International Science Index

5
10004002
Precision Grinding of Titanium (Ti-6Al-4V) Alloy Using Nanolubrication
Abstract:

In this current era of competitive machinery productions, the industries are designed to place more emphasis on the product quality and reduction of cost whilst abiding by the pollution-preventing policy. In attempting to delve into the concerns, the industries are aware that the effectiveness of existing lubrication systems must be improved to achieve power-efficient and pollution-preventing machining processes. As such, this research is targeted to study on a plausible solution to the issue in grinding titanium alloy (Ti-6Al-4V) by using nanolubrication, as an alternative to flood grinding. The aim of this research is to evaluate the optimum condition of grinding force and surface roughness using MQL lubricating system to deliver nano-oil at different level of weight concentration of Silicon Dioxide (SiO2) mixed normal mineral oil. Taguchi Design of Experiment (DoE) method is carried out using a standard Taguchi orthogonal array of L16(43) to find the optimized combination of weight concentration mixture of SiO2, nozzle orientation and pressure of MQL. Surface roughness and grinding force are also analyzed using signal-to-noise(S/N) ratio to determine the best level of each factor that are tested. Consequently, the best combination of parameters is tested for a period of time and the results are compared with conventional grinding method of dry and flood condition. The results show a positive performance of MQL nanolubrication.  

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834
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4
10001609
Performance Evaluation and Economic Analysis of Minimum Quantity Lubrication with Pressurized/Non-Pressurized Air and Nanofluid Mixture
Abstract:

Water miscible cutting fluids are conventionally used to lubricate and cool the machining zone. But issues related to health hazards, maintenance and disposal costs have limited their usage, leading to application of Minimum Quantity Lubrication (MQL). To increase the effectiveness of MQL, nanocutting fluids are proposed. In the present work, water miscible nanographite cutting fluids of varying concentration are applied at cutting zone by two systems A and B. System A utilizes high pressure air and supplies cutting fluid at a flow rate of 1ml/min. System B uses low pressure air and supplies cutting fluid at a flow rate of 5ml/min. Their performance in machining is evaluated by measuring cutting temperatures, tool wear, cutting forces and surface roughness and compared with dry machining and flood machining. Application of nanocutting fluid using both systems showed better performance than dry machining. Cutting temperatures and cutting forces obtained by both techniques are more than flood machining. But tool wear and surface roughness showed improvement compared to flood machining. Economic analysis has been carried out in all the cases to decide the applicability of the techniques.

Paper Detail
1282
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3
10001314
Application of Ultrasonic Assisted Machining Technique for Glass-Ceramic Milling
Abstract:

In this study, ultrasonic assisted machining (UAM) technique is applied in side-surface milling experiment for glass-ceramic workpiece material. The tungsten carbide cutting-tool with diamond coating is used in conjunction with two kinds of cooling/lubrication mediums such as water-soluble (WS) cutting fluid and minimum quantity lubricant (MQL). Full factorial process parameter combinations on the milling experiments are planned to investigate the effect of process parameters on cutting performance. From the experimental results, it tries to search for the better process parameter combination which the edge-indentation and the surface roughness are acceptable. In the machining experiments, ultrasonic oscillator was used to excite a cutting-tool along the radial direction producing a very small amplitude of vibration frequency of 20KHz to assist the machining process. After processing, toolmaker microscope was used to detect the side-surface morphology, edge-indentation and cutting tool wear under different combination of cutting parameters, and analysis and discussion were also conducted for experimental results. The results show that the main leading parameters to edge-indentation of glass ceramic are cutting depth and feed rate. In order to reduce edge-indentation, it needs to use lower cutting depth and feed rate. Water-soluble cutting fluid provides a better cooling effect in the primary cutting area; it may effectively reduce the edge-indentation and improve the surface morphology of the glass ceramic. The use of ultrasonic assisted technique can effectively enhance the surface finish cleanness and reduce cutting tool wear and edge-indentation. 

Paper Detail
1692
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2
14178
Application of Nano Cutting Fluid under Minimum Quantity Lubrication (MQL) Technique to Improve Grinding of Ti – 6Al – 4V Alloy
Abstract:
Minimum Quantity Lubrication (MQL) technique obtained a significant attention in machining processes to reduce environmental loads caused by usage of conventional cutting fluids. Recently nanofluids are finding an extensive application in the field of mechanical engineering because of their superior lubrication and heat dissipation characteristics. This paper investigates the use of a nanofluid under MQL mode to improve grinding characteristics of Ti-6Al-4V alloy. Taguchi-s experimental design technique has been used in the present investigation and a second order model has been established to predict grinding forces and surface roughness. Different concentrations of water based Al2O3 nanofluids were applied in the grinding operation through MQL setup developed in house and the results have been compared with those of conventional coolant and pure water. Experimental results showed that grinding forces reduced significantly when nano cutting fluid was used even at low concentration of the nano particles and surface finish has been found to improve with higher concentration of the nano particles.
Paper Detail
2616
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1
5338
Tool Wear and Surface Roughness Prediction using an Artificial Neural Network (ANN) in Turning Steel under Minimum Quantity Lubrication (MQL)
Abstract:
Tool wear and surface roughness prediction plays a significant role in machining industry for proper planning and control of machining parameters and optimization of cutting conditions. This paper deals with developing an artificial neural network (ANN) model as a function of cutting parameters in turning steel under minimum quantity lubrication (MQL). A feed-forward backpropagation network with twenty five hidden neurons has been selected as the optimum network. The co-efficient of determination (R2) between model predictions and experimental values are 0.9915, 0.9906, 0.9761 and 0.9627 in terms of VB, VM, VS and Ra respectively. The results imply that the model can be used easily to forecast tool wear and surface roughness in response to cutting parameters.
Paper Detail
2645
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