Developer Experience – from intuitive to complex

It sounds like an exciting vision of the future: users from every discipline can use ready-made program modules to quickly and easily create simulations, optimization tasks or analyses using artificial intelligence (AI). This can then also be implemented by departments whose employees do not have knowledge of a high-level programming language. That’s the idea. Of course, developers must first create these program modules so business users can assemble a solution that meets their requirements.

AI-powered analytics for the business department

Together with our partners, we are researching in the AI marketplace project to get closer to this vision. The name-giving goal is to develop AI applications in the field of the product development process and offer them on a central trading platform. The range will also include services such as seminars on selected AI topics or contract development as well as ready-made AI-supported apps and program blocks for very specific tasks. The development and reuse of the apps are currently being tested. The project team is evaluating the benefits and quality of the results at the same time.

Different programming levels for extended use

So that’ s the state of research, but how exactly do we at CONTACT support the development of reusable program modules, the integration of simulation models or AI-supported analysis methods? One example of practical application can be found in the area of predictive maintenance. Predictive maintenance means that maintenance periods do not take place at fixed intervals as before, but are calculated depending on operating data and events at the machine or plant. For such use cases, our Elements for IoT platform provides a solution to analyze operating data directly. The digital twin stores the data of the machine or plant in a unique context. This data can be directly retrieved and easily analyzed using block-based programming. With the no-code functionality of the IoT platform, departments can intuitively create digital twins, define automatic rules and monitor events, and create diagrams and dashboards – without writing a line of code.

In addition, there are applications around the Digital Twin that require more programming expertise. For this, the platform offers analysts the possibility to develop their models themselves in a higher programming language using a Jupyter Notebook or other analysis tools. Especially in the area of prototyping, Python is the language of choice. However, it is also possible to work with a compiler-based programming language such as C++. Continuous calculation of the predictions is then done by automating the models, which are available in a runtime environment. The code is executed either in the company’s own IT infrastructure or directly at the plant or machine in the field (edge).

We call this procedure low-code development, because only the code for developing the models is written. The data connection is made via the Digital Twin and is done configurationally. The piece of program code can then be reused as a program block for various applications, such as digital twins within a fleet.

CONTACT Elements for IoT is thus open to interactions at different levels: from the use of predefined building blocks (no-code), to the possibility of interacting with self-written program code (low-code), to the definition of own business objects and the extension of the platform based on Python.

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:

  1. 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.

  2. 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.

  3. 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.