Asymmetric and Symmetric Study on Digital Twins and Cyber-Physical-Social Systems

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 20654

Special Issue Editors


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Guest Editor
School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, China
Interests: intelligent product design; intelligent product manufacturing; multi-objective optimization; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing, China
Interests: social manufacturing; industrial internet; cyber physical social system
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou 510006, China
Interests: intelligent manufacture

Special Issue Information

Dear Colleagues,

Symmetry is one of the most important notions in the digital twins [1] and cyber-physical-social systems[2]. Digital twin technologies leverage the new generation of information technologies, industrial Internet technologies, and artificial intelligence technologies to facilitate perceiving, learning, reasoning, and decision making in complex systems. The ultimate goal of digital twins is to drive systems smarter and more efficient. While digital twin technologies have shown promising benefits, there are still challenges in their implementations, for example, the development of computationally efficient algorithms for real-time response, the security of digital twins [3,4], and how to build symmetric digital twins in a distributed environment. It is urgent to comprehend the asymmetric and symmetric phenomenon on digital twins and cyber-physical-social systems and thereby make breakthroughs and innovations in the digital twins-based methods, technologies, and platforms for the design, (re)configuration, and optimization of a system.

The purposes of this Special Issue are to present asymmetric and symmetric study on digital twins and cyber-physical-social systems, to demonstrate the benefits, and to anticipate the potential challenges. We invite submissions that present original and high-quality research work on digital twins and cyber-physical-social systems. We consider submissions that introduce new research problems and concepts, develop novel and rigorous methodologies to tackle the problems, and present innovative applications. Successful real-world implementations are strongly encouraged.

The scope of this Special Issue covers all topics related to digital twins and cyber-physical-social systems, including but not limited to:

  • Asymmetries and symmetries in digital twins;
  • Asymmetries and symmetries in cyber-physical-social systems;
  • Social computing and social manufacturing;
  • Parallel control and parallel society;
  • Artificial intelligence in the digital twins;
  • Innovative theory and model based on digital twins;
  • Synchronization of the physical system and virtual model;
  • Hardware-in-the-loop (semiphysical) simulation;
  • Computationally efficient algorithms for online decisions;
  • Blockchain-secured digital twins and cyber-physical-social systems;
  • Case study on digital twins and cyber-physical-social systems;
  • Performance evaluation of digital twins;
  • Digital twins in industry;
  • Society 5.0 and Industry 5.0.

Reference

[1] Jiewu Leng, Hao Zhang, Douxi Yan, Qiang Liu, Xin Chen & Ding Zhang. (2019) Digital twin-driven manufacturing cyber-physical system for parallel controlling of smart workshop, Journal of Ambient Intelligence and Humanized Computing, 10:3, 1155–1166.

[2] Jiewu Leng, Pingyu Jiang, Chao Liu, and Chuang Wang. (2020) “Contextual self-organizing of manufacturing process for mass individualization: a cyber-physical-social system approach” Enterprise Information Systems. 14:8, 1124-1149.

[3] Jiewu Leng, Douxi Yan, Qiang Liu, Kailin Xu, J. Leon Zhao, Rui Shi, Lijun Wei, Ding Zhang & Xin Chen. (2020) ManuChain: combining permissioned blockchain with a holistic optimization model as bi-level intelligence for smart manufacturing, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50:1, 182-192.

[4] Jiewu Leng, Shide Ye, Man Zhou, J. Leon Zhao, Qiang Liu, Wei Guo, Wei Cao, and Leijie Fu 2021. Blockchain-secured smart manufacturing in Industry 4.0: A survey. IEEE Transactions on Systems, Man, and Cybernetics:Systems. 51(1): 237-252.

