Simulation-based optimization for determining AGV capacity in a manufacturing system

We consider a manufacturing system that uses Automated Guided Vehicles (AGVs) for material handling. Increasing the capacity of the AGVs used can lead to increased throughput and reduced inventory-holding costs. However, AGVs are typically expensive. Hence modeling the economics of buying an additional vehicle is an important problem from the standpoint of making a system lean. Optimization of the AGV’s capacity can be performed analytically only under some simplifying assumptions about the system. We present a simulation-optimization approach to determine the optimal capacity of an AGV in a closed loop path, where the AGV is used as a device for pick-up from machines and drop-off at a conveyor. Our focus in this work is on optimizing the capacity of the AGV.