Investigation of the Relationship Between Power Consumption and Noise Level During Hard Turning of CBN Tools and DIN 1.2367 Steel

Akkaş, Mehmet; Yavuz, Mehtap; Şahinoğlu, Abidin

doi:10.29109/gujsc.891815

Cited by 2 publications

(2 citation statements)

References 23 publications

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“…From all the graphs, it is evident that the best results are obtained from the cooling model with nano-MQL. Other researchers have also confirmed the dominant role of nano-MQL in sound intensity [44,45]. The findings suggest that the increase in parameters such as tool wear, surface roughness, and current plays a role in increasing cutting sound [46].…”

Section: Sound Intensitymentioning

confidence: 59%

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Exploring the Impact of Turning of AISI 4340 Steel on Tool Wear, Surface Roughness, Sound Intensity, and Power Consumption under Dry, MQL, and Nano-MQL Conditions

Fedai

2023

Preprint

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Optimizing input parameters not only improves production efficiency and processing quality but also plays a crucial role in the development of green manufacturing engineering practices. The aim of the present study is to conduct a comparative evaluation at cutting performance and machinability process during the turning of AISI 4340 steel under different cooling conditions. The study analyses cutting operations during turning using dry, minimum quantity lubrication (MQL), and nano-MQL. As control parameters in the experiments, three different cooling types, cutting speed (100, 150, 200 m/min), and feed rate (0.1, 0.15, 0.20 mm/rev) levels were applied. The experiment results present that the optimal output values are found as Vb=0.15 mm, Ra=0.81µm, 88.1 dB for sound intensity, and I=4.18 A for current. Moreover, variance analysis (ANOVA) was performed to determine the effects of input parameters on response values. Under dry, MQL, and nano-MQL processing conditions, parameters affecting tool wear, surface roughness, current by the motor shaft, and sound level were examined in detail, along with the chip morphology. The responses obtained were optimized according to the Taguchi S/N method. As a result of optimization, it was concluded that the optimum values for cutting conditions (A3B1C1) were nano-MQL cooling and V=100 m/min, f=0.1 mm/rev cutting. Last but not least, it was observed that there was a 13% improvement in tool wear, 7% in current, 9% in surface roughness, and 8% in sound intensity compared to the standard conditions. In conclusion, it was determined that nano-MQL and the lowest level of cutting and feed rate values provided the optimum results.

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Section: Sound Intensitymentioning

confidence: 59%

Section: Sound Intensitymentioning

confidence: 72%

Exploring the Impact of Turning of AISI 4340 Steel on Tool Wear, Surface Roughness, Sound Intensity, and Power Consumption under Dry, MQL, and Nano-MQL Conditions

Fedai

2023

Preprint

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Effect of cutting parameters on the machinability of X37CrMoV5-1 hot work tool steel

Özdemir

2022

Materials Testing

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Hard turning was carried out on an X37CrMoV5-1 hot work tool steel with a hardness of 50 ± 2 HRC on a computer numerical control lathe, using a ceramic insert without the use of a coolant. The cutting parameters included three different cutting speeds, three different feed rates, and three different cutting depths. A full factorial design (FFD) was created, and 33=27 experiments were carried out. The effects of cutting parameters on cutting force (Fc), surface roughness (Ra), material removal rate (MRR), specific cutting energy (SCE), current (Cu), and sound intensity (SI) were investigated. As a result of the analysis of variance (ANOVA), the effect ratios of cutting parameters on Fc, Ra, MRR, SCE, Cu, and SI were examined, and important parameters were determined. As a result, the effective rates of the feed rate, which is the most effective parameter, on Fc, Ra, and MRR were determined as 61.72, 95.90, and 61.70%, respectively. The cutting depth was 54.81 and 34.37% on SCE and SI, respectively, and the cutting speed was effective on Cu by 79.87%. By using FFD and response surface methodology (RSM), the regression equations of the results of Fc, Ra, MRR, SCE, Cu, and SI were extracted, and r 2 values were examined. In the validation experiments performed after the optimization experiments, the experimental results were estimated using FFD, RSM, and Taguchi method, and the differences between them were analyzed.

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Investigation of the Relationship Between Power Consumption and Noise Level During Hard Turning of CBN Tools and DIN 1.2367 Steel

Cited by 2 publications

References 23 publications

Exploring the Impact of Turning of AISI 4340 Steel on Tool Wear, Surface Roughness, Sound Intensity, and Power Consumption under Dry, MQL, and Nano-MQL Conditions

Exploring the Impact of Turning of AISI 4340 Steel on Tool Wear, Surface Roughness, Sound Intensity, and Power Consumption under Dry, MQL, and Nano-MQL Conditions

Effect of cutting parameters on the machinability of X37CrMoV5-1 hot work tool steel

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