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Institute
The aim of the related research project eCloud is to enable small and medium sized enterprises (SMEs) to implement flexible energy management without in-depth energy knowledge and with little distraction from day-to-day business, which is prepared for current and future challenges in the field of energy use. The overall result is a validated prototype for a plug and automate capable (i.e. without implementation effort) operational energy management, which can be successively set up in SMEs based on a cloud platform. Through its gradual and modular implementation, energy management meets the individual needs of each company and contributes to energy system transformation and climate protection by reducing energy costs and greenhouse gas emissions by up to 25%. In total, three expansion stages are available with the levels of monitoring, load management and grid usage, which consist of various Software as a Service (SaaS) modules from the cloud that can be retrieved as required. Thus, the user only needs a minimal hardware intervention in his production and saves a complex IT infrastructure. The methodology developed has been successfully applied by two user companies so far. This proves the effectiveness of the method.
Since 2016, the “Digital in NRW” Competence Centre has been supporting SMEs in the manufacturing industry in designing their individual digital transformation. With an Industry 4.0 maturity assessment, we define the status quo of SMEs, derive SME-specific measures from this, develop a digitalization roadmap and accompany the SME transformation. This paper presents the results of the four-year SME support. By analyzing the results of all maturity assessments, potential analysis and design workshops, we present the most frequent and most effective measures for a successful digital transformation of SMEs. The result of the paper is an action guideline for SMEs to initiate their own digital transformation based on formalized experience.
Progress in the development of small electric and hybrid aircraft promises business opportunities for thin-haul air mobility services. In order to develop demand-oriented flight plan scenarios for Germany, this paper presents a model to estimate the marked volume of thin-haul air mobility. To quantify the potential demand, our model includes the steps of trip generation, trip distribution and mode choice. Trip generation and distribution takes place between 412 geographic subdivisions of Germany and is based on calibrated traffic forecast data for the year 2030. For the first time the five relevant modes of transport, namely: car, intercity train, intercity bus, commercial aircraft and thin-haul air mobility services, have been included in one model. The step of choosing the transport mode is implemented via a generalized cost approach, taking into account travel costs and travel time. Additionally, route modeling of all transport modes is enhanced by real market data using large-scale data readouts of web interfaces. As primary result we predict a market share of 6 % or 81 million trips per year for thin-haul air mobility services. The demand concentrates on a small number of airports: 30 % of the trips are estimated to be between only 20 airports. Hubs and main routes are identified to offer the potential for scheduled air services.
Auf Basis einer systematischen Literaturanalyse wurden insgesamt 11 Kennzahlen identifiziert, welche die Grundlage zur Beschreibung der operativen Leistungsfähigkeit von Unternehmen bilden. Die Kennzahlen wurden in die vier Leistungsdimensionen Effizienz, Qualität, Zeit und Flexibilität eingeteilt.
Es geht um die Entwicklung eines Software-Tools zur Unterstützung bei der Auswahl von geeigneten 3D-Druckdienstleistern im Kontext der additiven Ersatzteillogistik. Im Fokus steht der Logistikdienstleister als potentieller Nutzer des Softwaretools. Das Softwaretool erfüllt zwei zentrale Funktionen: Überprüfung ob ein Ersatzteil additiv gefertigt werden soll und Auswahl eines konkreten Produzenten durch Matchingalgorithmus.
Als größter Berufsverband für Beschäftigte im Kundendienst und im After-Sales-Service innerhalb der DACH-Region verbindet der Kundendienst-Verband Deutschland e. V., kurz KVD, unterschiedliche Akteure
im Thema Service, so zum Beispiel aus Wissenschaft und Wirtschaft. Dabei gelingt es dem KVD nicht nur, seine Mitglieder untereinander zu vernetzen, sondern ihnen stets brandaktuelle Inhalte anzubieten.
Die enge Kooperation mit Forschungseinrichtungen ermöglicht es dem KVD und seinen Mitgliedern immer wieder, neue Themen und nützliche Werkzeuge für die praktische Anwendung zur Verfügung zu stellen.
Data Driven Services
(2020)
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.
Störungen und Änderungen des Produktionssystems führen zu Kosten und Aufwänden, bieten jedoch auch die Chance zur kontinuierlichen Verbesserung.
Um Änderungsanfragen zu erfassen, können etablierte Ansätze genutzt werden. Diese vernachlässigen jedoch die Anforderungen, denen sich ein Produktionssystem im Zeitalter der Digitalisierung ausgesetzt sieht. Der vorliegende Beitrag stellt einen Ansatz zur standardisierten Erfassung von Änderungsanfragen vor, welcher die Ausgangsbasis für die Bewertung von Änderungsanfragen in bestehenden IT-Systemen bietet.