Data-driven decision support system enabling the circularity of products

Implementing a Circular Economy (CE) is one approach to reach a higher level of sustainability for products. The individual product's circularity and the resulting choice of the best fitting life cycle path are influenced for instance by varying product properties due to stochastic influences of processes or during use, developments in the availability of (re-)process techniques and prospective changes in regulatory constraints. To support the product circularity by selecting the most sustainable path and decide for instance to reuse, remanufacture or recycle, an evaluation of the potentially available strategies is necessary when planning the life cycle of circular products as well as for improving the circularity of each individual product in the use stage. For this, gathering, processing and analyzing product-specific data, such as initial product properties, intensity of use and external influences, is a key element. Against this background, a framework and procedure model for the implementation of a data-based decision support system to evaluate and assess possible life cycle strategies is proposed. With this, recommendations for selecting and designing the most sustainable life cycle path depending on specific target functions can be derived.