Experimental investigation of nanofluids in minimum quantity lubrication during turning of EN-24 steel

2019 ◽  
Vol 234 (5) ◽  
pp. 712-729
Author(s):  
Archana Thakur ◽  
Alakesh Manna ◽  
Sushant Samir
Keyword(s):  
Comparative Analysis ◽  
Desirability Function ◽  
Cutting Temperature ◽  
Minimum Quantity Lubrication ◽  
Hybrid Nanofluid ◽  
Machining Performance ◽  
Optimization Of Parameters ◽  
Minimum Quantity ◽  
Response Optimization ◽  
Hybrid Nanofluids

The present work evaluates the performance of different machining environments such as dry, wet, minimum quantity lubrication, Al2O3 nanofluids based minimum quantity lubrication, CuO nanofluids based minimum quantity lubrication and Al–CuO hybrid nanofluids based minimum quantity lubrication on machining performance characteristics during turning of EN-24. The nanofluids and hybrid nanofluids were prepared by adding the Al2O3, CuO and Al2O3/CuO to the soluble oil with different weight percentages (0.5 wt.%, 1 wt.%, 1.5 wt.%). The thermal and tribological properties of hybrid nanofluid and nanofluids were analyzed. The comparative analysis of different turning environments has been done. From comparative analysis it is clearly observed that the nanofluids and hybrid nanofluid shows better performance during turning of EN-24 steel. So there is a need for optimization of parameters during turning of EN-24 under Al2O3 nanofluids based minimum quantity lubrication, CuO nanofluids based minimum quantity lubrication and Al–CuO hybrid nanofluids based minimum quantity lubrication. The optimization of parameters has been done by response surface methodology. The significance of developed model was identified from analysis of variance. Multi-response optimization was done using desirability function approach. To verify the accuracy of developed models, confirmatory experiments were performed. The experimental results reveal that Al–CuO hybrid nanofluids based minimum quantity lubrication significantly improves surface quality, reduces cutting temperature and cutting forces.

scholarly journals A Novel Study on The Effects of Minimum Quantity Lubrication and Machining Parameters in Turning of Ti-6Al-4V Alloy By Applying Al2O3-Graphene Hybrid Nanoparticle Enriched Cutting Fluid

2021 ◽  
Author(s):  
Kashif Riaz Wattoo ◽  
Muhammad Zubair Khan ◽  
Asif Israr ◽  
Muhammad Amin
Keyword(s):  
Surface Roughness ◽  
Vegetable Oil ◽  
Thermophysical Properties ◽  
Cutting Temperature ◽  
Minimum Quantity Lubrication ◽  
Hybrid Nanofluid ◽  
Cutting Fluids ◽  
Machining Parameters ◽  
Machining Performance ◽  
Minimum Quantity

Abstract In Minimum Quantity Lubrication (MQL) very small amount of cutting fluids are used. Currently, nanoparticles are added into cutting fluids to magnify the cooling and lubricating properties. Several studies are available on MQL to check the machining performance in terms of cooling and lubrication using nanofluids like Ag, SiO2, MoS2, Al2O3, Cu and MWCNT. However, limited evidences are available in applying hybrid nanoparticles in machining processes. Present research investigates the effect of hybridization of two different nanofluids on machining performance in turning operation of Ti-6Al-4V alloy. Moreover, machineability was evaluated and analyzed by performing turning using minimum quantity lubrication (MQL) cooling technique. Cutting temperature and surface roughness of machined surface were taken as technological performance parameters to evaluate the machinability of Ti-6Al-4V alloy. Hybridization was performed by mixing alumina based nanofluid into graphene nanoparticles in a fixed volumetric proportion 80:20 using vegetable oil as base fluid. Additionally, machining performance was evaluated by preparing hybrid nanofluid in different concentrations like (0.25,0.50,0.75 and 1.00vol%) and tested for thermophysical properties before experimentation. Significant improvements in thermophysical properties were observed during hybridization of Al2O3 and Graphene. For parametric optimization and design of experiment, Taguchi orthogonal array has been employed. Machining performance of vegetable oil base alumina-graphene hybrid nanofluid was compared with monotype alumina based nanofluid and a significant reduction cutting temperature and surface roughness was observed respectively.

