Digital twin technology in surgery: A narrative review of applications, evidence, and implementation challenges

Abstract: Digital twin technology, which creates virtual replicas of physical assets, processes, and systems, is transforming industries by enabling real-time monitoring, simulation, and optimization. This book chapter explores the fundamental principles, key components, and diverse applications of digital twins across various sectors, including manufacturing, healthcare, energy, automotive, and smart cities. Through detailed case studies, the chapter illustrates the successful implementation and significant benefits of digital twins, such as enhanced operational efficiency, cost reduction, improved risk management, and accelerated innovation. It also addresses the technical challenges, security and privacy concerns, and regulatory issues associated with digital twin technology. Looking forward, the chapter highlights future trends and developments, predicting advancements in AI, edge computing, 5G, and quantum computing that will further enhance digital twin capabilities. The chapter concludes with a forward-looking perspective on the transformative potential of digital twins in shaping a smarter, more connected, and sustainable world. Keywords: Digital Twin Technology,Real-Time Monitoring,Simulation and Optimization,Manufacturing Efficiency,Predictive Maintenance,Healthcare Innovation,Energy Management,Smart Cities,IoT Integration,AI and Machine Learning,Edge Computing,5G Connectivity,Quantum Computing,Operational Efficiency,Risk Management,Sustainability,Industry 4.0,Virtual Prototyping and Future Trends in Technology. Condori, P. P. C. (2022). Digital Twin in Development of Products. Digital Twin Technology, 205–218. Portico. https://doi.org/10.1002/9781119842316.ch13 Fryer, T. (2019). Digital Twin - Introduction. This is the age of The Digital Twin. Engineering & Technology, 14(1), 28–29. https://doi.org/10.1049/et.2019.0125 Gnanamalar, R. H. (2024). Human Digital Twin Processes and their Future. Transforming Industry Using Digital Twin Technology, 187–217. https://doi.org/10.1007/978-3-031-58523-4_10 Korhan, O. (2023). Introductory Chapter: Digital Twin Technology. Digital Twin Technology - Fundamentals and Applications. https://doi.org/10.5772/intechopen.113345 Mythily, M., David, B., & Vijay, J. A. (2024). Digital Twin Application in Various Sectors. Transforming Industry Using Digital Twin Technology, 219–237. https://doi.org/10.1007/978-3-031-58523-4_11 Seolin Galindo, E., & Chagas, U. (2023). Perspective Chapter: Digital Twin Applied in the Brazilian Energy Sector. Digital Twin Technology - Fundamentals and Applications. https://doi.org/10.5772/intechopen.112598

Developments in virtual technology and data acquisition technology put way to digital twin (DT) technology. Digital twin is a virtual entity that is linked to a real-world entity. Both the link and the virtual representation can be realized in several different ways. Digital Technology plays a very much key role in different areas like in production management, manufacturing, health care, smart cities and so on. Mainly Digital Twin Technology is developed to improve manufacturing processes. With the development of new-generation information and digitalization technologies, more data can be collected, and it is time to find a way for the deep application of all these data. As a result, the concept of digital twin has aroused much concern and is developing rapidly. Digital twins facilitate to monitor, understand, and optimize the functions of all physical entities and for humans and also provide continuous feedback to improve quality of life and well-being. Digital Twin is best described as the effortless integration of data between a physical and virtual machine in either direction. This paper provides an overview of the Digital Twin technology used in different work spaces and also how it will be effective in the Internet of Things network.

The latest advancement in digital technologies has greatly revolutionized modern manufacturing processes, particularly through the adoption of Lean Manufacturing initiatives aimed at minimizing wastage and enhancing operational efficiency. Predictive Maintenance (PM) being one of the primary drivers of transformation in lean manufacturing by reducing equipment downtime and optimizing asset performance. The lack of failure data is one of the biggest obstacles to PM deployment because traditional maintenance methods are used to maintain equipment after they break down. In order to address the issue of data scarcity, this study investigates the use of Digital Twin (DT) technology, which creates a virtual duplicate of the physical item and enables real-time monitoring utilizing sensors and Internet of Things devices for predictive analysis. IoT and data analytics are well complemented by digital twin technology, giving the manufacturer access to real-time information about the state of the machines while they are operating. This connectivity allows them to predict future asset failures accurately and strategically schedule maintenance activities in advance. The findings presented in this paper demonstrate that digital twin applications can reduce maintenance costs by 35% and machine uptime by 98%. It also presents case studies of DT application across different industries, and comparative study of positive impacts achieved through DT adoption. Cumulatively, the study highlights DT's transformational capability to facilitate lean initiatives and demands further investigation into integrations of emerging technology for process improvement.

