IBM will introduce the latest cloud technologies and the Internet of Things in the Port of Rotterdam.

In the near future, the port of Rotterdam is expecting a new record: it will become not only the largest European port in terms of cargo turnover, but also the smartest port in the world. And IBM will help him in this.

Joint efforts will be focused primarily on the implementation of the system "Connected shipping"(connected shipping), similar to connected cars in the automotive industry. Vessels with access to the system are autonomously operated and communicate for safe navigation. According to the administration of the Port of Rotterdam, they plan to receive the first autonomous vessels in 2025.

The digitalization program is designed for several years. As a result, the 42-kilometer territory of the port will be organized into a single digital space with the help of cloud technologies IBM Cloud and the Internet of Things IBM IoT, and the port of Rotterdam will be rightfully called the smartest port in the world.

To build such a system, a port digital twin- an accurate digital model of all operations, which will accurately reflect resources and port capacities, ship movements, infrastructure, weather, geographic and hydrological conditions with 100% accuracy.

More than 140 thousand ships pass through the port annually; many stakeholders are involved in the cargo handling process. The digital model will allow you to see the big picture, test port scenarios and better coordinate the actions of all participants using a centralized control panel. This will increase the speed of port operations and the volume of cargo handled, as well as ensure compliance with the most stringent security standards. In the end the time spent by the vessel in the port will be reduced by an average of 1 hour... For port operators, this translates into order savings. USD 80,000, and for the port - in increasing the number of ships received.

The port will use IoT and Augmented Intelligence technologies, as well as intelligent meteorological and hydrological data, with which carriers can determine the most favorable time to enter the Port of Rotterdam. Favorable navigation conditions allow to save fuel, optimize approach and mooring speeds and ensure better cargo safety.

For this purpose, berths and buoys will be equipped with Digital dolphins- intelligent sensors that provide support for cargo transshipment, record vacancy or occupancy of mooring terminals, generate data on the status of port operations at a particular point in time, and also monitor environmental conditions that directly or indirectly affect navigation. Digital dolphins will be self-learning, and their real-time readings are claimed to be 100% accurate. The port plans to transmit this information to users through a specially developed application for planning and controlling operations.

Another initiative of the Port of Rotterdam is the creation of a Production Support Laboratory (RAMLAB). Its goal is to supply shipyards with quality industrial parts on demand. This is the first 3D printing laboratory focused on ports and sea carriers, able to reduce the waiting time for the desired part from 1.5-2 months to several days.

Speed ​​and efficiency are the top two strengths of any port - Paul Smits

“Speed ​​and efficiency are the two main strengths of any port,” says Paul Smits, Chief Financial Officer of the Port of Rotterdam Authority. “They are the ones that attract business and allow us to increase cargo turnover.” It is obvious that the innovations of the Port of Rotterdam directly serve to achieve these two goals.

Neural networks, digital twins, artificial intelligence. Industry 4.0 technologies will change the oil industry beyond recognition

Architects of the digital age

Spheres are usually considered the most technologically advanced. information technologies and biomedicine. Companies in traditional industries, such as metal rolling or oil production and refining, are treated differently. At first glance, they seem conservative, but many experts call them the main architects of the new digital age.

Industrial giants began to automate production processes back in the mid-30s of the last century. Over the decades, hardware and software complexes have been continuously improved and complicated. Automation of production processes - for example, in oil refining - has advanced far ahead. The operation of a modern oil refinery is monitored by hundreds of thousands of sensors and instruments, and fuel supplies are monitored in real time by satellite navigation systems. Every day the average Russian refinery produces over 50,000 terabytes of information. For comparison, 3 million books that are stored in the digital storage of the Russian State Library take hundreds of times less - "only" 162 terabytes.

This is the very same "big data", or Big Data, - a stream comparable to the information loading of the largest sites and social networks... The accumulated data array is a unique resource that can be used in business management. But traditional methods of information analysis are no longer suitable for this. Truly efficient work with such a volume of data is possible only with the help of Industry 4.0 technologies. In the context of a changing economic paradigm, rich production "historical experience" is a significant advantage. Big data is at the heart of artificial intelligence. His ability to learn, understand reality and predict processes directly depends on the amount of loaded knowledge. At the same time, industrial companies have a powerful engineering school, are actively involved in the implementation and improvement of new technologies. This is another circumstance that makes them key players in the "new economy".