Experimental investigation to study the effect of synthesized and characterized monotype and hybrid nanofluids in minimum quantity lubrication assisted turning of bearing steel

2021 ◽  
pp. 135065012110381
Author(s):  
Anup A Junankar ◽  
Yashpal Yashpal ◽  
Jayant K Purohit
Keyword(s):  
Zinc Oxide ◽  
Copper Oxide ◽  
Minimum Quantity Lubrication ◽  
Bearing Steel ◽  
Hybrid Nanofluid ◽  
Machining Performance ◽  
Minimum Quantity ◽  
Cutting Zone ◽  
Cutting Zone Temperature ◽  
Zone Temperature

A minimum quantity lubrication system using biodegradable cutting fluids has facilitated the excellent machining performance and is observed as more sustainable. In the view of enhancement of machining performance, the utilization of nanofluids with a minimum quantity lubrication system as a cutting fluid delivered noteworthy outcomes. For the present experimental investigation, the monotype nanofluids (copper oxide and zinc oxide) and a hybrid nanofluid (copper oxide/zinc oxide) were synthesized by using a two-step method. Scanning electron microscopy and energy dispersive X-ray analysis were performed to characterize the synthesized nanoparticles. A vegetable oil was utilized as a base fluid and three types of nanofluids were prepared by the addition of a surfactant (butenol). Also, ultrasonication has been performed to avoid the agglomeration of nanoparticles into the base fluid. The thermal conductivity evaluation of prepared nanofluids was carried out by using a hot wire method. The effects of three nanofluids were investigated by considering three machining input variables (cutting speed, feed rate and depth of cut) on response variables (surface roughness and cutting zone temperature) during bearing steel turning under nanofluid minimum quantity lubrication cooling conditions. The multi-objective optimization was performed by using grey relational analysis and found that the hybrid nanofluid (copper oxide/zinc oxide) was noted as the highly effective cooling condition as equated to copper oxide and zinc oxide monotype nanofluid. The hybrid nanofluid (copper oxide/zinc oxide) shows a 65% and 60% reduction in surface roughness on comparing with copper oxide and zinc oxide nanofluids, respectively. Also, the minimization of cutting zone temperature was observed under the hybrid nanofluid (copper oxide/zinc oxide) by 11% and 13% on equating with copper oxide and zinc oxide nanofluids, respectively.

Turning SKD 11 Steel Using Silver Nanofluids With Minimum Quantity Lubrication

2021 ◽  
Vol 11 (3) ◽  
pp. 74-95
Author(s):  
M. Naresh Babu ◽  
V. Anandan ◽  
M. Dinesh Babu ◽  
N. Muthukrishnan
Keyword(s):  
Surface Roughness ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Minimum Quantity Lubrication ◽  
Chip Morphology ◽  
Machining Performance ◽  
Weighting Method ◽  
Minimum Quantity ◽  
Simple Additive Weighting ◽  
The Impact

The influence of lubrication has an effect on health, surroundings, and manufacturing regions. In the current analysis, the impact of turning parameters such as cutting speed, feed rate and cutting conditions on surface roughness (Ra), cutting temperature, tool wear, and chip morphology are examined on SKD 11 steel. The experiments were performed with Taguchi's L18 orthogonal-array. The significance of the investigation involved in comparing the effect of dry, oil machining, and nano lubricants with minimum quantity lubrication (MQL) in turning process. Additionally, simple additive weighting method (SAW) has been utilized to enhance the turning parameters in SKD 11 steel for improved machining performance. Results indicate that the use of nanoparticles as cutting fluids serve in reducing the surface roughness, cutting temperature, and wear on the tool.

scholarly journals Towards Sustainable Machining of Inconel 718 Using Nano-Fluid Minimum Quantity Lubrication

2018 ◽  
Vol 2 (3) ◽  
pp. 50 ◽  
Author(s):  
Hussien Hegab ◽  
Hossam Kishawy
Keyword(s):  
Inconel 718 ◽  
Government Regulation ◽  
Effective Properties ◽  
Cutting Speed ◽  
Minimum Quantity Lubrication ◽  
Al2o3 Nanoparticles ◽  
Machining Performance ◽  
Multi Wall Carbon Nanotubes ◽  
Minimum Quantity ◽  
Cooling And Lubrication

