The Simulation and Experimental Study of Metal Cutting Based on Cold Air Technology

2011 ◽  
Vol 189-193 ◽  
pp. 242-247
Author(s):  
Qiong Lin ◽  
Zhen Xiang Zhang ◽  
Qiu Cheng Wang
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Stainless Steel ◽  
Metal Cutting ◽  
High Reliability ◽  
Fem Simulation ◽  
Green Manufacturing ◽  
Cold Air ◽  
Novel Approach ◽  
Green Manufacturing Technology

Metal Cutting based on cold air technology is a green manufacturing technology which has the potential of great application prospect. In order to study the influence of cold air technology on metal cutting characteristics, the experiment and FEM simulation of both 0Cr18Ni9 stainless steel and 45 steel were performed under three cutting conditions. The results are analyzed to reveal that with cold air technology the temperature of cutting area can be effectively reduced and the tool life, surface roughness and the shape of chip can be significantly improved. The study on metal cutting with cold air technology based on simulation has a relatively high reliability, which provides a novel approach for the research on metal cutting with cold air technology.

Experimental Study on Minimum Quantity Lubrication in Mechanical Micromachining

2012 ◽  
Vol 579 ◽  
pp. 193-200 ◽  
Author(s):  
Kuan Ming Li
Keyword(s):  
Surface Roughness ◽  
Metal Cutting ◽  
Minimum Quantity Lubrication ◽  
Green Manufacturing ◽  
Micro Milling ◽  
Experimental Investigations ◽  
Minimum Quantity ◽  
Green Manufacturing Technology ◽  
Micro Tools ◽  
Mechanical Micromachining

Mechanical micromachining is a promising technique for making complex microstructures. It is challenging to apply mechanical micromachining in the industry due to the low strength of micro tools. Therefore, it is not easy to accurately control the product dimension error and to raise the production rate. In this paper, the applications of minimum quantity lubrication (MQL) in micro-milling and micro-grinding are presented. MQL is considered as a green manufacturing technology in metal cutting due to its low impact on the environment and human health. This study compares the tool wear and surface roughness in MQL micromachining to completely dry condition based on experimental investigations. The supply of MQL in vibration-assisted grinding is also studied. It is found that the use of MQL results in longer tool life and better surface roughness in mechanical micromachining.

Study of Cutting Force and Surface Roughness on Drilling Stainless Steel 316L under Various Coolant Condition

2018 ◽  
Vol 791 ◽  
pp. 116-122
Author(s):  
K. Kamdani ◽  
A.A. Hamsah ◽  
N.H. Rafai ◽  
M.Z. Rahim ◽  
C.K. Wong ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Cutting Force ◽  
Metal Cutting ◽  
Thrust Force ◽  
Helix Angle ◽  
Industrial Sector ◽  
Stainless Steel 316L ◽  
High Tendency ◽  
Drilling Condition

Drilling is the metal cutting process that are widely used in industrial sector such as in aerospace, automotive and manufacturing to produce a various of durable parts. Stainless steels in general are regarded as difficult to machine materials due to their high tendency to work harden; their toughness and relatively low thermal conductivity. In this research, the experimental setup for the effect of various parameters on drill performance in term of cutting force and surface roughness. Stainless steel 316L used as workpiece and uncoated tungsten carbide drill bit as the tool. From the experimental investigation, the results show that internal coolant with helix angle of 40 and feed rate of 0.1 mm/rev condition is the best drilling condition in term of thrust force and surface roughness. By observation on experiment, MQL coolant condition give highest thrust force while internal coolant is best condition to have most minimum force. For internal coolant, MQL and external supply, the optimum helix angle to obtain low surface roughness is 15° and 40°.

