Implementation Of Digital Twin Research Articles

Integrating production and maintenance planning in process industries using Digital Twin: A literature review

Among the Industry 4.0 technologies transforming manufacturing environments, the Digital Twin (DT) technology is gaining attention as a driver for improving manufacturing performance and a platform to enhance collaboration. While the advantages of leveraging DT for supporting decision-making in production planning and maintenance planning are recognized, research taking an integrated perspective is scarce. In addition, besides the growing trend, recent studies highlight the limited adoption of DTs in process industries, emphasizing the necessity to address the unique features of their production processes. Through a literature review, this paper points out the main obstacles encountered during the implementation of DT in process manufacturing industries, as well as shows the research gap in exploiting DT to support the integration of decisions concerning production and maintenance and underscores the need for further investigation in this direction to discover its full potential.

Exploring Digital Twin Dynamics: An Analysis of Structure Configurations

Digital twin (DT) is an important technology to support the realization of the digital transformation, connecting the physical asset to its virtual copy and fostering realtime monitoring, simulation, and decision-support. However, the benefits of DT depend on its intended purpose and application, which is impacted by the design structure configuration that is used for its implementation. This paper discusses the advantages and challenges of considering different organizational structures for the implementation of DTs, namely centralised, hierarchical and decentralised, complemented with a case study that was used to analyse the implementation of DT focusing on centralised and decentralised approaches. Additionally, the paper includes an analysis of the main aspects of DT structures and their design guidelines, the key enabling technologies and the main challenges of distributing DTs.

Digital Twins Technology for Smart City Development. A Case Study of Poland’s Largest Cities

Smart city development aims to build urban areas providing a high quality of life through modern infrastructure. Local governments have different strategic priorities. In particular, they focus on socio-economic capabilities, technological benefits, and sustainability goals. These areas are interrelated through spatial, time, and infrastructural dependencies. Intelligent city management could benefit from the simulation and visualization of these relationships. A digital twin is a solution that can oversee the complexity of city infrastructure spanning multiple locations, IoT devices, and data from other systems. The essence of digital twins is a bi-directional mapping of the relationship between physical and virtual space. The article aims to identify the state of knowledge about digital twins among local governments and the areas and possibilities using this technology to support city management. To achieve these goals, the authors conducted a research procedure covering the following stages: (1) identifying the directions of application of digital twins in smart cities based on the literature; (2) Conducting interviews with local governments representatives of the ten largest cities in Poland; (3) Expert assessment of potential application areas of digital twins, taking into account the needs, existing infrastructure, and information resources. The paper’s contribution is recognizing the areas in city management that can benefit from digital twin implementation.

Digital twin architecture for assembly line performance monitoring

The forthcoming industrial requirements to ensure increasingly flexible and agile production processes will require an ever-increasing ability to recognise, predict and optimise the state of processes with respect to the planned state. Advanced tools such as Digital Twins (DT) and Cyber Physical Systems (CPS) can help manage and address these problems. This paper presents some results of the authors’ research on the adoption of a basic methodology for the design and implementation of Digital Twins aimed at manufacturing applications and subsequent integration into a Cyber Physical Production Systems (CPPS). Reference publications were selected based on the level of detail of DT and CPS architectures. The aim is also to combine methodological development with industrial tools and requirements. The architecture is potentially applicable to different production scenarios. Finally, the first results of application on a scale production line are shown.

Digital Twin in Fluid Power: Review- Technology Trends

The Digital Twin (DT) is the most modern technology in Industry 4.0, which combines digital and physical components, accurate visualization, and multifaceted perception to represent the digital-physical world in real-time. The use of simulation, monitoring, optimized performance, and projection are crucial and increasingly popular, particularly in the field of industrial automation. Fluid Power Application (FPA) is an essential industrial automation technology that offers accurate monitoring, immense power, flexibility, reliability, cost-effectiveness, and seamless compatibility with pre-existing automated systems through the utilization of hydraulic and pneumatic power. Nevertheless, certain technological elements and emergent DT technology in fluid power systems have not been extensively explored. Based on the conception and constituents addressed in a companion review paper (1), this paper looks into various technologies that allow the seamless integration of both physical and digital representations in diversified FPAs. This article intends to thoroughly examine the crucial role of technological enablers in the successful implementation of digital twin. The paper provides an in-depth review of the technological enablers that support DT, specifically focusing on software used for the simulation of FPA and programmable logic controllers (PLCs) with the accompanying software. This review paper enhances the academic discourse by emphasizing different emerging technologies and acts as a catalyst for DT in current investigation efforts and breakthroughs in FPAs.

