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According to a Deloitte study, the global market for digital twins (DT) is expected to grow by a 38% CAGR to reach $16 billion by 2023, with the proliferation of Internet of Things (IoT) technology accelerating this growth. DT is one of the most important technologies in Industry 4.0 available today. It is changing the way companies create, research, and optimize diverse processes, and it is firmly rooted in many industries, such as manufacturing or supply chains.
Digital twins allow industries to maximize OEE (overall equipment effectiveness) and make better decisions through the dynamic recalibration of equipment, production lines, processes, and systems – which is much safer and cheaper than in the physical world. Thanks to this ability, companies can get an accurate idea of what is happening in production and what may happen in the future.
In this blog post, you’ll find a brief overview of digital twins and examples of their use in various industries to gain a better understanding of why they have overcome industry barriers to become relevant far beyond the factory environment.
Digital twins have been enabled by the IoT sensors that collect data from the physical world and send it to a machine for reconstruction. Although the DT concept has been around for more than 20 years, it was IoT technology that made it available to many industries today. The digital twin helps to improve performance, increase efficiency, or identify a problem before it happens. Its status is maintained through real-time updates so DTs represent significant opportunities for manufacturers, including design, customization, production, and operation.
Creating a DT requires a lot of data and compliance with many technical conditions and production processes. The more production data is available, the better the technology works. Real operational input is vital. Industry 4.0 technologies, including IoT and DT, allow maintenance teams to detect problems ahead of time. Thus, by minimizing downtime, DT technology helps maintain profits.
A digital twin is different from a digital simulation. It starts as a simulation, but a digital twin uses real-time updates.
Today, engineers use simulations to test and evaluate the physical assets of a simulated version. But such modeling is static. It does not adapt with a physical asset unless the engineer uses new parameters in the simulation.
The digital twin receives real-time updates from a physical asset, process, or system. Engineers base their tests, assessments, and analyses on actual conditions. The state of the digital twin is constantly changing, which allows specialists to get results that are more accurate and valuable.
Security protocols need to be updated. According to Gartner, in 2023, about 75% of digital twins for OEMs connected to the IoT will use five different types of integration endpoints. This greatly increases the amount of data collected from these numerous endpoints. Each endpoint represents a potential area of security vulnerability. That’s why if you intend to use DT technology, you need to evaluate and update your security protocols.
Make sure your data is high quality. Virtual models of digital twins depend on data transmitted by thousands of sensors. These sensors are remote and can communicate over unreliable networks. You will need to be able to eliminate bad data and manage gaps in data flows.
Your team must be well qualified. If you intend to use a digital twin, your team of engineers must be prepared to completely change the way they work, which can potentially lead to problems in creating new technical capabilities. You need to make sure that your employees have the necessary skills and tools to work with DT models.
As more and more companies use the Internet of Things and big data, digital duplicate technology is becoming more popular. Here are ways to use digital twins to improve manufacturing operations.
Digital twins are widely used in supply chains and logistics. They can predict the performance of packaging materials by virtualizing product packaging and checking the process for errors. In this way, digital twins help logistics companies determine their viability. For example, DHL uses DT technology to optimize operations and anticipate mistakes based on past data. DTs also increase shipment protection by allowing logistics companies to analyze how different packaging conditions can affect product delivery.
With the help of digital twins, companies can optimize the design of warehouses. This includes specialists testing warehouse planning so the most efficient design to maximize productivity can be chosen.
Also, the DT supports the logistics network by transmitting information on road conditions, road planning, and construction. This assists with designing distribution routes and inventory storage locations.
Digital twins are widely used in medicine to improve health care and improve personalized patient care. This technology allows medical centers to create digital hospital duplicates, and run operational strategies, capabilities, staffing, and care models.
Pharmaceutical companies also use digital twins to model the genome code, physiological characteristics, and the patient’s lifestyle. This enables unique care and medication for each patient.
An amazing example of the use of DT technology in the industry is the Living Heart Project. Scientists are developing and testing high-precision digital models of the human heart based on MRI images and ECG data. The DT heart is used to simulate in vivo conditions, visualize anatomy that cannot be seen, and improve the design of cardiac devices faster. The team hopes this experiment will serve as a textbook for future in silico tests (performed using computer simulations).
The manufacturing industry is the one that benefits most from digital twins. The latest technology helps engineers test the feasibility of future products before launch. Specialists conduct testing and begin to develop an actual product according to their results. Digital twins even help create the concept of the product and personalize it.
For production purposes, the DT helps to track the operation of the machine and adjust it in real-time. Engineers also use DTs to monitor and analyze end products to see which products are defective or have lower performance than expected.
