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With significant advancement in information technologies, Digital Twin has gained increasing attention as it offers an enabling tool to realise digitally-driven, cloud-enabled manufacturing. Given the nonlinear dynamics and uncertainty involved during the process of machinery degradation, proper design and adaptability of a Digital Twin model remai...
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... an evolving digital replica of a physical system, Digital Twin becomes a key enabling technology for cybernetic manufacturing as shown in Figure 1. Digital Twin not only can be used for modelling and simulation of system development to support design or to validate system properties ( Schleich et al. 2017;Tao et al. 2018) but also can support the operation and manufacturing service for optimised operations and failure prediction. ...
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... to the constructed Digital Twin rotor model in Section 4.2, the parameters of three unbalance faults of the rotor system can be identified by the modal expansion method as shown in Figure 10. The equivalent load increases with the increase of unbalance mass at the seventh node. ...
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... is a common fault in rotating machinery, and it has been widely investigated using signal processing techniques, such as spectrum analysis, and time-frequency analysis. The analysis results of the measured vibration signals using Fourier transform and wavelet transform are shown in Figure 11. It can be found that the amplitudes of spectrum energy at rotating speed are elevated under the different unbalance fault conditions. ...
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... an evolving digital replica of a physical system, Digital Twin becomes a key enabling technology for cybernetic manufacturing as shown in Figure 1. Digital Twin not only can be used for modelling and simulation of system development to support design or to validate system properties ( Schleich et al. 2017;Tao et al. 2018) but also can support the operation and manufacturing service for optimised operations and failure prediction. ...
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... to the constructed Digital Twin rotor model in Section 4.2, the parameters of three unbalance faults of the rotor system can be identified by the modal expansion method as shown in Figure 10. The equivalent load increases with the increase of unbalance mass at the seventh node. ...
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... is a common fault in rotating machinery, and it has been widely investigated using signal processing techniques, such as spectrum analysis, and time-frequency analysis. The analysis results of the measured vibration signals using Fourier transform and wavelet transform are shown in Figure 11. It can be found that the amplitudes of spectrum energy at rotating speed are elevated under the different unbalance fault conditions. ...
Citations
... Moreover, DT is an essential visual tool that uses real-time collected data to integrate physical space with cyberspace. Hence, on-site workers can better understand the current status of products and equipment performance and even insight the future performance of products in real-time [15]. An intelligent control model can be developed for optimal assembly by dynamically online adjusting the process parameters to meet the assembly quality. ...
High-quality aircraft assembly is critical in aircraft manufacturing. To meet increasing quality demands, the aircraft assembly process needs to be monitored in real time. In recent years, digital twins have attracted increasing interest in different applications. However, due to the heterogeneous data and multiple protocols in the assembly field, the large amount of data needs to satisfy high throughput, low latency, and low storage cost requirements without interrupting the assembly process, which introduces challenges to real-time monitoring systems. In this paper, a real-time monitoring system based on the digital twin that provides interactive services for users based on multisource, multidimensional data and sophisticated analyses is designed. Moreover, we introduce a time series database (TSDB) for dynamic data storage and SQLServer for static data storage. Time series data can be regarded as a standard type of organized data that is convenient for hierarchical representations and constructing multidimensional data cubes for information traceability. The storage cost is significantly reduced because the compression rate reaches 3.8%. Furthermore, the powerful and comprehensive analysis engine of the TSDB ensures that the monitoring system has real-time responses of less than 4 ms. In addition, a flexible and scalable system that collects multidimensional data without affecting the existing workflow is proposed. We perform various experiments to verify the feasibility and effectiveness of assembling large-scale aircraft components. This study provides a solid data foundation for accelerating the pace of intelligent aircraft manufacturing.
... In Stage 3, cloud computing is discussed, followed by Stage 4, which addresses the utilization of software for data monitoring. Stage 5 pertains to the implementation of a dashboard for visual management, and finally, Stage 6 Sensors applied for predictive maintenance [5]; [12]; [26]; [25]; [27]; [6]; [23]; [28]; [29]; [14]; [30]; [31]; [32]; [33]; [34]; [35]; [36]; [37]; [38]; [19]; [39]; [40]; [41]; [2]; [42]; [43]; [44]; [9]; [45]; [46]; [47]; [48]; [49]; [1]; [50]; [51]; [52]; [53]; [54]; [55] 2 Interface between equipment and the cloud Identify communication device between sensor and cloud Processors, gateways, and communication devices that can be employed [12]; [27]; [29]*; [14]; [30]; [56]*; [57]; [33]*; [33]*; [24]; [38]*; [58]; [22]; [59]; [3]; [60]; [61]*; [19]; [39]; [62]*; [42]; [9]*; [45]; [63]*; [48]; [49]; [50]; [52]; [55]; [64].(*has no interface with the cloud but integration with local software) ...
