A steady escalation in AI-driven industrial automation across the global manufacturing sector has now culminated in one of the most significant technological deployments in beverage production history, with Krones formally operationalising a new class of autonomous digital twins that no longer just mirror plant conditions but actively optimise them.
What had been quietly taking shape across Krones’ engineering operations for some time crystallised into a landmark milestone: a multi-partner agentic digital twin system capable of completing fluid-dynamic bottling simulations in under five minutes, compared to the three to four hours previously required. The implications for the beverage industry are substantial.
The German bottling and packaging equipment giant developed the technology in collaboration with CADFEM, Microsoft, NVIDIA, SoftServe, and Ansys, now part of Synopsys. Together, the consortium has engineered a system built on NVIDIA Omniverse libraries and OpenUSD, with cloud compute handled through Microsoft Azure. For beverage producers managing high-throughput, precision-critical filling environments, the shift in speed and decision-making autonomy represents a genuine operational recalibration.
“With the Agentic Digital Twins, we are demonstrating that digitalisation and AI are not just visions for the future but deliver tangible efficiency gains and sustainable benefits today,” said Markus Tischer, Member of Krones’ Executive Board. “Together with our partners, we are setting new benchmarks for the beverage industry.”
Until now, digital twin technology operated in close coordination with human operators, requiring expert judgment to interpret simulation outputs and guide decisions. The new generation of Agentic Digital Twins breaks from that model entirely. The system runs iterative optimisation loops autonomously, adjusting parameters such as temperature, speed, and process control logic, then applies the best-performing configurations directly to physical machines without human intervention at each cycle step.
This matters acutely for beverage manufacturers. Fluid processing demands precise, real-time coordination across constantly shifting variables, from fill pressure and turbulence to bottle geometry and throughput rate. Even marginal inefficiencies in those parameters translate into measurable waste, yield loss, or downstream disruption. A system that can resolve those variables autonomously and in near real-time closes a gap that the industry has been trying to address for years.
“With real-time digital twins powered by OpenUSD, NVIDIA Omniverse libraries and accelerated computing, Krones is pioneering a new era of precision engineering,” said Naomi Betz, Senior Account Manager, Manufacturing and Industry at NVIDIA.
The innovation arrives at a critical moment for manufacturers navigating intensifying cost pressures, tightening sustainability expectations, and growing competitive differentiation around production efficiency. As Drinkabl.media has reported, global beverage multinationals are broadly recalibrating capital allocation and operational models in response to structural market shifts, making production-level efficiency gains not merely desirable but strategically necessary.
Gabriele Eder, General Manager Manufacturing at Microsoft Germany, framed the partnership’s ambitions plainly: “Together, we’re creating the solutions of today and the breakthroughs of tomorrow.”
The entire simulation stack runs in the cloud on Microsoft Azure, leveraging NVIDIA accelerated computing to achieve the processing speeds that make real-time operational application viable at scale. SoftServe served as systems integrator, designing the architecture and aligning data, logic, and AI as what the team describes as the “brain” of the digital twin.
For the wider beverage manufacturing sector, the Krones deployment raises the competitive bar on what digital investment is expected to deliver. Static simulation tools and operator-guided digital twins are increasingly insufficient for the production complexity modern beverage lines demand. The benchmark, as Tischer put it, has moved.
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