Engineering Commons^™

Quantifying Lock Criticality For Inland Waterway Navigation Using An Agent-Based Simulation, Ashwin Narayan

Industrial Engineering Undergraduate Honors Theses

Inland waterway travel has tremendous potential to improve multimodal transportation in the United States due to its environment-friendly and safe nature. Waterway travel has proven to be much cheaper per ton-mile and more fuel efficient than trucks. Millions of dollars have recently been invested in inland waterway networks to facilitate travel. The waterway infrastructure must be resilient to enable efficient waterway travel and prevent unnecessary delays. Locks, an important component of waterway infrastructure, enable vessels to travel between waterways of varying depths and must be maintained consistently to avoid unexpected failures. However, with limited resources, it is difficult to preserve …

Great South Metals: Slitter Head Building Process, Nabhan Karim, Evan Swierski, Raven Morin, Patrick Kelsey, Michael Williams

Senior Design Project For Engineers

Great South Metals (GSM) operates two steel slitter machines, which take large coils of flat rolled steel and cut them into smaller strips for use in customers’ applications. Setting up the working components of each machine, called the slitter head, is a precise and arduous task. This system relies on several manually performed calculations and acute attention to detail; and thus, is prone to human error. The management at GSM commissioned our team to simplify the slitter head assembly process by creating an automated computer program and make additional recommendations to improve their operations.

The program we created is a …

Using Convolutional Neural Networks For Autonomous Drone Navigation, Joshua Jowers

Industrial Engineering Undergraduate Honors Theses

Unmanned Aerial Vehicles (UAVs), more commonly known as drones, serve various purposes, notably in military applications. Consequently, there arises a need for navigation methods impervious to intercepted signals [1]. Previous research has explored numerous solutions, including machine learning. This paper delves into a specific machine learning approach employing a Convolutional Neural Network (CNN) to discern image locations [2]. It elucidates the conversion of a CNN model between two machine learning libraries and presents results from multiple experiments examining parameters and factors influencing the approach's efficacy. These experiments encompass testing different data sources, image quantities, and processing pipelines to gauge their …

Open-Source Optimization For Green Last Mile Delivery And Other Applications, John Sooter

Industrial Engineering Undergraduate Honors Theses

Solving combinatorial optimization problems at scale and of sufficiently interesting context has historically required commercial solvers and access to proprietary company data. The development of performant open-source mathematical programming software and crowdsourced datasets has created an opportunity for individuals and enterprises alike to consider alternative solutions to problems with social and personal implications. This honors thesis represents a summary of my undergraduate research work, an application of optimization to three distinct problems connected to these developments. First, we present an optimization study of a last mile delivery system that shows optimization for energy consumption can generate vehicleindependent fuel savings at …

Comparing North American Professional Sports League Season Formats Using Monte Carlo Simulation, Lathan Gregg

Industrial Engineering Undergraduate Honors Theses

Each NFL, NBA, and MLB season consists of a regular season, in which teams play a set number of scheduled games and a playoff, in which qualifying teams compete for a championship. At the conclusion of each season, teams are ranked based on their performance throughout the season. This study aims to investigate the ability of each league's season format to accurately rank teams using Monte Carlo simulation. Matches between two teams are simulated by using the team’s assigned strength ranks to calculate a winning probability for each team. The winning probabilities are simulated with different skill values, dictating how …

Sequential Optimization For Stressor-Informed Test Planning Through Integration Of Experimental And Simulated Data, Jacob Brecheisen

Data Science Undergraduate Honors Theses

This technical report details an innovative approach in reliability engineering aimed at maximizing system durability through a synergistic use of physical experimentation and computer-based modeling. Our methodology explores the efficient design and analysis of computer experiments and physical tests to facilitate accelerated reliability growth, while leveraging a sequential integration of data from these two distinct sources: costly physical experiments, characterized by random errors, and inexpensive computer simulations, marked by inherent systematic errors. The key innovation lies in the adoption of a closed-loop design and analysis method. This method begins by identifying a viable subset of important environmental stressors—such as temperature, …

Depression And Anxiety: Investigating The Impacts Of Scheduling On The Mental Health Of Healthcare Workers During The Covid-19 Pandemic, Christofer Gonzaga

All Theses

Depression is a growing problem in the United States and has ballooned into a globally recognized mental health issue that affects shift workers in various fields (Lee et al., 2017). Rates of depression and anxiety have been shown to be substantially increasing and the COVID-19 pandemic amplified this prevalence of depression and anxiety. In the United States, the prevalence of depression symptoms was more than 3- fold higher during COVID-19 compared to before the pandemic (Ettman et al., 2020). The delivery of healthcare services is an ongoing and dynamic process, requiring clinicians to work in various shifts to ensure the …