Unilever PLC has created virtual models of its factories and now uses eight digital twins in North America, South America, Europe, and Asia. At each location, special sensors transmit real-time performance data such as engine temperature and speed to the corporate cloud. The digital twin simulates complex scenarios to determine the best working conditions. This helps manufacturers use materials more accurately and limit the use of products that do not meet quality standards.
According to a Business Wire report, 75% of Air Force executives expressed confidence in the use of digital twins. Through this technology, engineers can ensure the safety of people on board by using analytics to predict possible future problems with gliders, engines, or other components.
Digital Twins are also used in the automotive industry to create virtual machine models. For example, developing a car starts with a clay model, but then automotive engineers use Siemens NX CAD to turn it into a real product.
Even before they start developing the automotive parts, engineers create the perfect virtual car. They model and analyze the stages of production and the problems that may arise when the car goes on the road. Digital twins are used not only in the traditional automotive industry but also in the development of self-driving vehicles. Self-driving cars contain numerous sensors that collect data about the vehicle itself and the car’s environment. Automotive companies create a digital twin car and test every aspect. This ensures that unexpected damage and accidents are minimized.
According to Boston Consulting Group, DTs help retailers minimize capital expenditures by 10%, reduce excess inventories by 5% and improve EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization) by 1-3%. Digital twins in retail allow companies to create supply chain simulations. Real-time sensor and equipment data, as well as ERP (enterprise resource planning software) and other business system data, are commonly used for this purpose. Engineers review the effectiveness of the supply chain, including assets, warehouses, material flows, inventory positions, and people.
The digital twins can be digital copies of stores using data from RFID readers, motion sensors, and smart shelves. These models analyze customer movement and customer behavior, as well as test the optimal placement of products.
The French supermarket chain Intermarché has created digital duplicates of its stores using data from the IoT-enabled sales systems and shelves. The digital twins allow store managers to easily manage inventory and test the effectiveness of different store layouts.
Manufacturing and healthcare are not the only areas in which digital twins can be used to improve processes. One of the most effective ways to improve the configuration of kitchens and dining areas in hotel restaurants for better people flow is to simulate real events and situations. Hotels use DT technology to analyze the use of their facilities and provide individual services to each guest.
What about a whole city or nation? Singapore and Shanghai can already boast of having complete digital twins. Engineers are working to improve cities, including improving energy consumption and traffic flow, and even helping with city development planning. Smart cities are fast becoming a reality, providing a great way to reduce pollution and increase the well-being of residents.
Back in 2018, Microsoft launched Azure Digital Twins. This technology has allowed users to develop digital models and graphs of knowledge using artificial intelligence algorithms. With Azure Digital Twins, users can simulate environments such as factories, farms, power grids, buildings, stadiums, railroads, and cities by connecting IoT devices and existing business systems.
Bosch Engineering and Technology offers DT control in a simple, convenient, and safe way. Bosch IoT Things is open source based on the Eclipse Ditto project. It helps devices communicate effectively through the API and supports security and common authentication mechanisms such as username or password.
General Electric Company (GE) has created its latest Digital Twin, which integrates analytical models for power plant components. These models measure asset status, depreciation, and performance with customer-defined KPIs and organizational goals. GE Digital Twin is based on the industrial platform Predix, which is used to process large amounts of data and perform analytical models.
IBM has also embraced the technology, developing the IBM Digital Twin Exchange for resource-intensive industries. This technology allows companies to create, monitor, and test virtual products to sell real products faster and make accurate predictions about their performance.
Siemens engineers have developed the Digital Enterprise Suite, which is used to comprehensively digitize the value-added process across different production modules. But this is not the only virtual product from Siemens. Another product, MindSphere, helps develop new digital business models and offers state-of-the-art cloud security features.
Oracle’s IoT Digital Twin Implementation runs on virtual duplicates, predictive duplicates, and dual projections to solve a variety of problems. Engineers have created a DT that uses a JSON-based model. This model creates a virtual representation of a physical asset or device in the cloud. Using Machine Learning (ML) methods, predictions and representations are generated in double projections to monitor the predicted state of the environment.
Back in 2020, Research and Markets conducted a study that showed that up to 89% of all IoT platforms by 2025 will include digital twins. They also noted that digital twinning will become a standard feature of IoT by 2027.
The above examples of the digital twins have shown the many benefits for business. One of the misconceptions about digital twins is that they are only used by large companies. But this is no longer the case, the opportunities for digital twins are becoming more accessible even in small organizations. This has been made possible by the rapid improvement of modeling capabilities, the proliferation of IoT sensors, and the increasing availability of tools and computing infrastructure.
Using a digital twin makes managing any property and asset much more efficient. Imagine how DTs could change your own operations. Although the uses of the digital twin may vary from sector to sector, DT technology can benefit businesses in all industries. The Postindustria team has years of experience in developing IoT technologies and can empower your company with proficient AI development solutions. Reach out to our team to see how we can bring your ideas to life!
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