Systematic Review of Difference Between Topology Optimization and Generative Design
Jagriti Srivastava, Hiroshi Kawakami
Abstract
This paper aims to study the concept and highlight the methodical difference between the results acquired by design for additive manufacturing methodologies: Topology Optimization (TO) and Generative Design. By meeting particular requirements and reducing a specified cost function, topology optimization (TO) is a mathematical technique that spatially optimizes the distribution of material inside a particular domain which is frequently mistaken for generative design. Software providers claim that generative design is more holistic because it is based on part requirements and restrictions and considers the design, manufacturing process, function, and many other crucial factors. TO as a classical approach has been around for over three decades and due to additive manufacturing, interest in TO is re-established. whereas generative design is an innovative approach that has recently gained acceptance through Computer-Aided Design (CAD) software. The bracket engine problem from General Electric is used as a case study to show how the TO and generative design approaches differ. Examples from earlier literature are taken into account for TO, and Autodesk Fusion 360 (educational license) software is used to produce the outputs for generative design. After carefully examining the entire procedure and the outcomes, a comparison chart is added to highlight the key distinctions between the two approaches.