Best of the week

Finally, domestic industrialists know the price of business efficiency. Russia is a country of great distances. Often, production assets are located at a great distance from consumers. In these conditions, it is very difficult to quickly respond to market fluctuations. Traditional technologies allow you to save no more than a tenth of a percent. Meanwhile, digital solutions today allow you to reduce costs up to 10-15% per month. The fact is obvious: in the era of the fourth industrial revolution, the one who learns the most effective use of new technologies in terms of accumulated experience will be competitive.

Petr Kaznacheev, Director of the Center for Raw Materials Economy, RANEPA: “Smart management and corporate planning could be considered as a first step towards an“ integrated ”artificial intelligence system in oil and gas. In this case, we could talk about creating an algorithm for digitizing all key information about the company's activities - from a field to a gas station. This information could be fed to a single automated center. Based on this information, using artificial intelligence methods, forecasts and recommendations for optimizing the company's work could be made. "

Leader of digital transformation

Recognizing this trend, industrial leaders in Russia and the world are rebuilding business processes that have developed over decades, introducing Industry 4.0 technologies into production based on the industrial Internet of things, artificial intelligence and Big Data. The most intensive transformation is taking place in the oil and gas industry: the industry is dynamically “digitalizing”, investing in projects that seemed fantastic just yesterday. Plants controlled by artificial intelligence and capable of predicting situations, installations that prompt the operator to the optimal mode of operation - all this is already becoming a reality today.

At the same time, the maximum task is to create a production, logistics, production and sales management system that would unite smart wells, factories and gas stations into a single ecosystem. In an ideal digital model, the moment the consumer presses the lever of the fuel nozzle, the company's analysts in the operations center instantly receive information about what brand of gasoline is being filled into the tank, how much oil needs to be produced, delivered to the refinery and processed to meet the demand in specific region. So far, none of the Russian and foreign companies have managed to build such a model. However, Gazprom Neft has advanced the farthest in solving this problem. Its specialists are currently implementing a number of projects, which ultimately should become the basis for creating a unified platform for processing, logistics and sales management. A platform that no one else in the world has yet.

Digital twins

Today Gazprom Neft's refineries are among the most modern in the industry. However, the fourth industrial revolution opens up qualitatively new opportunities, while simultaneously presenting new requirements for automation. More precisely, it is not so much about automation as about the almost complete digitalization of production.

The basis of the new stage will be the so-called "digital twins" - virtual copies of refinery installations. All processes and relationships that take place in real prototypes are accurately described in 3D models. They are based on the work of artificial intelligence based on neural networks. The "digital twin" can suggest optimal operating modes for equipment, predict its failures, and recommend repair times. Among its other advantages is the ability to constantly learn. The neural network itself finds errors, corrects and remembers them, thereby improving its performance and forecast accuracy.

An array of historical information serves as the basis for training the "digital twin". Modern refinery installations are as complex as the human body. Hundreds of thousands of parts, tens of thousands of sensors. The technical documentation for each installation occupies a room the size of an assembly hall. To create a "digital twin", all this information must first be loaded into a neural network. Then the most difficult stage begins - the stage of teaching artificial intelligence to understand the installation. It includes readings from sensors and instrumentation collected over the past few years of the installation. The operator simulates various situations, makes the neural network answer the question "what will happen if one of the work parameters is changed?" - for example, replacing one of the raw material components or increasing the power supply to the plant. The neural network analyzes the experience of past years and excludes non-optimal modes from the algorithm using the calculation method, and learns to predict the future operation of the installation.

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Gazprom Neft has already fully digitized two industrial complexes involved in the production of automotive fuel - a catalytic cracking gasoline hydrotreater at the Moscow Oil Refinery and a plant operating at the company's oil refinery in Omsk. Tests have shown that artificial intelligence is able to simultaneously take into account a huge number of parameters of their "digital counterparts", make decisions and notify about possible deviations in work even before the moment when the trouble threatens to develop into a serious problem.

At the same time, Gazprom Neft is testing complex solutions that will minimize the impact of the human factor on the scale of the entire production. Similar projects are currently being implemented at the company's bitumen plants in Ryazan and Kazakhstan. Successful empirically found solutions can subsequently be scaled up to the level of large refineries, which ultimately will create an effective digital production management platform.

