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

Architects of the digital age

Usually the most technologically advanced areas are considered to be information technologies and biomedicine. The attitude towards companies in traditional industries, such as metal rolling or oil production and refining, is quite different. 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 in the mid-30s of the last century. Over many decades, hardware and software systems have been continuously improved and complicated. Automation of production processes - for example, in oil refining - has moved far ahead. The operation of a modern oil refinery is monitored by hundreds of thousands of sensors and instruments, and fuel supplies are tracked in real time by satellite navigation systems. Every day, the average Russian refinery produces more than 50,000 terabytes of information. For comparison, 3 million books that are stored in the digital storage of the Russian State Library occupy hundreds of times less - "only" 162 terabytes.

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

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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. Under these conditions, it is very difficult to quickly respond to market fluctuations. Traditional technologies allow saving no more than a tenth of a percent. Meanwhile, digital solutions already today allow reducing costs by up to 10-15% per month. The fact is obvious: in the era of the fourth industrial revolution, those who learn how to most effectively apply new technologies in the context of accumulated experience will be competitive.

Petr Kaznacheev, Director of the Center for Resource Economics, RANEPA: “As a first step towards an “integral” artificial intelligence system in oil and gas, one could consider “smart” management and corporate planning. In this case, we could talk about creating an algorithm for digitizing all the key information about the company's activities - from the field to the gas station. This information could be sent 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.

Digital transformation leader

Realizing this trend, the industrial leaders of Russia and the world are restructuring business processes that have been developing for decades, introducing Industry 4.0 technologies based on the Industrial Internet of Things, artificial intelligence and Big Data into production. The most intensive transformation is taking place in the oil and gas industry: the industry is dynamically “digitizing”, investing in projects that seemed like science fiction just yesterday. Plants controlled by artificial intelligence and able to predict situations, installations that prompt the operator for the best mode of operation - all this is already becoming a reality today.

At the same time, the maximum task is to create a system for managing production, logistics, production and sales, which would unite smart wells, factories and gas stations into a single ecosystem. In an ideal digital model, the moment a consumer presses the fuel dispenser, the company's analysts in the operations center are instantly informed about what brand of gasoline is being filled into the tank, how much oil needs to be extracted, delivered to the plant and processed to meet demand in specific region. So far, none of the Russian and foreign companies have been able to build such a model. However, Gazprom Neft has advanced the farthest in solving this problem. Its specialists are now implementing a number of projects, which should ultimately become the basis for creating a single platform for managing processing, logistics and sales. 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, at the same time presenting new requirements for automation. More precisely, it is not so much about automation, but about the almost complete digitization of production.

The basis of the new stage will be the so-called "digital twins" - virtual copies of refinery units. 3D models reliably describe all the processes and relationships that occur in real prototypes. They are based on the work of artificial intelligence based on neural networks. " Digital Twin» can offer optimal modes of equipment operation, predict its failures, recommend repair terms. Among its other advantages is the ability to constantly learn. The neural network itself finds errors, corrects and remembers them, thereby improving its work and the accuracy of the forecast.

The basis for training the "digital twin" is an array of historical information. Modern oil refineries 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 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 last few years of plant operation. The operator simulates various situations, makes the neural network answer the question “what will happen if one of the operation parameters is changed?” - for example, to replace one of the components of the raw material or to increase the power supply of the installation. The neural network analyzes the experience of past years and excludes non-optimal modes from the algorithm by calculation, and learns to predict the future operation of the installation.

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Gazprom Neft has already completely “digitized” two industrial complex involved in the production of automotive fuel - a catalytic cracking gasoline hydrotreatment unit at the Moscow Oil Refinery and a unit operating at the company's oil refinery in Omsk. Tests have shown that artificial intelligence is able to simultaneously take into account great amount parameters of their "digital twins", 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, which will minimize the impact of the human factor on the scale of the whole production. Similar projects are currently being implemented at the company's bitumen plants in Ryazan and Kazakhstan. Successful solutions found empirically can subsequently be scaled up to the level of large refineries, which will eventually create an effective digital production management platform.