Prof. Dr. Jiewu Leng
Prof. Dr. Gang Xiong
Prof. Dr. Jinsong Bao
Prof. Dr. Qiang Liu
Guest Editors

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Published Papers (6 papers)

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Research

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16 pages, 2929 KiB  
Article
Research on the Multi-Screen Connection Interaction Method Based on Regular Octagon K-Value Template Matching
by Liang Chen, Shichen Zhang and Changhong Liu
Symmetry 2022, 14(8), 1528; https://doi.org/10.3390/sym14081528 - 26 Jul 2022
Viewed by 1477
Abstract
Manufacturing companies using CPSS integrate multiple data in organizational production and present the data in the form of data visualization with the help of a big screen data visualization. In order to help the manufacturing enterprises using the data visualization screen to understand [...] Read more.
Manufacturing companies using CPSS integrate multiple data in organizational production and present the data in the form of data visualization with the help of a big screen data visualization. In order to help the manufacturing enterprises using the data visualization screen to understand the data trend of the whole production process more conveniently, this paper proposes a method to establish the connection and interaction between the visualization screen and the mobile terminal based on the positive octagon K-value template matching algorithm, match the pre-processed mobile phone pictures with the visual large screen image, determine the area where the captured image is located in the large screen image, and return the detailed information of chart components contained in the visual large screen area to the mobile phone for users’ observation and analysis. This matching algorithm has good matching accuracy and time efficiency. Application cases and related investigations in enterprises also prove the practicability of this method to a certain extent. Full article
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14 pages, 8595 KiB  
Article
Service-Oriented Real-Time Smart Job Shop Symmetric CPS Based on Edge Computing
by Chuang Wang, Yi Lv, Qiang Wang, Dongyu Yang and Guanghui Zhou
Symmetry 2021, 13(10), 1839; https://doi.org/10.3390/sym13101839 - 1 Oct 2021
Cited by 9 | Viewed by 2079
Abstract
Symmetry is one of the most important notions in the digital twins-driven manufacturing cyber–physical system (CPS). Real-time acquisition of production data and rapid response to changes in the external environment are the keys to ensuring the symmetry of the CPS. In the service-oriented [...] Read more.
Symmetry is one of the most important notions in the digital twins-driven manufacturing cyber–physical system (CPS). Real-time acquisition of production data and rapid response to changes in the external environment are the keys to ensuring the symmetry of the CPS. In the service-oriented production process, in order to solve the problem of the service response delay of the production nodes in a smart job shop, a CPS based on mobile edge computing (MEC) middleware is proposed. First, the CPS and MEC for a service-oriented production process are analyzed. Secondly, based on MEC middleware, a CPS architecture model of a smart job shop is established. Then, the implementation of MEC middleware and application layer function modules are introduced in detail. By designing an MEC middleware model and embedding function modules such as data cache management, redundant data filtering, and data preprocessing, the ability of data processing is sunk from the data center to the data source. Based on that, the network performances, such as network bandwidth, packet loss rate, and delay, are improved. Finally, an experiment platform of the smart job shop is used to verify different data processing modes by comparing the network performance data such as bandwidth, packet loss rate, and response delay. Full article
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17 pages, 1654 KiB  
Article
An Approach for Chart Description Generation in Cyber–Physical–Social System
by Liang Chen and Kangting Zhao
Symmetry 2021, 13(9), 1552; https://doi.org/10.3390/sym13091552 - 24 Aug 2021
Cited by 10 | Viewed by 2306
Abstract
There is an increasing use of charts generated by the social interaction environment in manufacturing enterprise applications. To transform these massive amounts of unstructured chart data into decision support knowledge for demand-capability matching in manufacturing enterprises, we propose a manufacturing enterprise chart description [...] Read more.
There is an increasing use of charts generated by the social interaction environment in manufacturing enterprise applications. To transform these massive amounts of unstructured chart data into decision support knowledge for demand-capability matching in manufacturing enterprises, we propose a manufacturing enterprise chart description generation (MECDG) method, which is a two-phase automated solution: (1) extracting chart data based on optical character recognition and deep learning method; (2) generating chart description according to user input based on natural language generation method and matching the description with extracted chart data. We verified and compared the processing at each phase of the method, and at the same time applied the method to the interactive platform of the manufacturing enterprise. The ultimate goal of this paper is to promote the knowledge extraction and scientific analysis of chart data in the context of manufacturing enterprises, so as to improve the analysis and decision-making capabilities of enterprises. Full article
