Industrial Engineering Commons^™

Bridging Models And Real-World Performance: Capturing Represented, Hidden, And Unrepresented Dynamics In Complex Systems, Dixizi Liu

All Dissertations

Complex systems often depend on adaptive performance that is difficult to capture using structured data or formal models alone. This dissertation asks how predictive modeling, coordination-cost measurement, and simulation can be integrated to better represent the visible, hidden, and unrepresented dynamics that shape real-world system performance.

Sterile Processing Departments (SPDs) provide the empirical context for this work because they support safe and timely surgical care while operating under high workload variability, time pressure, and tight coordination with operating rooms. Hospitals rely on SPDs to clean, assemble, sterilize, and deliver surgical instrument trays so surgeries can start on time and proceed …

Human-Centered Design Of Extended Reality For Learning Adoption, Effectiveness, And Collaborative Training Performance, Bhargav Upadhyay

All Dissertations

Extended reality (XR) technologies like virtual reality (VR) and augmented reality (AR) can be used for technical training to help students learn and practice complex tasks in a safe digital environment. Despite known benefits evidence is required to explore the effectiveness of these technologies to support student learning outcomes. Furthermore, technical training programs need evidence about when these tools improve learning, what are the barriers to adoption of these technologies, and how training should be designed by leveraging these technologies. This dissertation examined how XR technologies can support higher education and workforce training, specifically focusing on barriers and facilitators to …

A Hybrid Machine Learning-Based Feasibility Prediction Of 3d Mechanical Designs Using Scalar And Geometric Features, Md Mohsin Uddin Fahim

Open Access Theses & Dissertations

The computational bottleneck of structural feasibility screening frequently hinders the transition from a digital 3D model to a physically manufactured component. Traditionally, engineers have relied on either overly rigid heuristic constraint checks or computationally exhaustive finite element simulations. To address this inefficiency, this thesis proposes and validates a hybrid machine-learning framework to predict the structural manufacturability of 3D mechanical designs. Moving beyond the conventional reliance on isolated scalar parameters, the proposed methodology extracts and integrates both scalar manufacturing constraints (e.g., tolerance, minimum feature thickness) and spatial geometric descriptors (e.g., bounding volume, aspect ratio) directly from STL mesh data. Utilizing a …

Prevention Vs Detection: A Discrete-Event Simulation Assessment Of Inspection Staffing, Pick-To-Light, And Ai-Based Inspection In Aerospace Wire Harness Kitting, Jorge Mares

Open Access Theses & Dissertations

Aerospace wire harness manufacturing operates under conditions that standard industrial engineering methods were not designed to address. Volumes are low, configurations change between orders, assembly is performed manually by certified labor that cannot be expanded quickly, and IPC/WHMA-A-620 Class 3 acceptance requires that every unit be verified rather than sampled. Kit assembly concentrates the resulting risk, because each item retrieved from the rack is an independent selection decision, and the attributes distinguishing a correct item from an incorrect one are frequently not visible to the operator. Errors introduced there are discovered downstream, after substantial certified labor has been invested. A …

A Causal Inference Protocol For Root-Cause Diagnosis In Non-Stationary Industrial Time Series, Cansu Yalim

Engineering Management & Systems Engineering Theses & Dissertations

Industrial fault diagnosis increasingly relies on data-driven methods, yet most approaches assume process stationarity and treat association-based rankings as sufficient evidence for root-cause identification. Neither assumption holds when operating phases and fault progression create distinct behavioral regimes with shifting relationships among variables, and neither answers which feasible corrective action would alter a fault trajectory. The absence of a procedure addressing non-stationarity, causal identifiability, and decision-relevant effect estimation constitutes the gap this dissertation targets. In this context, a regime is a time period in which the process operates under a relatively consistent setting, so the relationships among variables are approximately stable …

Leveraging Data Science And Analytics For Next-Generation Transportation And Logistics: Literature Review And Regional Analysis, Kazi Humayra Shams

Graduate Theses and Dissertations

The increasing integration of data science and analytics into next-generation transportation and logistics planning and operations offers improved system performance but requires managing and interpreting vast and complex datasets. The Arkansas Smart Transportation Research, Infrastructure and Data-Driven Engineering Systems (AR-STRIDES) program (NSF Award No. 2445877) is working to develop data science solutions and data-driven supply chain technologies for next-generation transportation and logistics systems. This thesis supports AR-STRIDES by providing a comprehensive literature review of recent literature studying data science and analytics in transportation and logistics systems and conducting a regional analysis of Arkansas to create a database of companies, higher …

Adopting Critical Power Grid Infrastructure Technologies: An Organizational Cybersecurity Assessment Against Ransomware, Fayez Alsoubaie

Dissertations and Theses

For many years, researchers and practitioners have studied emerging technologies in field of energy production and distribution. Power grid systems carry major weights in the energy branch of the economy. Researchers and scientists have been interested in finding ways to connect the power grid gap and improve protection for its technologies.