Nikolay Legkodimov, Head of the Advanced Technologies Advisory Group, KPMG in Russia and the CIS:“Solutions that model various components, 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 these models can be combined with each other, combined into a whole complex chain, then this will indeed allow solving problems at a completely new level - in particular, simulating the behavior of the system in critical, unfavorable and simply dangerous operating conditions. For those areas where retooling and upgrading equipment is very expensive, this will allow pre-testing of new components.”

Performance Management

In the future, the entire value chain in the logistics, refining and marketing 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, established a year ago in St. Petersburg. It is here that information from the “digital twins” will flow, here it will be analyzed, and here, based on the data received, management decisions will be made.

Already today, more than 250,000 sensors and dozens of systems transmit information to the Center in real time from all the company's assets included in the perimeter of the Gazprom Neft logistics, processing and marketing block. Every second, 180,000 signals arrive here. It would take a person just to view this information about a week. The Center's digital brain does this instantly: it monitors the quality of products and the quantity of oil products in real time along the entire chain - from the refinery outlet to the end consumer.

The strategic goal of the Center is, using the technologies and opportunities of Industry 4.0, to radically increase the efficiency of the downstream segment. That is, it’s not just about managing processes – this can also be done within traditional systems, but to make these processes the most efficient: using 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. This includes predicting the future 60 days ahead: how the market will behave in two months, how much oil will need to be processed to meet the demand for gasoline at the current time, what condition the equipment will be in, whether the plants will be able to cope with the upcoming load and whether them repair. At the same time, in the next two years, the Center should reach 50% capacity and begin to monitor, analyze and forecast the amount of oil product stocks 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 process equipment and develop measures to prevent the loss of oil products and the reduction in their quality.

By 2020, Gazprom Neft aims to reach 100% of the performance management center's capabilities. Among the declared indicators are the analysis of the reliability of all equipment, the prevention of losses in terms of quality and quantity of products, and the predictive management of technological deviations.

Daria Kozlova, Senior Consultant at VYGON Consulting:“In general, integrated solutions bring significant economical effect for the industry. For example, according to Accenture, the economic effect of digitalization could be more than $1 trillion. Therefore, when it comes to large vertically integrated companies, the introduction of integrated solutions is highly justified. But it is also justified for small companies, as efficiency improvements can free up additional funds for them by reducing costs, increase the efficiency of working capital management, etc. ”.

Discuss 0

In the New Word section, Apparat talks about recently emerging terms related to the new society. This release features a digital twin. A computer that knows everything about you and can imitate your behavior.

Digital Twin

The technological dream of the futurist and founder of the Acceleration Studies Foundation, John Smart, that special computer programs able to mimic the behavior of specific people. Using various technologies for collecting and analyzing your data, the computer will be able to answer your letters instead of you and even communicate with your relatives while you yourself are busy. According to Smart, digital twins should appear within the next five years.

It is assumed that in order to create a digital twin, special software will analyze your correspondence in social networks and e-mail, browsing history and purchases in online stores, information from wearable devices, smartphones or smart watch, and any other available information. Based on this data, with the help of special algorithms it will be possible to program your behavior: how would you answer your partner to a business letter, so that you would tell the children to their message on Facebook. Computers already know a lot about our preferences, for example, advertising companies analyze our search terms and emails, create a profile for each person and try to show him only those ads that he will be really interested in.

Software that mimics human behavior is also starting to creep into our lives: digital assistants- Siri from Apple, Cortana from Microsoft and Watson from IBM - communicate with the user, answer his questions, can keep up the conversation even on abstract topics. The first chatbots have been developed that successfully pass the Turing test - that is, they mislead people who communicate with them and make them believe that they are not artificial intelligence, but real human.

