Technical Summary

Additive manufacturing (AM) is a transformative technology that fabricates objects by sequentially layering materials according to digital designs. Unlike traditional subtractive methods that remove material, AM minimises waste while enabling the creation of intricate and complex geometries. It has broad applications across industries—from healthcare, where it supports the development of customised prosthetics and implants, to aerospace and automotive sectors, where lightweight, high-performance components are essential. Despite its advantages, the structural integrity of 3D-printed parts can be compromised by various issues, including poor layer adhesion, warping, porosity, surface roughness, mechanical weaknesses, and residual stresses. These defects often stem from factors such as uneven heating and cooling, excessive laser power, insufficient fusion, gas entrapment, and notably, the anisotropic grain structures characteristic of additively manufactured components. Addressing these challenges is critical to enhancing the strength, accuracy, and reliability of AM-produced parts for industrial applications.

This research focuses on the fracture behaviour of Powder Bed Fusion (PBF) components fabricated from Ti-6Al-4V (Ti64)—the most widely used titanium alloy due to its high strength-to-weight ratio and corrosion resistance. This work combines experimental testing and numerical simulations to characterise the fracture properties of Ti64 and assess the structural integrity of 3D-printed components. Experimental and computational findings will be cross-validated and used to develop a machine learning model capable of predicting crack initiation, crack propagation at multiple scales, and the overall strength and durability of AM parts.