A comprehensive review on minimum quantity lubrication (MQL) in machining processes using nano-cutting fluids

Said, Zafar; Gupta, Munish Kumar; Hegab, Hussien; Arora, Neeti; Khan, Aqib Mashood; Jamil, Muhammad; Bellos, Evangelos

doi:10.1007/s00170-019-04382-x

Cited by 187 publications

(59 citation statements)

References 149 publications

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“…Da Silva et al [ 43 ] focused on surface integrity and tool life under different cooling conditions, and high-pressure coolant provided the best tool life. Said et al [ 44 ] investigated the studies on using nano-cutting fluids comprehensively. Sarıkaya et al [ 45 ] studied the effects of dry, conventional cooling and minimum quantity lubrication methods on tool wear and surface roughness.…”

Section: Introductionmentioning

confidence: 99%

Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140

Kuntoğlu

Aslan

Sağlam

et al. 2020

Sensors

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Optimization of tool life is required to tune the machining parameters and achieve the desired surface roughness of the machined components in a wide range of engineering applications. There are many machining input variables which can influence surface roughness and tool life during any machining process, such as cutting speed, feed rate and depth of cut. These parameters can be optimized to reduce surface roughness and increase tool life. The present study investigates the optimization of five different sensorial criteria, additional to tool wear (VB) and surface roughness (Ra), via the Tool Condition Monitoring System (TCMS) for the first time in the open literature. Based on the Taguchi L9 orthogonal design principle, the basic machining parameters cutting speed (vc), feed rate (f) and depth of cut (ap) were adopted for the turning of AISI 5140 steel. For this purpose, an optimization approach was used implementing five different sensors, namely dynamometer, vibration, AE (Acoustic Emission), temperature and motor current sensors, to a lathe. In this context, VB, Ra and sensorial data were evaluated to observe the effects of machining parameters. After that, an RSM (Response Surface Methodology)-based optimization approach was applied to the measured variables. Cutting force (97.8%) represented the most reliable sensor data, followed by the AE (95.7%), temperature (92.9%), vibration (81.3%) and current (74.6%) sensors, respectively. RSM provided the optimum cutting conditions (at vc = 150 m/min, f = 0.09 mm/rev, ap = 1 mm) to obtain the best results for VB, Ra and the sensorial data, with a high success rate (82.5%).

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Section: Introductionmentioning

confidence: 99%

Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140

Kuntoğlu

Aslan

Sağlam

et al. 2020

Sensors

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“…Second, we discuss the influence of NGPs on lubrication, and it is crucial since the lubrication of cutting fluid is directly related to the broaching force and tool life [4,14,20,27]. After the droplets sprayed by MQL enter the cutting zone, viscosity is one of the main factors that affect lubrication performance [27]. The flow of high-viscosity cutting fluid is restricted by the viscous force, and thus, the fluid has poor flowability, which results in difficulty in penetrating the tool-chip slit.…”

Section: Influence Of Ngp On Lubricationmentioning

confidence: 99%

“…Secondly, the broaching force is usually very large; consequently, long-term broaching under dry or semi-dry conditions could greatly reduce the tool life. Although the MQL technology has been applied to many processing fields [25][26][27], the pouring of mineral oil-based cutting fluid with high viscosity is still adopted in broaching, at the cost of harm to the human body and environment.…”

Section: Introductionmentioning

confidence: 99%

Penetration and lubrication evaluation of vegetable oil with nanographite particles for broaching process

2020

Friction

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With increasing environmental concerns, the substitution of mineral oil-based cutting fluid has become an urgent issue. Using vegetable soybean oil as base fluid, nanofluid cutting fluids (NFCFs) were prepared by adding different weight concentrations of nanographite particles (NGPs), and their penetration and lubrication performances were studied. A novel simulated tool-chip slit with micrometer-sized geometry was manufactured to evaluate and quantify the penetration rate of the NFCFs by image analysis approach. Moreover, a large number of comparative experiments on the closed-type broaching machine were carried out to compare the performance of the proposed NFCFs and a commercial cutting fluid in terms of cutting force, workpiece surface roughness, and metal chip. It is found that there is an optimal NGP concentration in NFCF for practical cutting applications. When the concentration of NGP is 0.4 wt%, the broaching process lubrication exhibits an ideal mixed lubricate state, resulting in minimal friction resistance, and thus, both the cutting force and chip curling angle reach their corresponding best values. Moreover, the proposed NGP-based vegetable-oil cutting fluid exhibits excellent environment-friendliness and low-cost consumption in the minimal quantity lubrication (MQL) method; this demonstrates its potential for replacing the traditional broaching cutting fluid.

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“…In [18], Ramanuj Kumar It is noticeable that most publications suggested further investigation with machining parameters to improve effectiveness while utilizing nanoparticles in the MQL technique. After a comprehensive review [19], Zafar Said et al concluded that nanofl uid with the MQL technique was one of the best methods for lubricant, yet encouraged future researches for optimum effects. In this work, cutting speed, feed rate, depth of cut, and nanoparticle concentration were used as parameters to optimize the milling process of SKD61 steel regarding the surface roughness under MQL.…”

Section: Introductionmentioning

confidence: 99%

An empirical investigation of SIO2 nano concentration under MQL on surface roughness in hard milling of jis SKD61 steel

Tam¹,

Phan²

2020

J Appl Eng Science

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Surface roughness is an important assessment of metal cutting. This paper presents an empirical investigation of cutting conditions on the surface roughness in hard milling SKD61 steel. The cutting speed, feed rate, depth of cut, and nanoparticle concentration were taken as the parameters in the experimental setup. The mixer of SiO 2 particles with a size of 100nm based on cutting oil CT232 was used with 3 levels of concentration: 0, 2, and 4wt%. Twenty-seven experiments were carried out based on the DOE method developed by G. Taguchi. The best model from response surface methodology (RSM) was developed regarding the surface roughness. Further analysis with ANOVA method was performed to confi rm the signifi cant of the achieved model as well as machining parameters. According to experiment results, the weight percent of nanoparticles concentration had a great impact on the surface roughness, only after the feed rate. Additionally, the excellent effectiveness in reducing the roughness of MQL nanofl uid has been demonstrated when compared with conventional MQL.

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A comprehensive review on minimum quantity lubrication (MQL) in machining processes using nano-cutting fluids

Cited by 187 publications

References 149 publications

Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140

Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140

Penetration and lubrication evaluation of vegetable oil with nanographite particles for broaching process

An empirical investigation of SIO2 nano concentration under MQL on surface roughness in hard milling of jis SKD61 steel

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