A Comprehensive Review on Generative and Parametric Approaches in Cloud – Based CAD/CAM Platforms for 3D Printing Applications
Tanmay Bhadale, Yash Deshpande, Jueli Patil, Ć. IvanGRGI, V. Tiwary
TL;DR: This study provides a thorough examination of parametric and generative design processes for 3D printing applications, evaluating their techniques, industrial uses, benefits, problems and future potential.
: The integration of parametric and generative design approaches into cloud-based computer-aided design (CAD) and computer-aided manufacturing (CAM) platforms is transforming contemporary product development, especially in 3D printing applications. Parametric design prioritizes constraint-driven, feature-based modelling that embodies designer intent, facilitating editable, reusable, and changeable CAD models. Advanced datasets like WHUCAD, which include attributes such as fillets, chamfers, grooves, and shells, enhance deep learning and replication of human-computer interaction for 3D form development. Prominent parametric cloud systems, like Onshape, Autodesk Fusion 360, Siemens NX, and PTC Creo+, utilize server-side kernels and APIs to provide real-time collaboration and feature mapping. In contrast, generative design utilizes artificial intelligence and algorithmic methods - such as topology optimization, implicit modelling, and large language model (LLM)-assisted script generation - to independently investigate extensive design spaces and enhance products for performance, weight, and manufacturability. Innovative pipelines like ZOO text-to-CAD and GPT-enhanced FreeCAD scripting exemplify this approach. Parametric processes thrive in customization and precise assembly control, whereas generative approaches facilitate structural optimization and innovation from exploration, especially when combined with additive manufacturing. Future hybrid design methodologies seek to integrate parametric accuracy with generative creativity; however, obstacles persist in geometric fidelity, computing requirements and manufacturability verification. This study provides a thorough examination of parametric and generative design processes for 3D printing applications, evaluating their techniques, industrial uses, benefits, problems and future potential.