停工期
工作流程
虚拟表示法
计算机科学
制造工程
资产(计算机安全)
工业4.0
工厂(面向对象编程)
产品(数学)
供应链
过程(计算)
系统工程
工程类
可靠性工程
嵌入式系统
数据库
几何学
操作系统
计算机安全
数学
程序设计语言
法学
政治学
作者
Mohsen Soori,Behrooz Arezoo,Roza Dastres
出处
期刊:Sustainable manufacturing and service economics
[Elsevier]
日期:2023-04-01
卷期号:2: 100017-100017
被引量:73
标识
DOI:10.1016/j.smse.2023.100017
摘要
A virtual representation of a physical procedure or product is called digital twin which can enhance efficiency and reduce costs in manufacturing process. Utilizing the digital twin, production teams can examine various data sources and reduce the number of defective items to enhance production efficiency and decrease industrial downtime. Digital Twin can be utilized to visualize the asset, track changes, understand and optimize asset performance throughout the analysis of the product lifecycle. Also, the collected data from digital twin can provide the complete lifecycle of products and processes to optimize workflows of part production, manage supply chain, and manage product quality. The application of digital twin in smart manufacturing can reduce time to market by designing and evaluating the manufacturing processes in virtual environments before manufacture. Comprehensive simulation platforms can be presented using digital twins to simulate and evaluate product performances in terms of analysis and modification of produced parts. Commissioning time of a factory can also be significantly reduced by developing and optimizing the factory layout using the digital twin. Also, the productivity of part manufacturing can be enhanced by providing the predictive maintenance and data-driven root-cause analysis during part production process. In this paper, application of digital twin in smart manufacturing systems is reviewed to analyze and discuss the advantages and challenges of part production modification using the digital twin. So, the research field can advance by reading and evaluating previous papers in order to propose fresh concepts and approaches by using digital twins in smart manufacturing systems.
科研通智能强力驱动
Strongly Powered by AbleSci AI