... In Stage 3, cloud computing is discussed, followed by Stage 4, which addresses the utilization of software for data monitoring. Stage 5 pertains to the implementation of a dashboard for visual management, and finally, Stage 6 Sensors applied for predictive maintenance [5]; [12]; [26]; [25]; [27]; [6]; [23]; [28]; [29]; [14]; [30]; [31]; [32]; [33]; [34]; [35]; [36]; [37]; [38]; [19]; [39]; [40]; [41]; [2]; [42]; [43]; [44]; [9]; [45]; [46]; [47]; [48]; [49]; [1]; [50]; [51]; [52]; [53]; [54]; [55] 2 Interface between equipment and the cloud Identify communication device between sensor and cloud Processors, gateways, and communication devices that can be employed [12]; [27]; [29]*; [14]; [30]; [56]*; [57]; [33]*; [33]*; [24]; [38]*; [58]; [22]; [59]; [3]; [60]; [61]*; [19]; [39]; [62]*; [42]; [9]*; [45]; [63]*; [48]; [49]; [50]; [52]; [55]; [64].(*has no interface with the cloud but integration with local software) ...
... Cloud environments similar to those reported by the authors [12]; [65]; [27]; [6]; [14]; [30]; [57]; [66]; [67]; [24]; [36]; [58]; [3]; [60]; [61]; [19]; [68]; [2]; [42]; [45]; [49]; [1]; [50]; [52]; [69]; [54]; [55]; [64] 4 Software manual Define the software for monitoring the data collected by the sensors Compatible vibration analysis software [31]; [57]; [32]; [34]; [70]; [40]; [24]; [36]; [60]; [71]; [42]; [9]; [45]; [46]; [55] 5 Dashboard for visual management Define the model for presenting the results of the measurement process Web environment with remote access to the results dashboard [12]; [65]; [23]; [24]; [60]; [61]; [69]; [55] 6 End user integration Define how the end user will access the data Remote access to web diagnostics [12]; [65]; [23]; [14]; [30]; [34]; [24]; [36]; [58]; [60]; [19]; [72]; [71]; [62]; [45]; [73]; [1]; [50]; [69]; [64] is responsible for the integration with the end user, outlining how the maintenance team can access the collected data. ...
With the advancement of production processes in recent decades, machine tools have undergone significant evolution. Today, we witness the emergence of new technological developments, such as Internet of Things (IoT) systems, which have become crucial competitive advantages across various industries, including the manufacturing sector. Predicting machine failures in advance is essential for maximizing company performance and minimizing operational costs. In line with this objective, the present research aimed to develop an IoT system for the online management of machine tool spindles in operation, providing reliable data for maintenance management within the context of Industry 4.0 (I4.0). The system was developed using the design science research (DSR) methodology. The implementation and validation of the IoT system were demonstrated through a case study conducted in the automotive industry, utilizing participant observation. The main contributions of this research include the development and validation of the IoT system, as well as the associated predictive maintenance method. The IoT system showcases the normal behavior of spindles during operation, contributing to both academic knowledge and practical applications in the industry. It advances our understanding and helps prevent catastrophic failures in machine tools.
... This kind of model focuses on production efficiency improvement and basically does not involve the accuracy and performance of the manufactured product itself. The product digital twin studied by some scholars (Tong et al., 2020;Wang et al., 2019;Zheng & Sivabalan, 2020) were based on an ideal geometric model. Such models are sufficient to simulate and optimize macroscopic processes but cannot characterize the changes in accuracy and performance caused by structural microscopic form and properties. ...
... Current product digital twin studies were arguably all based on ideal design models. The virtual models of the 3D printer digital twin (Zheng & Sivabalan, 2020), intelligent machine tool digital twin (Tong et al., 2020), and rotar system digital twin (Wang et al., 2019) were all constructed based on ideal models. These models simulate macroscopic behaviors or features of physical products to improve the process. ...
