In this case study, Tolgahan Tarkan from Dijitalis presents how he optimized AGV fleet investments in large production system and saved more than 1.5 million USD  in capex using Simio simulation software. The presention was broadcasted at the Simio Sync 2025 simulation modeling summit.

The consultant shows details of how he built the model quickly using auto-create feature of Simio. The simulation model is highly flexible since most of the model is created using data-driven methodology therefore enabling any data in the data tables to be imported from Excel such as production schedule, product routings, bill of materials (BOM) so on.

The simulation model also acts as production schedule verification tool in terms of AGV/AMR timeliness. Dijitalis consultant also shows two heat maps, one for aisle congestion and second for aisle traffic flow rate all using Simio simulation software. The Gannt charts in Simio also provides information about delay causes in the initial system. Therefore it is possible to do root cause analysis with the Gannt charts of Simio software.

The consultant shows details of how he built the model quickly using auto-create feature of Simio. The simulation model is highly flexible since most of the model is created using data-driven methodology therefore enabling any data in the data tables to be imported from Excel such as production schedule, product routings, bill of materials (BOM) so on.

The simulation model also acts as production schedule verification tool in terms of AGV/AMR timeliness. Dijitalis consultant also shows two heat maps, one for aisle congestion and second for aisle traffic flow rate all using Simio simulation software. The Gannt charts in Simio also provides information about delay causes in the initial system. Therefore it is possible to do root cause analysis with the Gannt charts of Simio software.