Digital twins-based smart manufacturing system design in Industry 4.0: A review

Leng, Jiewu; Wang, Dewen; Shen, Weiming; Li, Xinyu; Liu, Qiang; Chen, Xin

doi:10.1016/j.jmsy.2021.05.011

Cited by 389 publications

(155 citation statements)

References 133 publications

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“…The major barrier that impedes the establishment of the high-fidelity digital twin of UPM is a lack of efficient and systematic multiphysics surface generation modeling methods and the online measurement methods for identifying and distinguishing different vibrations, as well as the lack of appropriate data analytics and the requirements for computation efficiency. Other industrial fields of digital twins research, such as manufacturing system design [5], showed that the digital twin model could organically map and coordinate the function, structure, behavior, control, intelligence, and performance dimension of the system. This kind of mapping and interaction is a potentially missed opportunity for current DT-UPM research.…”

Section: Discussionmentioning

confidence: 99%

“…The design of a UPM starts with the concepting, forming, and fine-tuning of its corresponding digital twin [5]. The concepting stage implies performing a fast multidisciplinary simulation to rapidly validate the conceptual scheme while not pursuing simulation accuracy.…”

Section: Framework For Incorporating Digital Twins Into Upm Design and Controlmentioning

confidence: 99%

“…The design and control of UPM essentially involve the functional, structural, and behavioral aspects. As shown in Figure 3, incorporating digital twins into UPM design and control could be implemented according to Function-Structure-Behavior-Control-Intelligence-Performance (FSBCIP) framework [5]: (1) The function dimension is a formal characterization of the activities and their relationships for machining the workpieces/features; (2) The structure dimension is a formal characterization of the fusion, connection, and assembly relationships of the mechanical modules that fulfill machining functions; (3) The behavior dimension is a formal characterization of the mechanical motion transmissions, the motion form transformations, and mutual relationships (e.g., force, displacement or velocity); (4) The control dimension includes the structural, operational, or calculus of a process by statistical or engineering approaches to regulate the outputted machining process; (5) The intelligence dimension describes, develops, and verifies the learning ability, optimization ability, and autonomy ability of a UPM from the control algorithm viewpoint; and (6) The performance dimension evaluates and optimizes the system performance including accuracy, efficiency, flexibility, reliability, and adaptivity. characterization of the activities and their relationships for machining the workpieces/features; (2) The structure dimension is a formal characterization of the fusion, connection, and assembly relationships of the mechanical modules that fulfill machining functions;…”

Section: Framework For Incorporating Digital Twins Into Upm Design and Controlmentioning

confidence: 99%

“…(3) The behavior dimension is a formal characterization of the mechanical motion transmissions, the motion form transformations, and mutual relationships (e.g., force, displacement or velocity); (4) The control dimension includes the structural, operational, or calculus of a process by statistical or engineering approaches to regulate the outputted machining process; (5) The intelligence dimension describes, develops, and verifies the learning ability, optimization ability, and autonomy ability of a UPM from the control algorithm viewpoint; and (6) The performance dimension evaluates and optimizes the system performance including accuracy, efficiency, flexibility, reliability, and adaptivity. Abstracting and using the above six models in digital twins could benefit the accuracy and efficiency of the design and control of UPM equipment.…”

Section: Framework For Incorporating Digital Twins Into Upm Design and Controlmentioning

confidence: 99%

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Digital Twins-Based Smart Design and Control of Ultra-Precision Machining: A Review

