Mississippi State University
Terril C. Falls
Date of Degree
Original embargo terms
Graduate Thesis - Open Access
Master of Science
James Worth Bagley College of Engineering
Computational Engineering Program
This study proposed a utility-driven two-stage stochastic mixed-integer linear programming model to understand how the patient preferences impact the additive manufacturing (AM) supply chain design decisions. The goal of the mathematical model is to maximize the utilities derived from the customer preferences by appropriately allocating the AM facilities in the targeted region under customer decision and demand uncertainty. The mathematical model is visualized and validated by developing a real-life case study that utilizes the biomedical implants data for the state of Mississippi. A number of sensitivity analyses are conducted to understand how the patients' behavioral decisions (e.g., price-centric versus time- or quality-centric customers) to purchase biomedical implants impact the AM supply chain design decisions. The results revealed key managerial insights that could be utilized by healthcare service providers and interested stakeholders to provide quality healthcare services by managing patient-centric AM facility siting decisions.
Institute for Systems Engineering Research (ISER), Mississippi State University
Ranta, Julekha Hussain, "Additive manufacturing supply chain design and modeling using customer product choices: an application with biomedical implants" (2021). Theses and Dissertations. 5222.