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Institute
Service Engineering Models
(2019)
Since the field of service engineering emerged in the late 20th century, the service industry has undergone drastic changes. Among the reasons for these changes is the increasing digitalization, which has made it difficult for companies to successfully develop new service offerings. While numerous service engineering models are available to provide guidance during the design of new services, many of them cannot keep up with the requirements of today’s economic environment. The present paper examines the requirements that service engineering models need to meet in order to be suitable guidelines for the digital age. To this end, the introduction illustrates how digitalization has changed the service industry. Afterwards, selected service engineering models and related norms are presented. Finally, a set of requirements for modern service engineering models derived from best practices from recent years is introduced.
Smart Service Engineering
(2019)
In our digitalized economy, many traditional service engineering models lack flexibility, efficiency and adaptability. As today’s market differs significantly from the market of the late 20th century, service engineering models must meet different requirements today than they had to meet in the past. The present paper starts off by providing an overview of the requirements that modern service engineering models need to fulfill in order to succeed in today’s economic environment. Afterwards, three promising models that meet several of these requirements will be introduced.
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)
Die in der produzierenden Industrie fortschreitende Digitalisierung geht mit großen Potenzialen einher. Nichtsdestotrotz blieb der realisierte Nutzen aus der Digitalisierung bisher hinter den Erwartungen zurück. Durch Smart Services besteht die Möglichkeit, neue digitale Geschäftsmodelle mit Fokus auf einen hohen Kundennutzen zu realisieren und folglich mit einer individuellen und dennoch skalierbaren Lösung auf effiziente Weise Wertschöpfung zu generieren.
Smart-Farming-Welt
(2019)
Smart-Farming-Welt
(2019)
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.
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.
Through data-based insights into customer behavior, products and service offers can be improved. For manufacturing companies, smart product-service systems (SPSS) offer the possibility to collect customer data during the usage phase of the product. As the focus on customer analytics is too often on sales and marketing, SPSS are overlooked as a source of customer data. However, manufacturing companies need to integrate data from all interactions with their customers along the complete customer journey to achieve a holistic data-based view of the customers. To identify these interactions and the customer data derived from them, the concept of a digital shadow will be applied to the customer journey. The projected results for the presented work in progress are a reference process model for the customer journey in manufacturing and a data model of the customer data created along this process.
Das Ziel des Forschungsprojekts ToMiC war die Entwicklung einer Typologie zum lebenszyklusorientierten Management unternehmensinterner Communitys wissensintensiver Dienstleister. Jene befähigt insbesondere kleine und mittlere Unternehmen erstmals dazu, die aktuelle Lebensphase der eigenen Social-Software-basierten Community zu bestimmen. Die vorliegende Veröffentlichung ist der Abschlussbericht dieses Projekts.