Smart circular economy

In the »Smart Circular Economy« research focus area, we use digital technologies such as IoT, AI and digital twins to create sustainable solutions for the circular economy. We are researching the development of smart circular economy services, -applications and business processes as well as CE transformation processes. We are also working on federated data ecosystems, which provide the digital infrastructure for sharing digital twins for a smart circular economy. The aim is to enable companies to implement circular initiatives and R-strategies such as reduce, reuse, repair, remanufacturing and recycling.

Our experts develop holistic circular solutions, i.e. with a view to technology, value creation process, business model and product. They combine service engineering methods for circular, digital business processes and business models with the possibilities of federated data ecosystems such as Gaia-X and Manufacturing-X. They utilise cloud platforms and apply AI methods such as machine learning. A particular focus is on exploring the opportunities that lie in the introduction of the digital product passport (DPP). This is how circularity becomes a resource-saving growth driver!

Our subject areas

Circular Service Engineering & Prototyping

To implement a circular economy, companies need new technology-based CE business processes and services for the entire life cycle of products along the R-strategies.

Analysing the framework conditions and developing circular economy strategies: Evaluation of political, legal, technical, economic and environmental factors to develop suitable circular economy strategies for companies
Identification and conceptualisation of circular business processes: Systematic investigation of different business model options, modelling and selection taking into account technological, economic and ecological factors and development of prototypes for business processes
Development and modelling of the necessary R-processes: Modelling of the necessary R processes, technological requirements for IoT and AI and development of data architectures and models
Conception and prototypical implementation of new smart services for the circular economy: development from design thinking and detailed requirements analysis to practical implementation in digital prototypes
Design of value creation ecosystems: Systematic modelling of value creation ecosystems for the selected circular economy strategy, including the identification and description of relevant roles and actors, as well as the consideration of flows of goods, money and data

Federated data ecosystems

Data ecosystems such as Catena-X and Manufacturing-X enable the exchange and utilisation of data across company boundaries. They are the basis for new smart services and added value in secure, trustworthy and sovereign data spaces.

Potential of federated data ecosystems: Developing an understanding of federated data ecosystems from a business and technical perspective to implement a smart circular economy
Enabling companies to participate in data ecosystems such as Catena-X and manufacturing: Supporting companies, especially SMEs, in participating in data ecosystems
Development of new business models and smart services for the circular economy in data ecosystems: Supporting companies in developing new business models and smart services and identifying the value of data
Support with governance strategies and structures: Advice on determining the value of data through proven valuation methods, designing access rights to data and sensitising companies to their role in the data ecosystem

Digital Product Passport (DPP) & Digital Twin

The digital product passport is the digital image of products over their entire life cycle. It forms the starting point for digital twins and the exchange of data

Provision of information on current legal standardisation initiatives, regulatory requirements and international and national standardisation initiatives, including the development of an overview of technical implementation options for the DPP
Identifying and analysing the potential and added value of the DPP and determining the mandatory requirements for new business processes and smart services
Gathering product-specific requirements and modelling data models: Requirements analysis and specification of the DPP as well as documentation of the results in data models, also using the Asset Administration Shell (AAS) to ensure data standardisation and interoperability
Development of customised DPP concepts and prototype implementation: Design of DPPs and prototype implementation, supported by digital tools for identifying and introducing suitable solutions as well as by the AAS and other technological solutions

