Digital Twin of Organization, DTO

A digital twin is a virtual prototype of real production assets - a well, a turbine, a wind electric plant, etc. This is a complex software product, it is created on the basis of a wide variety of data and using numerous IoT sensors. The digital model helps to change the operating parameters of the equipment and make improvements much faster and safer than when experimenting on real objects.

Digital Twin significantly expands the capabilities of cloud analytical services used in the concept of the industrial Internet of Things (IIoT) of the fourth industrial revolution.

Evolution of DT

digital representation to meet the requirements of a set of use cases - IIC

Digital Twin - a digital model of a specific physical element or process with data connections that provides convergence between physical and virtual states at the appropriate synchronization rate (Digital Twin - digital model of a particular physical element or a process with data connections that enables convergence between the physical and virtual states at an appropriate rate of synchronization) - ISO 23247

Digital Organization Twin

The digital counterpart of the organization is a model that describes as accurately as possible the real causal relationships between the production, economic, financial and organizational indicators of the Company

Objectives - to support the adoption of optimal management decisions at the stages of planning, monitoring and analysis of both the Company as a whole and individual areas of activity (functional blocks, programs/projects, assets, etc.)

Some applications of the organization's digital twins are:

• Value Chain Cost Management
• Digital Transformation Program Management
• Asset Development Management
• Integrated production and economic planning based on standards
• Investment Planning/Project Portfolio Management/Innovation Management
• Risk Management

Digital twin in device lifecycle

Digital Twin is used at all stages of the product life cycle, including development, manufacture and operation.

Already at the stage of sketch design using a digital twin, it is possible to create variations of the system model of the product being developed for evaluation and selection from various versions of technical solutions. Further, at the FEED stage, the model obtained at the previous stage can be refined and refined using more accurate system models of elements, which in turn can be obtained through numerical modeling, integration of embedded software and control interfaces is possible, and much more. This multi-physical accurate system model allows you to take into account and optimize the interaction of all elements, taking into account the operating modes and environmental impacts.

At the manufacturing stage, the developed system model (which can already be called a digital product twin) will help in determining the required tolerances, manufacturing accuracy for compliance with the characteristics and trouble-free operation of the product during the entire service life, as well as quickly identify the causes of malfunctions during testing.

When moving to the product operation stage, the digital twin model can be modified and used to implement feedback with the development and manufacture of products, diagnostics and forecasting of malfunctions, increasing the efficiency of work, recalibration, identification of new consumer needs.

An important aspect of the successful use of digital twins is that the development of devices and systems should be carried out with this concept in mind, which will significantly affect the construction of business processes of the enterprise and the creation of new service services.

Digital Twins in Healthcare

• Digital Twins in Healthcare

Applications

Digital twins have found their application in a wide variety of fields. One of their most important functions is to improve production processes. Using digital twins, companies can in a digital environment create copies of their smart enterprises, identify bottlenecks (in components, systems, processes and other assets), test potential solutions, model the results of interactions between components, and predict stochastic changes that can occur during operations. This simulation saves organizations the time, resources, and money they need to test working hypotheses in practice.

Digital doubles have also found their place in industrial design and product testing. Take, for example, a jet engine mounted on one of the most popular aircraft: Several thousand individual components first come together and then undergo extensive control tests to check the safety of the engine as a whole. But now the manufacturer does not have to collect an expensive physical sample of an aircraft engine, it can replace it with a digital twin - an exact three-dimensional copy. It is it that is properly analyzed, evaluated and tested according to the current requirements. Moreover, a digital twin can be created for an engine that is already in service to analyze the state of its components and calculate predictive maintenance^[1].

The most effective use of digital twins is for products with the following criteria:

• Product support by qualified specialized service (condition control, monitoring, technical support)
• Long product life cycle (5.. 70 years)
• Large number of installed equipment
• Wide range and variety of operating conditions
• Inaccessibility of the product for maintenance

This is a very extensive list of criteria under which products from various industries fall, such as:

• power engineering (nuclear, oil and gas, turbomachine engineering);
• aircraft engines and systems;
• complex industrial equipment (pumps, drives, etc.);
• rail and road transport systems;
• medical equipment.

