|Tatyana Golovina||Department of Management and Public Administration Central Russian Institute of Management, Branch of RANEPA Orel, 302028, Russia|
|Andrey Polyanin||Department of Management and Public Administration Central Russian Institute of Management, Branch of RANEPA Orel, 302028, Russia|
|Alexander Adamenko||Department of Accounting Theory, Federal State Budgetary Educational Institution of Higher Education (Kuban State Agrarian University named after I.T. Trubilin), Krasnodar, 350044, Russia|
|Elena Khegay||Department of Management, Far Eastern Federal University, Vladivostok, 690922, Russia|
|Vladimir Schepinin||Peter the Great St. Petersburg Polytechnic University, St. Petersburg, 195251, Russia|
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.
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