Statistical analysis to assess porosity equivalence with uncertainty across additively manufactured parts for fatigue applications

TL;DR

This paper introduces a statistical framework with uncertainty quantification to compare porosity in additively manufactured parts, improving fatigue failure predictions by capturing pore size distribution variability.

Contribution

It develops a novel uncertainty-aware extreme value statistical method to assess porosity equivalence across different geometries in additive manufacturing.

Findings

Largest pore size distribution varies between geometries despite similar dimensions.

Uncertainty quantification improves pore size estimation accuracy.

Porosity equivalence assessment informs better fatigue design strategies.

Abstract

Previous work on fatigue prediction in Powder Bed Fusion - Laser Beam has shown that the estimate of the largest pore size within the stressed volume is correlated with the resulting fatigue behavior in porosity-driven failures. However, single value estimates for the largest pore size are insufficient to capture the experimentally observed scatter in fatigue properties. To address this gap, in this work, we incorporate uncertainty quantification into extreme value statistics to estimate the largest pore size distribution in a given volume of material by capturing uncertainty in the number of pores present and the upper tail parameters. We then applied this statistical framework to compare the porosity equivalence between two geometries: a 4-point bend fatigue specimen and an axial fatigue specimen in the gauge section. Both geometries were manufactured with the same process conditions using Ti-6Al-4V, followed by porosity characterization via X-ray Micro CT. The results show that the largest pore size distribution of the 4-point bend specimen is insufficient to accurately capture the largest pore size observed in the axial fatigue specimen, despite similar dimensions. Based on our findings, we provide insight into the design of witness coupons that exhibit part-to-coupon porosity equivalence for fatigue.