Developing an integrative framework for digital twin applications in the building construction industry: A systematic literature review

In response to the global advocacy for digitalization, numerous industrial sectors are actively advancing the implementation of digital twins (DTs). However, the construction industry has been slow to adopt DT, lagging behind sectors such as manufacturing and medicine, where digitalization has made significant strides. Given the demonstrated benefits and potential of DT, it is crucial to increase research efforts for enhancing its application in the construction industry. To accurately identify prospective areas for future research, a comprehensive review and analysis of the status quo of relevant research is urgently needed. This study undertook a systematic literature review to understand how DT can enhance operational intelligence in the building construction industry. The findings, based on a review of pertinent literature, revealed that existing studies predominantly focused on the application of DT during the construction phase and the operation and maintenance phase. However, its potential use during the planning and design phase and the demolition and recovery phase was largely overlooked. Three main categories of key digital facilitating technologies for DT in the building construction industry have been identified: (1) data-related technologies; (2) high-fidelity modeling technologies; and (3) model-based simulation technologies. These technologies have finally culminated into an integrative framework. Furthermore, three significant research gaps in the application of DT in the building construction industry have been identified, suggesting future studies explore how to (1) centralize diverse stakeholders from a lifecycle perspective; (2) address various existing technological defects; and (3) establish a universal industry standard. This paper provides a valuable roadmap for relevant stakeholders to understand the status quo of DT application and the existing deficiencies in its full implementation, which should facilitate the efficient digitalization of the construction industry.

A Digital Twin and Data Spaces framework towards Resilient Manufacturing Value Chains

Due to the fact that uncertainties and disruptions are increasing because of the complexity of the supply chains, resilience has become a very important and imperative aspect for modern manufacturing industries. The ability to overcome challenging circumstances without significant additional costs is referred to as resilience. Digital technologies are considered as key enablers for manufacturers to achieve resilience in their manufacturing systems either in shopfloor or in value chain level. This work presents the framework of an information system for implementing Resilient Manufacturing value chains. The objective is to achieve resilience by applying the framework which leverages on data space technology, such as Gaia-X or International Data Space (IDS), and the Asset Administration Shell (AAS), where AAS supports the implementation of Digital Twins. Moreover, this work discusses the integration, within the proposed architecture, of two services namely Resilience Assessment and Reconfiguration Services. The architecture is validated in an industrial production environment from the steel industry. Finally, a discussion on existing challenges, limitations and future potentials takes place.

Integrating multiscale data for digital twin-enhanced manufacturing systems: A conceptual and case demonstration

This paper explores the integration of data within digital twin-driven multiscale manufacturing systems, examining the core characteristics of data flows in digital twin (DT) environments tailored to manufacturing. In DT frameworks, data are inherently bidirectional, automated, and real-time, which are critical for maintaining the operational integrity of interconnected manufacturing subsystems. Different scales (from machine tool focus to supply chains) and timelines (from operations events to long term planning) make manufacturing system operation complex. This in turn means data integration across these scales and timelines is inherently complex. This study focuses on the dynamics of data flows in DT-driven manufacturing systems that support both forward and backward communication across DT modules and the central DT platform. The overall DT data scheme manages the supervision and cataloging of actions, which includes technical data related to machinery, processes, resources, and rules, alongside performance metrics across various scales and levels over time. A case study of a DT-driven manufacturing unit illustrates the data flow and interdependency in DT data framework. It highlights how data integration across multiple manufacturing stages can improve operational efficiency, fault diagnosis, and resource optimisation. This study lays the groundwork for the implementation of DT in complex, multiscale manufacturing systems by providing an extendible structured framework.

Challenges Faced During Implementation of Digital Twin in Construction Project Monitoring

