Development of a CAD–FEA Integrated Automation Add-In for DfAM-Aware Topology Optimization: A Case Study on an Additively Manufactured Pusher Duct Support Bracket for a Novel UAV Prototype
Source abstract
Abstract
The integration of additive manufacturing (AM) and topology optimization (TO) is transforming mechanical design and prototyping practices across multiple engineering sectors, including agricultural and aerospace applications. This study presents the development of TODfAM, a bespoke SOLIDWORKS add-in that automates TO workflows and embeds Design for Additive Manufacturing (DfAM) principles directly within a parametric CAD environment. The tool integrates parametric modelling, finite element analysis (FEA)-based structural evaluation, and TO in a unified platform, enabling automated generation and assessment of design iterations with respect to both mechanical performance and AM-specific manufacturability constraints. A case study on a pusher-duct support bracket for an Unmanned Aerial Vehicle (UAV) was conducted to demonstrate the functionality of the developed workflow. The optimized bracket achieved a 13.77% mass reduction while maintaining structural integrity under representative loading conditions. The CAD-integrated framework reduces toolchain hand-offs and allows early manufacturability evaluation within the design environment, thereby improving workflow continuity and consistency. The principal novelty of this work lies in the establishment of a fully CAD-native, DfAM-aware optimization framework that consolidates the design-to-manufacturing process into a single automated environment. This approach not only streamlines pre- and post-processing tasks but also promotes wider industrial adoption of AM by providing a practical, designer-oriented route to lightweight and manufacturable structures.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Topology Optimization in Engineering · Additive Manufacturing and 3D Printing Technologies · Additive Manufacturing Materials and Processes
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Agricultural Machinery and Technology Engineering, Akdeniz University, Antalya 07070, Turkey
School of Engineering, The University of Southampton, Southampton SO16 7QF, UK
Elixtek Engineering Software Solutions, Kocaeli 41030, Turkey
School of Engineering, Lancaster University, Lancaster LA1 4YW, UK
Funding
Scientific Research Projects Coordination Unit of Akdeniz University · Scientific and Technological Research Council of Turkey
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