Nikolay Legkodimov, Head of Advanced Technologies Consulting Group, KPMG in Russia and the CIS:“Solutions that simulate various units, assemblies and systems have been known and used for a long time, including in the oil and gas industry. One can speak of a qualitative leap only when a sufficient breadth of coverage of these models has been achieved. If we succeed in combining these models with each other, combining them into a whole complex chain, then this will really allow solving problems at a completely new level - in particular, simulating the behavior of the system in critical, unprofitable and simply dangerous working conditions. For those areas where retooling and upgrading equipment is very expensive, this will allow preliminary testing of new components. "

Performance management

In the future, the entire value chain in the logistics, refining and sales block of Gazprom Neft will be united by a single technological platform based on artificial intelligence. The “brain” of this organism will be the Performance Management Center, created a year ago in St. Petersburg. It is here that information from the "digital twins" will flock, here it will be analyzed and here, on the basis of the data obtained, management decisions will be made.

Already today, in real time, more than 250 thousand sensors and dozens of systems transmit information to the Center from all the company's assets included in the perimeter of the Gazprom Neft logistics, refining and sales unit. Every second 180 thousand signals are received here. It would take a person about a week just to view this information. The digital brain of the Center does it instantly: in real time it monitors the quality of products and the quantity of petroleum products along the entire chain - from the exit from the refinery to the end consumer.

The strategic goal of the Center is to radically increase the efficiency of the downstream segment using the technologies and capabilities of Industry 4.0. That is, it is not just to manage processes - this can be done within the framework of traditional systems, but to make these processes the most effective: through predictive analytics and artificial intelligence at every stage of the business, reduce losses, optimize processes and prevent losses.

In the near future, the Center should learn how to solve several key tasks that affect the efficiency of business management. Including forecasting the future 60 days ahead: how the market will behave in two months, how much oil will need to be refined to meet the demand for gasoline at the current time, what state the equipment will be in, whether the installations will be able to cope with the upcoming load and whether it is needed repair them. At the same time, in the next two years, the Center should reach 50% capacity and begin to monitor, analyze and predict the amount of petroleum product reserves at all oil depots and refueling complexes of the company; in automatic mode monitor more than 90% of production parameters; analyze the reliability of more than 40% of technological equipment and develop measures to prevent the loss of oil products and a decrease in their quality.

By 2020, Gazprom Neft sets a goal to reach 100% of the capabilities of the Performance Management Center. Among the declared indicators - analysis of the reliability of all equipment, prevention of losses in quality and quantity of products, predictive management of technological deviations.

Daria Kozlova, senior consultant at VYGON Consulting:“In general, integrated solutions bring significant economic benefits for the industry. For example, according to Accenture estimates, the economic effect of digitalization could be more than $ 1 trillion. Therefore, when it comes to large vertically integrated companies, the implementation of integrated solutions is highly justified. But it is also justified for small companies, since improving efficiency can free them up additional funds by reducing costs, increasing the efficiency of working capital management, etc. "

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We would like to thank the editorial staff of the corporate magazine Sibirskaya Neft PJSC Gazprom Neft for providing this material.

What is a Digital Twin?

The digital twin is a new word in modeling and production planning - a single model that reliably describes all processes and relationships both at a separate facility and within a whole production asset in the form of virtual installations and simulation models. Thus, a virtual copy of the physical world is created.

The use of a digital twin, which is an exact copy of a real asset, helps to quickly simulate the development of events depending on certain conditions and factors, find the most effective modes of operation, identify potential risks, integrate new technologies into existing production lines, and reduce the time and cost of project implementation. In addition, the digital twin helps to define the steps to ensure safety.

Modern technologies make it possible to build digital twins of absolutely any production assets, be it an oil refinery or a logistics company. In the future, these technologies will allow remote control of the entire production process in real time. On the basis of the digital twin, it is possible to combine all systems and models used for planning and managing production activities, which will increase the transparency of processes, the accuracy and speed of decision-making.

The digital twin can also be considered as an electronic passport of a product, which records all data on raw materials, materials, operations performed, tests and laboratory research. This means that all information, from drawings and production technology to rules for maintenance and disposal, will be digitized and available for reading by devices and people. This principle allows you to track and guarantee the quality of products, to provide effective service.

From drawings to 3D models

A bit of history. Drawings and diagrams have always been needed by people, from the moment of the first inventions of the wheel and the lever, in order to transmit information to each other about the structure of these devices and the rules for their use. At first, these were primitive drawings containing only the simplest information. However, the designs became more complex and the images and instructions more detailed. Since then, technologies for visualizing, documenting and storing knowledge about structures and mechanisms have come a long way. However for a long time the main medium for fixing engineering thought was paper, and the working space was a plane.

