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How the World's Biggest Companies Use Digital Twins in Manufacturingby@Slava-Podmurnyi
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2,081 reads

How the World's Biggest Companies Use Digital Twins in Manufacturing

by Slava Podmurnyi7mFebruary 9th, 2023
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Manufacturers use digital twin technology to monitor assets, factories, production networks, and employees efficiency. Digital twins are an analogue of a physical object or process that simulates its characteristics and behavior in real time. The main advantage is the prediction of the quality of the final product and the stimulation to make optimal decisions.
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In the mass production industry, the path to an excellent product can have many challenges. The smart manufacturing era has brought many technologies to market players to solve them. To monitor assets, factories, production networks, and employees efficiency, manufacturers use digital twin technology 🏭

In essence, digital twins are an analogue of a physical object or process that simulates its characteristics and behavior in real time. The main advantage is the prediction of the quality of the final product and, as a result, the stimulation to make optimal decisions for the improvement of internal processes 📈💼

This post aims to inspire you with examples of the digital twin use in the manufacturing industry and to reveal the three essentials for its creation. So let’s dive in! 🐬

How Market-Leading Companies Use Digital Twin in Manufacturing

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.

Tech Basics You Should Consider When Developing DTs 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 them 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 ; 

Frontend development – HTML/CSS, Javascript & jQuery, TypeScript, ReactVue, A-Frame.

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.

IoT Sensors

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.

To give you an advanced understanding of the digital twin architecture, we published this article

Summing Up

Like many other industries, manufacturing is powered by impressive digital twins. The examples of giant companies on the market help a lot to consider the ways and methods of their use 🤔💡

Despite the difference between these methods, they are united by the application of basic techniques - Cloud & Edge Computing, Data Collection & Analytics, and IoT Sensors. With such a combination of technologies, you can create your own virtual double for the implementation of smart production, reducing the time and costs involved in industrial production, provision, and repairs ⏳💰

Also published at https://www.visartech.com/blog/digital-twin-solutions-in-manufacturing/