Modulbeschreibung
Smart Factory
Kurzzeichen:
Unterrichtssprache:
ECTS-Credits:
Leitidee:
The digitalization of a factory is a decisive prerequisite for the future of Switzerland as a manufacturing location. Students should become familiar with concepts and methods for designing an efficient, intelligent, digital factory of the future. Students will be familiar with the relevance of data and the handling of data for the factory of the future so that they can make the right decisions for the innovation process. They will also learn to evaluate and apply the concepts in a goal-oriented manner in order to be able to make an important contribution to the transformation of an industrial company today.
Modulverantwortung:
Standort (angeboten):
Modultyp:
Modulbewertung:
Leistungsnachweise und deren Gewichtung
Modulschlussprüfung:
Gewichtung:
Bemerkungen:
open book exam
Inhalte
Angestrebte Lernergebnisse (Abschlusskompetenzen):
Professional competence:
Students will be able to:
- Experience, model and develop the flow of data and materials for the relevant use cases for the smart factory.
- Understand and design the connection of the physical product and its manufacture to the digital world. The technologies of injection molding and adaptive robotics are primarily used for this purpose.
- Use, configure, implement and further develop the relevant IT systems with their interfaces (IT, Internet of Things, machine standards) and the necessary master data.
- Understand, model and program data analyses and simulations based on the available data up to the algorithm for machine learning.
Self-competence
- Dealing with complexity and interdisciplinarity and developing solutions in a team
Social skills
- Actively tackle interdisciplinarity to implement the smart factory and improve communication / understanding between the disciplines and build bridges
Modul- und Lerninhalt:
Create a basic understanding of the topic of smart factory, know and evaluate concepts and approaches. Personal experience in the OST smart factory (digital and physical learning environment).
Experience, apply and evaluate your own implementation of data acquisition and vertical communication from the sensor to the cloud using a simple example in the factory. In addition, the methods of machine learning and discrete event simulation for optimization are deepened in order to understand a digital factory and to help shape it as a development manager.