Operations Research, Systems Engineering and Industrial Engineering Commons^™

Advancing Wood Chip Moisture Content Prediction Using Advanced Generative Ai Techniques, Daniel Esteban Marulanda

Theses and Dissertations

In this study we propose a deep learning method to optimize the classification of wood chip moisture content levels using the Vision Transformer and then ultimately increase the classification performance by creating synthetic images using the diffusion transformer model. In the first chapter of our study, we complete a detailed explanation of how the moisture content levels of 10 different wood chips were gathered ranging from 2 to 50$\%$. This chapter serves as a foundation for subsequent sections, illustrating the challenges associated with the current data collection process, which is both time-consuming and inefficient. Accurately determining moisture content for wood …

Development Of Non-Precious Iron-Cobalt Alloy Catalyst For Electrocatalytic Reaction, Harsh Panchal

Electronic Theses & Dissertations

The development of a FeCo alloy catalyst with tunable Fe/Co ratios is examined to improve electrocatalytic performance in reactions like the oxygen evolution reaction (OER), hydrogen evolution reaction (HER), and oxygen reduction reaction (ORR). Many energy conversion devices, such as fuel cells, metal-air batteries, and water-splitting systems, depend on these interactions to function. These technologies have huge potential to meet the increasing need for hydrogen production and renewable energy sources worldwide, which are critical to attaining a sustainable energy future. When compared with noble metal-based catalysts, the FeCo alloy catalyst shows much higher catalytic activity, according to previous studies. Hydrothermal …

The Importance Of Community: An Investigation Of Stress, Coping, And The Value Of Social Support For First Responders, Brian Reid

Theses and Dissertations

People are designed to be in community with others, to work together and share the load and weight of life. First responders are a community that has not emphasized the importance of social support to mitigate and buffer against the stress inherent in their jobs. This study investigates the sources of stress, coping methods, and social support of first responders. Results from the first study show the impact of workplace and family stress on the first responder is impactful from the beginning. The secondary study finds that adaptive coping methods are the preferred method to cope with stress and that …

Enhancing Profitability In The Air Transport Industry Through Improved Air Passenger Forecasting: A Comparative Analysis Of Arima, Holt-Winters And Lstm Time Series Forecasting Techniques, Megan Skowronek

Theses and Dissertations

Predicting air passenger volumes is crucial for airports and airlines seeking to reduce costs and enhance profitability. Accurate forecasting enables better planning and efficiency improvements within the air transport industry. This study applies LSTM, ARIMA and HW to U.S. air passenger datasets. Each analysis shows a methodology for predicting air passenger volumes across airports, airlines and across airports and airlines simultaneously. ARIMA was found to have limited applicability, since only a subset of the datasets was stationary. LSTM and HW were applicable to all airlines and ARIMA was applicable to no airlines. LSTM had less error compared to HW at …

In-Hand Singulation, Scooping, And Cable Untangling With A 5-Dof Tactile-Reactive Gripper, Yuhao Zhou, Pokuang Zhou, Shaoxiong Wang, Yu She

School of Industrial Engineering Faculty Publications

Manipulation tasks often require a high degree of dexterity, typically necessitating grippers with multiple degrees of freedom (DOF). While a robotic hand equipped with multiple fingers can execute precise and intricate manipulation tasks, the inherent redundancy stemming from its high-DOF often adds complexity that may not be required. In this paper, we introduce the design of a tactile sensor-equipped gripper with two fingers and five-DOF. We present a novel design integrating a GelSight tactile sensor, enhancing sensing capabilities and enabling finer control during specific manipulation tasks. To evaluate the gripper's performance, we conduct experiments involving three challenging tasks: 1) retrieving, …

Data-Driven Dynamic Decision-Making Using Discrete Optimization And Supervised Machine Learning, Navid Rashedi

Dartmouth College Ph.D Dissertations

In recent years, the operations research community has developed data-driven optimization techniques to solve complex combinatorial problems with the aid of machine learning. This thesis contributes to these efforts by combining machine learning with optimization to expedite online decision-making, with applications in transportation and healthcare.

In the domain of airline operations recovery, the focus is on the aircraft recovery process—repairing disrupted schedules by minimizing overall disruption costs. Traditional exact methods are too time-consuming, while heuristic approaches often yield poor solution quality and lack generalizability across varying formulations. To address these challenges, this research employs supervised machine learning to identify near-optimal …

Fff Process Parameter Identification With Machine Learning Models, Owen Davis Smith

Honors Theses

Additive manufacturing (AM) has seen increasing popularity in recent times, owing to its efficiency and high speeds, particularly with processes such as Fused Filament Fabrication (FFF). Input process parameters have large impacts on the final part. Incomplete process parameters, which can occur for a variety of reasons, make tasks such as replicating AM studies difficult. A machine learning model can be trained on in-situ layer-wise images collected during a print to combat this issue, predicting process parameters with sufficient data. In this study, two parameters were tested: infill pattern orientation and extrusion width. Twelve parts were produced per parameter and …

