Abstract
Sustainability is no longer a secondary issue, but a central system goal of technical value creation. The focus is on a holistic view of the product life cycle from material selection, manufacturing, use, repair and upgrades to return and recycling. The approach of the AI based System of Systems Lifecycle Management of Digital Threads opens up new ways of managing environmental responsibility based on data. Instead of evaluating sustainability retrospectively, it is anchored early on in the development process through data driven methods, digital twins and networked decision making platforms. This not only allows environmental goals to be defined, but also makes them measurable and controllable.
The combination of life cycle analysis (LCA), digital traceability and circular design forms the methodological backbone of this approach. ISO 14040/44 compliant LCAs provide the basis for transparency and comparability, while digital twins capture real world usage data, enabling continuous optimisation. Companies can only successfully implement sustainability as a system goal if data quality, governance and technical interoperability are guaranteed. Clear responsibilities, defined roles and the principle of ‘bounded flexibility’ i.e. binding standards with situational freedom of adaptation play a decisive role here.
The aim is to understand sustainability not as an external goal, but as an integral part of technical and organisational decision making processes. The early integration of LCA findings, standardised key performance indicators (ecological, circular and maturity KPIs) and the use of digital tools creates a learning, self improving system. Research and practice show that it is precisely the linking of data, processes and responsibility that offers the greatest leverage for ecological effectiveness. In this way, sustainability becomes not just a marketing term, but a guiding principle throughout the entire life cycle from the initial idea to recycling.
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