Engineering Commons^™

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 …

Characterizing Logistics Operations Within A Federal Staging Area For Hurricane Response: A Qualitative Analysis Of Federal, State And Local Perspectives, Jannatul Shefa

Graduate Theses and Dissertations

A successful deployment of logistics operations following a disaster is a collective contribution of federal, state, and local entities to ascertain an efficient and effective response. This research analyzes data from interviews with disaster response logistics experts from these entities. The objective is to investigate the information sources and planning processes used in these organizations to plan vehicle routes for critical resource deliveries to impacted areas. Special attention is directed to the impacts of incomplete knowledge of infrastructure status, such as road disruptions due to debris or flooding. Supported by both qualitative and quantitative evidence, the study finds that incomplete …

Demand Prediction And Inventory Management Of Surgical Supplies, Rajon Paul Pantha

Graduate Theses and Dissertations

Effective supply chain management is critical to operations in various industries, including healthcare. Demand prediction and inventory management are essential parts of healthcare supply chain management for ensuring optimal patient outcomes, controlling costs, and minimizing waste. The advances in data analytics and technology have enabled many sophisticated approaches to demand forecasting and inventory control. This study aims to leverage these advancements to accurately predict demand and manage the inventory of surgical supplies to reduce costs and provide better services to patients. In order to achieve this objective, a Long Short-Term Memory (LSTM) model is developed to predict the demand for …

Efficient Routing For Disaster Scenarios In Uncertain Networks: A Computational Study Of Adaptive Algorithms For The Stochastic Canadian Traveler Problem With Multiple Agents And Destinations, Neel Chanchad

Graduate Theses and Dissertations

The primary objective of this research is to develop adaptive online algorithms for solving the Canadian Traveler Problem (CTP), which is a well-studied problem in the literature that has important applications in disaster scenarios. To this end, we propose two novel approaches, namely Maximum Likely Node (MLN) and Maximum Likely Path (MLP), to address the single-agent single-destination variant of the CTP. Our computational experiments demonstrate that the MLN and MLP algorithms together achieve new best-known solutions for 10,715 instances. In the context of disaster scenarios, the CTP can be extended to the multiple-agent multiple-destination variant, which we refer to as …

Interaction Effects And Selecting Regression Models Of Taylor Swift Song Popularity, Halle Schneidewind

Industrial Engineering Undergraduate Honors Theses

Understanding music popularity and what drives it is important not only for artists but for other individuals who are financially tied to music sales including producers, writers, and record labels. Studies have been done to define how a song’s popularity can be measured, what attributes or features are drivers for popularity, and to what extent can a song’s popularity even be predicted. This paper takes two linear regression approaches to predicting the popularity of a Taylor Swift song on Spotify based on auditory features the Spotify API estimates and historic popularity of songs on Spotify. One model takes into consideration …

Detecting Pathobiomes Using Machine Learning, Valerie Jackson, Valerie Jackson

Industrial Engineering Undergraduate Honors Theses

Machine learning is a field with high growth potential due to the overall continuous progressions, developments, advancements, and improvements caused by the way it is used to help interpret and use large amounts of data [1]. One type of data that can be collected and analyzed by these machine learning models is data that is associated with DNA and information that the DNA gives. The research will be focusing specifically on using machine learning technology to detect pathobiomes indicative of salmonella pork. The pathobiome associated with salmonella is very similar to others, and this causes a problem for classification/detection with …

The Impact Of A Carbon Tax On Emissions, Jessica Creech

Industrial Engineering Undergraduate Honors Theses

A carbon tax is an economic policy that aims to reduce various emissions to serve the protection of the environment. Versions of this policy have been implemented in multiple countries across the world to introduce a cost for contributing to environmental damage. Since climate change is prevalent in today’s world, finding an effective method to reduce emissions is essential. However, many countries hesitate to utilize a carbon tax for two reasons. First, they are unsure if the carbon tax is effective at reducing emissions. Second, there is a concern that the implementation of such a tax will be detrimental to …

Testing The Effects Of Different Designs On The Physical Properties Of 3d-Printed Watch Bands, Ross Harper

Industrial Engineering Undergraduate Honors Theses

Technological innovation progresses at an ever-increasing rate, and this is especially true in the field of 3D-printing. 3D-printing has become popular in manufacturing settings and among amateur hobbyists alike, largely because 3D-printers can fabricate an enormous number of designs from an array of materials and allow for fine-tuning through several setting options. Individuals with proficient 3D-printing abilities can produce a nearly infinite number of components for diverse applications in manufacturing, recreation, ergonomics, and many more. Some individuals use their skills to create functional substitutes for name-brand items, including bands to fit and be worn with a smart watch. However, little …

