Smart factory? Not without a digital twin
Digital twins for machines and production equipment are an important part of the Industrial Internet of Things, or Industry 4.0 for short. Digital Twins use IoT data to optimize both production and products.
When the premier of the German state of North Rhine-Westphalia, Armin Laschet, received the first e.Go in May 2019, four years of development work had already been put into the Aachen-based e-car manufacturer. But it’s not only the 3.35-meter-long electric car’s affordable price tag that’s convincing: e.Go Mobile AG is also one of the first companies to produce an electric car in a smart factory. It relies on a so-called digital twin, which allows the simulation of a machine or product operating in the real-world. With the digital twin, data can be collected and evaluated showing how the original would behave in certain situations. The effect? During the development phase, the engineers at e.Go Mobile were able to decide more quickly and intelligently what the next steps should look like. In addition, the digital twin at e.Go reduces production downtime and increases product quality. Even after a vehicle has been sold, data still flows back into the digital twin.
TWO THIRDS OF COMPANIES PLAN TO USE DIGITAL TWINS
The digital image of a smart factory is an example of how more and more digital twins are finding their way into companies. According to a Gartner survey on IoT usage in mid-2018, only about 13 percent of the nearly 600 companies surveyed had deployed virtual images in production. But another 62 percent said they wanted to introduce digital twins within a year. The analysts therefore assume that by 2021 half of all industrial companies will already be using a digital twin.
ALTER PRODUCTS WITH REAL-TIME DATA
What do companies expect from these virtual images? Interest is primarily being driven by the Industrial Internet of Things (IIoT), which is also known as Industry 4.0. The Internet of Things allows the digital twins to mirror the complete development, production and operating cycle of a product or system. Users equip their products with IoT sensors in order to reduce downtime and repair costs on the basis of current machine data, or to individually design their products.
EVALUATING IOT DATA WITH AI
Permanently networking a physical object with its twin means both develop identically at all times. So once created, a digital twin accompanies a product through its entire lifecycle. IoT sensors record operating data in real-time and send it to the cloud. There all information is collected on a digital platform so machine learning and AI algorithms can evaluate the data. This has two main advantages: A product can be optimized during operation and maintenance can be scheduled precisely. And the data helps manufacturers improve the next generation of their products.
AN EXACT IMAGE OF THE REAL FACTORY
As is already the case today with e.Go Mobile, companies will be able to map entire factories with a digital twin in the future. This digital twin will depict machinery, other means of production, buildings, utilities and whole processes in data models. These will then be virtually redesigned as required. In the smart factory, everything revolves around real-time operation and optimization. To do this, the virtual factories and production systems must be an exact replica of the real factory – and not just the geometry and kinematics like a 3D model does.
Five popular application scenarios for digital twins
- Product development
- Product redesign
- Real-time quality management
- Systems planning
- Logistics planning
A DIGITAL TWIN CAN EVEN OPTIMIZE ITSELF
All physical objects – tools, machines, each part and product to be produced, but also factory buildings, robots and autonomous transport units – are represented by digital images in a smart factory. The logical behavior and control of the manufacturing units are also part of a digital twin. The individual components of a virtual factory communicate with each other just as they do in the real environment of a smart factory. This ensures the digital twin can organize and optimize itself independently.
“Regardless if it’s a machinery, shoe or bicycle maker: A digital twin is worthwhile for all kinds of manufacturers. They don’t leave things to chance during the product development phase, for example, when it comes to research and development.”
Frank Lamack, Senior Consultant at T-Systems
“Regardless if it’s a machinery, shoe or bicycle maker: A digital twin is worthwhile for all kinds of manufacturers. They don’t leave things to chance during the product development phase, for example, when it comes to research and development.”
Frank Lamack, Senior Consultant at T-Systems
It’s like having a copy of one of the world’s largest Tetra Pak warehouses in Singapore – only one is real and the other is its digital twin. DHL has been simulating the warehouse since June 2019 using a combination of IoT and data analysis to monitor all processes in the smart warehouse in real-time – around the clock. The DHL warehouse enables Tetra Pak to reduce bottlenecks, conserve resources and distribute the workload better.
Data sources for digital twins (Source: Gartner)
- CAE-Software / 48%
- ERP / 47%
- MRO / 45%
- Sensoren (IoT) / 44%
- System Engineering / 44%
Further information:
Daniel Kunz
Expert Digital Marketing
Digitization and the Internet of Things are among the favourite topics of Daniel Kunz. He has been with Deutsche Telekom since 2017 and regularly writes about technology trends and many exciting topics, especially for the retail trade and the logistics industry.
Daniel Kunz
Expert Digital Marketing
Digitization and the Internet of Things are among the favourite topics of Daniel Kunz. He has been with Deutsche Telekom since 2017 and regularly writes about technology trends and many exciting topics, especially for the retail trade and the logistics industry.
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