Digital Production Twin

Opportunities

• Real-time display of equipment status on the 3D model of the shop floor
• Additional indication and inscriptions on the model
• Ability to display full kinematics of nodes

For guidance

• Tool for operational control of significant production indicators
• Possibility of making operational and balanced management decisions

For employees

• Shop Floor Visualization as a Lean Manufacturing Tool
• Reduction of response time of service and repair services
• Encouraging competitive spirit
• Easy maintenance of multiple machines by one operator

2024: Russia has created a digital double of an employee at work. That he can

At the National Research University, ITMO created a digital double of a worker in production. Thanks to the new technology, it will be possible to reduce the number of industrial injuries and equipment breakdowns, the press service of the Platform of the National Technological Initiative (NTI) reported at the end of April 2024. Read more here.

2023: Where digital doubles are most commonly used. Top-6

The global digital twin market grew by 71% from 2020 to 2022. At the same time, almost two-thirds of enterprises (about 63%) implement such solutions or plan to develop them. This is stated in the report of IoT Analytics, published on March 7, 2023.

The published data are based on the analysis of 100 different projects in the area under consideration. It is noted that many digital transformation initiatives include the creation of digital twins - copies of physical objects or processes: this approach helps to optimize business efficiency and accelerate innovation. As of the end of 2022, approximately 29% of manufacturing companies worldwide have fully implemented or implemented a digital twin strategy for some of their operating assets.

In general, IoT Analytics defines the concept of digital twins as a virtual model that reproduces the behavior of an existing or potential real asset, system, or several systems. At the same time, six main areas of application of such solutions are distinguished: system forecasting, system modeling, interoperability of assets, maintenance, visualization and product modeling. In some cases, digital twins can solve problems in several directions.

1. System prediction

This group includes about 30% of the projects analyzed. In this case, digital twins are used to predict entire systems - for example, part or all of a plant, building, power plant, or even a city. Virtual copies of objects help determine the behavior and future state of a physical system based on current data and past event records.

2. System modeling

Such initiatives account for approximately 28%. Modeling complex systems allows engineers to test all kinds of scenarios according to the "what happens if" scheme. In this case, a huge number of various parameters and variables can be taken into account. Examples of use - modeling enterprises before opening or making significant changes, virtual deployment of the railway network or transport infrastructure in the metropolis.

3. Interoperability of assets

Approximately every fourth (24%) project meets the criteria for this category. These digital twins simplify and streamline common data formats and allow standardizing the I/O of metrics during the operation or optimization phase of an object. Moreover, you can extract various data from assets in real time.

4. Maintenance

The main task of such digital twins, which account for 21%, is to help the system during the maintenance stage. Often such models include certain forecasting functions. Such solutions are mainly designed to ensure the operational efficiency of the facility.

5. Visualization

Approximately 20% of the analyzed digital twin projects are focused on visualizing the system at the stage of its operation. Among the most common types of visualizations used are three-dimensional elements that help you get an idea of ​ ​ the work of a particular object or service.

6. Product modeling

These decisions accounted for 9%. Digital twins play a key role in the development of new and improved products. The main use case is the modeling of various elements and structures in the virtual space, which eliminates the need to create expensive prototypes and allows you to quickly test thousands (and in some cases millions) of product options.^[2]

Service by actual condition

At the beginning of 2018, during the operation of equipment, there are three main strategies for managing its maintenance and repair (MR):

• event maintenance (TOC) or reactive maintenance;
• scheduled preventive maintenance (WEP);
• Service by actual condition (OPS).

Event maintenance involves the replacement of failed parts upon their breakdown, which often increases the cost of repair and the time of forced downtime during work.

Scheduled preventive maintenance is the most common type of maintenance to date and involves the replacement of parts at certain time intervals, which are determined by calculating the average time between failures.

