Browsing by Author "Esme, Ugur"

Now showing 1 - 12 of 12

Citation - WoS: 2
Citation - Scopus: 4
Application of a Taguchi-Based Neural Network for Forecasting and Optimization of the Surface Roughness in a Wire-Electrical Machining Process
(Inst Za Kovinske Materiale I In Tehnologie, 2012) Kazancoglu, Yigit; Esme, Ugur; Kulekci, Mustafa Kemal; Kahraman, Funda; Samur, Ramazan; Akkurt, Adnan; Ipekci, Melih Turan
Wire-electrical-discharge machining (WEDM) is a modification of electro-discharge machining (EDM) and has been widely used for a long time for cutting punches and dies, shaped pockets and other machine parts on conductive materials. WEDM erodes workpiece materials by a series of discrete electrical sparks between the workpiece and an electrode flushed or immersed in a dielectric fluid. The WEDM process is particularly suitable for machining hard materials as well as complex shapes. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the surface roughness in a WEDM process. A back-propagation neural network (BPNN) was developed to predict the surface roughness. In the development of a predictive model, machining parameters of open-circuit voltage, pulse duration, wire speed and dielectric flushing pressure were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the surface roughness (R-a). Finally, the Taguchi approach was applied to determine the optimum levels of machining parameters.
Citation - WoS: 4
Grey-Based Fuzzy Algorithm for the Optimization of the Ball Burnishing Process
(Carl Hanser Verlag, 2015) Esme, Ugur; Kulekci, Mustafa Kemal; Ustun, Deniz; Kahraman, Funda; Kazancoglu, Yigit
In the present study, Grey based fuzzy algorithm was used for the optimization of complex multiple performance characteristics of the ball burnishing process. Experiments have been planned according to Taguchi's L-16 orthogonal design matrix. Burnishing force, number of passes, feed rate and burnishing speed were selected as input parameters, whereas surface roughness and microhardness were selected as output responses. Using Grey relation analysis (GRA), Grey relational coefficient (GRC) and Grey relation grade (GRG) were obtained. Then, Grey-based fuzzy algorithm was applied to obtain Grey fuzzy reasoning grade (GFRG). Analysis of variance (ANOVA) was carried out to find the significance and contribution of parameters on multiple performance characteristics. Finally, a confirmation test was applied at the optimum level of GFRG to validate the results. The results also show the feasibility of the Grey-based fuzzy algorithm for continuous improvement in product quality in complex manufacturing processes.
Magnesium Applications for Fuel Economy and Energy Production
(Carl Hanser Verlag, 2011) Kulekci, Mustafa Kemal; Yelken, Tugba; Esme, Ugur; Kazancoglu, Yigit
In this study, the properties, applications, technological barriers, and future projection of magnesium and magnesium based materials in fuel economy and energy production were evaluated. Mg lowers fabrication and joining costs, substitution by lightweight materials enable weight savings, in addition lifetime fuel costs and CO2 emission are reduced. Studies state that reducing the automotive weights by a certain amount will result in a similar reduction in fuel consumption and CO2 emissions. Most power systems, either renewable or nuclear, provide solutions for electricity production, but to date, there is no satisfactory substitute for liquid fossil fuel for use in transportation (cars, airplanes, and the like) due to environmental reasons or security of supply. A resent approach to this problem is to use hydrogen as fuel. Researches on Magnesium-Air Fuel Cell (MAFC) Technology resulted in new and improved technologies which have advanced the magnesium-air fuel cell to commercialization. The MAFC approach to an alternative energy source is the development of a powerful, reliable and environmentally friendly non-toxic fuel cell that generates energy using magnesium. From the results of the resarches it is concluded that magnesium applications reduce CO2 emission, and fuel costs.
Citation - WoS: 1
Modeling and Optimization of Cnc Milling of Aisi 1050 Steel by a Regression Based Differential Evolution Algorithm (dea)
(Carl Hanser Verlag, 2016) Esme, Ugur; Kulekci, Mustafa Kemal; Ustun, Deniz; Buldum, Baris; Kazancoglu, Yigit; Ocalir, Seref
The present study is aimed at finding an optimization strategy for the CNC pocket milling process based on regression analysis including differential evolution algorithm (DEA). Milling parameters such as cutting speed, feed rate and depth of cut have been designed using rotatable central composite design (CCD). The AISI 1050 medium carbon steel has been machined by a high speed steel (HSS) flat end cutter tool with 8 mm diameter using the zig-zag cutting path strategy under air flow condition. The influence of milling parameters has been examined. The model for the surface roughness, as a function of milling parameters, has been obtained using the response surface methodology (RSM). Also, the power and adequacy of the quadratic mathematical model have been proved by analysis of variance (ANOVA) method. Finally, the process design parameters have been optimized based on surface roughness using bio-inspired optimization algorithm, called differential evolution algorithm (DEA). The enhanced method proposed in this study can be readily applied to different metal cutting processes with greater and faster reliability.
