Theses and Dissertations

Issuing Body

Mississippi State University

Advisor

Raed Jaradat

Committee Member

Linkan Bian

Committee Member

Terril C. Falls

Date of Degree

8-6-2021

Original embargo terms

Worldwide

Document Type

Graduate Thesis - Open Access

Major

General Engineering

Degree Name

Master of Science

College

James Worth Bagley College of Engineering

Department

Computational Engineering Program

Abstract

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.

Sponsorship

Institute for Systems Engineering Research (ISER), Mississippi State University

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