The main objective of this work was to propose and evaluate a methodology for shielding-gas selection in additive manufacturing assisted by wire arc additive manufacturing (WAAM) with an austenitic stainless steel as feedstock. To validate the proposed methodology, the impact of multi-component gases was valued using three different Ar-based blends recommended as shielding gas for GMA (gas metal arc) of the target material, using CMT (cold metal transfer) as the process version. This assessment considered features that potentially affect the building of the case study of thin walls, such as metal transfer regularity, deposition time, and geometrical and metallurgical characteristics. Different settings of wire-feed speeds were conceived to maintain a similar mean current (first constraint for comparison’s sake) among the three gas blends. This approach implied different mean wire-feed speeds and simultaneously forced a change in the deposition speed to maintain the same amount of material deposited per unit of length (second comparison constraint). The composition of the gases affects the operational performance of the shielding gases. It was concluded that by following this methodology, shielding-gas selection decision-making is possible based on the perceived characteristics of the different commercial blends. © 2024 by the authors.

Conventional path-planning strategies for GMA-WAAM may encounter challenges related to geometrical features when printing complex-shaped builds. One alternative to mitigate geometry-related flaws is to use algorithms that optimise trajectory choices—for instance, using heuristics to find the most efficient trajectory. The algorithm can assess several trajectory strategies, such as contour, zigzag, raster, and even space-filling, to search for the best strategy according to the case. However, handling complex geometries by this means poses computational efficiency concerns. This research aimed to explore the potential of machine learning techniques as a solution to increase the computational efficiency of such algorithms. First, reinforcement learning (RL) concepts are introduced and compared with supervised machining learning concepts. The Multi-Armed Bandit (MAB) problem is explained and justified as a choice within the RL techniques. As a case study, a space-filling strategy was chosen to have this machining learning optimisation artifice in its algorithm for GMA-AM printing. Computational and experimental validations were conducted, demonstrating that adding MAB in the algorithm helped to achieve shorter trajectories, using fewer iterations than the original algorithm, potentially reducing printing time. These findings position the RL techniques, particularly MAB, as a promising machining learning solution to address setbacks in the space-filling strategy applied. 

Layered stainless steel samples were manufactured using Plasma Wire Arc Additive Manufacturing by depositing alternating layers of two dissimilar stainless steels onto an AISI 316L substrate. The selected materials were the M430 ferritic and M316L austenitic stainless steels. Comprehensive microstructural characterization in different areas, including interfaces between the two different materials, was achieved through optical microscopy and electron backscatter diffraction. Results revealed good weldability among the two-layered steels and on the substrate. Also, a gradient duplex structure was observed mainly at the layer interfaces, suggesting a nuanced blending of properties in the deposited zone. To establish a direct correlation with mechanical properties in the observed structures, macro and micro-hardness tests were conducted along the cross-section. These tests evidenced the presence of a harder phase along the interface compared to the individual materials. The microstructural analysis corroborated the presence of mixing between phases in conjunction with some areas of delta ferrite. 

Hardfacing is commonly used in parts recovery and in obtaining surfaces with improved properties. Within this field, it is important to analyze the effect of alloying elements on the properties of the deposited layers. One of the critical parameters affecting alloying performances in SMAW is improper arc length. This article examines the effect of the addition of niobium in different quantities (0, 2, 4, 6, and 8% by weight) to the electrode coating in Fe-Cr-C shielded metal arc welding (SMAW), with short and long arc lengths, on the operational process efficiency, dilution, arc energy, microstructure, and microhardness of the deposited layers. A decrease in operational process efficiency and dilution was found with increases in niobium content. On the other hand, it was found that adding niobium leads to a refinement in chromium carbide sizes, directly affecting the hardness of the obtained deposits. There is a direct relationship between the arc energy, with both short and long arc lengths, leading to a tendency to decrease the dilution in the obtained hardfacing. 

Wire Arc Additive Manufacturing (WAAM) of thin walls is an adequate technology for producing functional components made with aluminium alloys. The AlMg5 family is one of the most applicable alloys for WAAM. However, WAAM differs from traditional fabrication routes by imposing multiple thermal cycles on the material, leading the alloy to undergo cyclic thermal treatments. Depending on the heat source used, thermal fluctuation can also impact the microstructure of the builds and, consequently, the mechanical properties. No known publications discuss the effects of these two WAAM characteristics on the built microstructure. To study the influence of multiple thermal cycles and heat source-related thermal fluctuations, a thin wall was built using CMT-WAAM on a laboratory scale. Cross-sections of the wall were metallographically analysed, at the centre of a layer that was re-treated, and a region at the transition between two layers. The focus was the solidification modes and solubilisation and precipitations of secondary phases. Samples from the wall were post-heat treated in-furnace with different soaking temperatures and cooling, to support the results. Using numerical simulations, the progressive thermal cycles acting on the HAZ of one layer were simplified by a temperature sequence with a range of peak temperatures. The results showed that different zones are formed along the layers, either as a result of the imposed thermal cycling or the solidification mode resulting from CMT-WAAM deposition. In the zones, a band composed of coarse dendrites and an interdendritic phase and another band formed by alternating sizes of cells coexisted with the fusion and heat-affected zones. The numerical simulation revealed that the thermal cycling did not significantly promote the precipitation of second-phase particles. 

