Digital twins offer a promising approach to sustainable value creation by providing specific life cycle data and enabling the monitoring and implementation of circular economy strategies throughout the product’s life cycle. By analyzing product, component, and material data, as well as process data, it is possible to create transparency throughout a product’s life cycle, build a data-driven product ecosystem, and establish new business and value creation models, from SMEs to large enterprises. This paper identifies application scenarios, their technological readiness level, and the challenges of digital twins for the circular economy in the manufacturing industry based on a systematic literature review. Gaps such as ensuring a continuous flow of information and taking into account the different levels of digitalization of companies are identified. As a main result, a holistic concept for the scoping of a digital twin for the circular economy is presented. One specific use case for end-of-life decision-making is elaborated upon. It is shown that the circular economy can be supported by digital twin data, especially for the optimal decision on end-of-life vehicles.

Product Service Systems (PSS) and Smart Services are powerful means for deploying Circular Economy (CE) goals in industrial practices, through dematerialization, extension of product lifetime and efficiency increase by digitization. Within this article, approaches from PSS design, Smart Service design and Model-based Systems Engineering (MBSE) are combined to form a Methodology for Smart Service Architecture Definition (MESSIAH). First, analyses of present system modelling procedures and systems modelling notations in terms of their suitability for Smart Service development are presented. The results indicate that current notations and tools do not entirely fit the requirements of Smart Service development, but that they can be adapted in order to do so. The developed methodology includes a modelling language system, the MESSIAH Blueprinting framework, a systematic procedure and MESSIAH CE, which is specifically designed for addressing CE strategies and practices. The methodology was validated on the example of a Smart Sustainable Street Light System for Cycling Security (SHEILA). MESSIAH proved useful to help Smart Service design teams develop service-driven and robust Smart Services. By applying MESSIAH CE, a sustainable Smart Service, which addresses CE goals, has been developed.

The mobility sector is the world’s second-largest producer of energy-related CO₂ emissions, and it is facing a global resource shortage. The demand for circular products, the use of secondary materials in future vehicles, and the need for sustainable business models in the mobility sector is increasing. However, a transparent and end-to-end data exchange throughout the entire value network is missing, which is hindering an efficient circular economy. Relevant information on the vehicle, its components, and materials at the end of the product life cycle are often missing. In this context, this paper presents a decision support system based on Digital Twin data for a circular economy solution as a software application. It was developed within the German research project Catena-X following an integrated approach of user-centered design, the V-model, and within the Scaled Agile Framework. By combining these methodological approaches, customer-oriented solutions were developed and continuously improved at each stage of development to shorten the time-to-market. Catena-X is based on Gaia-X principles. In Gaia-X, necessary core services are developed, and contraction negotiation for data exchange and usage policies is enabled and implemented. The decision support system provides important information about the exact composition and condition of the vehicle, its components, and its materials. Thus, it helps to improve efficiency, sustainability, and the implementation of the circular economy. The decision support system was tested and validated with a use case that provided Digital Twin data on the end-of-life vehicle.

Traditionally, manufacturing companies focus on the value-adding processes at production sites but during the last decades, life-cycle thinking is emphasized. The principle of Sustainable Development contributes as a significant driver for this way of thinking. It demands manufacturing companies to implement sustainable aspects into their engineering actions. The state of the art shows that theoretical solutions to integrate sustainability into a company exist at all corporate levels (normative, strategic and operational). Against this background, the question arises how companies are actually implementing sustainability. Within this study, the company’s internal implementations were examined. Eventually, the need for action is identified and future recommendations are described.

The realization of smart-circular Product-Service Systems has theoretically promising advantages compared to traditional products. Nevertheless, the sustainability improvement, especially for the ecological dimension is not yet satisfactorily proved. In this paper, the authors examined the current state of research within a systematic literature review with a specific focus on the overlap of the topics: Life Cycle Assessment, Model-Based Systems Engineering, Product-Service Systems, and Circular Economy. The aim is to analyze the potential of a proactive quantification of the ecological impact in an early stage during the development of smart-circular PSS – the system architecture definition. As a result of the systematic review, 27 relevant papers were identified and analyzed and the findings are presented in a structured way. The main finding is that the current state of the art in this research field still is in the conceptualization stage. In addition, a proactive approach is rare and circularity is not considered to its fullest. Quantified use cases do not draw the system boundaries Cradle-to-Cradle and not every of the 9R-strategies is considered. Furthermore, the potentials and challenges of the revealed research gap are summarized.

With digital twins, manufacturers are able to use real-time data and simulations to optimize production and improve sustainability. The aim of this paper is to develop a twin architecture specially for the maintenance process of turbine blades. As a result, an ontology-based framework for a digital twin of turbine blades is presented that enables the connection of information and data during maintenance. The operational mechanisms of the digital twin are described, and the connectivity between the physical and virtual elements is demonstrated using the ontology model. The framework also supports analysis to optimize production, improve maintenance, and provide information to the services used throughout the lifecycle. Further research within ongoing projects will implement the digital twin and validate the use of the presented ontology in the digital twin.