Industrial Engineering Commons^™

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. …

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 …

Optimizing Military Fighter Jet Selection: A Decision Analysis Approach For Nuclear-Capable Aircraft, Eni Kelechi Ofong

Theses and Dissertations

This research investigates the strategic decision-making process involved in selecting a nuclear-capable fighter aircraft for NATO (North Atlantic Treaty Organization) nations in Europe. In adaptation to the continuously changing technology landscape and the necessity for enhanced deterrence capabilities, this study evaluates three potential aircraft: the legacy Panavia Tornado (PA-200), the widely deployed F-16 Fighting Falcon (F-16), and the advanced F-35 Lightning II (F-35). Each platform presents distinct advantages and limitations regarding operational performance, mission adaptability, cost-effectiveness, and long-term sustainability. To systematically assess these alternatives, the study employs various decision analysis frameworks, including Multi-Criteria Decision Analysis (MCDA), single dimensional value function …

Lecun-Pso Hybrid Initialization Of Neural Network Using Asymmetric Gait Features For Classification Of Parkinson’S Disease, Michael Joseph Carter

Theses and Dissertations

Parkinson's disease (PD) is a complex condition with a wide range of clinical symptoms. It is a progressive neurological disorder that has afflicted an estimated 1 million people in the US and 10 million worldwide. The diagnosis of PD is typically based on the presence of clinical features, with no specific diagnostic test or biomarker. The methods of assessment for PD are also used, in whole or in part, for similar symptom diseases such as Multiple Sclerosis, Essential Tremors, Multiple System Atrophy, Supranuclear Palsy, Dementia with Lewy bodies and Huntington’s disease. Many of the current clinical tests have low sensitivity …

Exploring The Impact Of Incorporating Artificial Intelligence Integrated Systems In The Workplace, Catherine Cruz Agosto Noda

Theses and Dissertations

This study focuses on assessing the impact of incorporating systems integrated with in the workplace by assessing the constructs of usability, cognitive load, and trust. The constructs are assessed by generation and experience level to determine which factors are relevant in a workplace setting. A workplace scenario was simulated by asking participants to complete tasks where they assumed the role of a warehouse manager assigned with assessing two scheduling systems – one with artificial intelligence and one without artificial intelligence. The participants were presented with three tasks of increasing difficulty for each prototype. Both quantitative and qualitative measures were used …

Transforming Movement Assessment In Physical Therapy Through Subaquatic Data Collection, Kaitlyn Mcdonald

Theses and Dissertations

This study explored the interest and perceived barriers to integrating subaquatic diagnostic technologies (SDTs) into hydrotherapy among licensed physical therapists. Seventeen semi-structured interviews were conducted using a mixed-methods design, with 15 interviews included in the final analysis. Quantitative data were analyzed using chi-square tests, while qualitative responses were coded thematically. Results indicated no statistically significant relationships between SDT interest and career stage or hydrotherapy access, though qualitative data highlighted concerns about cost, limited access, and usability. Despite mixed interest in adoption, participants identified several potential benefits of SDTs, including improved treatment tailoring, increased patient buy-in, and enhanced outcome monitoring. Functional …

Low-Dimensional Learning For Remaining Useful Life Prediction Of Batteries Operating Under Various Environments, Rodrigo Benavides

Theses and Dissertations

In reliability, we typically define the standard operating conditions under which a component operates. However, the differences in battery operating conditions cause variability in the degradation patterns of identically manufactured batteries, rendering remaining useful life prediction a major challenge. To aid this task, several sensors are utilized to monitor battery state-of-health. However, traditional prognostics algorithms do not scale well to the volume of data generated. Furthermore, several authors do not explicitly consider operating environments in their prediction models. Therefore, we present a high-dimensional data analytics framework that integrates operating environment information for battery prognostics. This framework combines Multilinear Principal Component …

Investigation Of The Effect Of Material Density And Particle Size On Mixed Powder Spreading Behavior In Powder Bed Fusion Process, Alfred Kofi Apianing Achenie

Theses and Dissertations

Powder spreading marks a crucial step in the Laser powder bed fusion process, directly impacting the powder bed uniformity and paving the way for subsequent stages in the process. The laser powder bed fusion process depends heavily on the composition of the metallic powder feedstock. While most existing studies focus on pre-alloyed powders, limited work has explored the use of elemental powder blends as feedstock as used in in-situ alloying. Pre-alloyed powders are often costly, exhibit irregular morphologies and offer limited flexibility in material selection. This study uses Discrete Element Method (DEM) simulations to investigate how variations in material density …