Digital twin, a core technology for intelligent manufacturing, has gained extensive research interest. The current research was mainly focused on digital twin based on design models representing ideal geometric features and behaviors at macroscopic scales, which is challenging to accurately represent accuracy and performance. However, a numerical representation is essential for precision microstructures whose accuracy and performance are difficult to measure. The concept of a digital twin for an accurate representation, proposed in 2015, is still in the conceptual stage without a clear construction method. Therefore, the goal of accurate representation has not been achieved. This paper defines the concept and connotation of an accuracy and performance-oriented accurate digital twin model and establishes its architecture in two levels: geometric and physical. First, a geometric digital twin model is constructed by the contact surfaces distributed error modeling and virtual assembly with nonuniform contact states. Then, based on this, a physical digital twin model is constructed by considering the linear and nonlinear response of the structural internal physical properties to the external environment and time to characterize the accuracy and performance variation. Finally, the models are evaluated. The method is validated on microtarget assembly. The estimated values of surface modeling, center offset, and stress prediction accuracy are 94.22%, 89.3%, and 83.27%. This paper provides a modeling methodology for the digital twin research to accurately represent accuracy and performance, which is critical for product quality improvements in intelligent manufacturing. Research results can be extended to larger-scale precision structures for performance prediction and optimization.
... Despite these challenges, the benefits of using a digital twin of a magnetic bearing system are clear. By providing real-time insights into the system's performance, the digital twin can help identify vibration for imbalance mass potential problems before they occur and optimize the control algorithms to improve performance and reduce energy consumption [24,25]. Additionally, the digital twin can simulate different operating conditions and test different control strategies, providing valuable information for designing and developing new magnetic bearing systems [26]. ...
... Substituting Equation (25) into Equation (24) to find the equation of rotor dynamic results in ...
As an essential enabling technology to realize advanced concepts such as digitization, intelligence, and service, information technology plays a critical role in shaping modern society and driving innovation across various industries and domains. The concept of the digital twin is attracting attention from academics and industry, and how to apply it in various fields. In this paper, the performance of the magnetic bearing system may be simulated in real-time using a digital twin, especially the resulting vibration from the unbalanced rotor mass, which caused a drop in performance and a high risk of system instability and potential safety accidents. It is suggested to use a model-data combination driven digital twin model to examine its dynamic characteristics and vibration mechanism. The vibration data of the magnetic bearing was collected through experiments and compared with the data derived from the simulation results. The efficiency of the suggested strategy is demonstrated by confirming that digitally anticipated vibration signals are consistent with physical space measurements. The result shows that the fine digital twin geometric model of magnetic bearing is more consistent with the actual operation. By allowing the identification of problems before they become critical, using a digital twin may increase the dependability of magnetic bearings while reducing the possibility of unexpected downtime or failures.
... Fault-Detection [42,[92][93][94] DT-based fault diagnostic methods for Distributed PV systems, rotating machinery and power converters have been studied. ...
The concept of the digital twin has been adopted as an important aspect in digital transformation of power systems. Although the notion of the digital twin is not new, its adoption into the energy sector has been recent and has targeted increased operational efficiency. This paper is focused on addressing an important gap in the research literature reviewing the state of the art in utilization of digital twin technology in microgrids, an important component of power systems. A microgrid is a local power network that acts as a dependable island within bigger regional and national electricity networks, providing power without interruption even when the main grid is down. Microgrids are essential components of smart cities that are both resilient and sustainable, providing smart cities the opportunity to develop sustainable energy delivery systems. Due to the complexity of design, development and maintenance of a microgrid, an efficient simulation model with ability to handle the complexity and spatio-temporal nature is important. The digital twin technologies have the potential to address the above-mentioned requirements, providing an exact virtual model of the physical entity of the power system. The paper reviews the application of digital twins in a microgrid at electrical points where the microgrid connects or disconnects from the main distribution grid, that is, points of common coupling. Furthermore, potential applications of the digital twin in microgrids for better control, security and resilient operation and challenges faced are also discussed.
... Industrial pioneers and academic communities have explored the applications in various scenarios, covering the critical manufacturing life cycle from design, manufacturing, operation, and maintenance (PTC, 2022). The above-mentioned applications of DT in the manufacturing industry mainly include (1) product design (Lim et al., 2020a(Lim et al., , 2020bTao et al., 2019aTao et al., , 2019b, (2) production management and control (Zhuang et al., 2018;Zheng et al., 2019;Yi et al., 2021), (3) manufacturing system design (Liu et al., 2019c), (4) system fault diagnosis (Saraeian & Shirazi, 2022;Wang et al., 2019), (5) system risk prevention (Bevilacqua et al., 2020), (6) production data management (Park et al., 2020a), (7) manufacturing system management , etc., as shown in Table 3. ...