This work presents the evaluation of the interlayer temperature (IT) with travel speed (TS) combined effect for a given wire feed speed (WFS) on operational, geometrical, and metallurgical features of thin walls with the same width deposited by wire arc additive manufacturing (WAAM) with a low alloy steel, using or not active cooling. A preliminary experimental design was carried out to define a range of IT that could prevent the molten pool from running down and, then, be used in the main experimental design. The main tests were planned and performed to find different IT and TS combinations for a given WFS capable of depositing walls with the same target effective wall width. After selecting the parameters, six walls were deposited, three under natural cooling (NC) and three under near immersion active cooling (NIAC). A more significant temperature variability along the layer length (ΔT/ΔLL) is observed in increasing IT-TS combination and under NIAC. Regardless of the cooling approach, a worse surface aspect was observed with lower IT and TS. However, NC or NIAC do not affect the wall width (effective or external) or the layer height. On the other hand, they are affected by the IT with TS combination. A shorter production time was obtained on the walls with NIAC and higher IT-TS. No marked microstructural differences were observed comparing the walls, regardless of the cooling approach. However, microstructure tempering (hardness reduction) was observed in the walls deposited with NC using higher IT levels.  

Purpose

This study aims to propose and evaluate the progress in the basic-pixel (a strategy to generate continuous trajectories that fill out the entire surface) algorithm towards performance gain. The objective is also to investigate the operational efficiency and effectiveness of an enhanced version compared with conventional strategies.

Design/methodology/approach

For the first objective, the proposed methodology is to apply the improvements proposed in the basic-pixel strategy, test it on three demonstrative parts and statistically evaluate the performance using the distance trajectory criterion. For the second objective, the enhanced-pixel strategy is compared with conventional strategies in terms of trajectory distance, build time and the number of arcs starts and stops (operational efficiency) and targeting the nominal geometry of a part (operational effectiveness).

Findings

The results showed that the improvements proposed to the basic-pixel strategy could generate continuous trajectories with shorter distances and comparable building times (operational efficiency). Regarding operational effectiveness, the parts built by the enhanced-pixel strategy presented lower dimensional deviation than the other strategies studied. Therefore, the enhanced-pixel strategy appears to be a good candidate for building more complex printable parts and delivering operational efficiency and effectiveness.

Originality/value

his paper presents an evolution of the basic-pixel strategy (a space-filling strategy) with the introduction of new elements in the algorithm and proves the improvement of the strategy’s performance with this. An interesting comparison is also presented in terms of operational efficiency and effectiveness between the enhanced-pixel strategy and conventional strategies.

Continuous cooling transformation (CCT) diagrams of base metals are common in welding. They can be built using physical or numerical simulations, each with advantages and limitations. However, those are not usual for weld metal, considering its variable composition due to the dilution of the weld into the base metal. Wire Arc Additive Manufacturing (WAAM) is a distinctive casein which the interest in materials comparable with weld composition raises attention to estimating their mechanical properties. Notwithstanding, this concept is still not used in WAAM. Therefore, the aim of this work was to address a methodology to raise MC-CCT (Multiple Cycle ContinuousCooling Transformation) diagrams for WAAM by combining physical and numerical simulations. A high-strength low-alloy steel (HSLA) feedstock (a combination of a wire and a shielding gas) was used as a case study. To keep CCT as representative as possible, the typical multiple thermal cycles for additive manufacturing thin walls were determined and replicated in physical simulations (Gleeble dilatometry). The start and end transformations were determined by the differential linear variation approach for each thermal cycle. Microstructure analyses and hardness were used to characterise the product after the multiple cycles. The same CCT diagram was raised by a commercial numerical simulation package to determine the shape of the transformation curves. A range of austenitic grain sizes was scanned for the curve position matching the experimental results. Combining the experimental data and numerically simulated curves made estimating the final CCT diagram possible.

WAAM (wire arc additive manufacturing) of aluminium requires special operational care to avoid problems such as instabilities, contamination or porosities. This work aims at verifying whether supplementary shielding gas can affect the WAAM performance when building Al alloy thin walls, in terms of metal transfer, porosity, superficial finishing, and geometrical and metallurgical features. Thin walls were manufactured with and without supplementary shielding (ultra-pure Ar). A dedicated nozzle was designed in-house to provide additional protection against the reaction with surrounding atmospheric gases. Pure Ar and two Ar-based commercial shielding gases with different additives were employed to make the conclusions more sustainable. It was possible to conclude that supplementary shielding leads to better metal transfer regularity, cleaner lateral and surface, a shinier top layer appearance, and a slight trend to higher microhardness. On the other hand, it does not affect porosity after layer depositions, wall geometry (the total and effective layer width, layer height, and surface waviness of the walls), and microstructures. Finally, regarding the performance of shielding gases, there is no evidence of any effect from the supplementary shielding, since this approach improved the process operationality with the three different shielding gases but did not change their individual tendencies. 

To overcome a shortage of flexible and low-cost solutions for wire arc additive manufacturing (WAAM) preprocessing, this work´s objective was to develop and validate an in-house computational programme in an open-source environment for WAAM preprocessing planning. Algorithms for reading STL (stereolithography) files and implementing rotation, slicing, trajectory planning, and machine code generation were elaborated and implemented in the Scilab environment (free and open-source). A graphical interface was developed to facilitate user interaction, with 5 options for path planning. The functionality of each work step is detailed. For validation of the software, single and multiple-layer prints, with different geometrical complexity and printing challenges, were built in a CNC table geared by the generated machine code. The validation criteria were deposition imperfection, morphological, and dimensional tolerances. The outputs showed that the parts were successfully printed. Therefore, this work demonstrates that Scilab provides the necessary resources for companies and universities to implement and/or develop algorithms for planning and generating trajectories for WAAM. Moreover, emerging ideas can be reasonably easily implemented in such software, not always possible in commercial packages.