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    Analysis of cutting parameters and cooling/lubrication methods for sustainable machining in turning of Haynes 25 superalloy
    (Elsevier Sci Ltd, 2016) Sarikaya, Murat; Yilmaz, Volkan; Gullu, Abdulkadir
    While the use of cutting oils in machining operations facilitate material removal, the use of these oils are questioned based on the risks they pose for operator health and the environment. As an alternative to the excessive use of cutting oils, the Minimum Quantity Lubrication (MQL) method aims to reduce the use of cutting fluids as a step in achieving clean, environmentally friendly, and sustainable manufacturing. In this study, the machinability of cobalt-based Haynes 25 superalloy, which is a difficult-to-machine alloy used in strategic applications, was investigated under three separate-cutting methods (dry, conventional cooling and lubrication, and minimum quantity lubrication). The experiments were conducted on a CNC turning machine using uncoated carbide cutting tools using four separate cutting speeds (15 m/min, 30 m/min, 45 m/min, and 60 m/min), three separate feed, rates (0.08 mm/rev, 0.12 mm/rev and 0.16 mm/rev), and a fixed depth of cut value (1 mm). To determine the relationships among machining parameters and outputs, tool wear (VN) and surface roughness (R-a) values were measured. Additionally, the wear mechanisms acting on the cutting inserts were determined using scanning electron microscope (SEM). Following the conclusion of experiments, the Taguchi's signal to noise ratio (S/N) analysis was used to establish the optimal set of cutting parameters. In conclusion, when the MQL method was employed in conjunction with high pressure, the amount of oil used was reduced while the machinability of the material was improved. Tests conducted under all three methods of cutting revealed poor surface roughness at low cutting speeds, and high tool wear at high cutting speeds. (C) 2016 Elsevier Ltd. All rights reserved.
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    DEEP MICRO-HOLE DRILLING FOR HADFIELD STEEL BY ELECTRO-DISCHARGE MACHINING (EDM)
    (Inst Za Kovinske Materiale I In Tehnologie, 2015) Yilmaz, Volkan; Sarikaya, Murat; Dilipak, Hakan
    In this study, a new system for drilling deep micro-holes was designed for Hadfield steel (which is difficult to process with classical methods) with the electro-discharge-machining method (EDM) and the system was experimentally examined. The tests were carried out at three different discharge currents (6, 12 and 24) A, three different electrode-tool rotational speeds (200, 400 and 600) r/min, three different dielectric spray pressures (40, 80 and 120) bar, a constant pulse duration (12 mu s) and a constant pulse interval (3 mu s). After the tests the effects of the processing parameters on the basic performance outputs (the material removal rate -MRR), the electrode wear rate (EWR) and the relative wear (RW)) were investigated. Additionally, an analysis of variance (ANOVA) was also applied to identify the most significant factor. Optimum operating parameters were determined using the desirability-function analysis through the response surface methodology (RSM). It was found that the most effective variable affecting the MRR, EWR and RW was the discharge current. The discharge current was found to be the most significant control factor influencing the performance of the machining process.
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    Frezeleme islemlerinde kesme kuvveti, titresim ve yüzey pürüzlülügü sonuçlarinin modellenmesi
    (Erciyes Üniversitesi, 2014) Yilmaz, Volkan; Dilipak, Hakan; Sarikaya, Murat; Yilmaz, Ceren Yaman; Özdemir, Mustafa
    Bu çalismada, frezeleme islemlerinde kesme parametrelerinin kesme kuvveti, titresim ivmesi ve yüzey pürüzlülügü üzerindeki etkisi çoklu regresyon analiziyle arastirilmistir. Deneylerde isleme parametreleri olarak 132, 220, 308 m/min kesme hizi, 0,05, 0,1, 0,15, 0,2 mm/tooth ilerleme, 1, 1,5 mm kesme derinligi ve 1, 2, 4 adet sayilardaki kesici uç kullanilmistir. Bu isleme parametreleri ile 100x50x20 mm ebatlarinda AISI 1050 deney malzemesi üzerinden talas kaldirilmistir. Deney sonuçlarina etki eden parametrelerin oranlari Minitab 15.0 yazilimi kullanilarak çoklu regresyon analiziyle ANOVA (Varyans Analizi) tablolari olusturularak bulunmustur. Ayrica ara degerlerin hesaplanmasinda sonuçlar için üç ayri matematiksel formül gelistirilmis ve tahminsel sonuçlar elde dilmistir.
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    Investigation of deep-drilled micro-hole profiles in Hadfield steel
    (Carl Hanser Verlag, 2016) Yilmaz, Volkan; Sarikaya, Murat; Dilipak, Hakan
    Hadfield steel, due to its high manganese content, is difficult to drill and work-hardens very quickly. In this study, Hadfield steel material was drilled with micro-size deep holes using the electrical discharge machining (EDM) technique, and hole diameter values were examined for specific machining parameters. Experiments were carried out with three different discharge currents (6, 12 and 24 A), three different electrode rotational speeds (200, 400 and 600 rev x min(-1)), three different pulse durations (12, 50 and 100 mu s), a fixed dielectric spray pressure (40 bars) and a fixed pulse interval (3 mu s). It was determined that the hole profiles obtained following the tests are directly related to the machining parameters, and that the resulting average overcut (AOC) and taper (Tp) values increased with discharge current, electrode rotational speed and pulse duration. Analysis of variance (ANOVA) conducted demonstrates that pulse duration is the dominant parameter affecting AOC, whereas pulse duration has the highest effect on Tp. When determination coefficients and normal probability plots were compared for the mathematical models obtained from analyses conducted for the prediction of test values, it was observed that the models obtained by quadratic regression analysis exhibited a better performance than the models produced by linear regression analysis.