The research supports organizational adoption and prioritization of critical cybersecurity technologies for ransomware protection in power grid infrastructure. As utilities increasingly integrate digital technologies, they become more vulnerable to sophisticated cyberattacks that can disrupt services and put public safety at risk. The main focus of the study is to …

A Simulation-Based Lean Six Sigma Framework For Process Optimization In Textile Manufacturing Toward Industry 4.0, Md Shafiqul Islam Chowdhury

Masters Theses

This study focuses on integrating simulation modeling with Lean Six Sigma (LSS) within the DMAIC (Define, Measure, Analyze, Improve, Control) framework for process optimization in textile manufacturing industry. Although traditional LSS framework such as Value Stream Mapping (VSM) and Root Cause Analysis are effective in identifying waste, they mainly rely on static and historical data which make their capability limited for real analysis or predictive decision making. As a result, many textile manufacturing processes still face challenges such as production delays, excessive work-in-process (WIP), high cycle time, and inefficient resource utilization. To address this issue, this research proposes a simulation-based …

Material Costs, Karima Weinman

Masters Theses

This thesis investigates how migration fatality and disappearance data can be reinterpreted through material craft to create a more reflective encounter with information. Working with the Missing Migrants Project's dataset, this project asks how design can communicate dimensions of human loss that conventional data visualization cannot reach.

The work situates contemporary border violence within a longer colonial history, arguing that the logics of surveillance and quantification that structured European imperial expansion persist in the databases that govern mobility in the Mediterranean today.

Terrazzo is a 15th-century Venetian flooring technique built from discarded fragments bound together into a unified surface. This …

Improving And Supporting Flight Instructor’S Decisions For First Solo, Isabella Piasecki

Theses and Dissertations

Flight instructors have the burden of determining when a student is ready for their first solo flight, and many have expressed uncertainty over their own decision-making skills during this phase of a student’s training. Prior studies have examined flight instructors’ pre-solo decisions in other countries, but no such study has been conducted with American flight instructors. For this study, current flight instructors with multiple prior endorsements for a student pilot’s first solo were interviewed to identify the more abstract concepts they use to guide their decision. Qualitative themes were identified from their experiences. Using this information, a checklist was developed …

Feasibility-Aware Deep Reinforcement Learning For Sustainable Timber Procurement Under Hurricane Demand Uncertainty, Jarod Wright

Theses and Dissertations

The timber supply chain connects landowners and mills to provide wood products but faces challenges from stochastic demand, seasonal variations, and disruptions such as hurricanes. Fur- thermore, sustainability concerns like transportation emissions create trade-offs in procurement. This study proposes a feasibility-aware Deep Reinforcement Learning framework for sustainable timber procurement and inventory control under joint demand–hurricane uncertainty. We develop a stochastic mathematical model capturing mill-landowner interactions, seasonal demand, hurricane- driven pricing, and carbon emissions. The problem is formulated as a constrained Markov decision process and solved using Proximal Policy Optimization with a feasibility-enforcing layer. A Mississippi-based case study with 2,100 landowners …

Machine Learning-Based Decision Support Models With Applications In Postsecondary Education, Marco Paolo Anglesio

Theses and Dissertations

This dissertation investigates the deployment of machine learning methodologies in an industrial engineering framework for the development of advanced decision support systems in the context of enrollment management. Drawing on techniques from educational data mining, the research addresses three key phases in the lifecycle of traditional and non-traditional students. First, it analyzes student retention using predictive classification models designed to identify individuals at elevated risk of attrition. Second, it employs temporal convolutional networks for time series forecasting, estimating aggregate enrollment levels over highly variable, finite planning horizons on the basis of partially observed data and using an asymmetric loss function. …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

Process Optimization Of Directed Energy Deposition Via Dmaic Methodology And Lean Manufacturing Principles, Erick Gerardo Molina Castaneda

Open Access Theses & Dissertations

Additive Manufacturing (AM), particularly Direct Energy Deposition (DED), has gained increasing relevance in industrial and research environments due to its capability to manufacture complex geometries and repair high-value components. However, despite its technological advantages, DED processes often lack standardization, clear documentation, and structured workflows, especially in academic laboratories. This research aims to optimize and standardize DED processes through the application of Lean Manufacturing principles using the DMAIC (Define, Measure, Analyze, Improve, Control) methodology. The study was conducted at the Keck Center for 3D Innovation, focusing on pre-printing and printing activities. Key issues were identified. Improvement actions included the implementation of …