In the second half of the twentieth century, it became clear that the usual army of draftsmen, armed with drawing boards, was no longer able to keep up with the rapid growth of industrial production and the complexity of engineering developments. Acceleration of the processing of voluminous and complex information (for example, a technological unit for atmospheric distillation of oil contains more than 30 thousand pieces of equipment) required changes in the work technology of designers, designers, builders, technologists, operation and maintenance specialists. The evolution of technical means of design has made another round, and in the early 90s of the last century computer-aided design systems (CAD) came to the oil industry. They first used 2D drawings, and then, towards the end of the 2000s, they came to 3D.

Modern design systems allow engineers to carry out the layout and design of industrial facilities in volumetric form, taking into account all the restrictions and requirements of the production process, as well as industrial safety requirements

Modern design systems allow engineers to carry out the layout and design of industrial facilities in volumetric form, taking into account all the restrictions and requirements of the production process, as well as industrial safety requirements. With their help, you can create a design model of a particular installation and correctly place technological and technical components on it without contradictions and collisions. Experience shows that through the use of such systems, it is possible to reduce the number of errors and inconsistencies in the design and operation of various installations by 2-3 times. The figure is impressive when you consider that for large-scale industrial equipment, the number of errors that have to be corrected during the design review process is estimated at thousands.

From the point of view of designers and builders, the use of 3D models makes it possible to dramatically improve the quality of design documentation and reduce design time. The constructed information model of the object is also useful at the stage of operation. This is a new level of ownership of an industrial facility, where personnel can obtain any information required to make a decision or complete a task in the shortest possible time, based on the existing model. Moreover, when, after some time, the modernization of equipment is required, future designers will have access to all relevant information, with a history of repairs and maintenance.

Omsk pilot

Sergey Ovchinnikov, Head of the Management Systems Department, Gazprom Neft:

The development and implementation of an engineering data management system is undoubtedly an important part of the innovative development of the logistics, processing and marketing unit. The functionality inherent in "SUPrID", the potential of the system will allow the block in particular and the company as a whole to become leaders in the digital management of engineering data in oil refining. Moreover, this software product is an important component of the entire line of related IT systems, which are the foundation of the BLPS Performance Management Center, which is currently being created.

In 2014, Gazprom Neft launched a project to create a system for managing engineering data for oil refining facilities - SUPrID. The project is based on the use of 3D modeling technologies for the design, construction and maintenance of industrial facilities. Thanks to their use, the time for the creation and reconstruction of oil refineries is reduced, the efficiency and safety of their operation is increased, and the downtime of the plant's technological equipment is reduced. Implementation modern system Engineering data management on the latest Smart Plant for Owners / Operators (SPO) platform is handled by specialists from the Department of Control Systems of the Logistics, Processing and Sales Unit, as well as from the subsidiary company ITSK and Avtomatika Servis.

At the end of last year, a pilot project was successfully completed to deploy the platform's functionality and set up business processes for the newly reconstructed primary oil refining unit at the Omsk Refinery - AT-9. The system implements the functionality for storing, managing and updating information about the installation throughout its entire life cycle: from construction to operation. Along with the system, regulatory and methodological documentation, requirements for the designer and standards for engineering data management were developed. "SUPrID" is a good assistant in the work, - said the head of the AT-9 unit at the Omsk Refinery Sergey Shmidt. - The system allows you to quickly access engineering information about any equipment, view its drawing, clarify technical parameters, localize the location and take measurements on a three-dimensional model that exactly reproduces the real installation. The use of "SUPRID" helps, among other things, to train new specialists and trainees. "

How it works?

The task of the SUPRID system is to cover all stages of the life cycle of a technological object. Start by collecting engineering information at the design phase and then updating the information at subsequent stages - construction, operation, reconstruction, displaying the current state of the facility.

It all starts with information from the designer, which is sequentially transmitted and loaded into the system. The initial data are: design documentation, information on the functional, technological and construction and installation structure of the facility, intelligent technological schemes. It is this information that becomes the basis of the information model, allowing you to instantly receive address information about construction objects and the technological scheme of the installation, making it possible in a few seconds to find the desired position of technological equipment, instrumentation and automation equipment on the technological scheme, to determine its participation in the technological process.

