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Institute
Smartification and digital refinement of products to enable the design of smart ones is a pivotal challenge in the manufacturing industry. Companies fail to design smart products due to missing knowledge of digital technologies and their integral part in product development processes. This paper presents a methodology that enables the derivation of digital functions for smart products through selected cases in manufacturing usage. We develop a morphology that consists of digital functions for smartification. In this context, we explained and derived characteristics by a set of examples regarding smart products in the manufacturing industry. Our methodology reduces the time spent initiating a development project with the focus on smartification.
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.
In order to introduce load management in the manufacturing industry, some obstacles need to be pointed out. This paper presents a feasible approach on how to implement load management measures in companies. To do so, load management and energy management are explained and distinguished in a first step. Subsequently, the implementation method is introduced. Therefore, by using this paper, companies will be enabled to use load management measure and reduce their energy costs significantly.
In the age of digitalization, manufacturing companies are under increased pressure to change due to product complexity, growing customer requirements and digital business models. The increasing digitization of processes and products is opening up numerous opportunities for mechanical engineering companies to exploit the resulting potential for value creation. Subscription business is a new form of business model in the mechanical engineering industry, which aims to continuously increase customer benefit to align the interests of both companies and customers. Characterized by a permanent data exchange, databased learning about customer behavior, and the transfer into continuous innovations to increase customer value, subscription business helps to make Industry 4.0 profitable. The fact that machines and plants are connected to the internet and exchange large amounts of data results in critical information security risks. In addition, the loss of knowledge and control, data misuse and espionage, as well as the manipulation of transaction or production data in the context of subscription transactions are particularly high risks. Complementary to direct and obvious consequences such as loss of production, the attacks are increasingly shifting to non-transparent and creeping impairments of production or product quality, which are only apparent at a late stage, or the influencing of payment flows. A transparent presentation of possible risks and their scope, as well as their interrelationships, does not exist. This paper shows a research approach in which the structure of subscription models and their different manifestations based on their risks and vulnerabilities are characterized. This allows suitable cyber security measures to be taken at an early stage. From this basis, companies can secure existing or planned subscription business models and thus strengthen the trust of business partners and customers.
The number of cyber-attacks on small and medium enterprises (SMEs) is constantly increasing. SMEs do not recognize the attacks until the damage has occurred. Only then, they fight with measures to increase IT-security and IT-safety. Many studies come to the point that this refers to a lack of budget, expertise and awareness of the need for IT-security. There are many compendia with recommendations for action, but they are too comprehensive and unspecific to the individual needs of SMEs. In this paper, we present the results of a research activity on the gaps that address the challenges faced by SMEs. In addition, we develop a concept for a serious gaming approach that includes an economic perspective on IT-security measures and shows how SMEs can derive their own IT-seurity target state
The manufacturing industry has to exploit trends like “Industrie 4.0” and digitization not only to design production more efficiently, but also to create and develop new and innovative business models. New business models ensure that even SMEs are able to open up new markets and canvass new customers. This means that in order to stay competitive, SMEs must transform their existing business models.
The creation of new business models require smart products. The required data base for new business models cannot be provided by SMEs alone, whereas smart products are able to provide a foundation, given the creation of smart data and smart services they enable. These services then expand functions and functionality of smart products and define new business models.
However, the development of smart products by small and medium-sized enterprises is still lined with obstacles. Regarding the product development process the inclusion of smart products means that new and SME-unknown domains diffuse during the process. Although there are many models regarding this process there appears to be a substantial lack of taking into account the competencies enabled by the implementation of digital technologies. Hence, several SME-supporting approaches fail to address the two major challenges these enterprises are faced with. This paper generally describes valid objectives containing relevant stakeholders and their allocation to the phases of the product life cycle.
Within each objective the potential benefit for customers and producers is analyzed. The model given in this paper helps SMEs in defining the initiation of a product development project more precisely and hence also eases project scoping and targeting for the smartification of an already existing product.
Dieses Forschungs- und Entwicklungsprojekt wurde durch das Bundesministerium für Bildung und Forschung (BMBF) im Rahmen des Programms „KMU-innovativ: Produktionsforschung“ (Förderkennzeichen 02K19K010) gefördert und vom Projektträger Karlsruhe (PTKA) betreut. Die Verantwortung für den Inhalt dieser Veröffentlichung liegt bei den Autoren.
Im Rahmen des Forschungsprojekts "FlAixEnergy" sollen kleine und mittlere Unternehmen (KMU) sowohl als dezentrale Erzeuger von regenerativer Energie als auch als Energieverbraucher (Smart Industrial Customer) zu Flexibilitätsclustern zusammengefasst werden. Ziel des Projekts ist die Entwicklung einer Plattform zwischen Energieversorgungsunternehmen (EVU) und Unternehmen, mittels derer die bewertete Energieflexibilität der energieverbrauchenden Unternehmen aggregiert und so die Partizipation am Energiemarkt ermöglicht wird. Ein in diesem Kontext relevantes Thema ist die Charakterisierung der eingebundenen industriellen Verbraucher bezüglich ihres Energiebedarfsverhaltens und ihrer Flexibilität. Hierzu soll ein sogenannter "energetischer Fingerabdruck" entwickelt werden, der dazu dient, Flexibilitätspotenziale und Lastprognosen von industriellen Stromverbräuchen systematisch an Energieversorgungsunternehmen zu kommunizieren. Das Projekt wird mit Mitteln des Bundesministeriums für Wirtschaft und Energie (BMWi) gefördert.
Die vorliegende Publikation beinhaltet die Projektergebnisse des Forschungsprojekts „FlAixEnergy – Innovative Energieflexibilitätsplattform zur Synchronisation und Vermarktung des regionalen Stromverbrauchs industrieller Anwender mit dezentraler Energieerzeugung in der Modellregion Aachen“ (Förderkennzeichen 0325819A-I). Dieses Forschungs- und Entwicklungsprojekt wurde mit Mitteln des Bundesministeriums für Wirtschaft und Energie (BMWi) gefördert und vom Projektträger Jülich (PTJ) betreut. Die Autoren sind für den Inhalt der Veröffentlichung verantwortlich.
Energieflexibilität stellt eine mögliche Lösung dar, um die Herausforderungen der steigenden Volatilität in den Versorgungsnetzen in Deutschland zu beherrschen. Die Bundesregierung gibt den Weg vor: Die Energieversorgung Deutschlands wird in Zukunft verstärkt bis ganzheitlich durch erneuerbaren Energien gedeckt werden. Heute gibt es jedoch wenige innovative Energiedienstleistungen, die dieses Ziel verfolgen und die beschriebene Herausforderung in Zukunft beherrschbar machen.
Im Projekt "FlAixEnergy" wird eine Roadmap innovativer Energiedienstleistungen entwickelt. Diese zeigt auf, welche Smarten Services derzeit im Markt fehlen und in Zukunft erforderlich werden. Das Projekt wird mit Mitteln des Bundesministeriums für Wirtschaft und Energie (BMWi) gefördert.