Intelligent Digital Twins: Trends and Applications in the Human-Centered Manufacturing Context

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

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 15779

Special Issue Editors

Department of Mechanical, Energy and Management Engineering, University of Calabria, 87036 Rende, Italy
Interests: industry 4.0; supply chains and logistics; modeling and simulation; industrial engineering; digital transformation
Special Issues, Collections and Topics in MDPI journals
Department of Mechanical, Energy and Management Engineering, University of Calabria, 87036 Rende, Italy
Interests: Industry 4.0; simulation modeling; smart operators; sustainable production and logistics
Special Issues, Collections and Topics in MDPI journals
Associate Professor, Department of Mechanical, Energy and Management Engineering, University of Calabria, 87036 Rende, Italy
Interests: Industry 4.0; human-centered manufacturing; smart operators; simulation modeling; digital transformation
Associate Professor, Department of Mechanical, Energy and Management Engineering, University of Calabria, 87036 Rende, Italy
Interests: Industry 4.0; human-centered manufacturing; smart operators; simulation modeling; digital transformation

Special Issue Information

Dear Colleagues,

Within the vision of Industry 4.0, in the nearer future, complex problems due to planning, scheduling and control of production and logistic processes are derived by data-driven decisions that will enable manufacturing companies to accurately predict and plan their activities on the machine, the plant, as well as at the supply chain-level. In recent times, data-driven decision support based on Simulation, integrated Operations Research models, Advanced Data Analytics, Computational Intelligence, and AI are changing how modern manufacturing processes are planned and executed. The potential of such novel technologies is also being expanded by the interaction with smart sensors, the Internet of Things (IoT), cloud computing, and Cyber-Physical Systems (CPS), which made it possible to realize the “digital twin” (DT) of a product, system, and process. Despite the term, DT might be old and known to simulation experts, the growing searches and attention from worldwide companies (including consulting companies mentioning DT in the technological roadmaps for the current digital transformation) toward the DT concept arises new questions about how the theoretical soundness of the DT concept and how it can be implemented in practice. Despite many people may think that DTs are simulation models, a simulation model may not necessarily be a DT. Digital models used in simulations often have the same type of sensor information and controls as a DT, but the information may be generated and manipulated within the simulation in an offline fashion. The simulation may replicate what could happen in the real world, but not necessarily what is currently happening. If the digital model is fed with an automated one-way data flow between the physical and digital objects, e.g., a simulation model using real-time sensor data as inputs, this has been referred to as the digital shadow. In production and logistics, hybrid simulation (defined as models that combined at least two traditional simulation approaches, e.g., DES + ABS) is very popular to model complex enterprise-wide systems. Recently, other concepts, such as “Big Simulation”, were proposed as an evolution of currently distributed simulations to take big data input and produce big data output in near to real-time. The so-called Symbiotic Simulation has recently emerged as an interesting framework for integrating simulation with Digital Twin, IoT and Big Data. However, the concept is still in its infancy and requires considerations, for example, in terms of direct data collection from the sensors in a cyber-physical system or in terms of running constantly in the background to monitor and attempt to improve the performance of the system via simulation. The human factor is also poorly discussed when it comes to a representation in the digital twin of a manufacturing or production system. This is the ultimate maturity stage of Digital Twins, but still, the body of knowledge is limited and theoretical advances and practical solutions showing and discussing insights from real case studies are needed.

We invite authors to submit scientific papers that approach the aspects of integrating simulation, continuous/discrete optimization, human factors and decision support models based on simulation and distributed intelligence into the digital twin of manufacturing and logistics systems. Submissions involving case studies and innovative applications in the field of smart manufacturing and logistics systems are welcomed. Both empirical and conceptual, quantitative and qualitative original research studies are welcomed. Case studies and practical applications are encouraged. To that end, we seek submissions with an original perspective and advanced thinking on the development of the smart manufacturing and logistics field, instead of theoretical studies and frameworks on simulation-digital twin integration. Although they can contain some review of the literature, we look for submissions that go beyond systematic reviews and propose and discuss fresh conceptual and methodological avenues for further development of the field.