In turn, using the project 3D-model of the object loaded into the system, you can visualize it, see the configuration of blocks, the spatial arrangement of equipment, the environment with neighboring equipment, and measure the distances between various elements of the installation. The formation of the operational information model is being completed by linking as-built documentation and 2D and 3D models "as built", which provide an opportunity to obtain detailed information on the properties and technical characteristics of any equipment or its elements at the stage of operation. Thus, the system is a structured and interconnected set of all engineering data of an object and its equipment.

Roman Komarov, Deputy Head of the Department of Engineering Systems "ITSK", Head of Development "SUPrID":

After many years of assessing the benefits of the project and preliminary study, the pilot of the system was implemented in a short time. Implementation of "SUPrID" allowed the company to obtain a tool for managing engineering data of oil refining facilities. The next global step, which we will gradually approach, is the formation of a digital information model of an oil refinery.

To date, more than 80,000 documents have been uploaded to the SUPrID electronic archive. The system allows performing a positional search of relevant information about any type of equipment, providing the user with comprehensive information on each position, including specifications, overall dimensions, material design, design and operating parameters, etc. "SUPRID" makes it possible to view any part of the installation in a three-dimensional model or on a technological scheme, open scanned copies of documents related to this position: working, executive or operational documentation (passports, acts, drawings, etc.).

Such variability significantly reduces the time spent on access to up-to-date information and its interpretation, avoids mistakes during reconstruction and technical re-equipment of the facility, replacement of obsolete equipment. SUPRID helps to analyze the operation of the installation and its equipment in assessing the efficiency of operation, contributes to the preparation of changes in technological regulations, investigation of failures, malfunctions, accidents at the facility, education and training of maintenance personnel.

SUPRID is integrated with other information systems BLPS and forms a unified information environment for engineering data, which, among other things, will become the basis for the innovative Unit Efficiency Management Center. Interconnection with programs such as KSU NSI (corporate system for managing reference information), SAP TORO (maintenance and repair of equipment), SU PSD (design and estimate documentation management system) "TrackDoc", Meridium APM, forms a unique integrated automation system processes for managing the production assets of an oil refinery, allowing you to increase the economic effect of their joint use for the company.

Project efficiency

In a relatively short period of time, Gazprom Neft's IT specialists managed not only to master the intricacies of the SPO platform, on which the engineering data management system is built, but also to create a completely new infrastructure for the company, develop a set of regulatory documents, and ultimately develop a qualitatively new approach to construction of oil refining facilities.

At an early stage of the project, it became obvious that the system would be in demand by the plant's operational services and capital construction services. Suffice it to say that using it saves up to 30% of the time spent on searching and processing. technical information for any object. When integrating "SUPrID" with systems of normative and reference information, Maintenance and equipment repair, design and estimate documentation and other relevant engineering data become available for prompt and high-quality service of technological equipment. The system's capabilities also make it possible to create a simulator for maintenance services, which will undoubtedly increase the level of training of their specialists. For the capital construction departments of the refinery, the system will become a design tool at the stage of minor and medium repairs. This approach greatly simplifies control over the course of reconstruction of industrial facilities and improves the quality of repairs.

It is assumed that the investments made in the implementation of "SUPrID" will pay off in about 3-4 years. This will be possible due to the reduction in design time, earlier transfer of units from the stage of commissioning to commercial operation and, as a result, an increase in the volume of finished products. Another significant plus is the acceleration of the preparation and implementation of maintenance work and the implementation of reconstructions and upgrades of installations by reducing the time required for checking new design documentation by the refinery operating services and timely detecting shortcomings and errors in the work of design and construction contractors.

The "SUPrID" implementation program is designed for the period up to 2020. It will be used to digitize both existing installations and the construction of new facilities. At present, specialists are preparing to replicate the system at the Moscow Refinery.

Text: Alexander Nikonorov, Alexey Shishmarev,Photo: Yuri Molodkovets, Nikolay Krivich

More recently, German Gref, president of Sberbank, said that in 5 years artificial intelligence will replace many people: 80% of decisions will be made by machines, and this will lead to tens of thousands of people losing their jobs.

Machine learning and artificial intelligence expert Pedro Domingos goes even further: he suggests that people will acquire a computer psychological model of their personality. What will it be?

Sex, lies and machine learning

The digital future begins with the realization of the fact: when interacting with a computer - whether it be your own smartphone or a remote server thousands of kilometers away - you do it on two levels each time. The first is the desire to immediately get what you need: an answer to a question, a desired product, a new credit card. At the second level, strategic and most important, you tell the computer about yourself.

