Wire arc additive manufacturing (WAAM) is steadily increasing with significant research work are underway. The ability of WAAM to manufacture a large-scale product at a lower cost and shorter lead times has increased its development. The efficiency or potential of WAAM to become a new lead in the additive manufacturing industry is believed to be realized by a few factors. High efficiency and performance require a higher metal deposition rate, which implies higher heat input that negatively affects the manufacturing process. This paper review works for factors associated with heat input on the WAAM process. The factor affecting these properties were explained to identify the optimized WAAM process in terms of heat input. The paper focuses on the impact of heat input on the macrostructure, microstructure and mechanical properties of the parts deposited in the WAAM process. This review also discussed the effect of heat input used by eight different types of arc welding technologies, with appropriate use of wire materials. The study also highlights that heat input affected the microstructure of the WAAM, causing significant changes in grain structure, grain size and pore area percentage. Besides, it can be suggested that grain structure has a strong influence on the WAAM materials' mechanical properties.

Review on effect of heat input for wire arc additive manufacturing process

Wire arc additive manufacturing is currently rising as the main focus of research groups around the world. This is directly visible in the huge number of new papers published in recent years concerning a lot of different topics. This review is intended to give a proper summary of the international state of research in the area of wire arc additive manufacturing. The addressed topics in this review include but are not limited to materials (e.g., steels, aluminum, copper and titanium), the processes and methods of WAAM, process surveillance and the path planning and modeling of WAAM. The consolidation of the findings of various authors into a unified picture is a core aspect of this review. Furthermore, it intends to identify areas in which work is missing and how different topics can be synergetically combined. A critical evaluation of the presented research with a focus on commonly known mechanisms in welding research and without a focus on additive manufacturing will complete the review.

The Current State of Research of Wire Arc Additive Manufacturing (WAAM): A Review

Additive manufacturing (AM) route is a promising approach for fabricating complex and lightweight metallic structures that have applications in various sectors such as automotive, aerospace, and biomedical industries. Laser, electron beam, and electric arc are the common power sources available for AM. Out of different metal AM techniques, wire-feed additive manufacturing has been considered as a promising alternative for fabricating metallic parts for various applications. As it provides a high deposition rate, material utilization, density, and low cost with a low risk of contamination and porosity compared to powder-based raw material. Gas metal arc welding-based additive manufacturing (GMAW-AM) is a speciﬁc approach based on wire-feed AM. This technology uses a low-cost equipment which is suitable for fabricating components with large geometries and moderate structural complexity. These advantages attract the researchers and production industries for further developments in GMAW-AM to enhance its deposition performance, process capability, and applicability in various fields. The quality of metal deposited in GMAW-AM is generally represented by the surface form, dimensional quality, mechanical properties, relative density, hardness, etc. The present paper encompasses the research developments that occurred in the field of GMAW-AM in recent years. This review begins with the GMAW-AM procedure, performance capability, identification of factors affecting the deposition performance, and strategies adopted to overcome these issues. Several aspects such as mathematical modelling, optimization, key process parameters, and their combinations for a wide range of wire electrode material and percentage contributions are also reviewed and depicted in detail. Also, a comprehensive conclusion of this review, along with future perspectives, is explored subsequently. The current review work will help future researchers to select different wire materials and GMAW-AM parameters to achieve better performances. Lastly, several future research directions are suggested, specifically the need of a framework for GMAW-AM processes for fabricating quality products with minimum distortion.

Gas metal arc welding based additive manufacturing—a review

The COVID-19 pandemic has severely impacted factories all over the world, which have been closed to avoid the spread of COVID-19. As a result, ensuring the long-term operation of a factory amid the COVID-19 pandemic becomes a critical but challenging task. To fulfill this task, the applications of smart and automation technologies have been regarded as an effective means. However, such applications are time-consuming and budget-intensive with varying effects and are not necessarily acceptable to workers. In order to make full use of limited resources and time, it is necessary to establish a systematic procedure for comparing various applications of smart and automation technologies. For this reason, an evolving fuzzy assessment approach is proposed. A case study has been conducted to demonstrate the effectiveness of the evolving fuzzy assessment approach in ensuring the long-term operation of a factory amid the COVID-19 pandemic.

