The magazine of Friedhelm Loh Group

The magazine of Friedhelm Loh Group

Digital twin
Innovation – Eplan

What is the potential of the digital twin?

A true trailblazer. The digital twin plays a key role in digitization, helping companies expedite innovations and boost productivity.

Text Sonja Koesling ––– Photography

According to research on twins, their genetic features are not the only reason they feel, think and act alike. External environmental influences are also a factor. Common experiences cause twins to develop in the same way. Scientific research into what it is to be a twin dates back almost 150 years. By comparison, research focusing on the virtual equivalent – the digital twin – is still in its infancy. Despite that, the digital twin has become synonymous with the industrial revolution and is feted as a key trailblazer accompanying Industry 4.0.

According to IDC FutureScape 2018, just two years from now, 30 per cent of the world’s 2,000 largest companies will be using data from digital twins to improve the success rate of product innovations and raise productivity. The market research company is forecasting productivity gains of up to 25 per cent. Gartner, another market research company, also sees digital twins as a positive development. It predicts that half of large industrial companies will already be working with these virtual avatars by 2021 and improving their productivity by up to ten per cent as a result.

New value creation

“The digital twin opens the door to new, exciting areas of business for industrial companies,” agrees Prof. Rainer Stark, Chair of Industrial Information Technology at the Technical University of Berlin and Director of the Virtual Product Creation division at the Fraunhofer Institute for Production Systems and Design Technology IPK, whose research in this field dates back ten years. “Value creation used to be confined to the real world, but the digital twin is now laying the foundation for companies to obtain information from the actual product life cycle for further processing. This gives models that have to date been restricted to the start of the development chain a new value creation component and they now accompany a product throughout its entire life cycle,” he explains.

In the automotive industry, for example, this could help create a more customised driving experience by offering additional functions that suit a particular driving style. Use-based findings could also be incorporated into the design of further models. In the production environment, there is potential for deviations from the norm to be detected and rectified faster because problems such as tool wear would be identified at an early stage. Ad hoc changes to production workflows would also be conceivable, with their effects being simulated prior to commissioning. According to industry association Bitkom, the economic potential of all digital twins in the production sector will total over 78 million euros by 2025.

An empathic nature

This is all down to the nature of the digital twin. “The way the digital twin is interpreted varies a great deal. According to our definition, it’s the digital depiction of a specific product, using models, information and data to define this product’s characteristics, status and behaviour. It’s based on a digital master – the original virtual model according to which the product is to be manufactured,” says Stark. In the digital master, developers define what the product will look like and how it will work. Attribute models are then added. These computation models provide information about what happens if the product starts vibrating, how it reacts to impacts or collisions, how it is opened and closed, and so on.

Efficient twinning

The applications of digital twinning are wide-ranging, as the following three examples from different sectors show:

In water
Cruises are becoming increasingly popular. Maintaining ships is an expensive business, so General Electric is looking to equip cruise liners with sensors that measure wear and also factor in weather-related data. The intention is for a digital twin of the vessel to simplify maintenance and repairs by enabling engineers to simulate possible solutions using the virtual avatar before the ship comes into dock.

On foot
Fashion-conscious consumers want the material, colour and fit of their sports shoes to be customised. Adidas is working with Siemens to develop a digital twin of the Adidas Speedfactory production facility so that it can be flexible in catering to customer requirements. In the future, this will enable the entire production process to be simulated, tested and optimised. The sports industry is a frontrunner when it comes to fully customised products.

Under the skin
Charité Berlin is combining biology and IT. The university hospital has joined forces with biotech company Alacris Theranostics to produce the digital twin of a cancerous cell taken from skin cancer patients and is testing the effects of various drugs on it. If the drug works, it is administered to the patient. Initial treatments have proved successful.

“Some people believe that’s all there is to the digital twin, but our definition goes further. Each product creates a digital shadow with operating, status and process data. Only when a link is created – that is to say an intelligent connection between digital master and shadow – do we have a true digital twin,” Stark continues. In other words, the digital master is enhanced by real data from actual product usage and thus enables conclusions to be drawn and changes or optimisations to be tested and implemented.

However, the concept can only work if companies adopt a software-based design approach. “Many mechanical and plant engineering companies currently still rely on a mechatronic design approach in which functional integration is followed directly by physical integration in the form of a prototype,” explains Stark. The majority of companies will need a rethink to bring about the digital transformation. They will only succeed if rigid process chains are broken and replaced by functional units that communicate with each other. The key to a common language lies in standardising data formats. The data structure constitutes the DNA of the digital twin.

Simply a matter of negotiation

The Smart Engineering and Production 4.0 technology network is devising a solution for vertical data integration in the engineering and production process. Based on the example of an enclosure, partner companies Eplan, Rittal and Phoenix Contact are creating a digital twin to accompany the product throughout its life cycle – from development and commissioning to operation and maintenance.  “Detailed digital descriptions of the product’s individual components, functions and special features form the basis for this. Given that eCl@ss is becoming established as the global standard-compliant solution for classifying products and describing them unambiguously, manufacturers are already feeding component data in this format into the Eplan Data Portal,” says Eplan Product Manager Thomas Weichsel. “This represents a practical additional benefit for our company because it makes accessing product information very straightforward – by scanning in a QR code, for example,” adds Dr ­Andreas Schreiber, Head of Business & Product Innovation at Phoenix Contact. The main potential as he sees it lies in the ability to make the entire product life cycle more efficient and transparent, with all relevant product features available in a standardised form for both engineering and production processes. “That dispenses with the subsequent time-consuming manual steps of obtaining this data and entering it in the system,” says Schreiber. Enclosure manufacturer Phoenix Contact is therefore using Eplan Pro Panel software to design a 3D model that already provides full details of the individual wires, equipment, terminal blocks, wire bridges and signage as well as the component machining processes required. The digital master is now defined.

“The next step is using a manufacturer-neutral interface to incorporate the digital prototype into the production environment and, for example, into an intelligent production control system,” explains Weichsel. This system then checks which production steps are needed, whether production can meet the requirements for the relevant step and in which order these requirements can be met. “It’s always a case of using the data in the engineering process and implementing it in a machine control system for production purposes. This enables components to be prepared for machining, support rails to be made the correct length and terminal blocks to be fitted onto these as specified,” says Jan-Henry Schall, Head of the Rittal Innovation Center.

Connecting element

If this step is to be automated, the control system and machinery need to communicate and negotiate to agree on the upcoming tasks. “We’re making use of findings from the open Asset Administration Shell project initiated by RWTH Aachen University and the ZVEI industry association, which are working with mechanical engineering companies and the electrical industry to put Industry 4.0 into practice. And we’re adding specific switchgear engineering applications to these findings,” reports Weichsel. The project defines administration shells for all systems, machinery and components in a given value chain that are involved in the process and negotiate with each other. “It already works on a simple level,” reveals Weichsel. The aim is for systems also to be able to negotiate highly complex processes and production workflows in this way in the future. Having a positive impact on engineering decisions by factoring in production findings is just one example. “That’s currently a long way off, but we already revealed some initial progress at Hannover Messe,” says Weichsel.

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