Operations Research, Systems Engineering and Industrial Engineering Commons^™

Enhancing Diversity And Inclusion In Computer Science Undergraduate Programs: The Role Of Admissions, Ouldooz Baghban Karimi, Giulia Toti, Mirela Gutica, Rebecca Robinson, Lisa Zhang, James Paterson, Peggy Lindner, Michael O'Dea

Engineering Management and Systems Engineering Faculty Research & Creative Works

Despite continued efforts to further the participation of women in Computer Science (CS), progress has been limited during the past decades. Recent efforts have been focused on recruitment and retention, with a notable gap in exploring the impact of admissions processes on diversity and inclusion. Through an extensive literature review, contextual analysis of public admissions data from 40 universities across four regions around the world, and qualitative and quantitative analysis on surveys and interviews, we explored the role of admissions in enhancing diversity and inclusion in CS undergraduate programs. Our findings highlight the role of financials, the possible positive effects …

A Systems Approach To Process Design And Sustainability - Synergy Via Pollution Prevention, Control, And Source Reduction, Emmanuel Apau Aboagye

Theses and Dissertations

Historically, process design prioritized efficiency and profitability, often overlooking environmental and societal implications. However, given the global challenges like climate change and resource scarcity, there is a growing emphasis on embedding sustainability into process design. Adopting a systems-oriented approach provides a comprehensive view, spanning from raw material acquisition to end-of-life product management. Such an approach not only identifies potential sustainability challenges but ensures that solutions foster both environmental responsibility and economic viability. In this study, a comprehensive framework for designing industrial systems is introduced, aiming to encompass the entire lifecycle impacts of chemical processes. The research initially delves into two …

Improved Brain-Storm Optimizer For Disassembly Line Balancing Problems Considering Hazardous Components And Task Switching Time, Ziyan Zhao, Pengkai Xiao, Jiacun Wang, Shixin Liu, Xiwang Guo, Shujin Qin, Ying Tang

Henry M. Rowan College of Engineering Departmental Research

Disassembling discarded electrical products plays a crucial role in product recycling, contributing to resource conservation and environmental protection. While disassembly lines are progressively transitioning to automation, manual or human–robot collaborative approaches still involve numerous workers dealing with hazardous disassembly tasks. In such scenarios, achieving a balance between low risk and high revenue becomes pivotal in decision making for disassembly line balancing, determining the optimal assignment of tasks to workstations. This paper tackles a new disassembly line balancing problem under the limitations of quantified penalties for hazardous component disassembly and the switching time between adjacent tasks. The objective function is to …

Essays In Robust Optimization With Applications To Finance And Renewable Energy, Hao Jiang

Operations Research and Engineering Management Theses and Dissertations

Real-world optimization problems are often sensitive to uncertainties caused by estimation errors, forecasting inaccuracy, and imprecise data information. These uncertainties bring significant challenges to decision-making in many areas. Robust optimization (RO) is a tool for addressing the challenges of parameter uncertainty. In this dissertation, we focus on the studies of RO on two problems. (1) In the study of finance, we proposed a tractable RO model for a Mean-Variance portfolio selection problem. We consider Markowitz's Mean-Variance Optimization when stock returns are modeled using Sharpe's single-index framework, but the model coefficients Alpha and Beta, are not precisely known. This study assumes …

An Investigation Into Applications Of Canonical Polyadic Decomposition & Ensemble Learning In Forecasting Thermal Data Streams In Direct Laser Deposition Processes, Jonathan Storey

Theses and Dissertations

Additive manufacturing (AM) is a process of creating objects from 3D model data by adding layers of material. AM technologies present several advantages compared to traditional manufacturing technologies, such as producing less material waste and being capable of producing parts with greater geometric complexity. However, deficiencies in the printing process due to high process uncertainty can affect the microstructural properties of a fabricated part leading to defects. In metal AM, previous studies have linked defects in parts with melt pool temperature fluctuations, with the size of the melt pool and the scan pattern being key factors associated with part defects. …