The most advanced type of maintenance is maintenance by actual condition. It implies the elimination of equipment failures by interactive assessment of the technical condition of the equipment based on a set of data received from its sensors and determination of the optimal timing of repair work.

According to the Ministry power engineering specialists USA (2017^[3]key performance indicators for the use of OTS can achieve the following indicators:

• Maintenance costs, -25%.
• Elimination of accidents, -70%.
• Unplanned downtime, -35%.
• Performance, + 20%.

The digital twin is one of the OPS tools that allows you to simulate various options for complete and partial failures, the operation of devices taking into account their operating modes, environmental effects and various degrees of wear of parts.

Ontological models

Main article: Ontological models

How the concept of digital twins can change supply chains

According to a 2019 Gartner survey, 13% of Internet of Things (IoT) project organizations use digital twins, while 62% are in the process of implementing digital twins.

In the past, supply chains were built on the basis of the principles when the plant produced goods and sold them through the supply channel. This created a gap between supply and demand and inevitably led to poor inventory management, leading to shortages and waste. In 2020, it became possible to create a digital version of the supply chain. Using strategically unified computing environments and technologies, Industry 4.0 the digital supply chain moves assets, people and resources to where they are needed. By transferring data through cloudy servers databases and collecting in information the supply chain, it improves some manufacturing practices.

For example, manufacturers can conduct stress tests of their supply chain. Users can effectively manage stress and measure response by combining stress parameters with reaction readings. The digital twin could help transform the company's stresses into a quantitative view of real-world consequences, such as the effects of supplier delays.

Digital Supply Chain Twin

So what is a digital supply chain twin? It is a digital representation of the organization's real supply chain. His model uses predictive analytics, which collects data from both descriptive and predictive sources, to find the best course of action in any scenario before applying it to the decision-making process.

Using prescriptive models that work with real data, the digital supply chain twin extends this capability as input is input to the model in real time. For example, when a sales order is processed, the order and its associated transactions are automatically transferred to a digital twin.

However, to fully reflect the real world, other factors affecting the supply chain are taken into account. For example, if production equipment fails or supplies are delayed, information is sent to the digital twin through IoT devices such as sensors. After data matching, the digital twin determines the correct corrective action and supports supply chain optimization.

Predictive service

The performance of equipment in the supply chain is critical. Machines that regularly fail have detrimental effects, especially when downtime must be avoided at all costs.

3D modeling of the necessary equipment can be used for service maintenance. It combines machine learning to create a digital twin, which is used to monitor equipment performance, before running the algorithm in real time. Data derived from the 3D model combined with artificial intelligence (AI) is then used to maintain the equipment. The introduction of AI forecasting algorithms allows enterprise managers to apply forecasting strategies to their supply chain. By detecting failure patterns and anomalies, studying these models, and then predicting future machine component failures, manufacturers can replace equipment before it fails.

Digitalization Rollout

To optimize performance, however, the digital twin must reflect any limitations and consider trade-offs in its physical supply chain.

Modeling and predictive analytics are major components of the digital supply chain twin and should include programming languages to address these issues, such as the Fifth Generation Programming Languages (5GL). This important software enables operators to obtain detailed information about the supply chain, its structure, and formulas to optimize decision-making.

For example, Fleetpride, a U.S. firm that sells parts and provides heavy truck and trailer services, built a model that uses historical delivery data to predict warehouse delivery orders by day, week and month. By applying solution optimization to your model, you can define corrective actions when working with customers, people, and even when placing inventory on any given day. In fact, the company uses predictive analytics to translate data and forward-looking decisions into real, fact-based action plans. They no longer rely on intuition and use advanced analytics, statistical modeling, and decision-making to solve business planning, scheduling, pricing, and inventory problems, and other businesses have the ability to do the same.

Internet of Things

The idea of ​ ​ a digital twin is not new, but the concept of integrating data and input data from the real world differs. Devices connected to the Internet of Things are the building blocks of a digital twin, and sensor integration is key to ensuring that data is available.

