Due to increasing complexity on the shop floor associated with the digital transformation and growing penetration of modern production environments with smart services, the operational phase of automated production facilities is gaining additional importance. The growing range of hybrid service bundles, i.e., the combination of digital services and cyber-physical production systems (CPPS), is expanding the scope of utilization and requires the application of platform-based solutions for service integration. Efficient, scalable IT infrastructures as well as technological flexibility and independence are premises for the successful implementation of these platforms. The availability of ubiquitous communication for seamless networking of all entities also plays a central role. These prerequisites enable the vertical integration of automation components on the shop floor up to the context of strategic business processes based on continuous data and information models. This paper presents an approach for integrating CPPS elements into scalable, highly available service platforms and shows how modern control approaches can be successfully linked with smart service concepts. The exemplary use case for this is a test bench for electric drives.

The discussion about the term "Digital Twin" and its associated concepts has expanded remarkably in the scientific community in recent years. In the context of industrial production, the Digital Twin refers to a holistic, linked, virtual representation of a physical entity. The spectrum of these entities ranges from individual products to specific manufacturing processes up to complex automated production systems. Due to this diversity, many authors offer different interpretations of the topic, resulting in a wide range of use case-specific models. However, a common meta-model that integrates and classifies the different aspects is still to be presented. Starting with a brief overview of developments in recent years, this paper introduces a novel Digital Twin Structure Model in the context of manufacturing. After providing an overview and explanation of the dimensions, functionality and coupling of the Digital Twin in relation to its surroundings, specific Digital Twin realizations are characterized and compared using the proposed structure model.

The scientific discussion on the Digital Twin gained substantial momentum within the last couple of years. In the context of Industry 4.0, the Digital Twin in the broadest sense refers to the concept of a coupled virtual representation of a physical asset. The asset types may range from products and processes to whole production systems. Different authors offer a variety of interpretations on the actual nature of the Digital Twin, often defining it via implicit functional aspects rather than giving explicit definitions. At the same time, some authors use the term merely as a catchphrase, thus applying blur to this emerging paradigm. At this point, a comprehensive understanding as well as a unifying model of the Digital Twin are absent. This paper therefore provides a structured review of the body of relevant literature with the specific focus on finding explicit definitions of the term "Digital Twin" as well as stated models characterizing the Digital Twin concept. As a result, a relevance assessment provides the most important literature regarding the research questions. The found explicit definitions, being partly conflicting, are presented. Similar notions like Product Avatar and Digital Shadow are assorted accordingly. Further, depictions of Digital Twin models stated in the most relevant literature as well as derived Digital Twin purposes are provided. Thus, this paper extends the theoretical foundation, thereby setting a basis for future augmented Digital Twin modeling.

Global trends such as mass customization and lot size one, demand flexibility, autonomy and adaptability in production. Interoperability of devices is a key challenge as production systems evolve into Cyber-Physical Production Systems (CPPS). As part of the German strategic project Industrie 4.0 (I4.0), concepts and solutions for continuous digitization of production are being developed, in order to meet these numerous challenges. The concept of the Asset Administration Shell (AAS) was introduced in order to provide data and information in a standardized and semantically described manner, thus enabling interoperability and easy interaction. In this paper, we show how users can translate a semantic description of plants, machines or individual components that are based on a standardized Open Platform Communication Unified Architecture (OPC UA) information model, into the AAS information model.