Large amounts of data are generated in almost all areas of today's highly automated plants in the production industry. For example, during engineering or through the recording of several thousand, in some cases continuous, measured values during the operation of the production plant. Moreover, production plants are distributed worldwide, leading to increased complexity. The collected data can be analyzed - even across plants - and form the basis for interaction between the physical and digital worlds. Use cases are, for example, fault detection, increased plant availability, or even process optimisation.
Main Topics
The current industry challenge is managing large amounts of data, e.g., using model-based, statistical, or artificial intelligence approaches. Interconnectedness enables the aggregation of various data, even across company boundaries, and allows for a new way of information retrieval. However, the resulting increased complexity will lead to changes in the technical infrastructures of the companies and, thus, in the human tasks. Humans rarely have to intervene actively in the production process, but they have to monitor the production process in the case of an error. Therefore, the acquired information must also be appropriately provided to the operating personnel.
In our Summer School, we would like to address topics related to managing large amounts of data for resilient industrial IoT with the students. How can new knowledge be gained from the data, and how can this knowledge be integrated into the entire value chain?
In the first week of Summer School, students will learn the appropriate methods, concepts, and tools (e.g., SysML, BPMN, and DataMining methods). They will also learn the basics of market analysis, IT-enabled business model innovation, and business ecosystem analysis. Together with our globally operating industry partners, we aim to achieve this through exciting real industry examples and use cases. The partners will provide insights into the current challenges in the implementation of IoT technology.
The second week of Summer School is focused on teamwork. In small teams, students will develop and evaluate business models based on real-world examples from our industry partners and use the learned theory from the first week to implement an ecosystem analysis. In this process, they will practically apply the newly learned techniques and finally, present their innovative solutions.
Schedule
Intended Audience
The Summer School is open to young professionals, as well as Bachelor, Master or Ph.D. students who want to deep-dive into emerging digital technologies and learn how to turn these technologies into business. This will enable them to become innovators in the field of Automation as engineers and developers in start-ups or larger companies.
As the programme has a focus on business innovation and entrepreneurship, there is no need to have specific technical backgrounds or any coding knowledge to join our Summer School.
Location
The Summer School takes place at Campus Garching, the scientific and technical center of the Technical University of Munich (TUM). TUM was one of the first universities of excellence in Germany and is one of the top universities in Europe. With more than 15,000 students, Campus Garching is the largest of all TUM locations.
Munich's city center can be reached within 25 minutes on the U6 subway line. Together with the students, we want to experience Munich with its great variety of cultural, sports, and social activities, such as the Allianz Arena and Olympia Park, the Pinakotheken, and the English Garden.
Accommodation
Accommodation is available in the Hotel Ibis München Garching (Daimlerstrasse 5, 85748 Garching). Participants can book this hotel by using the keyword EIT Summer School 2023 on the website of the hotel and indicate if they want to be accommodated in a double or single room. Other Hotels:
Local school organisers will provide you with all support and info you may need. |