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    Modeling and multi-response optimization of milling characteristics based on Taguchi and gray relational analysis
    (Sage Publications Ltd, 2016) Sarikaya, Murat; Yilmaz, Volkan; Dilipak, Hakan
    This article focuses on experimental investigation and effective approach to optimize the milling characteristics with mono and multiple response outputs such as vibration signals, cutting force, and surface roughness. To achieve this goal, experiments were designed based on Taguchi's L-18 (2(1)x3(3)) orthogonal array. During the milling of AISI 1050 steel, process performance indicators such as vibration signals (RMS), cutting force (Fx), and surface roughness (Ra) were measured. The effect of process parameters such as depth of cut, feed rate, cutting speed, and number of insert on RMS, Fx, and Ra were investigated and parameters were simultaneously optimized by taking into consideration the multi-response outputs using Taguchi-based gray relational analysis. Taguchi's signal-to-noise ratio was employed to obtain the best combination with smaller-the-better and larger-the-better approaches for mono- and multi-optimization, respectively. Analysis of variance was conducted to determine the importance of process parameters on responses. Mathematical models were created, namely, RMSpre, Ra-pre, and Fx(pre), using regression analysis. According to the multi-response optimization results, which were obtained from the largest signal-to-noise ratio of the gray relational grade, it was found out that the optimum combination was depth of cut of 1mm, feed rate of 0.05mm/rev, cutting speed of 308m/min, and number of insert of 1 to minimize simultaneously RMS, Fx, and Ra. It was obtained that the percentage improvement in gray relational grade with the multiple responses is 42.9%. It is clearly shown that the performance indicators are significantly improved using this approach in milling of AISI 1050 steel. Moreover, analysis of variance for gray relational grade proved that the feed rate is the most influential factor as the minimization of all responses is concurrently considered.
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    Optimization and predictive modeling using S/N, RSM, RA and ANNs for micro-electrical discharge drilling of AISI 304 stainless steel
    (Springer London Ltd, 2018) Sarikaya, Murat; Yilmaz, Volkan
    In present work, micro-deep holes on AISI 304 stainless steel were drilled via electrical discharge machining (EDM) method. In the first phase of this work, the effect of test parameters on the drilling performance and the profile of drilled holes were investigated experimentally. Test parameters including discharge current, dielectric spray pressure and electrode tool rotational speed were taken and then the machining rate (MR), electrode wear rate (EWR), average over-cut (AOC) and taper angle (TA) were measured in order to assess the drillability of EDM. After experimental study, an analysis of variance was performed to identify the effect of the importance of test parameters on experiment outputs. In the second phase of this study, optimum process parameters were determined using signal-to-noise analysis and response surface methodology (RSM) for mono-optimization and multi-response optimization, respectively. In the last phase, regression analysis and artificial neural network (ANN) models for predicting the MRR, EWR, AOC and TA. As a result of experimental analysis, discharge current was the most important parameter for micro-drilling with EDM. It was found out that this parameter influenced positively MR, while it has negatively an effect on EWR, AOC and TA. Mathematical model based on ANNs exhibited a successful performance for predication of outputs. Optimum process parameters which were discharge current of 10.18 , dielectric liquid pressure of 58.78 bar and electrode tool rotational speed of 100 rpm for multi-objective optimization were determined through RSM with desirability function analysis in micro-deep hole EDM drilling of AISI 304 stainless steel.
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    Optimization of the wear behavior of uncoated, TiN and AlTiN coated cold work tool steel 1.2379 using response surface methodology
    (Carl Hanser Verlag, 2016) Bulbul, Ali Emrah; Dilipak, Hakan; Sarikaya, Murat; Yilmaz, Volkan
    In this study, the wear behavior of uncoated, TiN and AlTiN coated cold work tool steel 1.2379 which is widely used in the mold industry was investigated experimentally. Heat treatment was applied to the specimens, then TiN and AlTiN PVD coating process was performed. The wear tests were carried out at 0.5 m x s(-1) sliding speed, 5, 10 and 15 N loads and 120 m sliding distance by using reciprocating abrasion device. The microhardness was measured and metallographic tests of the samples were investigated by SEM and EDS analysis. In order to examine the effect of process parameters on wear results, a statistical method such as analysis of variance (ANOVA) was employed. A mathematical model was created by using regression analysis based on both linear model and quadratic model for predicted wear value. Process parameters were optimized using response surface methodology with desirability function analysis. It is observed that the uncoated specimens worn approximately two times more than AlTiN coated and one time more than TiN coated. In the SEM images and EDS analysis, it is seen that the coating is spread uniformly on the materials.