The topics of interest include, but are not limited to:

  • Definition of the role of simulation for digital twins in manufacturing and logistics
  • Digital twin maturity model for clear identification of simulation capabilities at each stage
  • Human factors and human digital twins
  • Real-time (or near real-time) execution of simulation models for digital twin implementation
  • Digital twin synchronization with the real manufacturing/logistics system counterpart
  • Data analytics integration
  • Digital twin for decision support in production and logistics
  • Distributed and Edge Intelligence
  • Mathematical optimization, heuristics and metaheuristics for simulation-based digital twins
  • Verification and validation of simulation models in digital twins
  • Integration of Simulation with Virtual, Mixed and Augmented Reality for Digital Twin Applications
  • Digital twin of stochastic production environments

Dr. Vittorio Solina
Dr. Antonio Padovano
Dr. Francesco Longo
Dr. Giovanni Mirabelli
Guest Editors

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Published Papers (8 papers)

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Research

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23 pages, 23985 KiB  
Article
Digital Twin Based on Historical Data and Simulation Results: Fault Detection and Estimation of the Remaining Useful Life of a Cyclone Bag Filter
Appl. Sci. 2023, 13(14), 8297; https://doi.org/10.3390/app13148297 - 18 Jul 2023
Cited by 2 | Viewed by 844
Abstract
This study deals with the development of a digital twin for monitoring the operating conditions of a cyclone bag filter installed on the suction system of a wheat mill. The model aims to be used for fault identification and real-time prediction of the [...] Read more.
This study deals with the development of a digital twin for monitoring the operating conditions of a cyclone bag filter installed on the suction system of a wheat mill. The model aims to be used for fault identification and real-time prediction of the remaining useful life (RUL). Computational fluid dynamics simulations were performed to characterize in detail the fluid-dynamic behavior of the airflow inside the system under different conditions of filter sleeve clogging. Furthermore, the simulation results were used to identify a location for the installation of a new velocity sensor that would allow, together with the pressure drop measured at the ends of the filter, monitoring of the systems’ conditions. A model able to assess the filter’s operating state, identify failure events or operating anomalies, and make a prediction of the RUL was then developed. A possible implementation of the developed model, based on the simulation results that aimed to optimize the management of the sleeve cleaning cycles was also proposed. The developed digital model was then tested on a working cycle lasting one year, in which a sleeve failure was simulated. It was shown how the simultaneous monitoring of the two identified quantities allows for the correct identification of the failure and the accurate prediction of the RUL. Full article
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22 pages, 2053 KiB  
Article
Using Intelligent Edge Devices for Predictive Maintenance on Injection Molds
Appl. Sci. 2023, 13(12), 7131; https://doi.org/10.3390/app13127131 - 14 Jun 2023
Viewed by 1083
Abstract
A considerable part of enterprises’ total expenses is dedicated to maintenance interventions. Predictive maintenance (PdM) has appeared as a solution to decrease these costs; however, the necessity of end-to-end solutions in deploying predictive models and the fact that these models are often difficult [...] Read more.
A considerable part of enterprises’ total expenses is dedicated to maintenance interventions. Predictive maintenance (PdM) has appeared as a solution to decrease these costs; however, the necessity of end-to-end solutions in deploying predictive models and the fact that these models are often difficult to interpret by maintenance practitioners hinder the adoption of PdM approaches. In this work, we propose a flexible architecture for PdM to recommend maintenance actions. The proposed architecture is based on containerized microservices on intelligent edge devices together with a hybrid model which fuses generalized fault trees (GFTs) and anomaly detection. Results on injection molds carried out at OLI, a Portuguese company, show that the proposed solution is suitable for deploying predictive models and services such as data preprocessing, sensor management, and data flow control, among others. These services run near the shop floor, allowing for greater flexibility, as they may be remotely managed and customized according to the company’s requirements. The results of the GFT model show an estimated reduction of more than 63% in current maintenance costs, while the distribution of analytics tasks by the edge devices reduces the burden on the network, requiring only 0.2% of the current cloud storage. Full article
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28 pages, 34047 KiB  
Article
Simulation Power vs. Immersive Capabilities: Enhanced Understanding and Interaction with Digital Twin of a Mechatronic System
Appl. Sci. 2023, 13(11), 6463; https://doi.org/10.3390/app13116463 - 25 May 2023
Cited by 2 | Viewed by 1181
Abstract
Automation Studio, a specialised simulation software, offers virtual commissioning capabilities and robust tools for modelling the behaviour and performance of a pneumatic robot controlled by a PLC. Conversely, Unity is a versatile platform primarily used for creating high-quality 3D games and interactive simulations, [...] Read more.
Automation Studio, a specialised simulation software, offers virtual commissioning capabilities and robust tools for modelling the behaviour and performance of a pneumatic robot controlled by a PLC. Conversely, Unity is a versatile platform primarily used for creating high-quality 3D games and interactive simulations, providing immersive experiences with DTs through mixed-reality environments. This paper provides a study that compares and contrasts the simulation power of Automation Studio and the immersive capabilities of Unity in the context of developing digital twins for a mechatronic system. This research explores how these complementary approaches enhance the development, validation, understanding, and interaction with digital twins. By examining both platforms in this context, the article provides valuable insights for engineers, developers, and researchers looking to create digital twins for mechatronic systems, but not only. This study demonstrates the potential of leveraging the combined power of simulation and immersive capabilities to improve the interaction between the real robotic arm manipulator cylindrical type and its digital twin in different scenarios, using an OPC approach for mirroring. The combination of Automation Studio and Unity provides a powerful platform for applied science education in the field of the digital twin of mechatronic systems. Full article