Project Management Practices In Manufacturing: An Analytical Case Study, Margaret Randle, Robert Reynolds

Honors Capstones

Global industries are undergoing significant transitions in organizational models, technological innovation, and non-economic indicators of product quality, including sustainability and operational efficiency. The current workforce needs to not only develop competency of these technical skills, but also an adaptive, system-oriented approach to problem-solving as well. This case study, which highlights a manufacturing company’s project of increasing production efficiency, presents concepts learned through the textbook Project Management: Achieving Competitive Advantage by Jeffrey K. Pinto. The study thoroughly breaks down the full project lifecycle and the integration of systems of people, data, and initiatives in a framework that can be used to …

Ergonomic And Material Flow Improvements For A Medical Device Assembly Line, Matthew Kobus

Honors Theses

This project evaluated material handling inefficiencies and ergonomic concerns within Stryker’s Neptune medical device assembly line. Two primary issues were identified: lack of a standardized part-location system in the supermarket and excessive operator travel between subassembly and main assembly. These issues resulted in search waste, motion waste, lost production time, and increased ergonomic strain.

To address the labeling issue, a standardized bin labeling system was developed and tested. A time study comparing labeled and unlabeled conditions showed that average retrieval time decreased from approximately 120 seconds to 22 seconds, an 81% reduction. Statistical analysis confirmed that this improvement was significant …

Harnessing Ml And Iiot For Traceability In Continuous Production Systems: A Conceptual Framework, Kholoud M. Abdelaal

Theses and Dissertations

In the era of rapid technological advancement, the manufacturing sector faces increasing pressure to leverage emerging technologies to enhance operational efficiency and minimize waste. In this context, traceability plays a pivotal role, as it provides complete visibility of processes and products throughout manufacturing systems, enabling them to identify areas for improvement and take corrective actions accordingly. Additionally, traceability ensures compliance, supports product recalls, provides a clear understanding of the system’s performance, and enables fact-driven decision-making in multiple aspects of the manufacturing system. Although the broad spectrum of traceability applications in batch production-based plants, traceability remains challenging to achieve in continuous …

Performance, Economic And Environmental Evaluation Of A Solar-Assisted Vacuum Deaeration Heating System., Liew Shan Kun

Student Works (2020-2029)

This research evaluates the performance of a solar-assisted heating (SAH) system for makeup water in a vacuum deaeration process. The system integrates solar energy into the heating process, with parametric analysis conducted across varying configuration of total solar radiation and water flow rates. The total solar radiation at the experimental site in Kuala Kangsar, Perak, Malaysia, characterized by tropical weather, fell within the range between 414W/m2 to 568W/m2. Performance analysis showed that a flow rate of 0.4 LPM achieved the target temperature of 61°C required for the deaeration process. Thermal efficiency peaked at 62.60% under a solar radiation of 900 …

Design Of Team Performance Evaluation Scenario Under Stress And Failures, Sam Tola

Open Access Master's Theses

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Development Of An Apparatus For Advanced Selective Laser Melting And Polishing Research, Joshua A. Fishbein

Open Access Master's Theses

Abstract contains Controlled Unclassified Information (CUI) and cannot be provided.

Simulation Optimization Of Intermodal Freight Transportation Under Disruptions, Israt Humayra

Graduate Theses, Dissertations, and Problem Reports (ETD)

Rapid growth in freight transportation in modern supply chains has led to increased operational costs, congestion, and severe environmental impacts, especially greenhouse gas emissions. Combining different modes, such as highway, railway, and waterway, intermodal transportation could thus offer considerable benefit to improve efficiency, sustainability, and resilience. However, most existing planning approaches rely on simplified assumptions, fixed schedules, and average cost estimates, making them less relevant to dealing with real-world uncertainties and disruptions. This study develops a simulation-optimization framework for intermodal freight transportation under disruption. We develop a mixed-integer programming model to represent an intermodal logistics planning framework on a multi-layered …

Ai-Based Porosity Detection In Babbitt Bore Turning, Kaylee Leggett, Hannah Adams Gemmell, Kaisa Shingleton

Williams Honors College, Honors Research Projects

For this project, an external company reached out to the University of Akron requesting assistance with defect detection during their vertical turning operations. As babbitt is removed in a vertical turning process, it occasionally reveals defects, mainly porosity, which can lead to costly downstream failures of the part. Current inspection techniques involve use of dye penetrant, which is time consuming, labor intensive, unergonomic, and a source of human error. The goal of the project is to create an alternative inspection method using an AI-based machine-learning model. After the turning operation, a camera is deployed to perform an in-place inspection, taking …