This project modeled a multi-deep automated pallet storage and retrieval system in which retrieving a pallet from the back of a lane required blocked pallets to be temporarily relocated. The objective was to determine whether the proposed system could meet throughput requirements under realistic operating conditions.

Challenge
Multi-deep storage improves density but introduces additional retrieval moves, robot congestion, and sensitivity to pallet placement.

Approach
- Built a streamlined FlexSim model of storage, retrieval, and digging logic.
- Simulated blocked-pallet relocations and return movements.
- Visualized SKU velocity using heatmaps.
- Compared random pallet placement with more natural settling behavior.
- Evaluated throughput and robot congestion across operating scenarios.

Outcome
The model showed that the system could meet throughput requirements despite relocation activity and localized congestion. It also demonstrated that random reshuffling did not naturally create effective slotting, reinforcing the need for deliberate inventory-placement logic.