Build parameter influence on strut thickness and mechanical performance in additively manufactured titanium lattice structures.

Additively manufactured lattices have been adopted in applications ranging from medical implants to aerospace components. For solid AM components, the effect of build parameters has been well studied but comparably little attention has been paid to the influence of build parameters on lattice performance. For this project, the main aim was to evaluate static compressive mechanical performance of regular and stochastic lattices as a function of build parameters.

Influence of topology optimization parameters on the mechanical response of an additively manufactured test structure.

Topology Optimization (TO) determines a material distribution within a domain under given conditions and design constraints, and generally generates complex geometries as a result. Complementary to TO, Additive Manufacturing (AM) offers the ability to fabricate complex geometries which may be difficult to manufacture using traditional techniques such as milling. AM has been used in multiple industries including the medical devices area.

Dimensional variability characterization of additively manufactured lattice coupons.

Background: Additive manufacturing (AM), commonly called 3D Printing (3DP), for medical devices is growing in popularity due to the technology's ability to create complex geometries and patient-matched products. However, due to the process variabilities which can exist between 3DP systems, manufacturer workflows, and digital conversions, there may be variabilities among 3DP parts or between design files and final manufactured products. The overall goal of this project is to determine the dimensional variability of commercially obtained 3DP titanium lattice-containing test coupons and compare it to the original design files.

Nylon lattice design parameter effects on additively manufactured structural performance.

Lattice structures are used in a multitude of applications from medical to aerospace, and their adoption in these applications has been further enabled by additive manufacturing. Lattice performance is governed by a multitude of variables and estimating this performance may be needed during various phases of the design and validation process. Numerical modeling and constitutive relationships are common methodologies to assess performance, address risks, lower costs, and accelerate time to market for innovative and potentially life altering products.