复制品
工业4.0
生产力
计算机科学
制造工程
工程类
经济
数据挖掘
宏观经济学
艺术
视觉艺术
作者
Maulshree Singh,Rupal Srivastava,Evert Fuenmayor,Vladimir Kuts,Yuansong Qiao,Niall Murray,Declan M. Devine
出处
期刊:Applied sciences
[Multidisciplinary Digital Publishing Institute]
日期:2022-06-04
卷期号:12 (11): 5727-5727
被引量:323
摘要
One of the most promising technologies that is driving digitalization in several industries is Digital Twin (DT). DT refers to the digital replica or model of any physical object (physical twin). What differentiates DT from simulation and other digital or CAD models is the automatic bidirectional exchange of data between digital and physical twins in real-time. The benefits of implementing DT in any sector include reduced operational costs and time, increased productivity, better decision making, improved predictive/preventive maintenance, etc. As a result, its implementation is expected to grow exponentially in the coming decades as, with the advent of Industry 4.0, products and systems have become more intelligent, relaying on collection and storing incremental amounts of data. Connecting that data effectively to DTs can open up many new opportunities and this paper explores different industrial sectors where the implementation of DT is taking advantage of these opportunities and how these opportunities are taking the industry forward. The paper covers the applications of DT in 13 different industries including the manufacturing, agriculture, education, construction, medicine, and retail, along with the industrial use case in these industries.
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