Overview of Methods and Software for the Design of Functionally Graded Lattice Structures

Lattice structures are known for their superior performance in weight reduction, stiffness, and increased manufacturability, but when materials need to be adaptive, multifunctional, and with tunable properties, functionally graded lattice structures (FGLS) play a crucial role in innovative solutions. Recent digital manufacturing technologies offer ideal conditions for creating lattice structures with high geometrical complexity and functional gradients. However, the design and development of these inherently complex structures often require the use of specialized methods and software tools. As researchers venture from diverse areas into the research of FGLS in search of novel applications, it is important to choose adequate design tools. Herein, an overview of methods and software for the design of FGLS is presented, identifying geometrical parameters of common lattice topologies and ways to manipulate them to create functional gradients. Fifty software applications or methods are listed, dedicated to the design of single material lattices produced by additive manufacturing processes. Typical applications of the reviewed software are identified, and FGLS design methods are compared. Generative Design seems more suited as an explorative process, Topology Optimization is an established efficiency‐focused design process, and Machine Learning is considered a promising data‐driven approach for the design of innovative FGLS. Herein, an overview is made of methods and tools for the design of functionally graded lattice structures (FGLSs). The most common lattice parameters are identified, and several design methods that are currently used for the design of graded lattices. Fifty design software applications are listed, the methods are compared and discussed, ending with typical application examples and general considerations.