Operations Research, Systems Engineering and Industrial Engineering Commons^™

Development Of A Putting Green Manufacturing Process, Tabitha R. Webster

Honors Theses

Our Capstone project investigates the end to end design, development, and production of a 6‑foot long portable putting green marketed for individuals seeking a high quality, competitively priced golf product for home or office use. The capstone project examines the full lifecycle of product creation applying manufacturing principles learned through the center of manufacturing’s coursework. From the initial concept through engineering design, market research, prototyping, manufacturing optimization, and final production the project emphasizes cross‑functional collaboration across engineering, business, and accountancy majors. Methods used to gather data included marketing surveys, CAD drawings, time studies during production runs, value stream mapping, and …

Modeling Individual Self-Protective Behavior During Epidemics, Geonsik Yu, Michael J. Garee, Mario Ventresca, Yuehwern Yih

Faculty Publications

Protecting public health from infectious diseases requires collective action, as individual behaviors—such as vaccination and mask-wearing—directly influence disease dynamics. During the COVID-19 pandemic, unexpected public responses often undermined the effectiveness of interventions, highlighting the need to understand collective behavioral patterns and motivations to design more effective mitigation strategies. This study presents an agent-based simulation model that captures how individuals adjust self-protective behaviors based on evolving opinions about disease risk and examines how these decisions interact with external factors, such as public health interventions, to shape collective outcomes. To improve the representativeness of the simulated population, multiple datasets were integrated to …

Development Of A Putting Green Manufacturing Process, Jose Andres Cepeda Santiago

Honors Theses

Our Capstone project investigates the end-to-end design, development, and production of a 6‑foot long portable putting green marketed for individuals seeking a high quality, competitively priced golf product for home or office use. The capstone project examines the full lifecycle of product creation applying manufacturing principles learned through the center of manufacturing’s coursework. From the initial concept through engineering design, market research, prototyping, manufacturing optimization, and final production the project emphasizes cross‑functional collaboration across engineering, business, and accountancy majors. Methods used to gather data included marketing surveys, CAD drawings, time studies during production runs, value stream mapping, and controlled documentation …

The Optimization Of A Robotic Welding Arm To Improve Efficiency, Margaret Close

Honors Theses

The main objective of this report is to optimize a robotic welding arm to improve a locker manufacturing process. The robotic welding arm, a Miller PerformArc, used by Lockers Manufacturing has been producing spatter. Spatter significantly reduces the quality of the product and increases the product’s manufacturing time. The goal of this project was to find the best solution to reduce spatter without weakening the welds and ensuring that efficiency will increase. The first step in this project was to test multiple weld testing variables such as voltage, current, welding angle, robot speed, and arc and crater ratios. For each …

Largest 2-Regular Subgraphs In Complete S-Partite Graphs, Yiyang Jiang

McKelvey School of Engineering Graduate Student Theses & Dissertations

In this thesis, we focus on the class of complete $S$-partite graphs, for $S$ an undirected graph possibly with self-loops, and address the problem of finding largest $2$-regular subgraphs of these graphs, which can be formulated as an integer linear program. Roughly speaking, a complete $S$-partite graph is obtained by replacing every single node of $S$ with a number of nodes, preserving the edge/non-edge relations of $S$. Our motivation in studying largest $2$-regular subgraphs is rooted in the structural systems theory, particularly in the problem of finding largest subnetworks that can sustain controllability or asymptotic stability of the corresponding subsystems. …

A Systems Perspective On Workstation Ergonomic Principles And Their Application In Emergency Care Environments, James Espinosa, Alan Lucerna

Rowan-Virtua Research Day

Background: Workstation ergonomic principles are commonly included in mandatory healthcare training programs. These recommendations—monitor height relative to eye level, neutral arm positioning, and adjustable seating—derive largely from occupational ergonomics literature designed to reduce musculoskeletal strain and improve comfort during computer work. Emergency Departments (EDs), however, represent dynamic environments with shared workstations and workflow interruptions that may influence the implementation of these recommendations.

Objective: To summarize the evidence supporting commonly taught workstation ergonomic principles and frame them within a systems perspective of ED work environments.