Digital Twins (DTs) are gaining popularity because they provide precise digital copies of assets, processes, and systems. This is especially true when these DTs are paired with real-time simulation models that make use of modern technologies like machine learning, artificial intelligence, and data analytics. These combinations can provide a comprehensive and dynamic view of the monitored systems. Digital twin (DT) has shown tremendous potential to bring about revolutionary improvements in the field of construction site surveillance. There is, however, a notable paucity of empirical research identifying the constant elements affecting DT adoption in this industry. This research tries to fill that void by identifying the important elements that determine the usage of DT in construction. The study adopts a complete framework with the goal of increasing the use of DT in building site monitoring. The elements influencing the adoption and effectiveness of distributed ledger technology (DT) are divided into three categories: technological, organizational, and economic. Technological factors include the system's appropriateness and the robustness of the data infrastructure. Organizational considerations include the company's openness to innovation and leadership support. Economic aspects include things like return on investment (ROI) and cost-effectiveness. The research technique combines case studies and literature reviews to examine the benefits and drawbacks of DT in construction monitoring. This study's expected output is a comprehensive framework that aids construction businesses in optimizing the use of DT in site monitoring. This would allow for more efficient, data-driven, and forward-thinking processes. The study's ultimate purpose is to provide critical knowledge that will assist the building sector in adopting cutting-edge methods. The industry may better plan for the integration of this sophisticated technology into their operations by knowing the potential of DT and the variables driving its adoption. This, in turn, can lead to more efficiency, lower risks, and improved overall performance

Malzeme Mühendisliğinde Gelişmiş Malzeme Davranışı Tahmini ve Üretim Süreci Optimizasyonu için Dijital İkizler ve Uygulamaları

The advent of Industry 4.0 and the digital revolution have brought forth innovative technologies such as digital twins, which have the potential to redefine the landscape of materials engineering. Digital twins, virtual representations of physical entities, can model and predict material behavior, enabling enhanced design, testing, and manufacturing of materials. However, the comprehensive utilization of digital twins for predictive analysis and process optimization in materials engineering remains largely uncharted. This research intends to delve into this intriguing intersection, investigating the capabilities of digital twins in predicting material behavior and optimizing manufacturing processes, thereby contributing to the evolution of advanced materials manufacturing. Our study will commence with a detailed exploration of the concept of digital twins and their specific applications in materials engineering, emphasizing their ability to simulate intricate material behaviors and processes in a virtual environment. Subsequently, we will focus on exploiting digital twins for predicting diverse material behaviors such as mechanical properties, failure modes, and phase transformations, demonstrating how digital twins can utilize a combination of historical data, real-time monitoring, and sophisticated algorithms to predict outcomes accurately. Furthermore, we will delve into the role of digital twins in optimizing materials manufacturing processes, including casting, machining, and additive manufacturing, illustrating how digital twins can model these processes, identify potential issues, and suggest optimal parameters. We will present detailed case studies to provide practical insights into the implementation of digital twins in materials engineering, including the advantages and challenges. The final segment of our research will address the current challenges in implementing digital twins, such as data quality, model validation, and computational demands, proposing potential solutions and outlining future directions. This research aims to underline the transformative potential of digital twins in materials engineering, thereby paving the way for more efficient, sustainable, and intelligent material design and manufacturing processes.

Investigating the relationship between Lean Six Sigma performance strategy with digital twin modeling: Practices and factors

This work examines the relationship between Lean Six Sigma performance strategy (LSS) and Digital Twin (DT) modeling approaches. This investigation involved the practices and factors in successfully implementing DT in the LSS system and how they can be synergistically integrated to improve the performance and quality of the production and service system. We followed a mixed-methods approach, combining qualitative and quantitative methodologies, which begins with an extensive literature review to establish a theoretical foundation & identify key concepts. The qualitative component involves in-depth interviews with experts the responses evaluated through ISM-MICMAC-DEMATEL analysis with Python programming. The findings are three folds; first, we explored the enablers of DT and LSS approaches and provided a comprehensive analysis on literature. Secondly, we prioritized the DT enablers for LSS practitioners by providing prominence casual values. It suggests that, among the identified enablers, real-time simulation was the most significant reason for DT implementation in LSS practices, followed by edge computing and Interoperability Standards. Additionally, results will help policymakers to faster DT implementation, ensuring LSS practices. This study explored the fact of limited attention on DTs-LSS in previous studies. Finally, empirical evidence and practical insights have promising aspects for performance enhancement including implications for the sustainable development goals (SDGs).

A comprehensive digital twin framework for building environment monitoring with emphasis on real-time data connectivity and predictability

The concept of digital twins, initially developed in manufacturing, has found applications in various industries. However, its adoption in the construction field is still nascent, with a limited understanding of its benefits and implications. Existing examples of digital twin implementation in construction mainly provide general frameworks or possibilities for performance. To effectively harness the potential of digital twins in construction, establishing connectivity and predictability for data exchange between the physical and virtual realms is crucial. This research defines the essential requirements for real-time connectivity and predictability in digital twin implementation and proposes a framework and architecture based on these principles. The proposed method is evaluated through the implementation of a digital twin for monitoring the environmental performance of existing buildings, revealing its effectiveness and challenges. This study serves as a valuable exemplar for the development of a digital twin platform dedicated to construction monitoring.