Scientists are also considering more fantastic options for creating a digital twin: the complete digitization of the brain, the so-called consciousness upload. But work in this direction is now only in its infancy: for example, as part of the Blue Brain project, by 2023, a digital version of the neocortex, the main part of the human cerebral cortex, should be fully simulated.

How to use the digital twin

Talk to a person after his death

One of the most ambitious plans is to create such a double that can replace a person after his death. “When you and I die, our children will not come to our graves. They will go and launch our digital twins and talk to them,” says John Smart. “Let this scenario sound a bit far-fetched,” he adds. “But people are already building a wailing wall on the pages of deceased relatives in in social networks and keep sending them private messages.” Such perspectives are loved by science fiction writers and directors. For example, one of the plots in the Black Mirror series tells how a young woman replaced her husband who died in a car accident with a digital copy. Later, she "uploaded" her husband's consciousness into an android robot - that is, she practically revived him.

Personal assistant

This option is much simpler to implement and does not require such high level cognitive abilities. To some extent, this is already being implemented, for example digital assistant Google Now analyzes your email and searches to provide suggestions that make your life easier. However, the digital twin can not only tell you something, but also take on some of your tasks, albeit quite simple ones: make an appointment with a doctor, set up a business meeting, and in the store point to products that are most suitable for your diet in terms of content. useful substances.

Project Disadvantages

One of the main shortcomings of this concept, which even its ideologue John Smart recognizes, is a complete violation of privacy. The program will read all your correspondence, analyze purchases and, in general, in every possible way penetrate into what is called personal life. Large corporations that collect less data are already facing protests.

John Smart

the ideologue of creating digital twins

You know, I would like to keep my health and financial information in a small safe so that no one can access it. But such thinking is an atavism. You can't get much if you don't sacrifice your privacy. I am sure that as long as people feel in control of the technology, data privacy will be secondary.

Image: Edward Blake Edwards

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 the fact that tens of thousands of people will lose 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 she be?

Sex, lies and machine learning

The digital future begins with the realization of the fact: interacting with a computer - whether it is your own smartphone or a server remote thousands of miles away - every time you do it at two levels. The first is the desire to immediately get what you need: an answer to a question, a product you want, 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 or manipulate you.

What model of your personality do you want to offer 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 interacting with people.

digital mirror

Think about all your data that is stored in all the 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 records, driving information recorded in on-board computer of your car, a map of movements registered by your mobile phone, all the pictures you've ever taken, brief appearances on security camera footage.

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

Imagine that you took all your data and gave it to the real Master 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, it will be a great tool for introspection - how to look at yourself in the mirror. But the mirror would be digital and would show not only your appearance, but everything that can be learned by watching you. The mirror could come to life and talk.

Benefits of the digital twin

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

Of all the books in the world, she'll recommend a dozen that you'll want to read first, and the advice is so deep that Amazon couldn't even dream 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 voicemail, news on Facebook and updates on Twitter, and when appropriate, reply for you.

She takes care of all the annoying little things modern life such as checking credit card bills, appealing wrong transactions, planning your schedule, renewing subscriptions, and filing tax returns. She will select the medicine for you, check with your doctor and order it in the online store.

The model will tell you who you like. And after you get to know each other and like each other, your model will team up with the model of your chosen one and choose restaurants that both of you can like. And this is where it gets really interesting.

Model Society

In the very fast approaching future, you will not be the only person with a "digital half" who runs your orders around the clock. A similar model of personality will appear in everyone, and the models will communicate with each other all the time.

If you are looking for a job and a company has X employees, then its model will interview yours. Their "conversation" will in many ways resemble a real, "live" one - your model will be well instructed, for example, it will not give out negative information about you - however, the whole process will take only a fraction of a second.

In the world of the Master Algorithm, "my people will contact yours" will become "my program will contact your program." Each person will have a retinue of bots, designed to make their way around the world easier and more enjoyable. Deals, negotiations, meetings - all this will be organized before you lift a finger.

