Traceability systems are the key enablers to smart manufacturing, as they provide transparency and structured documentation along with a product’s value generation flow. Especially in the automotive industry, recall costs are growing exponentially with particularly high growth rates for electrified and autonomous vehicles. A traceability system helps to reduce these costs through a more targeted containment of the recalls.
In her thesis Marlene Kuhn presents a modeling methodology to systematically develop traceability in manufacturing industries. In alignment with the proposed methodology, a traceability model for complex manufacturing systems is developed. The model is implemented for an automotive use case through a holistic application based on a graph database and a blockchain. The graph database allows to connect and store semantically rich and detailed manufacturing data, while the Ethereum-based permissioned blockchain enables tracing macro data for products as they move through the supply chain. The developed solution thus provides full transparency and safe documentation to complex and opaque production networks.
With the oral examination on 20.09.2022 Marlene Kuhn completed her PhD with the title:
“Model-based development of a traceability system for complex manufacturing using blockchain and graphs” successfully.