However, the design and integration of these sensors may require considerable resources and time, and it may be difficult to transfer data from older machines that are not technologically compatible. ^[4]

Hybrid twin

Hybrid twin is a technological type of hardware and software solutions of the digital twin class, based on combining simulated numerical modeling technologies with machine learning technologies and using this data in real time using the Internet of Things.

This approach appeared in the scientific environment and was implemented by ESI in the 2000s.

Complex twin

A complex twin is a combination of all known technologies for aggregation, modeling, analysis, orchestration and visualization of data, which allow solving the problems of predictive asset service, product quality, as well as optimal operation of equipment and organization of deserted production. It is a further development of the hybrid twin.

History

2024

An entire Russian city has a digital double

The city of Noyabrsk in the Yamalo-Nenets Autonomous Okrug has a digital twin in the form of a 3D map containing databases on real estate, land, communications and transport infrastructure. This became known on June 29, 2024. Read more here.

Engineers of the St. Petersburg Polytechnic applied the technology of digital twins in railway engineering

Specialists Scientific of the world-class center "Advanced Digital Technologies" St. Petersburg Polytechnic University Peter the Great (NCMU SPbPU) first used digital engineering methods and technology digital twins in the development of elements of railway rolling stock. transport The work is carried out on the basis the Russian of development - a digital platform for the development and use of digital twins. This was CML-Bench announced on March 15, 2024 by representatives of SPBPU. More. here

2023

Global Digital Twin Software Market Size Estimated at $12.81 Billion for the Year

At the end of 2023, the volume of the global digital twin market reached $12.81 billion. In the future, this industry expects rapid development, as stated in the report of Verified Market Research, published on March 29, 2024.

The study notes that digital twin technologies are increasingly being used in a variety of fields. For example, during the design and development phases, such tools simplify the prototyping, modeling, and testing of products and systems. Throughout the asset lifecycle, digital twins help organizations track and manage the performance of hardware, infrastructure solutions, and more. In addition, predictive maintenance becomes possible: twins simulate the actions and functionality of physical systems using data collected in real time.

Verified Market Research analysts believe that the digital twin industry will demonstrate CAGR (compound percentage CAGR) at 39.8% until 2030. As a result, by the end of this period, global costs in this area can reach $274.2 billion.

At the same time, the report names several factors that restrain the development of the market. This is, in particular, complexity and cost: the introduction of digital twin technology entails significant costs for hardware installation, software development and maintenance. In addition, there is a need to provide additional protection of corporate data and prevent possible leaks of confidential information. It is often difficult to integrate digital twins into the existing IT infrastructure of the enterprise. Plus, there is a shortage of qualified specialists. Another obstacle is the insufficient development of industry standards.^[5]

How digital doppelgangers help plan urban environments. 4 top trends

Digital twins can revolutionize the planning of the urban environment, increasing its efficiency and safety. Virtual models using artificial intelligence and machine learning technologies are used to analyze and determine how certain changes can make megacities more comfortable for life and work. In early October 2023, GIM International analysts named four main trends in geospatial urban planning based on digital twins.

1. Road modeling

As cities become increasingly populated, traffic congestion management is critical to maintaining mobility. By creating highly detailed virtual copies of metropolitan spaces, specialists can visualize the domino effects resulting from congestion. In particular, digital twins allow the simulation of new truck unloading/loading areas with real-time traffic data. At the same time, AI-based algorithms help identify alternative routes for large commercial vehicles, reducing the load on the main highways. It becomes possible to introduce smart traffic lights that dynamically adapt to the current situation: the switching time from the permitting signal to the prohibiting signal and vice versa is calculated based on many factors, such as the time of day, day of the week, road works carried out, accident sites, etc. Digital twins also help predict the consequences of various infrastructure projects and assist in training drivers who have to deliver goods or carry out passenger transportation.

