Digital Twins as a New Paradigm of an Industrial Enterprise

The aim of this research is to investigate the core principles and possibilities of using digital twin technology for the development of Russia’s industrial sectors, taking into account the international experience. Theoretical and methodological research has been based on the scientific works of domestic and foreign scientists on the use of digital technologies in the management of economic systems, including industry. The study was based on a set of quantitative and qualitative methods, including case analysis and text mining. A semantic analysis of scientific publications and industry literature was conducted to assess the condition of the problem field and determine trends in the digital transformation of industries from the standpoint of digital twin technology. In addition, an open-source collection of over 100 case files reflecting the practice of introducing digital twins into production processes was compiled. It has been proven that digital twins provide a wide range of possibilities for production enterprises: increased productivity, efficient use of resources, energy intensity and efficiency, reduction of different kinds of costs at all stages of the product life cycle, production of new types of products, and the modification of the organization’s business model. A SWOT analysis of economic entities using digital twins was undertaken, which made it possible to identify the opportunities and threats of their introduction into the production process. The study results have refined the model of a new generation industrial economic system based on the functionality of a digital twin, including the parameters of system and predictive analytics, as well as the Internet of Things platform.

Digital technology; Industry; Industry 4.0; Management; Virtual production concept

The manufacturing sector plays an important role in the economic development of countries. Industries are constantly developing, new technologies are being created, and processes to improve the quality of products are becoming more complex. The difficult economic situation currently prevailing in the world is leading to the validation of all promising technologies, primarily digital technologies, and in that connection, the industrial paradigm is changing. The previously predicted dynamics of the development and adaptation of digital technologies to production processes are difficult to achieve. It is worth noting that the impact of a complex epidemiological and economic situation on the development of specific technologies is not always negative. Under the new reality, a higher rate of development is attainable for certain groups. The technological trends of each digital technology are determined by the external conditions of their development, as well as by scientific, technological, and economic vectors. In conjunction, it is they who determine the technological development dynamics and direction of industries and the national economy as a whole.

In recent decades, the development of information and communication technologies and the resultant digitization of industry have brought significant changes in existing business models and products, making them digital and revolutionary, bringing benefits to the entire value chain, including the end-users of the products. Scientific and technological developments and increasing consumer demand for products with higher sophistication, improved quality, and lower costs have led to a broad debate on a new model for the development of industrial economies. The established practice of using the technological component ensures the formation of fundamentally new, highly efficient business models. It has already led to a significant transformation of social and economic processes. Among the factors determining the future of the production management system are the innovation cycle of the product, new technologies, and the Fourth Industrial Revolution (Industry 4.0). Additionally, among the main trends in the development of basic sciences, there has been a rise in interdisciplinary research, the emergence of new information processing technologies, and increased competition in the skilled labor market.

       Industry 4.0 is a new concept of production systems that includes technologies such as the Internet of Things, Big Data, cyber-physical systems, and intelligent objects. Industry 4.0 will present new challenges and opportunities for researchers and managers in the field of process safety and environmental protection. According to Badri et al. (2018), real-time communication, Big Data, remote sensing, production process control and management, off-line equipment, and interconnectivity will be the main assets in the modern industry. As the Fourth Industrial Revolution becomes the prevailing reality, it will lead to a new paradigm shift that will affect the management of labor protection.

Zezulka et al. (2018) consider the basics of building communication systems for open, safe, secure, almost in real-time, standardized communication interfaces and common architecture challenges that conform to Industry 4.0 principles for future enterprises. Müller et al. (2018) study how Industry 4.0 initiates changes in the business models of manufacturing plants. The results of their research show that Industry 4.0 includes three dimensions, namely, high-quality process digitization, intelligent production, and inter-company collaboration. Reischauer (2018) believes that Industry 4.0 is a revolution that will transform industries. He views the new industrial paradigm as a political innovation discourse in the manufacturing industries aimed at the institutionalizing of innovation systems, covering business, education, and politics. Industry 4.0 is a crucial research subject in the sphere of industrial systems management. Meissner et al. (2017) examine the issues of decentralized production control. They compare different properties of approaches and architectures with the goals of Industry 4.0, draw comparisons of how different architectures fit for Industry 4.0, and speak about the need for the development of tools for Industry 4.0 production management.

        In Russia, the leading scientific school that researches the effects of the introduction of digital twins is the school of Auzan–Borovkov (Auzan et al., 2019; Borovkov and Ryabov, 2019). The most interesting are the results of the estimation made by leading scientists of different disciplines about the introduction of digital twins. While Borovkov conducts serious technical and technological studies on the development of digital twins in the high-tech industry, Auzan conducts fundamental studies to assess the economic impact of the introduction and the effect of digital twins on the added value of businesses and the long-term competitiveness of corporations (Borovkov and Ryabov, 2019; Auzan et al., 2019). A large number of publications on the subject of digital twins now constitute either promotional articles or brief reports on the work being conducted in this field that do not bear scientific specifics (Shpak et al., 2020). At the same time, there are a small number of articles that reflect the possibilities of process modeling in transformers using 3D and 2D models (Tikhonov et al., 2020).

Digital technologies enable new prospects in the management of industrial economic systems. However, at present, there is no clear methodological support for the production organization using the function of a digital twin and its role in the realization of modern business models in various branches of the national economy. Thus, the aim of this study is to develop the concept of industrial systems control based on digital twin technology, taking into account the assessment of the accumulated domestic and foreign experience of using this digital tool. 

A digital twin is a virtual “layout” (prototype) of a real object or a group of objects of a technological process in industrial economic systems. The creation of digital twins ensures the rapid production and delivery of products with competitive properties in the context of global high-tech competition.

Using, to one degree or another, certain basic technologies of production digitalization, companies create their digital twins in the form of global platforms for modeling, simulation, and analysis of their production systems. Nevertheless, industrial enterprises wishing to realize the transition to a digital production model must identify, evaluate, and form new essential competencies, adapt their existing business strategies, and develop new ones as part of the implementation of the Industry 4.0 concept. The implementation of such a transformation requires the active application of a systematic approach in planning and evaluation, as well as a solution to the security and digital protection issues, the standardization processes, training and professional development, and the technological base.

Digital twins, as a new paradigm, can change the role of traditional production processes by changing the way the production is realized. Digital twin technology allows the realization of the transition to intelligent manufacturing technologies and the formation of Big Data processing systems. It helps to solve several complex technical industry problems. The use of digital twins, as well as the formation of a modern production infrastructure on their basis, will make it possible to ensure the optimal volume of production of more high-tech and science-intensive products that can most fully satisfy consumer needs. The prospect of technology development is the use of machine learning methods using neural networks, the development of online monitoring systems, and, as a whole, the formation of a self-learning intelligent digital model of an object to perform highly accurate predictive assessments and implement a multi-option design, taking into account various restrictions.

This research was supported by the Academic Excellence Project 5-100 proposed by Peter the Great St. Petersburg Polytechnic University.

Auzan, A.A., Komissarov, A.G., Bakhtigaraeva, A.I., 2019. Sociocultural Limitations of the Commercialization of Innovations in Russia. Economic Policy, Volume 14(4), pp. 76–95

Averyanov, A.A., Mikryukov, M.I., Rogova, I.N., 2019. Advantages of using an Integrated System of an Intelligent Digital Double of an Enterprise in the Operational and Strategic Management of Business Entities. Journal of Legal and Economic Research, Volume 2, pp. 122–125

Badri, A., Trudel, B., Souissi, A., 2018. Occupational Health and Safety in the Industry 4.0 Era: A Cause for Major Concern? Safety Science, Volume 109, pp. 403–411

Balakin, D.A., Kersky, E.V., 2020. Development of a Digital Twin of the Early Warning Radar. Journal of “Almaz-Antey” Air and Defense Corporation, Volume 1, pp. 10–18

Berawi, M.A., 2014. Modeling and Simulation in Engineering Design and Technology: Improving Project/Product Performance. International Journal of Technology, Volume 4(2), pp. 100–101

Berawi, M.A., 2018. The Fourth Industrial Revolution: Managing Technology Development for Competitiveness. International Journal of Technology, Volume 9(1), pp. 1–4

Borovkov, A.I., Ryabov Yu A., 2019. Digital Doubles: Definition, Approaches and Development Methods. In: The Collection: Digital Transformation of the Economy and Industry. Proceedings of the Scientific-Practical Conference with Foreign Participation, pp. 234–245

Bykova, V.N., Kim, E., Gadzhialiev, M.R., Musienko, V.O., Orudzhev, A.O., Turovskaya, E.A., 2020. The Use of the Digital Double in the Oil and Gas Industry. Actual Problems of Oil and Gas, Volume 1(28), pp. 8–12

Datta, S., 2017. Emergence of Digital Twins – Is This the March of Reason? Journal of Innovation Management, Volume 5(3), pp. 14–33

Govindaraju, R., Dwipayana, I.N.G.K., Salamah, S.Y., 2018. IT Governance and ERP Post-Implementation: Analysing the Impact of IT Business Alignment and IT Benefits Management on ERP Operation and Enhancement. International Journal of Technology, Volume 9(3), pp. 578–588

Grieves, M.W., 2014. Digital Twin: Manufacturing Excellence through Virtual Factory Replication, LLC Publication, pp. 1–7. Available Online at https://web.archive.org/web/20170517031855/http://innovate.fit.edu/plm/documents/doc_mgr/912/1411.0_

