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Digital Twins in Industry
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Digital Twins in Industry

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".

Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 104317

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Prof. Dr. Andrew Yeh Ching Nee

E-Mail Website
Guest Editor
Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117576, Singapore
Interests: manufacturing; augmented reality in manufacturing; product design; sustainable manufacturing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Soh Khim Ong

E-Mail Website
Guest Editor
Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117576, Singapore
Interests: augmented reality; digital twins; advanced manufacturing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Digital twin technology has seen rapid growth in the last ten years. It is a natural progression and fusion of many emerging technologies such as Internet of Things; wireless communication; sensors technology; cloud computing; artificial intelligence; big data analytics; data integration; data visualization in the form of virtual and augmented reality. It has been recognized as one of the pillars of Industry 4.0—the major effort in integrating all the elements in the manufacturing industry—toward achieving seamless control and communications between labor, machines, and management. Numerous potential applications have been proposed in the manufacturing industry, from prognostics and health monitoring of production equipment, to inventory control and purchasing, man–machine interaction, communication, and many more. Digital twin has also spread its wings in areas such as healthcare, urban and smart city development, civil and construction, aviation, and marine and shipping.

Academia has been very responsive in exploring the potential of digital twin, and numerous frameworks and propositions have been reported. Many of them, however, are hypothetical with little real-life implementation, and have largely remained in the realm of the laboratory environment.

This Special Issue will examine the industrial applications and implementation of digital twin technology across various industrial, commercial, and financial sectors. It will be particularly useful to learn of the approaches which have been undertaken by the industry in dealing with issues such as, for example, cybersecurity and intellectual property.

Prof. A.Y.C. Nee
Prof. S.K. Ong
Guest Editors

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Keywords

  • Digital twin
  • Prognostics and health monitoring
  • Cyberphysical systems
  • Cybersecurity
  • Industry 4.0
  • Internet of Things
  • Smart city
  • Healthcare

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Published Papers (12 papers)

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Editorial

Jump to: Research, Review

3 pages, 157 KiB  
Editorial
Special Issue on Digital Twins in Industry
by A. Y. C. Nee and S. K. Ong
Appl. Sci. 2021, 11(14), 6437; https://doi.org/10.3390/app11146437 - 12 Jul 2021
Cited by 3 | Viewed by 3077
Abstract
Digital twin (DT) is an emerging and fast-growing technology which provides a promising way to connect and integrate physical and virtual spaces seamlessly [...] Full article
(This article belongs to the Special Issue Digital Twins in Industry)

