Operations Research, Systems Engineering and Industrial Engineering Commons^™

An Online Adaptive Machine Learning Framework For Autonomous Fault Detection, Nolan Coulter

Doctoral Dissertations and Master's Theses

The increasing complexity and autonomy of modern systems, particularly in the aerospace industry, demand robust and adaptive fault detection and health management solutions. The development of a data-driven fault detection system that can adapt to varying conditions and system changes is critical to the performance, safety, and reliability of these systems. This dissertation presents a novel fault detection approach based on the integration of the artificial immune system (AIS) paradigm and Online Support Vector Machines (OSVM). Together, these algorithms create the Artificial Immune System augemented Online Support Vector Machine (AISOSVM).

The AISOSVM framework combines the strengths of the AIS and …

Routing Battery-Constrained Delivery Drones In A Depot Network: A Business Model And Its Optimization-Simulation Assessment, Yanchao Liu

Industrial and Systems Engineering Faculty Research Publications

This paper proposes a novel business model for on-demand package shipment services using drones, and evaluates different modeling and solution approaches for the drone routing problem that underpins the service operation. In the proposed service, customers’ shipment orders of arbitrary origins and destinations, payload weights and bid values are collected every five minutes, and available drones from multiple depots are then dispatched to fulfill a subset of these orders in a way to maximize profit. A drone path starts from a depot, serves one or more customer orders in sequence, and ends at a depot for battery recharging, which incurs …

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 …

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 …

Lead Distribution Modeling For Supply Chains With A Large Number Of Items, Wesley Tate

Industrial Engineering Undergraduate Honors Theses

Adding randomness into a simulation model allows for a better understanding of the variation that can occur in a real-life setting. This paper documents the methodology used to recommend a set of distribution models to cover administrative and production lead times for the simulation program involving hundreds of thousands of items. The problem of distribution fitting for large datasets is addressed, with histograms, Q-Q, and P-P plots being used to verify models in addition to goodness-of-fit test statistics. Variable level reduction using frequency and distribution matching approaches are outlined followed by the use of random forest modeling to identify key …

Optimizing Wedding Venue Selection Process Using Integer Programming, Luis Rodriguez

Theses/Capstones/Creative Projects

Choosing the right wedding venue can be extremely difficult for the unsuspecting engaged couple. There is a myriad of variables that must be taken into account prior to the illustrious wedding date; these variables include the option for a reception, the location, and food requirements, to name a few. Consequently, the typical couple seems to spend multiple months researching and visiting many wedding spaces. However, even though months go into planning, it still is not a guarantee that all variables are accounted for. Furthermore, without a wedding planner, these couples may second-guess their chosen site due to seemingly arduous issues …

Machine Learning For Ultraviolet Spectral Prediction, Linh Ho Manh

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Machine Learning has found wide applications in material science, including dielectric polymers, superconducting materials, and drug property prediction. The use of data analytics and machine learning methods to predict Vacuum Ultraviolet (VUV) spectra by encoding molecular structure is gaining interest because high-quality VUV spectral prediction capability would enable the study of new molecules without costly wet-lab measurements. This dissertation aims to study feature representations for molecular structures that enhance the prediction of VUV spectra via machine learning models. Both interpretable machine learning and deep learning are studied. Chapter 1 provides an overview of VUV/UV spectra retrieval, and Chapter 2 reviews …

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 …

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 …

Design And Development Of A Virtual Reality Training Platform For Fiber-Reinforced Composite Manufacturing, Taufiq Rahman

Industrial, Manufacturing, and Systems Theses - Archive

This study presents the design and development of a virtual reality (VR) training platform for manufacturing fiber-reinforced composites, a sophisticated and high-demand material in various industries. Due to the high costs and safety concerns associated with compression molding machines - essential equipment for this manufacturing process, the VR platform offers a promising alternative for training to educational institutions and manufacturing industries. The platform provides an immersive, interactive training and cost-efficient learning environment, allowing users to gain practical experience without the risks and expenses of physical training. The VR training module was developed using the Unity game engine and deployed on …

The Development And Use Of The Probabilistic Financial Decision Model For A Company Expansion, Elizabeth Wiese