Industrial Design, Husnain Khan

Publications and Research

Universal design is important because it helps with diverse disabilities. What is universal design and why do we need it? People design buildings, products or environments to make them accessible to people in need. Also, it minimizes the need for assistive technology, results in products compatible with assistive technology, and makes products more usable by everyone. Where can universal design be found? It's practical everywhere you go, such as public transport, parks, shops and services, and sidewalks. Universal design is affected by Several categories: people with disabilities, who are perhaps the most visible group affected by universal design, and parents …

A Human Factors Approach To Improve Layout Design For A Virtual Reality-Based Training Platform, Md Humaun Kobir, Taufiq Rahman, Yiran Yang, Shuchisnigdha Deb

SAGE Open Access Agreement Publications-Archive

In manufacturing industries, equipment arrangement, and layout design are critical factors that directly influence productivity, workplace safety, and workers’ performance. Link analysis, as a human factors approach, has been widely used in industries for many years to improve layout design and machinery arrangement. This approach considers humans' physical and cognitive capabilities and movement limitations to find an optimal design. Virtual reality significantly impacts our society from product design to worker training. Hence, effective virtual training platforms require the same attention to layout design as manufacturing work settings which offer efficient testing of multiple layouts. This research focuses on developing a …

Imerys: Tube Mill Optimization Project, Ryan Waltman, Dalton Beasley, Dyson Beasley, Tristan Mcmichael

Senior Design Project For Engineers

The Tube Mill Optimization Project is in partnership with Imerys for Tube Mill 81 at their Marble Hill site in Georgia. Tube Mill 81 is a dry ball mill that operates 24/7 and makes an intermediary product for Plant 3. Tube Mill 81 needs quality improvement and a production rate increase to meet demand. Imerys’s quality specification is between a particle size of 12-18 microns and an acceptable production rate of 5 tons per hour. This project focuses on the development and implementation of three solutions: increase the amps on the separator to increase production, replace missing classifier blades in …

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 …

Ethical Implications Of Ai-Based Algorithms In Recruiting Processes: A Study Of Civil Rights Violations Under Title Vii And The Americans With Disabilities Act, Vanessa Rodriguez

Cyber Operations and Resilience Program Graduate Projects

This research paper analyzes the ethical implications of utilizing artificial intelligence, specifically AI-based algorithms in business selection and recruiting processes, with a focus on potential violations under Title VII of the Civil Rights Act of 1964 and Title 1 of the Americans with Disabilities Act (ADA). Amazon’s attempt at launching AI recruiting tools is examined. This paper will assess the fairness of AI recruiting practices, considering data collection, potential biases, and accuracy concerns in its implementation process. Additionally, the paper will provide an overview of federal civil rights statutes enforced by the U.S. Equal Employment Opportunity Commission (EEOC) and recent …

Automated Usability Evaluation Utilizing Log Files And Data Mining Techniques., Sima Shafaei

Electronic Theses and Dissertations

Usability evaluation is one of the essential aspects of software production. This evaluation should be done during the entire life cycle of a software application, from pre-production to production and post-production. However, the collection and evaluation of usability data can be a very challenging, time-consuming, and expensive task to be conducted manually, particularly for certain types of products and working conditions. These challenges may include the need to recruit participants fully engage and motivate them during evaluation, and factor in environmental conditions. Other challenges may include collecting data in real-world environments, especially when the users are geographically dispersed, minimizing evaluator …

Probabilistic Multivariate Time Series Forecasting And Robust Uncertainty Quantification With Applications In Electricity Price Prediction, Jie Han

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Electricity price forecasting (EPF) is a crucial task for market participants seeking informed decisions in day-ahead electricity markets. The increasing penetration of stochastic renewable energy and the deregulation of electricity markets pose challenges to electricity price forecasting. Given the dependence of electricity prices on stochastic factors such as weather conditions, market dynamics, and customer behaviors, deterministic forecasting methods offer limited insight into the potential future states of energy prices in highly stochastic markets. In this study, a transformer-based electricity price forecasting (TDEPF) model was developed, utilizing a two-step training process and demonstrating superior performance compared to typical RNN models. Subsequently, …