Modeling Of Multi-Period Disaster Logistics Planning In The State Of South Carolina, Emma Simon

All Theses

South Carolina is one of the most vulnerable states in the United States to the impact of hurricanes. Currently, when threatened with a natural disaster such as a hurricane, the state government makes many vital decisions based on knowledge and experience. In this study, the distribution of disaster relief commodities to meet immediate needs is analyzed through two models for the case of South Carolina to generate an optimal logistics strategy that considers the social vulnerability of affected populations. The first model is a multi-objective pre-disaster logistics model that uses a four-index formulation for the multiple trip vehicle routing problem. …

Mathematical Modeling For Dental Decay Prevention In Children And Adolescents, Mahdiyeh Soltaninejad

Dissertations

The high prevalence of dental caries among children and adolescents, especially those from lower socio-economic backgrounds, is a significant nationwide health concern. Early prevention, such as dental sealants and fluoride varnish (FV), is essential, but access to this care remains limited and disparate. In this research, a national dataset is utilized to assess sealants' reach and effectiveness in preventing tooth decay, particularly focusing on 2nd molars that emerge during early adolescence, a current gap in the knowledge base. FV is recommended to be delivered during medical well-child visits to children who are not seeing a dentist. Challenges and facilitators in …

Optimization Of Human Interactions In The College Campus Model Via Simio Integration, Benjamin E. Chaback

Doctoral Dissertations and Master's Theses

College campuses are a significant part of life in some cities. Many students each year attend university, pursuing additional knowledge from faculty members. Both staff and faculty members rely on these students to have successful jobs and to ensure the university functions. Yet recently, more and more students are attending, leading to overcrowding, lower admission rates, and difficulty getting into good programs. Previous work exists on qualitative student affairs and quantitative retention data, yet little on using simulations to model this problem. This work aimed to (a) Determine the ability to successfully model human interactions/people flow on a college campus, …

Drivers’ Hazard Avoidance During Vehicle Automation: Impact Of Mental Models And Implications For Training, Ganesh Pai Mangalore

Doctoral Dissertations

Advanced Driver Assistance Systems (ADAS) are vehicle automation systems that have become more accessible and prevalent in vehicles in recent years. But the introduction of such technologies introduces new human factors challenges. Past literature suggests that users of vehicle automation lack the necessary and appropriate knowledge about their automation system. This may play a negative role in their hazard avoidance abilities when driving with automation features. Improving mental models and knowledge could generally lead to safer interactions with vehicle automation systems, but any effort to develop hazard avoidance skills when driving with vehicle automation is impeded by the lack of …

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 …

Containerization Of Seafarers In The International Shipping Industry: Contemporary Seamanship, Maritime Social Infrastructures, And Mobility Politics Of Global Logistics, Liang Wu

Dissertations, Theses, and Capstone Projects

This dissertation discusses the mobility politics of container shipping and argues that technological development, political-economic order, and social infrastructure co-produce one another. Containerization, the use of standardized containers to carry cargo across modes of transportation that is said to have revolutionized and globalized international trade since the late 1950s, has served to expand and extend the power of international coalitions of states and corporations to control the movements of commodities (shipments) and labor (seafarers). The advent and development of containerization was driven by a sociotechnical imaginary and international social contract of seamless shipping and cargo flows. In practice, this liberal, …

Development Of A High-Level Discrete Event Simulation Model For The Harvesting Of White Button Mushrooms With Human-Robot Collaboration (Hrc), Ava Recchia

Electronic Theses and Dissertations

Canada is a leading global mushroom producer, with the white button mushroom (Agaricus bisporus) being the most popular type produced. Harvesting activities are labour-intensive, and farms are currently experiencing labour shortages, which are impacting productivity, growth, and overall revenue. Robotic technologies are valid mechanisms for mushroom harvesting and demonstrate a potential to reduce this gap. Examining the performance of a harvesting system with different robotics scenarios, such as manual, robotics automation, and human robot collaboration (HRC) is crucial to realizing this potential. Simulation models are useful tools for testing and assessing systems without making any physical change to the system. …

Applying Functional Data Analysis To Estimate The Mental Workload Of The Human Driver, David Olorunfemi Eniyandunmo

Electronic Theses and Dissertations

Recent studies have focused on accurately estimating mental workload using machine learning algorithms and extracting features from psycho-physiological measures. However, feature extraction leads to the loss of valuable information and often results in binary classifications that lack specificity in the identification of optimum mental workload levels. This study investigates the feasibility of using raw psycho-physiological data (EEG, facial EMG, ECG, EDA, pupillometry) combined with Functional Data Analysis (FDA) to estimate mental workload of human drivers. A driving scenario with five tasks was employed, and subjective ratings were collected using the modified Bedford workload scale. Results demonstrate that the FDA applied …

