Digital Twin

The Digital Twin at the Center of Renewable Energy

According to the German Wind Energy Association (BWE), the share of wind energy in German electricity production this year is 27 percent, and in 2020 wind energy even represented the most important energy source in the German electricity mix. In total, more than 31,000 turbines have been installed, saving 89 million tons of CO₂ equivalent in 2019. Wind power is thus a mainstay of low-CO₂ and sustainable energy generation and makes an important contribution to the energy transition. Further increasing yields while reducing maintenance costs is therefore of great importance.

Increasing the efficiency of wind farms with smart systems

Digital Twins are the central element in exploiting the full potential of wind power and maximizing yields. Driven by the vision of creating a data-based development tool for the wind industry, the WIND IO joint project, funded by the German Federal Ministry for Economic Affairs and Energy, started a year and a half ago.

Under the leadership of the Institute for Integrated Product Development BIK at the University of Bremen, we are working with several consortium partners to build research facilities as cyber-physical systems and retrofit them with sensors, electronics and computers known as IoT gateways. This makes it possible to digitally map all the operating information of the real plant and combine it on a digital twin. The operating behavior can be simulated on the basis of the Digital Twin, which in turn provides insights for further optimization of the wind turbine. The Digital Twin not only provides information about the current energy yield, but also offers a comprehensive overall picture of the condition of each individual turbine.

Improved installation, maintenance and overhaul processes

The information obtained can be used, for example, to optimize maintenance and overhaul processes. For example, the data makes the aging process of components transparent at all times and automatically triggers an alarm if defined limit parameters are exceeded. The Digital Twin also uses the operating, environmental and weather data collected to determine a favorable time for maintenance of the plant. Ideally, this should be carried out when there is little wind, so as not to be at the expense of energy generation.

Both statistical methods and Artificial Intelligence (AI) models are used for the calculations. These methods also help to determine the best time to assemble a wind turbine, since the rotor blades can only be installed under certain conditions. For this purpose, in addition to weather data, additional parameters such as the vibration of the tower are included in the calculations.

Digital Twins for a sustainable industry

The WIND IO project vividly demonstrates the potential of digitization and especially the concept of the Digital Twin. In addition, companies can use their data to simulate entire production and operating cycles. This makes it possible to minimize resource consumption, reduce energy consumption and at the same time coordinate production steps more effectively and optimize transport routes. Concepts such as the Digital Twin and data-intensive analysis methods are thus essential for a gentle and efficient industry.

Black Box IoT?

Who wants to buy a pig in a poke? Especially when you are entering completely new territory with it… The first stroller, for example: you are already aware that you need it, but the decision between a small pack format or the bicycle trailer combination is more difficult.

The last time I bought a baby carriage was some time ago (now I am an expert in buying skateboards). But if you’re just about to make a choice, I recommend a dark model, because you can’t see the dirt so clearly.

An IoT system is usually not as sensitive to dirt, but its selection is all the more complex. Especially since many companies are breaking new ground with it and can already despair of the selection of the right criteria.

Here I have two good news for you. First: Which IoT solution fits is easy to try out. A Proof of Concept is a very good way to test a solution without major risks before you decide on a system. And secondly, as much as IoT offers new opportunities, smart business processes are based on good old business virtues:

Are you sure what your IoT business will look like and that it will stay that way for a long time? Probably not. IoT is a very volatile market where a lot is happening right now. So your IoT system needs to be responsive and best adaptable by the business department itself. The keyword behind this is “low code”, which means no time-consuming programming to map your processes. And if that’s not enough, the system should be so modular that you can simply “reload” additional components.
Does your IoT business emerge on the greenfield or does it expand your existing business? If the second is the case, then your IoT system should be able to talk to the rest of the IT world in your company: Spare parts orders, for example, should generally have passed through financial accounting once. Open or even certified interfaces are the most important thing here as well.
Do you manufacture industrial goods? Do you also have to do with spare parts and maintenance? Then your new best friend in IoT new territory becomes the “Digital Twin”. But only if it’ s also suitable for industrial use: it must be able to map the components of your system in detail (preferably with the corresponding 3D model), know the current parameters such as software statuses and, in particular, be able to document changes after maintenance or conversion.

To be honest, the connection of devices is usually only a question of fiddling, but usually not a fundamental problem. Step by step, standard protocols for machine-to-machine (M2M) communication such as MQTT (Message Queuing Telemetry Transport) or OPC/UA (Unified Architecture) are gaining acceptance and making life easier for everyone involved.

So: Just try it out with a Proof of Concept! If you also pay attention to the three touchstones, you’re in the running. Then the possibilities of “Analytics”, “Big Data”, “Data Driven Processes” or “Predictive Maintenance” are open to you.

Getting started with IoT in 4 steps

Everyone talks about the Internet of Things (IoT) and the digital twin – they form the framework for new, digital business models. According to a forecast by PwC, digitization will bring the manufacturing industry an increase in turnover of more than 270 billion euros in Germany alone over the next four years.

Companies are hoping for sales growth through smart products and digital business models. This is also confirmed by our current I oT study, which was conducted jointly with the Fraunhofer Institute for Production Systems and Design Technology (IPK) and the Association of German Engineers (VDI). It shows that companies have high expectations, but at the same time makes it clear that there is still a certain reluctance to implement the new legislation in practice. Many companies are faced with the question: “How does it actually work with IoT?”

In my experience, companies often think the second way before taking the first step, which leads to restraint. Of course, it is good and important to have a vision. The picture, which is often published in blogs and forums, usually shows very sophisticated IoT scenarios. They don’t start where many companies currently stand with their business model and technology knowledge.

That’s why it’s important to gain your own experience and gradually approach new digital business models, true to the motto Think big, start small, act now!. Own projects, also together with technology partners, automatically expand the wealth of experience. So why not start using the new technology to support classic business?

With my contribution I would like to show how companies can realize an effective IoT scenario for their business in just 4 steps.

Step 1: The digital twin as a communication interface

The necessary data for the d igital twin is usually already available in the company. The first step is a simple serial number. It serves as a documentation interface and connects the data with the product. 3D data is added later. The data is often already available in PLM or ERP systems – for example from production, purchasing or development – and should be displayed in a dashboard.

Step 2: Generate data via sensors

Sensors are also often already available, for example for controlling devices, machines and systems. They record states such as power, pressure, consumption, etc. This data is now consistently recorded and stored suitably. In this way, the current status can always be viewed. In addition, limit values are defined, for example for excessive current consumption, whereupon warnings can be sent and errors rectified.

Step 3: Initiate smart maintenance work

A detailed damage and wear picture can be derived from the analysis of the data and measures such as maintenance projects can be initiated as early as possible. The digital twin serves as a documentation interface. All adjustments to the product thus remain traceable. This data history can later be used for the development of predictions (predictive maintenance). The digital twin as maintained supports the documentation of product changes, can link them with historical data and thus also prove in which configuration the product functions optimally. The classic product lifecycle is thus extended to its usage.

Step 4: Request spare parts

In addition, the information is used to request spare parts. With the help of compressed service parts lists or spare parts catalogs, the data is assigned to the affected component and the required spare part is delivered in the event of imminent damage. This data is also already stored in ERP systems. This process can be triggered manually or automatically on the basis of the device messages. In this way, companies avoid downtime in their own production.

In these 4 simple steps, an efficient IoT scenario has been implemented and a big step towards a digital business model has been taken. I am sure that many companies will be able to get started with the new technology in this way.

So: Get started and use the experience gained for digital business models!