About this Abstract |
Meeting |
2022 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2022)
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Symposium
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2022 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2022)
|
Presentation Title |
Uncertainty Quantification of Response Surface Methodology to Establish an Efficient Printability Assessment Framework in Directed Energy Deposition |
Author(s) |
Jiahui Ye, Matthew Vaughan, Ibrahim Karaman, Raymundo Arroyave, Alaa Elwany |
On-Site Speaker (Planned) |
Jiahui Ye |
Abstract Scope |
Increasing impact of metal additive manufacturing (AM) on wider industrial sectors has motivated the development of new alloys specifically designed for AM. To efficiently assess whether a tailored alloy is a good candidate for metal AM, as well as identify process windows for defect-free parts, the AM community has gradually realized the significance of printability assessment frameworks. However, such a framework is still lacking for the complex powder-based laser directed energy deposition (L-DED) processes. In this presentation, we highlight an efficient printability assessment framework for L-DED demonstrated by the case study of 316 stainless steel. For printability maps establishment, a statistical model based on response surface methodology (RSM) is initially built to predict melt pool characteristics, followed by uncertainty quantification and Bayesian calibration to future improve model prediction accuracy. The proposed methodology provides a time- and cost-efficient solution to determine printability of both existing and newly designed alloys for L-DED. |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |