DRIVE-THRU REVOLUTION: ENHANCING CUSTOMER SATISFACTION THROUGH DIGITAL TWINS

Biopharma Is Going Digital … Bit by Bit

The combination of artificial intelligence (AI) and digital twin technology is reshaping businesses' approach to data. This chapter explores the transformative potential of AI-driven data analytics within digital twins, focusing on its implications for forward looking enterprises. The study delves into the intricate relationship between AI and digital twins, illustrating how AI-driven data analytics enhances digital twin capabilities. The authors substantiate the findings with real-world case studies, demonstrating how this integration optimizes operational efficiencies, minimizes downtime, and elevates product quality. Ethical and privacy considerations in this context are examined. The key findings highlight how real-time insights, predictive modelling skills, and well-informed decision support are provided to digital twins by AI-driven data analytics. Businesses are urged to take use of these synergies to gain a competitive edge, and researchers should look into ways to make AI models transparent and understandable.

Digital Twin was introduced over a decade ago, as an innovative all-encompassing tool, with perceived benefits including real-time monitoring, simulation, optimisation and accurate forecasting. However, the theoretical framework and practical implementations of digital twin (DT) are yet to fully achieve this vision at scale. Although an increasing number of successful implementations exist in research and industrial works, sufficient implementation details are not publicly available, making it difficult to fully assess their components and effectiveness, to draw comparisons, identify successful solutions, share lessons, and thus to jointly advance and benefit from the DT methodology. This work first presents a review of relevant DT research and industrial works, focusing on the key DT features, current approaches in different domains, and successful DT implementations, to infer the key DT components and properties, and to identify current limitations and reasons behind the delay in the widespread implementation and adoption of digital twin. This work identifies that the major reasons for this delay are: the fact the DT is still a fast evolving concept; the lack of a universal DT reference framework, e.g. DT standards are scarce and still evolving; problem- and domain-dependence; security concerns over shared data; lack of DT performance metrics; and reliance of digital twin on other fast-evolving technologies. Advancements in machine learning, Internet of Things (IoT) and big data have led to significant improvements in DT features such as real-time monitoring and accurate forecasting. Despite this progress and individual company-based efforts, certain research and implementation gaps exist in the field, which have so far prevented the widespread adoption of the DT concept and technology; these gaps are also discussed in this work. Based on reviews of past work and the identified gaps, this work then defines a conceptualisation of DT which includes its components and properties; these also validate the uniqueness of DT as a concept, when compared to similar concepts such as simulation, autonomous systems and optimisation. Real-life case studies are used to showcase the application of the conceptualisation. This work discusses the state-of-the-art in DT, addresses relevant and timely DT questions, and identifies novel research questions, thus contributing to a better understanding of the DT paradigm and advancing the theory and practice of DT and its allied technologies.

The article focuses on the project to develop a supply chain management information system using a digital twin for the maritime transport chain. Digital twins reflect real objects and processes in a virtual environment, which enables analysis, modelling and optimisation of supply chain operations. The author describes the main stages of the project, including requirements definition, system architecture development, implementation and testing. Particular attention is paid to the benefits of using digital twins in supply chain management, such as increased efficiency, reduced risk and improved forecasting. The results of the study show the potential of digital twins to optimise supply chain management and increase the competitiveness of companies. The article presents an approach to building a new model of interaction and systematic optimisation of business processes based on digital technologies at all stages of supply chain formation, which ensures the creation of a digital twin for the maritime transport chain. In order to improve supply chains, a digital twin has been proposed, which opens up great prospects for the management of logistics processes and the exchange of information between supply chain participants. This paper presents a framework for an integral Digital Supply Chain Twin (DSCT) capable of covering the entire transport chain. The proposed information system based on the use of the DSCT provides a number of improvements throughout the supply chain, as well as the ability to model and evaluate different scenarios for the supply chain. This creates opportunities to reduce the cost of organising and coordinating transport, improve the quality of transport and logistics services and make them more reliable by identifying potential problems at an early stage. The article analyses the main information technologies that facilitate the use of DSCT as a useful and reliable tool.

Controlling Unmanned Aerial Vehicles (UAVs) is a cognitively demanding task, with accidents often arising from insufficient situational awareness, inadequate training, and bad user experiences. Providing more intuitive and immersive visual feedback—particularly through Digital Twin technologies—offers new opportunities to enhance pilot awareness and the overall experience quality. In this study, we investigate how different virtual points of view (POVs) influence user experience and performance during UAV piloting in Virtual Reality (VR), utilizing a digital twin that faithfully replicates the real-world flight environment. We developed a VR application that enables participants to control a physical DJI Mini 4 Pro drone while immersed in a digital twin with four distinct camera perspectives: Baseline View (static external), First Person View, Chase View, and Third Person View. Nineteen participants completed a series of ring-based obstacle courses from each perspective. In addition to objective flight data, we collected standardized subjective assessments of user experience, presence, workload, cybersickness, and situational awareness. Quantitative analyses revealed that the First Person View was associated with significantly higher mental demand and effort, greater trajectory deviation, but smoother control inputs compared to the Third Person and Chase perspectives. Complementing these findings, preference data indicated that the Third Person View was most consistently favored, whereas the First Person View elicited polarized reactions.

Digital twin technology has been increasingly applied in healthcare and patient well-being in recent years. This paper provides an overview of the current methods and applications of digital twins in the healthcare field. One such application is digital twins in precision healthcare, where digital twins are used to create patient-specific models to assist in diagnosis and treatment planning. Digital twins are also used in hospital/clinic management, where they help to optimize resource allocation and workflow processes. In response to the COVID-19 pandemic, digital twins have been utilized to detect outbreaks and predict disease spread. In addition, digital twins have been applied in bio-manufacturing and pharmaceutical industry to improve manufacturing processes. Another application area is machine learning and modeling, where digital twins are used in machine learning, data generation, and system modeling for applications in healthcare and disease prediction. Security and ethical issues related to digital twins are also discussed in this paper, as privacy concerns and data protection remain important considerations in the application of digital twin technology in healthcare. Finally, the paper concludes by discussing the future challenges and directions of future work in this field. These include the need to develop more accurate and sophisticated digital twin models, addressing interoperability and integration issues, and further exploring the potential of digital twin technology in emerging areas such as telemedicine and personalized medicine.

Digital Twin technology is rapidly emerging as a transformative force in various industries, playing a pivotal role in the advancement of Industry 4.0. As industries evolve, the implementation of Digital Twin is anticipated to drive significant technological progress across sectors such as manufacturing, smart cities, healthcare, and transportation. This paper presents a layered Digital Twin framework that synthesizes recent advances in sensing, data analytics, and machine learning to enable real-time monitoring, analysis, and predictive capabilities for modern power systems. By leveraging these advanced sensors, the Digital Twin framework enables more accurate system modeling, enhanced situational awareness, and improved decision-making processes. This approach aims to significantly transform traditional smart grid operations by offering a more responsive, resilient, and efficient energy management system, ultimately contributing to the optimization and modernization of existing power infrastructure. Furthermore, by highlighting key smart grid applications, the paper demonstrates the effectiveness of Digital Twin and sensor technology in optimizing power distribution, reducing downtime, and addressing prevalent energy challenges, thereby paving the way for resilient and intelligent power systems.

Geometric parameter updating in digital twin of built assets: A systematic literature review

Aiming at the increasingly complex management and dispatching problems of power system, this paper combines Beidou precise space-time technology with digital twin system theory, and puts forward a method of constructing intelligent management and dispatching platform of power grid. The method combines Beidou and IoT (Internet of Things) sensors to form a digital twin management and scheduling platform which can perform state prediction, fault diagnosis, self-healing and other functions. Firstly, this paper analyzes the overall architecture of Beidou digital power twin system, then discusses the construction method of digital twin in power system from the aspects of digital twin modeling theory, data acquisition intelligent terminal based on Beidou, operation mode of digital twin platform, etc. Finally, the application test analysis is carried out. The research results show that the method proposed in this paper has reference value for improving the management and dispatching capability of smart grid.

The agricultural domain is experiencing an increasing use of digital twin technologies in greenhouse horticulture for the betterment of monitoring production. Research in this domain has started leading towards more advanced ways of visually interacting with these digital twins, and this could be by means of immersive technologies (such as virtual reality) to better allow farmers to feel a sense of presence when exploring these digital copies. Yet there are many remaining challenges for the technology’s integration and more studies are needed into user interaction; specifically regarding simulation sickness to cater for comfort during prolonged and regular use. Thus, this article documents the survey of 30 participants by means of the Simulator Sickness Questionnaire (before and after interaction) when using an immersive digital greenhouse twin environment. Findings indicate that users who experience simulation sickness tend to provide a lower evaluation score of the digital twin and their prior experience of gaming (on varied devices) affects the overall evaluation of the digital environment. Further, the level of playability and realism (referred to as convenience), statistically affects the end users’ level of sickness. For tracking crop growth by means of digital greenhouse twins, where prolonged user interaction may take place in a virtual environment, these are notable considerations for digital twin developers.