An Experimental Study of Surface Roughness Variation in End Milling of Super Duplex 2507 Stainless Steel

2018 ◽  
Vol 5 (2) ◽  
pp. 3682-3689 ◽  
Author(s):  
Jay Airao ◽  
Bhavesh Chaudhary ◽  
Vivek Bajpai ◽  
Navneet Khanna
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Stainless Steel ◽  
End Milling

Precision Honing of Stainless Steel Valve Core

2011 ◽  
Vol 487 ◽  
pp. 438-442
Author(s):  
Zhi Gang Dong ◽  
C.W. Kang ◽  
L. Xu
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Stainless Steel ◽  
Surface Topography ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Grit Size ◽  
Steel Cylinder

The paper reports an experimental study on the effect of honing parameters on the honing surface roughness, material removal rate and surface topography. A cylindrical honing machine was developed, on which the honing experiments for stainless steel cylinder parts were performed with different honing parameters including the abrasives and its grit size of honing stones, honing pressure and honing time. The results can provide helpful instruction to the determination of the honing process and parameters.

scholarly journals Prediction of Surface Roughness after Turning of Duplex Stainless Steel (DSS)

2021 ◽  
Vol 17 (2) ◽  
pp. 8-17
Author(s):  
Osamah F. Abdulateef
Keyword(s):  
Neural Network ◽  
Surface Roughness ◽  
Stainless Steel ◽  
Duplex Stainless Steel ◽  
Feed Rate ◽  
Metal Cutting ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Process Conditions ◽  
The Impact

Feed Forward Back Propagation artificial neural network (ANN) model utilizing the MATLAB Neural Network Toolbox is designed for the prediction of surface roughness of Duplex Stainless Steel during orthogonal turning with uncoated carbide insert tool. Turning experiments were performed at various process conditions (feed rate, cutting speed, and cutting depth). Utilizing the Taguchi experimental design method, an optimum ANN architecture with the Levenberg-Marquardt training algorithm was obtained. Parametric research was performed with the optimized ANN architecture to report the impact of every turning parameter on the roughness of the surface. The results suggested that machining at a cutting speed of 355 rpm with a feed rate of 0.07 mm/rev and a depth of cut 0.4 mm was found to achieve lower surface roughness with,  an increase in the cutting speed and feed rate with the increases of the surface roughness. In addition, an increase in the depth of cut was found to reduces the surface roughness. The outcome of this study showed that ANN is a versatile tool for prediction of surface roughness and may be easily extended with greater confidence to various metal cutting processes.

scholarly journals Liquid LCO2 Assisted Machining of Martensitic Stainless Steel with TiAlSiN PVD Coated Tools

2021 ◽  
Author(s):  
Matej Drobnič ◽  
Franci Pušavec ◽  
Miha Čekada
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Tool Life ◽  
Martensitic Stainless Steel ◽  
Life Time ◽  
Novel Approach ◽  
Coated Tool ◽  
Cutting Zone ◽  
Cooling And Lubrication ◽  
Lubrication Conditions

Sustainable machining involves the use of environmentally friendly cooling and lubrication fluids. A novel approach of lubricated liquid carbon dioxide (LCO2) can be used to replace conventional cutting fluids while promising benefits such as cleaner machining and higher productivity. In this study, milling of martensitic stainless steel was performed under different cooling and lubrication conditions (dry, flood, LCO2, LCO2 + MQL). Cutting tool (ball end mill, d = 8mm) was protected by a TiAlSiN PVD hard coating, while the same uncoated tool was used as a reference. Tool life time measurements were taken under different cooling and lubrication conditions at pre-determined time intervals, until the critical tool wear of 0.2 mm was reached on the flank face. At the same time, thermocouples were inserted into the workpiece to measure the temperature directly below the cutting zone. The influence of different cooling and lubrication conditions on surface roughness parameters was also investigated. From the experimental results, surprisingly, conventional flooding machining outperformed LCO2 and LCO2 + MQL assisted machining in terms of surface roughness. Moreover, the TiAlSiN coated tool exhibited roughly three times longer tool life time when compared to the uncoated tool at the same machining conditions. Whereas both, LCO2 and LCO2 + MQL cooling/lubricating strategies significantly reduce the temperature in the cutting zone, dry machining strategy provides the longest tool life time.

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