Case Study of Drone Delivery Reliability for Time-Sensitive Medical Supplies With Stochastic Demand and Meteorological Conditions

Abstract

Drones are increasingly being utilized to deliver medical supplies, and the COVID-19 pandemic has accelerated this trend. Drones arrive quickly by taking more direct paths and avoiding ground-based obstructions. However, drones are not completely reliable and may also experience failures and delays. For consumer products, delivery delays are an inconvenience, but for some medical supplies, delays may be fatal. This research focused on the drone reliability of one particular type of supply and event: automatic defibrillators for out-of-hospital cardiac arrests. A modeling framework was developed to analyze drone delivery reliability with stochastic demands and meteorological conditions. Using probability distributions based on real data from Portland, OR, this research quantified the failure rates as a function of drone range and meteorological conditions that included temperature, precipitation, and wind. Tradeoffs among drone reliability, fleet size, population size, and meteorological conditions were analyzed.