Statistically-substantiated density characterizations of additively manufactured steel alloys through verification, validation, and uncertainty quantification

Reed, Heather; Vinci, Richard P.; Robeck, Corbin; Verdonik, Trevor; Pires, Michael; Castro, María; Misiołek, Wojciech Z.; Haden, Christina Viau

doi:10.1109/bigdata.2017.8258119

Cited by 1 publication

(1 citation statement)

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“…A lot of the work on uncertainty evaluation in AM processes to date has focussed on assessing process variability by measuring the finished product and considering this as uncertainty [137][138][139]. Whilst this approach does not generally return enough information or understanding to know how to improve a process, it can provide information of the sort needed to validate models in a statistically meaningful way.…”

Section: General Overviewmentioning

confidence: 99%

Metal powder bed fusion process chains: an overview of modelling techniques

et al. 2021

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Metal powder bed fusion (MPBF) is not a standalone process, and other manufacturing technologies, such as heat treatment and surface finishing operations, are often required to achieve a high-quality component. To optimise each individual process for a given component, its progression through the full process chain must be considered and understood, which can be achieved through the use of validated models. This article aims to provide an overview of the various modelling techniques that can be utilised in the development of a digital twin for MPBF process chains, including methods for data transfer between physical and digital entities and uncertainty evaluation. An assessment of the current maturity of modelling techniques through the use of technology readiness levels is conducted to understand their maturity. Summary remarks highlighting the advantages and disadvantages in physics-based modelling techniques used in MPBF research domains (i.e. prediction of: powder distortion; temperature; material properties; distortion; residual stresses; as well as topology optimisation), post-processing (i.e. modelling of: machining; heat treatment; and surface engineering), and digital twins (i.e. simulation of manufacturing process chains; interoperability; and computational performance) are provided. Future perspectives for the challenges in these MPBF research domains are also discussed and summarised.

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Section: General Overviewmentioning

confidence: 99%