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- MakaleAçık Erişim2025Scopus SJRQ2Ultrasonic-assisted high-speed micro-milling of Ti6Al4V
Mahmat, Aybars; Agar, Salih; Tosun, Nihat
In this study, the effects of different cooling techniques and process parameters on the performance characteristics of ultrasonic and conventional micro-milling (1-micron fixed amplitude, 20 and 30 kHz frequencies) of Ti6Al4V alloy were experimentally investigated. The impact of independent factors on tool life, cutting force, surface topography, surface roughness and cutting temperature was determined in order to find out machinability characteristics in this paper. Machining operations were performed under 20,000, 40,000 and 60,000 rpm revolution speed. The cutting depth and feed rate of the machining were kept fixed at 0.02 mm and 0.66 mm/s, respectively. Uncoated carbide and TiSiN-coated carbide cutting tools were used in machining operations. Dry machining and two different minimum quantity of lubrication (MQL) methods were used as cooling methods. According to the results achieved in the existing study, the ultrasonic micro-milling improved the surface roughness, reduced cutting forces, cutting zone temperature, and cutting tool wear. It was also found that MQL methods among other methods used in the present study have a greater effect on performance characteristics. As the spindle speed increased, the workpiece surface roughness, cutting force and tool life decreased, while the cutting zone temperature increased.
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İncele - 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.
AtıfScopus5WoS5OpenAlex7İncele - MakaleYalnız künye2025Scopus SJRQ2Experimental comparison of conventional and ultrasonic-assisted high-speed drilling of glass fiber reinforced epoxy composites
Ağar, Salih; Mahmat, Aybars; Doğan, Akar
Glass fiber reinforced epoxy composites are favored in several industries, including automotive and aerospace, owing to their superior strength-to-weight ratio. Drilling is a prevalent machining procedure employed to add fasteners for laminate assembly. Nonetheless, drilling these composites presents significant challenges due to the abrasive characteristics of the reinforcement, necessitating an examination of machining performance. During the drilling of composites, cutting temperature, thrust force, and delamination damage are primary concerns. In recent years, high-speed ultrasonic drilling, an innovative machining technique designed to address these challenges, has garnered significant interest. This investigation involved high-speed ultrasonic drilling and conventional drilling of glass fiber reinforced epoxy material. In the studies, optimal conditions were studied by evaluating thrust force, cutting temperature, and delamination damage by varying speeds, feed rates, and frequencies. The thrust force was 11 N in the traditional approach at 40,000 rpm, but it was recorded at 9 N with the ultrasonic method. Moreover, with ultrasonic drilling, cutting temperatures decreased by over 25% relative to traditional drilling, attributable to the harmonic motion that dissipates heat in the drilling zone. Analysis of the drilling region revealed a notable enhancement in damage, particularly in delamination, with the application of ultrasonic drilling. The experimental results indicate that ultrasonic machining enhances machining performance.
- MakaleAçık Erişim2024Scopus SJRQ1Investigation of the effect of electrophoresis-assisted milling on machinability
Mahmat, Aybars
In this study, the electrophoresis-assisted milling (EAM) method, an alternative method to the conventional milling (CM) method, was proposed to increase the machinability of Ti6Al4V alloy, which is difficult to machine. The nanoparticles in the electrophoresis solution generated an electric field. This electric field collected abrasive particles around the cutting tool, and the machining quality was improved. The impacts of different cutting parameters on the performance characteristics were examined using both EAM and CM methods. The experimental results demonstrate that the proposed EAM method significantly improves these performance characteristics. In addition, increasing spindle speed increased tool wear and cutting temperature for both machining methods; It was observed that it reduced cutting force and surface roughness. It was concluded that as the feed rate increased, tool wear, cutting temperature, cutting force, and surface roughness increased. The experimental results showed that feed rate, machining method, and spindle speed affect machining quality. In conclusion, the experimental results significantly impact improving the machining performance of the EAM method.
AtıfScopus1WoS2OpenAlex2İncele