Operations Research, Systems Engineering and Industrial Engineering Commons^™

Multi-Agent Reinforcement Learning Method For Wargame Simulation Based On Suboptimal Demonstration Guidance, Zicong Zhou, Junjie Zeng, Yue Hu, Zhengqiu Zhu, Quanjun Yin

Journal of System Simulation

To address issues such as fixed behavior patterns and insufficient adaptability in complex adversarial environments exhibited by traditional wargame agent decision-making models, this paper proposes a multi-agent reinforcement learning method based on suboptimal demonstrations (MARLSD). The proposed method integrates reward relabeling with a self-imitation learning mechanism, effectively improving the training efficiency of multi-agent reinforcement learning algorithms in environments with large state-action spaces and sparse rewards, even when only a small number of suboptimal demonstrations are available, while encouraging agents to explore better strategies. Experimental results show that, compared with baselines such as QMIX and MAGAIL, MARLSD significantly improves performance and …

Annotation-Free 6-Dof Grasp Detection Method Integrating Physical And Geometric Priors, Min Shi, Shisheng Guo, Suqin Wang, Zhaoxin Li, Dengming Zhu

Journal of System Simulation

To improve the stability and cross-category generalization capability of grasp pose estimation in complex stacked scenes, an annotation-free 6-DoF grasp detection method integrating physical rules and geometric structure priors was proposed. In the offline stage, a template library of feasible grasp poses was constructed based on multi-physical constraints, without relying on manual grasp annotations. In the network design, the modeling of structural symmetry of objects and spatial overlap relationships was introduced; a geometric guidance mechanism with occlusion perception and exposure modeling capabilities was designed, and robust pose alignment of target objects was achieved by combining keypoint regression. A multi-type stacked …

Robust Two-Stage Mimo-Ofdm Channel Estimation Method Against Sensing Errors, Yi Peng, Jun Wang, Qingqing Yang, Jianming Wang, Hui Li

Journal of System Simulation

To address the challenges of performance degradation, high pilot overhead, and high computational complexity in traditi onal channel estimation methods for integrated sensing and communication (ISAC) assisted MIMO-OFDM systems when radar sensing information contains errors, this paper proposes a robust two-stage sparse channel estimation framework designed to be tolerant of sensing errors. In the first stage, a residual energy weighted simultaneous orthogonal matching pursuit (REW-SOMP) algorithm is designed. Leveraging locally adaptive dictionary expansion and a residual- weighted path selection mechanism, it accurately captures communication-associated paths even under sensing errors. The second stage introduces an adaptive penalty factor alternating direction method …

Data Driven Estimation Of Pore Size Using 1d Light Emissions For Laser Powder Bed Fusion Additive Manufacturing, Jose Galarza, Jorge Barron, Luis Jimenez, Tamer Oraby, Jianzhi Li, Farid Ahmed

Manufacturing & Industrial Engineering Faculty Publications

The quality assurance of the Laser Powder Bed Fusion Process (LPBF) has been extensively investigated over the last decade for in-situ monitoring of metal additive manufacturing. The process inherently generates voids within the bulk of the part, which can detrimentally affect the quality of the printed part. The characterization of these voids by estimating their size and identifying their geometrical features remains a challenge. This study introduces a Machine Learning (ML) based framework for estimating void sizes of varying geometries using layer-wise one-dimensional (1D) average light intensity signal obtained from the optical tomography system during the 3D printing of metallic …

An Analytical Framework For Quantifying Urban And Community Resilience To Natural Hazards From Cell-Phone Gps-Location And Traffic-Flow Data, Georgios Chatzikyriakidis

Civil and Environmental Engineering Theses and Dissertations

Urban areas are increasingly exposed to natural hazards while accommodating a growing share of the global population, yet a consistent science-based framework for quantifying urban and community resilience remains lacking. This dissertation develops a physics-based analytical framework grounded in statistical mechanics and the quantitative theory of Brownian motion. A city is conceptualized as a complex medium in which citizens move analogously to Brownian particles within a viscoelastic environment, influenced by socioeconomic interactions and infrastructure functionality.

A central premise is that urban resilience, interpreted as engineering resilience (an outcome), can be quantified through a single metric: the mean-square displacement MSD=⟨r²(t)⟩, of …

Feasibility-Aware Deep Reinforcement Learning For Sustainable Timber Procurement Under Hurricane Demand Uncertainty, Jarod Wright

Theses and Dissertations

The timber supply chain connects landowners and mills to provide wood products but faces challenges from stochastic demand, seasonal variations, and disruptions such as hurricanes. Fur- thermore, sustainability concerns like transportation emissions create trade-offs in procurement. This study proposes a feasibility-aware Deep Reinforcement Learning framework for sustainable timber procurement and inventory control under joint demand–hurricane uncertainty. We develop a stochastic mathematical model capturing mill-landowner interactions, seasonal demand, hurricane- driven pricing, and carbon emissions. The problem is formulated as a constrained Markov decision process and solved using Proximal Policy Optimization with a feasibility-enforcing layer. A Mississippi-based case study with 2,100 landowners …

