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A Review of the Design and Implementation of Digital Twins for Smart Manufacturing

智能制造 工业4.0 互操作性 制造业 制造工程 数字化转型 离散制造 先进制造业 信息物理系统 计算机科学 服务(商务) 生产(经济) 工程类 业务 万维网 嵌入式系统 营销 经济 宏观经济学 操作系统
作者
Shafahat Ali,S. Abdallah,Salman Pervaiz
标识
DOI:10.1115/imece2022-97113
摘要

Abstract The current massive use of machine learning and the 5G networks have supported the high demand for the digital twin and made it more popular and common in the industrial sector and scientific research related to smart manufacturing. As part of this research study, the currently available opportunities for smart manufacturing using digital twins have been reviewed and discussed in the industry 4.0 field. While digital twins have garnered much attention in the industrial internet of things, their use in smart manufacturing has been much less common. This discussion here focuses on the open challenges in smart manufacturing and industry 4.0 and suggests that in some cases. Digital twins should be treated differently to enhance industrial processes and smart manufacturing applications. On the other hand, this research examines the impact of digital twins on smart manufacturing and sustainable production rates, aiming to promote the industry’s digital transformation to meet the required production rate. The research discussed the digital twin concept and its origins and perspectives from academia and industrial sectors. It reveals its potential for the digitalization of manufacturing. Also, the review discussed how the digital twins could support the integrated, flexible, and collaborative manufacturing environments associated with the fourth industrial revolution. Different industrial operational technologies and communication technologies have profoundly changed smart manufacturing. Intelligent and automated information exchange, automated machine control, and interoperable production systems have all been enabled by Industry 4.0. System-level CPS and digital twins can collaborate through Smart Service Platforms for Digital Twins. In addition to optimizing production configurations, the digital twin is used to determine the impact of decisions made during modifications or upgrades. By analyzing the predictive maintenance of manufacturing lines, the time between production delays will be reduced. A specific alarm or notification will be sent to the user to enable them to take quick action. A digital twin application analyzes and simulates data by controlling, monitoring, and optimizing variables based on various factors in both online and offline modes. This study seeks to evaluate the evolution of digital twin concepts and their relevance to smart manufacturing. It summarized and explained the current state of digital twins in manufacturing literature, highlighting future directions for studies and the highest potential for future applications.
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