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Full-Text Articles in Industrial Engineering

Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson Aug 2022

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 …


Assessing The Influence Of Health Policy And Population Mobility On Covid-19 Spread In Arkansas, Tayden Barretto May 2022

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 …


Implementing The Cms+ Sports Rankings Algorithm In A Javafx Environment, Luke Welch May 2022

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. …


Supervised Representation Learning For Improving Prediction Performance In Medical Decision Support Applications, Phawis Thammasorn May 2022

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 …


Deep Learning Object-Based Detection Of Manufacturing Defects In X-Ray Inspection Imaging, Juan C. Parducci May 2022

Deep Learning Object-Based Detection Of Manufacturing Defects In X-Ray Inspection Imaging, Juan C. Parducci

Mechanical & Aerospace Engineering Theses & Dissertations

Current analysis of manufacturing defects in the production of rims and tires via x-ray inspection at an industry partner’s manufacturing plant requires that a quality control specialist visually inspect radiographic images for defects of varying sizes. For each sample, twelve radiographs are taken within 35 seconds. Some defects are very small in size and difficult to see (e.g., pinholes) whereas others are large and easily identifiable. Implementing this quality control practice across all products in its human-effort driven state is not feasible given the time constraint present for analysis.

This study aims to identify and develop an object detector capable …


Simulation, Optimization, And Economic Assessment Of Pelamis Wave Energy Converter, Hana Ghaneei, Mohammadreza Mahmoudi Apr 2022

Simulation, Optimization, And Economic Assessment Of Pelamis Wave Energy Converter, Hana Ghaneei, Mohammadreza Mahmoudi

Faculty Articles, Papers, and Other Scholarship

Wave energy and power is accessible on almost any body of water. One of the most widely known floating structures to generate renewable energy from the seas and the ocean is wave energy converter Pelamis. In this study, an attempt was made to simulate the dynamic behaviour of Pelamis P2 in the software AQWA under the influence of a nonlinear second-order Stokes wave. Pelamis P2 was simulated in different marine conditions including different water depths, wave heights, periods, and angles to assess its optimal operation. With the results in mind, it can be argued that with an increase in water …


The Traveling Salesman Problem: An Analysis And Comparison Of Metaheuristics And Algorithms, Mason Helmick Apr 2022

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.


Predicting Tf33-Pw-100a Engine Failures Due To Oil Issues Using Survival Analyses, Anna M. Davis Mar 2022

Predicting Tf33-Pw-100a Engine Failures Due To Oil Issues Using Survival Analyses, Anna M. Davis

Theses and Dissertations

In 2007, the Office of the Assistant Secretary of Defense for Sustainment pushed for the need to transition to a Condition Based Maintenance Plus (CBM ) initiative for weapon systems in the U.S. Department of Defense. The CBM initiative can help increase aircraft availability (AA) for the United States Air Force. There are many reasons where AA can be affected but one such issue is engine availability primarily due to oil issues. Within the CBM perspective, this study examines the risk of a jet engine failure due to an oil issue and attempts to predict an engines time until next …


Efficient Removal Of Lead Ions From Aqueous Media Using Sustainable Sources On Marine Algae, Hannah Namkoong, Erik Biehler, Gon Namkoong, Tarek M. Abdel-Fattah Jan 2022

Efficient Removal Of Lead Ions From Aqueous Media Using Sustainable Sources On Marine Algae, Hannah Namkoong, Erik Biehler, Gon Namkoong, Tarek M. Abdel-Fattah

Electrical & Computer Engineering Faculty Publications

The goal of this project is to explore a new method to efficiently remove Pb(II) ions from water by processing Undaria pinnatifida into immobilized beads using sodium alginate and calcium chloride. The resulting biosorbent was characterized by Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS). Using immobilized U. pinnatifida, we investigated the effect of various factors on Pb(II) ion removal efficiency such as temperature, pH, ionic strength, time, and underlying biosorption mechanisms. For Pb(II) ion biosorption studies, Pb(II) ion biosorption data were obtained and analyzed using Langmuir and Freundlich adsorption models. It …


Exploring Cyber-Physical Systems’ Security Governance In The Oil And Gas Industry, Soliman Mahmoud Jan 2022

Exploring Cyber-Physical Systems’ Security Governance In The Oil And Gas Industry, Soliman Mahmoud

