Fusheng Qiu, Ming Chen, Liang Wang, Yu Ying, Tang Tang
{"title":"The architecture evolution of intelligent factory logistics digital twin from planning, implement to operation","authors":"Fusheng Qiu, Ming Chen, Liang Wang, Yu Ying, Tang Tang","doi":"10.1177/16878132231198339","DOIUrl":null,"url":null,"abstract":"Digital twin is widely studied in the context of industry 4.0. It is expected that the application of digital twin in intelligent factory logistics can enrich connectivity, proactivity, and agility of the logistics. Architecture is one of the significant factors impacting on the selection of appropriate enabling technologies for constructing the intelligent logistics. This paper proposes a digital twin architecture for intelligent factory logistics. It mainly includes a physical layer, two cyber layers, and an interface layer. The architecture is in compliance with the architecture of the Human-Cyber-Physical System (HCPS). Moreover, the evolution of the architecture is elaborated during the planning, implement, and operation stages when construction of the digital twin. At the initial stage, human should participate in the decision-making process frequently to determine whether the results given by digital twin need to be changed. However, the data-driven model based digital twin will continually learn the human’s changing behaviors, thus constantly updating itself. It can evolution from digital model, digital shadow to digital twin with the continuous construction process. The ultimate digital twin should be able to assess operational key performance indicators (KPIs) and handle dynamic events.","PeriodicalId":49110,"journal":{"name":"Advances in Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Mechanical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/16878132231198339","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Digital twin is widely studied in the context of industry 4.0. It is expected that the application of digital twin in intelligent factory logistics can enrich connectivity, proactivity, and agility of the logistics. Architecture is one of the significant factors impacting on the selection of appropriate enabling technologies for constructing the intelligent logistics. This paper proposes a digital twin architecture for intelligent factory logistics. It mainly includes a physical layer, two cyber layers, and an interface layer. The architecture is in compliance with the architecture of the Human-Cyber-Physical System (HCPS). Moreover, the evolution of the architecture is elaborated during the planning, implement, and operation stages when construction of the digital twin. At the initial stage, human should participate in the decision-making process frequently to determine whether the results given by digital twin need to be changed. However, the data-driven model based digital twin will continually learn the human’s changing behaviors, thus constantly updating itself. It can evolution from digital model, digital shadow to digital twin with the continuous construction process. The ultimate digital twin should be able to assess operational key performance indicators (KPIs) and handle dynamic events.
期刊介绍:
Advances in Mechanical Engineering (AIME) is a JCR Ranked, peer-reviewed, open access journal which publishes a wide range of original research and review articles. The journal Editorial Board welcomes manuscripts in both fundamental and applied research areas, and encourages submissions which contribute novel and innovative insights to the field of mechanical engineering