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Machines
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Advances in Digital Twins for Manufacturing
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Advances in Digital Twins for Manufacturing

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Advanced Manufacturing".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 13716

Special Issue Editors

Dr. Michael Grieves

E-Mail Website
Guest Editor
Department of Engineering, University of Central Florida, Orlando, FL 32816, USA
Interests: manufacturing technology; life cycle assesment
Dr. John Vickers

E-Mail Website
Guest Editor
NASA, Washington, DC, USA
Interests: manufacturing; materials; digital twin

Special Issue Information

Dear Colleagues,

The proposed applications of digital twins have exploded in the last half decade. While applicable to all aspects human activities, digital twins are especially useful for products throughout their entire lifecycle, especially in manufacturing. The ability to effectively and efficiently manufacture products is critical to the products’ success. By trading information for wasting physical resources, digital twins can enable manufacturing to be as lean as possible.

The use of digital twins in manufacturing is important in two aspects. First, digital twins can be used in the manufacturing process itself, from creating the manufacturing process to monitoring and controlling the entire manufacturing process from raw material to final assembly and shipment. Digital twins can be used at all levels of production, from individual equipment to work cells to assembly lines to the entire manufacturing facility. Second, capturing information about how individual products have been manufactured is critical for creating the digital twin instance (DTI), which will then be connected to that product for the rest of the product’s life.

Dr. Michael Grieves
Dr. John Vickers
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. Machines 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 2400 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 predictive versus periodic maintenance
  • digital twin factory replication for monitoring and control
  • digital twin for front running simulation (FRS) of manufacturing for problem and failure avoidance
  • digital twin instance (DTI) creation in manufacturing
  • digital-twin-enabled manufacturability during product development
  • digital-twin-enabled manufacturing bill of process creation
  • digital twins for legacy manufacturing equipment
  • digital twin interoperability of different factory machines and equipment
  • digital twin metaverses and platforms for manufacturing facilities
  • digital-twin-based specification/quality manufacturing control

Published Papers (5 papers)

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Editorial

Jump to: Research

13 pages, 1747 KiB  
Editorial
Digital Twin Certified: Employing Virtual Testing of Digital Twins in Manufacturing to Ensure Quality Products
by Michael Grieves
Machines 2023, 11(8), 808; https://doi.org/10.3390/machines11080808 - 06 Aug 2023
Cited by 4 | Viewed by 1682
Abstract
Quality products are a main focus for manufacturers. Product users only determine a product to be a quality product if it performs in operation to the user’s perceived standard. Product manufactures need to take a product lifecycle quality (PLQ) perspective of quality and [...] Read more.
Quality products are a main focus for manufacturers. Product users only determine a product to be a quality product if it performs in operation to the user’s perceived standard. Product manufactures need to take a product lifecycle quality (PLQ) perspective of quality and not simply focus on manufacturing quality control, which is more accurately specification control. Manufacturing is the key phase where products take their physical form. There are increasing costs and decreasing risks of different physical quality strategies. The information provided using digital twins and virtual testing promises to be both low risk and cost and has the potential to predict what the customer will experience in operation by testing products passively with data and actively with simulation to destruction. Digital Twin Certified (DTC) is proposed as the methodology for accomplishing this. DTC will be especially important for the adoption of additive manufacturing. Full article
(This article belongs to the Special Issue Advances in Digital Twins for Manufacturing)
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Research

