Yazarlar
- Mahmat, Aybars(4)
- Tosun, Nihat(4)
- Alla, A.M.A.(1)
- Aslan, N.(1)
- AǦar, Salih(1)
- Aǧar, Salih(1)
- Dalgıç, Aras(1)
- Dogan, Gurkan(1)
- Ergen, Burhan(1)
- Rasul, Sleman Yahya(1)
- Say, Y.(1)
- Tosun, Gul(1)
- Özmen, H.(1)
Yayınlar
- MakaleYalnız künye2026Scopus SJRQ2Investigation of the effect of ultrasonic assisted milling and minimum quantity lubrication methods on the machinability of Hardox 500 steel
Dalgıç, Aras; Mahmat, Aybars
Hardox steel is widely used in agriculture, mining and transportation due to its mechanical properties such as high wear resistance, high impact resistance, high hardness, high durability and long life. The machinability of Hardox 500 is difficult as its high hardness and wear resistance lead to tool wear and low machining speed. Recently, various processing and cooling methods have been developed to increase machinability. Ultrasonic assisted milling (UAM), one of these methods, is a method used as an alternative to conventional milling (CM) in the milling of traditionally difficult-to-machine materials. In addition, minimum quantity lubrication (MQL) is a cooling method used to provide lubrication and cooling in the cutting area. In this study, the impacts of machining method, feed rate and spindle speed on cutting force, surface roughness and tool wear in milling of Hardox 500 steel were investigated. In the MQL method, mixtures with nano-sized SiC particles were obtained and applied to the cutting area. In the study, MQL reduced cutting forces by up to 19 %, surface roughness by 18 %, and tool wear by 30 % compared to dry machining, while UAM further decreased cutting forces by 17 %, surface roughness by 15 %, and tool wear by 12 % compared to CM. These results demonstrate that MQL and UAM significantly enhance machining performance over conventional and dry methods.
- MakaleAçık Erişim2025Scopus SJRQ2Modeling and analysis of WEDM with a new deep neural network
Mahmat, Aybars; Dogan, Gurkan; Ergen, Burhan; Tosun, Nihat
In some cases, the models targeted in machining processes are difficult to apply to industrial production. Artificial intelligence techniques applied to industrial production methods in recent times eliminate these problems in machining. The use of deep learning methods in solving these problems has recently increased. In this study, a new deep neural network (DNN) based on artificial neural networks is proposed to model the machining of AISI4140 steel by wire electrical discharge machining (WEDM). The proposed DNN model predicts surface roughness (SR) and wire wear ratio (WWR), which are the most important inferences in cutting with WEDM. Obtaining inferences such as SR and WWR in a real experimental environment means a lot of time and cost. With the proposed model, there is a significant reduction in time and cost factors. The dataset used to train and test the proposed model was obtained from the real experimental environment. For training and testing the model, the data set is divided into two parts: 20% test data and 80% training data. In the experimental tests carried out with the proposed model, error rates such as Mean Absolute Error (MAE), R2, and Mean Squared Error (MSE) accuracy rate between SR and WWR values estimated according to the SR and WWR values obtained from the real environment were examined. MAE, MSE, and R2 for SR reached 0.0495, 0.0005, and 98.48%, respectively, while MAE, MSE, and R2 for WWR reached 0.0156, 0.0036, and 98.39%, respectively. These results of the proposed model provided a lower error rate and higher accuracy than the state-of-the-art models in the literature.
AtıfScopus5WoS5OpenAlex7
İncele - MakaleAçık Erişim2024Scopus SJRQ3ENHANCING MILLING PERFORMANCE OF 6061 ALUMINUM ALLOY WITH NANOCUTTING FLUID AND MQL
Tosun, Nihat; Rasul, Sleman Yahya; Mahmat, Aybars; Tosun, Gul
During the machining of aluminum alloys, the adhesion of chips to the tool affects the performance characteristics. Today, different cooling systems are used to eliminate these negativities. In this study, the effects of end milling using HSS and carbide cutting tools of 6061-T6 aluminum alloy on surface roughness, chip thickness ratio and tool wear were examined using different cooling techniques (dry, minimum quantity lubrication (MQL) and nanocutting fluid). Different cutting speeds (180, 200, 220 m/min) and different feed rates (0.05, 0.06, 0.07 mm/rev) were used in the experiments. According to experimental findings, tool wear and surface roughness decreased at low cutting speed and feed rate by using nanocutting fluid with carbide cutting tools. It has been observed that the chip thickness ratio increases with high cutting speeds using nanocutting fluid and decreases with dry machining and high feed rates. The best milling performance of the aluminum alloy was achieved in experiments using carbide cutting tools and nanocutting fluid.
