PMD-X-MAPRO

Overview

Cross-company material data and material simulation in production

Project runtime: 01.07.2025 - 30.06.2026

Motivation

Material data enable the simulation of manufacturing processes, are used to define production parameters, help reduce production times, and minimize scrap. Currently, however, these data are still often transmitted in non-machine-readable formats such as PDFs or even on paper. This creates significant manual effort, increases the risk of errors, and causes major process delays. The PMD-X-MAPRO project is the first to implement a digital solution for cross-company transfer of machine-readable material data.

Objectives and Approach

The objective is to establish efficient bidirectional communication of material data along the entire supply chain through digital twins and data spaces, while also ensuring the reliable flow of material data from laboratories. In this way, data can already be made available before the physical delivery of materials:

• Optimization of manufacturing processes prior to material delivery

• Reduction of production times and minimization of scrap

• Bidirectional communication of material data along the supply chain

• Enabling new data-driven business models and strengthening competitiveness

Innovations and Perspectives

The project is developing the first fully digital material twin, seamlessly integrated into industrial manufacturing processes. By introducing bidirectional real-time communication and by using and extending PMD-compliant ontologies, material properties can be continuously optimized and adapted to changing conditions. Data spaces enable secure sharing of even sensitive company data. Bidirectional exchange ensures that all companies along the supply chain can benefit from the shared data.

Tasks within the project Location
Fraunhofer IESE
Open data space for digital material twins with support for bidirectional communication and usage control for the secure and controlled sharing of data.
Kaiserslautern
Fraunhofer IWM
Extension of the PMD ontology to include material information (flow curves, CCT diagrams, uncertainties), linking relevant simulation data directly to the digital twin for materials. Collection of relevant material data in an ontology-based, PMD-compliant data portal and extraction of selected information as a digital twin for the AAS.
Freiburg
Siemens AG
Development of a pipeline that automatically generates the “Process-Ready Material Twin” from PLM/ERP systems (Teamcenter) and integrates it into NX and Tecnomatix workflows.
München
SHS – Stahl-Holding-Saar GmbH & Co. KGaA
Implementation of the first closed-loop scenario, in which inline quality data from users flows back into the twin to refine its parameters – an industrial proof of concept for adaptive material models.
Dillingen/Saar
tec4U-Solutions GmbH
Linking the digital twin with the digital material passport and implementing requirements from the field of circular economy. Integration of ESG and recycling data directly from the digital twin.
Saarbrücken
credativ GmbH
Packaging of Generator, BaSyx runtime, and Dataspace Connector as Kubernetes Helm charts and operation as a managed service.
Mönchengladbach
Deutz AG
Application of the digital material twin in engine and component production.
Köln