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Digital Twins for Complex Systems
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Digital Twins for Complex Systems

A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 12982

Special Issue Editors

Dr. Fabrizio Fornari

E-Mail Website
Guest Editor
School of Science and Technology, Computer Science Department, University of Camerino, Camerino, Italy
Interests: business process management; software engineering; model-driven engineering; Internet of Things; digital twin
Dr. Pedro Valderas

E-Mail Website
Guest Editor
VRAIN Institute, Universitat Politècnica de València, Valencia, Spain
Interests: conceptual modeling; model-driven development; business processes; service engineering; adaptive systems; Internet of Things

Special Issue Information

Dear Colleagues,

In the current Big Data era, digital information pervades most Complex Systems. This is especially due to the wide integration of the Internet of Things in several sectors. This integration gives the opportunity to enhance business performance and achieve business competitiveness. Such opportunities are now pushed forward by the rise of Digital Twins that have become more affordable and promise to drive the future of complex systems.

A Digital Twin (DT) is a digital representation of a physical entity, system, or event. It mirrors a distinctive object, process, building, or human, regardless of whether that thing is tangible or non-tangible in the real world. DTs can leverage the advancement in Artificial Intelligence, Machine Learning, Cognitive Computing, Edge and Cloud Computing, and Augmented and Virtual Reality, to offer a great amount of business potential by predicting the future instead of analyzing the past of complex systems allowing us to evolve towards ex-ante business practices. To achieve these benefits, we must face the following challenges: accurate representation of physical objects; automatic evolution in real-time; runtime connectivity; process collaboration; conflict detection and resolving; human interaction; safety and security. In doing so, we must provide conceptualizations of DTs, define new DT engineering methodology, develop user-friendly software for the development of DT solutions, and foster the adoption of DT within complex systems.

The objective of this Special Issue is to gather empirical, experimental, methodological, and theoretical research reporting original and unpublished results contributing to the definition, design, implementation, and application of DT, shedding light on the continuous enhancement of complex systems integrating DTs, and that present possible solutions to open challenges, that proposes software solutions, practical experiences, use-cases, and case studies.

Potential topics include, but are not limited to:

  • Conceptual Modelling of Digital Twins
  • Management of Digital Twins for Complex Systems
  • Engineering Digital Twins Solutions
  • Digital Twin Conceptualization
  • Digital Twin Platforms
  • Safety and Security in Adopting Digital Twins
  • Accurate Representation of Physical Objects, Processes, and Complex Systems
  • Framework Definition for Digital Twins
  • Development of Digital Twin Platforms
  • Quality Assurance of Digital Twins
  • Enactment of Digital Process Twins
  • Collaboration among Digital Twins
  • Interaction and cooperation between Digital Twins and Humans
  • Complex System Architectures for Digital Twins
  • Smart Cities and Digital Twins
  • Artificial Intelligence Approaches for Digital Twins
  • Methods and Techniques for the Development of Digital Twins Solutions
  • Edge/Fog/Cloud Computing for Digital Twins
  • Practical Validation and Case Studies of Digital Twins
  • Digital Twin Enhanced Business Processes
  • Cognitive Computing for Digital Twins
  • Augmented and Virtual Reality for Digital Twin

Dr. Fabrizio Fornari
Dr. Pedro Valderas
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Big Data and Cognitive Computing is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digital twin
  • digital twin conceptualisation
  • digital process twin
  • digital twin platforms
  • Internet of Things
  • business processes
  • Artificial Intelligence
  • cognitive computing
  • complex systems
  • machine learning
  • augmented reality
  • virtual reality

Published Papers (5 papers)

