PhD abstract: Non-Destructive Defect Detection & Analysis for Additive Manufacturing (AM) of Metals

Introduction

Additive manufacturing (AM) exhibits many advantages over traditional manufacturing processing approaches, such as reduced raw material consumption, highly customised production, and simplification of manufacturing process trains. Thus, in recent years AM has become widely used in industry sectors that produce high-value low-volume products, e.g. aerospace & medical implants. However, unlike polymer AM, metal AM has not yet reached industrial maturity, e.g., material property-microstructure-processing relationships are not well understood. This key problem means that manufacturing defects are relatively common in AM parts, which can lead to suboptimal performance and in extreme cases failure. As mentioned above, such defects are strongly affected by the part material’s physical & mechanical properties.

Approach

Non-destructive testing (NDT) for defects is a key tool for both offline & (latterly) online analysis of new AM parts. NDT for defects has many subtypes including visual testing, electrical testing (eddy current analysis), electromagnetic testing (X‑ray CT), ultrasonic testing, etc. However, CT is the only NDT for defects method for non-destructive identification of internal pores. An obvious limitation is that it cannot distinguish features smaller than the size of one of its volume cells (‘voxels’). This limitation may be partially overcome with the recent method of data-constrained modelling (DCM). DCM enables detailed information about the part’s microstructure to be obtained, specifically estimation of the material’s phase distribution below the resolution of the original scan (sub-voxel material analysis). Therefore, the aim of the project is to build a robust framework for NDT of defects in AM parts using the following workflow; (i) X-ray image acquisition, (ii) CT reconstruction of slices along with artefact pre- & post-processing, and (iii) DCM analysis for 3D microstructure & porosity mapping. This workflow is novel by measuring datasets for porosity properties vs. raw material properties & manufacturing process parameters, an improved understanding of material property-microstructure-processing relationships will be obtained for the first time for a subset of AM methods. Thus, a defect-free product will be easier to produce by design.

Method

Cold spray additive manufacturing (CSAM) and electron beam melting (EBM) will be used to build samples. Micro-CT data will be collected for these samples, and reconstruction slices will be imported into the existing DCM software package. This software takes quantitative multi-energy X-ray CT data as its input and applies the DCM technique to generate microscopic partial volume distributions of material phases and pores at the original resolution of the 3D micro-CT dataset. Critically, unlike general CT image segmentation which treats each voxel as having a single-phase, the DCM method approximates more than one phase per voxel including porosity (Xavier et al., 2020; Ren et al., 2017). A robust workflow will be developed for detecting internal defects within AM metal using these combined NDT techniques, which will be compared in 2D with results from accompanying surface analysis measurements (SEM & EDS).

Materials

Titanium & its alloys are widely used for metal AM. Mixing commercially pure titanium (CPTi) with ceramics can further enhance its capability and reduce defect severity, thus improving finished part quality. Metal matrix composites (MMCs) will be used as an added material with titanium as the matrix.  DCM will be used here with titanium & its alloys to characterize their microstructure and classify the different type of defects and their location distribution.

References

• Ren, Y. Q. et al. (2017). ‘Characterization of heat treatment-induced pore structure changes in cold-sprayed titanium’, Materials Characterization, 132, pp. 69-75. DOI: 10.1016/j.matchar.2017.08.006.
• Xavier, M. S. et al. (2020). ‘Nondestructive quantitative characterisation of material phases in metal additive manufacturing using multi-energy synchrotron X-rays microtomography’, International Journal of Advanced Manufacturing Technology, 106 (5-6), pp. 1601-1615. DOI: 10.1007/s00170-019-04597-y.