Multi response optimization of nozzle process parameters in MQL assisted face milling of AISI 52,100 alloy steel using TGRA

Rana, Mohit; Singh, Talvinder; Saini, Abhineet; Singh, Jaswinder; Sharma, Vijay Kumar; Singh, Maninderjeet; Rooprai, Ranbir Singh

doi:10.1016/j.matpr.2021.02.830

Cited by 11 publications

(3 citation statements)

References 13 publications

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“…Maruda, et al [21] studied the effects of nozzle outlet velocity, nozzle distance, angle of the nozzle, and diameters of oil mist on machining performance, and found that a smaller droplet of mist can improve the machining performance. Rana, et al [22] analyzed the effects of the nozzle parameters, elevation angle, and the spray distance on the processing quality and temperature, and obtained the optimal parameters. However, most of the studies mainly focused on the nozzle inlet conditions and relative positions, and there were few studies on the internal parameters of the nozzle, so it has a certain research value.…”

Section: Introductionmentioning

confidence: 99%

Parameter optimization of the MQL nozzle by the computational fluid dynamics

Yan,

Luo,

Jiang

et al. 2024

Int J Adv Manuf Technol

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Minimum quantity lubrication (MQL) has achieved a good effect in precision machining. The geometric parameter of the nozzle has an important effect on the performance of MQL. In order to improve and optimize the performance of MQL, the orthogonal experimental method was adopted in this paper, and ANSYS Fluent software was used to carry out the computational fluid dynamics (CFD) simulation and the simulation data were statistically analyzed. The effects of six influencing factors (i.e. width of gas-phase narrow flow region, taper, output tube length, length of gas-phase narrow flow region, output aperture and pressure) on the performance of MQL were studied. The results showed that the primary and secondary order of the six influencing factors was different under different evaluation criteria. The most important parameter affecting the composite index was the absolute gas velocity at 0.1m away from the outlet. The optimal combination of the geometric parameters of the nozzle was output aperture of 2 mm, taper of 40 degrees, length of gas-phase narrow flow region of 1.5 mm, width of gas-phase narrow flow region of 0.3 mm, output tube length of 15.5 mm, and pressure of 5 bar.

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Section: Introductionmentioning

confidence: 99%

Parameter optimization of the MQL nozzle by the computational fluid dynamics

Yan,

Luo,

Jiang

et al. 2024

Int J Adv Manuf Technol

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“…The results confirmed the experimental parameters. Rana et al [ 29 ] evaluated the surface roughness in machining under the MQL condition. The experimental plan was created with the full factorial design method.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Tool Wear, Surface Roughness, Cutting Forces, Tool Tip Temperature, and Chip Shape during Sustainable Turning of Bearing Steel

et al. 2023

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In this study, a comparison of measured cutting parameters is discussed while machining AISI 52100 low-alloy hardened steel under two different sustainable cutting environments, those in which a dry and minimum quantity lubrication (MQL) medium are used. A two-level full factorial design method has been utilized to specify the effect of different experimental inputs on the turning trials. Experiments were carried out to investigate the effects of three basic defining parameters of turning operation which are namely cutting speed, cutting depth, feed rate effects and also the effects of the cutting environment. The trials were repeated for the combination of different cutting input parameters. The scanning electron microscopy imaging method was used to characterize the tool wear phenomenon. The macro-morphology of chips was analyzed to define the influence of cutting conditions. The optimum cutting condition for high-strength AISI 52100 bearing steel was obtained using the MQL medium. The results were evaluated with graphical representations and they indicated the superiority of the pulverized oil particles on tribological performance of the cutting process with application of the MQL system.

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“…In the metal cutting process, surface roughness Ra is often considered the most important criterion. Depending on the range of roughness Ra, suitable cutting techniques such as milling and grinding are applied [5]. The experimental research about the influence of cutting parameters on surface quality and the relationship between them is established as the regression models that have been published to improve product quality, especially surface roughness [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Investigation and optimization of parameters in face milling of S50C steel under MQL system

Nguyen¹,

Pham²

2023

J Appl Eng Science

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This paper aims to investigate cutting and lubrication parameters on surface roughness, cutting force, and material removal rate in face milling of JIS S50C carbon steel under a peanut oil-assisted Minimum Quantity Lubricant system. The five 3-level cutting process parameters were considered variants, including cutting speed, feed rate, depth of cut, air pressure, and lubrication flow. The experimental design was based on Taguchi's orthogonal array L27. The Analysis of variance is used to analyze the effect of cutting parameters and lubrication conditions on the surface roughness and cutting force. In addition, both regression optimizer procedures based on regression models and the Multi-Criteria Decision Making method were successfully applied to find the optimum conditions of the cutting parameter. The results showed the advantage and disadvantages of each technique. The Multi-Objective Optimization by Ratio Analysis was used in finding the best alternative. However, these values may not be an optimum condition. Mathematically, a regression optimizer may better determine the optimal value.

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Multi response optimization of nozzle process parameters in MQL assisted face milling of AISI 52,100 alloy steel using TGRA

Cited by 11 publications

References 13 publications

Parameter optimization of the MQL nozzle by the computational fluid dynamics

Parameter optimization of the MQL nozzle by the computational fluid dynamics

Comparison of Tool Wear, Surface Roughness, Cutting Forces, Tool Tip Temperature, and Chip Shape during Sustainable Turning of Bearing Steel

Investigation and optimization of parameters in face milling of S50C steel under MQL system

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