Federated Active Learning For Network Intrusion Detection, Matthew D. R. Sauer

Theses and Dissertations

This thesis addresses challenges with detecting attacks on computer networks within a Federated Learning (FL) framework, when labeled instances are few. We explore the integration of active learning (AL) and semi-supervised learning (SSL). AL efficiently uses data that would otherwise be wasted or require substantial time for labeling. SSL provides capacity to train models that have a limited amount of labeled data, by utilizing additional unlabeled data that is available. We show how FL combined with AL or SSL can realize a detection system that adapts and trains quickly to new networks, reducing the total amount of data labeling needed. …

An Improved Saliency Map With Trustworthiness For Localizing Abnormalities In Medical Imaging, Nolan C. Skelly

Theses and Dissertations

Saliency maps are a widely used methodology to make deep learning models more interpretable. They provide post-hoc explanations through identification of the most pertinent areas of an input medical image. These techniques have been assessed based on 1) localization utility, 2) sensitivity to model weight randomization, 3) repeatability, and 4) reproducibility. Ten saliency map techniques will be tested, Grad, Smooth Grad, Integrated Gradients, Smooth Integrated Gradients, XRAI, Grad-CAM, Guided Backpropagation, Guided GradCAM, GradCAM++, and ScoreCAM. The neural networks used to predict and read medical information require a reliable solution to provide medical practitioners intelligible results. Using the information of two, …

Barriers To Integrating Magnetic Resonance Imaging Systems In Emergency Medical Service Ambulances For Stroke Care, Arvind Kolangarakath

All Theses

Stroke is a life-threatening condition that can cause permanent damage by stopping blood flow in the brain. Quick and precise intervention is imperative, as every second lost increases tissue deterioration and impacts patient outcomes. Several technological advancements such as Magnetic Resonance Imaging (MRI), have revolutionized stroke care by enabling more accurate and quicker diagnoses in hospitals. Portable head MRI scanners with lower magnetic fields are a recent innovation capable of providing neuroimaging at the point of care within hospital settings. Integrating such a device into ambulances could potentially enhance stroke care during transit, facilitating prompt diagnosis and prognosis. However, few …

A Multi-Objective Stochastic Programming Model For Resilient And Sustainable Supply Chains Under Uncertainty, Mohammad H. Majdfaghihi

Dissertations

Supply chain resilience (SCRES) and sustainable supply chain management (SSCM) have garnered significant attention in the field of Supply Chain Management (SCM) science. This heightened interest is largely attributable to the increasing frequency and severity of uncertainty and disruptions in global supply chains. Resilience is a beneficial approach to managing uncertainties and preparing for and mitigating the adverse consequences of Supply Chain (SC) disruptions. Sustainability is a key concept in SCM, driven by governmental regulations and heightened stakeholder and customer concerns for environmental and societal well-being. Studies on SCRES have traditionally focused on preparing for and reacting to disruptions and …

A Study Of Group Effectiveness In A Virtual Reality Environment., Dalton Clay Sparks

Electronic Theses and Dissertations

Virtual Reality (VR) technology has revolutionized the study of team effectiveness, yet many studies in this domain lack a comprehensive approach, focusing narrowly on performance metrics. This thesis investigates VR team effectiveness by integrating traditional Team Effectiveness frameworks with VR-specific dynamics. Utilizing Data Envelopment Analysis (DEA) and Group Style Inventory (GSI), this study assesses teams within a VR environment, specifically a multiplayer submarine simulation game, IronWolfVR. Fifteen groups, totaling 45 participants, were observed for their collaborative gameplay, incorporating physiological measures (Heart Rate and Electrodermal Activity), team coordination dynamics, and various survey-based assessments (demographics, System Usability Scale, Simulator Sickness Questionnaire, and …

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 …

Optimal Route Planning Using Computer Simulation In The Context Of Distributor-To-Consumer Supply Network, Miriam Aguilera Nava

