In manufacturing, every minute of downtime can cost millions, and any mistake in equipment setup can lead to a whole batch of products being rejected. How can these problems be prevented? Digital twin technology comes to the rescue. It creates exact virtual replicas of machines, production lines and entire factories. This allows you to test any production changes safely and risk-free, and to predict potential malfunctions before they occur in the real world.
Digital twins in manufacturing are becoming an indispensable tool for modern production facilities seeking efficiency and innovation. That’s why we decided to delve into this topic, analyzing what benefits this technology can bring and how to use it effectively.
What Is a Digital Twin in Manufacturing?
Benefits of Using a Digital Twin for Smart Manufacturing
Top 10 Applications of Digital Twins in Manufacturing
Complementary Technologies Compatible With Digital Twins
Challenges in Using Digital Twins
Many people mistakenly think that a digital twin is a three-dimensional model of equipment that can be spun on a computer screen. Others think it is just a simple computer simulation or a beautiful visualization for presentations. But this is not the case at all.
A digital twin is a sophisticated element of custom software for manufacturing. It is a virtual replica of a real piece of equipment or manufacturing process that accurately reflects its characteristics and behaviour. Imagine, for example, that you have an automated product packaging line. Its digital twin is a computer model that contains all the information about the line: speed, temperature, pressure, vibrations and other parameters. This model is constantly updated, thanks to sensors installed on the real equipment.
If something changes on the real line — packaging speed or film heating temperature — these changes are instantly reflected in the digital twin. With this model, engineers can monitor equipment performance, conduct virtual tests of new settings and even ‘look into the future’ by predicting possible malfunctions. This is similar to the way modern cars tell the driver to change the oil before engine problems occur.
According to Digital Twin Market Report 2023–2027, 29% of global manufacturing companies have either fully or partially implemented a digital twin strategy. This high adoption rate is no coincidence. This technology has proven its effectiveness in solving core operational challenges. Let’s take a look at the key benefits for enterprises that have implemented digital twins into their processes.
Digital twins enable real-time optimization of manufacturing processes. The system analyzes machine performance data and suggests the best operating modes, helping to eliminate production bottlenecks and reduce downtime. For example, if the company produces automotive components, a digital twin can automatically adjust machine settings to achieve the optimum balance between speed and quality.
With a digital twin, new products and changes in the manufacturing process can be tested without incurring the risks and costs of actual testing. Imagine a home appliance manufacturer is developing a new model of washing machine. Using a digital twin, engineers can virtually test different drum configurations and verify washing efficacy and noise levels without building physical prototypes. This saves months of development time and significant money on the production of test samples.
A digital twin constantly analyzes the condition of the equipment and can predict possible malfunctions before they occur. The system alerts technicians to the need for maintenance in advance, allowing them to schedule repairs at a convenient time and avoid sudden breakdowns. This is especially important for continuous production, where unplanned shutdowns can cause high losses.
A digital twin can provide managers and engineers with a complete picture of the production process based on real data. This allows them to make decisions based on accurate information rather than assumptions. For example, when planning an operational expansion, various scenarios can be virtually simulated to make it possible to choose the most efficient option, taking into account all factors, from equipment location to staff utilization.
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Digital twins are being applied to more and more areas of modern manufacturing, helping companies fulfil a wide range of tasks. From product development to employee training, this technology is becoming an indispensable tool for every stage of the production process.
Let’s take a look at 10 of the most effective uses of digital twins that are already helping businesses work better, faster and more effectively.
Before the advent of digital twins, creating a new product required multiple physical prototypes and extensive testing. This posed significant challenges for manufacturers, including high costs for materials and equipment for each prototype and long development timelines due to the need to physically build and test each version. Additionally, the scope for experimentation was narrow, as not all ideas could be tested, due to cost constraints or technical limitations.
Now engineers can virtually test new ideas and designs. For example, BMW uses digital twins to streamline their car design and testing processes. By creating virtual replicas of their vehicles, BMW can simulate performance, safety, and aerodynamics under various conditions before building physical prototypes. This approach significantly reduces costs and development time.
A digital twin helps continuously monitor product quality by analyzing hundreds of parameters simultaneously. This fundamentally changes the approach to quality control: instead of random inspections of finished products, there is 100% control at all stages of production.
Imagine the production of car tires: the system monitors the temperature and pressure of each tire, instantly detecting deviations from the norm and preventing defective products from coming off the line. This approach not only improves product quality but also significantly reduces the cost of rejects and subsequent complaints.