Difficult-to-cut materials have been widely employed in many engineering applications, including automotive and aeronautical designs because of their effective properties. However, other characteristics; for example, high hardness and low thermal conductivity has negatively affected the induced surface quality and tool life, and consequently the overall machinability of such materials. Inconel 718, is widely used in many industries including aerospace; however, the high temperature generated during machining is negatively affecting its machinability. Flood cooling is a commonly used remedy to improve machinability problems; however, government regulation has called for further alternatives to reduce the environmental and health impacts of flood cooling. This work aimed to investigate the influence of dispersed multi-wall carbon nanotubes (MWCNTs) and aluminum oxide (Al2O3) gamma nanoparticles, on enhancing the minimum quantity lubrication (MQL) technique cooling and lubrication capabilities during turning of Inconel 718. Machining tests were conducted, the generated surfaces were examined, and the energy consumption data were recorded. The study was conducted under different design variables including cutting speed, percentage of added nano-additives (wt.%), and feed velocity. The study revealed that the nano-fluids usage, generally improved the machining performance when cutting Inconel 718. In addition, it was shown that the nanotubes additives provided better improvements than Al2O3 nanoparticles.

Effect of Minimum Quantity Lubrication to Prediction of Cutting Temperature Distribution in Turning Material AISI-1045

2020 ◽  
Vol 902 ◽  
pp. 97-102
Author(s):  
Tran Trong Quyet ◽  
Pham Tuan Nghia ◽  
Nguyen Thanh Toan ◽  
Tran Duc Trong ◽  
Luong Hong Sam ◽  
...  
Keyword(s):  
Temperature Distribution ◽  
Shear Zone ◽  
Orthogonal Cutting ◽  
Cutting Temperature ◽  
Chip Thickness ◽  
Minimum Quantity Lubrication ◽  
Minimum Quantity ◽  
The Difference ◽  
Secondary Shear Zone ◽  
Cutting Model

This paper presents a prediction of cutting temperature in turning process, using a continuous cutting model of Johnson-Cook (J-C). An method to predict the temperature distribution in orthogonal cutting is based on the constituent model of various material and the mechanics of their cutting process. In this method, the average temperature at the primary shear zone (PSZ) and the secondary shear zone (SSZ) were determined for various materials, based on a constitutive model and a chip-formation model using measurements of cutting force and chip thicknes. The J-C model constants were taken from Hopkinson pressure bar tests. Cutting conditions, cutting forces and chip thickness were used to predict shear stress. Experimental cutting heat results with the same cutting parameters using the minimum lubrication method (MQL) were recorded through the Testo-871 thermal camera. The thermal distribution results between the two methods has a difference in value, as well as distribution. From the difference, we have analyzed some of the causes, finding the effect of the minimum quantity lubrication parameters on the difference.

Model-based sensitivity analysis of machining-induced residual stress under minimum quantity lubrication

2015 ◽  
Vol 231 (9) ◽  
pp. 1528-1541 ◽  
Author(s):  
Xia Ji ◽  
Steven Y Liang
Keyword(s):  
Residual Stress ◽  
Sensitivity Analysis ◽  
Cutting Force ◽  
Cutting Temperature ◽  
Minimum Quantity Lubrication ◽  
Cutting Parameters ◽  
Tool Geometry ◽  
Depth Of Cut ◽  
Mixture Ratio ◽  
Minimum Quantity

This article presents a sensitivity analysis of residual stress based on the verified residual stress prediction model. The machining-induced residual stress is developed as a function of cutting parameters, tool geometry, material properties, and lubrication conditions. Based on the residual stress predictive model, the main effects of the cutting force, cutting temperature, and residual stress are quantitatively analyzed through the cosine amplitude method. The parametric study is carried out to investigate the effects of minimum quantity lubrication parameters, cutting parameters, and tool geometry on the cutting performances. Results manifest that the cutting force and residual stress are more sensitive to the heat transfer coefficient and the depth of cut, while the cutting temperature is more sensitive to the cutting speed. Large maximum compressive residual stress is obtained under a lower flow rate of minimum quantity lubrication, small depth of cut, and the proper air–oil mixture ratio. This research can support the controlling and optimization of residual stress in industrial engineering by strategically adjusting the application parameters of minimum quantity lubrication.

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