A Critical Review of the Material Characteristics of Additive Manufactured IN718 for High-Temperature Application

Yong, Ching Kiat; Gibbons, Gregory John; Wong, Chow Cher; West, Geoff

doi:10.3390/met10121576

Cited by 32 publications

(5 citation statements)

References 147 publications

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“…However, when it comes to the machinability, the high mechanical strength of IN718 can be a drawback. The machining operation of this alloy is a time-consuming and costly process [15], which is a big hindrance to forming the complex geometry components needed in the aforementioned industries. This limitation has led to the inability of traditional manufacturing techniques in the fabrication of IN718 parts with complicated geometries.…”

Section: Introductionmentioning

confidence: 99%

A Prediction Model for Additive Manufacturing of Inconel 718 Superalloy

et al. 2021

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Inconel 718 is a nickel-based superalloy and an excellent candidate for the aerospace, oil, and gas industries due to its high strength and corrosion resistance properties. The machining of IN718 is very challenging; therefore, the application of additive manufacturing (AM) technology is an effective approach to overcoming these difficulties and for the fabrication of complex geometries that cannot be manufactured by the traditional techniques. Selective laser melting (SLM), which is a laser powder bed fusion method, can be applied for the fabrication of IN718 samples with high accuracy. However, the process parameters have a high impact on the properties of the manufactured samples. In this study, a prediction model is developed for obtaining the optimal process parameters, including laser power, hatch spacing, and scanning speed, in the SLM process of the IN718 alloy. For this purpose, artificial neural network (ANN) modeling with various algorithms is employed to estimate the process outputs, namely, sample height and surface hardness. The modeling results fit perfectly with the experimental output, and this consequently proves the benefit of ANN modeling for predicting the optimal process parameters.

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Section: Introductionmentioning

confidence: 99%

A Prediction Model for Additive Manufacturing of Inconel 718 Superalloy

et al. 2021

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“…Gamma phase is observed as the main phase in Figure 9, which is also mentioned in [4,22,42,43]. The XRD analysis revealed no presence of Ni 3 (Al, Ti), Ni 3 Nb, and intermetallic Laves ((Ni, Cr, Fe) 2 (Nb, Mo, Ti)) phases [4,44,45]. As shown in Figure 9, the intensity of the maximums varies, which can be explained by differences in texture.…”

Section: Microstructural and Phase Analysismentioning

confidence: 57%

Modification of Mechanical Properties in Directed Energy Deposition by a Static Magnetic Field: Experimental and Theoretical Analysis

et al. 2021

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The superimposed magnetic field affects the microstructure and mechanical properties of additively manufactured metal parts. In this work, the samples were fabricated from Inconel 718 superalloy by directed energy deposition under a 0.2T static field. The magnetohydrodynamic 1D model is proposed for the estimation of a fluid flow inside a molten pool. According to the theoretical predictions, the fluid flow is slightly decreased by an applied field. The estimated thermoelectric magnetic convection in the mushy zone is shown to be negligible to change in subgrain size, but enough to reduce the hard-to-dissolve Nb-rich phase, thereby improving the average ultimate elongation from 23% to 27%. The obtained results confirm that an external static magnetic field can modify and enhance the mechanical properties of additively manufactured materials.

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“…Furthermore, a comprehensive review of the mechanical properties of additively manufactured IN718 was done by Hosseini and Popovich [ 25 ]. Additionally, the characteristics of additively manufactured IN718 for high-temperature applications were reviewed by Yong et al [ 26 ].…”

Section: Solidification Microstructure Evolution Within Pbf-lbmentioning

confidence: 99%

Digitisation of metal AM for part microstructure and property control

et al. 2022

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Metal additive manufacturing, which uses a layer-by-layer approach to fabricate parts, has many potential advantages over conventional techniques, including the ability to produced complex geometries, fast new design part production, personalised production, have lower cost and produce less material waste. While these advantages make AM an attractive option for industry, determining process parameters which result in specific properties, such as the level of porosity and tensile strength, can be a long and costly endeavour. In this review, the state-of-the-art in the control of part properties in AM is examined, including the effect of microstructure on part properties. The simulation of microstructure formation via numerical simulation and machine learning is examined which can provide process quality control and has the potential to aid in rapid process optimisation via closed loop control. In-situ monitoring of the AM process, is also discussed as a route to enable first time right production in the AM process, along with the hybrid approach of AM fabrication with post-processing steps such as shock peening, heat treatment and rolling. At the end of the paper, an outlook is presented with a view towards potential avenues for further research required in the field of metal AM.

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A Critical Review of the Material Characteristics of Additive Manufactured IN718 for High-Temperature Application

Cited by 32 publications

References 147 publications

A Prediction Model for Additive Manufacturing of Inconel 718 Superalloy

A Prediction Model for Additive Manufacturing of Inconel 718 Superalloy

Modification of Mechanical Properties in Directed Energy Deposition by a Static Magnetic Field: Experimental and Theoretical Analysis

Digitisation of metal AM for part microstructure and property control

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