2. Noise Pollution Map

Digital twins make it possible to simulate noise levels from various objects and vehicles in an urban environment, which contributes to effective decision-making. For example, virtual models show exactly what sound impact trams have on residential buildings, offices and public institutions. Potential tenants or buyers of apartments can use this information in advance to determine how noisy the room will be at a certain time of day. In turn, urban transport designers can use the same model to determine the best routes in order to reduce noise impact. Developers can decide to use soundproofing materials that will protect homes, hospitals and schools from noise pollution.

3. Planning the construction of skyscrapers

Due to the high cost of land in densely populated cities, developers are forced to build high-rise buildings. At the same time, digital twins allow you to assess a variety of effects from construction: the potential impact of skyscrapers on the visibility of existing buildings and the quality of life of citizens, the impact on the existing transport infrastructure, the availability of parking areas, etc. Virtual models make it possible to quickly calculate the economic effect, for example, from increasing or decreasing the number of storeys of a building, adding a penthouse, etc.

4. Event Planning

Based on digital twins, organizers of various events can create detailed and accurate virtual models of venues. For example, you can determine the most suitable seating areas, calculate the optimal acoustic parameters and placement points for lighting fixtures, and simulate ticket sales areas, entrances, and exits. In addition, security is increased thanks to a detailed study of evacuation plans, routes for the arrival of police squads, ambulances and fire engines. Digital twins even help program sophisticated pyrotechnics or drone shows.^[6]

Create a laboratory to develop digital material twins for photonics

On September 1, 2023, it became known about the creation on the basis of the Perm State National Research University (PGNIU) of the laboratory "Computational Materials Science in the Field of Photonics and Quantum Technologies." As part of this initiative, scientists will be engaged in the creation of digital doubles of materials for photon integrated circuits, optical fibers, single-photon emitters and other photon devices. Read more here.

Digital "SKIF." Why does a scientific megaproject worth 47 billion rubles create a virtual double

At the end of August, 2023 it became known of creation of the digital double of experimental stations of the Siberian Ring Source of Photons (SRSP). Mikhail Marchenko, director of the Institute of Computational Mathematics and Mathematical Geophysics of the Siberian Branch of the Russian Academy of Sciences (IVMiMG SB RAS), spoke about the benefits of such an IT project . Read more here.

In Tomsk, launched the first of its kind installation for creating digital twins of aircraft engines

The Tomsk Polytechnic University (TPU) has launched unique equipment for testing aviation fuel for Russia. Thanks to the new installation, scientists will be able to find the most effective fuel compositions, as well as create digital twins of propulsion systems, the press service of the university said. Read more here.

The first school with smart climate control created with the help of a digital double of the building has opened in Russia

The first school with smart climate control, created using the building's digital twin, has opened in Russia. This was announced in early February 2023 in the development group "Airplane," which implemented this project. Read more here.

2022

Russian vegetable oil manufacturer Blago creates digital doubles of its plants

The Russian manufacturer of vegetable oils "Blago" creates digital twins of its plants. To do this, the group entered into an agreement with Sberbank. Read more here.

In Russia, created a digital twin of space to control satellites

At the end of December 2022, it became known about the creation in Russia of a digital twin of space, which helps to control satellites. This is the development of the Central Research Institute of Mechanical Engineering (TsNIImash), part of the state corporation Roscosmos). Read more here.

2021

Russia is the first in the world to approve standards in the field of digital twins

In mid-September 2021, Russia was the first in the world to approve standards in the field of digital twins. The corresponding document, approved by Rosstandart and put into effect on January 1, 2022, was called "Numerical Modeling" - GOST R 57700.37-2021 "Computer Models and Modeling. Digital product twins. General provisions. "

The national standard in the field of digital product twins will apply to mechanical engineering products, but if necessary, standards may be developed on its basis that establish the requirements for digital product twins in various industries.

The standard is the first in a series of national and industry regulatory technical documents that will determine the procedure for developing digital twins, standard requirements for the structure and procedure for their maintenance during the operation of the product, the procedure for accounting and storage, etc.

The standard is a completely domestic development. In particular, for the first time in world practice, a single definition of "digital product twin" is established - "Digital product twin: A system consisting of a digital product model and bilateral information relations with a product (if there is a product) and (or) its components." Also, within the framework of the standard, the following concepts were standardized for the first time: "digital (virtual) tests," "digital (virtual) test bench" and "digital (virtual) test site."

The new standard was developed by a working group led by the Center NTI "New Production Technologies" Peter the Great St. Petersburg Polytechnic University (SPbPU) and the Federal State Unitary Enterprise "Russian Federal Nuclear Center -) All-Russian Research Institute of Experimental Physics (FSUE RFNC-VNIIEF) as part of the activities of the Technical Committee No. 700" Mathematical Modeling and High-Performance Computing Technologies "(TK 700).^[7]

Google unveils digital doppelganger tool in logistics and manufacturing

On September 14, 2021, Google announced the release of Supply Chain Twin, a new cloud solution that allows companies to create digital twins. Read more here.

250 Russian enterprises will switch to digital twin technologies by 2024

250 Russian enterprises will switch to digital twin technologies by 2024. This became known on June 30, 2021.

Digitalization of production has become the main focus of the Technet 4.0 roadmap, developed with the participation of the Technet Association and the expert community. It is planned that by 2035 Russia will export products created using advanced production technologies for 800 billion rubles. And the country's share in the world markets of "factories of the future" will reach 1.5%, the press service of the Association reports.

In addition, the plan for the development of digital production provides for the following goals:

• 20 service providers to create "factories of the future" will be included in the top 50 leading technology companies in Russia;
• the number of "factories of the future" "Technet" NTI will grow to 30;
• the number of test sites (TestBeds) will increase to 25;
• additional experimental digital certification authorities will open;
• 50 thousand specialists will undergo training and retraining programs on BSA.
• In addition, by 2024, more than 250 Russian enterprises will switch to digital twin technologies. In the next three years, a network of "factories of the future" should be formed throughout the country, which will then enter global markets. As of June 2021, there are 6 such factories in Russia.

The updated "road map" "Technet" NTI sets two global goals:

1. Formation of a set of key competencies in the country, ensuring the integration of production technologies and business models for their distribution as "factories of the future."
2. Create globally competitive personalized latest generation products for NTI markets. And also - for high-tech industries. industries

The first edition of the "Technet roadmap" NTI was approved back in February 2017. In 2021, the updated Technet 4.0 roadmap (advanced production technologies) of NTI was approved at a meeting of the NTI Interdepartmental Working Group under the Government Commission for Economic Modernization and Innovative Development of ^[8] Russian Federation^[9].

Create digital road object twins using Avtodiscaveri

At the end of April 2021, the Urbantech company announced a software and hardware complex designed to create digital twins and monitor the state of road transport infrastructure facilities. A system called Avtodiskaveri was created as part of the Digital Roads project. Read more here.

Digital Twins: A Practical Approach

In March 2021, Alexander Semenov, Deputy Director for New Markets at Reksoft, spoke about the possibilities of using digital twins. Read more here.

Digital twin of the Northern Sea Route is being created in Russia

In mid-January 2021, it became known about the creation of a digital twin of the transport system of the Northern Sea Route (NSR, the shortest sea route between the European part of Russia and the Far East). This project is jointly implemented by the Far East Development Fund (FRDV), ВЭБ.РФ, the Ministry for the Development of the Russian Far East and Lomonosov Moscow State University. Read more here.

2020

MarketsandMarkets: Global Digital Twin Market Valued at $3.1 Billion

The global digital twin market is valued at $3.1 billion at the end of 2020, and by 2026, it is expected to grow to $48.2 billion. According to analysts, spending on digital twin projects will increase by an average of 58% per year. The rise in demand for digital twins is mainly caused by the outbreak of the COVID-19 pandemic, as well as the changing nature of medical care, according to a study by MarketsandMarkets.