Walden Dissertations and Doctoral Studies

The Fourth Industrial Revolution, which utilizes modern communication-dependent technologies, including cyber-physical systems (CPS), has made exploration and production operations more efficient in the oil and gas industry. CPS in this industry should be secured against operational threats to prevent interruption of critical oil and gas supplies and services. However, these systems are vulnerable to cyberattacks, and many oil and gas companies have not incorporated effective cybersecurity measures into their corporate management strategies. This qualitative, multiple-case study, which was guided by the routine activity theory, explored how cybersecurity governance was applied to develop controls that stopped or mitigated the consequences of …


Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa Dec 2021

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 …


The Development Of Authentic Virtual Reality Scenarios To Measure Individuals’ Level Of Systems Thinking Skills And Learning Abilities, Vidanelage L. Dayarathna Dec 2021

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 …


Statistical Modeling, Learning And Computing For Stochastic Dynamics Of Complex Systems, Mohammadmahdi Hajiha Dec 2021

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 …


Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim Dec 2021

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 …


Manufacturing: The Qualitative Study Of A Transition To A Green Facility, Brandon David Staves Oct 2021

Manufacturing: The Qualitative Study Of A Transition To A Green Facility, Brandon David Staves

Masters Theses & Specialist Projects

This qualitative study focused on answering three core questions: How have facilities reduce pollutions in regards to the quality of air, water, land, light and noise? Which Types of pollution reduction projects are more or less successful to implement? What types of pollution are facilities focusing on and why? The results of the 15 companies surveyed show a variety of projects that facilities have used to reduce pollution, it also shows that cost is a major factor in the unsuccessful projects, and that facilities are actively focused on reducing Air, Land, and Water pollution. While the data shows a variety …


High-Density Parking For Autonomous Vehicles., Parag J. Siddique Aug 2021

High-Density Parking For Autonomous Vehicles., Parag J. Siddique

Electronic Theses and Dissertations

In a common parking lot, much of the space is devoted to lanes. Lanes must not be blocked for one simple reason: a blocked car might need to leave before the car that blocks it. However, the advent of autonomous vehicles gives us an opportunity to overcome this constraint, and to achieve a higher storage capacity of cars. Taking advantage of self-parking and intelligent communication systems of autonomous vehicles, we propose puzzle-based parking, a high-density design for a parking lot. We introduce a novel method of vehicle parking, which leads to maximum parking density. We then propose a heuristic method …


A Machine Learning Approach To Understanding Emerging Markets, Namita Balani Jul 2021

A Machine Learning Approach To Understanding Emerging Markets, Namita Balani

Graduate Theses and Dissertations

Logistic providers have learned to efficiently serve their existing customer bases with optimized routes and transportation resource allocation. The problem arises when there is potential for logistics growth in an emerging market with no previous data. The purpose of this work is to use industry data for previously known and well-documented markets to apply data analytic techniques such as machine learning to investigate the uncertainty in a new market. The thesis looks into machine learning techniques to predict miles per stop given historical data. It mainly focuses on Random Forest Regression Analysis, but concludes that additional techniques, such as Polynomial …


Knowledge Discovery From Complex Event Time Data With Covariates, Samira Karimi Jul 2021

Knowledge Discovery From Complex Event Time Data With Covariates, Samira Karimi

Graduate Theses and Dissertations

In particular engineering applications, such as reliability engineering, complex types of data are encountered which require novel methods of statistical analysis. Handling covariates properly while managing the missing values is a challenging task. These type of issues happen frequently in reliability data analysis. Specifically, accelerated life testing (ALT) data are usually conducted by exposing test units of a product to severer-than-normal conditions to expedite the failure process. The resulting lifetime and/or censoring data are often modeled by a probability distribution along with a life-stress relationship. However, if the probability distribution and life-stress relationship selected cannot adequately describe the underlying failure …


Scheduling Allocation And Inventory Replenishment Problems Under Uncertainty: Applications In Managing Electric Vehicle And Drone Battery Swap Stations, Amin Asadi Jul 2021

Scheduling Allocation And Inventory Replenishment Problems Under Uncertainty: Applications In Managing Electric Vehicle And Drone Battery Swap Stations, Amin Asadi

Graduate Theses and Dissertations

In this dissertation, motivated by electric vehicle (EV) and drone application growth, we propose novel optimization problems and solution techniques for managing the operations at EV and drone battery swap stations. In Chapter 2, we introduce a novel class of stochastic scheduling allocation and inventory replenishment problems (SAIRP), which determines the recharging, discharging, and replacement decisions at a swap station over time to maximize the expected total profit. We use Markov Decision Process (MDP) to model SAIRPs facing uncertain demands, varying costs, and battery degradation. Considering battery degradation is crucial as it relaxes the assumption that charging/discharging batteries do not …