Open Access Theses & Dissertations

Effective route planning for distribution centers is a multifaceted challenge crucial tobusiness success, as it directly impacts time and cost savings while enhancing overall delivery efficiency. Oversight of proper planning can lead to problems and inefficiencies in the distribution process. Hence, this work undertakes a comparative experiment of two delivery strategies in a distributor-to-consumer supply network. While the first strategy investigates the delivery process by zip area, the second strategy considers the clustering of the areas for more streamlined delivery fulfillment. The effectiveness of the delivery process is gauged based on a set of metrics, including total distance traveled, average …

Finite Element Modeling And Analysis Of Perforated Steel Members Under Blast Loading, Mahmoud T. Nawar, Ayman El-Zohairy, Ibrahim T. Arafa

Faculty Publications

Perforated steel members (PSMs) are now frequently used in building construction due to their beneficial features, including their proven blast-resistance abilities. To safeguard against structural failures from explosions and terrorist threats, perforated steel beams (PSBs) and perforated steel columns (PSCs) offer a viable alternative to traditional steel members. This is attributed to their impressive energy absorption potential, a result of their combined high strength and ductile behavior. In this study, numerical examinations of damage assessment under the combined effects of gravity and blast loads are carried out to mimic real-world scenarios of external explosions close to steel structures. The damage …

Gaze Tracking Embedded Collaborative Robots For Automated Metrology And Reverse Engineering, Sachithra H. Karunathilake

Theses and Dissertations

Conventional geometric metrology, or three-dimensional (3D) scanning, and reverse engineering heavily rely on the experience of the operators. With an increasing need for automation, robot arms have been adopted for this task. However, due to the large variety of parts and designs, automated path planning could provide a scanning solution that may overlook the critical area, which could potentially deteriorate the scan results. This study explores the integration of collaborative robotics (cobots) with eye tracking technology to improve the autonomous 3D scanning process. The primary objective of this study is to enhance the accuracy and efficiency of cobots in …

A System Theoretic Process Analysis Framework And Model Based Approach For Resilient Space Architecture Design, Eric T. Sommer

Theses and Dissertations

As the capabilities provided by space-based systems offer significant contributions toward defense applications, potential adversaries stand to gain significant value in disrupting them. Therefore, the United States must pursue the development and operation of resilient space architectures, capable of delivering capabilities in the face of disruptions. To support this development, systems engineering methods require innovation to effectively ensure design of complex space architectures to meet their objectives. This thesis recommends and demonstrates a System-Theoretic Process Analysis (STPA) framework to qualitatively analyze space architectures. The analysis outputs identify design considerations, requirements, and constraints required for resilience. To enable a model-based systems …

Design Space Visualization And Exploration For Many Goal Problems Under Uncertainity, Niharika Balaji

Theses and Dissertations

ABSTRACT

Designing a complex engineered system is challenging due to many conflicting goals, uncertainties, and multiple interactions. Traditional optimization approaches often yield single-point solutions, which may not be suitable for early design stages due to their susceptibility to changes in conditions and uncertainties. To address this challenge, a satisficing approach is employed. This approach enables designers to effectively navigate the design space and identify satisficing solutions that balance conflicting goals in the face of uncertainties and changes in conditions. From a systems design perspective, we view design as an iterative process that involves making informed decisions based on available information …

Task Optimization Utilizing Digital Transformation Concepts - Automation Project Execution Via Agile Methodology, Anthony Steven Maiello

Theses and Dissertations

Task Optimization via the use of automated process improvements is becoming more widespread as more industries lean into the concepts surrounding digital transformation. This shift also necessitates a complementary adaptation in project management methodologies to support the rapid and ever-changing environment, requirements, and innovations. This thesis examines the effectiveness of Agile methodology in managing digital automation projects, with a specific focus placed on process improvements with systems engineering. It accomplished this by contrasting the original model, designed and derived utilizing traditional project management techniques, with the proposed model which is a direct result of the application of Agile project practices. …

Neural Airport Ground Handling, Yaoxin Wu, Jianan Zhou, Yunwen Xia, Xianli Zhang, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

