New research project: AI4SCM analyzes supply chain risks
The AI4SCM research project funded by the German Federal Ministry of Education and Research with the participation of Ubermetrics and the joint partners Neofonie and the Berlin University of Applied Sciences (BHT) has started. The goal is to develop methods for the monitoring and detection of supply chain risks.
The crises of recent years have impressively illustrated how much the German economy and consumers depend on functioning supply chains. However, far more mundane events, such as a lack of sales growth or a product recall at a supplier, are often signs of an impending supplier problem. Some of these events occur extremely rarely, but can quickly impact the entire supply chain, representing one of many potential supply chain risks.
The AI4SCM project creates the data foundation for machine learning-based SCM-related data products that underlie the demonstrator, and thus AI4SCM's business and exploitation models, through the automated identification, connection, and querying of global enterprise and local news websites, among others.
This strengthens the essential trust in functioning supplier relationships, which is central to the globally active German economy. The aim of the project is to research methods for the detection of supply chain events in text-based sources and in the context of the supply chain due diligence law. Among other things, training data from SMEs will be used and visualized in dashboards. To prove the marketability of the results, companies such as the building services manufacturer Westaflex are involved to test prototypes and the possibilities of integration into their in-house processes.