        Digital_Twin_White_Paper_Dr_Grieves.pdf, Accessed on October, 2020

Hehenberger, P., Bradley, D., 2016. Digital Twin—The Simulation Aspect. In: Mechatronic Futures: Challenges and Solutions for Mechatronic Systems and Their Designers, Hehenberger, P., (ed.), Springer International Publishing, New York, USA, pp. 59–74

Kokorev, D.S., Posmakov, N.P., 2019. The Use of “Digital Doubles” in Production Processes. Colloquium Journal, Volume 26-2(50), pp. 68–74

Lee, J., Bagheri, B., Kao, H.A., 2015. A Cyber-Physical Systems Architecture for Industry 4.0-Based Manufacturing Systems. Manufacturing Letters, Volume 3, pp. 18–23

Makarov, V.L., Bakhtizin, A.R., Beklaryan, G.L., 2019. Developing Digital Twins for Production Enterprises. Business Informatics, Volume, 13(4), pp. 7–16

Marr, B., 2017. What Is Digital Twin Technology—And Why Is It So Important? Available Online at http://www.forbes.com/sites/bernardmarr/2017/03/06/what-is-digital-twin-technology-and-why-is-it-so-important/#277a78772e2a, Accessed on October, 2020

Meissner, H., Ilsen, R., Aurich, J., 2017. Analysis of Control Architectures in the Context of Industry 4.0. Procedia CIRP, Volume 62, pp. 165–169

Müller, J., Buliga, O., Voigt, K.-I., 2018. Fortune Favors the Prepared: How SMEs Approach Business Model Innovations in Industry 4.0. Technological Forecasting and Social Change, Volume 132, pp. 2–17

Parshina, I.S., Frolov, E.B., 2020. Development of a Digital Twin of a Production System on the Basis of Modern Digital Technologies. Economics in Industry, Volume 13(1), pp. 29–34

Ponomarev, K.S., Feofanov, A.N., Grushina, T.G., 2019. Digital Production Double—A Means of Digitalizing the Organization’s Activities. Automation and Modeling in Design and Management, Volume 2(4), pp. 11–17

Pospelova, T.A., Strekalov, A.V., Knyazev, S.M., Kharitonov, A.N., 2020. Implementation of Digital Twins for Gas Field Management. Oil Province, Volume 1(21), pp. 230–242

Reischauer, G., 2018. Industry 4.0 as Policy-Driven Discourse to Institutionalize Innovation Systems in Manufacturing. Technological Forecasting and Social Change, Volume 132, pp. 26–33.

Saddik, A.El., 2018. Digital Twins: The Convergence of Multimedia Technologies. IEEE MultiMedia, Volume 25(2), pp. 87–92

Schwab, K., 2020. The Fourth Industrial Revolution: What It Means and How to Respond. Moscow. Eksmo, p. 208 (Top Business Awards)

Serdyukov, R.D., 2020. Conceptualization of the Concept of “Digital Double” in the Industrial Segment of the Economy. In: The Collection: Digital Economy and Industry 4.0: Foresight Russia. Proceedings of the Scientific-Practical Conference with Foreign Participation. St. Petersburg Polytechnic University of Peter the Great, pp. 250–258

Shpak, P.S., Sycheva, E.G., Merinskaya, E.E., 2020. The Concept of Digital Doubles as a Modern Trend in the Digital Economy. Bulletin of the Omsk University, Series: Economics, Volume 18(1), pp. 57–68

Suryanegara, M., Harwahyu, R., Asvial, M., Setiawan, E.A., Kusrini, E., 2019. Information and Communications Technology (ICT) as the Engine of Innovation in the Co-Evolution Mechanism. International Journal of Technology, Volume 10(7), pp. 1260–1265

Tikhonov, A.I., Stulov, A.V., Snitko, I.S., Similar, A.V., 2020. Development of 2D-Models of the Magnetic Field for the Implementation of Digital Twin Technology and Generative Design of Power Transformers. Bulletin of the Ivanovo State Energy University, Volume 3, pp. 32–43

Tsekhla, S.Yu., Simchenko, N.A., 2020. Methodological Aspects of the Study of the Economic Effects of the Introduction of Digital Doubles in Industry. Bulletin of the South Russian State Technical University (Novocherkassk Polytechnic Institute), Series: Socio-economic Sciences, Volume 13(2), pp. 35–39

Zezulka, F., Marcon, P., Bradac, Z., Arm, J., Benesl, T., Vesely, I., 2018. Communication Systems for Industry 4.0 and the IoT. IFAC-PapersOnLine, Volume 51(6), pp. 150–155