This paper reviews the recent development of Digital Twin technologies in manufacturing systems and processes, to analyze the connotation, application scenarios, and research issues of Digital Twin-driven smart manufacturing in the context of Industry 4.0. To understand Digital Twin and its future potential in manufacturing, we summarized the definition and state-of-theart development outcomes of Digital Twin. Existing technologies for developing a Digital Twin for smart manufacturing are reviewed under a Digital Twin reference model to systematize the development methodology for Digital Twin. Representative applications are reviewed with a focus on the alignment with the proposed reference model. Outstanding research issues of developing Digital Twins for smart manufacturing are identified at the end of the paper.
There is a recognized need for mass personalization for sustainability at scale. Mass personalization is becoming a leading research trend in the latest Industrial Revolution, whereas substantial research has been undertaken on the role of Industry 4.0 enabling technologies. The world is moving beyond mass customization, while manufacturing has led to mass personalization ahead of other industries. However, most studies have not treated human capabilities, machines, and technologies as sustainable collaboration. This research investigates mass personalization as a common goal under the latest Industrial revolutions. Also, it proposes a Reference Architecture Model for achieving mass personalization that contributes to understanding how Industry 5.0 enhances Industry 4.0 for higher resilience and sustainability through a human-centric approach. The study implies that Human Capital 5.0 leads collaboration with machines and technologies, bringing more value-added and sustainable products.
Manufacturing is becoming smart with capabilities of self-awareness, autonomous decision-making, and adaptive excitation and collaboration. Standardization is a crucial enabler for achieving the required intelligence for smart manufacturing. Though a large number of efforts have been made to the development of manufacturing standards, there is still a significant research gap to be fulfilled. This paper reviews the landscape of existing standards in the context of smart manufacturing and offers guidance on the selection of the standards for different smart manufacturing applications.
Digital Twin is one of the key enabling technologies for smart manufacturing in the context of Industry 4.0. The combination with advanced data analytics and information and communication technologies allows Digital Twins to perform real-time simulation, optimization and prediction to their physical counterparts. Efficient bi-directional data exchange is the foundation for Digital Twin implementation. However, the widely mentioned cloud-based architecture has disadvantages, such as high pressure on bandwidth and long latency time, which limit Digital Twins to provide real-time operating responses in dynamic manufacturing processes. Edge computing has the characteristics of low connectivity, the capability of immediate analysis and access to temporal data for real-time analytics, which makes it a fit-for-purpose technology for Digital Twin development. In this paper, the benefits of edge computing to Digital Twin are first explained through the reviews of the two technologies. The Digital Twin functions to be performed at the edge are then elaborated. After that, how the data model will be used in the edge for data mapping to realize the Digital Twin is illustrated and the data mapping strategy based on the EXPRESS schemas is discussed. Finally, a case study is carried out to verify the data mapping strategy based on EXPRESS schema. This research work refers to ISO/DIS 23247 Automation systems and integration — Digital Twin framework for manufacturing.
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