Research

Jump to: Editorial, Review

14 pages, 418 KiB  
Article
Sustainability Requirements of Digital Twin-Based Systems: A Meta Systematic Literature Review
by Rui Carvalho and Alberto Rodrigues da Silva
Appl. Sci. 2021, 11(12), 5519; https://doi.org/10.3390/app11125519 - 15 Jun 2021
Cited by 32 | Viewed by 8377
Abstract
Sustainable development was defined by the UN in 1987 as development that meets the needs of the present without compromising the ability of future generations to meet their own needs, and this is a core concept in this paper. This work acknowledges the [...] Read more.
Sustainable development was defined by the UN in 1987 as development that meets the needs of the present without compromising the ability of future generations to meet their own needs, and this is a core concept in this paper. This work acknowledges the three dimensions of sustainability, i.e., economic, social, and environmental, but its focus is on this last one. A digital twin (DT) is frequently described as a physical entity with a virtual counterpart, and the data, connections between the two, implying the existence of connectors and blocks for efficient and effective data communication. This paper provides a meta systematic literature review (SLR) (i.e., an SLR of SLRs) regarding the sustainability requirements of DT-based systems. Numerous papers on the subject of DT were also selected because they cited the analyzed SLRs and were considered relevant to the purposes of this research. From the selection and analysis of 29 papers, several limitations and challenges were identified: the perceived benefits of DTs are not clearly understood; DTs across the product life cycle or the DT life cycle are not sufficiently studied; it is not clear how DTs can contribute to reducing costs or supporting decision-making; technical implementation of DTs must be improved and better integrated in the context of the IoT; the level of fidelity of DTs is not entirely evaluated in terms of their parameters, accuracy, and level of abstraction; and the ownership of data stored within DTs should be better understood. Furthermore, from our research, it was not possible to find a paper discussing DTs only in regard to environmental sustainability. Full article
(This article belongs to the Special Issue Digital Twins in Industry)
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19 pages, 4295 KiB  
Article
A Virtual Prototype for Fast Design and Visualization of Gerotor Pumps
by Juan Pareja-Corcho, Aitor Moreno, Bruno Simoes, Asier Pedrera-Busselo, Ekain San-Jose, Oscar Ruiz-Salguero and Jorge Posada
Appl. Sci. 2021, 11(3), 1190; https://doi.org/10.3390/app11031190 - 28 Jan 2021
Cited by 9 | Viewed by 3929
Abstract
In the context of generation of lubrication flows, gear pumps are widely used, with gerotor-type pumps being specially popular, given their low cost, high compactness, and reliability. The design process of gerotor pumps requires the simulation of the fluid dynamics phenomena that characterize [...] Read more.
In the context of generation of lubrication flows, gear pumps are widely used, with gerotor-type pumps being specially popular, given their low cost, high compactness, and reliability. The design process of gerotor pumps requires the simulation of the fluid dynamics phenomena that characterize the fluid displacement by the pump. Designers and researchers mainly rely on these methods: (i) computational fluid dynamics (CFD) and (ii) lumped parameter models. CFD methods are accurate in predicting the behavior of the pump, at the expense of large computing resources and time. On the other hand, Lumped Parameter models are fast and they do not require CFD software, at the expense of diminished accuracy. Usually, Lumped Parameter fluid simulation is mounted on specialized black-box visual programming platforms. The resulting pressures and flow rates are then fed to the design software. In response to the current status, this manuscript reports a virtual prototype to be used in the context of a Digital Twin tool. Our approach: (1) integrates pump design, fast approximate simulation, and result visualization processes, (2) does not require an external numerical solver platforms for the approximate model, (3) allows for the fast simulation of gerotor performance using sensor data to feed the simulation model, and (4) compares simulated data vs. imported gerotor operational data. Our results show good agreement between our prediction and CFD-based simulations of the actual pump. Future work is required in predicting rotor micro-movements and cavitation effects, as well as further integration of the physical pump with the software tool. Full article
(This article belongs to the Special Issue Digital Twins in Industry)
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22 pages, 4106 KiB  
Article
Developing a Digital Twin and Digital Thread Framework for an ‘Industry 4.0’ Shipyard
by Toh Yen Pang, Juan D. Pelaez Restrepo, Chi-Tsun Cheng, Alim Yasin, Hailey Lim and Miro Miletic
Appl. Sci. 2021, 11(3), 1097; https://doi.org/10.3390/app11031097 - 25 Jan 2021
Cited by 107 | Viewed by 14765
Abstract
This paper provides an overview of the current state-of-the-art digital twin and digital thread technology in industrial operations. Both are transformational technologies that have the advantage of improving the efficiency of current design and manufacturing. Digital twin is an important element of the [...] Read more.
This paper provides an overview of the current state-of-the-art digital twin and digital thread technology in industrial operations. Both are transformational technologies that have the advantage of improving the efficiency of current design and manufacturing. Digital twin is an important element of the Industry 4.0 digitalization process; however, the huge amount of data that are generated and collected by a digital twin offer challenges in handling, processing and storage. The paper aims to report on the development of a new framework that combines the digital twin and digital thread for better data management in order to drive innovation, improve the production process and performance and ensure continuity and traceability of information. The digital twin/thread framework incorporates behavior simulation and physical control components, in which these two components rely on the connectivity between the twin and thread for information flow and exchange to drive innovation. The twin/thread framework encompasses specifications that include organizational architecture layout, security, user access, databases and hardware and software requirements. It is envisaged that the framework will be applicable to enhancing the optimization of operational processes and traceability of information in the physical world, especially in an Industry Shipyard 4.0. Full article
