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

Korean Society of Computer Information (한국컴퓨터정보학회)
권호 표지
DOI QR코드

DOI QR Code

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)
  • Received : 2024.10.21
  • Accepted : 2024.11.18
  • Published : 2024.11.29
Download PDF
⟨ Previous Next ⟩

Abstract

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.

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.

Keywords

Acknowledgement

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

References

  1. Khandakar Akhter Hossain, Analysis of Present and Furue Use of Artificial Intelligence(AI) in line of Fourth Industrical Revolution(4IR), Scientific Research Journal), Vo.11, No.8, pp.1-50, 2023. DOI: 10.31364/SCIRJ/v11.i8.2023.P0823954 
  2. Peter C. Verhoef, Thijs Broekhuizen, Yakov Bart, Abhi Bhattacharya, John Qi Dong, Nicolai Fabian, Michael Haenlein, Digital transformation: A multidisciplinary reflection and research agenda, Journal of Business Research, Vol.122, pp.889-901, 2021. https://doi.org/10.1016/j.jbusres.2019.09.022. 
  3. Jinfeng Liu, Yiming Zhang, Zhuoyao Liu, Jiewu Leng, Honggen Zhou, Shimin Gu, Xiaojun Liu, Digital twins enable shipbuilding, Alexandria Engineering Journal, Vol. 107, pp. 915-931, 2024, https://doi.org/10.1016/j.aej.2024.09.007. 
  4. Joo Hwan Kim, A Study of World Championship of Korean Shipbuilding Industry: With a Focus on Developmental Strategy Responding to Product Cycle, Journal of Korean Political Science Society, Vol.16, No.1, pp.251-276, 2008. 
  5. Bae Suk Man, The Korean Shipbuilding Industry in the 1960s~70s: Dramatic Conversion to an Industry specialized in Exportation, Critical Review of History, Vol.122, pp.71-105, 2018. doi: 10.38080/crh.2018.02.122.71 
  6. http://metalunion.re.kr/bbs/board.php?bo_table=B04&wr_id=188&sst=wr_hit&sod=desc&sop=and&page=11(Access date: 2024.10.05) 
  7. https://www.clunix.com/insight/it_trends.php?boardid=ittrend&mode=view&idx=804(Access date:2024.10.01.) 
  8. Zimmerman MA. Resiliency theory: a strengths-based approach to research and practice for adolescent health. Health Educ Behav. 2013 Aug;40(4):381-3. doi: 10.1177/1090198113493782. PMID: 23863911; PMCID: PMC3966565. 
  9. Piera Centobelli, Roberto Cerchione, Amedeo Maglietta, Eugenio Oropallo, Sailing through a digital and resilient shipbuilding supply chain: An empirical investigation, Journal of Business Research, Vol.158, 2023. https://doi.org/10.1016/j.jbusres.2023.113686. 
  10. Sara Scipioni, Gianluca Dini, Federico Niccolini, Exploring circular shipbuilding: A systematic review on circular economy business models and supporting technologies, Journal of Cleaner Production, Vol.422, 2023. https://doi.org/10.1016/j.jclepro.2023.138470. 
  11. Wesley J. Johnston, Roberto Mora Cortez, Business-to-business digitalization, artificial intelligence, and social action, Journal of Business Research, Vol.172, 2024. https://doi.org/10.1016/j.jbusres.2023.113952. 
  12. Sibyl Hanna Brunner, Robert Huber, Adrienne Gret-Regamey, A backcasting approach for matching regional ecosystem services supply and demand, Environmental Modelling & Software, Vol.75, pp.439-458, 2016. https://doi.org/10.1016/j.envsoft.2015.10.018. 
  13. https://esg.hd.com/ko/news/743https://esg.hd.com/ko/news/743 (Access date: 2024.10.01.) 
  14. https://cwn.kr/article/1065577195280335 (Access date: 2024.10.01.) 
  15. https://www.shinailbo.co.kr/news/articleView.html?idxno=1917216 (Access date: 2024.10.08.) 
  16. https://www.fincantieri.com/en/media/press-releases/2024/fincantieri-and-accenture-join-forces-to-lead-digital-industrial-innovation-for-ports-and-vessels/(Access date: 2024.10.08.) 
  17. https://www.imarinenews.com/7998.html/(Access date: 2024.10.08.) 
  18. Haseeb, M.; Hussain, H.I.; Slusarczyk, B.; Jermsittiparsert, K. Industry 4.0: A Solution towards Technology Challenges of Sustainable Business Performance. Soc. Sci. Vol.154, No.8, 2019. https://doi.org/10.3390/socsci8050154 
  19. Soo Kee Tan, RACE IN THE SHIPBUILDING INDUSTRY: CASES OF SOUTH KOREA, JAPAN AND CHINA, International Journal of East Asian Studies Vol. 6, No.1, pp.65-81, 2017.  https://doi.org/10.22452/IJEAS.vol6no1.5
