Reliability-based topology optimization as effective strategy for additive manufacturing: Influence study of geometry uncertainty on resulting layouts

Abstract

Abstract The effectiveness of Additive Manufacturing (AM) is to fabricate very complex configurations that can be resulting layouts from topology optimization. The topology optimization can be classified into two models: Deterministic Topology Optimization (DTO) and Reliability-Based Topology Optimization (RBTO). The DTO may lead to unrealistic designs since it provides a single solution for a given design space. However, the RBTO is considered as a topology generator which provides several layouts. This way the designer can overcome the manufacturing constraint problems such as overhang, minimum feature size, anisotropy …, that may lead to a failure during the production process. Two RBTO strategies based on the Inverse Optimum Safety Factor (IOSF) are presented in this work: Objective-Based IOSF Approach and Performance-Based IOSF Approach. These approaches can be efficiently used as a topology regularization procedure. In addition, to consider the geometry uncertainty, different layouts can be obtained when increasing the reliability index values in order to provide more choices for designers. The geometry uncertainty is applied here in a manner to not affect the boundary conditions which can lead to change the structure’s functioning. The resulting RBTO layouts in this work, are too organic which leads to manufacturability problems. To use the conventional manufacturing procedures, classic CAD primitives must be used to simplify the geometry, that may lead to lose the optimality. Because of this manufacturability difficulty, AM is then obligatory. The RBTO being a good design tool for AM, paves the way to the next developments to overcome other fabrication constraints considering the reliability index values as a topology regulator.