Leng

2021

Symmetry

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Ultra-Precision Machining (UPM) is a kind of highly accurate processing technology developed to satisfy the manufacturing requirements of high-end cutting-edge products including nuclear energy producers, very large-scale integrated circuits, lasers, and aircraft. The information asymmetry phenomenon widely exists in the design and control of ultra-precision machining. It may lead to inconsistency between the designed performance and operational performance of the UPM equipment on stiffness, thermal stability, and motion accuracy, which result from its design, manufacturing, and control, and determine the form accuracy and surface roughness of machined parts. The performance of the UPM equipment should be improved continuously. It is still challenging to realize the real-time and self-adaptive control, in which building a high-fidelity and computationally efficient digital twin is a valuable solution. Nevertheless, the incorporation of the digital twin technology into the UPM design and control remains vague and sometimes contradictory. Based on a literature search in the Google Scholar database, the critical issues in the UPM design and control, and how to use the digital twin technologies to promote it, are reviewed. Firstly, the digital twins-based UPM design, including bearings module design, spindle-drive module design, stage system module design, servo module design, and clamping module design, are reviewed. Secondly, the digital twins-based UPM control studies, including voxel modeling, process planning, process monitoring, vibration control, and quality prediction, are reviewed. The key enabling technologies and research directions of digital twins-based design and control are discussed to deal with the information asymmetry phenomenon in UPM.

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Section: Discussionmentioning

confidence: 99%

Section: Framework For Incorporating Digital Twins Into Upm Design and Controlmentioning

confidence: 99%

Section: Framework For Incorporating Digital Twins Into Upm Design and Controlmentioning

confidence: 99%

Section: Framework For Incorporating Digital Twins Into Upm Design and Controlmentioning

confidence: 99%

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Digital Twins-Based Smart Design and Control of Ultra-Precision Machining: A Review

Leng

2021

Symmetry

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“…We identified the issues, e.g., privacy disclosure and user impersonation, in this area. In the future, potential research can be conducted with the help of advances in Artificial Technologies (AI) [173] and digital twins [174] to address such issues. The advantages of both emerging technologies (i.e., AI and digital twins) in the IIoT are promising, but at the same time, they bring various security concerns related to identity issues.…”

Section: Discussion and Future Research Directionmentioning

confidence: 99%

Analysis of Security Issues and Countermeasures for the Industrial Internet of Things

Pal

Jadidi

2021

Applied Sciences

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Industrial Internet of Things (IIoT) can be seen as an extension of the Internet of Things (IoT) services and applications to industry with the inclusion of Industry 4.0 that provides automation, reliability, and control in production and manufacturing. IIoT has tremendous potential to accelerate industry automation in many areas, including transportation, manufacturing, automobile, marketing, to name a few places. When the benefits of IIoT are visible, the development of large-scale IIoT systems faces various security challenges resulting in many large-scale cyber-attacks, including fraudulent transactions or damage to critical infrastructure. Moreover, a large number of connected devices over the Internet and resource limitations of the devices (e.g., battery, memory, and processing capability) further pose challenges to the system. The IIoT inherits the insecurities of the traditional communication and networking technologies; however, the IIoT requires further effort to customize the available security solutions with more focus on critical industrial control systems. Several proposals discuss the issue of security, privacy, and trust in IIoT systems, but comprehensive literature considering the several aspects (e.g., users, devices, applications, cascading services, or the emergence of resources) of an IIoT system is missing in the present state of the art IIoT research. In other words, the need for considering a vision for securing an IIoT system with broader security analysis and its potential countermeasures is missing in recent times. To address this issue, in this paper, we provide a comparative analysis of the available security issues present in an IIoT system. We identify a list of security issues comprising logical, technological, and architectural points of view and consider the different IIoT security requirements. We also discuss the available IIoT architectures to examine these security concerns in a systematic way. We show how the functioning of different layers of an IIoT architecture is affected by various security issues and report a list of potential countermeasures against them. This study also presents a list of future research directions towards the development of a large-scale, secure, and trustworthy IIoT system. The study helps understand the various security issues by indicating various threats and attacks present in an IIoT system.

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Use of Digital Twin in Predicting the Life of Aircraft Main Bearing

Kumari,

Malhotra

2024

Simulation Techniques of Digital Twin in Real‐Time Applications

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Digital twins-based smart manufacturing system design in Industry 4.0: A review

Cited by 389 publications

References 133 publications

Digital Twins-Based Smart Design and Control of Ultra-Precision Machining: A Review

Digital Twins-Based Smart Design and Control of Ultra-Precision Machining: A Review

Analysis of Security Issues and Countermeasures for the Industrial Internet of Things

Use of Digital Twin in Predicting the Life of Aircraft Main Bearing

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