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Research

20 pages, 1188 KiB  
Article
Applied Digital Twin Concepts Contributing to Heat Transition in Building, Campus, Neighborhood, and Urban Scale
by Ekaterina Lesnyak, Tabea Belkot, Johannes Hurka, Jan Philipp Hörding, Lea Kuhlmann, Pavel Paulau, Marvin Schnabel, Patrik Schönfeldt and Jan Middelberg
Big Data Cogn. Comput. 2023, 7(3), 145; https://doi.org/10.3390/bdcc7030145 - 25 Aug 2023
Viewed by 1951
Abstract
The heat transition is a central pillar of the energy transition, aiming to decarbonize and improve the energy efficiency of the heat supply in both the private and industrial sectors. On the one hand, this is achieved by substituting fossil fuels with renewable [...] Read more.
The heat transition is a central pillar of the energy transition, aiming to decarbonize and improve the energy efficiency of the heat supply in both the private and industrial sectors. On the one hand, this is achieved by substituting fossil fuels with renewable energy. On the other hand, it involves reducing overall heat consumption and associated transmission and ventilation losses. In addition to refurbishment, digitalization contributes significantly. Despite substantial research on Digital Twins (DTs) for heat transition at different scales, a cross-scale perspective on heat optimization still needs to be developed. In response to this research gap, the present study examines four instances of applied DTs across various scales: building, campus, neighborhood, and urban. The study compares their objectives and conceptual frameworks while also identifying common challenges and potential synergies. The study’s findings indicate that all DT scales face similar data-related challenges, such as gathering, ownership, connectivity, and reliability. Also, hierarchical synergy is identified among the DTs, implying the need for collaboration and exchange. In response to this, the “Wärmewende” data platform, whose objectives and concepts are presented in the paper, promotes research data and knowledge exchange with internal and external stakeholders. Full article
(This article belongs to the Special Issue Digital Twins for Complex Systems)
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14 pages, 6577 KiB  
Article
Executable Digital Process Twins: Towards the Enhancement of Process-Driven Systems
by Flavio Corradini, Sara Pettinari, Barbara Re, Lorenzo Rossi and Francesco Tiezzi
Big Data Cogn. Comput. 2023, 7(3), 139; https://doi.org/10.3390/bdcc7030139 - 08 Aug 2023
Cited by 1 | Viewed by 1554
Abstract
The development of process-driven systems and the advancements in digital twins have led to the birth of new ways of monitoring and analyzing systems, i.e., digital process twins. Specifically, a digital process twin can allow the monitoring of system behavior and the analysis [...] Read more.
The development of process-driven systems and the advancements in digital twins have led to the birth of new ways of monitoring and analyzing systems, i.e., digital process twins. Specifically, a digital process twin can allow the monitoring of system behavior and the analysis of the execution status to improve the whole system. However, the concept of the digital process twin is still theoretical, and process-driven systems cannot really benefit from them. In this regard, this work discusses how to effectively exploit a digital process twin and proposes an implementation that combines the monitoring, refinement, and enactment of system behavior. We demonstrated the proposed solution in a multi-robot scenario. Full article
(This article belongs to the Special Issue Digital Twins for Complex Systems)
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25 pages, 4475 KiB  
Article
Industrial Insights on Digital Twins in Manufacturing: Application Landscape, Current Practices, and Future Needs
by Rosario Davide D’Amico, Sri Addepalli and John Ahmet Erkoyuncu
Big Data Cogn. Comput. 2023, 7(3), 126; https://doi.org/10.3390/bdcc7030126 - 29 Jun 2023
Viewed by 1923
Abstract
The digital twin (DT) research field is experiencing rapid expansion; yet, the research on industrial practices in this area remains poorly understood. This paper aims to address this knowledge gap by sharing feedback and future requirements from the manufacturing industry. The methodology employed [...] Read more.
The digital twin (DT) research field is experiencing rapid expansion; yet, the research on industrial practices in this area remains poorly understood. This paper aims to address this knowledge gap by sharing feedback and future requirements from the manufacturing industry. The methodology employed in this study involves an examination of a survey that received 99 responses and interviews with 14 experts from 10 prominent UK organisations, most of which are involved in the defence industry in the UK. The survey and interviews explored topics such as DT design, return on investment, drivers, inhibitors, and future directions for DT development in manufacturing. This study’s findings indicate that DTs should possess characteristics such as adaptability, scalability, interoperability, and the ability to support assets throughout their entire life cycle. On average, completed DT projects reach the breakeven point in less than two years. The primary motivators behind DT development were identified to be autonomy, customer satisfaction, safety, awareness, optimisation, and sustainability. Meanwhile, the main obstacles include a lack of expertise, funding, and interoperability. This study concludes that the federation of twins and a paradigm shift in industrial thinking are essential components for the future of DT development. Full article