Among the main players in the digital doubles market at the end of 2020:

• General Electric (USA);
• IBM (USA);
• PTC (USA);
• Microsoft Corporation (США);
• Siemens AG (Germany);
• ANSYS (USA);
• SAP (Germany)
• Oracle (USA);
• Robert Bosch (Germany);
• SWIM.AI (USA).

As reported in a study published in November 2021, North America has the largest share in the digital twin market. In recent years, the development of various software and implementation of automation solutions in the manufacturing industry have improved production lines and related operations. These developments positively impacted market growth North America in due to high economic growth rates and a large number of suppliers offering digital twins. Moreover, the growth RESEARCH AND DEVELOPMENT in the region, IoT as well as the growing demand for efficient and cost-effective technologies for the production of products, also support the growth of the regional market.

In 2019, the automotive and transportation industry accounted for the largest share of the digital twin market. Experts explain this situation by the increase in the use of digital twins for design, modeling, maintenance, repair, production and after-sales car services. Automotive and transport are one of the industries that will see high growth in the introduction of digital twins in the post-COVID-19 period, as industry players will try to use digital solutions for their end-to-end operations to minimize the losses that have occurred due to the pandemic.

The digital twin plays an important role in monitoring the patient's health, in particular the effects of drugs on the body. A special interest in this technology was revealed in the medical industry against the background of COVID-19. For example, French startup Exactcure, which is developing a software solution to reduce medication errors, developed a product using digital twins to reduce exposure to improperly dosed drugs. With this technology, the effectiveness and interaction of drugs in the patient's body is monitored based on his personal characteristics, such as age, sex and, for example, the condition of his kidneys. In addition, companies are increasingly investing in research and development related to new changes in daily life due to the COVID-19 pandemic. Thus, companies are trying to develop a solution based on digital twins to identify people who have symptoms of COVID-19 infection or recovered people with antibodies, as well as people who have come into contact with an infected person. Using such solutions, the authorities of a particular country could easily control the green and red zones. Also, such solutions can be effectively implemented in smart cities.

Due to COVID-19, industry participants face many health and safety issues, supply chain, supplier sustainability, labor shortage, etc. These problems can be solved using digital twins, however, many companies still do not have a specific plan to implement these technologies for product management, and they are not yet making significant investments in this area, since they are not confident in economic benefits, and profitability in the near future.^[10]

Digital doubles of workers appeared at construction sites in Moscow

As it became known on December 8, 2020, digital doubles of workers appeared at the construction sites of Moscow. This is a joint project of the metropolitan departments of urban planning policy and information technologies, as well as the National Research Technological University "MISiS." Read more here.

Ministry of Digital Development: Digital doubles of documents of Russians will appear in 2021

In early November 2020 Ministry of Digital Development, Communications and Mass Media of the Russian Federation , it announced the appearance of electronic duplicates of documents in the country. They are expected to be available in 2021 of the Federation Council , the head said during a meeting of the economic policy committee. Ministry of Digital Development RUSSIAN FEDERATION Maksut Shadayev More. here

Rostec began creating digital twins of aircraft engines integrated into production

On October 23, 2020, Rostec announced the creation of digital counterparts of the second level of TV7-117 aircraft engines. The state corporation is implementing this project together with St. Petersburg Polytechnic University. Read more here.

The start of the creation of a "digital double" of St. Petersburg

On September 7, 2020, the Governor of St. Petersburg, Alexander Beglov, announced the beginning of the creation of a "digital twin" of the city, which will allow monitoring the state of city facilities. To do this, the Internet portal "Certification of objects of improvement of St. Petersburg," which contains data on 15 million objects of the urban environment, will receive the status of a state information system (GIS) and will be renamed "Objects of the urban environment of St. Petersburg." Read more here.

Digital doubles will appear in all major cities of Kuzbass

On June 29, 2020, the Deputy Governor of Kuzbass for Economic Development Konstantin Wenger announced that by the end of 2021, digital twins of all major cities in the region will be created - namely, 20 municipalities. Read more here.

See also

• Smart Computer System as a Human Replacement
• Imitation versus intuition: how mathematical modeling services make life easier for businesses

Notes