The consequences of climate change and current economic and political crises are presenting manufacturing companies with ever greater challenges. On the one hand, increasingly stringent regulations regarding environmental sustainability must be complied with. On the other hand, the use of resources must be adapted to increasingly unstable global supply chains. The application of circular economy strategies holds great potential in terms of business resilience and sustainability. However, despite being highly effective, circular processes have so far only been implemented in very few discrete manufacturing companies. A key component in the optimization of processes towards an economically viable circular economy lies around inspection processes. The information gained about the product's condition during the inspection process forms the basis for a decision to select suitable subsequent treatment strategies. Decision-making processes are mainly based on the experience of experts gained over many years. Due to the increasing shortage of skilled workers, it is therefore important to record and systematically standardize this knowledge to assist unskilled employees in inspection processes in the future. Therefore, this paper presents an approach to support systemized decision-making processes in industrial diagnosis processes with the aid of an assistance system. First, the basic concepts of assistance systems and circular economy, as well as the associated decision-making processes, are presented. Finally, the developed concept for decision support is introduced and transferred to a practical application.
