Process-structure relationship in the directed energy deposition of cobalt-chromium alloy (Stellite 21) coatings

Smoqi, Ziyad; Toddy, Joshua; Halliday, Harold; Shield, Jeffrey E.; Rao, Prahalada

doi:10.1016/j.matdes.2020.109229

Cited by 23 publications

(5 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…-20 [86] 200 [87] -410 [85] 0.25 [88] -0.7 [87] 0.25 [87] -0.5 [85] 0.57 [88] -5 [86] Within range: [87,88] Within range: [86,88] 0.25 [88] -0.7 [87] Within range: [87] W 2 [ 89] -5 [90] 200 [89] -2000 [90] 0. 1100 [92] 4.7 [92] 0.75 [92] 2 0 [ 92] Table 3.…”

Section: [85]mentioning

confidence: 99%

Large-scale metal additive manufacturing: a holistic review of the state of the art and challenges

Lehmann

Rose

Ranjbar

et al. 2021

International Materials Reviews

View full text Add to dashboard Cite

Additive Manufacturing (AM) has the potential to completely reshape the manufacturing space by removing the geometrical constraints of commercial manufacturing and reducing component lead time, especially for large-scale parts. Coupling robotic systems with direct energy deposition (DED) additive manufacturing techniques allow for support-free printing of parts where part sizes are scalable from sub-metre to multi-metre sizes. This paper offers a holistic review of large-scale robotic additive manufacturing, beginning with an introduction to AM, followed by different DED techniques, the compatible materials and their typical as-built microstructures. Next, the multitude of robotic build platforms that extend the deposition from the standard 2.5 degrees of freedom (DOF) to 6 and 8 DOF is discussed. With this context, the decomposition and slicing of the computerized model will be described, and the challenges of planning the deposition trajectory will be discussed. The different modalities to monitor and control the deposition in an attempt to meet the geometrical and performance specifications are outlined and discussed. A wide range of metals and alloys have been reported and evaluated for large-scale AM parts. These include steels, Ti, Al, Mg, Cu, Ni, Co-Cr and W alloys. Different post-processing steps, including heat treatments, are discussed, along with their microstructures. This paper finally addresses the authors' perspective on the future of the field and the largest knowledge gaps that need to be filled before the commercial implementation of robotic AM.

show abstract

Section: [85]mentioning

confidence: 99%

Large-scale metal additive manufacturing: a holistic review of the state of the art and challenges

Lehmann

Rose

Ranjbar

et al. 2021

International Materials Reviews

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

“…They have high hardness at high temperature and high corrosion resistance under high pressure and abrasive medium. Among Stellite alloys, Stellite 21 is a popular candidate, [1] containing cobalt-rich dendrites with face-centered-cubic (FCC) crystal structure.Recently, laser cladding-based additive manufacturing has been a trend to deposit such hardfacing metal alloy-based coating to repair/restore industrial components with an aim of improving their wear, corrosion, and fatigue performance. [2] Due to rapid cooling and solidification, the lasercladded microstructure becomes inhomogeneous in the presence of internal residual tensile stresses.…”

mentioning

confidence: 99%

Effect of Combined Grinding–Burnishing Process on Surface Integrity, Tribological, and Corrosion Performance of Laser‐Clad Stellite 21 Alloys

et al. 2023

View full text Add to dashboard Cite

Herein, the influence of the grinding–burnishing on surface integrity, mechanical properties, and corrosion performance of Stellite 21 alloys coating deposited by laser cladding is investigated. The as‐clad specimens are first ground followed by further modification by ball burnishing at forces of 424 N and 509 N. Results show that the grinding–burnishing enhances surface finish by lowering Ra from 2.6 to 0.73 μm and Rz from 13 to 4.9 μm, respectively. Surface porosity is found to decrease from 3.8% to 0.9%. Hardness is increased from 609 HV to 702 HV, with a surface alteration as deep as 250 μm, while wear resistance increases by reducing worn volume from 4.15 to 2.95 mm3. Because of high hardness, the grinding–burnishing increases impact resistance by lowering indent depth by 20%. Grains flatten and surface undulations are remarkably reduced due to burnishing. Finally, grinding–burnishing at 509 N improves the corrosion resistance by increasing positive corrosion potential from −0.41 to −0.14 V and lowering corrosion current density from 6.34 × 10−4 A cm−2 to 2.19 × 10−5 A cm−2, as compared to grinding. This synergistic grinding–burnishing can be a plausible post‐treatment route for the laser‐clad alloys.

show abstract

“…The DED process is particularly valuable for rapid repair or upgrading of damaged or legacy components, enabling the affordable addition of complex features. The process can also enhance existing parts with protective wear or thermal barrier coatings (Smoqi et al , 2021; Saboori et al , 2019).…”

Section: Introductionmentioning

confidence: 99%

Thermal modeling of directed energy deposition additive manufacturing using graph theory

Riensche

Severson

Yavari

et al. 2022

RPJ

Self Cite

View full text Add to dashboard Cite

Purpose The purpose of this paper is to develop, apply and validate a mesh-free graph theory–based approach for rapid thermal modeling of the directed energy deposition (DED) additive manufacturing (AM) process. Design/methodology/approach In this study, the authors develop a novel mesh-free graph theory–based approach to predict the thermal history of the DED process. Subsequently, the authors validated the graph theory predicted temperature trends using experimental temperature data for DED of titanium alloy parts (Ti-6Al-4V). Temperature trends were tracked by embedding thermocouples in the substrate. The DED process was simulated using the graph theory approach, and the thermal history predictions were validated based on the data from the thermocouples. Findings The temperature trends predicted by the graph theory approach have mean absolute percentage error of approximately 11% and root mean square error of 23°C when compared to the experimental data. Moreover, the graph theory simulation was obtained within 4 min using desktop computing resources, which is less than the build time of 25 min. By comparison, a finite element–based model required 136 min to converge to similar level of error. Research limitations/implications This study uses data from fixed thermocouples when printing thin-wall DED parts. In the future, the authors will incorporate infrared thermal camera data from large parts. Practical implications The DED process is particularly valuable for near-net shape manufacturing, repair and remanufacturing applications. However, DED parts are often afflicted with flaws, such as cracking and distortion. In DED, flaw formation is largely governed by the intensity and spatial distribution of heat in the part during the process, often referred to as the thermal history. Accordingly, fast and accurate thermal models to predict the thermal history are necessary to understand and preclude flaw formation. Originality/value This paper presents a new mesh-free computational thermal modeling approach based on graph theory (network science) and applies it to DED. The approach eschews the tedious and computationally demanding meshing aspect of finite element modeling and allows rapid simulation of the thermal history in additive manufacturing. Although the graph theory has been applied to thermal modeling of laser powder bed fusion (LPBF), there are distinct phenomenological differences between DED and LPBF that necessitate substantial modifications to the graph theory approach.

show abstract

Process-structure relationship in the directed energy deposition of cobalt-chromium alloy (Stellite 21) coatings

Cited by 23 publications

References 38 publications

Large-scale metal additive manufacturing: a holistic review of the state of the art and challenges

Large-scale metal additive manufacturing: a holistic review of the state of the art and challenges

Effect of Combined Grinding–Burnishing Process on Surface Integrity, Tribological, and Corrosion Performance of Laser‐Clad Stellite 21 Alloys

Thermal modeling of directed energy deposition additive manufacturing using graph theory

Contact Info

Product

Resources

About