Automated Visualization Pipeline For Near Real-Time Risk Management System, Paris Joslin

Industrial Engineering Undergraduate Honors Theses

In modern society, technological capabilities and the amount of data readily available to users continue to grow exponentially. Many have adopted these new capabilities but lack the infrastructure needed to efficiently utilize high-powered software and programs. Without a method to collect, store, and process large datasets in real-time, individuals and businesses can quickly become overwhelmed, inhibiting effective decision-making processes. There is potential to improve decision-making abilities by enhancing the computing infrastructure. To accomplish this task, we will explore the ideas surrounding High Performance Computing (HPC) and data visualization software. High Performance Computing is the ability to process data and perform …

A Multi-Criteria Ranking System For Prioritizing Maintenance Of Levee Systems In Arkansas, Nguyen Danh Phan

Graduate Theses and Dissertations

There are 208,009 properties in Arkansas that have more than a 26% chance of being severely affected by flooding over the next 30 years, which represents 13% of all properties in the state. A levee system is designed to reduce the flooding risk for urban and rural communities; however, most of the state's levees have been significantly outdated or built with engineering standards less rigorous than current best practices. The Levee Safety Action Classification (LSAC), as recorded in the National Levee Database (NLD), communicates the risk associated with living behind a particular levee and assists local, state, and federal stakeholders …

Using Reinforcement Learning To Improve Network Reliability Through Optimal Resource Allocation, Henley Wells

Graduate Theses and Dissertations

Networks provide a variety of critical services to society (e.g. power grid, telecommunication, water, transportation) but are prone to disruption. With this motivation, we study a sequential decision problem in which an initial network is improved over time (e.g., by adding or increasing the reliability of edges) and rewards are gained over time as a function of the network’s all-terminal reliability. The actions during each time period are limited due to availability of resources such as time, money, or labor. To solve this problem, we utilized a Deep Reinforcement Learning (DRL) approach implemented within OpenAI-Gym using Stable Baselines. A Proximal …

Simulating Emergency Evacuation Response In An Auditorium Space, Anna Lee

Industrial Engineering Undergraduate Honors Theses

The successful execution of emergency evacuations is very important for the protection of the public. Some emergency events, such as fires, can occur with very little warning and turn into a dangerous situation in less than a minute. With high population densities, universities have increased risk involved with evacuations. One specific area that presents high risk is auditorium spaces such as lecture halls with high densities combined with added barriers such as tables and chairs. The ability to assess a building’s emergency preparedness is necessary for keeping the public safe. Simulation is a way to conduct a theoretical event and …

Deep Learning Applications In Industrial And Systems Engineering, Winthrop Harvey

Graduate Theses and Dissertations

Deep learning - the use of large neural networks to perform machine learning - has transformed the world. As the capabilities of deep models continue to grow, deep learning is becoming an increasingly valuable and practical tool for industrial engineering. With its wide applicability, deep learning can be turned to many industrial engineering tasks, including optimization, heuristic search, and functional approximation. In this dissertation, the major concepts and paradigms of deep learning are reviewed, and three industrial engineering projects applying these methods are described. The first applies a deep convolutional network to the task of absolute aerial geolocalization - the …

Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson

Graduate Theses and Dissertations

This research proposes problems, models, and solutions for the scheduling of space robot on-orbit servicing. We present the Multi-Orbit Routing and Scheduling of Refuellable On-Orbit Servicing Space Robots problem which considers on-orbit servicing across multiple orbits with moving tasks and moving refuelling depots. We formulate a mixed integer linear program model to optimize the routing and scheduling of robot servicers to accomplish on-orbit servicing tasks. We develop and demonstrate flexible algorithms for the creation of the model parameters and associated data sets. Our first algorithm creates the network arcs using orbital mechanics. We have also created a novel way to …

Ensemble Tree-Based Machine Learning For Imaging Data, Reza Iranzad

Graduate Theses and Dissertations

In particular medical imaging data, such as positron emission tomography (PET), computed tomography (CT), and fluorescence intravital microscopy (IVM), have become prevalent for use in a wide variety of applications, from diagnostic purposes, tracking diseases' progress, and monitoring the effectiveness of treatments to decision-making processes. The detailed information generated by medical imaging has enabled physicians to provide more comprehensive care. Although numerous machine learning algorithms, especially those used for imaging data, have been developed, dealing with unique structures in imaging data remained a big challenge. In this dissertation, we are proposing novel statistical tree-based methods with more efficient and more …

Modeling The Impact And Accelerating The Process Of Transitioning To A Sustainable Healthy Diet Through Decision Support Systems, Prince Agyemang