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22 pages, 20334 KiB  
Article
Design and Simulation Debugging of Automobile Connecting Rod Production Line Based on the Digital Twin
Appl. Sci. 2023, 13(8), 4919; https://doi.org/10.3390/app13084919 - 14 Apr 2023
Cited by 3 | Viewed by 1819
Abstract
The goal of ‘Industry 4.0’ is to promote the transformation of the manufacturing industry to intelligent manufacturing. Because of its characteristics, the digital twin perfectly meets the requirements of intelligent manufacturing. In this paper, through the signal and data of the S7-PLCSIM-Advanced Connecting [...] Read more.
The goal of ‘Industry 4.0’ is to promote the transformation of the manufacturing industry to intelligent manufacturing. Because of its characteristics, the digital twin perfectly meets the requirements of intelligent manufacturing. In this paper, through the signal and data of the S7-PLCSIM-Advanced Connecting TIA Portal and NX MCD, the conceptual design and simulation-based debugging of mechatronics in an automobile connecting rod production line based on a digital twin are realized. The main contents are as follows: Firstly, the data on the automobile connecting rod production line are collected. The data sources in this article are mainly MCD virtual sensors, CAD models, and factory processing history production data. Secondly, the modeling of connecting rod parts and the production line is carried out. The automobile connecting rod production line model is mainly divided into five areas: processing area, assembly area, cleaning area, inspection area, and inventory area. Thirdly, for the validation of the model, the simulation sequence is designed according to the actual processing data of the factory to ensure that it accurately represents the production line. Fourthly, control system design, mainly including the main program, reset program, sequence control system flow program, human-computer interaction, and so on. Fifthly, simulation and debugging through the debugging of the connecting rod in the process of transportation in the process of the sudden slipcase are analyzed. Sixthly, model deployment, through the specific analysis of the accumulation of workpieces to be processed between process 10 and process 11 to discuss the optimization of the production line. Seventhly, the model refinement, which explains the limitations of the research content and discusses future work. Finally, by comparing the traditional product debugging mode with the virtual simulation debugging mode of the automobile connecting rod production line based on digital twin, it is concluded that the virtual simulation debugging of the automobile connecting rod production line based on digital twin will greatly reduce the actual debugging time of the production line, thus speeding up the research and development progress and improving the industrial competitiveness. Full article
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26 pages, 8443 KiB  
Article
Enhancing Digital Twins of Semi-Automatic Production Lines by Digitizing Operator Skills
Appl. Sci. 2023, 13(3), 1637; https://doi.org/10.3390/app13031637 - 27 Jan 2023
Cited by 2 | Viewed by 1542
Abstract
In recent years, Industry 4.0 has provided many tools to replicate, monitor, and control physical systems. The purpose is to connect production assets to build cyber-physical systems that ensure the safety, quality, and efficiency of production processes. Particularly, the concept of digital twins [...] Read more.
In recent years, Industry 4.0 has provided many tools to replicate, monitor, and control physical systems. The purpose is to connect production assets to build cyber-physical systems that ensure the safety, quality, and efficiency of production processes. Particularly, the concept of digital twins has been introduced to create the virtual representation of physical systems where both elements are connected to exchange information. This general definition encompasses a series of major challenges for the developers of those functionalities. Among them is how to introduce the human perspective into the virtual replica. Therefore, this paper presents an approach for incorporating human factors in digital twins. This approach introduces a methodology to offer suggestions about employee rotations based on their previous performance during a shift. Afterward, this method is integrated into a digital twin to perform human performance assessments to manage workers’ jobs. Furthermore, the presented approach is mainly comprised of a human skills modelling engine and a human scheduling engine. Finally, for demonstrating the approach, a simulated serial single-product manufacturing assembly line has been introduced. Full article
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21 pages, 6811 KiB  
Article
Design-Manufacturing-Operation & Maintenance (O&M) Integration of Complex Product Based on Digital Twin
Appl. Sci. 2023, 13(2), 1052; https://doi.org/10.3390/app13021052 - 12 Jan 2023
Cited by 4 | Viewed by 2590
Abstract
This paper presents a complex product design-manufacturing-operations and maintenance integration method based on digital twin technology. This method aims to solve the problem of information silos in the design, manufacturing and operation and maintenance phases of complex products in the context of intelligent [...] Read more.
This paper presents a complex product design-manufacturing-operations and maintenance integration method based on digital twin technology. This method aims to solve the problem of information silos in the design, manufacturing and operation and maintenance phases of complex products in the context of intelligent manufacturing and to integrate the design, manufacturing and operation and maintenance processes of complex products. To address the integration needs of complex product design, manufacturing, operation and maintenance business integration, a framework for complex product design-manufacturing-operation and maintenance integration based on the digital twin is first proposed, in addition to designing a model and operation mechanism for combining the virtual and real of the digital twin model. Then, the implementation of multistage collaborative design technology, data intelligent sensing technology, and data integration and fusion technology for the digital twin-based design-manufacturing-operations and maintenance integration processes are analyzed and discussed. Finally, a case study involving the fault prediction of key components of the bogie of an EMU demonstrated the integrated mode of operation in the design-manufacture-operation and maintenance process of the EMU. It verified the effectiveness of the proposed framework, process and methodology. Full article
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Review

