Cavitation erosion–corrosion characteristics of laser surface modified NiTi shape memory alloy

2003 ◽  
Vol 162 (2-3) ◽  
pp. 147-153 ◽  
Author(s):  
Z.D Cui ◽  
H.C Man ◽  
F.T Cheng ◽  
T.M Yue
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Cavitation Erosion ◽  
Laser Surface ◽  
Niti Shape Memory Alloy ◽  
Erosion Corrosion ◽  
Surface Modified

scholarly journals Parametrical optimization of laser surface alloyed NiTi shape memory alloy with Co and Nb by the Taguchi method

2009 ◽  
Vol 223 (8) ◽  
pp. 969-979 ◽  
Author(s):  
K W Ng ◽  
H C Man ◽  
J Lawrence ◽  
T M Yue
Keyword(s):  
Shape Memory Alloy ◽  
Taguchi Method ◽  
Shape Memory ◽  
Laser Processing ◽  
Processing Parameters ◽  
Laser Surface ◽  
Niti Shape Memory Alloy ◽  
Metal Powders ◽  
Surface Alloying ◽  
Laser Surface Alloying

Different high-purity metal powders were successfully alloyed on to a nickel titanium (NiTi) shape memory alloy (SMA) with a 3 kW carbon dioxide (CO2) laser system. In order to produce an alloyed layer with complete penetration and acceptable composition profile, the Taguchi approach was used as a statistical technique for optimizing selected laser processing parameters. A systematic study of laser power, scanning velocity, and pre-paste powder thickness was conducted. The signal-to-noise ratios (S/N) for each control factor were calculated in order to assess the deviation from the average response. Analysis of variance (ANOVA) was carried out to understand the significance of process variables affecting the process effects. The Taguchi method was able to determine the laser process parameters for the laser surface alloying technique with high statistical accuracy and yield a laser surface alloying technique capable of achieving a desirable dilution ratio. Energy dispersive spectrometry consistently showed that the per cent by weight of Ni was reduced by 45 per cent as compared with untreated NiTi SMA when the Taguchi-determined laser processing parameters were employed, thus verifying the laser's processing parameters as optimum.

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