A Data Driven Approach To Student Success: Visualizing Engagement And Performance Metrics, Araohat Kokate

2025 Spring Honors Capstone Projects - Archive

Many tutoring centers lack tools to analyze and visualize key performance metrics, limiting data driven decision making. This study develops a data visualization feature for the CSE Student Success Center App at the University of Texas at Arlington, enabling administrators to track student engagement, tutor performance and session trends. Using the data of students and tutors, the feature provides interactive dashboards for real-time insights. Administrators can monitor attendance patterns, tutor workloads and booking trends, optimizing resource allocation. Findings indicate that real-time data visualization enhances decision-making, reducing manual effort while improving operational efficiency. This can further help improve student support services. …

Air And Missile Defense Threat Scenario Variation To Reduce Pretest Sensitization, Video Games As A Case Study, Julie Renee Szekerczes

All-Inclusive List of Electronic Theses and Dissertations

This study uses fixed and variable video game types to measure pretest sensitization as a proxy for repeated and varied threat test scenarios in system performance testing of air and missile defense systems. The pretest sensitization phenomenon exists when repeated exposure to a test condition influences the participant's response. Research shows air and missile defense development correlates with video games, resulting in similar interfaces and computer operating environments. Department of Defense acquisition test and evaluation results must reflect system performance without prior knowledge of the threat scenarios confounding the results. System performance results inform acquisition decisions, such as further funding …

Community Wastewater Treatment Resilience Assessment, Tristan Veal

All Theses

With the rising threat of climate change and cascading impacts from infrastructure failure there is a growing need to strengthen community resilience. Theoretical and practical resilience frameworks are available, but they vary in aim and scope; there is no standard tool to assess resilience. This research expands on the resilience matrix (RM) application methods of previous research completed by the United States Army Corps of Engineers (USACE) and Clemson University. That work focused on drinking water treatment systems and developed a few dozen specific indicators, or metrics, to quantify resilience. This research adds wastewater infrastructure with the aim of identifying …

Minimizing Uncovered Triples: An Integer Programming Approach To College Football Conference Scheduling, Caleb Mallett

Industrial Engineering Undergraduate Honors Theses

Collegiate football teams often compete in groups of 8-20 teams known as conferences. One such conference, the Atlantic Coastal Conference (ACC), added three new schools for the 2024-25 season, bringing their total to 17 teams. Currently, each ACC team plays eight games against others within the ACC. At the season’s conclusion, the two ACC teams with the best intraconference record compete in a conference championship game. With 17 total teams each playing eight games, the ACC could have a three-way tie for the best record where none of top the three teams play one another. To avoid this situation, we …

Developing 3d-Printed Packaging To Protect Biodegradable Sensors Used For Large-Scale, Efficient Water Quality Monitoring, Han L. Siew

Industrial Engineering Undergraduate Honors Theses

Freshwater degradation due to human activities costs the United States over $2.2 billion annually, highlighting the urgent need for improved water quality monitoring methods. Traditional water sampling techniques are labor-intensive, time-consuming, and reliant on single-use plastics that contribute to environmental pollution. This research aims to address these issues by developing 3D-printed biodegradable sensor packaging for unmanned aerial vehicle (UAV)-assisted water sampling. By utilizing biodegradable materials, the research seeks to create an eco-friendly solution that ensures sensor durability while reducing negative environmental impact. The study will involve adjusting the packaging design to withstand UAV deployment by testing and improving the resistance …

Tradespace Exploration With Statistical Modeling Techniques And Immersive Visual Representation In Virtual Environments, Nikhil Raj

All Theses

Statistical modeling techniques combined with virtual reality (VR) visualization offer powerful new approaches to tradespace exploration in engineering design. The research presented addresses the challenge of analyzing and communicating insights from complex multidimensional datasets, particularly for autonomous ground vehicle systems.

Beginning with a review of statistical methods—including Principal Component Analysis (PCA), Analysis of Variance (ANOVA), and correlation analysis—the study examines their applications in tradespace exploration. Building on this foundation, three distinct visualization pathways connecting MATLAB data to virtual environments are developed and evaluated: VRML representation, STL conversion, and Blender integration. Each approach is assessed for its ability to maintain data …

Survival Signature Estimation Using Optimization And Monte-Carlo Simulation For K ≥ 3 Classes Of Nodes On Two-Terminal Networks, Md Sazid Rahman

