Anonymous Brewer

Before commissioning a new automated distribution center, an anonymous brewer needed to verify that its planned automated storage and retrieval system (AS/RS) and integrated conveyor network would perform reliably under real-world demand patterns. In Food & Beverage, distribution operations must handle significant variability — seasonal peaks, promotional surges, and irregular pallet flows — without costly downtime or fulfillment delays. Building and discovering flaws in a physical system after installation would have been prohibitively expensive to correct. The brewer required a way to stress-test the design, expose hidden bottlenecks, and validate design changes before committing to final construction.

Rockwell Automation implemented a digital twin simulation of the full distribution center layout before physical construction began. The model replicated the complete material flow: pallets entering at a scanner level, moving in pairs via two elevators to upper levels, and feeding four pick-up points for narrow-aisle cranes. Each aisle was modeled with asymmetrically placed pickup and drop-down stations across two levels, with each aisle section assigned its own crane and dedicated loading/unloading stations. Animated, real-time statistics were embedded in the simulation to surface throughput metrics and congestion points dynamically. This virtual environment allowed engineers to run the system through anticipated peak and trough demand scenarios — without touching physical hardware — and iterate on design modifications before finalizing the build.

The digital twin validation confirmed that the proposed AS/RS design was robust against the full range of anticipated pallet input and output variability. Critically, the simulation identified unexpected bottlenecks that were not apparent in the original design — findings that were subsequently confirmed by the system's own designers. Because these issues surfaced in the virtual environment rather than after installation, feasible design modifications were tested and incorporated into the final system specification without costly rework. The brewer avoided the risk of commissioning a system with structural throughput constraints, and the design team gained validated confidence in the system's ability to sustain operations through demand peaks.

• Simulate before you build: Digital twins surface bottlenecks that static design reviews miss — discovering these virtually is orders of magnitude cheaper than post-installation rework.
• Model the full material flow end-to-end: Isolated component testing misses system-level interactions; the value here came from modeling conveyors, elevators, and cranes as an integrated network.
• Stress-test against demand variability, not average throughput: Food & Beverage distribution centers must handle peaks and troughs — validate specifically against those extremes.
• Use simulation output to create design consensus: When the digital twin flagged bottlenecks that the original designers later confirmed, it built alignment across engineering teams and accelerated design sign-off.