Surface roughness evaluation using cutting vibrations in high speed turning of Ti-6Al-4V - an experimental approach

2016 ◽  
Vol 18 (3) ◽  
pp. 288 ◽  
Author(s):  
Grynal D' ◽  
N.A. Mello ◽  
P. Srinivasa Pai ◽  
N.P. Puneet ◽  
Ning Fang
Keyword(s):  
Surface Roughness ◽  
High Speed ◽  
Experimental Approach ◽  
High Speed Turning ◽  
Cutting Vibrations ◽  
Roughness Evaluation

Adaptive Neuro-Fuzzy Inference System Modelling of Surface Roughness in High Speed Turning of AISI P 20 Tool Steel

2011 ◽  
Vol 314-316 ◽  
pp. 341-345
Author(s):  
Bo Di Cui
Keyword(s):  
Experimental Data ◽  
Surface Roughness ◽  
Tool Steel ◽  
Fuzzy Inference System ◽  
High Speed ◽  
Fuzzy Inference ◽  
System Modelling ◽  
Inference System ◽  
High Speed Turning ◽  
Neuro Fuzzy

Accurate predictive modelling is an essential prerequisite for optimization and control of production in modern manufacturing environments. In this paper, an adaptive neuro-fuzzy inference system (ANFIS) model was developed to predict the surface roughness in high speed turning of AISI P 20 tool steel. Experiments were designed and performed to collect the training and testing data for the proposed model based on orthogonal array. For decreasing the complexity of the ANFIS structure, principal component analysis (PCA) was used to deal with the experimental data. The comparison between predictions and experimental data showed that the proposed method was both effective and efficient for modelling surface roughness.

Research on Machined Surface Quality for High Speed Turning Titanium Alloy Membrane Discs and Optimization of Cutting Parameters

2010 ◽  
Vol 33 ◽  
pp. 246-250
Author(s):  
Wei Zhang ◽  
Min Li Zheng ◽  
Ming Ming Cheng ◽  
Wen Yong Shi
Keyword(s):  
Surface Roughness ◽  
Titanium Alloy ◽  
Empirical Model ◽  
High Speed ◽  
Cutting Parameters ◽  
Machined Surface ◽  
Cutting Parameter ◽  
High Speed Turning ◽  
Machined Surface Roughness ◽  
Cutting Parameter Optimization

By high speed turning experiment of aerospace engine titanium alloy membrane discs, it researches cutting parameters influence on machined surface roughness of titanium alloy membrane discs, meanwhile measures and analyzes machined surface topography. Machined surface roughness multi-linear regression empirical model of high speed end-surface turning titanium alloy membrane discs is established. Using cutting parameter combination obtained from cutting parameter optimization makes process verification experiment of high speed turning titanium alloy membrane discs. The results show that the established machined surface roughness empirical model of high speed turning titanium alloy membrane discs is credible in statistics, and the process verifying experiment effect is good by using optimized cutting parameters.

scholarly journals SURFACE ROUGHNESS INVESTIGATIONS IN MINIMUM QUANTITY LUBRICATION ASSISTED HIGH SPEED TURNING OF TWO AEROSPACE MATERIALS

2019 ◽  
Vol 2019 (04) ◽  
pp. 3364-3372
Author(s):  
X.J. Wang ◽  
M.K. Gupta ◽  
Q. Song ◽  
Z. Liu ◽  
C.I. Pruncu ◽  
...  
Keyword(s):  
Surface Roughness ◽  
High Speed ◽  
Minimum Quantity Lubrication ◽  
Aerospace Materials ◽  
Minimum Quantity ◽  
High Speed Turning

Experimental Investigation of Surface Roughness in High Speed Turning of Hardened AISI P20 Steel

2011 ◽  
Vol 418-420 ◽  
pp. 1228-1231 ◽  
Author(s):  
Bo Di Cui
Keyword(s):  
Surface Roughness ◽  
Experimental Investigation ◽  
High Speed ◽  
Cutting Parameters ◽  
Machining Process ◽  
Depth Of Cut ◽  
High Speed Turning ◽  
Aisi P20 ◽  
Optimal Cutting Parameters ◽  
Aisi P20 Steel

Surface roughness is one of the most important product quality characteristics. In this paper, experimental investigation of surface roughness was performed in high speed turning of hardened AISI P20 steel with CBN tool based on design of experiment. The influence of cutting speed, feed rate, depth of cut and nose radius on surface roughness were assessed using analysis of variance (ANOVA). Optimal cutting parameters were found to improve the machining performance. Due to the complexity of machining process, artificial neural network (ANN) was employed to develop the predictive model of surface roughness. Simulations were done to study the relationship between surface roughness and cutting parameters based on the proposed model.

Study on Machinability of 35CrMnSiA Steel in Hard Turning Process

2006 ◽  
Vol 532-533 ◽  
pp. 349-352
Author(s):  
Wen Xiang Zhao ◽  
Si Qin Pang ◽  
Zhen Hai Long ◽  
Xi Bin Wang
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
High Speed ◽  
Cutting Temperature ◽  
High Strength ◽  
Depth Of Cut ◽  
Turning Process ◽  
High Speed Turning ◽  
Cutting Velocity ◽  
Strength Alloy

35CrMnSiA, is a kind of important engineering materials that used widely in modern manufacturing fields. The machinability of 35CrMnSiA Steel with hardness of HRc40±2 in high speed turning process was studied in this paper. It is concluded that, when high speed turning of this ultra-high strength alloy steel, the chief wear mode of ceramics is the crater on rake faces; the interaction of depth of cut and feed rate is one of statistic significant effects on cutting force; the interaction of cutting velocity of cut and feed rate is one of statistic significant effects on surface roughness Ra; besides, the empirical formula of average cutting temperature, cutting forces, surface roughness Ra, was established.

Sign in / Sign up

Export Citation Format

Share Document