(This article belongs to the Special Issue Digital Twins for Complex Systems)
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17 pages, 2065 KiB  
Article
Virtual Reality-Based Digital Twins: A Case Study on Pharmaceutical Cannabis
by Orestis Spyrou, William Hurst and Cor Verdouw
Big Data Cogn. Comput. 2023, 7(2), 95; https://doi.org/10.3390/bdcc7020095 - 10 May 2023
Cited by 1 | Viewed by 3053
Abstract
Digital Twins are digital equivalents of real-life objects. They allow producers to act immediately in case of (expected) deviations and to simulate effects of interventions based on real-life data. Digital Twin and eXtended Reality technologies (including Augmented Reality, Mixed Reality and Virtual Reality [...] Read more.
Digital Twins are digital equivalents of real-life objects. They allow producers to act immediately in case of (expected) deviations and to simulate effects of interventions based on real-life data. Digital Twin and eXtended Reality technologies (including Augmented Reality, Mixed Reality and Virtual Reality technologies), when coupled, are promising solutions to address the challenges of highly regulated crop production, namely the complexity of modern production environments for pharmaceutical cannabis, which are growing constantly as a result of legislative changes. Cannabis farms not only have to meet very high quality standards and regulatory requirements but also have to deal with high production and market uncertainties, including energy considerations. Thus, the main contributions of the research include an architecture design for eXtended-Reality-based Digital Twins for pharmaceutical cannabis production and a proof of concept, which was demonstrated at the Wageningen University Digital Twins conference. A convenience sampling method was used to recruit 30 participants who provided feedback on the application. The findings indicate that, despite 70% being unfamiliar with the concept, 80% of the participants were positive regarding the innovation and creativity. Full article
(This article belongs to the Special Issue Digital Twins for Complex Systems)
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20 pages, 9783 KiB  
Article
Digital Twin Four-Dimension Fusion Modeling Method Design and Application to the Discrete Manufacturing Line
by Jieyu Xie and Jiafu Wan
Big Data Cogn. Comput. 2023, 7(2), 89; https://doi.org/10.3390/bdcc7020089 - 08 May 2023
Cited by 4 | Viewed by 2058
Abstract
With the development of new-generation information technologies, such as big data and artificial intelligence, digital twins have become a key technology in intelligent manufacturing. The introduction of digital twin technology has addressed many problems in discrete manufacturing lines, including low visualization and difficult [...] Read more.
With the development of new-generation information technologies, such as big data and artificial intelligence, digital twins have become a key technology in intelligent manufacturing. The introduction of digital twin technology has addressed many problems in discrete manufacturing lines, including low visualization and difficult cyber–physical integration. However, the application of digital twin technology to discrete manufacturing lines still faces problems of low modeling accuracy, response delay, and insufficient production line control accuracy. Therefore, this paper proposes a digital twin four-dimension fusion modeling method to solve the above problems. First, a digital twin system architecture for a discrete manufacturing production line is designed. Then, the information control dimension is integrated into traditional digital twin modeling methods. Further, a digital twin geometry–physics–behavior–information control four-dimension fusion modeling method is proposed. This method can describe the geometric and physical characteristics of a physical entity and map its behavior mechanism. More importantly, it reveals the control logic and virtual–real mapping rules, which provides important support for the virtual–real intelligent mutual control. Finally, the feasibility and effectiveness of the proposed method are verified by experiments on a fidget spinner discrete manufacturing line, and a digital twin operation and maintenance management system is developed. The results presented in this study could provide ideas for the digital transformation of discrete manufacturing enterprises. Full article
(This article belongs to the Special Issue Digital Twins for Complex Systems)
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