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

This does not mean that you will find yourself in a “filter bubble” and only see what you are guaranteed to like, without any surprises. The digital person will be much smarter, they will be instructed to leave room for chance, let you touch new experiences, look for happy accidents.

As the models improve, the interaction will become more and more similar to what would happen 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 to try 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 have begun to appear in computers. So far, these theories are still primitive, but they are developing rapidly, and we will have to work with them no less than with other people to get what we want.

Based on the materials of the book "The Supreme Algorithm"

In Russia today it is difficult to talk about the 4th industrial revolution, but we believe that it is necessary to speak. Among the technological drivers in industrial enterprises in the new generation, there will be platforms for the industrial Internet of things that implement the concept of a digital twin.

Forrester analysts define a digital twin as the creation of a real physical object in an abstract digital form that acts as an intermediary for any connection to a real device.

According to General Electric, the idea behind the digital twin is to go beyond just working with digital models. The company says maintenance will also take place in sync with the digital model of the real facility through sensor systems and communications.

Analyst agency Gartner predicts that by 2021, half of large industrial companies will use digital twins and, as a result, these organizations will receive a 10% increase in operational efficiency.

“Digital twins are driving the business impact of IoT by offering a powerful way to monitor and manage assets and processes,” said Alfonso Velosa, research vice president at Gartner. This is especially exciting for our team, since we in the SAYMON project are very closely involved in automated monitoring and control, including information systems and internet things. Of course, the competition in the IoT management platform market is quite strong - literally every large digital corporation today claims to have platforms, but not everyone has managed to make their own developments or acquire a company with a ready-made solution. Often a statement of availability is a tribute to decency - there is a technological trend, there is a statement of a corporation.

Today we do not work with digital models and drawings yet - we are open to partners with experience in this field. On the this moment there is experience of cooperation with a company that forms photo-realistic copies of industrial facilities and as a result, a separate project VIOTR was born, combining the power of digitized space with the ability to obtain data from real sensors and video cameras, the ability to control switches, relays and dampers in the real world. The VIOTR project today has a focus on the educational technologies of the future, but in essence it is part of the concept of a digital twin.

This is exactly what our colleagues from Computer Weekly also formulate - a new approach involves managing communication between edge devices and internal systems and mirror reflection changes in the virtual model of the device - in other words, a digital twin appears.

The examples show that even for such simple operations as controlling door locks, you can get significant savings in operation. Dormakaba, which makes smart door locks, has been using control software since 2012 field work ServiceMax enterprise by helping him control his installations. Detailed data on the operation of each door helps Dormakaba and its partners manage buildings more efficiently. A recent Vanson Bourne study for ServiceMax found that industrial companies are losing $260,000 an hour due to unplanned downtime. Predicting failure using digital twins can help overcome this problem. The digital twin can provide engineers at Dormakaba with an up-to-date record of every action or event that the sensors on the doors register, log component installations and firmware updates, and can be used service team Dormakaba to determine the service life of the product along with detailed description a security log that is tied to the door. It is also important to ensure close communication with suppliers of parts and components and management life cycle product, providing an extremely precise level of control and service. By using digital lock prediction, Dormakaba expects to reduce customer calls and improve service quality. Together with Swisscom, a cloud platform for lock management was created. Partner training is an important element of this innovation and business transformation, Dormakaba acknowledges.

In a Gartner report Digital Twins Will Impact Economic and Business Models, the analytics firm draws an analogy between the amount of data collection done by companies like Google, Amazon and Netflix and the amount of data digital twins in industrial firms will create to constantly monitor the operation of equipment connected to control systems.

Analysts warn that this will require even more control over components and software upgrades, and will require car manufacturers to become software vendors. “Asset operators will need to add software skills to their operations units as they add smarter assets and also add ownership software and data into support contracts,” analysts warn.