Airport ground handling (AGH) offers necessary operations to flights during their turnarounds and is of great importance to the efficiency of airport management and the economics of aviation. Such a problem involves the interplay among the operations that leads to NP-hard problems with complex constraints. Hence, existing methods for AGH are usually designed with massive domain knowledge but still fail to yield high-quality solutions efficiently. In this paper, we aim to enhance the solution quality and computation efficiency for solving AGH. Particularly, we first model AGH as a multiple-fleet vehicle routing problem (VRP) with miscellaneous constraints including precedence, time windows, …

A Poisson-Based Distribution Learning Framework For Short-Term Prediction Of Food Delivery Demand Ranges, Jian Liang, Jintao Ke, Hai Wang, Hongbo Ye, Jinjun Tang

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic has caused a dramatic change in the demand composition of restaurants and, at the same time, catalyzed on-demand food delivery (OFD) services—such as DoorDash, Grubhub, and Uber Eats—to a large extent. With massive amounts of data on customers, drivers, and merchants, OFD platforms can achieve higher efficiency with better strategic and operational decisions; these include dynamic pricing, order bundling and dispatching, and driver relocation. Some of these decisions, and especially proactive decisions in real time, rely on accurate and reliable short-term predictions of demand ranges or distributions. In this paper, we develop a Poisson-based distribution prediction (PDP) …

Application Of Virtual-Real Simulation In Military Field, Ziquan Mao, Jialong Gao, Jianxing Gong, Quan Liu

Journal of System Simulation

Abstract: The definition and content of the virtual-real simulation are presented. According to different technical ideas, the development status and existing problems of virtual-real simulation are summarized from three aspects of digital twin, live-virtual-constructive (LVC) simulation, and parallel system. The similarities and differences, as well as the advantages and disadvantages of the three methods are analyzed and compared, and their main application fields are discussed. In order to deal with difficulties encountered in military training, operational tests, equipment development, and equipment maintenance, a solution based on virtual-real simulation is proposed by means of theoretical guidance, case comparison, and transfer and …

Image Semantic Segmentation Algorithm Based On Improved Deeplabv3+, Weiping Zhao, Yu Chen, Song Xiang, Yuanqiang Liu, Chaoyue Wang

Journal of System Simulation

Abstract: Mainstream image semantic segmentation networks currently face problems such as incorrec segmentation, discontinuous segmentation, and high model complexity, which cannot be flexibly and efficiently deployed in practical scenarios. To this end, an image semantic segmentation network that optimizes the DeepLabv3+ model is designed by comprehensively considering the network parameters, prediction time, and accuracy. The lightweight EfficientNetv2 is adopted to extract backbone network features and improve parameter utilization. In the atrous spatial pyramid pooling module, the mixed strip pooling is utilized to replace the global average pooling, and a depthwise separable dilated convolution is introduced to reduce parameters and improve …

Intercell Dynamic Scheduling Method Based On Deep Reinforcement Learning, Jing Ni, Mengke Ma

Journal of System Simulation

Abstract: In order to solve the intercell scheduling problem of dynamic arrival of machining tasks and realize adaptive scheduling in the complex and changeable environment of the intelligent factory, a scheduling method based on a deep Q network is proposed. A complex network with cells as nodes and workpiece intercell machining path as directed edges is constructed, and the degree value is introduced to define the state space with intercell scheduling characteristics. A compound scheduling rule composed of a workpiece layer, unit layer, and machine layer is designed, and hierarchical optimization makes the scheduling scheme more global. Since double deep …

Analysis Of Autonomous Aerial Refueling Capability Requirements And Key Evaluation Indicators, Quan Zou, Yixin Hua, Zhu Shao, Wenbi Zhao

Journal of System Simulation

Abstract: From the perspective of flight tests, how to evaluate the autonomous aerial refueling (AAR) capability and select key indicators for evaluation is a key problem to be solved for AAR trials. The standards requirements of aerial refueling and manned aircraft aerial refueling experience in China and abroad are analyzed. The total capability of AAR is studied, and key evaluation indicators in the AAR whole process including rendezvous, formation, docking, refueling, and disengagement are proposed. The evaluation method is demonstrated in both numerical simulation and hardware-in-loop test environments. Finally, the key indicators affecting the docking success of AAR are analyzed, …