Parametric Optimization of Laser Additive Manufacturing of Inconel 625 Using Taguchi Method and Grey Relational Analysis

Abstract

In order to improve the forming quality of the Inconel 625 cladding layer and make it to be more widely used. This paper addresses an experimental investigation on the influence of major process parameters like laser power, scanning speed, powder feed rate, and overlapping rate along with their interactions on surface roughness and width error of laser additive manufacturing process for forming Inconel 625 samples. Taguchi method and grey relational analysis were used to optimize the selected parameters, and the verification tests were carried out. The change of microhardness and microstructure in the overlapping zone and nonoverlapping zone of the cladding layer were studied by microhardness tester and scanning electron microscopy (SEM). The results show that the most significant effect in processing parameters on surface roughness and width error are both overlapping rate, and the optimal levels of laser power, scanning speed, powder feeder rate, and overlapping rate are 1800 W, 8 mm/s, 10 g/min, and 30%, respectively. Analysis of microstructure and composition showed that the content of Cr was high both in the Laves phase and matrix, the content of Nb in the Laves phase increased significantly and reached up to 24.48 wt%, and the Laves in the nonoverlapping zone was more compact than the overlapping zone.

Optimization of Selective Laser Melting Process Parameters Via Taguchi's Methods and Gray Relational Analysis for 3D Printing of 18Ni‐300 Maraging Steel

“…In the present work, the higher-is-better quality characteristic was chosen for all four responses in order to obtain better mechanical properties. Equation ( 3) was used to convert the results obtained into S/N ratio for the higher-is-better quality characteristic [13,23] S=N Ratio…”

“…Recently, researchers have implemented Taguchi methods together with gray relational analysis (GRA) to study laser additive manufacturing processes. [12][13][14][15] The Taguchi methods were used to identify the main contributing factors that influence a particular response, while GRA was used to determine optimal processing conditions for the simultaneous improvement of multiple responses. Besides that, researchers have utilized analysis of variance (ANOVA) [16] and response surface methodology (RSM) [17] to determine optimal processing conditions for 3D printing 18Ni-300 maraging steel.…”

Influence of process parameters on mechanical strength, build time, and material consumption of 3D printed polylactic acid parts

“…Six FDM printing process parameters with their three levels have been chosen based on the findings of the previous literature. [38][39][40] The FDM process parameters and their levels have been mentioned in Table 2. Taguchi L 27 orthogonal array (OA) has been applied to reduce the number of experiments for further investigation.…”

Modeling and Optimization Approaches of Laser-Based Powder-Bed Fusion Process for Ti-6Al-4V Alloy

“…It provides a systematic approach to optimize designs for quality and cost [7]. The Taguchi method has been employed to optimize the settings of process parameters in metal AM processes such as directed energy deposition (DED) [8][9][10] and fused deposition modeling (FDM) [11,12]. Liu et al [8] optimized the DED process parameters, including laser power, scanning speed, powder feeding rate, and shielding gas flow rate, to obtain the highest density of AlSi10 Mg parts using the Taguchi L 25 orthogonal array.…”

“…They obtained the best interfacial bonding between the substrate and the deposition material by measuring the hardness variations in these regions. Yang et al [10] pointed out the limitation of the Taguchi method in optimizing only a single performance characteristic at a time in the DED processing of Inconel 625. Donstov et al [12] found the application of this method useful in improving the physical, mechanical, and tribological properties of FDM-manufactured metal-polymer composite samples in terms of uniformity of powder mixing as well as the structural uniformity of the produced samples.…”