Senior Honors Theses

In the United States, companies are expanding constantly. However, in an industrial equipment dealership expanding into a new state, it is important to understand the industry, new market, and costs associated with expanding. With using financial statements of data-backed percentages for growth, research seeks to set up a financial model to see if expansion for an industrial equipment dealership into the state of North Carolina will be a financially wise decision. Wesley Worldwide, an industrial equipment dealership, is moving forward with the investment of expanding into North Carolina. However, it is vital to understand the financial predictions for profit return …

Rattus Norvegicus As A Biological Detector Of Clandestine Remains And The Use Of Ultrasonic Vocalizations As A Locating Mechanism, Gabrielle M. Johnston

Master's Theses

In investigations, locating missing persons and clandestine remains are imperative. One way that first responder and police agencies can search for the remains is by using cadaver dogs as biological detectors. Cadaver dogs are typically used due to their olfactory sensitivity and ability to detect low concentrations of volatile organic compounds produced by biological remains. Cadaver dogs are typically chosen for their stamina, agility, and olfactory sensitivity. However, what is not taken into account often is the size of the animal and the expense of maintaining and training the animal. Cadaver dogs are typically large breeds that cannot fit in …

Trace Dna Detection Using Diamond Dye: A Recovery Technique To Yield More Dna, Leah Davis

Master's Theses

This study aspires to find a new screening approach to trace DNA recovery techniques to yield a higher quantity of trace DNA from larger items of evidence. It takes the path of visualizing trace DNA on items of evidence with potential DNA so analysts can swab a more localized area rather than attempting to recover trace DNA through the general swabbing technique currently used for trace DNA recovery. The first and second parts consisted of observing trace DNA interaction with Diamond Dye on porous and non-porous surfaces.

The third part involved applying the Diamond Dye solution by spraying it onto …

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 …

Network Effects Of Emergency Department Clinician Strain And Patient Congestion, Aisha Nelson

All Theses

We develop a discrete-event simulation model to study how staffing strain affects patient outcomes across a network of Emergency Departments (EDs). The aim is to observe how clinician staffing and transfers throughout the system affect the system’s behavior. We will study the network of the seven EDs in the Prisma Health-Upstate system. Patient acuity and resource need are stratified using the five-level Emergency Severity Index (ESI). Patient flow data within and between EDs are collected from EPIC, staffing data from ShiftAdmin, and environmental COVID-19 prevalence data from the Department of Health and Environmental Control. Time periods include the Omicron wave …

Mapping Information Flows That Support Adaptive Capacity In The Sterile Processing Department (Spd), Jacob Hionis

All Theses

The Sterile Processing Department (SPD) is the part of the hospital that is responsible for decontaminating, assembling, and sterilizing surgical trays for use in the Operating Rooms (ORs). Errors in the SPD can lead to delayed surgeries or patient harm. The SPD is a complex system, with multiple interconnected subdepartments and roles. Complex systems require coordination between stakeholders. This study aims to discover how an organization can adapt to scale, and how information flows support these adaptations. In this study, observations, semi-structured interviews, and on-the-job interviews were conducted with members across the SPD and OR to elicit pressures, adaptations, and …

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 …

Electric Vehicle Routing Problem – Models And Algorithms, Hesamoddin Tahami

Engineering Management & Systems Engineering Theses & Dissertations

The transportation sector is a major greenhouse gas emitter that is heavily regulated to reduce its dependence on oil. These regulations along with the growing customer awareness of global warming have led to the investigation of new transportation problems that consider using eco-friendly vehicle fleets. Promising alternatives to traditional fleets include alternative fuel vehicles (AFVs) and electric vehicles (EVs). These twenty-first-century vehicles offer an appealing advantage of consistently reducing their environmental impact, but due to the current technology, they exhibit bothersome limitations. The short driving range along with limited charging infrastructure may consequently cause issues related to range anxiety, i.e., …

Sealion Cubesat Mission Architecture Using Model Based Systems Engineering With A Docs As Code Approach, Kevin Yi-Tzu Chiu

Mechanical & Aerospace Engineering Theses & Dissertations

CubeSats are a growing population within the space industry. Every year, universities launch numerous amounts of CubeSats due to their inexpensive cost of development, launch, and deployment. However, this comes with numerous challenges. As the number of university-CubeSats grow, so too do the numbers that fail. With development teams consisting mainly of students with little to no training, proper and yet easy to use tools or methods should be implemented to help ensure mission success. Especially in the critical stages of planning before and during development, a technical approach to quickly track life cycle development of a CubeSat is needed. …

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 …