Geometric design best practices of wire arc additive manufacturing for an expert system
Year: 2025
Type: article
Abstract: Significant research using Wire arc Directed Energy Deposition (DED) has been conducted within the last decade. A common issue researchers encounter are the unknown geometric limitations that are present in a design that can have significant negative impacts on DED builds. This research focused on developing an expert system and cost model to optimize the process of identifying geometric risk factors that would negatively affect a particular design. The expert system, implemented in Python, leverages build rules to provide users with recommended machine and design parameters, enhancing part quality and manufacturability. Validation testing, conducted using six geometries from prior research efforts, confirmed that the system's outputs are both accurate and reproducible. These advancements not only underscore the technical and economic benefits of wire arc DED but also pave the way for its broader application in industry, driving improvements in efficiency, cost-effectiveness, and design flexibility.
Authors: Emily S. Wall, Gehendra Sharma, Walker Jarrell, Joel Austin, Elton Freeman, Sarah Miele
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,520
Award: G245949513
OpenAlex ID: W4413426371