Digital twin technology is increasingly becoming an important means to enhance efficiency at various stages of oil and gas development, serving as a key driver for building intelligent oil and gas reservoirs and advancing the digital transformation of the oil and gas industry. In recent years, foreign oil and gas companies have actively promoted the application of digital twin technology in intelligent oil and gas reservoirs, achieving certain progress and breakthroughs in some key technologies and application scenarios. Based on summarizing the characteristics and the current state of digital twin technology for intelligent oil and gas reservoirs, this paper analyzes the latest research and development progress of digital twin technology in foreign intelligent oil and gas reservoirs, explores the key technologies and future development trends of digital twin technology for intelligent oil and gas reservoirs, and, considering the current state of digital technology development in China's oil and gas development, proposes technical development suggestions in areas such as basic theories of digital twins, digital twin technology for oil and gas equipment, wellbore digital twin technology, digital twin technology for oil and gas reservoirs, and digital twin software platforms. The research results show that: 1. As an integration of digital technologies, digital twin technology is currently in the initial stages of research and application in oil and gas development, constrained by data collection, algorithm models, and open platforms; 2. Model construction and intelligent algorithms based on application scenarios are the core of digital twins, and efforts should focus on applying and integrating traditional mechanistic models and artificial intelligence models in scenarios with urgent needs, solid foundations, and significant potential; 3. The future development of digital twin technology for intelligent oil and gas reservoirs will move towards surface-subsurface integration, multidisciplinary integration, and the integration of the entire lifecycle of oil and gas reservoirs, enhancing cooperation between operators and contractors through integrated open platforms, breaking down disciplinary boundaries, and promoting the sharing of data from geological exploration, well construction, and development production. The research results provide valuable reference and guidance for timely understanding and mastering the latest progress in digital twin technology for intelligent oil and gas reservoirs abroad, accelerating the construction of digital twin technology systems for intelligent oil and gas reservoirs, tackling key technologies and integrating applications, and promoting the digital transformation and intelligent development of the oil and gas industry.

Smart city sustainability initiatives prioritize creating environmentally, economically, and socially sustainable urban environments. Digital Twin (DT) technology creates precise digital replicas of physical assets, systems, or processes. These digital twins play a crucial role in advancing the goals of smart city sustainability. This paper explores the development and application of DT technology for integrated regional energy systems in smart cities, emphasizing its potential to optimize energy consumption, reduce costs, and enhance overall system performance. The CloudIEPS platform, an energy internet planning platform based on digital twin technology, is a great example of how digital twin technology can be applied in practice, helping optimize energy efficiency and reduce costs. Integrating digital twin technology with the Multi-Criteria Decision-Making (MCDM) methods offers a novel approach to managing and optimizing energy systems in smart cities. The paper aims to create a consistent and robust approach to determining the best digital twin solution for energy systems in smart cities. The paper identifies critical factors for decision-making and establishes a method for assessing the significance of criteria using Triangular Neutrosophic Sets (TNS) through the MEthod based on Removal Effects of Criteria (MEREC) and the Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) approach. These methods are used to evaluate and prioritize multiple criteria in decision-making processes. Furthermore, the methods are combined with Triangular Neutrosophic Sets (TNS) to support decision-making for smart cities' energy systems, better accounting for the complex and uncertain nature of energy systems. A case study is conducted to apply and validate the developed methodology and perform a sensitivity analysis of the experimental results. The research outcomes indicated that the proposed methodology is robust and effective in handling the uncertainty and complexity inherent in smart cities' energy systems. The sensitivity analysis further confirms the stability and adaptability of the proposed methodology across different scenarios, making it a valuable tool for policymakers and stakeholders in the energy sector.