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23 pages, 8120 KiB  
Article
Digital Twin-Driven Tool Wear Monitoring and Predicting Method for the Turning Process
by Kejia Zhuang, Zhenchuan Shi, Yaobing Sun, Zhongmei Gao and Lei Wang
Symmetry 2021, 13(8), 1438; https://doi.org/10.3390/sym13081438 - 5 Aug 2021
Cited by 23 | Viewed by 4360
Abstract
Accurate monitoring and prediction of tool wear conditions have an important influence on the cutting performance, thereby improving the machining precision of the workpiece and reducing the production cost. However, traditional methods cannot easily achieve exact supervision in real time because of the [...] Read more.
Accurate monitoring and prediction of tool wear conditions have an important influence on the cutting performance, thereby improving the machining precision of the workpiece and reducing the production cost. However, traditional methods cannot easily achieve exact supervision in real time because of the complexity and time-varying nature of the cutting process. A method based on Digital Twin (DT), which establish a symmetrical virtual tool system matching exactly the actual tool system, is presented herein to realize high precision in monitoring and predicting tool wear. Firstly, the framework of the cutting tool system DT is designed, and the components and operations rationale of the framework are detailed. Secondly, the key enabling technologies of the framework are elaborated. In terms of the cutting mechanism, a virtual cutting tool model is built to simulate the cutting process. The modifications and data fusion of the model are carried out to keep the symmetry between physical and virtual systems. Tool wear classification and prediction are presented based on the hybrid-driven method. With the technologies, the physical–virtual symmetry of the DT model is achieved to mapping the real-time status of tool wear accurately. Finally, a case study of the turning process is presented to verify the feasibility of the framework. Full article
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21 pages, 2524 KiB  
Article
Task Decomposition Based on Cloud Manufacturing Platform
by Yanjuan Hu, Ziyu Zhang, Jinwu Wang, Zhanli Wang and Hongliang Liu
Symmetry 2021, 13(8), 1311; https://doi.org/10.3390/sym13081311 - 21 Jul 2021
Cited by 6 | Viewed by 2393
Abstract
As a new service-oriented manufacturing paradigm, cloud manufacturing (CMfg) realizes the optimal allocation of resources in the product manufacturing process through the network. Task decomposition is a key problem of the CMfg system for resource scheduling. A high-quality task decomposition method can shorten [...] Read more.
As a new service-oriented manufacturing paradigm, cloud manufacturing (CMfg) realizes the optimal allocation of resources in the product manufacturing process through the network. Task decomposition is a key problem of the CMfg system for resource scheduling. A high-quality task decomposition method can shorten product development time, reduce costs for resource service providers, and provide technical support for the application of CMfg. However, a cloud manufacturing system has to manage the allocation the correct amount of manufacturing resources, complex production processes, and highly dynamic production environments. At the same time, the tasks issued by service demanders are usually asymmetric and tightly coupled. We solve the complex task decomposition problem by using the traditional methods, that are hard to complete in CMfg. To overcome the shortcomings of CMfg, this paper proposed a task decomposition method based on the cloud platform. For achieving modular production, this approach creatively divides the product production process into four stages: design, manufacturing, transportation, and maintenance. Then a hybrid method, which combines with depth-first search algorithm, fast modular optimization algorithm, and artificial bee colony algorithm, is introduced. The method can obtain a multi-stage task optimization decomposition plan in CMfg. Simulation results demonstrate the proposed method can achieve complex task optimization decomposition in a CMfg environment. Full article
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Review

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21 pages, 8047 KiB  
Review
Digital Twins-Based Smart Design and Control of Ultra-Precision Machining: A Review
by Lei Wu, Jiewu Leng and Bingfeng Ju
Symmetry 2021, 13(9), 1717; https://doi.org/10.3390/sym13091717 - 16 Sep 2021
Cited by 29 | Viewed by 6249
Abstract
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 [...] Read more.
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. Full article
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