Title

Additively Manufactured Lattices for Orthopedic Implants and Process Monitoring of Laser-Powder Bed Fusion Using Neural Networks

Date of Award

1-1-2019

Degree Name

M.S. in Electrical Engineering

Department

Department of Electrical and Computer Engineering

Advisor/Chair

Advisor: Amy Neidhard-Doll

Abstract

The call for orthopedic implants is a growing concern with a vastly enlarging elderly population and countries with developing healthcare, such as China and India. Lattice structures created by additive manufacturing offer patient specific orthopedic implants with viscoelastic properties similar to bone, less material consumption (such as titanium) and promotion of internal bone growth for better fixation. Patient specific lattices are possible with the onset of medical imaging technologies, allowing for custom additive manufacturing implants suited to each individual. Current orthopedic implants are restricted to numerous standard sizes, where a surgeon will choose between two or more sizes for implant insertion. An implant with better fitment will reduce complications and make the surgical process simpler. Two different biomimetic lattice structures with cubic and diamond strut geometries were printed in Ti-6Al-4V of an open architecture selective laser melting machine. These lattice structures varied in pore size of 400, 500, 600 and 900?m to mini varying densities of trabecular bone in-vivo. Properties needed to promote osseointegration were reviewed, such as pore size and lattice geometry. A convolutional neural network was employed to detect defects and geometries during the selective laser melting process. Identifying defects and geometries is called process monitoring. Combining process monitoring, along with non-destruction evaluation such as computer tomography scanning and scanning electron microscope techniques, can properly identify defects for biomedical and aeronautical applications.

Keywords

Electrical Engineering, Orthopedic Implants, Neural Networks, Lattice, Biomimetic, SLM, Ti-6Al-4V, Process Monitoring

Rights Statement

Copyright 2019, author

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