The development of advanced information technologies are paving the digital transformation of manufacturing systems, of which Digital Twin-based manufacturing system (DTMS) has become a prevailing topic attracted ever-increasing concerns from both industry and academia. As a cutting-edge smart manufacturing system, DTMS can improve manufacturing accuracy and efficiency based on high fidelity simulation, near real-time monitoring and control in a cyber-physical integrated manner. However, the connotation and boundary of DTMS lack a clear definition and systematic analysis. Therefore, this paper reviews the existing Digital Twin reference models and implementation architectures on manufacturing system, and further proposes a reference model of DTMS. Based on it, the characteristics and operational mechanism of DTMS are analyzed from three perspectives: hierarchy, dimension, and scale. Specifically, the composition of DTMS is described from a multi-level perspective, the specific characteristics of the DTMS are analyzed from a multi-dimensional perspective, and the temporal and spatial characteristics of the DTMS under different application scenarios are depicted from a multi-scale perspective, respectively. At last, the potential research directions of DTMS are highlighted in terms of reusability, interpretability and adaptability. It is envisioned that this work can provide a clear understanding with insightful knowledge to attract more in-depth research of DTMS.
... A big advantage of this upgraded digital twin design is the potential to give much more than just a perfect duplicate in order to provide value-added services on top of digital twins which are not accessible on physical assets [30] . Fig. 2 depicts the architecture of the Digital Twin for digital production [31] . ...
... Because for digital twins to be effective, they must accurately mirror the condition of real devices. Privacy and security of data is also another challenge of part manufacturing modification using [31] . digital twin. ...
... Digital twins can be used in industrial manufacturing to ensure consistency during mass production [94] . Fig. 4 illustrates a digital twin mapping strategy through model update and optimization procedure [31] . ...
A virtual representation of a physical procedure or product is called digital twin which can enhance efficiency and reduce costs in manufacturing process. Utilizing the digital twin, production teams can examine various data sources and reduce the number of defective items to enhance production efficiency and decrease industrial downtime. Digital Twin can be utilized to visualize the asset, track changes, understand and optimize asset performance throughout the analysis of the product lifecycle. Also, the collected data from digital twin can provide the complete lifecycle of products and processes to optimize workflows of part production, manage supply chain, and manage product quality. The application of digital twin in smart manufacturing can reduce time to market by designing and evaluating the manufacturing processes in virtual environments before manufacture. Comprehensive simulation platforms can be presented using digital twins to simulate and evaluate product performances in terms of analysis and modification of produced parts. Commissioning time of a factory can also be significantly reduced by developing and optimising the factory layout using the digital twin. Also, the productivity of part manufacturing can be enhanced by providing the predictive maintenance and data-driven root-cause analysis during part production process. In this paper, application of digital twin in smart manufacturing systems is reviewed to analyze and discuss the advantages and challenges of part production modification using the digital twin. So, the research field can advance by reading and evaluating previous papers in order to propose fresh concepts and approaches by using digital twins in smart manufacturing systems. A digital twin is a virtual representation of a physical system or process that allows for real-time monitoring, analysis, and optimization. In the context of smart manufacturing, a digital twin can be used to simulate and optimize the production process, predict and prevent equipment failures, and improve efficiency and quality of part production [1, 2]. The digital twin can provide a detailed, accurate representation of the physical object or system, including its behavior, performance, and interactions with the environment [3]. Digital twins use machine learning, data analytics, and multi-physics simulation in order simulate and analyze different working conditions and other factors affect a system [4]. The creation of the digital twin is a critical component of future technology that will have an impact on several global sectors [5]. By analyzing data from the physical object, the Digital Twin can provide real-time feedback, monitor its performance, and identify potential issues before they occur [6]. A digital twin can be used in order to optimize the operation of a physical system, by simulating its behavior and identifying areas where improvements can be made. [7]. Furthermore, companies can utilize digital twins to model, anticipate, and improve products and manufacturing processes in different industries, including automotive, green energy, and aviation before organizations invest in actual prototypes and assets, [8]. As a result, digital twins can help businesses and manufacturing process in order to make better decisions, reduce costs, and improve performance across a range of industries and applications.
... physical workshop environment, used product quality, and design constraints. Digital twin (DT), acting as a mirror of the real world, provides a means of simulating, predicting, and optimizing manufacturing system and process [13] and has been widely used in various fields, such as product assembly [14,15], 3D printing [16], fault diagnosis [17], and remanufacturing paradigm [18]. As a key to two-way mapping, dynamic interaction, and real-time connection between virtual and real environments, DT can map the attributes, structure, state, performance, function, and behavior of physical entities to the virtual world [19]. ...