The emergence of Digital Twin (DT) technology has garnered significant attention in healthcare, providing a revolutionary approach to patient care, diagnostics, and treatment planning. Digital twins are virtual replicas of physical entities (in this case, human beings), created through the integration of real-time data collected from sensors and devices. This paper explores the potential role of Digital Twin technology in healthcare, its applications, challenges, and opportunities. We review recent studies and current implementations, focusing on the integration of digital twins for personalized care, predictive analytics, and decision-making. The research also highlights the barriers such as data privacy concerns, high implementation costs, and technological limitations. The findings point to a future where Digital Twin technology plays a central role in improving patient outcomes, operational efficiency, and the accuracy of treatments in healthcare. The paper concludes with a discussion of future research directions and applications for digital twins in healthcare. The purpose of this research study is to examine how digital twins can transform healthcare by going over the prospects, difficulties, and future course of their integration into healthcare systems. This study looks at the existing situation in an effort to offer insightful information about how digital twins can transform healthcare delivery and enhance patient care, while also identifying the challenges that need to be addressed for their widespread adoption

The Halal supply chain, which encompasses the sectors of food, medicines, cosmetics, has enormous challenges to comply with Islamic rules, maintain product traceability and combating fraud. Given the increasing global demand for Halal products, the demand for technology innovations to enhance supply chain transparency and ensure Halal compliance is growing. This paper explores the application of Digital Twin (DT) technology in Halal supply chain management, highlighting its ability to address these challenges. The main research question of this paper is as follows: How can Digital Twin technology facilitate transparency, traceability, and compliance in the Halal supply chains? The current study employs a qualitative methodology through a review of the extant literature and reviews of industrial case studies. The study reveals that the Digital Twin technology promises to considerably improve the operational excellence of Halal supply chains through real-time Halal status monitoring ensuring that products comply with religious and ethical requirements along the supply chain. The main applications include tracking Halal certification, preventing cross-contamination, and enhancing transparency for certification bodies, manufacturers, and consumers. The results indicate that Digital Twin technology has the potential to transform Halal supply chains by reducing fraud, improving operational efficiencies, and building consumer trust. As a comprehensive Halal compliance solution, Digital Twin can enable a more transparent and trustworthy Halal certification process on a global scale. The study extends the knowledge body on technology innovations in supply chain management especially with religious and ethical product certifications and sets the stage for future research in the area.

The paper investigated the use of digital twin (DT) technologies in the energy industry. It analyzed the available digital twin technology used in the energy industry using the SWOT method. The DT serves as the real-time presentation of the actual process or physical object with the Internet of Things (IoT). Typically, fabrication work productivity depends on the process flow and the human behaviours that contribute to delay or non-productive time—digital technology to learn the overall process, human behaviour, and machinery uptime. Visual learning was established to monitor the operation activity as well as the construction work and to capture the general behaviours of the human such as welding, resting, taking a break or even non-productive work such as break outside break hour, smoking, wrong sequence of the working process and other external interruptions. This study will explore all the available DT technology in the market and its function and capabilities and then identify five (5) DT technology applications that can improve performance in the energy industry. After that, to determine and summarize the strength, weakness, opportunity, and threat of all five (5) applications of DT technologies already used in the energy industry using SWOT methodology. The SWOT analysis found that the benefit in terms of Strength and Opportunity is more significant than the threat and weakness of the Digital Twin technology. Then, it is clearly indicated that the DT technology is capable of utilising in many other areas of business in objective to understanding the overall system efficiency and capable of providing information for accurate and precise decision making for the company.

This paper investigates the latest advancements and industrial applications of Digital Twin (DT) technology, focusing on 3D behavior representation across the entire lifecycle, from design and initial planning to testing, implementation, and optimization. In this comprehensive review, the authors define 3D behavior as the virtualization and simulation of controlled technologies, encompassing processes performed, movement scenarios of the various parts of the technology, and their responses to the actual states and the surrounding environment. The study also explores the industrial applicability of 3D modeling and simulation using the latest software tools and methodologies. Furthermore, the authors define several use cases, derived from their own research experiences, that illustrate the different variants of Digital Twins across various stages of development and production within digitalized technology. These use cases highlight how Digital Twin solutions are applied in real-world scenarios, aligning with current digitalization trends and Industry 4.0 standards. The findings are discussed from an innovative perspective, emphasizing how Digital Twin technology can significantly improve all phases of industrial digitalization. This paper not only examines the research, theoretical foundation, and historical development of industrial Digital Twins but also clarifies key concepts such as modeling and model-based design, while providing an overview of relevant software tools. In addition, five detailed industrial use cases are presented, illustrating the practical implementation and benefits of Digital Twin technology in various industrial applications.

