How Industrial Digital Twin Helps to Enhance Productivity

Digital twin solutions have proven highly efficient in many industries, from healthcare to the oil&gas sector. This technology simplifies smart manufacturing for companies and reduces the time and costs involved in industrial production, provision, and repairs.

In this article, we discuss the business advantages of digital twin in manufacturing and guide you on implementing this tech solution in your company.

Along with IoT and big data, DT development is currently the most popular digital solution in manufacturing. The stats are quite revealing: the mass production industry is the largest market for digital twin services. The global value of the DT market for manufacturers can reach 6.69 billion in 2025, as stated by Statista.

In the section below, we will explore how exactly it accelerates the production processes in manufacturing and achieve higher efficiency.

But what is a digital twin in manufacturing, by definition?

The digital twin recreates physical objects, assets, and operations, allowing for timely and cost-effective optimization, process monitoring, improvement, and maintenance. The digital twin in manufacturing uses current operational data to create a synchronized copy that executives can rely on.

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In smart manufacturing, a digital twin connects the industrial IoT to its physical counterpart. It serves to build an abstraction of a real-world object in a digital space. The metrics from the object are then used to model and predict its status in the ever-changing working environment.

The most revolutionary thing about applying the digital twin for manufacturing is a step from analyzing the past to recreating real-time dynamics and predicting the future. For businesses, this means avoiding unnecessary expenses and achieving a competitive advantage.

The digital twin model evolves and reflects real-life changes in processes, personnel, and machinery. The DT system not only improves the productivity of a single production line. It also adjusts the production network of interconnected systems and responds to changing business requirements.

So what are the practical benefits of digital twins? To understand how their characteristics translate into concrete benefits, let’s see how they resolve the common problems that enterprises usually face.

Product Quality Control and Improvement

Digital twin solution helps manufacturers improve the overall quality of goods, due to the timely detection and prediction of possible defects. They can also detect when exactly the quality issues occurred, making it easier to determine and eliminate their cause.

Warranty Costs and Services

Digital twin data sends manufacturers real-time reports about the equipment state, which helps predict and prevent possible breakdowns. This potentially enables them to save on warranty and support costs and run maintenance routines exactly when needed.

Operations Cost

The reduction of operating costs is a result of these factors:

• Better equipment performance;
• Decreased variability of processes;
• Better engineering and design;
• Timely support and maintenance.

Digital transformation in manufacturing boosts the overall efficiency and product quality, which leads to reduced operating expenses.

New Product Launch and Lead Time

A digital twin process not only reduces the costs of a new product but also speeds up its launch date.  The product journey from the ideation stage to consumers is shorter and easier. This is because the information generated by DTs helps identify and eliminate obstacles before they hinder production.

The digital twins in manufacturing boost product quality, reduce maintenance and operating expenses and accelerate innovations giving companies competitive advantages. Let’s now explore how we can use this tech solution for innovative manufacturing.

Practically speaking, there are four ways in which enterprises may leverage digital twins in the manufacturing industry. We could also view these aspects as angles from which DTs are impacting smart manufacturing.

A DT simulation can replicate manufacturing assets: machinery, equipment, production tools, etc. The IoT devices connected to an asset capture its vital metrics. We can then process them in cyberspace and apply them to develop an asset’s digital twin. Thus, manufacturers can see an accurate representation of the asset’s condition in its current environment, make conclusions and take action.

An example may include factory machines equipped with sensors that monitor their temperature, vibration, rotation rates, etc. If any of the machines suddenly fails, the DT can quickly estimate the cause of its failure. Better yet, it can report the equipment state before the malfunction and automatically schedule repairs.

Workers can also have their representations in the factory’s virtual space. Factories in dangerous settings can monitor employees’ physical and emotional well-being with sensors to avoid accidents and exhaustion. You can also use this information to monitor and improve working conditions and create a favorable environment for human-machine interactions.

Besides. digital twin technology has practical applications for training in created simulations and testing employee skills.

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A digital twin system may also replicate an entire factory environment. Such a factory digital twin will bring you a 3D view of all the interactions within your smart plant. To create a plant digital twin, you need to connect all factory operations and track data.