(This article belongs to the Special Issue Digital Twins in Industry)
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35 pages, 2117 KiB  
Article
Towards Integrated Digital Twins for Industrial Products: Case Study on an Overhead Crane
by Juuso Autiosalo, Riku Ala-Laurinaho, Joel Mattila, Miika Valtonen, Valtteri Peltoranta and Kari Tammi
Appl. Sci. 2021, 11(2), 683; https://doi.org/10.3390/app11020683 - 12 Jan 2021
Cited by 33 | Viewed by 7799
Abstract
Industrial Internet of Things practitioners are adopting the concept of digital twins at an accelerating pace. The features of digital twins range from simulation and analysis to real-time sensor data and system integration. Implementation examples of modeling-oriented twins are becoming commonplace in academic [...] Read more.
Industrial Internet of Things practitioners are adopting the concept of digital twins at an accelerating pace. The features of digital twins range from simulation and analysis to real-time sensor data and system integration. Implementation examples of modeling-oriented twins are becoming commonplace in academic literature, but information management-focused twins that combine multiple systems are scarce. This study presents, analyzes, and draws recommendations from building a multi-component digital twin as an industry-university collaboration project and related smaller works. The objective of the studied project was to create a prototype implementation of an industrial digital twin for an overhead crane called “Ilmatar”, serving machine designers and maintainers in their daily tasks. Additionally, related cases focus on enhancing operation. This paper describes two tools, three frameworks, and eight proof-of-concept prototypes related to digital twin development. The experiences show that good-quality Application Programming Interfaces (APIs) are significant enablers for the development of digital twins. Hence, we recommend that traditional industrial companies start building their API portfolios. The experiences in digital twin application development led to the discovery of a novel API-based business network framework that helps organize digital twin data supply chains. Full article
(This article belongs to the Special Issue Digital Twins in Industry)
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20 pages, 4782 KiB  
Article
Digital Twin for Monitoring Ergonomics during Manufacturing Production
by Alessandro Greco, Mario Caterino, Marcello Fera and Salvatore Gerbino
Appl. Sci. 2020, 10(21), 7758; https://doi.org/10.3390/app10217758 - 2 Nov 2020
Cited by 63 | Viewed by 5610
Abstract
Within the era of smart factories, concerning the ergonomics related to production processes, the Digital Twin (DT) is the key to set up novel models for monitoring the performance of manual work activities, which are able to provide results in near real time [...] Read more.
Within the era of smart factories, concerning the ergonomics related to production processes, the Digital Twin (DT) is the key to set up novel models for monitoring the performance of manual work activities, which are able to provide results in near real time and to support the decision-making process for improving the working conditions. This paper aims to propose a methodological framework that, by implementing a human DT, and supports the monitoring and the decision making regarding the ergonomics performances of manual production lines. A case study, carried out in a laboratory, is presented for demonstrating the applicability and the effectiveness of the proposed framework. The results show how it is possible to identify the operational issues of a manual workstation and how it is possible to propose and test improving solutions. Full article
(This article belongs to the Special Issue Digital Twins in Industry)
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21 pages, 8607 KiB  
Article
Towards Semi-Automatic Generation of a Steady State Digital Twin of a Brownfield Process Plant
by Seppo Sierla, Lotta Sorsamäki, Mohammad Azangoo, Antti Villberg, Eemeli Hytönen and Valeriy Vyatkin
Appl. Sci. 2020, 10(19), 6959; https://doi.org/10.3390/app10196959 - 5 Oct 2020
Cited by 22 | Viewed by 4494
Abstract
Researchers have proposed various models for assessing design alternatives for process plant retrofits. Due to the considerable engineering effort involved, no such models exist for the great majority of brownfield process plants, which have been in operation for years or decades. This article [...] Read more.
Researchers have proposed various models for assessing design alternatives for process plant retrofits. Due to the considerable engineering effort involved, no such models exist for the great majority of brownfield process plants, which have been in operation for years or decades. This article proposes a semi-automatic methodology for generating a digital twin of a brownfield plant. The methodology consists of: (1) extracting information from piping and instrumentation diagrams, (2) converting the information to a graph format, (3) applying graph algorithms to preprocess the graph, (4) generating a simulation model from the graph, (5) performing manual expert editing of the generated model, (6) configuring the calculations done by simulation model elements and (7) parameterizing the simulation model according to recent process measurements in order to obtain a digital twin. Since previous work exists for steps (1–2), this article focuses on defining the methodology for (3–5) and demonstrating it on a laboratory process. A discussion is provided for (6–7). The result of the case study was that only few manual edits needed to be made to the automatically generated simulation model. The paper is concluded with an assessment of open issues and topics of further research for this 7-step methodology. Full article
(This article belongs to the Special Issue Digital Twins in Industry)
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10 pages, 2632 KiB  
Article