Intrinsic capacity (IC) refers to the sum of the physical and mental capacities of an individual. Conventional IC assessment requires substantial temporal and human resources. Digital twin (DT) technology emerges as a promising solution for efficiently mapping ICs. This study aims to explore older adults' perspectives on the DT technology and their perceptions of how it could effectively represent their ICs. A qualitative study was used. Face-to-face semistructured interviews with 23 older adults were conducted. The interviews were transcribed verbatim and analyzed via content analysis approach. The analysis identified five themes and 16 subthemes: (1) "opt for or not my digital twin," revealing the older adults' decisions regarding whether to use DT technology for mapping ICs; (2) "my ideal digital avatar," describing the older adults' preferences for personalized digital avatar appearances; (3) "my digital twin maps my intrinsic capacity," highlighting how multimodal reminders and synchronized avatar changes enhanced their comprehension of ICs; (4) "the benefits my digital twin can deliver," emphasizing the potential of the DT system to provide feedback services to older adults; (5) "some expectations for my digital twin," outlining their expectations for DT technology. Based on the above insights, a conceptual model, "windmill" model, was further developed to better understand how to build DTs of older adults and map their ICs. DT technology was a promising tool for mapping ICs of older adults. Furthermore, the "windmill" model provided a framework to build tailored DTs. The findings of this study could provide references to develop DT model to support IC management.

Background: With the rapid development of digital twinning technology, the compatibility of digital twinning technology to other technologies is continuously enhanced. It is because of this that the application of image recognition technology in digital twinning technology becomes a reality. However, the key technology of digital twin, the virtual-actual mutual control technology, is not mature enough, and the image recognition technology applied in digital twin technology also has the problem of coordinate system transformation, which becomes an important link of image recognition technology in digital twin. Methods: Based on the above two problems, we take the tangram splicing project as an example to realize a virtual-actual mutual control method, so that the digital twinning technology can be well presented. Furthermore, we implement an image recognition applied to the conversion of digital twinning technology, so that digital twinning technology and image recognition have a seamless connection, allowing the application range of digital twinning technology to be further expanded. Results: In this paper, image recognition technology is successfully applied to digital twin technology by adopting the conversion between different coordinate systems and the real and virtual real time control, which makes the applicability of digital twin technology in high-tech fields such as smart factories and smart manufacturing to a higher level. Conclusions: Finally, through the tangram splicing project, the motion trajectories of the robotic arm and the tangram are consistent with the virtual robotic arm and the tangram in the computer. It is proved that our method can well combine digital twinning technology and image recognition technology.

Background With the rapid development of digital twinning technology, the compatibility of digital twinning technology to other technologies is continuously enhanced. It is because of this that the application of image recognition technology in digital twinning technology becomes a reality. However, the key technology of digital twin, the virtual-actual mutual control technology, is not mature enough, and the image recognition technology applied in digital twin technology also has the problem of coordinate system transformation, which becomes an important link of image recognition technology in digital twin. Methods Based on the above two problems, we take the tangram splicing project as an example to realize a virtual-actual mutual control method, so that the digital twinning technology can be well presented. Furthermore, we implement an image recognition applied to the conversion of digital twinning technology, so that digital twinning technology and image recognition have a seamless connection, allowing the application range of digital twinning technology to be further expanded. Results In this paper, image recognition technology is successfully applied to digital twin technology by adopting the conversion between different coordinate systems and the real and virtual real time control, which makes the applicability of digital twin technology in high-tech fields such as smart factories and smart manufacturing to a higher level. Conclusions Finally, through the tangram splicing project, the motion trajectories of the robotic arm and the tangram are consistent with the virtual robotic arm and the tangram in the computer. It is proved that our method can well combine digital twinning technology and image recognition technology.

