Estimation of part waiting time and fleet sizing in AGV (automatic guided vehicle) systems

As manufacturing systems have grown in size and complexity, material flow control has become one of the key issues for system efficiency, and determination of the number of vehicles required is an important issue in the design of the AGV (automatic guided vehicle) systems for automated material flow control. In an AGV system, a part issues a delivery request for its transportation, and then an empty vehicle is assigned based on a pre-determined vehicle selection rule and provides delivery service. This research presents a fleet sizing procedure for an AGV system with multiple pickup and delivery stations. A queueing model is used to estimate part waiting times. The fleet sizing procedure estimates the minimum number of vehicles needed to ensure a predefined part waiting time limit. While most stochastic models assume first-come-first-served or random vehicle selection rules for the selection of an empty vehicle, this model considers such additional rules as the nearest vehicle selection rule, which is the most popular among all vehicle selection rules. The performance of the proposed model is examined through computational experiments.