Methods: Narrative review of occupational ergonomics guidelines, ergonomic intervention studies, and human factors literature relevant to …

Digital Lean Transformation Through Mes–Scada Intergration: Reducing Transactional And Cognitive Waste In High-Volume Electronics Manufacturing, Kamal Alalul

Graduate Dissertations and Theses

This research addresses inefficiencies in Manufacturing Execution System (MES)-driven workflows, where excessive user interactions and fragmented access to work instructions introduce transactional and cognitive waste. To address these limitations, an integrated architecture was developed using Ignition as a SCADA-based operator interface connected to the MES through API-based communication. The system replaces direct MES interaction with a unified interface that embeds work instructions and automates transaction execution within the production workflow. The approach was implemented and evaluated through an industrial case study on a 15 station electronics manufacturing line. Results show a 51% reduction in total cycle time, decreasing from 2,996 …

Leveraging Information Theory And Ecological Network Analysis To Monitor Communication Networks In A Student Aerospace Team, Christine Sessions

Doctoral Dissertations and Master's Theses

Effective communication is a critical component of successful collaboration in group projects and team settings. However, systematically tracking and analyzing team communications can be challenging, especially in complex, multi-member teams such as those found in the aerospace industry. This paper explores an information-theoretic approach that leverages encoding techniques and graph theory to analyze communication networks within a university’s multi-year, student-led cubesat design project (Project COMET). By utilizing Shannon Entropy as a measure of information flow, encoding communication patterns, and analyzing Ecological Network Analysis parameters, this research aims to understand how an Embry-Riddle Aeronautical University student project team evolves over the …

Engineering Design And Analysis Using Creo® Cad, Cae, And Manufacturing Applications, Swapnil Moon

Open and Affordable Textbooks

This textbook presents a structured approach to computer-aided design using Creo, integrating CAD, CAE, and CAM workflows within a unified engineering framework. The material emphasizes parametric modeling, design intent, and feature-based modeling as foundations for creating robust and adaptable engineering models. Through progressively structured tutorials, students develop skills in part modeling, assemblies, engineering drawings, mechanism design, simulation, and manufacturing. The text incorporates real-world engineering components and workflows, including structural and thermal analysis, motion simulation, and toolpath generation, reflecting modern engineering practice. Designed for upper-division undergraduate and graduate students, this open educational resource supports hands-on learning and prepares students for industry-relevant …

Introduction To Computer-Aided Design Using Solidworks® : A Structured Approach To Parametric Modeling And Design Intent, Swapnil Moon

Open and Affordable Textbooks

This textbook introduces computer-aided design (CAD) using SOLIDWORKS® through a structured, design-centered approach that emphasizes parametric modeling and engineering reasoning. Rather than focusing solely on software commands, the material develops foundational skills in design intent, constraint-based modeling, and feature relationships to create robust, adaptable models.

The content is organized progressively, beginning with basic sketching and feature creation and advancing to complex part modeling, assemblies, motion studies, and engineering drawings. Each chapter builds upon prior concepts, reinforcing systematic modeling practices and promoting the development of system-level thinking required in real-world engineering design workflows.

Designed for undergraduate students with little or no …

Reflective Analysis Of Industrial Engineering Leadership Skills Applied In Being A Capstone Team Leader, Sarah Nesmith

Industrial Engineering Undergraduate Honors Theses

This paper presents a reflective analysis of leadership skills that I, Sarah Nesmith, have acquired and applied as an honors student serving as a capstone team leader within the Industrial Engineering program at the University of Arkansas. My senior capstone project is in partnership with Walmart’s Transportation and Optimization Department and focuses on identifying the root and contributing causes of empty miles (miles driven without freight on a truck) and exploring backhaul opportunities. The ultimate goal is the development of a tool or method that can identify these opportunities to save money while maintaining service level. As the appointed team …

A Multi-Objective Optimization Framework For Equitable Stormwater Management In Urbanizing Rural Communities, Harry L. Wilson

Industrial Engineering Undergraduate Honors Theses

Due to limited technical and financial resources, urbanizing rural communities often face growing stormwater management challenges while undergoing rapid development. This thesis proposes a mixed-integer linear programming (MILP) framework that integrates topography-driven stormwater flow behavior, infrastructure placement constraints, and multiple planning objectives to support cost-effective stormwater infrastructure decisions. Our model accounts for budget constraints, gravity-driven surface water flow, infiltration capacity, and spatial contiguity requirements to determine optimal pond placements that balance flood reduction and implementation costs. A synthetic discretized grid representing a small municipality is used to demonstrate model behavior under varying rainfall and topographic conditions. Results demonstrate the framework's …