In today’s manufacturing facilities, every second counts, and any downtime results in significant losses. The digital twin analyzes the entire process and finds ways to make it more efficient. This application is especially important in the face of growing competition and the need to reduce production costs.
For example, Shell uses digital twins to create virtual models of their physical assets, simulating their behavior and conditions in real time. These digital replicas help engineers test and optimize processes virtually before applying changes to the physical systems.
At Shell’s Energy and Chemical Park Rotterdam, autonomous robots collect data that is analyzed to identify issues such as corrosion or unsafe practices. By using digital twins, Shell optimizes equipment performance, predicts failures, and ensures smooth, cost-effective operations across its facilities.
A common problem in manufacturing is supply-chain disruptions that can paralyze an entire enterprise. A digital twin helps solve this problem. It can coordinate a complex network of suppliers, production and customers, anticipating potential problems and suggesting alternative solutions.
Just as a navigator finds the best route, taking into account traffic jams, the digital twin finds the best ways to deliver materials and finished products, taking into account timing, cost and possible risks. The system can warn of possible delivery delays in advance and automatically adjust the production plan.
With energy prices constantly on the rise, efficient energy management is critical to maintaining a company’s competitiveness. A digital twin constantly analyzes energy consumption and suggests ways to optimize it by considering numerous factors simultaneously.
For example, in a manufacturing plant, a digital twin can monitor equipment energy use in real time, identify energy-hungry processes, and propose adjustments, such as rescheduling energy-intensive tasks to off-peak hours.
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Training on real equipment always involves risks. An inexperienced employee can damage expensive equipment or get injured. A digital twin completely solves this problem. New employees can practice on virtual equipment without risk to themselves or production, practicing both standard operations and emergency situations.
Just as pilots train to deal with critical situations in an aircraft simulator, machine operators can safely learn how to respond to breakdowns, malfunctions and emergencies. This significantly increases the level of safety in production and reduces training time.
The re-planning of a production facility is a complex and expensive process, where a mistake can cost a lot. A digital twin helps to avoid these risks. Before moving heavy equipment, you can simulate the new layout virtually and see how it will work in practice. The system takes into account everything from forklift routes to the placement of utilities, helping to find the best solution without costly trial and error.
Sudden equipment breakdowns always result in high production losses. A digital twin helps to prevent such situations. Engineers can monitor equipment performance and predict possible malfunctions from anywhere in the world.
The system continuously analyzes data from sensors and can spot even minor deviations that could lead to serious problems in the future. Just as a smart watch alerts you to possible health problems by measuring heart rate and other indicators, the digital twin alerts you to equipment maintenance needs by analyzing vibration, temperature and other operating factors.
Traditional maintenance approaches, such as waiting for something to break or sticking to a fixed schedule, are often costly and inefficient. The digital twin completely changes this pattern. The system constantly analyzes the condition of every piece of equipment and can determine exactly when and what maintenance is actually needed. This provides three important benefits:
In manufacturing, efficient waste management is becoming increasingly important — from both an environmental and economic point of view. Using a digital twin offers an innovative approach to reducing waste. The system analyzes the entire production process and helps find ways to minimize waste before it occurs. It also suggests optimal ways to recycle unavoidable waste.
For example, in a food production facility, a digital twin can:
HQSoftware has extensive experience in integrating various technologies with digital twins to create various solutions for industrial enterprises. Combining digital twins with advanced technologies significantly expands their capabilities and increases production efficiency. For instance, AR/VR in manufacturing enhances visualization and interaction with digital twins, allowing workers to better understand complex processes or simulate real-world scenarios.
Let’s take a look at the main technologies that perfectly complement digital twins and with which our team successfully works.
| Technology | Description | Advantages for manufacturing |
| Artificial Intelligence (AI) | In combination with digital twins, AI significantly enhances their analytical and predictive capabilities. Whereas a digital twin collects and displays production data, AI turns this data into concrete recommendations for process optimization.
