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„Promovieren? Promovieren!" Mit diesem Slogan wirbt das FIR an der RWTH Aachen in seinen Stellenanzeigen für die industrienahe Promotion am Forschungsinstitut. Was junge Hochschulabsolvent:innen der Ingenieur- und Wirtschaftswissenschaften dazu motiviert, diesen Weg zu gehen, welche Erfahrungen sie am FIR machen und welche Perspektiven die Mitarbeit sowie die Promotion am FIR für ihre zukünftige Karriere eröffnet, beantworteten Dr. Jana Frank, ehemals Bereichsleiterin Dienstleistungsmanagement am FIR und heute 'Country Business Head' für Singapur und Malaysia bei der Henkel AG & Co. KGaA sowie Antoine Gaillard, seit Februar 2022 wissenschaftlicher Mitarbeiter des FIR an der RWTH Aachen im Bereich Produktionsmanagement.
Industry 4.0 and Smart Maintenance represent a great opportunity to make manufacturing and maintenance more effective, safer, and reliable. However, they also represent massive change and corresponding challenges for industrial companies, as many different options and starting points have to be weighed and the individual right paths for achieving Smart Maintenance need to be identified. In our paper, we describe our approach to evaluating maintenance organizations in a case study for the oil and gas industry, developing a shared vision for the future, and deriving economical and effective measures. We will demonstrate our approach, by showcasing a specific example from the oil and gas industry, where a need for action on HSE-relevant critical flanges in the company's piping systems was identified. We describe the steps, that were taken to identify the need for action, the specifications of the project and the criticality analysis of the piping system. This resulted in the derivation of a digitalization measure for critical flanges, which was first commercially analyzed and then the flanges were equipped with a continuous monitoring solution. Finally, a conclusion is drawn on the performed procedure and the achieved improvements.
[Der Sammelband] Widmet sich den in Wissenschaft und Praxis aktuell intensiv diskutierten Fragestellungen zu Smart Services. Befasst sich mit Geschäftsmodellen, Erlösmodellen und Kooperationsmodellen von Smart Services. Geht auf branchenspezifischen Besonderheiten von Smart Services ein. (link.springer.com)
Electricity generated by wind turbines (WT) is a mainstay of the transition to renewable energy. In order to economically utilize WT is, operating and maintenance costs, which account for 25% of total electricity generation costs in onshore WT’s, are a focus of cost reduction activities. Implementing a data-driven prescriptive maintenance approach is one way to achieve this. So far, various approaches for prescriptive maintenance for onshore WT’s have been suggested.
However, little research has addressed the practical implementation considering sociotechnical aspects. The aim of this paper is therefore to identify success factors for the successful implementation of such a maintenance strategy with clear and holistic guidance on how existing knowledge on prescriptive maintenance from science can be transferred to business practice. These recommendations are developed through case study research and classified in the four structural areas of Acatech’s Industry 4.0 Maturity Index: Resources, Information Systems, Organizational Structure and Culture.
Smart Services als Enabler von Subscription-Geschäftsmodellen in der produzierenden Industrie
(2022)
[Der Sammelband] Widmet sich den in Wissenschaft und Praxis aktuell intensiv diskutierten Fragestellungen zu Smart Services. Befasst sich mit Geschäftsmodellen, Erlösmodellen und Kooperationsmodellen von Smart Services. Geht auf branchenspezifische Besonderheiten von Smart Services ein. (link.springer.com)
Subscription-Geschäftsmodelle (SGM) spielen eine wesentliche Rolle bei der Monetarisierung von Industrie 4.0 Potenzialen für produzierende Unternehmen. Durch die Vernetzung von Maschinen und digitalen Produkten können dem Kunden völlig neue Leistungen geboten werden, die durch ein rein transaktionsbasiertes Geschäftsmodell nicht möglich wären. Der folgende Beitrag widmet sich der Charakterisierung von Subscription-Geschäftsmodellen und zeigt vier Handlungsfelder auf, die bei ihrer Umsetzung berücksichtigt werden müssen.
In the food industry, a very large potential of data ecosystems is seen, in which data is understood, exchanged and monetized as an economic asset. However, despite the enormous economic potential, companies in the food industry continue to rely on traditional, product-oriented business models. Existing data in the value chain of industrial food production, e.g., in harvesting, logistics, and production processes, is primarily used for internal optimization and is not monetized in the form of data products. Especially the pricing of data products is a key challenge for data-based business models due to their special characteristics compared to conventional, analog offerings and multiple design options. The goal of this work is therefore to solve this issue by developing a framework that allows the identification of pricing models for data products in the industrial food production. For this purpose, following the procedure of typology formation, essential design parameters and the respective characteristics are derived. Furthermore, three types for pricing models of data products are shown. The results will serve not only stakeholders in the food industry but also manufacturing companies in general as input for an orientation of their databased business models.
Industrial food production represents one of the largest industries, accounting for a share of ten percent of the world’s gross domestic product. Simultaneously, it is responsible for 26 percent of global greenhouse gas emissions. Due to increasing CO2 taxes and population’s call for sustainability and CO2 reduction, it is facing challenges in terms of economic profitability and stakeholder demands. These challenges could partly be overcome by participating in data ecosystems in which data are refined as data products, understood, exchanged and monetized as economic goods. Despite large amounts of data, collected parenthetically along the value chain in food production, potentials of data analytics and data ecosystems are only marginally exploited. Food production mainly focuses on traditional, product-centric business models. This work shows the conceptualization of a data ecosystem for food production, enabling data-based business models. Therefore, resources, ac- tors, roles and underlying relationships of future ecosystem are analyzed. Building on these, corresponding architectural and analytical artifacts that support data ecosystem exploitation are presented. A food production data ecosystem is exemplified by applying data analytics to compressor data, which reveals high potentials for CO2 reduction.