Improving And Supporting Flight Instructor’S Decisions For First Solo, Isabella Piasecki

Theses and Dissertations

Flight instructors have the burden of determining when a student is ready for their first solo flight, and many have expressed uncertainty over their own decision-making skills during this phase of a student’s training. Prior studies have examined flight instructors’ pre-solo decisions in other countries, but no such study has been conducted with American flight instructors. For this study, current flight instructors with multiple prior endorsements for a student pilot’s first solo were interviewed to identify the more abstract concepts they use to guide their decision. Qualitative themes were identified from their experiences. Using this information, a checklist was developed …

Machine Learning-Based Decision Support Models With Applications In Postsecondary Education, Marco Paolo Anglesio

Theses and Dissertations

This dissertation investigates the deployment of machine learning methodologies in an industrial engineering framework for the development of advanced decision support systems in the context of enrollment management. Drawing on techniques from educational data mining, the research addresses three key phases in the lifecycle of traditional and non-traditional students. First, it analyzes student retention using predictive classification models designed to identify individuals at elevated risk of attrition. Second, it employs temporal convolutional networks for time series forecasting, estimating aggregate enrollment levels over highly variable, finite planning horizons on the basis of partially observed data and using an asymmetric loss function. …

Modeling Psychological And Demographic Predictors Of Analog Astronaut Mission Participation, Christian Yeara Herrero, Frányerson R. López Ochoa, Mackenzie Thomas, Phoebe Fleshman

Student Research Symposium (SRS)

As plans accelerate to send humans into orbit and to other celestial bodies, whether to lunar outposts, Mars bases, or commercial space stations, it becomes increasingly important to understand how to maintain healthy, cohesive, and productive crews in confined, isolated environments. A practical way to study human adaptation to these conditions is through analog astronaut missions on Earth. Although imperfect, these facilities provide the closest Earth-based simulation of space mission conditions. Currently, over ten analog research centers are operating worldwide, including NASA’s Human Exploration Research Analog (HERA) and the Crew Health and Performance Exploration Analog (CHAPEA) habitats. Selecting and recruiting …

Beyond Accuracy: Machine Learning Models For Predicting Presence Of Permanent Molar Caries In U.S. Children And Adolescents With Fairness Consideration, Pritam Deb, Lin Li, Christina R. Scherrer

Faculty Articles

Background

Although predictors of dental caries have been previously explored, a comprehensive understanding of factors influencing permanent‐molar decay in U.S. children and adolescents, especially with respect to racial and ethnic biases remains limited. This study aims to develop and evaluate machine‐learning (ML) models incorporating algorithmic fairness to predict caries in permanent molars.

Methods

Data from the National Health and Nutrition Examination Survey (NHANES) were analyzed, using the 2011–2014 cycles for training and validation and the 2015–2016 cycle for testing. The primary outcome was decayed, missing, and filled teeth (DMFT) in at least one permanent molar, dichotomized to represent the presence …

Development Of A Putting Green Manufacturing Process, Tabitha R. Webster

Honors Theses

Our Capstone project investigates the end to end design, development, and production of a 6‑foot long portable putting green marketed for individuals seeking a high quality, competitively priced golf product for home or office use. The capstone project examines the full lifecycle of product creation applying manufacturing principles learned through the center of manufacturing’s coursework. From the initial concept through engineering design, market research, prototyping, manufacturing optimization, and final production the project emphasizes cross‑functional collaboration across engineering, business, and accountancy majors. Methods used to gather data included marketing surveys, CAD drawings, time studies during production runs, value stream mapping, and …

Modeling Individual Self-Protective Behavior During Epidemics, Geonsik Yu, Michael J. Garee, Mario Ventresca, Yuehwern Yih

Faculty Publications

Protecting public health from infectious diseases requires collective action, as individual behaviors—such as vaccination and mask-wearing—directly influence disease dynamics. During the COVID-19 pandemic, unexpected public responses often undermined the effectiveness of interventions, highlighting the need to understand collective behavioral patterns and motivations to design more effective mitigation strategies. This study presents an agent-based simulation model that captures how individuals adjust self-protective behaviors based on evolving opinions about disease risk and examines how these decisions interact with external factors, such as public health interventions, to shape collective outcomes. To improve the representativeness of the simulated population, multiple datasets were integrated to …

Development Of A Putting Green Manufacturing Process, Jose Andres Cepeda Santiago

Honors Theses

Our Capstone project investigates the end-to-end design, development, and production of a 6‑foot long portable putting green marketed for individuals seeking a high quality, competitively priced golf product for home or office use. The capstone project examines the full lifecycle of product creation applying manufacturing principles learned through the center of manufacturing’s coursework. From the initial concept through engineering design, market research, prototyping, manufacturing optimization, and final production the project emphasizes cross‑functional collaboration across engineering, business, and accountancy majors. Methods used to gather data included marketing surveys, CAD drawings, time studies during production runs, value stream mapping, and controlled documentation …

The Optimization Of A Robotic Welding Arm To Improve Efficiency, Margaret Close

Honors Theses

The main objective of this report is to optimize a robotic welding arm to improve a locker manufacturing process. The robotic welding arm, a Miller PerformArc, used by Lockers Manufacturing has been producing spatter. Spatter significantly reduces the quality of the product and increases the product’s manufacturing time. The goal of this project was to find the best solution to reduce spatter without weakening the welds and ensuring that efficiency will increase. The first step in this project was to test multiple weld testing variables such as voltage, current, welding angle, robot speed, and arc and crater ratios. For each …

Largest 2-Regular Subgraphs In Complete S-Partite Graphs, Yiyang Jiang

McKelvey School of Engineering Graduate Student Theses & Dissertations

In this thesis, we focus on the class of complete $S$-partite graphs, for $S$ an undirected graph possibly with self-loops, and address the problem of finding largest $2$-regular subgraphs of these graphs, which can be formulated as an integer linear program. Roughly speaking, a complete $S$-partite graph is obtained by replacing every single node of $S$ with a number of nodes, preserving the edge/non-edge relations of $S$. Our motivation in studying largest $2$-regular subgraphs is rooted in the structural systems theory, particularly in the problem of finding largest subnetworks that can sustain controllability or asymptotic stability of the corresponding subsystems. …

A Systems Perspective On Workstation Ergonomic Principles And Their Application In Emergency Care Environments, James Espinosa, Alan Lucerna

Rowan-Virtua Research Day

Background: Workstation ergonomic principles are commonly included in mandatory healthcare training programs. These recommendations—monitor height relative to eye level, neutral arm positioning, and adjustable seating—derive largely from occupational ergonomics literature designed to reduce musculoskeletal strain and improve comfort during computer work. Emergency Departments (EDs), however, represent dynamic environments with shared workstations and workflow interruptions that may influence the implementation of these recommendations.

Objective: To summarize the evidence supporting commonly taught workstation ergonomic principles and frame them within a systems perspective of ED work environments.

Methods: Narrative review of occupational ergonomics guidelines, ergonomic intervention studies, and human factors literature relevant to …

Digital Lean Transformation Through Mes–Scada Intergration: Reducing Transactional And Cognitive Waste In High-Volume Electronics Manufacturing, Kamal Alalul

Graduate Dissertations and Theses

This research addresses inefficiencies in Manufacturing Execution System (MES)-driven workflows, where excessive user interactions and fragmented access to work instructions introduce transactional and cognitive waste. To address these limitations, an integrated architecture was developed using Ignition as a SCADA-based operator interface connected to the MES through API-based communication. The system replaces direct MES interaction with a unified interface that embeds work instructions and automates transaction execution within the production workflow. The approach was implemented and evaluated through an industrial case study on a 15 station electronics manufacturing line. Results show a 51% reduction in total cycle time, decreasing from 2,996 …

Leveraging Information Theory And Ecological Network Analysis To Monitor Communication Networks In A Student Aerospace Team, Christine Sessions

Doctoral Dissertations and Master's Theses

Effective communication is a critical component of successful collaboration in group projects and team settings. However, systematically tracking and analyzing team communications can be challenging, especially in complex, multi-member teams such as those found in the aerospace industry. This paper explores an information-theoretic approach that leverages encoding techniques and graph theory to analyze communication networks within a university’s multi-year, student-led cubesat design project (Project COMET). By utilizing Shannon Entropy as a measure of information flow, encoding communication patterns, and analyzing Ecological Network Analysis parameters, this research aims to understand how an Embry-Riddle Aeronautical University student project team evolves over the …

Engineering Design And Analysis Using Creo® Cad, Cae, And Manufacturing Applications, Swapnil Moon

Open and Affordable Textbooks

This textbook presents a structured approach to computer-aided design using Creo, integrating CAD, CAE, and CAM workflows within a unified engineering framework. The material emphasizes parametric modeling, design intent, and feature-based modeling as foundations for creating robust and adaptable engineering models. Through progressively structured tutorials, students develop skills in part modeling, assemblies, engineering drawings, mechanism design, simulation, and manufacturing. The text incorporates real-world engineering components and workflows, including structural and thermal analysis, motion simulation, and toolpath generation, reflecting modern engineering practice. Designed for upper-division undergraduate and graduate students, this open educational resource supports hands-on learning and prepares students for industry-relevant …

Introduction To Computer-Aided Design Using Solidworks® : A Structured Approach To Parametric Modeling And Design Intent, Swapnil Moon

Open and Affordable Textbooks

This textbook introduces computer-aided design (CAD) using SOLIDWORKS® through a structured, design-centered approach that emphasizes parametric modeling and engineering reasoning. Rather than focusing solely on software commands, the material develops foundational skills in design intent, constraint-based modeling, and feature relationships to create robust, adaptable models.

The content is organized progressively, beginning with basic sketching and feature creation and advancing to complex part modeling, assemblies, motion studies, and engineering drawings. Each chapter builds upon prior concepts, reinforcing systematic modeling practices and promoting the development of system-level thinking required in real-world engineering design workflows.

Designed for undergraduate students with little or no …