Projects with practice partners
Your bridge builder for automation, digitization and artificial intelligence: Experts and scientific staff at the Kronach AI Hub work with you and your team to sharpen the focus on potential AI application areas in your work environment. With expertise and professional hardware equipment, we put the ideas into practice.
Servo presses are required in the manufacture of ceramic ignition systems (e.g. for heating systems) to join ignition ceramics to retaining plates. When using servo presses, however, it can happen that the ceramic components - not visible from the outside - are destroyed. The pressing process can be mapped using measurement curves and therefore optimized with the aid of machine learning. In this way, rejects as well as time-consuming and costly test runs in quality inspection can be reduced.
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Grinding machines must be serviced regularly, and in the event of a fault, action must be taken as quickly as possible in order to optimize the intervals between grinding belt changes and thus keep downtimes to a minimum. Can the fault case be predicted on the basis of production noises? Artificial neural networks (here: Auto Encoder) were used to learn and predict, based on the grinding noise, when the next fault case and thus the need for grinding belt change will occur.
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Assessing the stability of a deep drilling process and thus the quality of the end product is extremely complex. In order to gain better insights for this, data from acceleration sensors were used to describe the drilling process in the form of artificial neural networks in an abstracted manner. In this way, it is possible for the AI models to be trained and to detect anomalies in the deep drilling process based on the acceleration data of the deep drill. This can significantly reduce material wear as well as scrap.
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For complex components such as liquid distributors, the calculation of manufacturing costs is very complex, which makes it difficult to create a valid quote. Based on various historical data from an SAP database in combination with AI models, the factors influencing manufacturing costs could be better understood and future cost estimates optimized. For example, the necessary CAD hours can be predicted via the predicted number of screws per component.
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The certificate course in digitization
The certificate course in digitization at the TH Nuremberg is the flow heater for your digital know-how and your future design. The course is aimed at anyone who wants to technically advance digitization in their company (e.g. software engineers) or design digitization strategies (e.g. managers).
Accordingly, the five modules (e.g. Digitalization Bootcamp, Innovation Management, Organizational Development) cover the field of digitalization holistically. The modular structure of the course allows you to set your own pace and adapt it to your professional and private situation. Practical relevance is lived everywhere at LCC - and this is also true of the continuing education courses. Experienced professors and experts from the field provide hands-on knowledge - and as part of your coursework, you can work on a digitization project from your company.
In order to give as many people as possible access to this course, a university degree or vocational training including relevant work experience is usually sufficient.
You can find detailed information on the website of the OHM Professional School at the TH Nuremberg.
Your contact persons
For projects
Prof. Dr. Tobias Bocklet
Fakultät Informatik
- Telephone: +49 911 5880-1186
- E-mail: tobias.bocklet@th-nuernberg.de
