{"title":"Digital twins enable shipbuilding","authors":"","doi":"10.1016/j.aej.2024.09.007","DOIUrl":null,"url":null,"abstract":"<div><p>In the context of Industry 4.0, the most important trend in the shipbuilding industry is to efficiently manufacture intelligent and more environmentally friendly ships. This requires the shipbuilding industry to achieve technological innovations in all aspects of the ship's life cycle and accelerate the digital transformation of the industry. Thanks to the development of new-generation information technology, digital twins have received widespread attention and application in the manufacturing industry. The excellent performance of digital twins in monitoring, diagnosis and decision support also provides strong support for the digital transformation of the manufacturing industry. However, the application and development of digital twin technology are constrained when faced with the complex and discrete manufacturing processes in the shipbuilding industry. To address the constraints in the shipbuilding industry, promote the application of digital twin technology, and support the digital transformation of the shipbuilding industry, a statistical analysis of publications linked to the shipbuilding industry and digital twin using the Web of Science and the Scopus are done in this paper. The application and development of digital twin in the shipbuilding industry was systematically analyzed, the problems restricting the development of digital twin in the shipbuilding industry was summarized. Finally, the development trend of digital twin in shipbuilding industry prospects.</p></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110016824010226/pdfft?md5=90c80a1a8794849a4c485b366e5664bb&pid=1-s2.0-S1110016824010226-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"alexandria engineering journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1110016824010226","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
In the context of Industry 4.0, the most important trend in the shipbuilding industry is to efficiently manufacture intelligent and more environmentally friendly ships. This requires the shipbuilding industry to achieve technological innovations in all aspects of the ship's life cycle and accelerate the digital transformation of the industry. Thanks to the development of new-generation information technology, digital twins have received widespread attention and application in the manufacturing industry. The excellent performance of digital twins in monitoring, diagnosis and decision support also provides strong support for the digital transformation of the manufacturing industry. However, the application and development of digital twin technology are constrained when faced with the complex and discrete manufacturing processes in the shipbuilding industry. To address the constraints in the shipbuilding industry, promote the application of digital twin technology, and support the digital transformation of the shipbuilding industry, a statistical analysis of publications linked to the shipbuilding industry and digital twin using the Web of Science and the Scopus are done in this paper. The application and development of digital twin in the shipbuilding industry was systematically analyzed, the problems restricting the development of digital twin in the shipbuilding industry was summarized. Finally, the development trend of digital twin in shipbuilding industry prospects.
期刊介绍:
Alexandria Engineering Journal is an international journal devoted to publishing high quality papers in the field of engineering and applied science. Alexandria Engineering Journal is cited in the Engineering Information Services (EIS) and the Chemical Abstracts (CA). The papers published in Alexandria Engineering Journal are grouped into five sections, according to the following classification:
• Mechanical, Production, Marine and Textile Engineering
• Electrical Engineering, Computer Science and Nuclear Engineering
• Civil and Architecture Engineering
• Chemical Engineering and Applied Sciences
• Environmental Engineering