High throughput mechanical testing platform and application in metal additive manufacturing and process optimization

2021 ◽  
Vol 66 ◽  
pp. 494-505
Author(s):  
Ke Huang ◽  
Chris Kain ◽  
Nathalia Diaz-Vallejo ◽  
Yongho Sohn ◽  
Le Zhou
Keyword(s):  
Additive Manufacturing ◽  
Mechanical Testing ◽  
Process Optimization ◽  
High Throughput ◽  
Metal Additive Manufacturing ◽  
Testing Platform ◽  
Metal Additive

scholarly journals Uncertainty quantification and reduction in metal additive manufacturing

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Zhuo Wang ◽  
Chen Jiang ◽  
Pengwei Liu ◽  
Wenhua Yang ◽  
Ying Zhao ◽  
...  
Keyword(s):  
Quality Control ◽  
Additive Manufacturing ◽  
Computational Model ◽  
Uncertainty Quantification ◽  
High Throughput ◽  
Surrogate Model ◽  
Metal Additive Manufacturing ◽  
Uncertainty Sources ◽  
Melt Pool ◽  
Metal Additive

AbstractUncertainty quantification (UQ) in metal additive manufacturing (AM) has attracted tremendous interest in order to dramatically improve product reliability. Model-based UQ, which relies on the validity of a computational model, has been widely explored as a potential substitute for the time-consuming and expensive UQ solely based on experiments. However, its adoption in the practical AM process requires overcoming two main challenges: (1) the inaccurate knowledge of uncertainty sources and (2) the intrinsic uncertainty associated with the computational model. Here, we propose a data-driven framework to tackle these two challenges by combining high throughput physical/surrogate model simulations and the AM-Bench experimental data from the National Institute of Standards and Technology (NIST). We first construct a surrogate model, based on high throughput physical simulations, for predicting the three-dimensional (3D) melt pool geometry and its uncertainty with respect to AM parameters and uncertainty sources. We then employ a sequential Bayesian calibration method to perform experimental parameter calibration and model correction to significantly improve the validity of the 3D melt pool surrogate model. The application of the calibrated melt pool model to UQ of the porosity level, an important quality factor, of AM parts, demonstrates its potential use in AM quality control. The proposed UQ framework can be generally applicable to different AM processes, representing a significant advance toward physics-based quality control of AM products.

scholarly journals Hybrid metal additive manufacturing: A state–of–the-art review

2021 ◽  
Vol 2 ◽  
pp. 100032
Author(s):  
J.P.M. Pragana ◽  
R.F.V. Sampaio ◽  
I.M.F. Bragança ◽  
C.M.A. Silva ◽  
P.A.F. Martins
Keyword(s):  
Additive Manufacturing ◽  
State Of The Art ◽  
Metal Additive Manufacturing ◽  
Metal Additive

scholarly journals Towards the industrialization of metal additive manufacturing

2021 ◽  
Vol 18 (3) ◽  
pp. 32-37
Author(s):  
Francesca Moglia ◽  
Antonio Raspa
Keyword(s):  
Additive Manufacturing ◽  
Metal Additive Manufacturing ◽  
Metal Additive

scholarly journals Influences of powder morphology and spreading parameters on the powder bed topography uniformity in powder bed fusion metal additive manufacturing

2021 ◽  
Vol 38 ◽  
pp. 101807
Author(s):  
Andre Mussatto ◽  
Robert Groarke ◽  
Aidan O’Neill ◽  
Muhannad Ahmed Obeidi ◽  
Yan Delaure ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Powder Bed Fusion ◽  
Powder Morphology ◽  
Powder Bed ◽  
Metal Additive Manufacturing ◽  
Bed Topography ◽  
Metal Additive

An optimized pressure vessel made of metal additive manufacturing: Preliminary results

2021 ◽  
pp. 104434
Author(s):  
Hassan Mohamed Abdelalim Abdalla ◽  
Daniele Casagrande ◽  
Francesco De Bona ◽  
Thomas De Monte ◽  
Marco Sortino ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Pressure Vessel ◽  
Metal Additive Manufacturing ◽  
Preliminary Results ◽  
Metal Additive

scholarly journals An integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing

2020 ◽  
Vol 51 ◽  
pp. 26-31
Author(s):  
Mihail Babcinschi ◽  
Bernardo Freire ◽  
Lucía Ferreira ◽  
Baltasar Señaris ◽  
Felix Vidal ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Metal Additive Manufacturing ◽  
Metal Additive
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