Implementation of Digital Twin for Engine Block Manufacturing Processes
by Roman Bambura, Marek Šolc, Miroslav Dado and Luboš Kotek
Appl. Sci. 2020, 10(18), 6578; https://doi.org/10.3390/app10186578 - 21 Sep 2020
Cited by 31 | Viewed by 4944
Abstract
The digital twin (DT) is undergoing an increase in interest from both an academic and industrial perspective. Although many authors proposed and described various frameworks for DT implementation in the manufacturing industry context, there is an absence of real-life implementation studies reported in [...] Read more.
The digital twin (DT) is undergoing an increase in interest from both an academic and industrial perspective. Although many authors proposed and described various frameworks for DT implementation in the manufacturing industry context, there is an absence of real-life implementation studies reported in the available literature. The main aim of this paper is to demonstrate feasibility of the DT implementation under real conditions of a production plant that is specializing in manufacturing of the aluminum components for the automotive industry. The implementation framework of the DT for engine block manufacturing processes consists of three layers: physical layer, virtual layer and information-processing layer. A simulation model was created using the Tecnomatix Plant Simulation (TPS) software. In order to obtain real-time status data of the production line, programmable logic control (PLC) sensors were used for raw data acquisition. To increase production line productivity, the algorithm for bottlenecks detection was developed and implemented into the DT. Despite the fact that the implementation process is still under development and only partial results are presented in this paper, the DT seems to be a prospective real-time optimization tool for the industrial partner. Full article
(This article belongs to the Special Issue Digital Twins in Industry)
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31 pages, 31523 KiB  
Article
Digital Twin and Web-Based Virtual Gaming Technologies for Online Education: A Case of Construction Management and Engineering
by Samad M.E. Sepasgozar
Appl. Sci. 2020, 10(13), 4678; https://doi.org/10.3390/app10134678 - 7 Jul 2020
Cited by 154 | Viewed by 17172
Abstract
Mixed reality is advancing exponentially in some innovative industries, including manufacturing and aerospace. However, advanced applications of these technologies in architecture, engineering, and construction (AEC) businesses remain nascent. While it is in demand, the use of these technologies in developing the AEC digital [...] Read more.
Mixed reality is advancing exponentially in some innovative industries, including manufacturing and aerospace. However, advanced applications of these technologies in architecture, engineering, and construction (AEC) businesses remain nascent. While it is in demand, the use of these technologies in developing the AEC digital pedagogy and for improving professional competence have received little attention. This paper presents a set of five novel digital technologies utilising virtual and augmented reality and digital twin, which adds value to the literature by showing their usefulness in the delivery of construction courses. The project involved designing, developing, and implementing a construction augmented reality (AR), including Piling AR (PAR) and a virtual tunnel boring machine (VTBM) module. The PAR is a smartphone module that presents different elements of a building structure, the footing system, and required equipment for footing construction. VTBM is developed as a multiplayer and avatar-included module for experiencing mechanisms of a tunnel boring machine. The novelty of this project is that it developed innovative immersive construction modules, practices of implementing digital pedagogy, and presenting the capacity of virtual technologies for education. This paper is also highly valuable to educators since it shows how a set of simple to complex technologies can be used for teaching various courses from a distance, either in emergencies such as corona virus disease (COVID-19) or as a part of regular teaching. This paper is a step forward to designing future practices full of virtual education appropriate to the new generation of digitally savvy students. Full article
(This article belongs to the Special Issue Digital Twins in Industry)
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16 pages, 3683 KiB  
Article
Digital Twin for Variation Management: A General Framework and Identification of Industrial Challenges Related to the Implementation
by Kristina Wärmefjord, Rikard Söderberg, Benjamin Schleich and Hua Wang
Appl. Sci. 2020, 10(10), 3342; https://doi.org/10.3390/app10103342 - 12 May 2020
Cited by 39 | Viewed by 4784
Abstract
Digital twins have gained a lot of interest in recent years. This paper presents a survey among researchers and engineers with expertise in variation management confirming the interest of digital twins in this area. The survey shows, however, a gap between future research [...] Read more.
Digital twins have gained a lot of interest in recent years. This paper presents a survey among researchers and engineers with expertise in variation management confirming the interest of digital twins in this area. The survey shows, however, a gap between future research interest in academia and industry, identifying a larger need in industry. This indicates that there are some barriers in the industry to overcome before the benefits of a digital twin for variation management and geometry assurance can be fully capitalized on in an industrial context. To identify those barriers and challenges, an extensive interview study with engineers from eight different companies in the manufacturing sectors was accomplished. The analysis identifies industrial challenges in the areas of system-level, simulation working process, management issues, and education. One of the main challenges is to keep the 3D models fully updated, including keeping track of changes during the product development process and also feedback changes during full production to the development engineers. This is a part of what is called the digital thread, which is also addressed in this paper. Full article
(This article belongs to the Special Issue Digital Twins in Industry)
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Review

