Special Issue "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: 31 December 2020.

Special Issue Editors

Prof. A.Y.C. Nee
Website
Guest Editor
National University of Singapore
Prof. S.K. Ong
Website
Guest Editor
National University of Singapore

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

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 papers will be 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. Applied Sciences is an international peer-reviewed open access semimonthly 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
  • Prognostics and health monitoring
  • Cyberphysical systems
  • Cybersecurity
  • Industry 4.0
  • Internet of Things
  • Smart city
  • Healthcare

Published Papers (6 papers)

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Research

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Open AccessArticle
Digital Twin for Monitoring Ergonomics during Manufacturing Production
Appl. Sci. 2020, 10(21), 7758; https://doi.org/10.3390/app10217758 - 02 Nov 2020
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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Open AccessArticle
Towards Semi-Automatic Generation of a Steady State Digital Twin of a Brownfield Process Plant
Appl. Sci. 2020, 10(19), 6959; https://doi.org/10.3390/app10196959 - 05 Oct 2020
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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Open AccessArticle
Implementation of Digital Twin for Engine Block Manufacturing Processes
Appl. Sci. 2020, 10(18), 6578; https://doi.org/10.3390/app10186578 - 21 Sep 2020
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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Open AccessArticle
Digital Twin and Web-Based Virtual Gaming Technologies for Online Education: A Case of Construction Management and Engineering
Appl. Sci. 2020, 10(13), 4678; https://doi.org/10.3390/app10134678 - 07 Jul 2020
Cited by 2
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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Open AccessArticle
Digital Twin for Variation Management: A General Framework and Identification of Industrial Challenges Related to the Implementation
Appl. Sci. 2020, 10(10), 3342; https://doi.org/10.3390/app10103342 - 12 May 2020
Cited by 2
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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Open AccessReview
Digital Twin and Internet of Things—Current Standards Landscape
Appl. Sci. 2020, 10(18), 6519; https://doi.org/10.3390/app10186519 - 18 Sep 2020
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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