Page 27 - IJAMD-1-3

International Journal of AI for
Materials and Design
Prediction of wall geometry for wire arc additive manufacturing

Cong et al. examined different arc modes in CMT and successfully fabricated a multilayer structure. Mai et
to fabricate parts with zero porosity, whereas Ali et al. al. explored the fabrication of 308L stainless steel parts
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examined the influence of arc energy and thermal fields using WAAM, by combining experimental design and
on the mechanical properties and microstructures of optimization through analysis of variance (ANOVA). The
hot-work tool steel in CMT-based WAAM. The shape of optimized parameters resulted in remarkable mechanical
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each weld bead in WAAM depends on the energy input properties, highlighting the importance of optimization.
and determines the quality and dimensional precision of Chaudhari et al. analyzed the influence of WAAM
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the resulting parts. Hence, numerous studies have focused process parameters on bead geometry for single-layer
on the influence of process parameters on single-bead deposits, focusing on the trends of BW and BH under
geometry. Fu et al. investigated the interplay between wire varying TS, WFS, and V. Using a Box–Behnken design,
feed speed (WFS) and travel speed (TS), examined its they identified WFS as the most influential factor for BW
influence on the width (BW) and height (BH) of a single and BH, followed by V and TS. Their optimized settings
weld bead in bainite steel WAAM, and reported a decrease (TS = 141 mm/min, WFS = 5.50 m/min, and V = 19 V)
in BW/BH with increasing WFS across all TS levels. led to the successful fabrication of a multilayer structure.
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Ayarkwa et al. highlighted the importance of the WFS/ Natryan et al. used the Taguchi method to examine the
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TS ratio and discovered that a higher ratio results in wider effects of TS, welding current, and filler diameter on the
and taller beads during the fabrication of aluminum walls quality of welded joints. By employing an orthogonal array
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through CMT. Kazanas et al. studied the fabrication of design and performing statistical analyses, they identified
inclined steel and aluminum walls using CMT at a constant an optimal parameter combination that minimized defects
WFS/TS ratio, discovered the substantial influence of TS and improved bead geometry and weld penetration. Vora
on wall quality, and recommended a value between 0.2 and et al. optimized bead shape for GMAW-based WAAM
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0.25 m/min for optimal surface smoothness. 8 using a Box–Behnken design for bead-on-plate tests.
The temperature of the workpiece at the beginning They applied ANOVA to analyze regression equations and
of deposition of each new layer, known as the interlayer employed a teaching‒learning-based optimization method
temperature, is a critical factor in WAAM. 9-11 This to determine the best parameters, achieving a minimum
temperature influences the microstructures and BW of 4.73 mm and a maximum BH of 7.81 mm. The
characteristics of the final components. For instance, in optimized parameters enabled the fabrication of a
Ti–Al WAAM, increasing the interlayer temperature from multilayer structure without layer disbonding. Kumar
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100°C to 500°C decreases the alpha phase content, leading et al. employed a genetic algorithm to identify optimal
to reduced hardness. If not properly controlled, the process parameters for WAAM, achieving near-net-
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interlayer temperature can cause longitudinal cracking and shaped deposition with fewer layers. The genetic algorithm
substantial residual stress in the initial layers of Fe–Al parts. effectively optimized these parameters to yield the desired
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In addition, in Ti6Al4V, rising interlayer temperatures outcomes. Liberini et al. focused on selecting optimal
influence bead geometry along the build direction. Xiong process parameters for WAAM through a multiobjective
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et al. discovered that low interlayer temperatures enhance optimization approach, successfully identifying the best
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the surface quality of thin-walled components fabricated values for BW, BH, porosity, and deposition rate. Wang
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using WAAM, whereas another study demonstrated et al. employed a multiwire indirect-arc-directed energy
that maintaining the interlayer temperature within a deposition method, discovering that WFS, current, and
specific low range improves the final quality of steel thin- wire angle substantially impacted indirect-arc-directed
walled parts. These processes are influenced by material energy deposition. This method achieved favorable
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properties, such as the impact of the contact angle on bead microstructures and mechanical properties compared
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geometry. Notably, the development of multibead walls is with conventional methods. Mishra et al. optimized
essential for advancing WAAM technology. Kumar et al. the topology and deposition direction in WAAM using
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attempted to optimize GMAW-based WAAM for creating a mathematical model and a combination of genetic
multilayer beads on steel, focusing on process parameters to algorithm- and gradient-based optimization techniques.
improve dimensional precision and mechanical properties. This approach improved part quality and reduced
They employed a response surface methodology design manufacturing durations compared with traditional
for single-layer deposits, considering variables such as methods.
TS, voltage (V), current, and gas flow rate. Their findings To achieve high surface quality and precise dimensions
revealed that TS critically influenced BW and BH, altering in WAAM, ensuring predictable and controllable weld
them by 52.29% and 43%, respectively. By applying a beads for each layer is essential. Developing models
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desirability function, they identified optimal parameters that can accurately forecast weld bead geometry based

Volume 1 Issue 3 (2024) 21 doi: 10.36922/ijamd.4285