A review on measurement science needs for real-time control of additive manufacturing metal powder bed fusion processes

Mani, Mahesh; Lane, Brandon; Donmez, M A.; Feng, Shaw C.; Moylan, Shawn P.

doi:10.1080/00207543.2016.1223378

Cited by 177 publications

(70 citation statements)

References 121 publications

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“…12 Furthermore, in order to reduce oxygen contamination, the chamber is kept under positive pressure. [13][14] SLM is suitable for producing highly complex parts with high dimensional tolerance. The build resolution is generally dictated by the powder size used, which is typically the range of 10 μm to 45 μm in diameter.…”

Section: Metal Additive Manufacturingmentioning

confidence: 99%

Corrosion of Additively Manufactured Alloys: A Review

et al. 2018

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Additive manufacturing (AM), often termed 3D printing, has recently emerged as a mainstream means of producing metallic components from a variety of metallic alloys. The numerous benefits of AM include net shape manufacturing, efficient use of material, suitability to low volume production runs, and the ability to explore alloy compositions not previously accessible to conventional casting. The process of AM, which is nominally performed using laser (or electron) based local melting, has a definitive role in the resultant alloy microstructure. Herein, the corrosion of alloys prepared by AM using laser and electronbased methods, relating the corrosion performance to the microstructural features influenced by AM processing, are reviewed. Such features include unique porosity, grain structures, dislocation networks, residual stress, solute segregation, and surface roughness. Correlations between reported results and deficiencies in present understanding are highlighted.

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Section: Metal Additive Manufacturingmentioning

confidence: 99%

Corrosion of Additively Manufactured Alloys: A Review

et al. 2018

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“…A summary of in situ methods is provided in several reviews (e.g., References [ 17 , 18 , 19 , 20 , 21 ]). Most sensor techniques are related to either optical (e.g., References [ 16 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 ]) or acoustic methods (e.g., References [ 32 , 33 , 34 , 35 , 36 ]), which were often originally applied to laser welding [ 37 ].…”

Section: Introductionmentioning

confidence: 99%

Pyrometric-Based Melt Pool Monitoring Study of CuCr1Zr Processed Using L-PBF

et al. 2020

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The potential of in situ melt pool monitoring (MPM) for parameter development and furthering the process understanding in Laser Powder Bed Fusion (LPBF) of CuCr1Zr was investigated. Commercial MPM systems are currently being developed as a quality monitoring tool with the aim of detecting faulty parts already in the build process and, thus, reducing costs in LPBF. A detailed analysis of coupon specimens allowed two processing windows to be established for a suitably dense material at layer thicknesses of 30 µm and 50 µm, which were subsequently evaluated with two complex thermomechanical-fatigue (TMF) panels. Variations due to the location on the build platform were taken into account for the parameter development. Importantly, integrally averaged MPM intensities showed no direct correlation with total porosities, while the robustness of the melting process, impacted strongly by balling, affected the scattering of the MPM response and can thus be assessed. However, the MPM results, similar to material properties such as porosity, cannot be directly transferred from coupon specimens to components due to the influence of the local part geometry and heat transport on the build platform. Different MPM intensity ranges are obtained on cuboids and TMF panels despite similar LPBF parameters. Nonetheless, besides identifying LPBF parameter windows with a stable process, MPM allowed the successful detection of individual defects on the surface and in the bulk of the large demonstrators and appears to be a suitable tool for quality monitoring during fabrication and non-destructive evaluation of the LPBF process.

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“…In order to show its practical applicability and to highlight the benefits of a functional data approach, the FoF linear regression model is applied to a real‐life case study in the additive manufacturing (AM) field. The impact of many characteristics of raw materials on the final properties of the produced parts is in fact still an open research issue and hampers the industrialization of additive technologies, 18–21 which are, on the other hand, also very costly. In particular, the considered AM process refers to a laser powder bed fusion (L‐PBF) technique for metals, which enables the layer‐wise production of complex‐shaped components through spreading and selective laser melting of subsequent metal powder layers onto a substrate plate 22–24 …”

Section: Introductionmentioning

confidence: 99%

Function‐on‐function regression for assessing production quality in industrial manufacturing

Palumbo

Centofanti

2020

Quality & Reliability Eng

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Key responses of manufacturing processes are often represented by spatially or time‐ordered data known as functional data. In practice, these are usually treated by extracting one or few representative scalar features from them to be used in the following analysis, with the risk of discarding relevant information available in the whole profile and of drawing only partial conclusions. To avoid that, new and more sophisticated methods can be retrieved from the functional data analysis (FDA) literature. In this work, that represents a contribution in the direction of integrating FDA methods into the manufacturing field, the use of function‐on‐function linear regression modelling is proposed. The approach is based on a finite‐dimensional approximation of the regression coefficient function by means of two sets of basis functions, and two roughness penalties to control the degree of smoothness of the final estimator. The potential of the proposed method is demonstrated by applying it to a real‐life case study in powder bed fusion additive manufacturing for metals to predict the mechanical properties of an additively manufactured artefact, given the particle size distribution of the powder used for its production.

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A review on measurement science needs for real-time control of additive manufacturing metal powder bed fusion processes

Cited by 177 publications

References 121 publications

Corrosion of Additively Manufactured Alloys: A Review

Corrosion of Additively Manufactured Alloys: A Review

Pyrometric-Based Melt Pool Monitoring Study of CuCr1Zr Processed Using L-PBF

Function‐on‐function regression for assessing production quality in industrial manufacturing

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