Enhancement of Surface Quality of DMLS Aluminium Alloy using RSM Optimization and ANN Modelling

Abstract

Direct Metal Laser Sintering (DMLS) is an additive manufacturing technology gaining popularity due to its ability to produce near net-shaped functional components. As there is a great need to improve the surface quality of DMLS components to upgrade their dynamic properties, an attempt was made to study the influence of process parameters like laser power, scan speed, and overlap rate on the surface quality of DMLS Aluminum alloy (AlSi10Mg) in as-built condition. The optimized process window to generate the best surface quality was achieved using Response Surface Method (RSM). Artificial Neural Network (ANN) modeling is also developed to map the influence of process parameters on surface quality. Conclusively, Scan speed is found to be most influential over surface quality as per the F and P test results. The optimized process parameters for best surface quality (3.52 µm) were 300 W laser power, 600 mm/sec scan speed, and 25% overlap rate. Both RSM and ANN models were accurate in prediction. However, ANN is recorded as superior with the highest coefficient of correlation (R).

Effect of Process Parameters on Surface Roughness, Thrust Force and Tool Wear of Coated HSS Tool during Drilling of Customized EN8 Alloy

“…F-ratio of the tabulation represents ratio of mean square to mean square error. The p-value of equal or less than 0.05 is taken a significant and higher than this value is taken as in-significant [7][14][20] [26].…”

“…Tool 3 produces highest surface roughness preceding being the Tool 4 followed by Tool 1. Hardness of the tool does not have much effect on surface finish as can be seen [1][20] [26]. Maximum and minimum feed rate was noticed in case of Tool 3 and Tool 2.…”

“…The probability plot for tool wear for tools with R1 to R4 composition is shown in Figure 7. As discussed afore the scattering of the points are nearer to the straight line are feasible [1][13] [26]. 8(a) and (b) shows SEM images of tool wear for tools 2 and 3 at microscopic magnification of 200 μm.…”

“…Better surface roughness is obtained for CC650WG and GC6050WH than the conventional CC650 insert during a study of AISI D2 tool with different ceramic inserts during hard turning of tool steel [24]. During grinding of Inconel 718, depth of cut and transverse speed had maximum influence on surface roughness [26].…”

“…Figure 2: Main effects plot for surface roughness, (a) Tool 1, (b) Tool 2, (c) Tool 3, and (d) Tool 4These plots give acceptable probability for Ra with the test results. It was observed that better surface finish is obtained for highwer cutting speed[1][26].…”