Mechanical design is considered a fundamental factor in ensuring the structural integrity and functionality of engineering systems. This research offers a parametric design technique for automating the generation of 3D models of Material Handling Equipment (MHE). By integrating this automated solution into the process, the gap between conceptual design and practical implementation will be bridged. The objective is to streamline the generation process by employing the parametric capabilities of programming-based CAD. A tailored system has been developed to turn natural language user design prompts into precise, modifiable models. The Methodology highlights the deployment of a custom Large Language Model (LLM), trained to generate 3D models with high reusability and scalability, enabling OpenSCAD users of all levels of expertise to have a smooth experience. The work in this research supports the development of cognitive CAD tools, especially where flexibility and customization are vital. The model implemented has been tested on a range of common MHE parts, successfully generating accurate and fully parametric OpenSCAD models. The results demonstrate the model’s ability to understand various prompts and produce modifiable outputs suitable for rapid prototyping and design analysis.
ELhadad et al. (Thu,) studied this question.