Citation - WoS: 28
Citation - Scopus: 36
Multi-Objective Optimization of the Cutting Forces in Turning Operations Using the Grey-Based Taguchi Method
(Inst Za Kovinske Materiale I In Tehnologie, 2011) Kazancoglu, Yigit; Esme, Ugur; Bayramoglu, Melih; Guven, Onur; Ozgun, Sueda
This study investigated the multi-response optimization of the turning process for an optimal parametric combination to yield the minimum cutting forces and surface roughness with the maximum material-removal rate (MRR) using a combination of a Grey relational analysis (GRA) and the Taguchi method. Nine experimental runs based on an orthogonal array of the Taguchi method were performed to derive objective functions to be optimized within the experimental domain. The objective functions were selected in relation to the parameters of the cutting process: cutting force, surface roughness and MRR. The Taguchi approach was followed by the Grey relational analysis to solve the multi-response optimization problem. The significance of the factors on the overall quality characteristics of the cutting process was also evaluated quantitatively using the analysis-of-variance method (ANOVA). Optimal results were verified through additional experiments. This shows that a proper selection of the cutting parameters produces a high material-removal rate with a better surface roughness and a lower cutting force.
Citation - WoS: 59
Citation - Scopus: 96
Optimization of Weld Bead Geometry in Tig Welding Process Using Grey Relation Analysis and Taguchi Method
(Inst Za Kovinske Materiale I In Tehnologie, 2009) Esme, Ugur; Bayramoglu, Melih; Kazançoğlu, Yiğit; Ozgun, Sueda
This study investigated the multi-response optimization of tungsten inert gas welding (TIG) welding process for an optimal parametric combination to yield favorable bead geometry of welded joints using the Grey relational analysis and Taguchi method. Sixteen experimental runs based on an orthogonal array of Taguchi method were performed to derive objective functions to be optimized within experimental domain. The objective functions have been selected in relation to parameters of TIG welding bead geometry; bead width, bead height, penetration, area of penetration as well as width of heat affected zone and tensile load. The Taguchi approach followed by Grey relational analysis to solve the multi-response optimization problem. The significance of the factors on overall quality characteristics of the weldment has also been evaluated quantitatively by the analysis of variance method (ANOVA). Optimal results have been verified through additional experiments. This shows application feasibility of the Grey relation analysis in combination with Taguchi technique for continuous improvement it) product quality in manufacturing industry.
Citation - WoS: 4
Process Capability Analysis in Machining for Quality Improvement in Turning Operations
(Carl Hanser Verlag, 2012) Kahraman, Funda; Esme, Ugur; Kulekci, Mustafa Kemal; Kazancoglu, Yigit
Process capability indices are effective tools for both, process capability analysis and quality assurance. In quality assurance programs, process capability indices reflect the performance of key quality characteristics for a control process. Quality assurance in mass production is enabled by using statistical process control techniques. In this study, various statistical process control techniques were carried out using the measured values taken from the workpieces that represent the whole process in the medium sized company. The chances for using statistical techniques for quality estimation processes have been discussed. For this purpose, normal probability plots and histograms were prepared and the process capability indices were calculated. As a result of this study, it turned out that the process capability for the whole process was inadequate and the mass production was unstable. Some actions must be taken by engineers to improve the quality level by shifting the process mean to target value and reducing the process variation.
Citation - WoS: 1
Citation - Scopus: 1
Regression Based Neural Network Modeling for Forecasting of the Metal Volume Removal Rate in Turning Operations
(Carl Hanser Verlag, 2012) Kahraman, Funda; Esme, Ugur; Kulekci, Mustafa Kemal; Kazancoglu, Yigit
The present paper focuses on two techniques, namely regression and neural network, for predicting tool wear. Predicted values of tool wear by both techniques were compared with experimental values. Also, the effects of the main machining variables on tool wear have been determined. The metal volume removed (MVR) was taken as response (output) variable and cutting speed, feed rate, depth of cut and hardness were taken as input parameters, respectively. The relationship between tool wear and machining parameters was found out by direct measurement of the tool wear by MVR. The results showed the ability of regression and neural network models to predict the tool wear, accurately.
