UNIST Launches Major AI Initiative to Transform Shipbuilding Industry
Led by UNIST, the consortium includes HD Hyundai Heavy Industries, HD Korea Shipbuilding & Offshore Engineering, and CrowdWorks.
UNIST has launched a major interdisciplinary research initiative to accelerate AI-driven transformation (AX) across the shipbuilding sector. Selected under the Ministry of Science and ICT’s national initiative for large-scale industrial AI, the project is supported by a total budget of KRW 40.3 billion (approximately USD 30 million). It aims to develop domain-specific AI foundation models trained on real-world shipyard data and deploy them in operational environments. The initiative brings together faculty from the Graduate School of Artificial Intelligence (AIGS), along with multiple engineering and business disciplines, forming a collaborative structure that spans the full lifecycle of industrial AI—from data generation and model training to system deployment and real-world validation. At the core of the project is the development of a multimodal, domain-specific foundation model for shipbuilding. This effort is led by Professor Sung Youb Kim from the Graduate School of Semiconductor Materials and Devices Engineering, with participation from Professors Seung-Hoon Na, Youngsoo Jang, Seungryul Baek, and Taehwan Kim from AIGS, along with Professor Hayoung Chung from the Department of Mechanical Engineering. The team will develop a model capable of integrating diverse data generated across shipyard operations, serving as a central engine for a wide range of downstream applications. Complementing this effort, a parallel workstream led by Professors Sung Whan Yoon, Jae-Young Sim, and Yeon-Chang Lee from AIGS, along with Professor Saerom Park (Department of Industrial Engineering) and Professor Seongil Wi (Department of Computer Science and Engineering) will establish a scalable industrial platforms for optimized for heterogeneous datasets. In parallel, Professors Seungjoon Yang, Gi-soo Kim, and Yeon-Chang Lee from AIGS will lead research on synthetic data generation, addressing limitations in real-world data and improving model robustness across diverse scenarios. Application-focused research will be led by Professors Youngdae Kim, Sungil Kim, Hyungho Na, Dong Young Lim, and Chiehyeon Lim from the Department of Industrial Engineering, along with Professor Junghoon Kim (Department of Computer Science and Engineering), Professor Jinyoung Choi (AIGS), and Professor Junhyoung Ha (Department of Mechanical Engineering). Their work will focus on manufacturing optimization, production scheduling, predictive maintenance, and the intelligent operation of collaborative robotic systems. The development of lightweight, on-device AI technologies will be led by Professors Taesik Gong (Department of Computer Science and Engineering), Jongeun Lee (Department of Electrical Engineering), and Ranggi Hwang (Department of Computer Science and Engineering). Meanwhile, Professors Byeong Ki Seo (School of Business Administration) and Namhun Kim (Department of Mechanical Engineering) will oversee field validation and service deployment to ensure practical application and scalability. To ensure real-world impact, the initiative will be carried out in close collaboration with industry partners, including HD Hyundai Heavy Industries, HD Korea Shipbuilding & Offshore Engineering, and CrowdWorks. By leveraging operational data from active shipyards, the consortium will validate and refine technologies through on-site implementation. Professor Seung-Hoon Na, who coordinates the overall project, stated, “This initiative goes beyond developing AI models—it establishes a foundation for industrial AX. By integrating AI into production planning, process optimization, and quality control, we expect to drive meaningful innovation across the shipbuilding industry.” The UNIST Office of Research Affairs supported the initiative through its Pre-Award pilot program, providing strategic and administrative assistance in proposal development, budgeting, and coordination. The university plans to further advance its research management framework to support large-scale, high-impact initiatives.
- 2026-04-13
- JooHyeon Heo
- 290