Graduate Theses and Dissertations

This research develops an efficient approach to estimating survival signatures for two-terminal networks with more than two classes of components. Recently, the survival signature has gained substantial attention in the literature on network reliability estimation due to its unique separability property, which enables passing the network topology information independent of the failure distribution of the components. Following recent results from the literature, estimating the two-terminal survival signature by Monte Carlo simulation entails solving a multi-objective maximum capacity path problem on a two-terminal network in each replication. We adapt a multi-objective Dijkstra’s algorithm from the literature to construct the set of …

Life Cycle Analysis Of Cosmetic Products -- Assessing Environmental Sustainability And Potential Impacts, Karina Magro Machado

Theses, Dissertations and Culminating Projects

The cosmetic industry has a significant environmental footprint due to its reliance on water, energy, petrochemical-derived ingredients, and plastic-based packaging. This study performs a cradle-to-grave Life Cycle Analysis (LCA) to evaluate the environmental impacts of three cosmetic products: CeraVe Daily Moisturizing Lotion, bareMinerals Gen Nude Powder Blush, and Gillette Foamy Regular Shave Cream. The analysis was conducted using OpenLCA software and free databases, modeling each product across raw materials, packaging, manufacturing, transportation, use and end-of-life phases. The results showed that the shave cream had the highest environmental burden to three out of the four categories, especially in consumption and carbon …

Decomposition And Coordination For Multiobjective Optimization: A Framework And Methodology, Philip J. De Castro

All Dissertations

In this work, we consider finding Pareto efficient solutions for complex multiobjective optimization problems (MOPs). Complex MOPs are unique in the literature because they have many more objective functions than is typically considered. In fact, such complex MOPs will have 30+ objective functions. This large problem size presents computational and coginitive difficulties. Computationally, standard techniques for solving MOPs are often ineffective and cognitively it is difficult for a decision maker (DM) to handle all of the information provided in such a large problem. To address these challenges, we develop a decomposition and coordination framework. This framework will allow us to …

Extending Simulation-Enhanced Bayesian Optimization Of System Designs: A Computational Study, Luke Kim

Data Science Undergraduate Honors Theses

This honors thesis builds off work initially accepted for publication in the Proceedings of the 2025 IISE Annual Conference & Expo, which introduced “Simulation-Enhanced Bayesian Optimization” (SEBO)—a hybrid testing optimization approach that combined the usage of unbiased but costly physical experiments with the usage of cheaper but potentially biased computer experiments to optimize engineered systems. The original study established the SEBO methodology and demonstrated its effectiveness on a multimodal, two-dimensional benchmark function. Expanding on the work performed, we conduct a broader evaluation of the SEBO framework through parameter testing and experimentation under a variety of additional benchmark functions. This investigation …

A Causal Model Of Performance Shaping Factors For Human Reliability Analysis In Manufacturing., Prameet Ranjan Jha

Electronic Theses and Dissertations

Human reliability analysis is a critical component of probabilistic risk assessment, aimed at predicting and mitigating human errors in complex systems. This dissertation develops a novel approach to human reliability analysis in manufacturing by integrating structural equation modeling and Bayesian networks to improve the estimation of human error probabilities. Traditional human reliability assessment methods, such as the Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) and the Technique for Human Error Rate Prediction (THERP), provide structured techniques for estimating human error probabilities. However, these methods often fail to capture the complex interdependencies among performance shaping factors (PSFs), limiting their applicability in …

Engineering Solutions For The Transplant Supply Gap: Social Network Analysis, Artificial Intelligence, And Optimization In Living Kidney Donation., Joshua Nielsen

Electronic Theses and Dissertations

Kidney transplantation is the gold standard for treating end-stage renal disease, yet over 90,000 patients remain on the transplant waitlist. This dissertation introduces engineering-driven solutions to help reduce the transplant supply gap by addressing three challenges: illicit trafficking, donor recruitment, and evaluation inefficiencies. First, we model illicit organ trafficking networks using social network analysis. We demonstrate that targeting transplant clinics alone is insufficient to disrupt operations. Instead, disrupting the network requires detaining brokers who organize behind-the-scenes logistics—offering a more effective strategy for intervention. Second, we seek to identify a latent population of potential living donors who face barriers such as …

A Digital Twin Approach To Job Shop Scheduling: Simulation And Optimization In Anylogic, Alan Alejandro Corral Lopez

Open Access Theses & Dissertations

In complex manufacturing environments such as job shops, machine breakdowns and maintenance activities can significantly disrupt production flow, leading to delays, bottlenecks, and reduced throughput. This thesis presents the development of a digital twin for a job shop system using AnyLogic simulation software to evaluate the effectiveness of fallback routing logic, where jobs are dynamically rerouted to alternative machines when primary machines are unavailable due to scheduled and unscheduled events. The digital twin replicates real-world job shop conditions, incorporating variable job sequences, machine-specific processing times, and both preventive and corrective maintenance schedules. Two scenarios were compared: a baseline configuration with …