Image from https://www.ge.com/

There is a better way. Identification of ways to improve the efficiency of design and technological design processes

Aaron Frenkel, Jan Larssen

Product manufacturing is undoubtedly the most important part of all life cycle processes. At this stage, ideas turn into reality. What's more, without coordinated design and manufacturing processes to ensure that the product is successfully assembled on the shop floor, ideas will remain just beautiful blueprints or not fully realized. For many years, the methods of designing and developing technological processes have remained unchanged, retaining all the traditional disadvantages that lead to an increase in cost and time. Considering that today innovations have become vital for the survival of machine-building enterprises, Siemens PLM Software analyzed the pre-production processes in order to identify ways to further optimize them. In this article, Aaron Frankel, Senior Director of Marketing for Machinery Solutions, and Jan Larsson, Senior Director of Marketing for Europe, the Middle East and Africa at Siemens PLM Software, discuss which sources of inefficiency should be be eliminated in order to implement the concept of a "digital twin of the product", and how this will affect the way products are produced.

beautiful symphony

If you find yourself in a modern factory, you will see an amazing symphony of human labor, robots and machines, the movement of materials and parts - all done to the nearest second in order to keep up with the schedule. The picture is just fantastic.

But behind the scenes we will see outdated processes of design and technological preparation of production. We are not going to criticize anyone. Developing a product design is no small achievement in itself. Design can be very challenging task. In some cases, a product consists of millions of parts, and thousands of employees and partners work to create it, often all over the world. Moreover, critical industries such as electronics (faster processors, miniaturization), automotive (green and emission reduction) and aerospace (green and composite materials) are constantly striving to optimize and accelerate the process of creating new products. Given the high complexity of the tasks to be solved, the reluctance to deviate from field-proven pre-production processes is quite understandable. However, our customers are reporting common product design and manufacturing issues that in some cases result in costly delays.

Common problems

One of the most serious difficulties that we see is that designers and technologists use different systems. In practice, this leads to the fact that designers transfer their developments to technologists who are trying to create technological processes in computer systems to which they are accustomed. In this scenario - and it occurs very often - there is a desynchronization of information, which makes it difficult to control the situation. In addition, the likelihood of errors increases.

Problems regularly arise during the development of shop floor plans. The reason for this is that layouts are usually created in the form of 2D floor plans and paper drawings. This is a long and laborious process. 2D drawings are an important part of the process, but they don't have the flexibility you need. It often happens that the rearrangement of equipment in the workshop is not fixed on the drawing. The problem is especially exacerbated when operating in rapidly changing markets (eg, consumer electronics), which require constant expansion and modernization of production systems. Why? Because two-dimensional layouts lack intelligence and associativity. They prevent technologists from knowing exactly what is happening on the shop floor and making smart decisions quickly.

After creating the layout, a technological route is developed. As a rule, then it passes the control stage. Here lies another significant obstacle to the growth of efficiency. Technologists usually have to wait until the equipment is installed to evaluate the performance of the equipment. Moreover, if the characteristics are lower than expected, then it is too late to develop an alternative technology. Our experience shows that this situation leads to significant delays.

Finally, customers report two more problems at the end of the pre-production cycle. This is an assessment of the performance of individual operations and the entire technological process as a whole.

Due to the high complexity of modern production and the frequent lack of coordination between various systems In process design, identifying which particular operations or production areas are causing delays in the operation of the entire line is not easy. And when it comes to the actual manufacture of a product, customers report that it is usually extremely difficult to assess the productivity and degree of compliance of real processes with planned ones. And again, the problem is high complexity, as well as the lack of feedback between production, designers and technologists.

Digital Twin

A digital twin is a virtual copy of a real object that behaves just like the real object. Without going into the technical details of our products here, suffice it to say that our Product Lifecycle Management (PLM) tools provide a complete digital platform. It supports the use of digital twins that accurately model end-to-end product design and manufacturing processes.

What does all this mean in practice? Let's take a look at the above steps again and show the main features provided by the new approach.

