Systems Engineering Commons^™

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 …

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, …

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, …

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 …

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 …

Automation Complacency On Humans And Cyber-Physical Systems In The Energy Sector, Shannon Olaveson

Cyber Operations and Resilience Program Graduate Projects

Cyber-physical systems (CPS) and the Industrial Internet of Things (IoT) enable industrial systems and technology to work together to achieve increased connectivity and operational efficiency through the use of automation. Because automation requires less human interaction to run industrial tasks, a reliance may form on this integration to take over an otherwise manual process. This reliance can cause human behavior to affect operational safety and security, leading to unintentional outcomes or vulnerable areas of adversarial opportunity. The energy sector is one of the most critical infrastructure areas becoming a part of the rise to automation, resourcing gas, oil, and electricity …

Kwad - Ksu All Weather Autonomous Drone, Nick Farinacci, Sebastian Gomez, Stewart Baker, Ed Sheridan

Symposium of Student Scholars

"KWAD" or "KSU all-Weather Autonomous Drone" project was sponsored by Ultool, LLC to the KSU Research and Service Foundation to create a lightweight drone capable of capturing HD video during all-weather operations. The conditions of all-weather operation include rainfall of one inch per hour and wind speeds of up to twenty miles per hour. In addition, a global minimum structural safety factor of two is required to ensure the system's integrity in extreme weather conditions. Potential mission profiles include autonomous aerial delivery, topological mapping in high moisture areas, security surveillance, search and rescue operations, emergency transportation of medical supplies, and …

Tank Level Controller Plc Lab, Siddhi Upadhyaya, Teghvir Grewal

Electrical Engineering

The California Polytechnic State University San Luis Obispo’s Electrical Engineering Department is currently developing lab experiments for the new EE435 (Industrial Power Control and Automation) class. In order to support these efforts, fourth year Cal Poly students are expected to develop laboratory experiments that will be conducted during this new class for the semester system. The lab experiment focused on in this project is called the Tank Level Controller. This experiment will introduce EE 435 students to Schneider Electric Programmable Logic Controller (PLC) hardware and software, which is prominent in the automation industry.
This experiment will require students to develop …

Smart Warehousing Implementaion And Education Of Supply Chain Management Leaders, David Quintanilla

Doctoral Dissertations

Paper #1 Overview

Businesses have to adapt to new challenges and technologies in the marketplace which influence warehousing. In order to support this growth, Industry 4.0 technologies have been implemented along the value chain to optimize their organizations and production processes; however, there are still gaps for warehousing research for Industry 4.0. We present four pillars¾location strategy, infrastructure/design, data management, and advanced planning and control¾ as a framework for businesses to use for their adaptation into smart warehousing. In particular, this framework will guide companies in their logistics journey into Industry 4.0. Industry experts and senior logistics professionals were interviewed …

Accelerating Manufacturing Decisions Using Bayesian Optimization: An Optimization And Prediction Perspective, Taofeeq Olajire

Graduate Theses, Dissertations, and Problem Reports

Manufacturing is a promising technique for producing complex and custom-made parts with a high degree of precision. It can also provide us with desired materials and products with specified properties. To achieve that, it is crucial to find out the optimum point of process parameters that have a significant impact on the properties and quality of the final product. Unfortunately, optimizing these parameters can be challenging due to the complex and nonlinear nature of the underlying process, which becomes more complicated when there are conflicting objectives, sometimes with multiple goals. Furthermore, experiments are usually costly, time-consuming, and require expensive materials, …

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 …

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 …

Hard-Real-Time Computing Performance In A Cloud Environment, Alvin Cornelius Murphy

Engineering Management & Systems Engineering Theses & Dissertations

The United States Department of Defense (DoD) is rapidly working with DoD Services to move from multi-year (e.g., 7-10) traditional acquisition programs to a commercial industrybased approach for software development. While commercial technologies and approaches provide an opportunity for rapid fielding of mission capabilities to pace threats, the suitability of commercial technologies to meet hard-real-time requirements within a surface combat system is unclear. This research establishes technical data to validate the effectiveness and suitability of current commercial technologies to meet the hard-real-time demands of a DoD combat management system. (Moreland Jr., 2013) conducted similar research; however, microservices, containers, and container …

Study Of Stochastic Market Clearing Problems In Power Systems With High Renewable Integration, Saumya Sakitha Sashrika Ariyarathne

Operations Research and Engineering Management Theses and Dissertations

Integrating large-scale renewable energy resources into the power grid poses several operational and economic problems due to their inherently stochastic nature. The lack of predictability of renewable outputs deteriorates the power grid’s reliability. The power system operators have recognized this need to account for uncertainty in making operational decisions and forming electricity pricing. In this regard, this dissertation studies three aspects that aid large-scale renewable integration into power systems. 1. We develop a nonparametric change point-based statistical model to generate scenarios that accurately capture the renewable generation stochastic processes; 2. We design new pricing mechanisms derived from alternative stochastic programming …

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 …

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 …

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 …

Examining The Impact Of Design Features Of Electronic Health Records Patient Portals On The Usability And Information Communication For Shared Decision Making, Rong Yin