This may take time but will prove totally worth the effort. A process digital twin can detect the source of issues and malfunctions quickly, predict resource requirements, detect and eliminate production bottlenecks, and ensure employee security and timely equipment repairs.

The DT technology enables manufacturers to create full-scale networks connecting every aspect of a business: people, processes, and factories. It’s also possible to develop a digital twin platform connecting DT networks between companies. By doing this, we can view the interactions of the entire supply chain.

The production digital twin connected to the same system in another factory helps predict performance bottlenecks, resource needs, and environmental impact.

Assets simulation is currently the most common way of using a digital twin solution in manufacturing. As you can see, though, the digital twin use cases extend much further. So the true potential of DTs for enterprises yet has to be revealed.

Today, most enterprises recognize the impact of the virtual twin in mass production. Some are already reaping benefits. Below is a brief overview of the most spectacular digital twin examples.

Even though creating a digital twin is a new approach, industry giants from different segments have already embraced it. Today, the list of companies using digital twins to boost their manufacturing processes includes:

The French automotive giant uses the virtual digital twin to develop virtual copies of real-world vehicles before they are produced. The product journey begins with creating the virtual vehicle design: from shape and appearance up to the smallest interior details. After the design is ready, the engineering department begins working on the virtual model of all the technological parts. It includes engines, electronics, mechanics, and navigation systems.

By building a digital twin like this, Renault can test their vehicles before producing the final design and engineering version. This ensures maximum safety. The manufacturers can check if the vehicle’s modules comply with existing standards and make changes before assembling the actual product.

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The German compressor production and service firm is another manufacturer on the list of companies using digital twins. Kaeser uses the technology to expand its product range.

Rather than selling compressor units and leaving customers to operate them, the company adopted an as-a-service model. Kaeser charges the customer based on their air usage. Taking care of the unit throughout its lifecycle, including maintenance and repairs, is up to the company.

The DT lets the vendor know about everything that happens to a product or asset before the customers even notice any changes in the unit’s operations or behavior. The digital twin process enables Kaesen to eliminate problems before they become possible and develop predictive maintenance programs for their products.

This manufacturing giant offers us one of the most impressive examples of using the manufacturing digital twin. The company started out by building 8 DTs of its factories located in different world regions. As of 2020, Unilever has built over 100 digital manufacturing sites to generate a virtual model of the whole supply chain.

This approach helps the company boost productivity, cut waste, optimize material usage, and ensure high compliance and quality. Every factory process gets monitored with sensors sending data to an enterprise cloud where the DT is recreated. The employees on sites can assess the DT data via handheld devices, model problems and solutions, and share data with colleagues.

The world’s largest aerospace company is using DTs for aircraft modeling, engineering, and design. The need to organize, manage and derive information from loads of data prompted Boeing to create a digital twin of every asset and system involved in production. Boeing plans to share the results of this fundamental project with the supply chain participants.

The DTs are now helping the airspace giant to predict product components’ performance in varying conditions, and plan repairs and replacements. Boeing also uses a digital twin to calculate cargo balances for the optimal and safe use of cargo room on board.

Another example of digital twin in operation is a Bridgestone case study. The company uses product DTs to estimate how various conditions including driving styles will impact their products. This helps vehicle fleets pick the optimal tire options for their purposes. Thus, the application of DTs helps increase product lifespans and protect the wheels from breakages.

The company also uses virtual models to test and design its products. Running tests in a virtual environment helps Bridgestone accelerate production by almost 50%. Moreover, the digital twin applications in manufacturing allows them to share copies of upcoming products with partners for approval.

FMC Technologies uses DT to improve the processes’ quality, detect and eliminate bottlenecks, and plan production in advance. It helps them to meet future market needs. The company initially implemented DTs to maximize output and adjust its manufacturing lines to higher product quantities.

DTs allow them to examine and optimize operating processes, evaluate resource requirements, reduce risks, and make informed decisions about equipment spending. FMC Technologies expanded the production throughput by 50%, due to digital manufacturing.

