4 August 2023
on course website
Methods and Tools for Resilient Industrial IoT
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.
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?
The Summer School takes place at the 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.
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.
Acceptance of transfer credit is always a decision of receiving institutions.
EUR 1150: The Early Bird fee is available until April 15.
EUR 1350: Standard fee.
on course website