Modeling And Solving The Outsourcing Risk Management Problem In Multi-Echelon Supply Chains, Arian A. Nahangi Jun 2021

Modeling And Solving The Outsourcing Risk Management Problem In Multi-Echelon Supply Chains, Arian A. Nahangi

Master's Theses

Worldwide globalization has made supply chains more vulnerable to risk factors, increasing the associated costs of outsourcing goods. Outsourcing is highly beneficial for any company that values building upon its core competencies, but the emergence of the COVID-19 pandemic and other crises have exposed significant vulnerabilities within supply chains. These disruptions forced a shift in the production of goods from outsourcing to domestic methods.

This paper considers a multi-echelon supply chain model with global and domestic raw material suppliers, manufacturing plants, warehouses, and markets. All levels within the supply chain network are evaluated from a holistic perspective, calculating a total …


Improving Logistics Efficiency Through Collaborative Truck Routing, Patrick Dougherty May 2021

Improving Logistics Efficiency Through Collaborative Truck Routing, Patrick Dougherty

Industrial Engineering Undergraduate Honors Theses

The logistics industry is among the world’s largest and most essential. Specifically, trucking is a massive component of the modern logistics system. In 2012, truck transportation carried 68% of all freight tonnage in the U.S. However, trucking currently faces significant problems with efficiency and sustainability. Of all miles driven by trucks yearly in the U.S., 25% are driven with empty loads and 36% are driven with underutilized loads. In addition to this economic inefficiency, the industry faces social and environmental challenges. Driver turnover rates are near 100%, and trucking accounts for a significant level of greenhouse gas emissions. One potential …


A Dynamic Programming Approach To Determine Optimum Modularity Level In Industrial Packaging, Marshal Louie, Kumar B Mar 2021

A Dynamic Programming Approach To Determine Optimum Modularity Level In Industrial Packaging, Marshal Louie, Kumar B

Journal of Applied Packaging Research

Modular packaging facilitate customization for accommodating variable product sizes in a product family. When determining package sizes for product variability, packaging engineers does not find difficulty to determine package dimension for less product variety whereas if the product variety is more, then determining the dimension of modular package involves complex decision-making and time-consuming process to find the optimal solution. This in turn directly impacts the overall lead time of the supply chain. Thus, in this paper a dynamic programming is developed to determine the quantity and dimension of modular packages for every demand of assorted products sizes. The program helps …


A Two-Warehouse Inventory Model With Rework Process And Time-Varying Demand, Nurnadiah Nurhasril Jan 2021

A Two-Warehouse Inventory Model With Rework Process And Time-Varying Demand, Nurnadiah Nurhasril

Student Works (2020-2029)

It is commonly assumed that in a classical inventory model, all items produced during a production cycle are of perfect items. However, contradictory to reality, production processes are not perfect at all times, hence resulting in the production of defectives. In order to minimise the cost incurred and reduce wastage in a production process, we might consider a rework process to be implemented on the defective items. Besides that, most classical inventory models also consider the assumption that the available storage facility has an unlimited capacity. Conversely, in reality an additional storage space commonly known as a rented warehouse (RW) …


Agile Software Development: Creating A Cost Of Delay Framework For Air Force Software Factories, J. Goljan, Jonathan D. Ritschel, Scott Drylie, Edward D. White Jan 2021

Agile Software Development: Creating A Cost Of Delay Framework For Air Force Software Factories, J. Goljan, Jonathan D. Ritschel, Scott Drylie, Edward D. White

Faculty Publications

The Air Force software development environment is experiencing a paradigm shift. The 2019 Defense Innovation Board concluded that speed and cycle time must become the most important software metrics if the US military is to maintain its advantage over adversaries.1 This article proposes utilizing a cost-o­f-d­elay (CoD) framework to prioritize projects toward optimizing readiness. Cost-­of-d­elay is defined as the economic impact resulting from a delaying product delivery or, said another way, opportunity cost. In principle, CoD assesses the negative impacts resulting from changes to the priority of a project.