  20. Dongkeun Lee, Influences behind the development of South Korea's shipbuilding industry from the 1960s to the 2000s, Marine Policy, Vol.167, 2024. https://doi.org/10.1016/j.marpol.2024.106251. 
  21. Yongjun Xu, Xin Liu, Xin Cao, Changping Huang, Enke Liu, Sen Qian, Xingchen Liu, Yanjun Wu, Fengliang Dong, Cheng-Wei Qiu, Junjun Qiu, Keqin Hua, Wentao Su, Jian Wu, Huiyu Xu, Yong Han, Chenguang Fu, Zhigang Yin, Miao Liu, Ronald Roepman, Sabine Dietmann, Marko Virta, Fredrick Kengara, Ze Zhang, Lifu Zhang, Taolan Zhao, Ji Dai, Jialiang Yang, Liang Lan, Ming Luo, Zhaofeng Liu, Tao An, Bin Zhang, Xiao He, Shan Cong, Xiaohong Liu, Wei Zhang, James P. Lewis, James M. Tiedje, Qi Wang, Zhulin An, Fei Wang, Libo Zhang, Tao Huang, Chuan Lu, Zhipeng Cai, Fang Wang, Jiabao Zhang, Artificial intelligence: A powerful paradigm for scientific research, The Innovation, Vol.2, No.4, 2021. https://doi.org/10.1016/j.xinn.2021.100179. 
  22. Jinfeng Liu, Yiming Zhang, Zhuoyao Liu, Jiewu Leng, Honggen Zhou, Shimin Gu, Xiaojun Liu, Digital twins enable shipbuilding, Alexandria Engineering Journal, Vol. 107, pp.915-931, 2024. https://doi.org/10.1016/j.aej.2024.09.007. 
  23. https://www.korea.kr/briefing/pressReleaseView.do?newsId=156639069&pWise=mSub&pWiseSub=C5#pressRelease(Access date: 2024.10.08.) 
  24. Shafiabady N, Hadjinicolaou N, Hettikankanamage N, Mohammadi Savadkoohi E, Wu RMX, Vakilian J. eXplainable Artificial Intelligence (XAI) for improving organisational regility. PLoS One. Vol.24. No.19, 2024. doi: 10.1371/journal.pone.0301429. 
  25. Davy Tsz Kit Ng, Jac Ka Lok Leung, Samuel Kai Wah Chu, Maggie Shen Qiao, Conceptualizing AI literacy: An exploratory review, Computers and Education: Artificial Intelligence, Vol.2, 2021. https://doi.org/10.1016/j.caeai.2021.100041. 
  26. Bernd W. Wirtz, Jan C. Weyerer, Ines Kehl, Governance of artificial intelligence: A risk and guideline-based integrative framework, Government Information Quarterly, Vol.39, No.4, 2022. https://doi.org/10.1016/j.giq.2022.101685. 
  27. Adib Bin Rashid, MD Ashfakul Karim Kausik, AI revolutionizing industries worldwide: A comprehensive overview of its diverse applications, Hybrid Advances, Vol.7, 2024. https://doi.org/10.1016/j.hybadv.2024.100277. 
  28. Kenneth Nordberg, Age Mariussen, Seija Virkkala, Community-driven social innovation and quadruple helix coordination in rural development. Case study on LEADER group Aktion Osterbotten, Journal of Rural Studies, Vol.79, pp.157-168, 2020. https://doi.org/10.1016/j.jrurstud.2020.08.001. 
  29. Priyanka Gupta, Bosheng Ding, Chong Guan, Ding Ding, Generative AI: A systematic review using topic modelling techniques, Data and Information Management, Vol.8, No.2, 2024. https://doi.org/10.1016/j.dim.2024.100066. 
  30. Aizhan Tursunbayeva, Hila Chalutz-Ben Gal, Adoption of artificial intelligence: A TOP framework-based checklist for digital leaders, Business Horizons, Vol.67, No.4, pp.357-368, 2024. https://doi.org/10.1016/j.bushor.2024.04.006. 
  31. Nastasa A, Dumitra TC, Grigorescu A. Artificial intelligence and sustainable development during the pandemic: An overview of the scientific debates. Heliyon. Vol.16, No.10, 2024. doi: 10.1016/j.heliyon.2024.e30412. 
  32. Riyadh, M., Transforming the Shipping Industry with Autonomous Ships and Artificial Intelligence. Maritime Park: Journal of Maritime Technology and Society, Vol.3, No.2, pp.81-86, 2024. https://doi.org/10.62012/mp.v3i2.35386 
  33. Elahi, M., Afolaranmi, S.O., Martinez Lastra, J.L. et al. A comprehensive literature review of the applications of AI techniques through the lifecycle of industrial equipment. Discov Artif Intell, Vol..43, No.3, 2023. https://doi.org/10.1007/s44163-023-00089-x 
  34. Xieling Chen, Haoran Xie, Di Zou, Gwo-Jen Hwang, Application and theory gaps during the rise of Artificial Intelligence in Education, Computers and Education: Artificial Intelligence, Vol.1, 2020. https://doi.org/10.1016/j.caeai.2020.100002. 
  35. Lahusen, C., Maggetti, M. & Slavkovik, M. Trust, trustworthiness and AI governance. Sci Rep, Vol.14, 2024. https://doi.org/10.1038/s41598-024-71761-0