Operations Research, Systems Engineering and Industrial Engineering Commons^™

The Development And Use Of The Probabilistic Financial Decision Model For A Company Expansion, Elizabeth Wiese

Senior Honors Theses

In the United States, companies are expanding constantly. However, in an industrial equipment dealership expanding into a new state, it is important to understand the industry, new market, and costs associated with expanding. With using financial statements of data-backed percentages for growth, research seeks to set up a financial model to see if expansion for an industrial equipment dealership into the state of North Carolina will be a financially wise decision. Wesley Worldwide, an industrial equipment dealership, is moving forward with the investment of expanding into North Carolina. However, it is vital to understand the financial predictions for profit return …

Experimental Investigation Of The Self-Healing Potential Of Bacteria For Sustainable Concrete Structures, Pitiporn Asvapathanagul, Simone Galano, Andrea Calabrese, Mehran Rahmani, Maggie Ly, Daniela Flores, Michael Hernandez, Nicholas Banuelos

Mineta Transportation Institute

Although concrete is the most widely used building material in the world, its limited tensile strength makes cracking a common phenomenon in concrete elements. This study investigates the potential of autonomous self-healing as an eco-friendly and lowcost method to increase the durability of concrete. The crack-healing potential of different types of high-alkaline-tolerant bacteria or calcite-precipitation microorganisms is investigated. High-alkaline-tolerant bacteria and calcite-precipitation microorganisms were used to retrofit lab-fractured concrete samples. The samples healed with each of these bacteria groups were cast and tested under compressive load up to failure to measure the compressive strength of the concrete samples. The outcomes …

Naphtha Characterization (Piona, Density, Distillation Curve And Sulfur Content): An Origin Comparison, Aline Pioli Silva, Juliana Otavia Bahú, Renato Soccol Jr., Leonardo Rodriguez-Urrego, William Stive Fajardo-Moreno, Hiram Moya, Jeffrey Leon-Pulido, Víktor Oswaldo Cárdenas Concha

Manufacturing & Industrial Engineering Faculty Publications and Presentations

Naphtha is an important distillation product of crude oil, and is used as a raw material for first-generation products such as ethylene, propylene, gasoline, xylene (BTX), and others. However, due to the different sources of crude oil, differences in naphtha composition impact the quality of conversion processes. Parameters such as pressure, charge flow, and temperature need to be adjusted for conversion efficiency. This work aims to compare naphtha samples from different origins, through the analysis of distillation curve (ASTM D86), density (ASTM D4052), total sulfur (ASTM D4294), and n-paraffins, iso-paraffins, olefins, naphthene, and aromatics (PIONA, ASTM D5134). Among these parameters …

Effective Use Methods For Continuous Sensor Data Streams In Manufacturing Quality Control, William Hitchcock

Senior Honors Theses

This work outlines an approach for managing sensor data streams of continuous numerical data in product manufacturing settings, emphasizing statistical process control, low computational and memory overhead, and saving information necessary to reduce the impact of nonconformance to quality specifications. While there is extensive literature, knowledge, and documentation about standard data sources and databases, the high volume and velocity of sensor data streams often makes traditional analysis unfeasible. To that end, an overview of data stream fundamentals is essential. An analysis of commonly used stream preprocessing and load shedding methods follows, succeeded by a discussion of aggregation procedures. Stream storage …

A Review On Learning To Solve Combinatorial Optimisation Problems In Manufacturing, Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song, Zhang Le, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

An efficient manufacturing system is key to maintaining a healthy economy today. With the rapid development of science and technology and the progress of human society, the modern manufacturing system is becoming increasingly complex, posing new challenges to both academia and industry. Ever since the beginning of industrialisation, leaps in manufacturing technology have always accompanied technological breakthroughs from other fields, for example, mechanics, physics, and computational science. Recently, machine learning (ML) technology, one of the crucial subjects of artificial intelligence, has made remarkable progress in many areas. This study thoroughly reviews how ML, specifically deep (reinforcement) learning, motivates new ideas …

Introduction To The Special Issue On Innovation In Transportation-Enabled Urban Services, Part 1, Niels Agatz, Soo-Haeng Cho, Hai Wang, Saif Benjaafar

Research Collection School Of Computing and Information Systems

Rapid developments in city infrastructure and technol-ogies are creating numerous opportunities and inspiring innovative and emerging urban services. Among these innovations, complex systems of urban transportation and logistics have embraced advances and have been reshaped significantly. They enable innovative new urban services, which are now booming and changing everyday life for urban residents.This special issue of Service Science explores perspectives on innovation in transportation-enabled urban services. We hope that the special issue will enhance the understanding of the planning, operation, and management of such services. Contributions are expected to demonstrate rigorous model development, economic/ econometric analysis, and decision-making tools based …

Introduction To Bioaerosols Assessment And Control, 2nd Edition, Cheri Marcham, John (Jack) Springston

Publications

• Risk Assessment
• Assessment for the Presence of Bioaerosols
• Sampling
• Purpose/ Necessity
• Interpretation Controls
  • Ventilation
  • Other Controls

Study Of The Graphene Energy Absorbing Layer And The Viscosity Of Sodium Alginate In Laser-Induced- Forward-Transfer (Lift) Bioprinting, Shuqi Zhou, Jianzhi Li, Ben Xu