Citation - WoS: 1
Temperature Distribution of Multipass Tig Welded Aisi 304 L Stainless Steel
(Carl Hanser Verlag, 2011) Esme, Ugur; Bayramoglu, Melih; Serin, Hasan; Guven, Onur; Aydin, Hakan; Kazancoglu, Yigit
Tungsten inert gas welding (TIG) is one of the most important material-joining processes widely used in industry. AISI type 304L stainless steel plates with 8 and 10 mm thicknesses are widely used in the fabrication of pressure vessels and other components. These plates are mostly joined together by multipass welding methods. The temperature distribution that occurs during multipass welding affects the material microstructure, hardness, mechanical properties, and the residual stresses that will be present in the welded material. Very limited experimental data regarding temperature distribution during multipass welding of plates is available in the literature. Experimental work was carried out to find out the temperature distribution during multipass welding of the AISI 304L stainless steel plates. The temperature distribution curves obtained during the experiments are presented. The average maximum temperature rise during each pass of welding is calculated and plotted against the distance from the weld pad centre line. From these plots, the maximum temperature rise expected in the base plate region during any pass of welding operation can be estimated.
Citation - WoS: 3
Citation - Scopus: 3
Tensile Shear Strength and Elongation of Fsw Parts Predicted by Taguchi-Based Fuzzy Logic
(Carl Hanser Verlag, 2016) Kulekci, Mustafa Kemal; Esme, Ugur; Ocalir, Seref; Ustun, Deniz; Kazancoglu, Yigit
This paper represents the fuzzy logic model for modeling and prediction of tensile shear strength and percent elongation of parts produced by the friction stir welding (FSW) process. A Taguchi L-16 orthogonal array is used to plan and select the parameters and their levels. Weld travel speed, pin diameter and tool rotation are used as input variables. Therefore, a three-input and two-output fuzzy model is used to correlate these variables to the responses of tensile shear strength and percent elongation using the fuzzy rules generated based on experimental results. Close agreement is obtained between the fuzzy predicted and experimental results with the correlation coefficients of 0.931 and 0.895 for tensile shear strength and elongation, respectively.
Citation - WoS: 5
Citation - Scopus: 5
The Use of Artificial Neural Networks in Predicting Fatigue Life of Friction Stir Welded Lap Joints of Aa 5754
(Sampe Publishers, 2010) Esme, Ugur; Kulekci, M. Kemal; Kazancoglu, Yigit
Friction stir welding (FSW) is currently being widely investigated in the aerospace industry for joining high strength Al-alloys that are difficult to weld using conventional fusion techniques. The quality of the process mainly depends on the pin diameter, pin height, tool rotation and traverse speed. In the present work, an artificial neural network (ANN) method was used for modeling and predicting the fatigue life of friction stir welded lap joints of AA5754 aluminum alloy. The ANN model of fatigue life is developed with the welding parameters such as pin diameter, pin height, tool rotation, traverse speed and with the weld property of fatigue strength. The experimental results were trained in an ANN program and the results were compared with experimental values. It is observed that the experimental results coincided with ANN results.
Citation - WoS: 16
Citation - Scopus: 19
Use of Grey-Taguchi Method for the Optimization of Oblique Turning Process of Az91d Magnesium Alloy
(Carl Hanser Verlag, 2012) Buldum, Baris; Esme, Ugur; Kulekci, Mustafa Kemal; Sik, Aydin; Kazancoglu, Yigit
This study investigated the multi-response optimization of turning process for an optimal parametric combination to yield minimum cutting forces and surface roughness with maximum material removal rate (MRR) using the combination of Grey relational analysis (GRA) and Taguchi method. Nine experimental runs based on an orthogonal array of Taguchi method were performed to derive objective functions to be optimized within experimental domain. The objective functions have been selected in relation to parameters of cutting process: cutting force, surface roughness and MRR. The Taguchi approach followed by Grey relational analysis to solve the multi-response optimization problem. The significance of factors on overall quality characteristics of the cutting process has also been evaluated quantitatively by the analysis of variance method (ANOVA). Optimal results have been verified through additional experiments. This shows proper selection of the cutting parameters produces, high material removal rate with better surface roughness and lower cutting force.