The more you teach him, the better he will serve you or manipulate you.

What model of your personality do you want to propose to the computer? What data can be given to him so that he builds this model? These questions need to be kept in mind whenever you interact with a machine learning algorithm - just like when you interact with people.

Digital mirror

Think about all your data that is recorded in all computers in the world. These are emails, MS Office documents, texts, tweets, Facebook and LinkedIn accounts, Internet search history, clicks, downloaded files and orders, credit history, taxes, phone and medical card, driving information recorded in the on-board computer of your car , the displacement map registered by your mobile phone, all the photos you've ever taken are short appearances in security camera recordings.

If the future biographer had access only to this "data exhaust" and to nothing else, what picture would he have? Probably pretty accurate.

Imagine that you took all your data and gave it to the real Supreme Algorithm of the future, which already has knowledge about human life that we can teach it. He will create your model, and you can carry it on a flash drive in your pocket. Of course, this will be a great tool for introspection - how to look at yourself in the mirror. But the mirror would be digital and show not only your appearance, but everything that can be learned from watching you. The mirror could come alive and talk.

Benefits of the digital twin

What would you like to do, what tasks to entrust your digital half? Probably the first thing you would want from your model is to instruct her to negotiate with the world on your behalf: to release her into cyberspace so that she will look for all sorts of things for you.

Of all the books in the world, she will recommend a dozen that you want to read first, and the advice will be so deep that Amazon never dreamed of. The same will happen with movies, music, games, clothing, electronics, whatever. Of course, your refrigerator will always be full. The model will filter your email and voice mail, Facebook news and Twitter updates, and when appropriate, reply for you.

She takes care of all the annoying little things of modern life, such as checking credit card bills, appealing against incorrect transactions, scheduling, updating subscriptions and filing tax returns. She will select a medicine for you, check with your doctor and order it from the online store.

The model will tell you who you like. And after you meet and like each other, your model will team up with your chosen one's model and choose restaurants that you both might like. And this is where it gets really interesting.

Model Society

In a very fast-moving future, you will not be the only person with a “digital half” who carries out your orders around the clock. Everyone will have a similar personality model, and the models will communicate with each other all the time.

If you are looking for a job and Company X is looking for employees, then her model will interview yours. Their "conversation" will in many ways resemble a real, "live" one - your model will be well instructed, for example, she will not give out negative information about you - but the whole process will take only a split second.

In the world of the Supreme Algorithm, "my people will link to yours" becomes "my program will link to your program." Each person will have a retinue of bots, designed to make his journey around the world easier and more enjoyable. Deals, negotiations, meetings - all this will be organized, before you have time to lift your finger.

Your digital half will be like a power steering: life will go where you want, but with less effort on your part.

This does not mean that you will find yourself in a “filter bubble” and will only see what you are guaranteed to like, without any surprises. The digital personality will turn out to be much smarter, she will have instructions to leave room for a chance, to give you contact with new experiences, to look for happy accidents.

As the models improve, the interaction will become more and more similar to what it would be in the real world, but it will happen in silico and a million times faster. The cyberspace of tomorrow will turn into a very vast parallel world, which will choose all the most promising in order to try it in reality. It will be like a new, global subconscious, the collective "ID" of humanity, or "It".

Today's world is notable for the fact that theories of mind began to appear in computers as well. While these theories are still primitive, they are developing rapidly, and we will have to work with them as much as with other people to get what we want.

Based on materials from the book "The Supreme Algorithm"

Perhaps anyone who has watched films about the terminator or "The Matrix" wondered when artificial intelligence will become a part of our daily life, and whether humans and robots will be able to coexist in peace and harmony. Such a future is much closer than you think. Today we will tell you about such technology as "digital twins", which is already widely used in industry and, possibly, will soon become a part of our daily life.

Who are the digital twins?

It is a mistake to believe that the term "digital twins" refers to robots and artificial intelligence in the guise of some kind of humanoid being. The term itself is currently applied mostly to industrial production. For the first time the concept of "digital twins" appeared in 2003. The term came into use after the publication of an article by Michael Greaves, Professor and Assistant Director of the Center for Lifecycle Management and Innovation at Florida Institute of Technology, "Digital Twins: Manufacturing Excellence Based on a Virtual Plant Prototype." The concept itself was invented by a NASA engineer who was a colleague of the professor.