An In Depth Examination Of Educational, Family, Economic, And Personal Determinants On Academic Performance, Engagement, And Stress: A Comprehensive Study Among Engineering Students, Oumaima Larif

Theses and Dissertations

This study explores the effects of family, education, economic, and personal factors on students’ decisions to pursue engineering as a profession and their long-term impact on performance as engineering students. We adopted a mixed-method approach, collecting data through surveys administered to undergraduate and graduate engineering students at Mississippi State University. The study results revealed that family, education, economic, and personal factors profoundly influence students' decisions to study engineering. We found that parental expectations, background information, and socioeconomic status, in conjunction with cultural norms, values, gender expectations, and religious beliefs, affect students. Additionally, this study identified gaps in the existing literature …

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 …

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 …

An Analysis Of Hardware Modification Cost: A Test Of A 1:1 Ratio Heuristic, Oluwasegun Faleye

Theses and Dissertations

Accurate cost estimation for Department of Defense (DoD) hardware modification programs remains a critical challenge due to the complexity of Group A and Group B modifications and their associated installation costs. This study evaluates the validity of a 1:1 ratio heuristic, which suggests that Group A modification kits combined with installation costs should equate to the costs of Group B modification kits. This study analyzes cost relationships across system types and modification categories using a dataset of 255 modification programs from the Air Force Life Cycle Management Center (AFLCMC). Statistical methods, including means tables and regression modeling, evaluate the validity …

Incorporating Sustainability In Facility Layout Planning Algorithms And Assessing Hybridization Techniques On An Egyptian Case Study, Islam Atia

Theses and Dissertations

Due to the growing consequences faced as a result of global warming and climate change; humanity has come together to take an inclusive stance to combat this serious phenomena and work towards a more sustainable future. Large amounts of carbon dioxide emissions are a major contributor to global warming, and a vast proportion of this emission come from industrial and commercial facilities. Hence, if industrial facilities are built with a larger focus on carbon footprint, it will yield a significant reduction in global emissions throughout the lifetime of the facility and will constitute a huge milestone in the journey to …

Enhanced Intellectual Property Protection Mechanisms Towards Collaborative Data Sharing In Metal-Based Additive Manufacturing, Durant Hayes Fullington

Theses and Dissertations

This dissertation aims to develop effective methodologies towards enhanced intellectual property protections for data sharing frameworks in metal-based additive manufacturing (AM). Currently, many small-to-medium sized manufacturers face data availability challenges due to the prohibitive high cost to collect, process, and analyze large amounts of process-related data for AM. Because these manufactures rely heavily on small-scale data, it can be difficult for them to effectively train complex machine learning (ML) algorithms, which are commonly used for AM process monitoring. One popular solution is to develop collaborative data sharing frameworks, where multiple independent AM users can share their data to increase the …

On Topological Measures And Network Vulnerability Patterns: A Review And Comparative Analysis, Saviz Saei

Theses and Dissertations

Despite much hope for climate change to slow down or even reverse, younger generations face a future overshadowed by extreme events. The indisputable reality is that unless the United Nations establishes comprehensive and sustained climate justice policies, children today will experience five times more extreme events than those that took place a century ago. On Monday, July 3rd of 2023, an unprecedented peak in global temperatures was documented, marking the highest global temperature ever recorded, as the U.S. National Centers for Environmental Prediction reported. These increasing temperatures indicate the ongoing and intensifying phenomenon of climate change, which amplifies the frequency …

Rsm For The Optimization Of Selective Laser Melting Process Parameters For Manufacturing Initial Layers Of Horizontal Overhang Structures, Prince Yaw Asamani

Theses and Dissertations

While prevalent in 3D printed objects, overhang features are difficult to print with selective laser melting due to the limitation of a purely vertical laser. To address this issue, overhang features are typically built on temporary supports, which are removed following printing. However, this results in wasted material and longer production time. Several authors have studied printing overhangs without support structures. However, there has not been a systematic approach to studying the effect of multiple process parameters on the quality of a printed overhang. This thesis investigates the effect of laser power, scanning speed, and hatch distance on the surface …