Unsere Expertise

Our expertise	Your challenges
We use a comprehensive portfolio of methods including roadmapping, service innovation and engineering, smart circular economy design thinking, process modelling, ecosystem modelling, scenario building and AI-supported tools to develop and implement new, digital circular economy business models, smart services and R-processes. We use maturity models, potential analyses and innovation management methods to support companies in assessing the prerequisites for participating in federated data ecosystems. We use data analysis methods and evaluation tools to identify economic and ecological potential. We support the development and prototypical implementation of digital product passports by applying methods of requirement engineering, data modelling, service engineering and simulations to design efficient interfaces for implementation and create new business opportunities through the DPP.	Resource availability and resilience: Ensuring the availability of resources in value chains and strengthening resilience require the development of new innovative circular economy services and business processes. The use of digital technologies and data plays a decisive role as an enabler for a smart circular economy. However, many companies are unsure how they can use digital technologies to establish sustainable and circular resource flows and adapt flexibly to market changes. This uncertainty leads to questions about the effective use of data and the implementation of new digital circular economy business models. Without a clear understanding of these aspects, companies risk missing valuable opportunities to improve their resilience and sustainability. The need to develop digital solutions and robust approaches to sustainable resource utilisation is thus becoming a key concern that poses major challenges for many companies. Data utilisation for new services: Companies must be prepared to share their data to succeed in a circular economy. However, many do not know how to effectively integrate into federated data ecosystems such as Gaia-X and Manufacturing X. This uncertainty leads to questions about the real value of the data they provide, as well as the opportunities to develop and offer new and innovative services within these ecosystems. Without a clear understanding of these aspects, companies risk not reaping the benefits of collaboration in a data-driven environment, which could jeopardise their competitiveness and sustainability goals. The need to establish a secure and effective data infrastructure thus becomes a key concern that poses major challenges for many organisations. Digital Product Passport & Digital Twin: The introduction of the Digital Product Passport (DPP) poses considerable challenges for companies. From 2027, the Ecodesign for Sustainable Products Regulation (ESPR) will require the implementation of a DPP for certain products and materials. However, many companies are unsure how to fulfil these requirements and develop a DPP for their products. They need support in setting up and prototyping the DPP, including methods such as requirements engineering, data modelling, service engineering and simulations to create efficient interfaces and exploit new business opportunities. Without a clear strategy and the right methods, organisations risk failing to meet requirements and missing opportunities.

Our expertise

Your challenges

We use a comprehensive portfolio of methods including roadmapping, service innovation and engineering, smart circular economy design thinking, process modelling, ecosystem modelling, scenario building and AI-supported tools to develop and implement new, digital circular economy business models, smart services and R-processes.
We use maturity models, potential analyses and innovation management methods to support companies in assessing the prerequisites for participating in federated data ecosystems. We use data analysis methods and evaluation tools to identify economic and ecological potential.
We support the development and prototypical implementation of digital product passports by applying methods of requirement engineering, data modelling, service engineering and simulations to design efficient interfaces for implementation and create new business opportunities through the DPP.

Resource availability and resilience: Ensuring the availability of resources in value chains and strengthening resilience require the development of new innovative circular economy services and business processes. The use of digital technologies and data plays a decisive role as an enabler for a smart circular economy. However, many companies are unsure how they can use digital technologies to establish sustainable and circular resource flows and adapt flexibly to market changes. This uncertainty leads to questions about the effective use of data and the implementation of new digital circular economy business models. Without a clear understanding of these aspects, companies risk missing valuable opportunities to improve their resilience and sustainability. The need to develop digital solutions and robust approaches to sustainable resource utilisation is thus becoming a key concern that poses major challenges for many companies.
Data utilisation for new services: Companies must be prepared to share their data to succeed in a circular economy. However, many do not know how to effectively integrate into federated data ecosystems such as Gaia-X and Manufacturing X. This uncertainty leads to questions about the real value of the data they provide, as well as the opportunities to develop and offer new and innovative services within these ecosystems. Without a clear understanding of these aspects, companies risk not reaping the benefits of collaboration in a data-driven environment, which could jeopardise their competitiveness and sustainability goals. The need to establish a secure and effective data infrastructure thus becomes a key concern that poses major challenges for many organisations.
Digital Product Passport & Digital Twin: The introduction of the Digital Product Passport (DPP) poses considerable challenges for companies. From 2027, the Ecodesign for Sustainable Products Regulation (ESPR) will require the implementation of a DPP for certain products and materials. However, many companies are unsure how to fulfil these requirements and develop a DPP for their products. They need support in setting up and prototyping the DPP, including methods such as requirements engineering, data modelling, service engineering and simulations to create efficient interfaces and exploit new business opportunities. Without a clear strategy and the right methods, organisations risk failing to meet requirements and missing opportunities.

Smart circular economy for complex products and services

Domain and industry focus