Digital transformation in the manufacturing industry : technologies and architectures

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dc.identifier.uri http://dx.doi.org/10.15488/9243
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/9296
dc.contributor.author Olivotti, Daniel ger
dc.date.accessioned 2020-01-21T13:45:22Z
dc.date.available 2020-01-21T13:45:22Z
dc.date.issued 2020
dc.identifier.citation Olivotti, Daniel: Digital transformation in the manufacturing industry : technologies and architectures. Hannover : Gottfried Wilhelm Leibniz Universität, Diss., 2020, XXII, 178 S. DOI: https://doi.org/10.15488/9243 ger
dc.description.abstract This cumulative dissertation aims to contribute to the field of digital transformation in the manufacturing industry and is based on several scientific publications. Special focus is given to technologies and architectures and, in particular, to three main research topics that will contribute to this area. The first research topic addresses the maintenance of industrial machines. By enhancing static maintenance intervals and shifting to conditionbased maintenance or, further, to predictive maintenance, cost and time can be saved, and the likelihood of breakdown can be reduced. Different models help to calculated the optimal number of spare parts or optimize maintenance planning. To predict machine breakdowns, not only statistical methods but also advanced data analytic techniques are necessary. The field of industrial machines is very broad, and even a single company faces the issue of having its components or machines used in several different applications. The development of analysis models is therefore challenging. Concepts for enhancing data analytic techniques through combinations of domain knowledge experience are presented in this dissertation. The growing interest in predictive maintenance has led to various business models in the manufacturing industry. A taxonomy to classify these predictive maintenance business models is presented within this dissertation. Second, a detailed image of a machine or plant can provide valuable information to operators and managers. Therefore, this dissertation addresses the topic of installed base management and digital twins. Insights into the health status of individual components or plants are necessary for timely reactions to events and to support decision making. With the help of a digital representation of a component, machine or plant, new services can also be enabled. The third research topic addresses the increasing importance being place by industry on new services for manufacturing. Products are no longer sold independently but are offered along with services as product-service systems. Furthermore, so-called smart services offer the potential for digital transformations in the manufacturing industry. These services are customer-centric and are based on the usage of various data. In addition knowledge management for smart services is considered. By combining the features described in these topics, digital transformation in the manufacturing industry is driven and enabled. This digital transformation means changes for companies in terms of the technologies and IT architectures used as well as disruptive changes to current business models. However, with the help of digital transformation, customer demand can be satisfied, processes improved or accelerated and new value networks established. ger
dc.language.iso eng ger
dc.publisher Hannover : Institutionelles Repositorium der Leibniz Universität Hannover
dc.rights Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. ger
dc.subject Digital Transformation eng
dc.subject Manufacturing Industry eng
dc.subject Architectures eng
dc.subject Digital Twin eng
dc.subject Product-Service-Systems eng
dc.subject Predictive Maintenance eng
dc.subject Digitale Transformation ger
dc.subject Industrie ger
dc.subject Architekturen ger
dc.subject Vorausschauende Wartung ger
dc.subject Digitaler Zwilling ger
dc.subject Produkt-Service-Systeme ger
dc.subject.ddc 330 | Wirtschaft ger
dc.title Digital transformation in the manufacturing industry : technologies and architectures eng
dc.type DoctoralThesis ger
dc.type Text ger
dcterms.extent XXII, 178 S.
dc.description.version publishedVersion ger
tib.accessRights frei zug�nglich ger


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