Remanufacturing used products is an important technological approach in sustainable
development and circular economy. Meanwhile, redesign is the key component of remanufacturing,
as it can innovate the function and structure of used products. However, due to the uncertain quality,
variety, and small batches of the returned used products for remanufacturing, it is difficult to generate
a sound redesign scheme to satisfy the customer demand quickly and dynamically. In addition, it is
unpredictable whether the redesign scheme is suitable for the remanufacturing processes, which may
lead to additional remanufacturing costs. In order to improve the efficiency of design and obtain the
optimal design scheme, it is necessary to use intelligent technology to quickly generate and optimize
the redesign scheme. To address this, an intelligent redesign method for used products based on the
digital twin is proposed in this paper. Digital twin (DT) technology can connect the physical world
with the virtual world and use the virtual model to simulate the redesign process, which is conducive
to the dynamic adjustment and optimization of the redesign scheme. Firstly, the redesign process
framework is constructed based on the axiomatic design (AD) method, and the redesign features of
the used products are analyzed to determine the redesign problems. Then, based on the connotation
of a digital twin, an intelligent redesign framework is constructed, which provides detailed guidance
for building the digital-twin-driven redesign system. Henceforth, the application of the redesign
process based on a digital twin is discussed, a technical approach of the digital-twin-driven redesign
is proposed, and data processing methods, such as data cleaning, data integration, and data analysis,
are used to realize the redesign scheme decision. Finally, the feasibility of this method is verified by
the redesign of a used clutch.
... The deep learning system may simply identify the malfunction in the system by observing the weakening of the actual part and making a comparison with its normal behavior. Digital Twins are used to creating a defect diagnosis for an electrical machine, which is proposed in [20]. A modified DT with the Industrial IOT system is introduced in [24] to improve the vision for smart production. ...
... Due to the enormous amount of data, it must be a combination of DT with other techniques such as analysis methods, Big data procedures, and data fusion algorithms to deal with it that gives precise, meaningful data [6]. • A fault diagnosis and fault prognosis use digital traces [20]. Both gathered data and feature extraction are combined to verify the location of the fault and apply this Information Real Virtual Data Fig. 1 Model of digital twins diagnosis to enhance the system's design so that the same error and trouble will arise less in the future. ...
... It describes the structure of subsystems, subassemblies, and modules and creates a simulated version of every component with the gained receiving measurements from production, actions, and operation. To improve the product's reliability, Fig. 2 Vision of digital twins in PLM a replica of the sensors can be introduced inside the digital part of the system [20]. Also, the digital simulation could be a mirror image of the physical items by detecting and classifying the key element of actual items. ...
In recent years, there have been concentrations on the Digital Twin from researchers and companies due to its advancement in IT, communication systems, Cloud Computing, Internet-of-Things (IoT), and Blockchain. The main concept of the DT is to provide a comprehensive tangible, and operational explanation of any element, asset, or system. However, it is an extremely dynamic taxonomy developing in complication during the life cycle that produces an enormous quantity of the engendered data and information from them. Likewise, with the development of the Blockchain, the digital twins have the potential to redefine and could be a key strategy to support the IoT-based digital twin’s applications for transferring data and value onto the Internet with full transparency besides promising accessibility, trusted traceability, and immutability of transactions. Therefore, the integration of digital twins with the IoT and blockchain technologies has the potential to revolutionize various industries by providing enhanced security, transparency, and data integrity. Thus, this work presents a survey on the innovative theme of digital twins with the integration of Blockchain for various applications. Also, provides challenges and future research directions on this subject. In addition, in this paper, we propose a concept and architecture for integrating digital twins with IoT-based blockchain archives, which allows for real-time monitoring and control of physical assets and processes in a secure and decentralized manner. We also discuss the challenges and limitations of this integration, including issues related to data privacy, scalability, and interoperability. Finally, we provide insights into the future scope of this technology and discuss potential research directions for further improving the integration of digital twins with IoT-based blockchain archives. Overall, this paper provides a comprehensive overview of the potential benefits and challenges of integrating digital twins with IoT-based blockchain and lays the foundation for future research in this area.
... Some studies have been performed to address this concern. Wang et al. designed a digital twins fault prediction model for rotating machinery, aiming to evaluate its effectiveness in quantifying and localizing unbalance [13]. Jain et al. proposed a digital twin-based framework for detecting faults in photo voltaic systems, which involves real-time estimation of measurable characteristic outputs from the photovoltaic energy conversion unit [14]. ...