Multi-City Travel Routing Tool: Reducing Travel Costs And Time Spent Planning Using Apis, Trey R. Merreighn

Industrial Engineering Undergraduate Honors Theses

Travel planning is a time-consuming and ever-changing problem that can diminish the travel experience and greatly increase expenditure, if not done correctly. It is important to have an easy travel planning experience so you can enjoy the travel experience more and not waste time where it is not needed. This thesis aims to minimize the costs and time spent on travel planning using APIs and simple optimization models, creating a travel planning tool. This travel planning tool was developed in Java with the main API being Amadeus, this was combined with a greedy best-permutation heuristic to create the main route …

The Expectation Of Pain: Effects On Threshold, Tolerance, And Perception, Emma Paulus

Mechanical Engineering Undergraduate Honors Theses

Brain activity in pain-related regions of the cortex is thought to be influenced by interactions between expectations and incoming sensory information. However, the subjective experience of pain based on expectation has not been thoroughly explored. By changing visual and auditory cues to set expectation levels, a relationship between unconscious expectation of pain and actual sensory pain experienced was characterized. With IRB approval, volunteers were randomly and blindly grouped into low and high pain expectancy groups. Each group completed a survey about initial pain expectations before the muscle stimulation tolerance test, followed by a survey about actual pain perception after the …

A Forecasting Framework For Distribution Center Capacity Utilization: An Applied Industry Study, Jordan J. Shortt

Data Science Undergraduate Honors Theses

This project develops and evaluates a predictive modeling framework for forecasting distribution center capacity utilization at Company Y, with monthly forecast horizons up to one year. Motivated by the operational challenges of seasonal demand volatility, promotional cycles, and the absence of a formally defined capacity metric, the study first constructs a historical capacity utilization measure from raw warehouse management system data — reconciling item volumes, location dimensions, and utilization factors across all DCs — which serves as the target variable for all modeling work. Four models are developed and evaluated against a naïve seasonal baseline: SARIMA, LightGBM, LSTM, and a …

Optimizing College Food Pantry Locker Systems Through Simulation Techniques, Jacob W. Holmes

Industrial Engineering Undergraduate Honors Theses

Food insecurity affects 10.5% of households in the United States. Among those affected, college students are a group with increasing food insecurity. Through novel food pantry order methods, such as locker order systems, some effects of college food insecurity can be alleviated. The Jane B. Gearhart Full Circle Food Pantry (FCFP) at the University of Arkansas implemented a locker system, beginning in the Fall of 2020. There is a lack of investigation into locker management policies for pantries, such as how much time clients should be allowed to pick up orders after they are placed in lockers, how many lockers …

The Influence Of Social Media On The Product Life Cycle In Fast Fashion: A Shein Case Study On Environmental And Social Impacts, Clara R. Devine

Industrial Engineering Undergraduate Honors Theses

Fast fashion has transformed global consumer culture through its rapid product cycles, affordability, and accessibility. However, this model has also contributed significantly to environmental degradation, excessive textile waste, and unethical labor practices. Social media platforms have accelerated these patterns by amplifying short-lived trends and influencing consumer purchasing behavior. This study aims to analyze the relationship between social media activity and the fast-fashion life cycle, with a focus on how online engagement drives consumption, production speed, and environmental impact. The research utilized a quantitative and analytical approach, combining correlation analysis and time-series data to evaluate the connection between SHEIN’s growing user …

A Study Of Visualized Diagnostics In Early Stage Digital Twin Implementation Of An Industrial Control System, Michael R. Kinzel

All-Inclusive List of Electronic Theses and Dissertations

Industrial Control Systems (ICS) are used for process control in almost all industries. An ICS combines Operational Technologies (OT) with Information Technologies (IT) to allow human supervision of a process through surveillance of process variables and manipulation of controlling elements such as valves to maintain stable process conditions. ICSs have been in-service for several decades and may remain operational past their technological service life. Organizational personnel interact with the ICS through visual displays that both indicate the process variables and also the controlling elements. The Human Machine Interface (HMI) allows visibility of the process and the ability to manipulate controlling …

A New Approach To Generate Combinatorial Patterns In Logical Analysis Of Data And Its Application To Predict College Retention, Salihah Ahmed E. Jaafari