Data-Driven Approaches For Achieving Carbon Neutrality: Predictive Models For Reducing Co2 Emissions And Enhancing Industrial Sustainability, Farzana Islam

Graduate Theses, Dissertations, and Problem Reports

In response to the escalating challenges posed by climate change and industrial inefficiency, this thesis presents a comprehensive investigation aimed at advancing the predictive modeling of global CO2 emissions and enhancing operational efficiency in steel manufacturing through Electric Arc Furnace (EAF) temperature optimization. Leveraging a rich dataset sourced from the World Development Indicators database alongside a meticulously curated dataset specific to EAF operations, our study applies an innovative blend of econometric and machine learning techniques, including Pooled Ordinary Least Squares (Pooled OLS), Random Effects (RE), Fixed Effects (FE), and Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) models. The …

Milk Collection Problem: Integrating The Traveling Salesman And Set Covering Problem - A Case Study In West Virginia, Usa, Md Rabiul Hasan

Graduate Theses, Dissertations, and Problem Reports

Route determination for perishable products is complex due to its unique characteristics, such as limited shelf-life regulatory requirements, or possibility of getting damaged. This research investigates a novel problem of collecting raw milk from a rural network of dairy farms. The research problem is grounded in a real scenario of milk collection in West Virginia, USA. The milk in this scenario is produced by small farms incapable of realizing transportation economies of density out in mostly rural areas throughout the state. Maximum coverage area and milk processing overhead costs are used to identify suitable locations for intermediate milk collection centers …

Prediction Of Anomalous Events With Data Augmentation And Hybrid Deep Learning Approach, Ahmed Shoyeb Raihan

Graduate Theses, Dissertations, and Problem Reports

In this study, we propose a novel anomaly detection framework designed specifically for Multivariate Time Series (MTS) data, addressing the prevalent challenges in analyzing such complex datasets. The detection of anomalies within MTS data is notably difficult due to the complex interplay of numerous variables, temporal dependencies, and the common issue of class imbalance, where one category significantly outnumbers another. Traditional deep learning (DL) approaches often fall short in simultaneously tackling these issues. Our framework is designed to address these challenges through a two-phased approach. Phase I employs Conditional Tabular Generative Adversarial Networks (CTGAN) to create strategic synthetic data, setting …

The Effects Of Blue Light From Digital Displays On Visual Fatigue, Victor Taboadela

Theses

With the ever-increasing viewing time of digital displays, the potential effects of blue light emitted from these displays on eye health and eye fatigue are a real concern. This study presents a literature review of six laboratory studies conducted between 2014 and 2022 on the effect of using filters to attenuate the harmful effects of blue light. The review delves into smartphone and computer screen effects, recent literature reviews on blue light, and potential hazards associated with short-wavelength light. Although the majority of the studies recommended blue light filters, only three of the six laboratory studies (Shi et al. 2021, …

Imerys: Tube Mill Optimization Project, Ryan Waltman, Dalton Beasley, Dyson Beasley, Tristan Mcmichael

Senior Design Project For Engineers

The Tube Mill Optimization Project is in partnership with Imerys for Tube Mill 81 at their Marble Hill site in Georgia. Tube Mill 81 is a dry ball mill that operates 24/7 and makes an intermediary product for Plant 3. Tube Mill 81 needs quality improvement and a production rate increase to meet demand. Imerys’s quality specification is between a particle size of 12-18 microns and an acceptable production rate of 5 tons per hour. This project focuses on the development and implementation of three solutions: increase the amps on the separator to increase production, replace missing classifier blades in …

Optimal Route Planning Using Computer Simulation In The Context Of Distributor-To-Consumer Supply Network, Miriam Aguilera Nava

Open Access Theses & Dissertations

Effective route planning for distribution centers is a multifaceted challenge crucial tobusiness success, as it directly impacts time and cost savings while enhancing overall delivery efficiency. Oversight of proper planning can lead to problems and inefficiencies in the distribution process. Hence, this work undertakes a comparative experiment of two delivery strategies in a distributor-to-consumer supply network. While the first strategy investigates the delivery process by zip area, the second strategy considers the clustering of the areas for more streamlined delivery fulfillment. The effectiveness of the delivery process is gauged based on a set of metrics, including total distance traveled, average …

Reliability Modeling And Improvement Of Critical Infrastructures: Theory, Simulation, And Computational Methods, José Carlos Hernández Azucena

Graduate Theses and Dissertations

This dissertation presents a framework for developing data-driven tools to model and improve the performance of Interconnected Critical Infrastructures (ICIs) in multiple contexts. The importance of ICIs for daily human activities and the large volumes of data in continuous generation in modern industries grant relevance to research efforts in this direction. Chapter 2 focuses on the impact of disruptions in Multimodal Transportation Networks, which I explored from an application perspective. The outlined research directions propose exploring the combination of simulation for decision-making with data-driven optimization paradigms to create tools that may provide stakeholders with optimal policies for a wide array …

