This cumulative dissertation aims to contribute to the field of digital transformation inthe manufacturing industry and is based on several scientific publications. Special focusis given to technologies and architectures and, in particular, to three main research topicsthat will contribute to this area. The first research topic addresses the maintenance ofindustrial machines. By enhancing static maintenance intervals and shifting to conditionbasedmaintenance or, further, to predictive maintenance, cost and time can be saved,and the likelihood of breakdown can be reduced. Different models help to calculated theoptimal number of spare parts or optimize maintenance planning. To predict machinebreakdowns, not only statistical methods but also advanced data analytic techniques arenecessary. The field of industrial machines is very broad, and even a single company facesthe issue of having its components or machines used in several different applications. Thedevelopment of analysis models is therefore challenging. Concepts for enhancing dataanalytic techniques through combinations of domain knowledge experience are presentedin this dissertation. The growing interest in predictive maintenance has led to variousbusiness models in the manufacturing industry. A taxonomy to classify these predictivemaintenance business models is presented within this dissertation. Second, a detailedimage of a machine or plant can provide valuable information to operators and managers.Therefore, this dissertation addresses the topic of installed base management and digitaltwins. Insights into the health status of individual components or plants are necessaryfor timely reactions to events and to support decision making. With the help of a digitalrepresentation of a component, machine or plant, new services can also be enabled. Thethird research topic addresses the increasing importance being place by industry on newservices for manufacturing. Products are no longer sold independently but are offeredalong with services as product-service systems. Furthermore, so-called smart services offerthe potential for digital transformations in the manufacturing industry. These servicesare customer-centric and are based on the usage of various data. In addition knowledgemanagement for smart services is considered. By combining the features described inthese topics, digital transformation in the manufacturing industry is driven and enabled.This digital transformation means changes for companies in terms of the technologies andIT architectures used as well as disruptive changes to current business models. However,with the help of digital transformation, customer demand can be satisfied, processes improvedor accelerated and new value networks established.