Revisiting fundamental welding concepts to improve additive manufacturing: From theory to practice

https://doi.org/10.1016/j.pmatsci.2019.100590Get rights and content

Highlights

  • Vast knowledge on welding can be used in additive manufacturing.

  • Criteria to optimize parameters in additive manufacturing is proposed.

  • Proposed criteria provides an upper bound limit for key process parameters.

  • A dimensionless parameter is proposed to compute the energy density.

  • The dimensionless parameter allows to compare works from different research groups.

Abstract

Additive manufacturing technologies based on melting and solidification have considerable similarities with fusion-based welding technologies, either by electric arc or high-power beams. However, several concepts are being introduced in additive manufacturing which have been extensively used in multipass arc welding with filler material. Therefore, clarification of fundamental definitions is important to establish a common background between welding and additive manufacturing research communities. This paper aims to review these concepts, highlighting the distinctive characteristics of fusion welding that can be embraced by additive manufacturing, namely the nature of rapid thermal cycles associated to small size and localized heat sources, the non-equilibrium nature of rapid solidification and its effects on: internal defects formation, phase transformations, residual stresses and distortions. Concerning process optimization, distinct criteria are proposed based on geometric, energetic and thermal considerations, allowing to determine an upper bound limit for the optimum hatch distance during additive manufacturing. Finally, a unified equation to compute the energy density is proposed. This equation enables to compare works performed with distinct equipment and experimental conditions, covering the major process parameters: power, travel speed, heat source dimension, hatch distance, deposited layer thickness and material grain size.

Introduction

Additive manufacturing allows structures fabrication in a layer-by-layer deposition process and is revolutionizing the manufacturing industry due to its ability to obtain near-net shape products, in a short time span, with almost no material waste.

An upmost key feature of additive manufacturing based on melting and solidification, is the use of fundamental knowledge generated by decades of research on welding metallurgy and technologies, based on electric arc and high-energy density beams (laser and electron beam). This experience in welding can be used to better understand the additive manufacturing process and the implications on the microstructural features of the produced parts, including the origin of internal defects (type, morphology, location and quantity).

Most prevailing industrial applications of additive manufacturing use laser beam systems which, under appropriate process control, produce parts with good dimensional precision and surface finish [1], [2], [3]. However, electron beam-based systems tend to deliver sound parts with better mechanical properties, since the process is developed in a vacuum chamber at a uniform high temperature, which decreases residual stresses that build-up during layer deposition. Both electron and laser systems require high investment costs. Thus, additive manufacturing with electric arc and plasma are dedicated to large parts manufacturing.

Alternatively to high-power beams, electric arc heat sources can be used in additive manufacturing where the production rate is a major requirement [4]. Nevertheless, laser or electron beam sources are preferred for parts with fine features or requiring high dimensional tolerances, due to their small size heat source.

Additive manufacturing techniques based on melting and solidification induce complex thermal profiles throughout the material [5], [6]. Whether, the added material is powder or wire, the first layer is melted and solidified onto a substrate. When a second layer is deposited on the previous, the introduced heat must completely melt this second layer and partially re-melt the one underneath. Moreover, a heat affected zone is created in the first deposited layer, which, depending on the material, may promote additional solid-state transformations. This process is repeated over and over until the part is complete. Therefore, the heat introduced to deposit each layer generates successive heat affected zones on previously deposited layers, in a process similar to multipass fusion welding [7], [8], [9], [10]. As in welding, additive manufactured parts experience non-equilibrium solidification [11], [12], [13], due to fast cooling rates observed. The effect of multiple thermal cycles over these non-equilibrium structures may promote the formation of new phases and precipitates if the permanence time at a specific temperature for the solid-state transformation to occur is reached.

As additive manufacturing technologies based on electric arc or high-power beams are still being matured, well-established knowledge from welding metallurgy can be transferred to better understand and improve additive manufacturing techniques.

Currently, the processing parameters used by the additive manufacturing community lack comparability and, thus, a comprehensive effort to encompass the vast generated knowledge over the past years is necessary to foster the development of additive manufacturing techniques into new applications.

Recently, a very comprehensive revision on additive manufacturing was published by DebRoy et al. [1]. The present paper aims to revise fusion welding concepts applicable to additive manufacturing of metals, highlighting the similarities between both technologies and the procedures used in welding that can be directly applicable in additive manufacturing. Specifically, this paper focus on strategies to control the microstructure of the fusion zone in welds in terms of heat source manipulation, optimization of operating procedures and correction of microstructure, to improve mechanical performance and avoid internal defects in additively manufactured parts. In fact, most of existing literature on additive manufacturing is built on welding technology and welding metallurgy. Therefore, this paper intends to evidence how the welding and additive manufacturing communities can establish a synergetic relationship. Concerning additive manufacturing process optimization, distinct criteria (geometric, energetic and thermal) are proposed to determine an upper bound limit for the hatch distance. Finally, an equation to compare energy densities used with different additive manufacturing equipment and varying the most relevant process parameters (power, travel speed, hatch distance, layer thickness, grain size and diameter of the heat source) is proposed.

