Towards a Smart Services Enabling Information Architecture for Installed Base Management in Manufacturing

In the manufacturing industry the provision of smart services is an opportunity to gain a competitive advantage. As there are high demands on machine availability, smart services in the field of installed base management are important. Through integrating condition monitoring data with installed base data a digital twin of the installed base can be created. This enables comprehensive analyses and the provision of individualized smart services. But this requires to structure and standardize the data. Following the action design research (ADR) approach, in this article design principles of an information architecture are developed. The architecture is evaluated and improved in the context of an international engineering and manufacturing company. A test run with real machine data shows the applicability in practice

Modeling Framework for Integrated, Model-based Development of Product-Service Systems

Product-service systems (PSS) are seen as the 21st-century solution for direct delivery of value to customers under the requirements of high availability, quality, and reduced risks. With mutual benefits for customers, manufacturers, service providers and often the environment, PSS represent a promising approach to sustainable development. This paper addresses the integrated development of product-service systems consisting of physical products/systems and services and proposes an integrated modeling framework that utilizes the Systems Modeling Language. A use case from Lenze, a German automation company, demonstrates the applicability of the integrated modeling framework in practice

Predictive maintenance as an internet of things enabled business model : A taxonomy

Predictive maintenance (PdM) is an important application of the Internet of Things (IoT) discussed in many companies, especially in the manufacturing industry. PdM uses data, usually sensor data, to optimize maintenance activities. We develop a taxonomy to classify PdM business models that enables a comparison and analysis of such models. We use our taxonomy to classify the business models of 113 companies. Based on this classification, we identify six archetypes using cluster analysis and discuss the results. The “hardware development”, “analytics provider”, and “all-in-one” archetypes are the most frequently represented in the study sample. For cluster analysis, we use a visualization technique that involves an autoencoder. The results of our analysis will help practitioners assess their own business models and those of other companies. Business models can be better differentiated by considering the different levels of IoT architecture, which is also an important implication for further research. © 2020, The Author(s)

Sonographic Monitoring During Distraction Osteogenesis

Distraction osteogenesis is a method of bone healing and regeneration widely used to correct bone malformations, shortenings, and other bone defects. Despite its benefits, it is a long-duration therapy with considerable physical and psychological morbidity. Treatment optimization is fundamental and monitoring techniques are being studied. This chapter discusses monitoring methods with a focus on ultrasound evaluation of distraction osteogenesis

Digital transformation in the manufacturing industry : technologies and architectures

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

Focusing the customer through smart services: a literature review

Smart services serve customers and their individual, continuously changing needs; information and communications technology enables such services. The interactions between customers and service providers form the basis for co-created value. A growing interest in smart services has been reported in the literature in recent years. However, a categorization of the literature and relevant research fields is still missing. This article presents a structured literature search in which 109 relevant publications were identified. The publications are clustered in 13 topics and across five phases of the lifecycle of a smart service. The status quo is analyzed, and a heat map is created that graphically shows the research intensity in various dimensions. The results show that there is diverse knowledge related to the various topics associated with smart services. One finding suggests that economic aspects such as new business models or pricing strategies are rarely considered in the literature. Additionally, the customer plays a minor role in IS publications. Machine learning and knowledge management are identified as promising fields that should be the focus of further research and practical applications. Concrete ideas for future research are presented and discussed and will contribute to academic knowledge. Addressing the identified research gaps can help practitioners successfully provide smart services