Digital twin solutions have proven highly efficient in a number of industries, from healthcare to the oil&gas sector. The application of this technology changes the way companies implement smart manufacturing, and reduces the time and costs involved in industrial production, provision, and repairs.
In this article, we will talk about the business benefits of digital twins (DTs) and offer clues on the approaches to industrial digital twin implementation in your company.
Exploring the DT Potential for Mass Production
Along with IoT and big data, DT development is currently the major driver of digital transformation 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 is predicted to 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 leverages the most recent operational data to create a fully-synchronized replica that the decision-makers can rely on.
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In smart manufacturing, a digital twin connects the industrial IoT to its physical counterpart, which 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 but is also able to adjust the production network of interconnected systems and intelligently respond to changing business requirements.
What is the True Business Value of DTs?
So what are the practical advantages of creating digital twins? The easiest way to see how their characteristics translate into concrete benefits is by considering how they resolve the common problems that enterprises usually face.
Product Quality Control and Improvement
Digital twin solution helps manufacturers to 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 originated, 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.
The reduction of operational costs is a cumulative result of a number of factors:
- Better equipment performance;
- Decreased variability of processes;
- Better engineering and design;
- Timely support and maintenance.
An impact of an enterprise DT boosts the overall efficiency and product quality, which leads to reduced operational expenses.
New Product Launch and Lead Time
A digital twin process reduces not only the costs of a new product but also its time-to-market. The product journey from the ideation stage to consumers is significantly shorter and easier. This is because the information generated by DTs helps identify and eliminate obstacles before they hinder production.
The application of digital twins in manufacturing boosts product quality, reduces maintenance and operational expenses, accelerates innovations, and brings companies tangible competitive advantages. Let’s now explore the types of digital twin uses for innovative manufacturing.
How Do DTs Transform Enterprise Operations?
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.
DTs for Assets
A DT simulation can replicate manufacturing assets: machinery, equipment, production tools, etc. The IoT devices connected to an asset capture its vital metrics, which are later processed in cyberspace and applied to develop an asset’s digital twin model. Thus, manufacturers can view a realistic picture of the asset’s state in its current operating environment, draw the necessary 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.
DTs for People
Workers can also have their representations in the factory’s virtual space. In hazardous environments, factories may use sensors to track the employees’ biological metrics and emotional states to prevent accidents and workplace fatigue. This information can also be leveraged to monitor and improve working conditions and create a favorable environment for human-machine interactions.
DT technology also has practical applications for training in created simulations and testing employee skills.
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DTs for Factories
A digital twin system may also replicate an entire factory environment. Such a digital twin factory will bring you a 3D view of all the interactions within your smart plant. To create a digital twin of this type you will need to ensure the connectivity and data-tracking of all the factory operations.
This may take time but will prove totally worth the effort. A process digital twin will allow you to detect the source of issues and malfunctions quickly, predict resource requirements, detect and eliminate production bottlenecks, and ensure employee security and timely equipment repairs.
DTs for Production Networks
The DT technology enables manufacturers to create full-scale networks connecting every aspect of a business: people, processes, and factories. Moreover, it is also possible to develop a digital twin platform connecting DT networks between companies and gain an unprecedented view of the interactions of the entire supply chain.
The production digital twin connected to the same system in another factory may help to predict performance bottlenecks, resource needs, and environmental impact on a wider scale.
Currently, asset simulations account for the majority of the digital twin applications in manufacturing. As you can see, though, the digital twin use cases, extend much further and the true potential of DTs for enterprises yet has to be revealed.
Today, most enterprises recognize the transformative impact of the digital twin in manufacturing. Some are already reaping tangible benefits. Below is a brief overview of the most spectacular digital twin manufacturing use cases.
