Operations Research, Systems Engineering and Industrial Engineering Commons^™

Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa

Theses and Dissertations

“Energy Trilemma” has recently received an increasing concern among policy makers. The trilemma conceptual framework is based on three main dimensions: environmental sustainability, energy equity, and energy security. Energy security reflects a nation’s capability to meet current and future energy demand. Rational energy planning is thus a fundamental aspect to articulate energy policies. The energy system is huge and complex, accordingly in order to guarantee the availability of energy supply, it is necessary to implement strategies on the consumption side. Energy modeling is a tool that helps policy makers and researchers understand the fluctuations in the energy system. Over the …

Virtual Analyzers For Increasing The Intelligence Of Industrial Process Control Systems, Umidjon Abdimajotovich Ruziev Phd, Marufjon Kobuljanovich Shodiev

Chemical Technology, Control and Management

It is shown that the development and implementation of virtual analyzers of the quality of the final industrial products is an effective tool for increasing the efficiency of industrial production. The methodology and stages of development of virtual analyzers for predicting the quality of products, monitoring non-measurable or difficult-to-measure parameters of continuous and periodic technological processes are considered, and issues of supporting and adapting a virtual analyzer during its operation without restructuring are also considered.

End Milling Process Modeling Using Artificial Neural Networks, Khaled Abdel-Hamid Elsayed

Archived Theses and Dissertations

No abstract provided.

Leveraging Choice Modeling Technique For Enhancing The Cyber Resilience Of The Smart Grid, Kesava Karishma Devi Dadi

Theses and Dissertations

This research focuses on the cyber-attack of the smart grid and its retrieval to a normal state by estimating the smart grid's resilience. This study developed a theoretical model to estimate the resilience of the smart grid using choice modeling. A utility function is formulated based on various factors and sub-factors of resilience to estimate the resilience of the smart grid. Choice modeling is applied to estimate the model parameters in various fields such as marketing, energy, transportation, and health and to predict the outcome.

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 …

Effects Of The Inclusion Of Rice Hull Derived Bio-Oil On Wood Pellet Production, Tyler E. Lowe

Theses and Dissertations

Wood pellet production has become an advancing industry for the sake of reducing greenhouse emissions into the atmosphere especially, in European Union countries. Researchers and industry executives seek new methods and materials to improve the pelletization process. Rice hulls or husks has the potential to aid in wood pelletization as they possess high calorific values. This study focuses on using rice hull derived bio-oil from pyrolysis, which will also decrease ash content, as an additive to aid in the wood pelletization process. Using two groups of rice hull derived bio-oil as an additive in wood pelletization: Group 1 uses heavy …

A Dual Perspective Towards Building Resilience In Manufacturing Organizations, Steven A. Fazio

Theses and Dissertations

Modern manufacturing organizations exist in the most complex and competitive environment the world has ever known. This environment consists of demanding customers, enabling, but resource intensive Industry 4.0 technology, dynamic regulations, geopolitical perturbations, and innovative, ever-expanding global competition. Successful manufacturing organizations must excel in this environment while facing emergent disruptions generated as biproducts of complex man-made and natural systems. The research presented in this thesis provides a novel two-sided approach to the creation of resilience in the modern manufacturing organization. First, the systems engineering method is demonstrated as the qualitative framework for building literature-derived organizational resilience factors into organizational structures …

The Development Of Authentic Virtual Reality Scenarios To Measure Individuals’ Level Of Systems Thinking Skills And Learning Abilities, Vidanelage L. Dayarathna

Theses and Dissertations

This dissertation develops virtual reality modules to capture individuals’ learning abilities and systems thinking skills in dynamic environments. In the first chapter, an immersive queuing theory teaching module is developed using virtual reality technology. The objective of the study is to present systems engineering concepts in a more sophisticated environment and measure students learning abilities. Furthermore, the study explores the performance gaps between male and female students in manufacturing systems concepts. To investigate the gender biases toward the performance of developed VR module, three efficacy measures (simulation sickness questionnaire, systems usability scale, and presence questionnaire) and two effectiveness measures (NASA …

Quantitative Characterization Of Complex Systems—An Information Theoretic Approach, Aditya Akundi, Eric Smith

