POSTER WORKSHOP

Advancing 3D CAD with Workflow Graph-Driven Bayesian Command Inferences

Yugyeong Jang, Kyung Hoon Hyun

ACM CHI 2024 LBW

Advancements in 3D generative AI have significantly improved design capabilities, particularly for creating 3D objects and environments. However, the focus of Generative AI on mesh-based models limits opportunities for detailed modifications. Accurate and complex 3D modeling is crucial for manufacturing, which requires high precision and considerable mental effort. This complexity often leads to variability in efficiency among designers, with some employing faster and more accurate techniques and others using less efficient workflows. This variation undergoes the need to optimize modeling sequences. By inferring a user's intended designs, tailored commands and sequences can be suggested to enhance the precision of 3D modeling. Addressing this, we propose a system that predicts user modeling steps using an inference model based on behavior, thereby promoting efficient workflow and precise command usage. User studies demonstrate that our system minimizes modeling errors, streamlines processes, and offers recommendations for effective command usage.

Toward AI-driven Multimodal Interfaces for Industrial CAD Modeling

Jiin Choi, Yugyeong Jang, Kyung Hoon Hyun

ACM CHI 2025 Workshop on Bridging HCI

and Industrial Manufacturing

paper

AI-driven multimodal interfaces have the potential to revolutionize industrial 3D CAD modeling by improving workflow efficiency and user experience. However, the integration of these technologies remains challenging due to software constraints, user adoption barriers, and limitations in AI model adaptability. This paper explores the role of multimodal AI in CAD environments, examining its current applications, key challenges, and future research directions. We analyze Bayesian workflow inference, multimodal input strategies, and collaborative AI-driven interfaces to identify areas where AI can enhance CAD design processes while addressing usability concerns in industrial manufacturing settings.