Theses and Dissertations

Student retention and degree completion remain central challenges for higher-education institutions, with significant implications for student success, institutional effectiveness, and public accountability. While advances in predictive analytics have enabled earlier identification of students at risk of withdrawal, many commonly used machine learning approaches suffer from limited interpretability, constraining their practical usefulness for advising, intervention, and policy decision making. This dissertation addresses the problem of predicting student persistence by developing and evaluating optimization based, interpretable classification models within the Logical Analysis of Data (LAD) framework. Building on existing LAD formulations, this research introduces two novel pattern generation models, the Best Term …

Factors Affecting Pedestrian-Vehicle Conflicts: An Empirical Analysis, Christo D. Jamo

Honors Scholar Theses

The number of pedestrian deaths increased by 78% between 2009 and 2023, while other motor vehicle crash deaths increased by 13% in the same period [1]. To identify potential pedestrian safety measures, this study analyzed the effects of location-based demographics, pedestrian phasing type, and other physical infrastructure and behavior variables on the probability of pedestrian-vehicle conflicts at signalized intersections, which is a surrogate measure of crash risk. Data were collected from 55 intersections in Connecticut, and the pedestrian-vehicle interactions were classified by severity based on the Swedish Traffic Conflict Technique: undisturbed passage, potential conflict, minor conflict, or serious conflict. Because …

Feasibility Study Of Transitioning From Thick Plates (0.250”) Mounted On 30-Point Pvc Carriers To Thinner Plate Technologies Mounted On Recyclable Foam And Pet (0.155”) For Post-Print Corrugated, Nathaniel J. Poole

All Theses

In the United States, the most common press configuration for brown-box printing is a 0.280” undercut press. These press configurations have long relied on thick 0.250” plates mounted on 0.030” PVC sheets to print onto corrugated substrates. Each year, around twenty million pounds of waste are produced by the printing industry, through paper waste, plate waste, among other materials. One large factor of that waste is flexographic plate waste, which either ends its life in a landfill or is repurposed into other products. This study establishes a comparison between traditionally used 0.250” plates on 30pt PVC versus 0.155” plates mounted …

Enhancing Control Charting Schemes And Exploring New Assessment Metrics To Advance Quality Control And Cyber-Attack Detection In Manufacturing, Ahmad Al Majali

Dissertations

The increasing integration of digital technologies and industrial control systems in modern manufacturing has introduced new cybersecurity vulnerabilities within cyber–physical production environments. Malicious actors can exploit these vulnerabilities to induce subtle process deviations that degrade product quality while remaining undetected by conventional statistical monitoring tools. Such attacks can be deliberately engineered to manipulate process behavior through transient shifts that vary in magnitude, duration, and frequency. Despite extensive research on transient shifts caused by assignable causes in Statistical Process Control (SPC), limited attention has been given to intelligently designed cyber–physical attacks that exploit the structural characteristics and limitations of control charting …

Decision Making For Large-Scale Problems Under Uncertainty And Conflict, Benjamin J. Hamlin

All Dissertations

Large-scale decision-making problems appear in many areas including long-range forecasting such as energy generation forecasting. Many such problems are subject to conflicting objectives and uncertain data, and can be modeled as linear optimization problems. We study novel theoretical results and algorithms for large-scale linear decision problems under conflict and uncertainty. First, we propose a parametric Benders decomposition algorithm for solving large-scale linear optimization problems with multiple objectives or deterministically uncertain objectives. Second, we extend the parametric Benders decomposition to a multi-stage setting, developing a parametric stochastic dual dynamic programming algorithm, which enables decision-making when conflicts and uncertainty have planning impacts …

Optimal Allocation Of Flexible Servers In Healthcare Systems, Tong Zhang

All Dissertations

This dissertation investigates the optimization of worker allocation in healthcare systems, focusing on flexible staffing models and the strategic prioritization of healthcare tasks. This research explores the dynamics among pre-operative, operative, and post-operative care units under various cost and service-rate constraints, using a series of models that represent realistic healthcare scenarios within a comprehensive framework for improving patient flow and reducing waiting costs.