A Dedicated Lane Analysis For Supply Chain Resilience In The U.S.-Mexico Border: Cost-Comparison And Simulation Models, Carlo A. Zorola Gonzalez

Theses and Dissertations

Supply chains have been actively developing and implementing strategies to enhance resilience in response to various disruptive events like the COVID-19 pandemic, hurricanes, geopolitical tensions, and climate change. These strategies aim to address demand and supply imbalances, logistical challenges, and policy restrictions encountered in transborder commerce. One area significantly impacted by such disruptions is cross-border trade between the US and Mexico. Understanding these strategies is crucial for achieving supply chain resilience, defined as the ability of a supply chain to quickly adapt to sudden disruptions without affecting the flow of goods. In both the US-Mexico and US-Canada borders …

Automated Image Registration For Titanium Aircraft Components Via Resolution-Robust Parallel Neural Networks, Paige T. Luebbering

Theses and Dissertations

Titanium alloys are vital to the structural integrity of military and commercial aircraft, comprising numerous critical components. These components are composed of microtexture regions (MTRs) that, at a specific size and orientation, can lead to aircraft failure. Existing MTR testing methods, such as Electron Backscatter Diffraction, often fall short in effectively detecting these MTRs without causing damage to the component. Addressing this gap, this thesis develops a Parallel Convolutional Neural Network (CNN) model tailored for multi-resolution image registration of Polarized Light Microscopy (PLM) images to enhance MTR identification in a non-invasive manner. The findings reveal a significant enhancement in the …

Assessing Adoption Barriers Of Sustainable Packaging In Egypt, Carol Ramses Morgan

Theses and Dissertations

Sustainable packaging has become an essential part of business decisions and corporate directions. With the rise of environmental damages due to improper waste management and unsustainable practices, businesses have a major responsibility to analyze their products’ life cycles and redesign them with sustainability in mind. Applying sustainable packaging could save companies large amounts of resources, therefore cutting costs, while also achieving the legal and social duty as a corporation towards society and the environment. Many developing countries, with specific focus on Egypt, have recently focused on legislative and corporate decisions in order to encourage more sustainable practices. Egypt’s new Waste …

Gaze Tracking Embedded Collaborative Robots For Automated Metrology And Reverse Engineering, Sachithra H. Karunathilake

Theses and Dissertations

Conventional geometric metrology, or three-dimensional (3D) scanning, and reverse engineering heavily rely on the experience of the operators. With an increasing need for automation, robot arms have been adopted for this task. However, due to the large variety of parts and designs, automated path planning could provide a scanning solution that may overlook the critical area, which could potentially deteriorate the scan results. This study explores the integration of collaborative robotics (cobots) with eye tracking technology to improve the autonomous 3D scanning process. The primary objective of this study is to enhance the accuracy and efficiency of cobots in …

Assessing And Predicting The Students’ Systems Thinking Preference: Multi-Criteria Decision Making And Machine Learning, Siham Tazzit

Theses and Dissertations

The 21st century is marked by a technological revolution that features digital implementation and high interconnectivity between systems across different domains, such as transportation, agriculture, education, and health. Although these technological changes resulted in modern systems capable of easing individuals’ lives, these systems are increasingly complex, and that increased complexity is only expected to continue. The increased system complexity is due to the rapid exchange of information between subsystems, which creates high interconnectivity and interdependence between the subsystems and their elements. Workforce skill sets, as a result, must be modified appropriately to ensure the systems’ success. Systems Thinking is an …

Ruggedness Test Of A New Standardized Test Method For Abrasion Resistance Of E-Textiles, Erin Parker

Theses and Dissertations

Standard test methods provide product developers with information regarding materials' suitability for different purposes. Typically, current standards are suitable for determining the mechanical properties of new materials. However, in the case of electronic textiles (E-Textiles) and wearable technology (wearables), adding conductive components with added functionality makes utilizing textile standards difficult, and these standards will not provide information on mechanical and electrical properties of conductive elements. New standards for E-Textile and wearables testing are needed to ensure product developers can obtain the information necessary to make informed decisions about new products. Standards organizations such as the American Society for Testing and …

Ai Methods For Identifying Process Defects In Advanced Manufacturing With Rare Labeled Data, Ayantha Umesh Senanayaka Mudiyanselage