Simulation Analysis Of The Distrix Protocol For Political Redistricting, Cui Fu

Theses and Dissertations

This thesis explores the process of political redistricting, a crucial component of ensuring fair representation in legislative bodies. The study first outlines the background and criteria of redistricting in the United States, emphasizing important criteria such as equal population, racial fairness, contiguity, and political fairness. It then focuses on the Distrix protocol for political redistricting in which two or more players (i.e., political parties) take turns assigning small pieces of territory to districts until no more unassigned territory remains. The Distrix protocol was recently introduced in a board game of the same name. After describing the Distrix protocol, we present …

Utilization Of Integer Programming For Scheduling Maintenance At Nuclear Power Plants, Timothy Gallacher

Doctoral Dissertations

This thesis develops a thought that naturally explores three specific motifs for solving the complexities of scheduling maintenance at Nuclear Power Plants (NPP). The first chapter of this paper will develop the initial thought around creating a schedule for a given work week, including all the various constraints inherent to this problem. Such constraints include but are not limited to personnel availability, allowable component out-of-service time, and the Plant Risk Assessment. The objective function being to minimize the total cost of worker’s compensation for that given week.

The second chapter addresses the question of whether this simple schedule can be …

Exact Models, Heuristics, And Supervised Learning Approaches For Vehicle Routing Problems, Zefeng Lyu

Doctoral Dissertations

This dissertation presents contributions to the field of vehicle routing problems by utilizing exact methods, heuristic approaches, and the integration of machine learning with traditional algorithms. The research is organized into three main chapters, each dedicated to a specific routing problem and a unique methodology. The first chapter addresses the Pickup and Delivery Problem with Transshipments and Time Windows, a variant that permits product transfers between vehicles to enhance logistics flexibility and reduce costs. To solve this problem, we propose an efficient mixed-integer linear programming model that has been shown to outperform existing ones. The second chapter discusses a practical …

A Multi-Objective Stochastic Programming Model For Resilient And Sustainable Supply Chains Under Uncertainty, Mohammad H. Majdfaghihi

Dissertations

Supply chain resilience (SCRES) and sustainable supply chain management (SSCM) have garnered significant attention in the field of Supply Chain Management (SCM) science. This heightened interest is largely attributable to the increasing frequency and severity of uncertainty and disruptions in global supply chains. Resilience is a beneficial approach to managing uncertainties and preparing for and mitigating the adverse consequences of Supply Chain (SC) disruptions. Sustainability is a key concept in SCM, driven by governmental regulations and heightened stakeholder and customer concerns for environmental and societal well-being. Studies on SCRES have traditionally focused on preparing for and reacting to disruptions and …

Automated Usability Evaluation Utilizing Log Files And Data Mining Techniques., Sima Shafaei

Electronic Theses and Dissertations

Usability evaluation is one of the essential aspects of software production. This evaluation should be done during the entire life cycle of a software application, from pre-production to production and post-production. However, the collection and evaluation of usability data can be a very challenging, time-consuming, and expensive task to be conducted manually, particularly for certain types of products and working conditions. These challenges may include the need to recruit participants fully engage and motivate them during evaluation, and factor in environmental conditions. Other challenges may include collecting data in real-world environments, especially when the users are geographically dispersed, minimizing evaluator …

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 …

Mining High Impact Combinations Of Conditions From The Medical Expenditure Panel Survey, Arjun Mohan

Masters Theses

The condition of multimorbidity — the presence of two or more medical conditions in an individual — is a growing phenomenon worldwide. In the United States, multimorbid patients represent more than a third of the population and the trend is steadily increasing in an already aging population. There is thus a pressing need to understand the patterns in which multimorbidity occurs, and to better understand the nature of the care that is required to be provided to such patients.

In this thesis, we use data from the Medical Expenditure Panel Survey (MEPS) from the years 2011 to 2015 to identify …

Multichannel Low-Cost Sensor For Iaq Monitoring: Implementation And Guidelines, Isaac Ntiamoah

LSU Master's Theses

Indoor air quality (IAQ) is adversely affected by both indoor and outdoor environments, and rental homes occupied by low-income families suffer the most. Poor indoor air can be detrimental to the health of occupants, especially for susceptible populations like those with respiratory diseases such as asthma. Although IAQ monitoring is necessary, it is a challenging, costly, and time-intensive task. Moreover, the protocol for assessing IAQ in residential settings varies, and additional research is needed to establish a standard operating procedure that incorporates new monitoring technologies, such as low-cost air sensors. However, there is a dearth of comprehensive, evidence-based protocols for …