Projects with practice partners
Your bridge builder for automation, digitalization and artificial intelligence: experts and research assistants at TTZ Kronach work with you and your team to sharpen your focus on potential AI application areas in your working 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 connect ignition ceramics with retaining plates. When using the servo presses, however, it can happen that the ceramic components - invisible from the outside - are destroyed. The pressing process can be mapped using measurement curves and therefore optimized with the help of machine learning. This can reduce rejects and time-consuming and costly test runs in quality inspection.
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Sanding machines require regular maintenance and, in the event of a fault, intervention must be as quick as possible in order to optimize the intervals between sanding belt changes and thus minimize downtime. Can faults be predicted based on production noises? Artificial neural networks (here: Auto Encoder) were used to learn from the sanding noise and predict when the next fault and therefore the need to change the sanding belt will occur.
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Assessing the stability of a deep drilling process and therefore the quality of the end product is extremely complex. In order to gain better insights into this, data from acceleration sensors was used to describe the drilling process in an abstract way in the form of artificial neural networks. This enables the AI models to be trained and recognize anomalies in the deep drilling process based on the acceleration data of the deep drill. This can significantly reduce material wear and scrap.
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Calculating manufacturing costs for complex components such as liquid distributors is very time-consuming, which makes it difficult to prepare a valid quotation. 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 required CAD hours can be predicted using the forecast number of screws per component.
To the project poster
The digitalization certificate course
The Nuremberg Institute of Technology's certificate course in digitalization is the key to your digital know-how and shaping your future. The course is aimed at anyone who wants to technically advance digitalization in their company (e.g. software engineers) or design digitalization 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 - including in the further education courses. Experienced professors and experts from the field provide hands-on knowledge - and as part of your coursework, you can work on a digitalization 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 professional experience is usually sufficient.
You can find detailed information on the website of the OHM Professional School at Nuremberg Institute of Technology.
Your contact persons
Prof. Dr. Tobias Bocklet
Akademischer Leiter
- Telephone: +49 911 5880-1186
- E-mail: tobias.bocklet(at)th-nuernberg.de
Sandra Kremer
Office Management
- Telephone: +49 911 5880 3382
- E-mail: sandra.kremer(at)th-nuernberg.de
René-Christian Effinger
Geschäftsführer
- Mobile phone: +49 911 5880 3381
- E-mail: rene-christian.effinger(at)th-nuernberg.de
Mario Pfeuffer
Referent Wissenschafts-kommunikation
- Mobile phone: +49 911 5880 3383
- E-mail: mario.pfeuffer(at)th-nuernberg.de