All Dissertations

The use of the Electronic Health Records (EHR) patient portal has been shown to be effective in generating positive outcomes in patients’ healthcare, improving patient engagement and patient-provider communication. Government legislation also required proof of its meaningful use among patients by healthcare providers. Typical patient portals also include features such as health information and patient education materials. However, little research has examined the specific use of patient portals related to individuals with specific diseases such as inflammatory bowel diseases (IBDs). IBDs are life-long, not curable, chronic diseases that can impact the whole population. Individuals with IBDs may have higher needs …

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 …

Forecasting Hypotension By Learning From Multivariate Mixed Responses.., Jodie Ritter

Electronic Theses and Dissertations

Blood Pressure is the main determinant of blood flow to organs. Hypotension is defined as a systolic blood pressure less than 90 mmHg or a diastolic blood pressure less than 50 mmHg. The severity and duration of hypotension is associated with low blood flow to organs often result in organ damage and a high mortality rate. Predicting hypotension prior to surgery and during the surgery can reduce the incidence and duration resulting in better patient outcomes. This thesis uses preoperative bloodwork and vital signs as well as perioperative vital signs in 5-minute increments as inputs to forecast hypotension. Hypotension can …

An Elliptical Cover Problem In Drone Delivery Network Design And Its Solution Algorithms, Yanchao Liu

Industrial and Systems Engineering Faculty Research Publications

Given n demand points in a geographic area, the elliptical cover problem is to determine the location of p depots (anywhere in the area) so as to minimize the maximum distance of an economical delivery trip in which a delivery vehicle starts from the nearest depot to a demand point, visits the demand point and then returns to the second nearest depot to that demand point. We show that this problem is NP-hard, and adapt Cooper’s alternating locate-allocate heuristic to find locally optimal solutions for both the point-coverage and area-coverage scenarios. Experiments show that most locally optimal solutions perform similarly …

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 …

The Traveling Salesman Problem: An Analysis And Comparison Of Metaheuristics And Algorithms, Mason Helmick

Senior Honors Theses

One of the most investigated topics in operations research is the Traveling Salesman Problem (TSP) and the algorithms that can be used to solve it. Despite its relatively simple formulation, its computational difficulty keeps it and potential solution methods at the forefront of current research. This paper defines and analyzes numerous proposed solutions to the TSP in order to facilitate understanding of the problem. Additionally, the efficiencies of different heuristics are studied and compared to the aforementioned algorithms’ accuracy, as a quick algorithm is often formulated at the expense of an exact solution.

Decision-Analytic Models Using Reinforcement Learning To Inform Dynamic Sequential Decisions In Public Policy, Seyedeh Nazanin Khatami

Doctoral Dissertations

We developed decision-analytic models specifically suited for long-term sequential decision-making in the context of large-scale dynamic stochastic systems, focusing on public policy investment decisions. We found that while machine learning and artificial intelligence algorithms provide the most suitable frameworks for such analyses, multiple challenges arise in its successful adaptation. We address three specific challenges in two public sectors, public health and climate policy, through the following three essays. In Essay I, we developed a reinforcement learning (RL) model to identify optimal sequence of testing and retention-in-care interventions to inform the national strategic plan “Ending the HIV Epidemic in the US”. …

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 …

Quantitative Methods For Total Lifecycle Risk Likelihood And Impact Assessment In Sustainable Product Design Decision Making, Christian Enyoghasi

Theses and Dissertations--Mechanical Engineering

Sustainable products promise significant economic, environmental, and societal benefits. Numerous methods are available for use during the new product development process to identify alternate product designs that optimize sustainability performance. Once any such design is selected and the product is launched, many uncertainties are likely to affect its performance over the total lifecycle. Such uncertainties give rise to risks that can influence the overall product sustainability performance. However, comprehensive quantitative methods to evaluate the likelihood or the impact of different risks to enable sustainable product design decision making are lacking.

This research aims to address this gap by developing a …

Deep Multi-Modal U-Net Fusion Methodology Of Infrared And Ultrasonic Images For Porosity Detection In Additive Manufacturing, Christian E. Zamiela

Theses and Dissertations

We developed a deep fusion methodology of non-destructive (NDT) in-situ infrared and ex- situ ultrasonic images for localization of porosity detection without compromising the integrity of printed components that aims to improve the Laser-based additive manufacturing (LBAM) process. A core challenge with LBAM is that lack of fusion between successive layers of printed metal can lead to porosity and abnormalities in the printed component. We developed a sensor fusion U-Net methodology that fills the gap in fusing in-situ thermal images with ex-situ ultrasonic images by employing a U-Net Convolutional Neural Network (CNN) for feature extraction and two-dimensional object localization. We …

Using A Systemic Skills Model To Build An Effective 21st Century Workforce: Factors That Impact The Ability To Navigate Complex Systems, Morteza Nagahi

Theses and Dissertations

The growth of technology and the proliferation of information made modern complex systems more fragile and vulnerable. As a result, competitive advantage is no longer achieved exclusively through strategic planning but by developing an influential cadre of technical people who can efficiently manage and navigate modern complex systems. The dissertation aims to provide educators, practitioners, and organizations with a model that helps to measure individuals’ systems thinking skills, complex problem solving, personality traits, and the impacting demographic factors such as managerial and work experience, current occupation type, organizational ownership structure, and education level. The intent is to study how these …