Web-based human-robot collaboration digital twin management and control system

Aim. Development of the author’s concept of increasing the efficiency of financial risk management on the basis of application of the technology of creating and using the digital twin of the enterprise.Objectives. To formalize the problems of existing approaches to solving the problems of financial risk management of enterprises of the real sector of economy; to identify trends in the development of digital twins, to formulate the advantages of their practical application and to give the author’s interpretation of the concept of “digital twin of the enterprise”; to build and substantiate a multilayer system of indicators of the digital twin of the enterprise in the context of improving the efficiency of financial risk management; to develop the principles of building a digital twin of the enterprise, focused on solving the problems of financial risk management.Methods. The research was carried out on the basis of system approach, in the process of realization of which the methods of synthesis, logical comparative, factor and graphical analysis, basic provisions of financial risk management and the results obtained in domestic and foreign scientific literature on the problems of realization of approaches and methods of financial risk management were used.Results. The author’s concept of increasing the efficiency of financial risk management based on the application of new technologies for creating digital twins is proposed. In particular, by means of formalizing the problems of existing approaches to solving the problems of financial management, identifying trends in the development of methodology and technologies for creating digital twins, the idea of increasing the efficiency of financial risk management on the basis of creating a digital twin of the enterprise is outlined. The multilayer system of indicators defining the structure of this digital twin is proposed and substantiated, the tasks are defined and the principles of its construction oriented to solving the tasks of financial risk management are developed. The financial kernel of the digital twin of the enterprise is constructed, containing the contours of formation of financial indicators common for different enterprises, determining the achievement of the objectives of financial risk management and its efficiency. The qualitative substantiation of increasing the efficiency of financial risk management with the application of the methodological basis for the creation and use of digital twins proposed in the article is given.Conclusions. Conceptual provisions of creation and use of digital twins for the purposes of financial risk-management, given in the article, create a theoretical and methodological basis for increasing the efficiency of financial risk-management taking into account the use of new digital technologies and can serve as a basis for practical construction of effective systems of financial risk-management at enterprises of the real sector of economy.

In modern medicine, novel technologies play a key role in improving the diagnosis, treatment, and management of patient health. One of the most promising innovations is Digital Twin technology, which enables the creation of virtual models of real-world objects, including human organs. This technology opens new possibilities for personalised medicine, disease prediction, and the optimisation of medical processes. Digital Twins are already actively used in various industries, such as manufacturing, aviation, and urban planning, but their potential in medicine is only beginning to unfold. They allow for creating detailed models of an individual patient’s body, contributing to more accurate diagnostics, simulation of treatment responses, and enhanced efficiency of medical interventions. This article explores the key aspects of Digital Twin medical applications, their advantages, challenges, and development prospects. Special attention is given to the technical foundations of this technology, its use in personalised medicine, health monitoring, disease prediction, and the optimisation of healthcare facilities. For the practical part, the study shows how to create a Digital Twin of a heart based on real patient data. Additionally, the study investigates a model of the heart’s Digital Twin, demonstrates its use, and illustrates how to replicate heart functionality using the Digital Twin. The study describes how a part of a Digital Twin was created using the suggested architecture and outlines how to use and extend this functionality. More than that, the study shows how to integrate artificial intelligence into the Digital Twin architecture and how artificial intelligence algorithms help create Digital Twins. The research shows how to build the Digital Twin using machine learning and artificial intelligence technologies, and how to choose the mathematical model for the Digital Twin. To conclude, the study defines further work, problems, and difficulties in creating the Digital Twin of the heart. The study shows the perspectives on using Digital Twins, their practicality, and real-life cases where Digital Twins can save lives. Also, the study defines the next steps for the Digital Twin creation, testing, implementation, and usage in the real-life healthcare industry.

Toward sustainability and resilience with Industry 4.0 and Industry 5.0

The article studies the practice of implementing the technology of creating digital twins in the energy system of foreign countries and that of the Russian Federation. The purpose of the study is to identify the key areas of application of the technology as well as the best Russian and international practices. The tasks include analyzing the factors of the internal and external environment that affect the pace of digitalization of the entire industry and implementation of the digital twin technology in particular. The study focuses on analyzing the problems and benefits of using the technology in solving regional energy problems as well as on evaluation of the impact of digitalization process on financial indicators of energy companies and the prospects for further expanded use of digital twin technology in Russia’s energy industry. The practice of implementation of digital twins by energy companies of Finland, Slovakia and Russia studied within the research carried out prove high effectiveness of their application in solving regional tasks of power industry by increasing their productivity and reliability of the distribution networks’ performance. Moreover, the projects of digitalization involving digital twins ensure the growth of the companies’ profits and profitability increasing their further potential for the implementation of innovation technologies.