri değerlerinde işlenmiştir. Elde edilen bulgulara göre en yüksek talaş hacmi 5 mm/dak nozul ilerleme miktarında 1387,25 mm3 elde edilmiştir. En yüksek kesme derinliği ise 0,94 mm olarak 100 dev/dak torna aynası devrinde elde edilmiştir. In this study the effect of processing parameters during turning of AISI 1040 steel with abrasive water jet on machining volume and depth of cut. In the study, in order to keep the experiment quantity low, former studies in literature were taken into consideration and therefore experiments were realized with processing parameters and experiences that are most suitable to pre-experiments. In experimental studies pump pressure (350 MPa), abrader dimensions (in garnet form and dimension 80 mesh) and nozzle diameter (1.2 mm) were kept constant. 1040 steel with dimensions of Ø 30 and 240 mm were processed at four different abrader flow rate (50, 150, 250 and 350 gr/min), nozzle distance (2, 5, 8 and 11 mm), nozzle feed rate (5, 15, 25 and 35 mm/min) and lathe chuck revolutions (25, 50, 75 and 100 rpm). According to the findings the most highly material removal rate of 5 mm / min nozzle feed rate 1387.25 mm3 in the amount has been achieved. The maximum depths of cut 0.94 mm spindle speed of 100 rpm were obtained. Anahtar kelimeler: Aşındırıcı su jeti, Tornalama, AISI 1040, Talaş hacmi, Kesme derinliği.