Enterprise AI
PepsiCo Achieves 20% Throughput Gains with Siemens Digital Twin Composer
The consumer goods company applied virtual simulation technology across US sites to test facility configurations, producing measurable efficiency improvements in production and capital planning.
PepsiCo's deployment of Siemens Digital Twin Composer integrated with NVIDIA Omniverse is a platform that generates high-fidelity 3D digital twins of manufacturing and warehouse facilities to simulate operational changes and optimize configurations before physical implementation.
Executive Summary
PepsiCo, operating in the consumer packaged goods sector, deployed Siemens Digital Twin Composer integrated with NVIDIA Omniverse across select US manufacturing and warehouse facilities. The system creates detailed simulations of plant operations and supply chains to evaluate configuration options virtually. Initial testing at a Gatorade production site produced a 20% throughput increase within three months while also uncovering opportunities for capital expenditure savings.
The deployment achieved 10 to 15 percent reductions in capital expenditure by revealing hidden capacity through virtual modeling. Up to 90 percent of potential issues were identified prior to any physical build activities. These outcomes stem from a multi-year collaboration announced at CES 2026 that includes plans for broader rollout across additional sites and eventually global operations.
PepsiCo executives framed the initiative as part of embedding artificial intelligence throughout the business to handle the scale and complexity of operations from farm to shelf. The quantified results provide a concrete example of how simulation technology can accelerate design cycles and reduce risks associated with facility modifications in large-scale manufacturing environments.
What operational challenges led PepsiCo to adopt digital twin technology?
PepsiCo manages extensive production networks that span raw material sourcing through final product distribution, creating layers of coordination complexity across dozens of facilities. Traditional methods for testing layout or equipment changes required physical trials that consumed time and resources while exposing the company to costly errors during implementation. Executives identified a need for tools that could model these variables in advance to support faster responses to shifting consumer demand patterns.
The scale of the business made incremental improvements through conventional engineering approaches insufficient for maintaining competitive positioning. By pursuing a unified digital foundation, PepsiCo sought to move from reactive facility management toward systems that anticipate requirements and adapt configurations accordingly. This strategic direction aligned with internal goals to operate with greater agility while controlling capital outlays in a capital-intensive industry.
How was the Siemens Digital Twin Composer with NVIDIA Omniverse implemented?
The implementation began with the creation of high-fidelity 3D digital twins of targeted US facilities using Siemens Digital Twin Composer built on NVIDIA Omniverse libraries. These models incorporated operational data to replicate workflows, equipment placements, and material flows in a virtual environment. Teams then ran simulations to test proposed upgrades and identify optimal configurations without disrupting live production.
Integration allowed real-time visualization and analysis of how changes would affect throughput, bottlenecks, and overall facility performance. The AI elements within the platform processed historical and real-time parameters to forecast outcomes across different scenarios. Siemens contributed domain expertise in industrial systems while NVIDIA supplied the underlying simulation and graphics capabilities required for accurate 3D modeling.
Deployment focused initially on manufacturing and warehouse sites where configuration adjustments could yield immediate efficiency gains. The approach supported faster design cycles by replacing portions of physical prototyping with virtual validation. Plans call for expanding the same framework to additional locations following the initial results at the Gatorade plant.
What quantified outcomes were measured at the initial Gatorade site?
The first deployment delivered a 20% increase in throughput measured over a three-month period after configuration changes identified through simulation were applied. This improvement resulted from optimized workflows and equipment arrangements that had been validated virtually before rollout. The gain translated directly into higher production volumes without proportional increases in resources or floor space.
Capital expenditure requirements dropped by 10 to 15 percent as the models demonstrated that existing assets could handle higher volumes once bottlenecks were addressed. The system also flagged up to 90 percent of potential issues that would have surfaced during physical construction, allowing corrections in the digital environment. These metrics were documented in announcements from both PepsiCo and Siemens following the CES 2026 reveal.
| Metric | Before | After | Attributed Source |
|---|---|---|---|
| Throughput | Baseline operations | 20% increase | PepsiCo Press Release |
| Capital Expenditure | Full projected spend | 10-15% reduction | Siemens CES 2026 Update |
| Issue Identification | Post-build discovery | Up to 90% pre-build | Siemens Digital Twin Composer Documentation |
What perspectives did company leaders express about the results?
Ramon Laguarta, Chairman and CEO of PepsiCo, highlighted the alignment between the technology and the company's need to manage massive operational complexity while embedding AI for consumer responsiveness. Other executives described the project as establishing a new industry standard for supply chain design and scaling through a unified AI-powered digital foundation.
The scale and complexity of PepsiCo’s business, from farm to shelf, is massive—and we are embedding AI throughout our operations to better meet the increasing demands of our consumers and customers. Our work with Siemens and NVIDIA will help accelerate our continued journey of becoming a future-fit company, operating with agility and foresight.Ramon Laguarta, Chairman and CEO of PepsiCo
Athina Kanioura, Global Chief Strategy and Transformation Officer, emphasized the shift toward facilities that anticipate rather than react to demand. Roland Busch, CEO of Siemens AG, positioned the collaboration as setting benchmarks for industrial AI applications across multiple sectors through combined technology stacks and domain expertise.
What implications arise for peer manufacturing executives?
The PepsiCo results illustrate that digital twin deployments can produce measurable throughput and cost outcomes within short timeframes when applied to complex production environments. Other enterprises may examine similar pilots to assess readiness of their own operational data and facility models for simulation-based decision making.
The documented reductions in capital expenditure and pre-build issue detection rates offer reference points for evaluating return on investment in comparable technologies. Global scaling intentions suggest that initial site successes can inform broader network strategies when supported by established technology partners.
- Assess data quality and integration points across target facilities before simulation begins.
- Select a single high-impact site for initial deployment to establish baseline metrics.
- Engage partners with combined industrial domain knowledge and simulation platform capabilities.
- Validate simulation outputs against existing operational records prior to physical changes.
- Develop internal capabilities to interpret and act on simulation-derived recommendations.
What next steps are planned for the collaboration?
PepsiCo will extend the Digital Twin Composer deployment to additional US manufacturing and warehouse locations based on the initial Gatorade plant performance. The multi-year agreement with Siemens and NVIDIA includes continued platform enhancements to incorporate more advanced predictive features.
Longer-term expansion targets global facilities to create a connected ecosystem where each site operates within a shared intelligent framework. This progression supports ongoing efforts to improve agility across the full supply chain from sourcing through distribution.
Frequently asked
How quickly did throughput improvements appear after deployment?
A 20% throughput increase was recorded within three months at the initial Gatorade plant site.
What percentage of issues can the system detect before physical work begins?
The deployment identified up to 90% of potential issues prior to any physical modifications according to Siemens documentation.
When was the PepsiCo collaboration with Siemens and NVIDIA announced?
The multi-year industry-first collaboration was announced at CES 2026 with initial US facility deployments already underway.
Sources
- PepsiCo — PepsiCo announced the multi-year collaboration and reported the 20% throughput increase from initial deployment.
- Siemens — Siemens documented faster design cycles, reduced capex, and up to 90% issue identification at PepsiCo facilities.
- Siemens — The partnership delivered a 20% throughput increase, 10 to 15% Capex reduction, and up to 90% pre-build issue detection at PepsiCo sites.