Strategies For Implementing Internet Of Things Devices In Manufacturing Environments, Todd Efrain Hernandez Jan 2021

Strategies For Implementing Internet Of Things Devices In Manufacturing Environments, Todd Efrain Hernandez

Walden Dissertations and Doctoral Studies

The Internet of Things (IoT) has been exploited as a threat vector for cyberattacks in manufacturing environments. Manufacturing industry leaders are concerned with cyberattacks because of the associated costs of damages and lost production for their organizations. Grounded in the general systems theory, the purpose of this multiple case study was to explore strategies electrical controls engineers use to implement secure IoT devices in manufacturing environments. The study participants were eight electrical controls engineers working in three separate manufacturing facilities located in the Midwest region of the United States. The data were collected by semistructured interviews and 15 organizational documents. …


The Utilization Of Shared Energy Storage In Energy Systems: Design, Modeling And Optimization, Rui Dai Nov 2020

The Utilization Of Shared Energy Storage In Energy Systems: Design, Modeling And Optimization, Rui Dai

USF Tampa Graduate Theses and Dissertations

Energy storage (ES) plays a significant role in modern smart grids and energy systems. With the advances of ES technologies, efficiently applying ES to energy systems has become the bottleneck for achieving the benefits of ES. The traditional approach of utilizing ES is the so-called distributed framework in which there is a separate ES for each individual user. Due to the inherent limits in the distributed framework such as cost inefficiency and space limitations, many studies have promoted to utilize a shared ES in energy systems to further exploit the potentials of ES. However, current studies always focus on maximizing …


Improvement Of The Effectiveness Of Greywacke Crushing Process By Applying An Impact Crusher In Quarry For The Production Of Railway Ballast, Krzysztof Kurus, Karolina Jąderko-Skubis Nov 2020

Improvement Of The Effectiveness Of Greywacke Crushing Process By Applying An Impact Crusher In Quarry For The Production Of Railway Ballast, Krzysztof Kurus, Karolina Jąderko-Skubis

Journal of Sustainable Mining

The production of aggregates in rock mining requires an optimal system of crushers, separators and conveyors. Proper machine selection allows to obtain aggregates with appropriate technical parameters and increase the output of required fractions with a given unit cost. The usage of rock raw materials for the production of railway ballast used in the railway track superstructure is connected with the necessity to meet strictly defined quality requirements.

This paper presents an example of the use of an impact crusher in a selected quarry for the purpose of obtaining the correct parameters of railway ballast and a suitable grain curve. …


Data Is Personal: We Should Treat It As Such, Kaleb Dunn Sep 2020

Data Is Personal: We Should Treat It As Such, Kaleb Dunn

Student Papers in Public Policy

The rise of the internet as a fact of daily life is the defining element of the modern age. Widespread use of the internet has fundamentally altered entire industries, and much of American life has migrated online. Dating is augmented by online dating; shopping by online shopping; television by internet streaming.

The digitization of American life has brought with it considerable benefits, including great convenience and innumerable efficiencies, but it has not come without a cost. Although there are many business models used by internet companies, many of the now-largest companies in the world have converged on one entity upon …


Combining Machine Learning And Empirical Engineering Methods Towards Improving Oil Production Forecasting, Andrew J. Allen Jul 2020

Combining Machine Learning And Empirical Engineering Methods Towards Improving Oil Production Forecasting, Andrew J. Allen

Master's Theses

Current methods of production forecasting such as decline curve analysis (DCA) or numerical simulation require years of historical production data, and their accuracy is limited by the choice of model parameters. Unconventional resources have proven challenging to apply traditional methods of production forecasting because they lack long production histories and have extremely variable model parameters. This research proposes a data-driven alternative to reservoir simulation and production forecasting techniques. We create a proxy-well model for predicting cumulative oil production by selecting statistically significant well completion parameters and reservoir information as independent predictor variables in regression-based models. Then, principal component analysis (PCA) …


Models For Data Analysis In Accelerated Reliability Growth, Cesar Alexander Ruiz Torres Jul 2020

Models For Data Analysis In Accelerated Reliability Growth, Cesar Alexander Ruiz Torres

Graduate Theses and Dissertations

This work develops new methodologies for analyzing accelerated testing data in the context of a reliability growth program for a complex multi-component system. Each component has multiple failure modes and the growth program consists of multiple test-fix stages with corrective actions applied at the end of each stage. The first group of methods considers time-to-failure data and test covariates for predicting the final reliability of the system. The time-to-failure of each failure mode is assumed to follow a Weibull distribution with rate parameter proportional to an acceleration factor. Acceleration factors are specific to each failure mode and test covariates. We …