Following the fourth industrial revolution and recent advances in information and communication technologies, the digital twinning concept is attracting the attention of maritime academia and the maritime industry worldwide. A digital twin is a representation in digital form of a physical item, thing, or system: a vessel, a car, a wind turbine, a power grid, a pipeline, or equipment such as a thruster or an engine. One of the key initiatives at the MAAP is to apply Digital Twin technology in the development of MASS (Maritime Autonomous Surface Ship), e-navigation, ship engine room management, training, and validation of operational concepts associated with smart and autonomous ships. To this end, the progress realized in adapting and exploring digital twin (DT) technologies at MAAP will be presented. In particular, the Kognitwin technology system (a Digital Twin system) developed by Kongsberg Maritime and other systems applicable to decision-making that ensure cost-effective, safer, and sustainable operations will be described. The focus will be placed on using digital twin technology in some of the grey areas: Optimization of Fleet with Virtual Transition of Ship Control System, Enhancing the Port and Terminal Operations, Awareness Situation about Operational Parameters, End-To-End Supply Chain Optimization, Amplified Security Ensuring Safety and Better vessel design and operation.

Digital Twin (DT) technology creates a dynamic virtual representation of a physical system using real-time data and computational modeling. While DTs have demonstrated profound impact in several medical disciplines, their translation into dentistry is still emerging and has not been comprehensively mapped. To systematically review and delineate the current applications, technological advancements, and prospective opportunities of digital twin (DT) technology in dentistry. A scoping review was conducted following the Joanna Briggs Institute (JBI) methodology and reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. A systematic search of MEDLINE (PubMed), EMBASE, Scopus, and Web of Science identified English-language publications from January 2000 to April 2025. All empirical and conceptual studies describing DT development, validation, and/or application in dental contexts were eligible. Two reviewers independently conducted screening and study selection, with a third reviewer resolving discrepancies. No automation tools were used. A total of 5989 records were retrieved, and 7 studies met the inclusion criteria. Included studies represented orthodontics, prosthodontics, endodontics, and dental education. DT applications primarily involved: patient-specific virtual modeling for diagnosis and treatment simulation, predictive or performance-monitoring frameworks using biomechanical/algorithmic analysis, and simulation-based skill training. Most were conceptual or prototype studies with small samples and limited clinical validation. DT technology has substantial potential to enhance precision, simulation, monitoring, and personalization in dentistry. However, current evidence remains constrained by fragmented research, methodological inconsistency and insufficient clinical validation. Future adoption of DT requires standardized data pipelines, robust ethical and regulatory frameworks and interdisciplinary collaboration to achieve clinically meaningful and widely adoptable DT integration in dental care.

Recent advancements in the healthcare sector have reached a pivotal juncture, catalysed by the emergence of Digital Twin (DT) technologies. These innovations facilitate the development of virtual replicas that accurately simulate real-world conditions, thereby transforming traditional approaches to medical analysis, diagnostics, and treatment planning. Although widely successful in manufacturing, the adoption of Digital Twins in healthcare is relatively limited, particularly regarding their impact on clinical efficiency and patient outcomes. This study addresses three primary research questions: (1) How does Digital Twin technology improve individualised patient treatments and care quality? (2) What is the role of Digital Twin technology in accurately predicting patient responses to medical interventions? (3) What are the significant challenges of integrating Digital Twin technology into healthcare? Synthesising findings from 70 peer-reviewed articles, this review identifies critical knowledge gaps and provides practical recommendations for healthcare stakeholders to effectively navigate these challenges. This research proposes a conceptual framework illustrating the lifecycle of Digital Twin implementation in healthcare and outlines essential strategies for successful adoption. It emphasises the importance of robust infrastructure, clear regulatory guidance, and ethical practices to fully leverage the advantages of DT technologies. Nevertheless, this review acknowledges its limitations, including reliance on secondary data and the absence of empirical validation. Future research should focus on practical applications, diverse healthcare contexts, and broader stakeholder perspectives to comprehensively assess real-world impacts.