Industrial Engineering Commons^™

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 …

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. …

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 …

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 …

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 …

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 …

Neural Architecture Search-Driven Unsupervised Domain Adaptation For Enhanced Wood Chip Quality Evaluation In Forest Industries, Abdur Rahman

Theses and Dissertations

Reliable and efficient measurement of wood chip moisture content is crucial for forest-reliant industries, including biofuel production, pulp and paper manufacturing, and bio-refineries, as it directly influences product quality and energy output. Traditional methods like the oven-drying technique, despite their widespread use, are time-consuming and impractical for real-time applications, while modern alternatives such as NIR spectroscopy, electrical capacitance, and microwave analysis are often costly, less portable, and require specialized expertise. This dissertation addresses these limitations by leveraging deep learning and machine vision to develop a scalable, accurate, and portable method for moisture content measurement using RGB images of wood chips. …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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. …

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 …

Developing An Early Life Cycle Manufacturability Assessment For Conceptual Designs, Tonya Gamblin Mccall

Theses and Dissertations

Studies have shown that 70 – 80% of a product's life cycle costs are committed by the end of the product design phase (Anderson, 2014; National Research Council, 1991; Swift, 1987). This supports the general claim that decision making in the conceptual stage drives the cost throughout the life cycle. The use of concurrent engineering has been viewed as the answer to this problem, offering the Design for Excellence (DFX) as one approach for evaluating product designs across specific disciplines. This research focuses on a subset of DFX referred to as Design for Manufacturability to develop a means to assess …

Human Gait Movement Analysis Using Wearable Solutions And Artificial Intelligence, Samaneh Davarzani

Theses and Dissertations

Gait recognition systems have gained tremendous attention due to its potential applications in healthcare, criminal investigation, sports biomechanics, and so forth. A new solution to gait recognition tasks can be provided by wearable sensors integrated in wearable objects or mobile devices. In this research a sock prototype designed with embedded soft robotic sensors (SRS) is implemented to measure foot ankle kinematic and kinetic data during three experiments designed to track participants’ feet ankle movement. Deep learning and statistical methods have been employed to model SRS data against Motion capture system (MoCap) to determine their ability to provide accurate kinematic and …

A Biomechanical Approach To Prevent Falls In Ergonomic Settings, Sachini Kodithuwakku Arachchige

Theses and Dissertations

Introduction: Fall-related injuries are exceptionally prevalent in occupational settings. While endangering the workers’ health, falls cause poor productivity and increased economic burden in the workplace. Hence, identifying these threats and training workers to achieve proper postural control is crucial. Purpose: Study 1: To investigate the ankle joint kinematics in unexpected and expected trip responses during single-tasking (ST), dual-tasking (DT), and triple-tasking (TT), before and after a physically fatiguing exercise. Study 2: To investigate the impact of virtual heights, DT, and training on static postural stability and cognitive processing. Methods: Study 1: Twenty collegiate volunteers (10 males and females, one left …

Assessing Readiness For Implementation Of Prognostics And Health Management In Small And Medium Enterprises, Sara C. Fuller

Theses and Dissertations

Prognostics and Health Management (PHM) refers to using robust sensing, monitoring, and control to detect, assess, and track system health degradation and failure modes, allowing for enhanced management and operational decisions. The need for PHM within a manufacturing facility has increased due to a variety of reasons, such as the increasing complexity of manufacturing equipment.

A lack of readiness for digital implementations is linked to failure. The literature highlights certain barriers and enablers that can signal whether a technology implementation will be successful, such as management and maintenance employees’ desire to change the existing process, an understanding and willingness to …

Developing Novel Optimization And Machine Learning Frameworks To Improve And Assess The Safety Of Workplaces, Amin Aghalari

Theses and Dissertations

This study proposes several decision-making tools utilizing optimization and machine learning frameworks to assess and improve the safety of the workplaces. The first chapter of this study presents a novel mathematical model to optimally locate a set of detectors to minimize the expected number of casualties in a given threat area. The problem is formulated as a nonlinear binary integer programming model and then solved as a linearized branch-and-bound algorithm. Several sensitivity analyses illustrate the model's robustness and draw key managerial insights. One of the prevailing threats in the last decades, Active Shooting (AS) violence, poses a serious threat to …

Bayesian Network Development For Depots Location Selection With Biomass Supply System Excellence, Alaa Ashraf Abulhamail

Theses and Dissertations

The renewable energy of the wood pellet market has taken great attention over the last few periods. However, the returns from the pellet business depend largely on how well the quality of biomass. The objective is to economically harvest pellets matching pellet standards set forward by the U.S. markets. The single-mindedness of this study is to develop a Bayesian network model to ensure a high-quality flow through the supply chain of the pallet industry in the top ten counties in Mississippi state. Multiple critical decisions (harvesting, storage, transportation, and quality control) of a biomass-to-pellet supply system could potentially affect the …

Modeling Multi-Criteria Decision-Making Problems With Applications In Last Mile Delivery And School Safety Assessment, Ayat Alrahahleh

Theses and Dissertations

The last-mile delivery option has become a focal point of academic research and industrial development in recent years. Multiple factors such as increased demands on delivery flexibility, customer requirements, delivery urgency, and many others are enforcing to adopt this option. For fulfilling this paradigm shift in delivery and providing additional flexibility, drones can be considered as a viable option to use for last-mile delivery cases. Numerous drones are available in the market with varying capacities and functionalities, posing a significant challenge for decision-makers to select the most appropriate drone type for a specific application. For this purpose, this study proposes …