Reflective Analysis Of Industrial Engineering Leadership Skills Applied In Being A Capstone Team Leader,
2026
University of Arkansas, Fayetteville
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,
2026
University of Arkansas, Fayetteville
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,
2026
University of Arkansas, Fayetteville
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,
2026
University of Arkansas, Fayetteville
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,
2026
University of Arkansas, Fayetteville
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,
2026
University of Arkansas, Fayetteville
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,
2026
University of Arkansas, Fayetteville
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,
2026
Indiana State University
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,
2026
Florida Institute of Technology
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,
2026
University of Connecticut - Storrs
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,
2026
Clemson University
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,
2026
Western Michigan University
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,
2026
Clemson University
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,
2026
Clemson University
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,
2026
University of South Alabama
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,
2026
University of Arkansas
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,
2026
Institute of Automation, Qilu University of Technology (Shandong Academy of Sciences). Address: 19 Keyuan st., 250000, Jinan city, China. E-mail: [email protected], Phone: +998-77-309-09-17;
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,
2026
Azerbaijan State Oil and Industry University. Address: Azadliq Avenue 20, AZ1010, Baku, Azerbaijan. Email: [email protected], Phone: +994-50-983-39-94.
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,
2026
academician of the Academy of Sciences of the Republic of Uzbekistan, doctor of technical sciences, professor of the department “Information Processing Systems and Control” at Tashkent state technical university named after Islam Karimov, Address: 100095, University str. 2, Tashkent, Uzbekistan. E-mail: [email protected];
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,
2026
Tashkent State Technical University. Address: University street 2, 100095, Tashkent city, Republic of Uzbekistan. E-mail: [email protected].
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 …
