Abstract
The daily medicine delivery is one of the most important activities in hospitals. The traditional medicine delivery, from hospital warehouses to the patients, typically involves a human delivery team supplying patients by handcarts. The multiple steps in the medicine delivery process impact the efficiency and increase the risk of contamination. Many hospitals are therefore on their way to automate this process. The Telelift-based automated medicine delivery system provides high health safety, low operational cost, and high system efficiency. This paper develops a stochastic model to evaluate and analyze the medicine delivery process by such an automated medicine delivery system. We adopt a two-moment approximation method and an aggregation approximation algorithm to solve the nested queuing model, considering regular and peak demand. We use simulation to validate the analytical model. The numerical experiments show that our analytical model is sufficiently accurate to evaluate the automated medicine delivery process. Our model can help decision makers of hospitals to reduce the patient waiting time and medicine response time. Our method can also be extended to other automated overhead material handling systems.