Physics-Informed Uncertainty Quantification in Modeling of Machining-Induced Residual Stress

Machining processes involve various sources of uncertainty which lead to inaccurate interpretation of results in the surface integrity of machined products. This work presents a physics-informed, data-driven modeling framework for achieving comprehensive uncertainty quantification (UQ) of the impact...

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Bibliographic Details
Published in:Procedia CIRP 2023, Vol.117, p.139-144
Main Authors: Hasan, Md Mehedi, Schoop, Julius
Format: Article
Language:English
Subjects:
Calibration
Residual Stress
Surface Integrity
Uncertainty Quantification
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Summary:Machining processes involve various sources of uncertainty which lead to inaccurate interpretation of results in the surface integrity of machined products. This work presents a physics-informed, data-driven modeling framework for achieving comprehensive uncertainty quantification (UQ) of the impact of process and material variability on machining-induced residual stress (RS). Uncertainty due to the variation in bulk material properties and model input parameters in machining are considered. Preliminary results showed that variations in calibration parameters have a substantial effect on modeling RS, while the variation in material properties has a smaller effect. Further research directions for UQ in machining are also outlined.
ISSN:2212-8271
2212-8271
DOI:10.1016/j.procir.2023.03.025