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Course of studies
Formal Description of Use Cases for Industry 4.0 Maintenance Processes Using Blockchain Technology
(2019)
Time – Made in Germany
(2019)
Flexible piezoresistive PDMS metal-thin-film sensor-concept for stiffness evaluation of soft tissues
(2019)
Neuroscience and Retail
(2019)
Semi-rigid ring-shaped electrode dielectric electroactive polymer membrane as buckling actuator
(2019)
Die Leitfrage der Bachelorarbeit lautet: „Wie reagieren Zulieferer von Verbrennungs-motorkomponenten auf die Veränderung der Automobilbranche durch den Trend der Elektrifizierung von Fahrzeugen?“. Aus dieser Leitfrage ergeben sich die folgenden Key Research Questions: „Was ist die Veränderung der Automobilbranche durch den Trend der Elektrifizierung von Fahrzeugen?“, „Wer sind die Zulieferer von Verbrennungsmotor-komponenten?“ und „Wie sind die untersuchten Unternehmen hinsichtlich externem Handlungsbedarf, internem Handlungsbedarf und Richtungsänderung zu bewerten?“. Durch die Beantwortung der Leitfrage und der Key Research Questions werden Beratungspotentiale identifiziert. Außerdem werden Zulieferer von Verbrennungsmotoren identifiziert, deren strategische Reaktion bereits Erfolg zeigt. Diese können bei einer Beratung als Benchmark dienen.
Due to the global increase in temperature, China has been dealing with severely increasing ecological disasters. The Chinese government has therefore increased its environmental protection measures in the past 15 years. This thesis delivers descriptive results of these measures, taken from the last three five-year plans as issued by the Chinese government. This is being done by applying the expected results of these measures into a so-called integrated assessment model. Furthermore, this thesis elaborates how integrated assessment models can be used in order to assess policies, such as these employed by the government of the PRC in order to compute their overall socio-economic impact on factors like welfare-maximization and technological advancement. This is rounded out by exploring the possibility of creating a holistic assessment model that combines the potential of backstop- and abatement technologies with a global or regionally disaggregated assessment model.
The rise of digital twins in the manufacturing industry is accompanied by new possibilities, like process automation and condition monitoring, real time simulations and quality and maintenance prediction are just a few advantages which can be realized. This paper takes a novel approach by extracting the fundamental knowledge of a data set from a production process and mapping it to an expert fuzzy rule set. Afterwards, new fundamental augmented data is generated by exploring the feature space of the previously generated fuzzy rule set. At the same time, a high number of artificial neural network (ANN)models with different hyperparameter configurations are created.
The best models are chosen, in line with the idea of survival of the fittest, and improved with the additional training data sets, generated by the fuzzy rule simulation. It is shown that ANN models can be improved by adding fundamental knowledge represented by the discovered fuzzy rules. Those models can represent digitized machines as digital twins. The architecture and effectiveness of the digital twin is evaluated within an industry 4.0 use case.