A Discrete Event Simulation (DES) is a method of modeling dynamic systems where events occur at distinct points in time. This DES project aimed to establish a complete, high-fidelity model of the end-to-end flow of operations within a modern fulfillment center (FC). This simulation encompassed many internal processes, including:

- Trailer Inbound
- Receiving/Putaway
- Carton Erection
- Carton to Robot Induction
- Collaborative Picking (incl. Travel)
- Pallet/Case Replenishment
- Carton Unloading, Void Fill, and Sealing
- Sortation
- Shipping

Key Objectives:
System Modeling — develop a detailed model that reflects the real-world dynamics of the FC, including operator schedules, inventory levels, robot and picker routing, machine rates and uptime, conveyor controls and much more.

Performance Analysis — analyze the performance of each resource in terms of utilization and throughput, and order cycle time.

Bottleneck Identification — identify bottlenecks and delays within the system. Delays are a result of factors like labor/equipment/or material availability.

Optimization — provide recommendations for process improvements and resource allocation to optimize overall efficiency.

Report and Recommendations — generate a comprehensive report summarizing the simulation results and providing data-driven recommendations for increasing system throughput and achieving service level agreements (SLAs). Estimate return on investment (ROI) based on the capital expenses (CapEx) and operating expenses (OpEx) of each option.

Results:
The simulation identified bottlenecks in the receiving and carton unloading process, which resulted in frequent item stockouts and robot queueing at pack finish. Addressing these bottlenecks increased overall throughput by 20%. Additional improvements were made by redistributing labor during peak times, establishing zone picking, increasing the number of cartons per trip, and improving robot traffic management. Implementing these recommendations lead to a 10% reduction in operational costs. Since, the FC was live, the baseline results were easily validated. The ability to manipulate variables and simulate days of operations within minutes, highlighted the main areas of opportunity to leadership. A final model was established and used in labor planning.