A Digital-Twin Methodology for the Non-destructive Certification of Lattice Structures

Abduladheem Almalki,Ma Qian,Bill Lozanovski,Rance Tino,Milan Brandt,Martin Leary,Anton Du Plessis,David Downing

doi:10.1007/s11837-021-05144-5

Abduladheem Almalki, Ma Qian + Show 6 more

Open Access

https://doi.org/10.1007/s11837-021-05144-5

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Journal: JOM	Publication Date: Mar 4, 2022
Citations: 6	License type: open-access

Affiliation: RMIT University, Stellenbosch University

Abstract

Additively manufactured (AM) lattice structures are applied in high-value applications such as lightweight aerospace design and biomedical implants. However, uncertainties of the geometry of as-manufactured AM lattice structures results in uncertainties in the associated mechanical response. This research proposes a non-destructive digital-twin certification methodology that quantifies the functional response of individual strut elements (and associated statistical distributions) from x-ray micro-computed tomography (µCT) data for as-manufactured AM lattice structures. This methodology may be algorithmically applied, as is required for the cost-effective certification of high-value lattice structures. The proposed methodology is demonstrated for a digital twin of over 2000 strut elements within a Ti-6AI-4V lattice fabricated with laser-based powder bed fusion. This digital twin allows various geometric or functional analyses to be performed, and in this case is demonstrated by acquiring statistical distributions of the predicted critical buckling load as a function of the strut element build orientation.

Highlights

Additive manufacturing (AM) enables the layerby-layer fabrication of three-dimensional geometry directly from CAD data, which provides significant advantages over conventional manufacturing.[1]
Lattice structures were fabricated using laser-based powder bed fusion (LB-PBF), a ManufacturingMetal additive manufacturing (MAM) method recognized for its high-resolution features and dimensional control.[4]
This mapping allows algorithmic extraction and quantification of functional elements from the digital twin, allowing numerical analysis of specific lattice elements and the reporting of the statistical response of each element within the entire lattice system. This capability can be applied directly for the algebraic certification of high-value lattice structures, as well as aiding in the optimization of design and processing variables for intended mechanical response. This proposed methodology is demonstrated by a digital twin of over 2000 strut elements within a Ti6AI-4V lattice fabricated by LB-PBF

Summary

Introduction

Additive manufacturing (AM) enables the layerby-layer fabrication of three-dimensional geometry directly from CAD data, which provides significant advantages over conventional manufacturing.[1]. AM can fabricate complex geometry as a single structure, for instance a unitized medical implant, whereas conventional manufacturing constrains designs by the need for tool access.[2]. AM is compatible with topology optimization, thereby enabling mass reduction. Despite these advantages, the AM process is subject to a series of potential technical challenges, including limited production rate, thermal stresses, potentially high material cost and availability, and uncertainties in as-manufactured geometry.[3]. Metal additive manufacturing (MAM) refers to a category of AM processes that melt metal feed stock layer-by-layer to fabricate novel, lightweight, and high-value components such as medical implants or optimized aerospace components. Lattice structures were fabricated using laser-based powder bed fusion (LB-PBF), a MAM method recognized for its high-resolution features and dimensional control.[4]

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