In Chapter 2, we model and analyze cross-trained nurse allocation policies within an inpatient surgical system. We model the surgical system as a tandem clearing queueing system and formulate Markov decision processes under different business rules governing …

Manufacturing Systems: Characteristics And Dynamics, Alan J. Fitzmorris

Graduate Theses and Dissertations (2019 - present)

This research answers three basic questions. First, what are the behaviors (dynamics) of a manufacturing system in the context of system performance? Are these dynamics best described as linear deterministic, periodic, nonlinear deterministic, or stochastic? Second, what are the complexity (chaotic) characteristics of a manufacturing system, namely the maximal Lyapunov exponent, correlation dimension, and Kolmogorov-Sinai entropy? Third, is there a relationship between complexity characteristics and manufacturing system performance? This research involves four high level steps: data analysis, system dynamics analysis, system complexity analysis, and correlation analysis. The data analyzed consists of concrete plant and shipbuilding shop time series performance data. …

Cross-Facility Reliable Deep Learning Based Beef Marbling Assessment Via Unsupervised Domain Adaptation Regression, Samuel Vinson

Biological and Agricultural Engineering Undergraduate Honors Theses

Inconsistent quality grading in beef production leads to inefficiencies, economic disparity, and consumer mistrust. While USDA meat grading traditionally relies on skilled visual inspectors, these human evaluations suffer from cross-facility variability and subjectivity. This paper introduces the first known application of unsupervised domain adaptation regression for cross-facility beef marbling score prediction—an innovation that improves generalization across diverse environments in the beef supply chain. Utilizing numerical scores ranging from 100-900, the research employed convolutional neural networks (CNNs), including ResNet, VGG, and AlexNet architectures. The study specifically introduced and validated a unified unsupervised domain adaptation regression method using the ResNet-50 architecture to …

Intelligent Manufacturing Of Edible Oil: From Smart Sensing To Big Data Platform, Ru Jiang, Nadirbek Yusupbekov

Chemical Technology, Control and Management

With the rapid advancement of Industry 4.0 technologies, intelligent manufacturing and big data platforms are profoundly transforming the production models of the traditional edible oil industry. The edible oil production process involves multiple complex unit operations such as refining, decolorization, and deodorization, which impose high requirements on process control and product quality monitoring. This paper presents a systematic review of key technological advances in the field of intelligent manufacturing of edible oil, establishing a comprehensive technical framework encompassing four dimensions: smart sensing, artificial intelligence applications, IoT communication, and big data platforms. The review begins by analyzing the global background and …

Data-Driven Neuro-Fuzzy Modeling And Rule Optimization For Intelligent Prediction Of Bioreactor Dynamics, Kamala Najaf Mammadzada

Chemical Technology, Control and Management

Modeling wastewater bioreactors is a challenging problem in environmental engineering because the processes are constantly changing and the microorganisms do not behave in a linear or predictable way. This makes it difficult to predict and control the system behavior. This research investigates three artificial intelligence approaches for modeling wastewater bioreactors: the Mamdani Fuzzy Inference System (FIS), the Adaptive Neuro-Fuzzy Inference System (ANFIS), and clustering-based fuzzy models. These models help us predict what is happening in the bioreactors. For instance they help us predict how the amount of substances in the water is changing over time like dS₀/dt dSs/dt …

Regular Synthesis Algorithms Of Control Devices In Nonlinear Control Systems, Husan Zakirovich Igamberdiyev, Iskandar Yusupovich Abdurakhmanov, Uktam Farkhodovich Mamirov

Chemical Technology, Control and Management

This paper examines the development of regularized algorithms for synthesizing control devices in control systems for polynomial objects, described by multidimensional Volterra functional series. The synthesis problem is solved using a two-stage procedure. In the first stage, the optimization problem is initially solved for an open-loop system. The second stage involves determining the parameters of the control device, i.e., its impulse response functions, by using the relationship between the characteristics of the open-loop and closed-loop systems. Regular algorithms are presented for finding the impulse response functions of the control device based on methods for regularizing the solution of operator equations …

Increasing The Prediction Accuracy Of Plant Oil Production Processes Through Adjusting The Parameters Of Machine Learning Models, Umidjon Ruziev, M.K. Shodiev, A.T. Rajabov

Chemical Technology, Control and Management

Vegetable oil production is characterized by high variability in output indicators due to nonlinear interactions between raw material parameters, equipment modes, and heat and mass transfer conditions. Existing approaches to applying machine learning in this field, as a rule, do not account for the impact of hyperparameter adjustments on forecasting quality across specific technological stages. The article presents a systematic methodology for adjusting model parameters (Ridge regression, SVR, GBM, LSTM) applied to three key tasks: predicting residual oil content in oil cake, color index during bleaching, and free fatty acid content during deodorization. In a set of 1000 observations, including …