Date of Graduation
5-2021
Document Type
Thesis
Degree Name
Bachelor of Science in Industrial Engineering
Degree Level
Undergraduate
Department
Industrial Engineering
Advisor/Mentor
Nurre Pinkley, Sarah
Committee Member/Reader
Sullivan, Kelly M.
Abstract
In the sub-Saharan region of Africa, the inability to perform emergency blood transfusions due to an inadequate blood supply has led to high fatality rates, especially among women and children. The prevalence of disease in this region limits the supply of local blood donations and, if blood is imported, then the region’s poor infrastructure inhibits fast distribution. There is a need for a technological update in the current process that overcomes the limitations of regional transportation, and drones present one promising solution for delivering small, lightweight items such as blood units. The current focus of this new delivery method is on the technological improvements of the drones to combat the short lifespan of drone batteries; however, there is an opportunity for research into logistical improvements of blood delivery. To increase delivery efficiency, countries can implement supply stations, or centralized locations that stock charged drone batteries and varying types of blood and medical supplies, from which drones are deployed to execute deliveries. Centralization allows for on-demand deliveries to the medical facilities that are in the station’s serviceable area.
To solve the location problem at hand, I created the Supply Station Coverage and Assignment model, a mathematical model to determine the optimal locations for these supply stations that maximizes the coverage of prioritized medical facilities and minimizes the distances between the supply stations and medical facilities. The restrictions of the drone’s flight radius and the capacity of a single supply station are used as constraints. As an output, the model allows the user to see which supply stations are implemented and the assignment of the implemented supply station to the covered medical facilities. The model was used to run tests on supply station capacity, health factors, area coverage, and overlap of coverage and the results are presented.
Keywords
Drone Delivery; Facility Location; Rwanda; Medical Supplies; Integer Programming
Citation
Suellentrop, M. (2021). Locating Drone Battery Supply Stations to Facilitate the Delivery of Medical Supplies in Low and Middle-Income Countries. Industrial Engineering Undergraduate Honors Theses Retrieved from https://scholarworks.uark.edu/ineguht/75
