Model-based Traceability System Development for Complex Manufacturing Applying Blockchain and Graphs

Description

Traceability systems are the key enablers to smart manufacturing, as they provide transparency and structured documentation along with a product’s value generation flow. With rising regulatory and organizational requirements, traceability systems have developed from a pure risk mitigation tool to an essential pillar of the data revolution in the context of Industry 4.0. 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.
This thesis 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 builds on a standardized traceability terminology consisting of trace objects, trace links, trace actors as well as tracking and tracing functions, and encompasses manufacturing data and supply chain data. 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.