Theses and Dissertations

This dissertation aims to provide efficient process defect identification methods for advanced manufacturing environments using AI tools/algorithms with limited labeled data availability. Asset and equipment quality become highly sensitive in sustaining virtuous performance and safety in various manufacturing domains. Internally generated process imperfections degrade finished products' optimum performance and mechanical attributes. The evolution of big data and intelligent sensing systems leverage data-driven defect identification in advanced manufacturing environments. Widely adopted data-driven process anomaly detection methods assume that the training (source) and testing (target) data follow the same distribution and that labeled data are available in both source and target domains. …

Distributionally Robust Unsupervised Domain Adaptation And Its Applications In 2d And 3d Image Analysis, Yibin Wang

Theses and Dissertations

Obtaining ground-truth label information from real-world data along with uncertainty quantification can be challenging or even infeasible. In the absence of labeled data for a certain task, unsupervised domain adaptation (UDA) techniques have shown great accomplishment by learning transferable knowledge from labeled source domain data and adapting it to unlabeled target domain data, yet uncertainties are still a big concern under domain shifts. Distributionally robust learning (DRL) is emerging as a high-potential technique for building reliable learning systems that are robust to distribution shifts. In this research, a distributionally robust unsupervised domain adaptation (DRUDA) method is proposed to enhance the …

Ai-Enabled Modeling And Monitoring Of Data-Rich Advanced Manufacturing Systems, Abdullah Al Mamun

Theses and Dissertations

The infrastructure of cyber-physical systems (CPS) is based on a meta-concept of cybermanufacturing systems (CMS) that synchronizes the Industrial Internet of Things (IIoTs), Cloud Computing, Industrial Control Systems (ICSs), and Big Data analytics in manufacturing operations. Artificial Intelligence (AI) can be incorporated to make intelligent decisions in the day-to-day operations of CMS. Cyberattack spaces in AI-based cybermanufacturing operations pose significant challenges, including unauthorized modification of systems, loss of historical data, destructive malware, software malfunctioning, etc. However, a cybersecurity framework can be implemented to prevent unauthorized access, theft, damage, or other harmful attacks on electronic equipment, networks, and sensitive data. The …

Passive Vs. Active Wearable Technology Monitoring Trunk Flexion In Elementary Teachers, Bailey Jose

Theses and Dissertations

The objective of this study was to assess the biomechanical and subjective measures of elementary school teachers while wearing active and/or passive wearable devices during the average workday. Five elementary school teachers wore a harness that held an Upright GO 2 posture tracking device and a Vicon Blue Trident sensor on the participant's upper back for two school days. Haptic feedback was on for one day and off for the other. Data from the Vicon wearable was analyzed to determine participants’ trunk flexion severity, frequency, and duration. Surveys were used to determine perceived exertion and perception of wearable technology. This …

A Generalizable Method And Case Application For Development And Use Of The Aviation Systems – Trust Survey (As-Ts)., Jamison Hicks

Theses and Dissertations

Automated systems are integral in the development of modern aircraft, especially for complex military aircraft. Pilot Trust in Automation (TIA) in these systems is vital for optimizing the pilot-vehicle interface and ensuring pilots use the systems appropriately to complete required tasks.

The objective of this research was to develop and validate a TIA scale and survey methodology to identify and mitigate trust deficiencies with automated systems for use in Army Aviation testing. There is currently no standard TIA assessment methodology for U.S. Army aviation pilots that identifies trust deficiencies and potential mitigations.

A comprehensive literature review was conducted to identify …

Developing Systems Engineering And Machine Learning Frameworks For The Improvement Of Aviation Maintenance, Fatine Elakramine

Theses and Dissertations

This dissertation develops systems engineering and machine learning models for aviation maintenance support. With the constant increase in demand for air travel, aviation organizations compete to maintain airworthy aircraft to ensure the safety of passengers. Given the importance of aircraft safety, the aviation sector constantly needs technologies to enhance the maintenance experience, ensure system safety, and limit aircraft downtime. Based on the current literature, the aviation maintenance sector still relies on outdated technologies to maintain aircraft maintenance documentation, including paper-based technical orders. Aviation maintenance documentation contains a mixture of structured and unstructured technical text, mainly inputted by operators, making them …