Digital-Twin-Based Fire Safety Management Framework for Smart Buildings

In recent years, the implementation of digital twin (DT) technology has gained significant attention in various industries. However, the fire safety management (FSM) sector has been relatively slow in adopting this technology compared to other major industries. Therefore, this study aims to explore the limitations, opportunities, and challenges associated with adopting DT technology in the FSM sector and further develop a DT-based FSM framework towards smart facility management (FM). To achieve this objective, this research started by reviewing several promising DTs for FSM, including building information modeling (BIM), the Internet of Things (IoT), artificial intelligence (AI), and augmented reality (AR). On this basis, a conceptual framework was synthesized in consideration of the benefits of each technology. A questionnaire was conducted for FM professionals to evaluate the proposed framework and identify the challenges of adopting DT in the FSM sector. The survey results reveal that the proposed framework can assist decision makers in obtaining comprehensive information about facilities’ communication among stakeholders. The survey results validate the potential of the adoption of DTs toward smart FM practices in FSM. The survey results provide insights into the perception of DT technology among FM practitioners and identify the current state of DT technology in the FSM sector, its expected benefits, and its potential challenges. The main barriers to adopting DTs in FSM are a lack of knowledge about DTs, their initial costs, user acceptance, difficulties in systems integration, education training costs, a lack of competence, development complexity, difficulties in data management, and a lack of trust in data security.

A Literature Review on the Development and Creation of Digital Twins, Cyber-Physical Systems, and Product-Service Systems.

Digital Twins offer vast potential, yet many companies, particularly small and medium-sized enterprises, hesitate to implement them. This hesitation stems partly from the challenges posed by the interdisciplinary nature of creating Digital Twins. To address these challenges, this paper explores systematic approaches for the development and creation of Digital Twins, drawing on relevant methods and approaches presented in the literature. Conducting a systematic literature review, we delve into the development of Digital Twins while also considering analogous concepts, such as Cyber-Physical Systems and Product-Service Systems. The compiled literature is categorised into three main sections: holistic approaches, architecture, and models. Each category encompasses various subcategories, all of which are detailed in this paper. Through this comprehensive review, we discuss the findings and identify research gaps, shedding light on the current state of knowledge in the field of Digital Twin development. This paper aims to provide valuable insights for practitioners and researchers alike, guiding them in navigating the complexities associated with the implementation of Digital Twins.

Implementation of Digital Twin and Real Production System to Address Actual and Future Challenges in Assembly Technology

Increasing volatility in manufacturing and rising sustainability requirements demand more efficient processes in production, especially in employee qualification and engineering during development and on-site adjustments before and after the start of production. One possible solution is using digital twins for virtual commissioning, which can speed up engineering processes, qualify employees, and save valuable resources. To solve these challenges, it is necessary to identify promising approaches for using the digital twin and virtual commissioning. Furthermore, creating an environment where these approaches can be optimally explored is essential. This paper presents promising research approaches and demonstrates the development of an assembly process and a production system with a digital twin designed to explore these aspects. The presented system is an interlinked production system for assembling an actual industrial product. It includes different levels of human–robot interaction and automation, which can be implemented virtually in the digital twin.

Orchestration of model computing assets for the development of digital twins

With the development of industries and manufacturing requirements, the use of digital twin technology is promising for increasing efficiency and improving product quality. An important component of digital twin implementation is the provision of tools for modeling and simulation processes. In this study, a solution based on the use of Python-based models and the Controller software platform, which provides communication between models and external elements of digital twins and other IIoT solutions, was proposed as such a toolkit. It defines the main approaches for creating model, scenario, and function libraries, along with the concept of implementing dynamic scenarios based on JSON requests from the orchestrator. In addition, the algorithm, the structure of the Controller, and its main functionality are considered. The resulting solution takes advantage of the Python and Node.js languages in performing the relevant tasks and contains several solutions that reduce traffic and workload on communication systems, increase system reliability, scale the system, etc.