7 Large Enterprises Using DTs
Despite the fact that creating digital twins is a relatively new approach, it is already widely embraced by industry giants across a number of segments, from consumer electronics to energy tech. As of today, the list of companies using digital twins to boost their manufacturing processes includes:
#1. Renault Group (Automotive)
The French automotive giant uses the product digital twin approach 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 details of the interior. After the design is ready, the engineering department begins working on the virtual model of all the technological parts: engine, electronics, mechanics, and navigation systems included.
Building a digital twin as detailed as this one enables Renault to test their vehicles before the actual verified design and engineering draft hits production and ensure maximum safety. The manufacturers can check if the vehicle’s modules comply with existing standards and make changes, if necessary, before assembling the actual product.
#2. Kaeser (Machinery Manufacturing)
The German compressor production and service firm is another manufacturer on the list of companies using digital twins. Kaeser uses digitization to expand its product range. Rather than selling compressor units and leaving customers to operate them, the company adopted an as-a-service model. The customer gets charged based on their air consumption rates, and the company leads the unit through its lifecycle along with all the necessary maintenance and repairs.
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.
#3. Unilever PLC (FMCG)
This manufacturing giant offers us one of the most impressive digital twin use cases in manufacturing. The company started out by building 8 DTs of its factories located in different world regions. As of 2020, Unilever has completed more than 100 digital manufacturing sites to create a virtual model of the entire supply chain.
This approach is helping to Anglo-Dutch FMCG giant to 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.
#4. Boeing (Aviation and Aerospace)
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’s other digital twin use cases in manufacturing include calculating cargo balances for the optimal and safe use of cargo room on board the plane.
#5. Bridgestone (Tire Manufacturer)
Another company using DTs is Bridgestone. The world’s top producer of tires and rubber 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%. The DT application also enables the company to share virtual twins of their upcoming products with partners for approval.
#6. FMC Technologies (EnergyTech)
In the energy sector, the oil and gas service company FMC Technologies is taking advantage of DT to improve the quality of their processes, detect and eliminate operation bottlenecks, and plan production in advance to meet future market needs. The company initially implemented DTs to maximize output and adjust its manufacturing lines to higher product quantities.
As a result of the digital twin implementation, the company managed to examine and optimize operational 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.
#7. Electrolux (Electronics)
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?’ and inspirations on how you could 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.
Three Tech Essentials For Digital Twin Development in Manufacturing
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.
Cloud & Edge Computing
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. The digital twin data is stored in a secure cloud environment and could be accessed from any location.
The term “edge computing” refers to the data processing technique, which 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, at least part of your enterprise operation should rely on a cloud-based infrastructure. At Visartech, we offer advanced cloud computing services, from cloud consulting and cloud migration to data engineering to building business-specific 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 for ;
Check out the expertise page to find out more about our cases.
Data Collection & Analytics
Digital twin development requires capturing, storing, and analyzing large volumes of data from various sources to create nearly synchronous simulations and predict 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 comprehensible making them easy to read and decipher by decision-makers. At Visartech we leverage 2D and 3D visualizations and immersive technologies to create visual representations of data that entrepreneurs could rely on in making 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 a variety of 3D sculpting and texturing, modeling, and animation technologies to create comprehensive and appealing interactive representations. These technologies can not only be applied to create simulations and effective visualizations, but also 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 a digital replica of an object, it is necessary to connect it to IoT sensors which will capture the necessary data and metrics on the object’s performance. This data will later be processed by AI and ML algorithms, and the insights it brings will be presented in a comprehensive and convenient visual format.
In custom digital twin development, IoT sensors help deliver useful data about the object’s current condition and synchronize its DT according to the latest alterations in its performance and environment. However, their use isn’t obligatory and will depend on the simulation type that you plan to create.
For manufacturers, digital twin services look promising from a business standpoint. The benefits like high product quality, reduced environmental footprint, and lower operational expenses, not to mention overall operations’ efficiency, urge enterprises to create DT solutions for their products, assets, production lines, or factories.
That being said, a lot of 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 manufacturing digital twin.