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21 pages, 2356 KiB  
Review
The Role of AI in Warehouse Digital Twins: Literature Review
Appl. Sci. 2023, 13(11), 6746; https://doi.org/10.3390/app13116746 - 01 Jun 2023
Cited by 2 | Viewed by 2976
Abstract
In the era of industry 5.0, digital twins (DTs) play an increasingly pivotal role in contemporary society. Despite the literature’s lack of a consistent definition, DTs have been applied to numerous areas as virtual replicas of physical objects, machines, or systems, particularly in [...] Read more.
In the era of industry 5.0, digital twins (DTs) play an increasingly pivotal role in contemporary society. Despite the literature’s lack of a consistent definition, DTs have been applied to numerous areas as virtual replicas of physical objects, machines, or systems, particularly in manufacturing, production, and operations. One of the major advantages of digital twins is their ability to supervise the system’s evolution and run simulations, making them connected and capable of supporting decision-making. Additionally, they are highly compatible with artificial intelligence (AI) as they can be mapped to all data types and intelligence associated with the physical system. Given their potential benefits, it is surprising that the utilization of DTs for warehouse management has been relatively neglected over the years, despite its importance in ensuring supply chain and production uptime. Effective warehouse management is crucial for ensuring supply chain and production continuity in both manufacturing and retail operations. It also involves uncertain material handling operations, making it challenging to control the activity. This paper aims to evaluate the synergies between AI and digital twins as state-of-the-art technologies and examines warehouse digital twins’ (WDT) use cases to assess the maturity of AI applications within WDT, including techniques, objectives, and challenges. We also identify inconsistencies and research gaps, which pave the way for future development and innovation. Ultimately, this research work’s findings can contribute to improving warehouse management, supply chain optimization, and operational efficiency in various industries. Full article
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20 pages, 2058 KiB  
Review
Human-Focused Digital Twin Applications for Occupational Safety and Health in Workplaces: A Brief Survey and Research Directions
Appl. Sci. 2023, 13(7), 4598; https://doi.org/10.3390/app13074598 - 05 Apr 2023
Cited by 4 | Viewed by 2220
Abstract
Occupational safety and health is among the most challenging issues in many industrial workplaces, in that various factors can cause occupational illness and injury. Robotics, automation, and other state-of-the-art technologies represent risks that can cause further injuries and accidents. However, the tools currently [...] Read more.
Occupational safety and health is among the most challenging issues in many industrial workplaces, in that various factors can cause occupational illness and injury. Robotics, automation, and other state-of-the-art technologies represent risks that can cause further injuries and accidents. However, the tools currently used to assess risks in workplaces require manual work and are highly subjective. These tools include checklists and work assessments conducted by experts. Modern Industry 4.0 technologies such as a digital twin, a computerized representation in the digital world of a physical asset in the real world, can be used to provide a safe and healthy work environment to human workers and can reduce occupational injuries and accidents. These digital twins should be designed to collect, process, and analyze data about human workers. The problem is that building a human-focused digital twin is quite challenging and requires the integration of various modern hardware and software components. This paper aims to provide a brief survey of recent research papers on digital twins, focusing on occupational safety and health applications, which is considered an emerging research area. The authors focus on enabling technologies for human data acquisition and human representation in a virtual environment, on data processing procedures, and on the objectives of such applications. Additionally, this paper discusses the limitations of existing studies and proposes future research directions. Full article
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