Fatigue Modeling for Laser-Fused Metal Components With Small Data: From Scattering to Reliability

Abstract Fatigue scattering caused by inherent geometrical defects in laser powder bed fusion (LPBF) imposes a great challenge for fabricating reliable load-bearing components. However, the lack of sufficient fatigue data and the limitation of runout conditions rationalize the need to bridge the gap between limited data and fatigue reliability. This work has developed two models based on censored linear regression (CR) and censored Gaussian process regression (CGP), respectively, to predict fatigue life scattering bounds at a given confidence for both as-built and heat-treated SS 316L samples. Furthermore, fatigue life reliability is modeled under different stress amplitudes with a CGP-based reliability model.

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Publication Details

Journal
Journal of Manufacturing Science and Engineering
Published
2025-07-18
DOI
https://doi.org/10.1115/1.4069197
Citations
1
Primary Topic
Additive Manufacturing Materials and Processes
Type
article
Field-Weighted Citation Impact
0.71
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article

Fatigue Modeling for Laser-Fused Metal Components With Small Data: From Scattering to Reliability

Shiyu Zhou, Zhimin Xi, Y. B. Guo, Panayiotis Kousoulas et al.
1 citations
Journal of Manufacturing Science and Engineering
Additive Manufacturing Materials and Processes
0.71
article

Fatigue Modeling for Laser-Fused Metal Components With Small Data: From Scattering to Reliability

Shiyu Zhou, Zhimin Xi, Y. B. Guo, Panayiotis Kousoulas, Vipul Bansal
article en
1 citations

Abstract

Abstract Fatigue scattering caused by inherent geometrical defects in laser powder bed fusion (LPBF) imposes a great challenge for fabricating reliable load-bearing components. However, the lack of sufficient fatigue data and the limitation of runout conditions rationalize the need to bridge the gap between limited data and fatigue reliability. This work has developed two models based on censored linear regression (CR) and censored Gaussian process regression (CGP), respectively, to predict fatigue life scattering bounds at a given confidence for both as-built and heat-treated SS 316L samples. Furthermore, fatigue life reliability is modeled under different stress amplitudes with a CGP-based reliability model.

Journal of Manufacturing Science and EngineeringVol. 147(10)
Rutgers, The State University of New Jersey (US), University of Wisconsin–Madison (US), Polish Institute of Arts and Sciences of America (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 29%
Additive Manufacturing Materials and Processes
0.71
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Fatigue Modeling for Laser-Fused Metal Components With Small Data: From Scattering to Reliability — Shiyu Zhou, Zhimin Xi, et al. · Journal of Manufacturing Science and Engineering (2025) | TGRS Research Map | TGRS