AI can predict equipment behaviour, find non-obvious causes of quality problems and suggest optimal operating modes, making the digital twin truly ‘smart’. |
– More accurate predictions of equipment failures
– Optimization of production processes – Automatic identification of defect causes – Intelligent resource planning |
| Augmented Reality/ Virtual Reality (AR/VR) | These technologies add a new dimension to digital twin operations, making them more visual and interactive. With AR, operators can see data from the digital twin directly on the running equipment, while VR allows for a fully immersive virtual production model. This is particularly useful for training staff and planning changes to the production process. | – Fast personnel training
– Reduced service errors – Efficient remote support – Clear data visualization |
| Internet of Things (IoT) | The IoT serves as the primary data source for digital twins, providing them with up-to-date information on the condition of real equipment. IoT sensors continuously transmit data on temperature, pressure, vibration and other factors, allowing the digital twin to accurately reflect the state of the real object in real time. Without this technology, digital twins would be static models unable to track real-world changes. | – Continuous parameter monitoring
– Instant response to deviations – Automation of routine operations – Accurate data for analysis |
Despite all the benefits of digital twins, implementing this technology is not without challenges. Understanding these challenges will help your business better prepare for the digital transformation process and avoid common mistakes.
One of the biggest challenges of working with digital twins is managing huge amounts of data. The system constantly collects information from thousands of sensors, creating massive amounts of data every day. Imagine that every machine in a production facility sends updates on its status every second; this creates a colossal flow of information that needs to be processed correctly. This raises several challenges:
This is like trying to connect a modern smartphone to an old TV set. It is technically possible, but it requires special solutions. Many enterprises still have equipment that was installed 20 to 30 years ago, when no one had conceived of digital twins. Therefore, the following difficulties arise:
When a company tries to implement digital twins across multiple facilities, the complexity of the system grows exponentially. It’s like trying to simultaneously conduct multiple orchestras located in different cities. Key challenges:
Implementing digital twins requires substantial investment at the initial stage. It’s like building a house — the main costs are incurred in building the foundations and basic structures. Investments are required in:
A digital twin is not just a program that can be installed and forgotten about. It is a living system that requires constant attention, like a garden that needs regular watering. Things to consider:
However, it is important to note that all of these challenges can be overcome with the right planning and approach to implementation. Many manufacturers have already successfully overcome these challenges and are enjoying significant benefits from the use of digital twins.
As is true for many digital products, developing a digital twin in the manufacturing industry is a project that can be divided into certain stages. At HQSoftware, we outline 4 main stages:
At this stage, we study regulatory documents, technical maps and instructions. Often, most of the information about the work of the company and its manufacturing processes is stored ‘in the heads’ of employees, so conducting interviews is a very important part of the preparatory stage. The more complete the picture we gather at the beginning of the work, the more accurate the digital twin we create will be.
It’s important to note that, even if a particular process is documented, it may not be carried out ‘strictly according to the instructions’ in real life. It may be executed differently, may not always be executed, or may be ignored completely. Since our task is to reproduce processes ‘as-is,’ it’s important to discuss things with experts in the field, rather than blindly follow regulatory documents.
The development phase is where the digital twin begins to take shape. Using the insights gathered during the research stage, HQSoftware developers start building the digital model. This involves:
In this stage, we test the digital twin by running it on historical data and comparing the results to real-world outcomes. If significant discrepancies arise, we identify the root cause and make adjustments to eliminate errors and inaccuracies.
The goal is to ensure that the digital twin closely mirrors its physical counterpart. Industry experts generally agree that an optimal error margin should not exceed 5%, as this ensures the digital twin is both reliable and accurate.
After testing, the digital twin is ready to be put to use in the real-world environment. At this stage:
After exploring the advantages, challenges, and applications of digital twins, let’s dive into real cases that highlight HQSoftware’s expertise and proven experience.
Our specialists partnered with an American machine analytics company to enhance their system with a predictive maintenance solution. Using AI and Machine Learning, our team developed an advanced algorithm that delivers real-time insights into equipment performance, availability, and production issues.
This enabled the client to address potential failures proactively, reducing equipment downtime by 63.8% and increasing automation by 36%. The project highlights our ability to use digital twins and AI/ML to create practical, efficient solutions for manufacturing.
Another example is an IoT-based system to monitor and analyze pump performance in real time. The HQSoftware team created a solution that aligned with the principles of digital twin technology.
Here are the key achievements of the project:
With this solution, the customer gained a modern, efficient system that mirrors the functionality of a digital twin, offering comprehensive insights into equipment performance and ensuring seamless operations.
If you are interested in digital twin technology, now is the time to contact us and get a free consultation. HQSoftware experts will help you evaluate the potential of using this technology in your specific case, develop an optimal implementation strategy and calculate the expected economic effect.
We understand that every production facility is unique, so we offer a customized approach to your challenges. Whether your company is just considering digital twins or has already started the process, our team is ready to provide the expertise and support you need.
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