Jump to: Editorial

15 pages, 2937 KiB  
Article
Digital Twin Data Management: Framework and Performance Metrics of Cloud-Based ETL System
by Austeja Dapkute, Vytautas Siozinys, Martynas Jonaitis, Mantas Kaminickas and Milvydas Siozinys
Machines 2024, 12(2), 130; https://doi.org/10.3390/machines12020130 - 12 Feb 2024
Viewed by 975
Abstract
This study delves into the EA-SAS platform, a digital twin environment developed by our team, with a particular focus on the EA-SAS Cloud Scheduler, our bespoke program designed to optimize ETL (extract, transform, and load) scheduling and thereby enhance automation within industrial systems. [...] Read more.
This study delves into the EA-SAS platform, a digital twin environment developed by our team, with a particular focus on the EA-SAS Cloud Scheduler, our bespoke program designed to optimize ETL (extract, transform, and load) scheduling and thereby enhance automation within industrial systems. We elucidate the architectural intricacies of the EA-SAS Cloud Scheduler, demonstrating its adeptness in efficiently managing computationally heavy tasks, a capability underpinned by our empirical benchmarks. The architecture of the scheduler incorporates Docker to create isolated task environments and leverages RabbitMQ for effective task distribution. Our analysis reveals the EA-SAS Cloud Scheduler’s prowess in maintaining minimal overhead times, even in scenarios characterized by high operational loads, underscoring its potential to markedly bolster operational efficiency in industrial settings. While acknowledging the limitations inherent in our current assessment, particularly in simulating real-world industrial complexities, the study also charts potential future research pathways. These include a thorough exploration of the EA-SAS Cloud Scheduler’s adaptability across diverse industrial scenarios and an examination of the integration challenges associated with its reliance on specific technological frameworks. Full article
(This article belongs to the Special Issue Advances in Digital Twins for Manufacturing)
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22 pages, 5000 KiB  
Article
Manufacturing 4.0: Checking the Feasibility of a Work Cell Using Asset Administration Shell and Physics-Based Three-Dimensional Digital Twins
by Quang-Duy Nguyen, Yining Huang, François Keith, Christophe Leroy, Minh-Thuyen Thi and Saadia Dhouib
Machines 2024, 12(2), 95; https://doi.org/10.3390/machines12020095 - 28 Jan 2024
Viewed by 1056
Abstract
Feasibility checking is a step in manufacturing system engineering for verifying the normalization and effectiveness of a manufacturing system associated with a specific configuration of resources and processes. It enables factory operators to predict problems before operational time, thus preventing equipment and machinery [...] Read more.
Feasibility checking is a step in manufacturing system engineering for verifying the normalization and effectiveness of a manufacturing system associated with a specific configuration of resources and processes. It enables factory operators to predict problems before operational time, thus preventing equipment and machinery accidents and reducing labor waste in physically organizing the shop floor. In Industry 4.0, feasibility checking becomes even more critical since emerging challenges, such as mass personalization, require reconfiguring work cells quickly and flexibly on demand. Regarding this need, digital twin technologies have emerged as an ideal candidate for practicing feasibility checking. Indeed, they are tools used to implement digital representations of manufacturing entities that can constitute a digital environment and context. Factory operators can test a manufacturing process within a digital environment in different contexts before the execution with physical resources. This approach currently receives significant attention from the manufacturing community; however, there is still a lack of sharing experiences to implement it. Thus, this paper contributes a methodology to engineer a digital environment and context for a manufacturing work cell using AAS digital twins and physics-based 3D digital twins technologies. Technically, this methodology is a specific case of N-DTs, a general methodology for engineering heterogeneous digital twins. The product assembly line case study, also presented in this paper, is a successful experiment applying the above contributions. The two methodologies and the case study can be helpful references for both public and private sectors to deploy their feasibility-checking frameworks and deal with heterogeneous digital twins in general. Full article
(This article belongs to the Special Issue Advances in Digital Twins for Manufacturing)
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25 pages, 818 KiB  
Article
The Anatomy of the Internet of Digital Twins: A Symbiosis of Agent and Digital Twin Paradigms Enhancing Resilience (Not Only) in Manufacturing Environments
by Joel Lehmann, Andreas Lober, Tim Häußermann, Alessa Rache, Lisa Ollinger, Hartwig Baumgärtel and Julian Reichwald
Machines 2023, 11(5), 504; https://doi.org/10.3390/machines11050504 - 22 Apr 2023
Cited by 7 | Viewed by 2652
Abstract
Due to the growing environmental and geopolitical challenges nowadays, which are causing supply chain complications, industry and society are facing significant new objections. As a complement and extension to the technology-driven premises of Industry 4.0, the value-driven Industry 5.0 focuses on society and [...] Read more.
Due to the growing environmental and geopolitical challenges nowadays, which are causing supply chain complications, industry and society are facing significant new objections. As a complement and extension to the technology-driven premises of Industry 4.0, the value-driven Industry 5.0 focuses on society and the environment. Human centricity, sustainability, and resilience should become a more integral part of both industrial and societal revolutions. One of the enabler technologies for both is the Digital Twin (DT). In order to make DTs intelligent, they must become active, online, goal-seeking, and anticipatory. To meet these requirements, the characteristics of Multi-Agent Systems (MASs) can be employed. This paper contributes to the bilateral emergence of the two industrial paradigms and establishes an approach for the provision of Intelligent Digital Twins (IDTs) within the Internet of Digital Twins (IoDT). Initially, a DT reference model aligned with already established Industry 4.0 reference models enriched with the goals of Industry 5.0 is developed, followed by an outline of how IDTs can be realized with the characteristics of MAS. The work is substantiated by an architectural design for IDTs choreographing marketplace-oriented production processes with a subsequent prototypical implementation, followed by a proof of concept. Full article
(This article belongs to the Special Issue Advances in Digital Twins for Manufacturing)
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18 pages, 42017 KiB  
Article
Implementing Digital Twins That Learn: AI and Simulation Are at the Core
by Bahar Biller and Stephan Biller
Machines 2023, 11(4), 425; https://doi.org/10.3390/machines11040425 - 27 Mar 2023
Cited by 11 | Viewed by 5434
Abstract
As companies are trying to build more resilient supply chains using digital twins created by smart manufacturing technologies, it is imperative that senior executives and technology providers understand the crucial role of process simulation and AI in quantifying the uncertainties of these complex [...] Read more.
As companies are trying to build more resilient supply chains using digital twins created by smart manufacturing technologies, it is imperative that senior executives and technology providers understand the crucial role of process simulation and AI in quantifying the uncertainties of these complex systems. The resulting digital twins enable users to replay history, gain predictive visibility into the future, and identify corrective actions to optimize future performance. In this article, we define process digital twins and their four foundational elements. We discuss how key digital twin functions and enabling AI and simulation technologies integrate to describe, predict, and optimize supply chains for Industry 4.0 implementations. Full article
(This article belongs to the Special Issue Advances in Digital Twins for Manufacturing)
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