Construction

NX (and other CAD systems) creates a model of the product and sends it to Teamcenter in 3D JT format. In seconds, the app creates thousands of different virtual product designs that exactly match the actual product. At the same time, big data processing technologies, design and technological information (PMI) contained in the models (tolerances, fits, relationships between parts and assemblies), as well as a basic description of the technological process are used to identify potential problems. This approach has already been tested in practice when creating our company's electronic products. For example, we were able to immediately determine that the threaded holes on the video output connector did not exactly line up with the screw holes on the PCB. If the error had gone undetected, it would have resulted in warranty claims from customers: the connector could have come loose from the printed circuit board. Identifying design errors early saves significant time and money, both in technology development and production.

Design of technological processes

The digital twin improves the collaboration between designers and technologists, optimizes the choice of location and manufacturing technology, as well as the allocation of necessary resources. Consider an example of making changes to the build process. Using our software, process engineers, based on the new design specification, add new operations to the working 3D model of the process. It is possible to simulate any production system from anywhere in the world: say, technologists in Paris are preparing production at a plant in Rio. With information about the time for each added operation, technologists check whether the new technological route meets the specified performance indicators. If this is not the case, then the technological operations are replaced or rearranged. Then numerical simulation is performed again until the selected technological route meets the requirements. The new workflow is immediately available to all developers for approval. If any problems are identified, then designers and technologists work together to eliminate them.

shop floor plans

When working on layouts, we recommend creating a digital twin containing mechanical equipment, automation systems and resources, and clearly related to the entire “ecosystem” of design and technological pre-production. With the help of a set of PLM tools, technological operations can be swapped by drag and drop. Just as easy is the placement of equipment and personnel on the production line and simulation of its operation. It is very simple, but at the same time exceptional effective method creation and editing of technological processes. When design changes are made that require a new industrial robot, numerical simulation specialists check, for example, whether it is possible to install a robot of this size without hitting the conveyor. The shop plan designer makes the necessary adjustments and prepares a notice of changes, on the basis of which the purchasing department purchases new equipment. This analysis of the consequences of the changes made allows you to avoid errors and, if necessary, immediately notify suppliers.

Control of technological design decisions

In the control phase, a digital twin is used to virtually verify the assembly process. Virtual modeling and quantitative analysis allows you to evaluate all the factors associated with manual labor in the assembly, and identify problems such as awkward posture of the worker. This makes it possible to avoid fatigue and work-related injuries. Based on the results of the simulation, training videos and instructions are created.

Performance optimization

The digital twin is used for statistical modeling and evaluation of the designed technological system. With it, it is easy to determine whether manual labor, robots, or a combination of robots and workers should be used. All processes can be simulated numerically, down to the energy consumption of a single machine, to optimize the technology as much as possible. The analysis shows how many parts are produced in each operation. This ensures that the performance of the actual production line will match the target.

and real worlds. This allows you to compare the design project with the actually manufactured one.
product. The figure shows how big data technologies are applied
to collect current information on product quality, which is transmitted for analysis
to a digital twin stored in Teamcenter

Product manufacturing

The digital twin provides feedback between the real and virtual world, which allows you to optimize the manufacturing processes of products. Technological instructions are transferred directly to the workshop, where equipment operators receive them along with videos. Operators provide production data to designers (such as the gap between two panel screws), while other automated systems collect performance data. Then there is a comparison of the design project and the actually manufactured product, while deviations are identified and eliminated.

New approaches to work

The use of a digital twin, which is an exact copy of a real product, helps to quickly identify potential problems, speeds up production preparation and reduces costs. In addition, the presence of a digital twin guarantees the possibility of manufacturing a product designed by designers; all technological processes are kept up-to-date and synchronized; the developed technologies turn out to be workable, and production functions exactly according to plan. The digital twin allows you to test how new technologies can be integrated into existing production lines. This eliminates the risks associated with the purchase and installation of equipment.

Mechanical engineering is one of the most advanced branches of the world industry, where proven in practice, but outdated approaches to the technological preparation of production have long been used. It's time to bring the spirit of innovation that paves the way for success in product development and manufacturing. It's time to try something new!