Monitoring machinery in the 21st century becomes an increasingly complex task. There is not only a need for digitalization, but also to manage the increasing complexity of machines and the operations. Additionally, the plant staff is aging and decreasing, creating an additional need for autonomous operations and maintenance. Industrial Analytics offers a state-of-the-art software as a service solution for machinery and industrial processes that enables the autonomous plant of the future. With a combined 40 years of engineering know-how, the company’s services and products equip operators with deep machinery knowledge and cutting-edge machine learning algorithms. Therefore, optimizing machines and processes to increase energy efficiency, enable prescriptive maintenance and performance optimization is where we set our focus and specialize in. 

Interview with Florian Stark, Business Development & Sales at Industrial Analytics IA GmbH.

Easy Engineering: Which are the fields of activity where you are operating?

Florian Stark: Our work focuses on the development of software enabling operational excellence of machines and processes. Our main areas of expertise are in vibration analysis and data analytics both on the edge and in the cloud. With our software-as-a-service business model our clients are gaining actionable insights into their machinery and operations, reducing monitoring efforts, gaining energy efficiency and a prescriptive maintenance which saves resources through an extended remaining useful life (RUL) of equipment and condition-based maintenance cycles. Our technology is in place within energy providers, gas storage and transport facilities, chemical industries, food & beverage manufacturing and in the transport sector.  

E.E: Which are the most significant projects from 2022?

F.S: We have taken many new developments with us from recent years. The Deutsche Bahn Mindbox Challenge, for example, has now resulted in an intensive collaboration that is now part of a project with the German Aerospace Institute, the University of Stuttgart and others. The vision of the project is autonomous driving and maintenance of trains within the fleet of the Deutsche Bahn. With our solutions, we lay the basic infrastructure for future developments and are pioneering in the field of object recognition and data analytics in trains.

In 2022 we expanded our client portfolio to industries such as food & beverage. Additionally, we acquired a new utility client helping to optimize compressors for gas storage facilities in the North of Germany. 

The greatest milestone so far in 2022 came in August. Infineon Technologies AG acquired 100% of our shares and we are now operating as part of the Industrial Power Control Unit of Infineon. This successful merger is a great opportunity for us to scale our services into new markets and increase the quality of our services with a strong partner in the back.

E.E: What projects were the most challenging?

F.S: Working in the field of high performing, power intensive assets is always a challenging environment due to the dependencies on external factors such as energy prices. The energy crisis evolving in the beginning of 2022 has definitely had its influence on our work. But to some extent in a positive way. The conviction that increasing energy & resource efficiency within power intensive industries is one of the most pressing challenges of our times, has arrived within the boards of many potential clients of ours. Today, saving energy and resources is not an ecological decision anymore but rather a financial one.

E.E: What are the usual challenges you encounter? 

F.S: Generally, clients reaching out to us are looking to digitize their operations and gain quicker value from machine and process data. Our clients are looking to improve their operations and maintenance strategies. We support our clients in their strategies by supplying AI services that are going beyond a simple monitoring of machine data. In collaboration with our clients, we build digital twins that are taking the physical correlations of machine components into account. Our machine learning models are hybrid, taking statistical data coming from the machines, calculated data and direct operator feedback into account. The latter is collected from operators maintaining and operating the machine day in day out. With this comprehensive way of digitally mirroring the machines, simulating potential changes and comparing actual behavior of the machine with ideal behaviors, our services unlock efficiency potentials and give actionable recommendations on how to do preventive measures and setup adjustments.     

E.E: How did you overcome the challenges?

F.S: As always, we develop our solution with our clients. Hand in hand we walk the path to the best strategy for our clients. It is very important to us to co-create and not develop solutions that are not recognized in the market. And so, we are working with our clients to overcome the current most pressing topics such as high energy prices, the need to decarbonize industrial processes and to save resources by prolonging the remaining useful lifetime of machines.

E.E: Which are the most innovative products/solutions in your lineup?

F.S: In 2022 we have expanded our services to AI assisted energy management within our product portfolio. The development of our energy management solutions stems from the need of our clients expressed in our regular feedback sessions and customer success evaluations. The need for energy management corresponds to the current increase to decarbonize operations. 

E.E: What was the research behind the products/solutions?

F.S: Research behind the development of energy management solutions was extensive. We increased the knowledge within our team with new colleagues that have experience in the field of energy management. Additionally, we have researched the market carefully and identified USPs that could be ideally connected with our existing services so that we can make use of a competitive advantage of us which is the AI services we have already in offer. 

E.E: What products / solutions were used in the projects?

F.S: Our AI services include the performance optimization of rotating equipment and high performing assets in general. Secondly, we build digital twins of our clients machines and processes which help to build up our prescriptive maintenance solutions, enabling our clients to prolong maintenance cycles, uncover inefficiencies and increase the remaining useful lifetime of machines. As mentioned, the newest services in our portfolio are the energy management services that enable our clients to report, monitor and optimize their energy consumption. All services have been used and implemented within our projects in 2022.

E.E: Why did the clients choose your products / solutions?

F.S: Our solution is based on our engineering expertise and experience. We use physical models, also called first-principal models, that are combined with other models and machine learning. With our digital twin the user can understand the correlations within the machinery and can see the dynamical behavior of the machinery. In our dashboard we are not only gathering the data from the machinery, but also from the operator. Our AI algorithm learns from the operator feedback and will notify the operator in the future when the failure occurs again. We use pre-trained models for different equipment like compressors, steam turbines etc., so the client doesn’t need extra data scientists to implement our solution. We build a scalable solution with an open IT architecture that is independent from manufacturers and solves client’s challenges. Due to those differentiation, we have towards our competitors our clients choose our services and trust our team.

Industrial Analytics IA GmbH powered by Infineon Technologies AG

Erkelenzdamm 59-61

10999 Berlin, Germany

https://industrial-analytics.io/

info@industrial-analytics.io