End-to-End Materials Data Integration from Metallography to ICME-Based Process Optimization

Abstract

Metallography is a core method of materials characterization that provides high-resolution images of microstructures. In practice, however, these images are often stored in isolated local systems without contextual information on their process history, testing, or simulations. This hinders comprehensive analysis and the identification of relationships between microstructure, processing, and material properties. The Matplus EDA platform presented here closes this gap by semantically linking metallographic data with materials testing, process chains, and ICME tools. By integrating these data into a knowledge graph, metallographic images are enriched with contextual information ranging from chemical composition and heat treatment parameters to mechanical properties and simulation results.

The solution provides web-based access to micrographs with integrated analysis and annotation functions without requiring specialized software. Open standards such as VDA 231-301 and BPMN 2.0 support seamless integration into existing IT environments and facilitate digital data exchange. Direct connectivity to ICME tools links metallographic analyses with calculated material properties, enabling microstructural interpretations to be supported by thermodynamic and kinetic simulations. Successful application in materials research on high-strength steels demonstrates how this end-to-end data integration ensures traceability from processing and local microstructure to the mechanical properties, thereby providing a basis for data-driven materials development.