한국컴퓨터정보학회논문지 (Journal of the Korea Society of Computer and Information)

  • 제29권11호
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  • Pages.353-369
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  • 2024
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  • 1598-849X(pISSN)
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  • 2383-9945(eISSN)
한국컴퓨터정보학회 (Korean Society of Computer Information)
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Establishment of backcasting-based strategic approach and resilience-based AI governance for the transformation of artificial intelligence in Korean shipbuilding industry

  • Changhee Lee (Div. of Navigation Convergence Studies, Korea Maritime and Ocean University) ;
  • Sangseop Lim (Div. of Navigation Convergence Studies, Korea Maritime and Ocean University)
  • 투고 : 2024.10.21
  • 심사 : 2024.11.18
  • 발행 : 2024.11.29
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초록

본 연구는 국내 조선산업이 디지털 전환을 넘어 인공지능(AI) 기반의 전환(AX) 시대를 맞이함에 따라, AI를 활용한 생산성 향상과 글로벌 경쟁력 강화 방안을 제시한다. 과거 노동 집약적인 산업이었던 조선업은 자동화와 디지털화를 거쳐 현재 AI 기반의 스마트 조선소로 진화하고 있으며, 친환경 규제와 친환경 연료의 중요성이 증가하고 있다. 특히, 암모니아, 액화수소 등와 같은 대체 연료의 도입이 시급한 상황이다. 그러나 글로벌 경쟁 심화와 기술 변화 속에서 새로운 도전에 직면하고 있다. 본 연구는 국내외 조선기업의 AI 전환 및 친환경 연료 채택 사례를 분석하고, AI 거버넌스를 구축하여 리스크를 관리하고 지속 가능한 성장을 위한 방안을 제시하였다. 특히, 백캐스팅 기법을 활용하여 친환경 규제를 준수하면서 단기, 중기, 장기 목표를 설정하고, 단계별 전략을 도출하여 국내 조선산업의 AI 전환을 위한 정책 수립 및 기업 전략 수립에 중요한 시사점과 의의가 있다.

This paper presents strategies for enhancing productivity and strengthening global competitiveness as the domestic shipbuilding industry transitions into the era of Artificial Intelligence Transformation (AX), moving beyond digital transformation. Historically a labor-intensive industry, shipbuilding has evolved into smart shipyards powered by automation and digitalization, with increasing emphasis on green regulations and the importance of green fuels. The urgent adoption of alternative fuels, such as ammonia and liquid hydrogen, is critical in this context. However, the industry faces new challenges amid intensifying global competition and rapid technological changes. This study analyzes both domestic and international cases of AI transformation and the adoption of eco-friendly fuels in shipbuilding companies, proposing ways to manage risks through the establishment of AI governance to ensure sustainable growth. In particular, by utilizing the backcasting method, the study sets short-term, mid-term, and long-term goals while deriving phased strategies to provide significant insights and implications for policy formulation and corporate strategies aimed at the AI transformation of the domestic shipbuilding industry while complying with environmental regulations.

키워드

과제정보

This research was supported by Korea Institute of Marine Science and Technology Promotion (KIMST) funded by the Ministry of Oceans and Fisheries, grant number RS-2023-00236321. This research was supported by the Ministry of SMEs and Startups(MSS), Korea Institute for Advancement of Technology(KIAT) through the Innovation Development(R&D) for Global Regulation-Free Special Zone

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