Abstract

Inventory management is a vital section of a supply chain system. In a hospital setting, where delivering high quality patient care is a prime concern, inventory management is often overlooked. With the ever increasing demand for products, it becomes challenging to manage inventory in a dynamic facility such as a hospital. Although there is abundant research in supply chain, seldom have the proposed methods found their way into execution in actual hospital settings. Additionally, much of the literature focuses on particular aspects of the supply chain. Current methods used in practice lead to system performance that is suboptimal, resulting in too much or too short inventory in stock, overtime work to manage supplies, expedited shipments and potentially substandard quality of care delivered to patients. Having the right products available at the point-of-use is important to the efficient and effective treatment of patients. With cost and budget constraints, merely managing demand is not sufficient. There is a need to develop a system design which enables hospitals and healthcare institutions to implement and benefit from methods that have been developed or are being developed for optimal inventory management systems. In this research, we study the hospital supply chain from manufacturers/distribution centers to the point-of-use within a hospital unit, taking into account the integration and implementation of the various echelon of the supply chain system. In particular, we design and develop a sim-heuristic methodology using operations research to evaluate inventory and operational decision variables based on service level and operational costs, subject to variability in demand and lead-time. In addition, we demonstrate the capabilities and limitations of the methodology and compare alternate system configurations including a (Q, r) inventory system and Kanban system.

Library of Congress Subject Headings

Hospitals--Inventory control; Business logistics; Operations research

Publication Date

7-26-2018

Document Type

Thesis

Student Type

Graduate

Degree Name

Industrial and Systems Engineering (MS)

Department, Program, or Center

Industrial and Systems Engineering (KGCOE)

Advisor

Michael E. Kuhl

Advisor/Committee Member

Katie McConky

Campus

RIT – Main Campus

Plan Codes

ISEE-MS

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