Anisotropic Strength-Based Topology Optimization for Part Design Using Additive Manufacturing

Abstract

Additive manufacturing (AM), specifically the process of Fused Deposition Modelling (FDM), is a manufacturing procedure where a part is constructed by extruding a melted filament in a layer-by-layer fashion from the bottom up. AM processes offer the ability to manufacture more complex features versus traditional subtractive and formative manufacturing methods. Topology optimization is a structural design tool which is known for generating high-stiffness designs having complex and organic features, making it an ideal tool for using with AM technologies. Traditional topology optimization performs well for stiffness design, but stress considerations are often neglected. A significant shortcoming of FDM is the tendency for tensile material properties in build direction to be significantly weaker than the strengths in the other axes. This work presents a methodology for maximizing the safety factor of structural components for fabrication using FDM AM technology by considering the anisotropy of the material strengths using the Tsai-Wu failure criterion. This is achieved through minimizing an aggregated failure index subject to a volume fraction constraint and is implemented into the framework of density-based topology optimization. Multiple numerical test cases are solved to test the behaviour and robustness of the methodology using fictious material properties. For simple test cases, then methodology does not provide competitive designs compared to the traditional stiffness-based topology optimization formulation; however, test cases which exhibit sharp corners and stress concentrations show significant improvements to the safety factor of the designs when compared to the traditional stiffness-based topology optimization formulation. Real-world material properties of plastic FDM are used to show that for the design of an L-shaped bracket, a common shape used in industrial topology optimization problems, the methodology successfully improves the strength of parts when compared to the equivalent stiffness-based topology optimization result.