Section snippets

Welding

The need to produce complex parts constituted a major driving force for the development of welding technologies. In fact, welding dates back from 8000 bC, namely brazing, where a molten metallic alloy with a low melting temperature was poured between two solid materials promoting joining [14]. However, it was just in beginning of the 20th century, that welding became a reality in industry, after major scientific and technological breakthroughs. Some of these developments included mastering of

Additive manufacturing

Several technologies of fusion-based additive manufacturing are currently under development. They all have two common features: (1) the use of computer aided design (CAD) tools to create parts and (2) the part is manufactured in a layer-by-layer deposition strategy. The most important advantage of this new way of manufacturing relies in the freedom to produce, virtually, any shape and geometry, in any material or combination of distinct materials. Other advantages emerge, such as: material

Strategies to improve weld fusion zone microstructures and its application to additive manufacturing

One of the critical issues in fusion-based welding is the development of coarse columnar grains in the fusion zone [61], which, according to the Hall-Petch equation [86], decreases the yield stress of the deposited material and, thus, its mechanical resistance. Additionally, for some materials, such as duplex stainless steels, the existence of large grains in the fusion zone is sufficient to promote a higher amount of austenite upon cooling, thus disrupting the nearly equal proportion of

Process parameter optimization criteria for additive manufacturing

A critical issue in additive manufacturing is to optimize the process parameters to obtain defect-free parts. Typically, in both laser and electron beam additive manufacturing research works, process parameters as power, travel speed and hatch distance are varied to obtain fully dense. However, a literature survey shows that there is a wide range of process parameters combinations capable of obtaining defect-free parts, or defective ones, even when the energy density is the same.

Additionally,

A dimensionless parameter for energy density calculations in additive manufacturing

As referred before, there is no universal equation to determine the energy input or energy density in additive manufacturing. Additionally, from the analysis previously presented, two parameters were not considered, and these were the diameter of the heat source and the powder grain size.

Thus, it is necessary to develop a more generic definition of the energy or power input during additive manufacturing that considers both the heat source diameter and the size of the powder particles or the

Conclusions

This paper evidences the major similarities between fusion-based multipass arc welding and fusion-based additive manufacturing, especially in terms of thermal effects, solidification mechanisms, and chemical reactions within the melted region, as well as, distortion and residual stresses. The major concepts developed in fusion welding were described in detail and applied to different materials that are also being used in additive manufacturing.

Several techniques exist to avoid defects and

Future outlook

Ongoing research on additive manufacturing is too much focused on controlling deposition strategies using internet of things and computer-based tools regardless of materials. This is an important field to assess the economic and social aspects of the technology. However, materials and their properties cannot be disregarded as they are the ones determining the performance of manufactured components.

Thus, refocusing on the technology, other areas still need to be addressed:

  • (1)

    Thermal analysis

Acknowledgements

The authors acknowledge Fundação para a Ciência e Tecnologia (FCT) for its financial support through the project UID/EMS/00667/2019, Fundo Regional para a Ciência e Tecnologia and Projeto de I&DT for companies in copromotion SLM-XL, (Ref 3346), funded by Fundo Europeu de Desenvolvimento Regional (FEDER) through Programa Operacional Regional de Lisboa. The authors acknowledge Dr. Bey Vrancken from Lawrence Livermore National Laboratory and Professor Haijun Gong from Georgia Southern University

J.P. Oliveira is PhD in Materials Science and Engineering (since 2016) and Assistant Professor at the Department of Mechanical and Industrial Engineering (DEMI), NOVA School of Science and Technology of NOVA University of Lisbon (FCT NOVA) and a researcher at UNIDEMI. Dr. Oliveira’s main expertise encompasses the use of advance characterization techniques to correlate the microstructure of welded joints and additive manufacturing parts with their functional and mechanical behavior. Optimization

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    J.P. Oliveira is PhD in Materials Science and Engineering (since 2016) and Assistant Professor at the Department of Mechanical and Industrial Engineering (DEMI), NOVA School of Science and Technology of NOVA University of Lisbon (FCT NOVA) and a researcher at UNIDEMI. Dr. Oliveira’s main expertise encompasses the use of advance characterization techniques to correlate the microstructure of welded joints and additive manufacturing parts with their functional and mechanical behavior. Optimization of manufacturing techniques for non-conventional alloys, such as shape memory alloys and high entropy alloys, is also a major part of his research work. He has lead several industrial and fundamental research projects in the areas of welding and additive manufacturing. He has more than 50 papers in peer-reviewed journal and an h-index of 16 (https://scholar.google.pt/citations?user=xAd2_3oAAAAJ&hl=pt-PT). Prior to his currently position at FCT NOVA he held positions at The Ohio State University and University of Waterloo.

    Telmo G. Santos is PhD in Mechanical Engineering and Associate Professor at the Department of Mechanical and Industrial Engineering (DEMI), NOVA School of Science and Technology of NOVA University of Lisbon (FCT NOVA) and a researcher at UNIDEMI. His main expertise is Non-Destructive Testing (NDT), Friction Stir Welding and Processing (FSW/FSP), Additive Manufacturing (AM) and hybrid manufacturing processes. Since 2011 he coordinated several research and industrial projects, and created the NDTLab at FCT NOVA (http://sites.fct.unl.pt/labndt-demi/). He has more than 50 papers indexed in SCOPUS and an h-index of 17 (https://scholar.google.pt/citations?user=jhGMP44AAAAJ&hl=pt-PT).

    Rosa M. Miranda got her Engineering degree in Metallurgical Engineering at Instituto Superior Técnico, Lisbon Technical University in 1981 and her PhD degree at the same University in 1996. In 2009 got her Habilitation at Faculdade de Ciências e Tecnologia, at Nova University of Lisbon. She is currently Associate Professor with Habilitation in Mechanical Engineering. Her major scientific interests are in the areas of Welding and Joining Technologies (Laser Welding, Friction Stir Welding, Processing and Surfacing Materials), Welding Metallurgy, Materials Processing and Characterization.Professor Miranda has a h-index of 29 (https://scholar.google.pt/citations?user=dgg54dkAAAAJ&hl=pt-PT).

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