Graduate Theses and Dissertations

Food production and consumption are essential in human existence, yet they are implicated in the high occurrences of preventable chronic diseases and environmental degradation. Although healthy food may not necessarily be sustainable and vice versa, there is an opportunity to make our food both healthy and sustainable. Attempts have been made to conceptualize how sustainable healthy food may be produced and consumed; however, available data suggest a rise in the prevalence of health-related and negative environmental consequences of our food supply. Thus, the transition from conceptual frameworks to implementing these concepts has not always been effective. This paper explores the …

Supervised Representation Learning For Improving Prediction Performance In Medical Decision Support Applications, Phawis Thammasorn

Graduate Theses and Dissertations

Machine learning approaches for prediction play an integral role in modern-day decision supports system. An integral part of the process is extracting interest variables or features to describe the input data. Then, the variables are utilized for training machine-learning algorithms to map from the variables to the target output. After the training, the model is validated with either validation or testing data before making predictions with a new dataset. Despite the straightforward workflow, the process relies heavily on good feature representation of data. Engineering suitable representation eases the subsequent actions and copes with many practical issues that potentially prevent the …

The Impact Of Reliability In Conceptual Design - An Integrated Trade-Off Analysis, Tevari James Barker

Graduate Theses and Dissertations

Research presented in this paper focuses on developing models to estimate the systemreliability of Unmanned Ground Vehicles using knowledge and data from similar systems. Traditional reliability approaches often require detailed knowledge of a system and are used in later design stages as well as development, operational test and evaluation, and operations. The critical role of reliability and its impact on acquisition program performance, cost, and schedule motivate the need for improved system reliability models in the early design stages. Reliability is often a stand-alone requirement and not fully included in performance and life cycle cost models. This research seeks to …

Comparing Actively Managed Mutual Fund Categories To Index Funds Using Linear Regression Forecasting And Portfolio Optimization, Luke Weiner

Industrial Engineering Undergraduate Honors Theses

The global investment industry offers a wide variety of investment products especially for individual investors. One such product, index funds, which are younger than actively managed mutual funds, have typically outperformed managed funds. Despite this phenomenon, investors have displayed a tendency to continue investing in actively managed funds. Although only a small percentage of actively managed funds outperform index funds, the costs of actively managed funds are significantly higher. Also, managed fund performances are most often determined by their fund category such as growth or real estate. I wanted to answer the following question for individual investors: can we …

Analyzing Vulnerabilities In The Northwest Arkansas Highway Network Using Mathematical Optimization, Brandon Jerome

Industrial Engineering Undergraduate Honors Theses

The highway and bridge network is a critical infrastructure that allows for the free transportation of citizens and enables truck-borne freight transportation. Disruption of this system could be caused by a terrorist attack, natural disaster, growth of population, required repairs and upgrades, or collapse caused by old age or malfunction. In the event of a disruption cities and regions can experience increased traffic and supply chain shortages, thus causing cascading effects throughout surrounding areas. With this motivation, we develop a network interdiction optimization model to identify a limited subset of roads that, if disrupted, causes the greatest increase in the …

Implementing The Cms+ Sports Rankings Algorithm In A Javafx Environment, Luke Welch

Industrial Engineering Undergraduate Honors Theses

Every year, sports teams and athletes get cut from championship opportunities because of their rank. While this reality is easier to swallow if a team or athlete is distant from the cut, it is much harder when they are right on the edge. Many times, it leaves fans and athletes wondering, “Why wasn’t I ranked higher? What factors when into the ranking? Are the rankings based on opinion alone?” These are fair questions that deserve an answer. Many times, sports rankings are derived from opinion polls. Other times, they are derived from a combination of opinion polls and measured performance. …

Assessing The Influence Of Health Policy And Population Mobility On Covid-19 Spread In Arkansas, Tayden Barretto

Industrial Engineering Undergraduate Honors Theses

The outbreak of COVID-19 has created a major crisis across the world since its start in 2019, and its influence on every realm of society is undeniable. Globally, more than 500 million cases have been recorded since March 2020, with almost 6 million deaths. In the wake of this crisis, many governments and health organizations have taken steps and precautions to mitigate its spread. These steps involve public mandates of information, reducing frequency of personal contact, and use of masks to minimize the risk of transmission. Current access to mobility data released from Google detailing population movements has provided a …

Predicting The Likelihood And Scale Of Wildfires In California Using Meteorological And Vegetation Data, Matthew Walters

Graduate Theses and Dissertations

Wildfires have devastating ecological, environmental, economical, and public health impacts through the deterioration of water and air quality, CO2 emissions, property damage, and lung illnesses. The early detection and prevention of wildfires allow for the minimization of these risks. The use of Artificial Intelligence (AI) in wildfire detection and prediction has been highly researched as a tool to assist firefighters in stopping wildfires in its early stages. The three common wildfire prediction categories include image and video detection, behavior prediction, and susceptibility prediction. Data such as climate, weather, vegetation, satellite images, and historical wildfire data is most commonly used. Many …

A Spatiotemporal Analysis Of Food Pantry Accessibility In Washington County, Arkansas, Coleman Warren

Industrial Engineering Undergraduate Honors Theses

Food pantries are an essential resource for impoverished and food insecure communities. Washington County, Arkansas has a food insecurity rate of 14.3% as compared to the national average of 10.9% (Feeding America, 2019). The Northwest Arkansas Food Bank has a robust pantry network in Washington County to support families and individuals who struggle with food insecurity.

