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The additive manufacturing (AM) offers the benefits of direct manufacturing of components with complex geometries. The Ti-6Al4V (Ti64) alloy prepared by AM requires high-quality densification if outstanding mechanical properties are sought. The method based on laser powder bed fusion can be accompanied by the appearance of micro-cracks/discontinuities in the case of the layer-by-layer thermal process. Nondestructive evaluation (NDE) based on ultrasound and eddy current allows the detection and estimation of the location and size of discontinuities in metal parts. They are oriented toward automation and data sharing in various technologies at the initial stage of production, which can exclude defective construction materials and identify the causes of certain damage. Research focused on NDE using complementary methods can provide potentially relevant data for the transition to NDE automation through learning.

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Complementary Methods for Assessing Integrity of Layered Mesostructures

  • 章节

  • 发表日期：

    2026年

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  • Savin Adriana,
  • Faktorova Dagmar,
  • Moraras Ciprian,
  • Stanciu Mariana Domnica,
  • Soare Marian,
  • Steigmann Rozina

摘要

The additive manufacturing (AM) offers the benefits of direct manufacturing of components with complex geometries. The Ti-6Al4V (Ti64) alloy prepared by AM requires high-quality densification if outstanding mechanical properties are sought. The method based on laser powder bed fusion can be accompanied by the appearance of micro-cracks/discontinuities in the case of the layer-by-layer thermal process. Nondestructive evaluation (NDE) based on ultrasound and eddy current allows the detection and estimation of the location and size of discontinuities in metal parts. They are oriented toward automation and data sharing in various technologies at the initial stage of production, which can exclude defective construction materials and identify the causes of certain damage. Research focused on NDE using complementary methods can provide potentially relevant data for the transition to NDE automation through learning.