Tailored Surface Texture Characterisation of Metal Additive Components for Aerospace Applications

Abstract

In the past decades, additive manufacturing (AM) has evolved from a rapid prototyping technology to a mature manufacturing process, offering significant advantages for lightweight design and specialized applications. Surface quality is crucial for the qualification of metal AM parts, particularly for load-bearing aerospace applications. Surface quality from a laser powder bed fusion (LPBF) AM process is typically characterised by agglomerations of attached powder particles, spatter, and weld or layer tracks, influenced by material, powder properties, build direction, and other factors. This work aims to provide a more comprehensive understanding and holistic description of LPBF surface quality, its formation, characterisation, and role in part functionality, using novel approaches and advanced optical measurement techniques.

The thesis is divided into three parts: "Measurement and Data Post-processing," "Surface Texture and Mechanical Properties," and "Areal Surface Features."

The first part discusses the application of optical measurements and related challenges for as-built and post-processed LPBF surfaces. Current industry practices use stylus contact measurements yielding 2D profiles, which are inadequate for LPBF's complex surface structures. Areal measurements, such as confocal microscopy and fringe projection, offer better surface coverage, reproducibility, and prevent surface damage. The transition from 2D to 3D parameters and from contact stylus to non-contact optical methods is proposed for comprehensive surface data.

The second part suggests describing AM surfaces in terms of part functionality, introducing surface texture parameters from the material ratio curve for fatigue performance, instead of traditional 2D parameters like Rt and Ra. Parameters like Svk, derived from the surface height distribution, relate well to fatigue failure modes in LPBF parts. Optimised processing parameters can achieve surface and mechanical properties comparable to post-processed and conventionally manufactured parts, potentially eliminating the need for surface post-processing.

The third part focuses on process-related surface texture characterisation, advancing functionality-based descriptions. It proposes using the particle size distribution of the processed metal powder to set pruning thresholds for feature segmentation, instead of ISO 25178's extreme value Sz. A novel approach to feature-based segmentation is developed.

These advancements will make AM more accessible and sustainable, broadening its application across various sectors with specialised functionality requirements.