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Smart and automation technologies for ensuring the long-term operation of a factory amid the COVID-19 pandemic: an evolving fuzzy assessment approach.

Wire arc additive manufacturing (WAAM) is capable of rapidly depositing metal materials thus facilitating the fabrication of large-shape metal components. However, due to the multi-process-variability in the WAAM process, the deposited shape (bead width, height, depth of penetration) is difficult to predict and control within the desired level. Ultimately, the overall build will not achieve a near-net shape and will further hinder the part from performing its functionality without post-processing. Previous research primarily utilizes data analytical models (e.g., regression model, artificial neural network (ANN)) to forwardly predict the deposition width and height variation based on single or cross-linked process variables. However, these methods cannot effectively determine the optimal printable zone based on the desired deposition shape due to the inability to inversely deduce from these data analytical models. Additionally, the process variables are intercorrelated, and the bead width, height, and depth of penetration are highly codependent. Therefore, existing analysis cannot grant a reliable prediction model that allows the deposition (bead width, height, and penetration height) to remain within the desired level. This paper presents a novel machine learning framework for quantitatively analyzing the correlated relationship between the process parameters and deposition shape, thus providing an optimal process parameter selection to control the final deposition geometry. The proposed machine learning framework can systematically and quantitatively predict the deposition shape rather than just qualitatively as with other existing machine learning methods. The prediction model can also present the complex process-quality relations, and the determination of the deposition quality can guide the WAAM to be more prognostic and reliable. The correctness and effectiveness of the proposed quantitative process-quality analysis will be validated through experiments. 

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Quality Prediction and Control in Wire Arc Additive Manufacturing via Novel Machine Learning Framework

Additive manufacturing (AM) is becoming increasingly popular since it offers flexibility to produce complex designs with less tooling and minimum material at shorter lead times. Wire arc additive manufacturing (WAAM) is a variant of additive manufacturing which allows economical production of large-scale and high-density parts. The WAAM process has been studied extensively on different steels; however, the influence of process parameters, specifically wire feed speed (WFS), travel speed (TS), and their ratio on bead geometry, microstructure, and mechanical properties, are yet to be studied. The present work aims at closing this gap by using the WAAM process with robotic cold metal transfer (CMT) technology to manufacture high-strength structural steel parts. For that purpose, single-bead welds were produced from HSLA steel by varying WFS between 5 and 10 m/min and the WFS to TS ratio between 10 and 20. Those variations produce heat inputs in the range of 266–619 J/mm. The results have shown that the wire feed speed to travel speed ratio is the major parameter to control the heat input. Increasing heat input increases characteristic bead dimension, whereas it reduces the hardness. In the second part of experiments, two single-bead walls were deposited via the parallel deposition strategy and one multiple-bead wall was produced using the oscillation strategy. The tensile properties were tested along two directions: parallel and perpendicular to deposition directions. For the yield strength and tensile strength, the difference between horizontally and vertically tested specimens was smaller than the standard deviations. On the other hand, the total and uniform elongation values exhibit up to 10% difference in the test direction, indicating anisotropy in ductility. Those tensile properties were attributed to repeated thermal cycles during the WAMM process, which can cause heat transfer in multiple directions. The yield strength of the multiple-bead wall produced via oscillation was lower, whereas its ductility was higher. The tensile properties and hardness differences were found to correlate well with the microstructure.

Wire arc additive manufacturing of high-strength low alloy steels: study of process parameters and their influence on the bead geometry and mechanical characteristics

Ahmet Suat Yildiz

Papers

Wire arc additive manufacturing of high-strength low alloy steels: study of process parameters and their influence on the bead geometry and mechanical characteristics

Thermal behavior determination for wire arc additive manufacturing process