Graduation Semester and Year

2006

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Industrial Engineering

Department

Industrial and Manufacturing Systems Engineering

First Advisor

Donald Liles

Abstract

Enterprises around the world are employing reverse supply chain practices to generate profit making opportunities while meeting new regulations. As a result of the rapid progress in technology the product lifecycles are shrinking faster than ever. In the face of global competition, heightened environmental regulations and a wealth of additional profits and improved corporate image opportunities, performing the reverse supply chain operations at a world class level is becoming quintessential. These factors in addition to the inherent complexity of reverse supply chains due to the uncertainties associated with the quantity, quality, and timing of returns make returns management very complicated. Existing literature on reverse supply chains focuses on how organizations are effectively using reverse logistics practices to sustain competition and how to optimize the overall reverse supply chain, but there is little investigation into how organizations are able to evaluate their reverse supply chain operations. This research spotlights this particular problem from a consumer electronics industry perspective, as it poses some of the greatest challenges in handling returns due to the presence of high clock speed products and greater return volume and variability. In this dissertation, a quantitative methodology called PEARL- Performance Evaluation Analytic for Reverse Logistics is developed to facilitate decision making from the perspective of an enterprise engaged in reverse logistics. It explores the various reverse logistics functions and product lifecycle stages. It also develops some key business strategies and performance metrics that can be employed to be successful in returns handling. The various relationships between these attributes are assessed using Analytical Network Process and Fuzzy Logic to generate an overall performance score called as the Reverse Logistics Overall Performance Index, indicating the organizations returns management process compared to best in class practices. Deployment of the PEARL methodology in organizations provides a real world assessment of what strategies, reverse logistics functions, product lifecycle stages, or key performance indicators impact the Reverse Logistics Overall Performance Index, thereby allowing organizations to continuously improve their returns management capabilities.

Disciplines

Engineering | Operations Research, Systems Engineering and Industrial Engineering

Comments

Degree granted by The University of Texas at Arlington

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