研究目的
To perform the laser milling on titanium alloy (Ti-6Al-4V) with 100% control over material removal rate (MRR) per laser scan and minimum surface roughness (SR).
研究成果
The optimized combinations of laser parameters have been proposed which ensure the conformance of 100% MRR and minimum surface roughness with composite desirability > 0.9. Confirmatory experiments revealed that the optimized parameters are capable to produce the laser milling results as per the models’ predicted results. Additionally, the microstructure of the subsequent layers below the milled area remains unchanged as compared with the microstructure of the base metal.
研究不足
The difficulty level becomes higher if high surface finish is desired alongside the precision machining. A precise control over the material removal rate per laser scan is highly desirable but difficult to achieve.
1:Experimental Design and Method Selection:
Laser milling was performed on titanium alloy (Ti-6Al-4V) substrates using a Q-switched Nd:YAG pulsed laser. The influence of five laser parameters (laser intensity, pulse frequency, scan speed, layer thickness, and track displacement) on MRR and SR was investigated.
2:Sample Selection and Data Sources:
Titanium alloy (Ti-6Al-4V) substrates with an average surface roughness of Ra
3:38 μm prior to laser machining were used. List of Experimental Equipment and Materials:
A Q-switched Nd:YAG pulsed laser with beam diameter of 20 μm and wavelength of 1064 nm was used. Lasertec 40 provided by DMG Mori Sieki was used during the experimentation.
4:Experimental Procedures and Operational Workflow:
Slots of rectangular cross section with 5 mm length and 3 mm width were machined. The depth of each milled slot was measured at three different locations through the depth-measuring probe of Lasertec 40 and an average depth of each slot was recorded.
5:Data Analysis Methods:
Analysis of variance (ANOVA) was performed to segregate the control factors into the significant and insignificant factors affecting the set responses. Mathematical models for both the responses (percent material removal rate (MRR%) and surface roughness (SR)) were developed.
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