Manufacturing & Industrial Engineering Faculty Publications and Presentations

A significant increase in System-of-Systems (SoS) is currently observed in the social and technical domains. As a result of the increasing number of constituent system components, Systems of Systems are becoming larger and more complex. Recent research efforts have highlighted the importance of identifying innovative statistical and theoretical approaches for analyzing complex systems to better understand how they work. This paper portrays the use of an agnostic twostage examination structure for complex systems aimed towards developing an information theorybased approach to analyze complex technical and socio-technical systems. Towards the goal of characterizing system complexity with information entropy, work was carried …

Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim

Electronic Theses, Projects, and Dissertations

Automobile collisions occur daily. We now live in an information-driven world, one where technology is quickly evolving. Blockchain technology can change the automotive industry, the safety of the motoring public and its surrounding environment by incorporating this vast array of information. It can place safety and efficiency at the forefront to pedestrians, public establishments, and provide public agencies with pertinent information securely and efficiently. Other industries where Blockchain technology has been effective in are as follows: supply chain management, logistics, and banking. This paper reviews some statistical information regarding automobile collisions, Blockchain technology, Smart Contracts, Smart Cities; assesses the feasibility …

Identifying An Optimization Technique For Maker Usage To Address Covid-19 Supply Shortfalls, Michael J. Wilson

Doctoral Dissertations

Fused Deposition Modeling (FDM) can be purchased for under five hundred dollars. The availability of these inexpensive systems has created a large hobbyist (or maker) community. For makers, FDM printing is used numerous uses.

With the onset of the COVID-19 pandemic, the needs for Personal Protective Equipment (PPE) skyrocketed. COVID-19 mitigation strategies such as social distancing, businesses closures, and shipping delays created significant supply shortfalls. The maker community stepped in to fill gaps in PPE supplies.

In the case of 3DP, optimization remains the domain of commercial entities. Optimization is, at best, ad-hoc for makers. With the need to PPE …

Forecasting Nigeria's Electricity Demand And Energy Efficiency Potential Under Climate Uncertainty, Olawale Olabisi

Doctoral Dissertations

The increasing population and socio-economic growth of Nigeria, coupled with the current, unmet electricity demand, requires the need for power supply facilities expansion. Of all Nigeria’s electricity consumption by sector, the residential sector is the largest and growing at a very fast rate. To meet this growing demand, an accurate estimation of the demand into the future that will guide policy makers to adequately plan for the expansion of electricity supply and distribution, and energy efficiency standards and labeling must be made. To achieve this, a residential electricity demand forecast model that can correctly predict future demand and guide the …

Change Sustainment Model (Csm) To Address Industry 4.0 In A Classified Environment, Hamilton Ervin

Electronic Theses and Dissertations, 2020-

Business and engineering have long intersected with each other in industry. In actuality, they are inseparable. That notion drove the thought process and actions taken to observe phenomena within a U.S. Fortune 500, Aerospace & Defense industry, Department of Defense, independent contractor. In Aerospace & Defense, the ability to implement technology freely and change to address an ever-evolving technological landscape in the world has proven to be difficult given the nature of the work performed. U.S. national security must be protected at all times, therefore information sharing guided by a "need-to-know" basis create an inability to easily implement organizational change …

Predicting Zero Bin In The Semiconductor Manufacturing Industry: Machine Learning Algorithms, Yazmin Montoya

Open Access Theses & Dissertations

The semiconductor industry has faced supply chain manufacturing shortages that ultimately led to a worldwide chip shortage during the COVID-19 pandemic. These chip manufacturers use sophisticated and advanced manufacturing machinery in their fabs to manufacture chips. As experienced during the pandemic, manufacturing unavailability is often due to the lack of critical manufacturing-related spare parts. This thesis evaluates the effectiveness of machine learning algorithms to identify significant factors contributing to manufacturing part outages (i.e., zero-bin) to keep manufacturing equipment running at total capacity within the organization. We propose clustering methods to segment the data and use logistic regression, logistic lasso regression, …

Advanced Analytics In Smart Manufacturing: Anomaly Detection Using Machine Learning Algorithms And Parallel Machine Scheduling Using A Genetic Algorithm, Meiling He

Theses and Dissertations

Industry 4.0 offers great opportunities to utilize advanced data processing tools by generating Big Data from a more connected and efficient data collection system. Making good use of data processing technologies, such as machine learning and optimization algorithms, will significantly contribute to better quality control, automation, and job scheduling in Smart Manufacturing. This research aims to develop a new machine learning algorithm for solving highly imbalanced data processing problems, implement both supervised and unsupervised machine learning auto-selection frameworks for detecting anomalies in smart manufacturing, and develop a genetic algorithm for optimizing job schedules on unrelated parallel machines. This research also …

