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IoT-Enabled Device - Finding the Right Software Solution

Using value-added services correctly

Reaching Your Goal With Data-Driven Applications - Iot-Enabled Services
Digital Transformation

In this phase of the IIoT maturity model, the foundations of machine networking are laid in the existing IT infrastructure. The focus is now on application areas that emerge from the company's IT ecosystem. These include all current and future applications and services based on collected data that offer decisive added value for the company. These include monitoring, behavioral monitoring, and maintenance topics.


The data collected by IoT-enabled machines can and must be analyzed extensively. This data basis results in numerous use cases for which specific software is developed. The following is an example of the possibilities for transferring data into value-adding applications.

Software for Monitoring System Functions and Behavior

The first application is software for directly evaluating machine data to obtain an overview of production in real-time. Continuous data acquisition enables the software to analyze various current parameters, data, and production processes. This subsequently provides valuable insights, for example, into the machine's performance. For a machine manager, one task is finding the optimum operating parameters. A comparison between historical and current operating data is an essential approach and ultimately promotes production efficiency.


However, it is not only possible to find the optimum machine parameters with the help of software. The permanent connection between software and machine also makes it possible to identify potential bottlenecks and machine failures early. A key point here is the integration of notifications and warning messages into the application. This means that all response times to sources of error can be reduced cost-effectively.

Software for Predictive Maintenance

Another critical factor that offers significant added value is predictive maintenance. The fundamental difference is that the software is based on simulation models and various approaches and algorithms, such as artificial intelligence, machine learning, and data mining. The collected data flows into the software as a basis from which corresponding maintenance strategies can be developed and derived. Among other things, this makes it possible to instruct maintenance work in good time and at an early stage and to minimize unplanned downtimes efficiently through preventive measures. As a result, machine downtimes are minimized, and service staff time is put to optimum use.

Software for Visualization

To make the above possible, visualization is crucial for decision-makers. This is because both the real-time data from the machine and the data processed in the cloud are primarily used to obtain information. However, information must be understood in a specific context depending on the use case. Ultimately, the information obtained from the data is used for business decision-making. It is precisely for this purpose to be converted into clear and understandable forms of presentation and visualization.

Transformation to the “IoT-Enabled Device”

With the secure and stable connection of the machines, numerous applications are conceivable that go beyond the use cases described above. In combination with efficient interface management (APIs) and good architecture governance, software solutions from different manufacturers can be used according to a plug-and-play principle. Networking across specialist departments (end-to-end process), with partners, or with the company's competitors (e.g., Manufacturing X) enables high innovation speeds, new sources of growth, and reduced maintenance and administration costs for the IT infrastructure.


The transformation to an "IoT-enabled device" allows companies to make their machines smarter and more responsive and thus offer customers more significant benefits. This step requires the successful implementation of the previous steps and is crucial for realizing the full potential of IoT integration. This is where the partnership between Arvato Systems and TTTech Industrial with the Nerve software platform comes in. They help you with this all-encompassing implementation to lead your company to a new IT standard. Once this has been achieved and the value-added services have been implemented correctly, the final step is introducing the hyperautomation processes and enhancing the benefits using artificial intelligence. We will inform you about this in the next and final blog post in the series on the IIoT maturity model.

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The authors

Johannes Fuhrmann is Head of Strategic Business Development at Arvato Systems. In this role, he is responsible for the portfolio and product development for the manufacturing industry. His focus is mainly on the topics of digital twin, digital administration shell and the development of shared data ecosystems in the industry. Prior to his career at Arvato Systems, Johannes Fuhrmann held various relevant positions within the manufacturing industry. For example, he worked as a Senior Consultant for Industry 4.0 at Deloitte Consulting and as Head of Digital Operations and Business Development at VELUX. Johannes Fuhrmann completed his studies at the University of Warwick with a Master of Science (MSc.) in Information Systems Management. He also holds a Bachelor of Arts (B.A.) in Technical Business Administration from the Hamburg University of Applied Sciences (HAW Hamburg).

Konstantin Klein has been Business Development Manager at TTTech Industrial Automation AG since 2022. In his role, he is responsible for the operational and strategic development of the Nerve product. The focus is primarily on the topics of EDGE computing, virtual PLC and the integration of technologies for digitization strategies for machine builders.

Mr. Klein has gained a lot of experience in discrete automation at ABB / B&R as Product Manager Industrial IoT Network Solutions. After finishing school and training as an electrician, he graduated from the Leipzig University of Applied Sciences with a Master of Science (M.Sc.) in Electrical Engineering and Information Technology for automation technology.

Written by

Fuhrmann, Johannes
Johannes Fuhrmann
Head of Strategic Business Development
ArvatoSystems_MA_Konstantin Klein
Konstantin Klein
Business Development Manager at TTTech Industrial Automation AG