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February 21, 2026Procedia CIRP0 citationsOpen Access

Characterisation of Geometric Accuracy in Metal Fused Filament Fabricated Parts Using X-ray Computed Tomography

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RTRoham Sadeghi TabarAKAndi KuswoyoCMChristos Margadji

Key Points

  • To quantify geometric deviations in metal parts produced by Fused Filament Fabrication using X-ray computed tomography.
  • Conducted geometric analysis using X-ray computed tomography on metal parts before and after sintering.
  • Utilized Ultrafuse 316L stainless steel filament for fabrication.
  • Implemented thermo-mechanical sintering simulation to predict shrinkage and deformation.
  • Aligned XCT data to nominal geometries for assessment of deviations.
  • Identified location-dependent discrepancies in deformation exceeding 2 mm in critical areas.
  • Simulation errors varied between 0.5 mm and 2 mm compared to XCT data.
  • Highlighted limitations of standard shrinkage scaling in the characterization process.

Abstract

This work presents a methodology for quantifying geometric deviations in metal parts fabricated via Fused Filament Fabrication (FFF) using Ultrafuse 316L stainless steel filament. A blade-shaped geometry is selected as a representative case and analysed before and after sintering using high-resolution X-ray computed tomography (XCT). The XCT data are aligned to nominal and scaled geometries to assess deviations introduced during each manufacturing stage. In parallel, a thermo-mechanical sintering simulation is performed to predict shrinkage and deformation. Comparison between simulated results and XCT data reveals location-dependent discrepancies, with deformation at critical regions exceeding 2 mm and simulation errors ranging from 0.5 to 2 mm. The study highlights the limitations of standard shrinkage scaling and demonstrates the value of XCT-based characterisation in validating and improving predictive models for metal FFF. The proposed approach provides a foundation for model-informed design and process compensation strategies in sintering-based additive manufacturing.

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Cite This Study

Tabar et al. (2026) studied this question.

synapsesocial.com/papers/69994bdd873532290d01fed1https://doi.org/10.1016/j.procir.2025.09.045
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