AtıfScopus4WoS4OpenAlex4İncele - MakaleAçık Erişim2023Scopus SJRQ1Influence of chemical etchings on surface properties, in-vitro degradation and ion releases of 316l stainless steel alloy for biomedical applications
Say, Y.; Aslan, N.; Alla, A.M.A.; Özmen, H.
Different surface treatments are applied to improve the surface properties of metallic biomaterials. Chemical etching is one of the common techniques used for roughening the surface. In this regard, the effects of different chemical media on the surface roughness, degradation, and ion release of 316L SS steel were investigated in this study. The 316L SS steel was exposed to chemical etching in six different chemical media including HNO3, H2SO4, HCl, HClO4, NaOH and Na2CO, at four different concentrations (1, 2, 4, and 8 Molar), and at three immersion times (10, 60, and 180 min). SEM, EDS, and XRD analyses were used to examine the morphological and chemical impacts of chemical etching on sample surfaces, and roughness was measured on all sample surfaces. The effect of surface treatment on the degradation and ion release of the samples was comparatively examined. Characterization analyses indicated that the HNO3, H2SO4, and HCl media did not cause a significant reaction on the surface of the 316L SS. On the other hand, different phases were observed on the sample surfaces exposed to HClO4, NaOH, and Na2CO3 media. It was determined that the roughness had no linear correlation with the concentration and immersion time, and similarly, the degree of degradation and amount of ion release displayed no change depending on the roughness. Samples etched in H2SO4, HClO4, NaOH and Na2CO3 provided the highest roughness. It was found that H2SO4 caused a significant increase in the amount of ion release.
AtıfScopus18WoS17OpenAlex20İncele - MakaleAçık Erişim2023Scopus SJRQ3EFFECT of the COOLING with AIR and WATER VAPOR on MILLING PERFORMANCES
Mahmat, Aybars; Tosun, Nihat; AǦar, Salih
This study aims to investigate experimentally and analytically the effects of different machining parameters such as cooling methods and cutting tool materials on surface roughness and chip thickness ratio for milling of AA7075-T6 aluminum alloy. The carbide and high-speed steel (HSS) end mills were used as cutting tools and the conventional, vapor, and compressed air were used as cooling methods in the experiments. The experiment conditions for compressed air at the cutting zone were 6 bar pressure and 30 m/s speed flow rate. A mixture of boron oil and water (1/20 mixture ratio) was used as cutting fluid in conventional cooling. The study was carried out using three levels of feed rates (20, 40, 80 mm/min), rotational speeds (780, 1330, 2440 rpm), and a constant 2 mm deep cut. As a result of the experiments, the surface roughness values increased with the increasing levels of feed rate. Besides surface roughness values decreased with increasing levels of the rotational speed. In addition, a better surface quality was obtained in milling processes by using carbide cutting tools compared to HSS tools. It was concluded that the most important parameter affecting the surface roughness and chip thickness ratio is feed rate and the rotational speed, respectively. Better surface roughness and chip thickness ratio were obtained from the vapor processing than the conventional and compressed air.
AtıfScopus2WoS1İncele - MakaleAçık Erişim2021Scopus SJRQ3Ultrasonic assisted turning of AISI 52100 steel using nanoparticle-MQL method
Aǧar, Salih; Tosun, Nihat
High cutting force and high cutting tool-chip interface temperature occur during machining of high strength materials like AISI 52100 by using conventional turning method and this makes to the difficult machining operation. Besides, in conventional turning (CT) of these materials, which has high abrasion resistance and hardness properties, an additional process such as grinding is required to achieve the desired surface quality. Ultrasonic assisted turning (UAT) method has been widely used in the machining industry in recent years, as it exhibits better surface quality, lower cutting forces, and cutting temperature than the CT method. This paper focused on experimentally and statistically determining the effects of different cutting parameters and cooling conditions (dry and minimum quantity lubrication-MQL) on surface roughness, workpiece surface texture, tangential direction cutting force, and cutting tool-workpiece interface temperature in the machining of AISI 52100 material by using UAT and CT methods. The experimental results revealed that significant improvements determined in the cutting forces and the surface roughness occurred in UAT compared to CT in all the cooling conditions. However, the increasing cutting speeds caused to observe higher interface temperature values in dry turning by the UAT method. Variance Analysis (ANOVA) was carried out to determine the significance grade of independent variables on dependent variables. According to ANOVA results, while the cutting speed is the most important factor on the surface roughness and the cutting zone temperature, and the cooling method is the most important factor on the cutting force. The effects of turning methods on corresponding surface topography, including surface defects, were evaluated. It is determined that in the surface topography analysis, feed marks are the main texture of the workpiece in the CT method while micro-level indentations and protrusions occurred on the workpiece surface in the UAT method.
AtıfScopus14WoS12OpenAlex14İncele