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People’s (and goods’) transport will fundamentally change due to autonomous driving and emission-reduced drives. This enables new mobility concepts, especially for inner-city transport of people. An example for such autonomous vehicles are so-called people-movers: small electrically powered busses carrying up to 15 passengers from individual departure points to individual destinations. Next to the research regarding autonomous driving and alternative types of drives, it is also necessary to study and research how future users are willing to use new types of inner-city transport. Such transport needs specific information platforms organizing the trips and routing the people mover. Those platforms do not yet exist.
As part of our research, we developed an exemplary people-mover platform architecture. We were using methods from agile software development to gather customer requirements, as well as an information logistics concept as a validated link between user requirements and the architecture. We designed the architecture using microservices to enable growth and adaptability at the same time. As the research is still going on, these characteristics are necessary in order to keep building a customer-focused platform for the inner-city mobility of the future.
The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.
Im B2B-Bereich werden die sich daraus ergebenden Potenziale bisweilen kaum genutzt oder sind noch gänzlich unbekannt. Experten sind sich einig, dass zügiges Handeln und die Umsetzung immer neuer Kundenanforderungen vonnöten sind, wenn ein Unternehmen nicht vom Wettbewerb überrannt oder gar von Mitbewerbern übernommen werden will. Angesichts dieser Entwicklungen hatten sich die Veranstalter der „CDO Aachen“ unter dem Titel „Chancen digitaler Plattformen ergreifen!“ zum Ziel gesetzt, CIOs, CDOs, innovationstreibenden Projektmanagern und impulsgebenden Führungskräften mit ausgeprägter Technologiebegeisterung Impulse und Handlungsempfehlungen zu liefern, wie sie in ihrem Unternehmen wichtige Voraussetzungen schaffen und Fähigkeiten aufbauen können, um am Mehrwert digitaler Plattformen zu partizipieren.