Abstract

With increasing environmental concerns, recovery of used products through various options has gained significant attention. In order to collect, categorize and reprocess used products in a cost and time efficient manner, a pre-evaluated network infrastructure is needed in addition to existing traditional forward logistics networks, in most cases. However, such networks, which are referred to as reverse logistics networks, impose inherent uncertainty in returned product supply and challenges additional to forward networks. Incorporating uncertainty in long term decisions with regards to network planning is significant especially in RL networks, since such decisions are difficult and costly to adjust later on. Uncertainty in product returns, dynamic and complex behavior of the system can be modeled as a queueing model, using a discrete event simulation methodology. In this work, a simulation based tool is developed which can be used as a platform for evaluating and comparing reverse logistics network configurations. In addition to defining system parameters, the tool provides experimentation with the number of collection, sorting, and processing centers, as well as the standard deviation of the return rate distribution. Various types of experiments are used in order to illustrate the use and goal of the tool, where the trade-offs within and across scenarios are addressed. Experiments are divided into three main parts; verification, pairwise detailed and a final more holistic scenario which illustrates the usage of the tool. A user interface is developed via Microsoft Excel for convenient specification of operational system parameters and scenario values. Upon running the simulation with specified experimental factors, the tool automatically computes and displays the total weighted score of each scenario, which is an indicator of the scenario quality.

Library of Congress Subject Headings

Remanufacturing--Management--Computer simulation; Recycling (Waste, etc.)--Management--Computer simulation; Business logistics--Data processing; Queueing theory

Publication Date

4-20-2016

Document Type

Thesis

Student Type

Graduate

Degree Name

Sustainable Engineering (MS)

Department, Program, or Center

Industrial and Systems Engineering (KGCOE)

Advisor

Michael E. Kuhl

Advisor/Committee Member

Brian K. Thorn

Comments

Physical copy available from RIT's Wallace Library at TS183.8 .Y36 2016

Campus

RIT – Main Campus

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