We conducted a spatiotemporal analysis of food pantry accessibility in Washington County, Arkansas to evaluate the effectiveness of the food pantry network in Washington County at supporting communities with the most need. This analysis was conducted using the Two-Step Floating Catchment Area (2SFCA) method …

21st Century Leadership: Leadership In Challenging Times, Adam Morris

Operations Management Presentations

Our global society has experienced unprecedented changes in the last couple years. The COVID-19 pandemic created drastic changes to our personal and professional lives. We went to a virtual work and learning environment almost overnight. People in leadership positions had to make impossible decisions on items no one has ever experienced. With all the changes that are happing in our world, what does it take to be a leader in today’s global society? Do basic leadership principles from 30 years ago still apply? Watch the latest installment of the MSEM/MSOM Lunch & Learn Webinar Series that will discuss these leadership …

Tools & Visualization Techniques Available To Support The Operations Manager, Kirk Michealson

Operations Management Presentations

Most organizations provide their employees the Microsoft Office Tools Suite with Excel. The University of Arkansas Master of Science in Operations Management (MSOM) Program has included Excel as a foundational aspect of the program for the last 7 years. In that time, Microsoft has increased the Excel capabilities dramatically. Simultaneously, business intelligence analytics interest has increased, and Tableau has been created as a visual analytics platform to help users see and understand data for modern business intelligence. As a result, to support the Operations Manager the MSOM Program has developed a new course to present the additional tools and visualization …

Statistical Modeling, Learning And Computing For Stochastic Dynamics Of Complex Systems, Mohammadmahdi Hajiha

Graduate Theses and Dissertations

With the recent advances in sensor technology, it is much easier to collect and store streams of system operational and environmental (SOE) data. These data can be used as input to model the underlying behavior of complex engineered systems and phenomenons if appropriate algorithms with well-defined assumptions are developed. This dissertation is comprised of the research work to show the applicability of SOE data when fed into proposed tailored algorithms. The first purposes of these algorithms are to estimate and analyze the reliability of a system as elaborated in Chapter 2. This chapter provides the derivation of closed-form expressions that …

Third Party Risk Management And Cyber Supply Chain Risk Management, Jerald Garner

Operations Management Presentations

Today’s business environment continues to be a challenge. Businesses whether small, or large leverage third-party vendors to provide critical services like data handling (security, transmitting, and storage), cloud storage/applications, and systems security monitoring.

Each business must ask themselves a few simple questions about one of their most valuable assets “Data”. If or when it leaves your secure working environment:

• How secure is your customer data in transit and storage?
• Do your third-party vendors handle your “critical information”?
  • Provide a secure environment for processing?
  • Comply with a proven Cyber Security Framework?
  • Perform a “Due Diligence” on-boarding step for the Nth vendors …

Hidden In Plain Sight: Why Sustainment Is So Critical To The Circular Supply Chains For Technical Products, Dave Peterson

Operations Management Presentations

• Technical products are typically complex, long-lived and high-cost equipment—such as: aircraft, vehicles, ships, capital equipment/machinery and utilities infrastructure. While many technical products are manufactured via traditional linear supply chains, their useful lives often rely upon sustainment systems incorporating significant aspects of circular supply chains. This webinar takes a closer look at technical products and the critical role of systems sustainment to achieve and fulfill circular supply chains. The key takeaways from this webinar are:
  • The Earth is running out of resources which will have a direct impact upon maintaining/improving our quality of life.
  • The circular economy philosophy has definite relevance …

Critical Chain – Or Why Wedding Planners Get Ulcers, Greg Hutto

Operations Management Presentations

Planning a wedding is one of the most challenging projects in a young life… So much to do! A respected journal in the project management literature -- Southern Bride -- advises well-off young couples to escape stress and employ a professional wedding planner+. In today's webinar we will contrast two project planning methods in examining one such wedding project -- hastily planned and beset with troubles. We will shed light on the science & art of project management and possibly help our wedding planners (both professional and amateur) avoid stress-induced medical complications. In this webinar, we’ll be spending time with …