Development Of Metaheuristic Algorithms For The Efficient Allocation Of Power Flow Control Devices, Eduardo Jose Castillo Fatule

Open Access Theses & Dissertations

Modern energy grids have become extremely complex systems, requiring more variable and active flow control. As a remedy to this, Distributed Flexible AC Transmission Systems (D-FACTS) are cost-efficient devices used to mitigate power flow congestion and integrate renewable energies. The objective of this research is then to propose an efficient multiple objective evolutionary algorithm to solve a stochastic model for D-FACTS allocation, which aims to optimize various objectives related to cost, grid health, and environmental impacts. The model was implemented on a modified RTS-96 test system, and the results show that optimally allocating D-FACTS modules using the proposed model can …

Supply Chain Optimization Of A Local Small Business From The Food-Service Industry Using Simulation Models, Aimee Montalvo

Open Access Theses & Dissertations

Various supply chain disruptions can cause revenue losses, low productivity, and damaged reputations. Some examples of such disruptions include increased supply costs, labor shortages, pandemics, natural disasters, or transportation delays. For instance, during the COVID-19 pandemic, several small and medium enterprises (SMEs) suffered greatly from labor shortages, delayed and costly supplies, and decreased demand. In this research, we present a case study of a small local business from the fast-food industry that experienced the loss of employees and delays and analyzed the increased cost of supplies. We created visualization modules with the SMEs supply chain performance measures to see the …

Decomposition Approach To Parametric Nonconvex Regression; Nuclear Resonance Analysis, Jordan L. Armstrong

Masters Theses

Parameterized nonconvex regression is a difficult problem for any optimization solver packages, often resulting in approximations and linearizations of the problem in order to be able to arrive a solution, if the problem is even solvable at all. These changes to the initial problem are largely dependent upon having appropriate domain knowledge and still often times result in a sizable gap between the achieved solution and the best true solution. We propose a novel method of decomposing the global problem into small, overlapping windows. Thus, the independent windows are now solvable. Subsequently, we offer a novel, sequential method of parameter …

Covid Response: Iterative Model Development In The Deployment Of Hand Sanitation Stations At A Large Public University, Tyler Obrien

All Theses

This study illustrates the significance of iterative model development using the deployment of hand sanitizer stations in buildings at Clemson University as a case study. The COVID-19 problem affected Clemson University, a major institution, in several ways requiring adaptations to existing policies and procedures to take place. Following guidelines provided by the Centers for Disease and Control (CDC), the university implemented several new strategies including placing hand sanitizer stations in several buildings on campus in order to try and mitigate the transmission of the virus. This study focuses on learning how the initial decision-making took place to then design a …

Understanding The Behavior Of The Covid-19 Pandemic Using Data Analytics, Mohammad Reza Davahli

Electronic Theses and Dissertations, 2020-

In December 2019, China announced the breakout of a new virus identified as coronavirus SARS-CoV-2 (COVID-19), which soon grew exponentially and became a global pandemic. Despite strict actions to mitigate the spread of the virus in various countries, the COVID-19 pandemic resulted in a significant loss of human life in 2020 and 2021. To better understand the pandemic, this doctoral research incorporated data analytics to evaluate the behavior and impacts of the virus. The doctoral research contributed to the scientific body of the knowledge in different ways including (1) presenting a systematic literature review of current research and topics about …

Framework Of Big Data Analytics In Real Time For Healthcare Enterprise Performance Measurements, Ahmed Mohamed

Electronic Theses and Dissertations, 2020-

Healthcare organizations (HCOs) currently have many information records about their patients. Yet, they cannot make proper, faster, and more thoughtful conclusions in many cases with their information. Much of the information is structured data such as medical records, historical data, and non-clinical information. This data is stored in a central repository called the Data Warehouse (DW). DW provides querying and reporting to different groups within the healthcare organization to support their future strategic initiatives. The generated reports create metrics to measure the organization's performance for post-action plans, not for real-time decisions. Additionally, healthcare organizations seek to benefit from the semi-structured …

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 …

Assessment Of Leadership Styles And Lean Six Sigma Critical Success Factors In The Aerospace And Defense Industry, Corey Gellis