Implementation of Digital Twin in Actual Production: Intelligent Assembly Paradigm for Large-Scale Industrial Equipment

The assembly process of large-scale and non-standard industrial equipment poses significant challenges due to its inherent scale-related complexity and proneness to errors, making it difficult to ensure process cost, production cycle, and assembly accuracy. In response to the limitations of traditional ineffective production models, this paper aims to explore and propose a digital twin (DT)-based technology paradigm for the intelligent assembly of large-scale and non-standard industrial equipment, focusing on both the equipment structure and assembly process levels. The paradigm incorporates key technologies that facilitate the integration of virtual and physical information, including the establishment and updating of DT models for assembly structures using actual data, the assessment of structural assemblability based on DT models, the planning and simulation of assembly processes, and the implementation of virtual commissioning technology tailored to the actual assembly process. The effectiveness of the proposed paradigm is demonstrated through a case study involving the actual assembly of a large-scale aerodynamic experimental equipment. The results confirm its ability to provide valuable technical support for the design, evaluation, and optimization of industrial equipment assembly processes. By leveraging the DT-based methodological system proposed in this paper, significant improvements in the transparency and intelligence of industrial equipment production processes can be achieved.

Towards capsule endoscope locomotion in large volumes: design, fuzzy modeling, and testing

AbstractWe present the design and deployment of a capsule endoscope via external electromagnets for locomotion in large volumes alongside its digital twin implementation based on interval type-2 fuzzy logic systems (IT2-FLSs). To perform locomotion, we developed an external mechanism comprising five external electromagnets on a two-dimensional translational platform that is to be placed underneath the patients’ bed and integrated multiple Neodymium magnets into the capsule. The interaction between the central bottom external electromagnet and the internal magnet forms a fixed body frame at the capsule center, allowing rotation. The interaction between the external electromagnets and the two internal magnets results in rotation. The elevation of the capsule is accomplished due to the interaction between the upper external electromagnet and the internal magnets. Through simulations, we model the capsule rotation as a function of torque and drive voltages. We validated the proposed locomotion approach experimentally and observed that the results are highly nonlinear and uncertain. Thus, we define a regression problem in which IT2-FLSs, capable of representing nonlinearity and uncertainty, are learned. To verify the proposed locomotion approach and test the IT2-FLS, we leverage our experimental effort to a stomach phantom and finally to an ex vivo bovine stomach. The experimental results validate the locomotion capability and show that the IT2-FLS can capture uncertainties while resulting in satisfactory prediction performance. To showcase the benefit in a clinical scenario, we present a digital twin implementation of the proposed approach in a virtual environment that can link physical and virtual worlds in real time.

Harnessing the untapped potential of digital twin technology in digital public health interventions

Digital technologies have garnered more attention in this epoch of public health emergencies like coronavirus disease 2019 (COVID-19) and monkeypox (mpox). Digital twin (DT) is the virtual cybernetic equivalent of a physical object (e.g., a device, a human, a community) used to better understand the complexity of the latter and predict, prevent, monitor, and optimize real-world outcomes. The possible use cases of DT systems in public health ranging from mass vaccination planning to understanding disease transmission patterns have been discussed. Despite potential applications in healthcare, several economic, social, and ethical challenges might hinder the universal implementation of DT. Nevertheless, devising appropriate policies, reinforcing good governance, and launching multinational collaborative efforts ascertain early espousal of DT technology.

Augmented Reality-Based BIM Data Compatibility Verification Method for FAB Digital Twin implementation

With the advancement of state-of-the-art technologies, the semiconductor industry plays a key role as an essential component in the manufacture of various electronic products. Since the manufacturing of a semiconductor goes through very sophisticated and complex processes, efficient and accurate work and management are essential in the design, construction, and operation stages of the semiconductor fabrication (FAB) plant. Recently, the combined application of building information modeling (BIM) and augmented reality (AR) technology has gained increased attention in this semiconductor FAB industry as an advanced way to improve work efficiency and accuracy while eliminating other related problems, such as human errors. Despite the perceived benefits of combined use of BIM and AR, many technical problems still exist when integrating the target test model and the 3D virtual object model using BIM data and existing AR visualization technology, due to the unique characteristics of the FAB sites. To solve these problems, this study proposed an AR-based real-time BIM data compatibility verification method for future FAB digital twin implementation and demonstrated that it could be converted into a system and applied to actual FAB sites. As a result of the development and verification of this system, the proposed AR-based real-time BIM data compatibility verification system enables the accurate fitting of the AR model and actual object through AR tracking and anchoring technology considering the characteristics of FAB sites. After the fitting, the system was able to maintain compatibility, even when the camera moved and the marker moved away from the screen. By expanding the effective distance of compatibility between the AR model and the actual object, it was possible to increase the AR application range between the 3D virtual object model and the test target model and to improve the compatibility.