The Swedish domestic electronics manufacturer runs 48 production sites and has a comprehensive digitization strategy. Its first steps involved the simultaneous launch of several manufacturing projects. Consequently, the company plans to create digital twins for all of its production facilities.

The company built a simulation of both the factory and the material flow in order to boost production capacity and efficiency. Due to the implementation of the pilot project, Electrolux managed to bring the products and manufacturing lines to the desired standard. Further, the company plans to launch a series of employee training to familiarize all its workers with the DTs.

The examples above should have given you an answer to the question of ‘What is digital twin in manufacturing?’. They also can give inspiration on how to use this technology to boost the efficiency of your facility. In the next section, we will cover the essential technology for custom digital twin development.

To create digital twin solutions, organizations leverage a combination of cloud computing, data analytics, and IoT. Let’s now explore these technologies in a little bit more detail.

Digital twin solutions feed on data to generate information that manufacturers could rely on in making decisions. Cloud computing allows organizations to store and operate large volumes of data, which would be nearly impossible to accomplish on-premises. By storing digital twin data in a secure cloud environment, you can access them from any location.

The term “edge computing” refers to the data processing technique. This technique distributes processing capacities closer to the data source, rather than moving the data to a processing facility.

 

To take full advantage of the digital twin technology, you should rely on a cloud-based infrastructure. At Visartech, we offer advanced cloud computing services. They can include cloud consulting, cloud migration, data engineering, or building SaaS apps. The technologies we use include the following. 

• Database building – Microsoft SQL Server, MySQL, PostgreSQL, MongoDB, Redis, Azure Cosmos DB, Azure Table Storage, and Amazon DynamoDB.
• Infrastructure services – Amazon Web Services, Microsoft Azure, Google CloudPlatform, Docker, Kubernetes, and Firebase.
• Web backend – NodeJs, ASP.NET, Java, Django/Python.
• Frontend development – HTML/CSS, Javascript & jQuery, TypeScript, ReactVue, A-Frame.

Check out the expertise page to find out more about our cases.

Digital twin development requires capturing, storing, and analyzing large volumes of data from various sources. This allows the creation of nearly synchronous simulations and predicts the objects’ behavior in changing conditions. Deriving information from raw data requires developing data analytics algorithms that would generate insights from the incoming metrics.

On top of that, insights should be clear making them easy to read and decipher by executives. Visartech uses 2D and 3D visualizations and immersive technologies to produce visual data representations that entrepreneurs can use for informed decisions. The tech stack we use consists of the following:

• 3D engines – Unity, PlayCanvas, Babylon.js, and three.js.
• Desktop and standalone VR kits – Steam VR, HTC Vive, Oculus VR, and Windows Mixed Reality.
• Mobile VR experiences – Google VR.
• Mobile AR – Apple AR Kit, Google AR, and CoreVuforia.

We also use many 3D sculpting and texturing, modeling, and animation technologies to create comprehensive and appealing interactive representations. With these technologies, we can also provide virtual training services, virtual tours, collaboration environments, and interactive apps.

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IoT is another essential technology for creating digital simulations. To develop operational digital twin, it is necessary to connect it to IoT sensors. These sensors will capture the necessary data and metrics on the object’s performance. Artificial intelligence and machine learning algorithms then process this data and present the resulting information in a convenient visual format.

In custom digital twin development, IoT sensors help deliver useful data about the object’s current condition. They also synchronize their DT according to the latest changes in its performance and environment. However, their use is optional and will depend on the simulation type that you plan to create.

For manufacturers, digital twin solutions look promising from a business standpoint. Enterprises are driven to develop this technology for their products, assets, production lines, or factories because of its benefits. Among them are high product quality, reduced environmental footprint, lower operating expenses, and overall operations efficiency.

Many companies across industries need a helping hand in building the necessary infrastructure and setting up the environment for successful digital twin implementation. At Visartech, we have experience in building simulations and visual representations, and expertise in technologies necessary to create an efficient digital twin in manufacturing.

Wondering how digitalization in manufacturing will help you reach your business objectives? Contact us now for a free consultation!