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At its core, digital twins are a concept that combines artificial intelligence, computer learning, and data-driven software to create living digital models. These "digital twins" are constantly being updated following the evolution of physical prototypes.

Where do the “digital twins” data come from for self-renewal?

A digital copy, as befits an artificial intelligence, is constantly self-learning and self-improving. To this end, the digital twin uses knowledge from humans, other similar machines, from larger systems and the environment of which it is a part.

Michael Greaves proposed three of his requirements that digital twins must meet. The first is to match the appearance of the original object. You need to understand that a similar appearance- this is not only the whole picture, but also the correspondence of individual parts to the real "twin". The second requirement is related to the behavior of the twin during testing. The last and most difficult thing is the information obtained from artificial intelligence about the merits and demerits of a real product.

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As Michael Greaves notes, when digital copies were introduced, even the criterion of external similarity was considered difficult to meet. Today, as soon as the digital twin is identical in the first parameters, it can already be used for solving practical problems.

Why are digital twins needed?

Digital copies are created to optimize physical prototypes, entire systems and manufacturing processes.

According to Colin J. Parris, Ph.D., vice president of research software GE Global Research Center, the digital twins, is a hybrid model (both physical and digital) that is created specifically for specific business goals, such as predicting failure, reducing maintenance costs, and preventing unplanned outages.

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Colin J. Parris states that when we talk about digital twins, this system works in three stages: see, think and do. At the “vision” stage, it is about obtaining data about the situation. There are two kinds of information: operating data (eg boiling point) and data from the environment. The next step, which Colin J. Parris tentatively called “think,” is due to the fact that at this stage, the “digital twin” can provide options for different requests on how best to act in a given situation or what options are preferable for business purposes. Artificial intelligence uses for analysis, for example, historical information, forecasts for revenue and expenses, and provides several options that are based on risk and confidence that these proposals will reduce them. The last step - "to do" - is directly related to the implementation of what needs to be done.

1971yes / bigstock.com

With the help of digital twins, for example, can see from within the problem of a physical object.

In production, we no longer need to see in front of us, for example, the entire turbine as a whole, in order to detect a hole. The technology of "digital twins" will allow you to see the problem in real time using computer visualization.

Zvi Fejer, executive vice president of software development at Siemens, said the digital twin is a PLM solution on the road to Industry 4.0.

What kinds of digital twins already exist?

As we said earlier, "digital twins" are actively used in industry: twin-parts (which are built for a specific production part), twin-products (related to the release of a product, their main task is to reduce the cost of maintenance), twin-processes ( their purpose may be, for example, to increase the service life), system twins (optimization of the entire system as a whole).

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According to the research and consulting agency in the field of high technologies Gartner, in the near future, hundreds of millions of "digital twins" will replace human labor. Some companies already use this. It is not necessary to have an employee on staff who would be involved in diagnosing production problems. With the help of "digital twins" you can get all the necessary data in real time and be ready in advance for equipment repair.

What about the person's "digital twin"?

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For those who want to have a terminator friend who would think like you, help in everything, be a brother and a friend, we have good news. According to futurologist and theoretical technologist John Smith, such a future is already close. He believes that in the near future there will be so-called software agents that will predict in advance the wishes and behavior of their real copy and will perform some actions for their human counterpart.

The "digital twin" will be able to make purchases, make business decisions, engage in social activities - in general, he will be able to do everything that we sometimes do not have enough time for.

We will also be able to shift all the routine work to our double. In addition, according to John Smith, our digital clones will know our interests, preferences, political views and, if necessary, will be able to defend them, since they will have a more complete historical context and see the modern picture of the world as a whole. And even a feeling of compassion. For example, the "digital twin" will show us, as it will be able to guess our emotional state.

It all sounds like a script for a utopian movie. I feel a catch. What are the disadvantages of digital twins?

The disadvantages of digital twins are obvious. First of all, the question arises about our security. Digital clones will use all possible resources to replenish information about us. These are algorithms that collect data from social media accounts, and our personal correspondence, and any documents and files that, in one way or another, concern us. Of course, this cannot but be alarming: as we have already found out, the "digital twins" are capable of constantly updating and improving. Therefore, one of the priority tasks should be the creation of a legal basis for determining the "limits of permissibility" of artificial intelligence.

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However, don't panic about this. Take an example from John Smith: he remains optimistic and believes that digital twins cannot replace humanity. They will simply become other versions of a person who can coexist with us in peace.

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