Abstract
One crucial advantage of additive manufacturing regarding the optimization of lattice structures is that there is a reduction in manufacturing constraints compared to classical manufacturing methods. To make full use of these advantages and to exploit the resulting potential, it is necessary that lattice structures are designed using optimization. Against this backdrop, two mixed integer programs are developed in order to use the methods of mathematical optimization in the context of topology optimization on the basis of a fitted ground structure method. In addition, an algorithm driven product design process is presented to systematically combine the areas of mathematical optimization, computer aided design, finite element analysis and additive manufacturing. Our developed computer aided design tool serves as an interface between state-of-the-art mathematical solvers and computer aided design software and is used for the generation of design data based on optimization results. The first mixed integer program focuses on powder-based additive manufacturing, including a preprocessing that allows a multi-material topology optimization. The second mixed integer program generates support-free lattice structures for additive manufacturing processes usually depending on support structures, by considering geometry-based design rules for inclined and support-free cylinders and assumptions for location and orientation of parts within a build volume. The problem to strengthen a lattice structure by local thickening or beam addition or both, with the objective function to minimize costs, is modeled. In doing so, post-processing is excluded. An optimization of a static area load with a practice-oriented number of connection nodes and beams was manufactured using the powder-based additive manufacturing system EOS INT P760.
Highlights
Additive Manufacturing (AM), originally referred to as rapid prototyping and commonly known as three-dimensional printing, is an additive process for rapid form manufacturing, where the final object is created by adding material in layers; each layer is a thin cross section of the part derived from the original 3D-Computer Aided Design (CAD) data (Burns 1993; Gibson et al 2014)
We focus on the optimization of lattice structures, as they offer some advantageous properties from a design perspective, such as lower weight, better performance and stability due to the large network of structural beams, good energy absorption and high thermal and acoustic insulation compared to its solid counterpart (Gibson and Ashby 1997; Liu et al 2018)
This paper has investigated how to systematically combine mathematical optimization, CAD, Finite Element Analysis (FEA) and AM into an algorithm driven product design process
Summary
Additive Manufacturing (AM), originally referred to as rapid prototyping and commonly known as three-dimensional printing, is an additive process for rapid form manufacturing, where the final object is created by adding material in layers; each layer is a thin cross section of the part derived from the original 3D-Computer Aided Design (CAD) data (Burns 1993; Gibson et al 2014). As stated by Jared et al (2017), AM offers unprecedented opportunities to design complex structures optimized for performance envelops inaccessible under conventional manufacturing constraints, so that a realization of engineered materials with microstructures and properties, that are impossible via traditional synthesis techniques, becomes possible. Enthused by these capabilities, optimization design tools have experienced a recent revival (Jared et al 2017). We focus on the optimization of lattice structures, as they offer some advantageous properties from a design perspective, such as lower weight, better performance and stability due to the large network of structural beams, good energy absorption and high thermal and acoustic insulation compared to its solid counterpart (Gibson and Ashby 1997; Liu et al 2018)
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