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17 pages, 5497 KiB  
Review
Is Digital Twin Technology Supporting Safety Management? A Bibliometric and Systematic Review
by Giulio Paolo Agnusdei, Valerio Elia and Maria Grazia Gnoni
Appl. Sci. 2021, 11(6), 2767; https://doi.org/10.3390/app11062767 - 19 Mar 2021
Cited by 76 | Viewed by 7829
Abstract
In the Industry 4.0 era, digital tools applied to production and manufacturing activities represent a challenge for companies. Digital Twin (DT) technology is based on the integration of different “traditional” tools, such as simulation modeling and sensors, and is aimed at increasing process [...] Read more.
In the Industry 4.0 era, digital tools applied to production and manufacturing activities represent a challenge for companies. Digital Twin (DT) technology is based on the integration of different “traditional” tools, such as simulation modeling and sensors, and is aimed at increasing process performance. In DTs, simulation modeling allows for the building of a digital copy of real processes, which is dynamically updated through data derived from smart objects based on sensor technologies. The use of DT within manufacturing activities is constantly increasing, as DTs are being applied in different areas, from the design phase to the operational ones. This study aims to analyze existing fields of applications of DTs for supporting safety management processes in order to evaluate the current state of the art. A bibliometric review was carried out through VOSviewer to evaluate studies and applications of DTs in the engineering and computer science areas and to identify research clusters and future trends. Next, a bibliometric and systematic review was carried out to deepen the relation between the DT approach and safety issues. The findings highlight that in recent years, DT applications have been tested and developed to support operators during normal and emergency conditions and to enhance their abilities to control safety levels. Full article
(This article belongs to the Special Issue Digital Twins in Industry)
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21 pages, 3415 KiB  
Review
Digital Twin and Internet of Things—Current Standards Landscape
by Michael Jacoby and Thomas Usländer
Appl. Sci. 2020, 10(18), 6519; https://doi.org/10.3390/app10186519 - 18 Sep 2020
Cited by 130 | Viewed by 16253
Abstract
Industry 4.0 is revolutionizing industrial production by bridging the physical and the virtual worlds and further improving digitalization. Two essential building blocks in industry 4.0 are digital twins (DT) and the internet of things (IoT). While IoT is about connecting resources and collecting [...] Read more.
Industry 4.0 is revolutionizing industrial production by bridging the physical and the virtual worlds and further improving digitalization. Two essential building blocks in industry 4.0 are digital twins (DT) and the internet of things (IoT). While IoT is about connecting resources and collecting data about the physical world, DTs are the virtual representations of resources organizing and managing information and being tightly integrated with artificial intelligence, machine learning and cognitive services to further optimize and automate production. The concepts of DTs and IoT are overlapping when it comes to describing, discovering and accessing resources. Currently, there are multiple DT and IoT standards covering these overlapping aspects created by different organizations with different backgrounds and perspectives. With regard to interoperability, which is presumably the most important aspect of industry 4.0, this barrier needs to be overcome by consolidation of standards. The objective of this paper is to investigate current DT and IoT standards and provide insights to stimulate this consolidation. Overlapping aspects are identified and a classification scheme is created and applied to the standards. The results are compared, aspects with high similarity or divergence are identified and a proposal for stimulating consolidation is presented. Consensus between standards are found regarding the elements a resource should consist of and which serialization format(s) and network protocols to use. Controversial topics include which query language to use for discovery as well as if geo-spatial, temporal and historical data should be explicitly supported. Full article
(This article belongs to the Special Issue Digital Twins in Industry)
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