Challenge

For this project, we collaborated with a global logistics company specializing in supply chain management, freight transportation, and warehousing solutions across air, land, and sea. They sought to develop a simulation model in AnyLogic to analyze the efficiency of human resources in their inbound warehouse operations.

Solution

The simulation model served two primary purposes: first, as a communication tool to visualize resource utilization through data, and second, as an experimentation platform to assess the impact of system input changes on key operational KPIs.

The simulation model represented the inbound warehouse operations, starting from the arrival of trucks with pallets to the storage of these pallets in their designated put-away locations. The operations included only inbound administrative work, unloading using forklifts, sorting, first article inspection, and material requirements planning.

Within this process, only three pallet types exist: Mono-Pallets GS1, Mono-Pallets non-GS1, and Mixed Pallets. Each pallet type follow a distinct subprocess within the operational scope.

Outcome

All operational parameters, such as labeling time, breakbulk time, and others, were configurable in an Excel file. This Excel file represented a specific scenario and contained all the necessary information to run that scenario. For any experiment the end user intended to run, the Excel file had to be uploaded to the AnyLogic simulation tool. In addition to the operational parameters, this file included assumptions, annual human resources data (fixed and temporary), pallet arrival details, and any other inputs the model required.

The simulation model featured three different views where the user could observe:

1. An animation of the operations in 2D and 3D.
2. The internal logic of the model.
3. Statistics, utilization, working hours, put-away information, and costs.

Special attention was given to optimizing the simulation speed by utilizing lightweight AnyLogic tools, ensuring compatibility with potential future optimization experiments.

Project Features

Industry: Warehouse, Logistics

Models: Discrete-Events

Duration: 1 month