© Fraunhofer IML, Vinzenz Neugebauer
Use data efficiently. Optimize processes. Validate decisions.
Modern production and logistics environments are characterized by high complexity and a wide variety of data sources. Companies face the challenge of managing these vast amounts of data in order to make informed decisions and optimize their processes in a sustainable manner.
OpenFactoryTwin (OFacT) is an open-source framework developed by Fraunhofer ISST that uses simulation-based digital twins to provide a holistic view of your production and logistics processes. OFacT integrates data from various sources—such as ERP systems, warehouse management systems (WMS), and IoT sensors—into a unified virtual model, thereby laying the foundation for data-driven decisions.
OFacT creates a digital twin of your production and logistics environment that reflects the actual operational status in real time. Using multi-agent simulation, dynamic processes are modeled and precise predictions about future system states are generated.
The framework is modular and scalable—perfectly tailored to your individual requirements, from optimizing individual production lines to managing complex global logistics networks.
OFacT builds trust and efficiency in digital production environments. The technology helps you make processes transparent, identify bottlenecks early on, and make informed decisions.
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We’d be happy to introduce you to OFacT in a short, free, and no-obligation Demo Session and show you how the solution can be used in your environment.
To make production and logistics processes transparent and identify opportunities for optimization, OFacT relies on a structured workflow:
1. Data Integration
OFacT connects to existing data sources—such as ERP systems, warehouse management systems (WMS), or IoT sensors—and aggregates them into a unified metadata framework.
2. Creation of the Digital Twin
Based on the integrated data, a digital twin is created that is continuously updated and virtually replicates the real-world system. Thanks to AI-powered modeling, digital twins are generated largely automatically—which significantly reduces effort, increases accuracy, and enables faster scaling.
3. Analysis and Decision Support
KPIs are visualized in real time. “What-if” simulations help you evaluate different strategies before putting them into practice. This ensures that decisions are data-driven and transparent.
Research Background: The Open Factory Twin was designed from the outset for use with AI-supported modeling. It is based on various projects conducted with different industrial companies.
OFacT is an open-source project available to developers, researchers, and companies worldwide. You can access the complete source code, documentation, and community resources on GitHub.
GitHub Repository: OpenFactoryTwin/ofact
A digital twin is a dynamic, virtual representation of physical processes, systems, or facilities. In contrast, traditional simulations use static data to model hypothetical scenarios, without continuous feedback from reality and without adaptation over the lifecycle.
The Administrative Asset Shell (AAS), developed in accordance with Industry 4.0 standards, is a structured description of physical or virtual assets and enables the interoperability of digital ecosystems. Simulation-based digital twins focus on real-time monitoring and optimization, while the AAS primarily supports the standardized representation and integration of assets.
Yes, Open Factory Twin is open source. Companies can freely access the base code, integrate, customize, and scale the solution according to their needs. Solutions developed by the community can also be implemented.
The Open Factory Twin is suitable for small, medium-sized, and large enterprises, particularly in manufacturing and logistics. Among other things, it helps increase efficiency in flexible production, warehouse management, and operational processes.
It increases efficiency by identifying bottlenecks, optimizing workflows, and reducing waste of resources in manufacturing.
Yes, through real-time data analysis and simulations, a digital twin supports optimal workforce planning and deployment, as well as shift management.
Digital twins reflect actual operational processes and can identify issues such as machine inefficiency, transportation delays, or warehouse bottlenecks at an early stage.
Yes, it allows you to simulate and compare alternative operating options before implementing them in practice.
The platform is built on open-source standards and modular interfaces that enable seamless integration with common enterprise systems.
Event logs from ERP/MES platforms are primarily required.
From the outset, the Open Factory Twin was designed for AI-powered modeling—which means that digital twins are generated largely automatically rather than modeled manually. This significantly reduces the effort required, increases accuracy, and enables faster scaling. This approach is based on various projects conducted with different industrial companies.
Would you like to learn more about OFacT or request a demo?
Contact us or explore our GitHub repository right away!
Fraunhofer Institute for Software and Systems Engineering