Electronic Theses and Dissertations, 2020-

The Aerospace and Defense industry has shifted into a global competitive market that is prioritizing innovative advancements in technological capabilities. Corporations are now having to further develop customer focused strategies based in adding value while reducing costs. Large manufacturing corporations often embrace continuous improvement methodologies, such as Lean Six Sigma, for process improvement. Many organizations have received minimal benefit from the methodology which may link back to leadership and culture. This research examined which styles of leadership are most effective when trying to gain the most value from Lean Six Sigma within manufacturing. The research study surveyed 112 black belt …

A Vision-Based Quality Control Model For Manufacturing Systems, Alejandra Figueroa-Lopez

Morehead State Theses and Dissertations

A thesis presented to the faculty of the College of Business and Technology at Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Alejandra Figueroa-Lopez on November 25, 2021.

Drug-Based Therapeutic Strategies For Covid-19-Infected Patients And Their Challenges, Khatereh Zarkesh, Elaheh Entezar-Almahdi, Parisa Ghasemiyeh, Mohsen Akbarian, Marzieh Bahmani, Shahrzad Roudaki, Rahil Fazlinejad, Soliman Mohammadi-Samani, Negar Firouzabadi, Majid Hosseini, Fatemeh Farjadian

Manufacturing & Industrial Engineering Faculty Publications and Presentations

Emerging epidemic-prone diseases have introduced numerous health and economic challenges in recent years. Given current knowledge of COVID-19, herd immunity through vaccines alone is unlikely. In addition, vaccination of the global population is an ongoing challenge. Besides, the questions regarding the prevalence and the timing of immunization are still under investigation. Therefore, medical treatment remains essential in the management of COVID-19. Herein, recent advances from beginning observations of COVID-19 outbreak to an understanding of the essential factors contributing to the spread and transmission of COVID-19 and its treatment are reviewed. Furthermore, an in-depth discussion on the epidemiological aspects, clinical symptoms …

Design And Analysis Of The Virtual Reality Welding Training, Ritesh Chakradhar

Morehead State Theses and Dissertations

A thesis presented to the faculty of the College of Business and Technology at Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Ritesh Chakradhar on November 19, 2021.

A Framework Of Dynamic Data Driven Digital Twin For Complex Engineering Products: The Example Of Aircraft Engine Health Management, Zhenhua Wu, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications and Presentations

Digital twin is a vital enabling technology for smart manufacturing in the era of Industry 4.0. Digital twin effectively replicates its physical asset enabling easy visualization, smart decision-making and cognitive capability in the system. In this paper, a framework of dynamic data driven digital twin for complex engineering products was proposed. To illustrate the proposed framework, an example of health management on aircraft engines was studied. This framework models the digital twin by extracting information from the various sensors and Industry Internet of Things (IIoT) monitoring the remaining useful life (RUL) of an engine in both cyber and physical domains. …

Systems Statistical Engineering – Hierarchical Fuzzy Constraint Propagation, Hengameh Fakhravar, Hesamoddin Tahami

Engineering Management & Systems Engineering Faculty Publications

Driven by a growing requirement during the 21st century for the integration of rigorous statistical analyses in engineering research, there has been a movement within the statistics and quality communities to evolve a unified statistical engineering body of knowledge (Hoerl & Snee, 2010). Systems Statistical Engineering research seeks to integrate causal Bayesian hierarchical modeling (Pearl, 2009) and cybernetic control theory within Beer's Viable System Model (S Beer, 1972; Stafford Beer, 1979, 1985) and the Complex Systems Governance framework (Keating, 2014; Keating & Katina, 2015, 2016) to produce multivariate systemic models for robust dynamic systems mission performance. (Cotter & Quigley, 2018) …

Optimization In The Application Of Varnishes Barrier On Cartonboard Packaging, Andre Ramalheiro De Andrade, Maria Isabel Rodrigues Phd, Eduardo Luiz Machado Phd

Journal of Applied Packaging Research

In this work adjustments in the rotogravure printing process are proposed to the varnish water vapor transmission rate (WVTR) aiming to obtain results smaller than 20g/m²/24h. One case study was used for the propositions for improvements, where focused on varnish application process in a gravure printer for an eight-printing unit cartonboard packaging, maximum printing speed of 175 m/min and a 285 g/m² weight cartonboard. The possible variables that influenced the WVTR result were selected from the technical expertise of the people involved in the project, the analysis in the printing process with the application of directed trials using experimental designs …