Krones achieves real-time optimization of packaging lines with digital twin framework
Krones, a leading provider of packaging and bottling systems, partnered with Synopsys to deploy a cutting-edge digital twin framework leveraging Microsoft Azure and NVIDIA Omniverse. Traditional fluid simulation in manufacturing took several hours per run, limiting real-time process optimization and scenario testing. By implementing a GPU-accelerated, cloud-native simulation environment hosted on Azure, Krones reduced simulation runtimes from hours to under 5 minutes. The system integrates Ansys Fluent physics, Omniverse libraries, and Azure AI, resulting in a virtually realized factory floor for real-time scenario comparison and adjustment. Enhanced collaboration is enabled across engineering, operations, and R&D teams, thanks to seamless concurrency and data-driven decision-making capabilities. CADFEM Germany GmbH customized solver settings for Krones’ needs and SoftServe provided system integration for the full deployment on Azure cloud infrastructure. The technical architecture enables scalable digital twins across industries, making sophisticated simulations accessible, which significantly reduces waste, increases resource efficiency, and speeds up product development cycles. Collaboration between Synopsys, NVIDIA, and Microsoft demonstrates how digital transformation can deliver practical, rapid agility to manufacturing operations, ultimately raising productivity to new industry standards.
- Organization
- Krones
- Industry
- Manufacturing
- Location
- Germany
- Published
- November 2025
Reported outcomes
5 minutes
timeTime & speed
Strategic outcomes
Primary read
Use case focus
Showing 3 of 3
- 1Real-time simulation-driven process optimization in manufacturing
- 2Digital twin-powered assembly line improvement
- 3Accelerated scenario testing for process engineering
- Slow simulation runtimes (3-4 hours) limited rapid optimization of manufacturing and packaging line processes.
- Resource allocation and process adjustments could not occur in real time, reducing operational competitiveness.
- Scenarios comparisons and iterative improvements were impractical due to high computational costs and time delays.
- Engineering and operations teams needed more collaborative digital tools for process optimization.
- Developed a GPU-accelerated, cloud-native digital twin framework using Microsoft Azure, NVIDIA Omniverse, and Ansys Fluent physics simulation.
- Integrated OpenUSD/Omniverse libraries for smooth interoperability across CAE tools and platforms.
- Custom solver settings by CADFEM Germany GmbH adapted to Krones’ requirements.
- System integration and cloud deployment on Azure delivered by SoftServe, enabling rapid, scalable access to simulations and digital factory models.
- Reduced simulation time from 3-4 hours to under 5 minutes.
- Enabled immediate scenario comparison and rapid process adjustments.
- Significantly reduced resource usage and product waste.
- Improved operational efficiency and data-driven decision-making across teams.
- Enhanced collaboration between engineering, operations, and R&D.
Architecture
The implementation utilizes a GPU-accelerated physics simulation environment hosted on Microsoft Azure, integrating Ansys Fluent for fluid dynamics, NVIDIA Omniverse libraries for digital twin interoperability, and Azure AI for scenario management and data-driven insights. CADFEM Germany GmbH tailored solver configurations, and SoftServe managed the end-to-end cloud deployment, enabling real-time virtual representation and optimization of complex manufacturing processes.
Implementation partners4
Sources & evidence1
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