Manufacturing & Industrial Engineering Faculty Publications and Presentations

Laser induced forward transfer (LIFT) bioprinting has been viewed as a new and actively developed three-dimensional bioprinting technology due to its high accuracy and good cell viability. The printing quality is highly dependent on the jet formation and its stability in the LIFT bioprinting process. The objective of this study is to investigate the effect of a graphene Energy Absorbing Layer (EAL) and alginate hydrogel (SA) (w.t. 1% and 2%) viscosity on jet generation in the LIFT bioprinting process. Since SA exhibits a shear-thinning behavior, it is a non-Newtonian fluid. The effect of EAL thickness and SA’s viscosity were addressed …

Ads-B Classification Using Multivariate Long Short-Term Memory–Fully Convolutional Networks And Data Reduction Techniques, Sarah Bolton *, Richard Dill, Michael R. Grimaila, Douglas Hodson

Faculty Publications

Researchers typically increase training data to improve neural net predictive capabilities, but this method is infeasible when data or compute resources are limited. This paper extends previous research that used long short-term memory–fully convolutional networks to identify aircraft engine types from publicly available automatic dependent surveillance-broadcast (ADS-B) data. This research designs two experiments that vary the amount of training data samples and input features to determine the impact on the predictive power of the ADS-B classification model. The first experiment varies the number of training data observations from a limited feature set and results in 83.9% accuracy (within 10% of …

Queueing System With Potential For Recruiting Secondary Servers, Srinivas Chakravarthy, Alexander N. Dudin, Sergey A. Dudin, Olga S. Dudina

Industrial & Manufacturing Engineering Publications

In this paper, we consider a single server queueing system in which the arrivals occur according to a Markovian arrival process (MAP). The served customers may be recruited (or opted from those customers’ point of view) to act as secondary servers to provide services to the waiting customers. Such customers who are recruited to be servers are referred to as secondary servers. The service times of the main as well as that of the secondary servers are assumed to be exponentially distributed possibly with different parameters. Assuming that at most there can only be one secondary server at any given …

An Effective Transfer Learning Based Landmark Detection Framework For Uav-Based Aerial Imagery Of Urban Landscapes, Bishwas Praveen, Vineetha Menon, Tathagata Mukherjee, Bryan Mesmer, Sampson Gholston, Steven Corns

Engineering Management and Systems Engineering Faculty Research & Creative Works

Aerial imagery captured through airborne sensors mounted on Unmanned Aerial Vehicles (UAVs), aircrafts, satellites, etc. in the form of RGB, LiDAR, multispectral or hyperspectral images provide a unique perspective for a variety of applications. These sensors capture high-resolution images that can be used for applications related to mapping, surveying, and monitoring of crops, infrastructure, and natural resources. Deep learning based algorithms are often the forerunners in facilitating practical solutions for such data-centric applications. Deep learning-based landmark detection is one such application which involves the use of deep learning algorithms to accurately identify and locate landmarks of interest in images captured …

A Genome-Wide Association Study Coupled With Machine Learning Approaches To Identify Influential Demographic And Genomic Factors Underlying Parkinson’S Disease, Md Asad Rahman, Jinling Liu

Engineering Management and Systems Engineering Faculty Research & Creative Works

Background: Despite the recent success of genome-wide association studies (GWAS) in identifying 90 independent risk loci for Parkinson's disease (PD), the genomic underpinning of PD is still largely unknown. At the same time, accurate and reliable predictive models utilizing genomic or demographic features are desired in the clinic for predicting the risk of Parkinson's disease. Methods: To identify influential demographic and genomic factors associated with PD and to further develop predictive models, we utilized demographic data, incorporating 200 variables across 33,473 participants, along with genomic data involving 447,089 SNPs across 8,840 samples, both derived from the Fox Insight online study. …

Improving Social Bot Detection Through Aid And Training, Ryan Kenny, Baruch Fischhoff, Alex Davis, Casey I. Canfield

Engineering Management and Systems Engineering Faculty Research & Creative Works

Objective: We test the effects of three aids on individuals' ability to detect social bots among Twitter personas: a bot indicator score, a training video, and a warning. Background: Detecting social bots can prevent online deception. We use a simulated social media task to evaluate three aids. Method: Lay participants judged whether each of 60 Twitter personas was a human or social bot in a simulated online environment, using agreement between three machine learning algorithms to estimate the probability of each persona being a bot. Experiment 1 compared a control group and two intervention groups, one provided a bot indicator …

Fugacity-Based Lattice Boltzmann Method For Multicomponent Multiphase Systems, Muzammil Soomro, Luis F. Ayala, Cheng Peng, Orlando M. Ayala

Engineering Technology Faculty Publications

The free-energy model can extend the lattice Boltzmann method to multiphase systems. However, there is a lack of models capable of simulating multicomponent multiphase fluids with partial miscibility. In addition, existing models cannot be generalized to honor thermodynamic information provided by any multicomponent equation of state of choice. In this paper, we introduce a free-energy lattice Boltzmann model where the forcing term is determined by the fugacity of the species, the thermodynamic property that connects species partial pressure to chemical potential calculations. By doing so, we are able to carry out multicomponent multiphase simulations of partially miscible fluids and generalize …

Computational Decision Support For Socio-Technical Awareness Of Land-Use Planning Under Complexity—A Dam Resilience Planning Case Study, Andreas Tolk, Jennifer A. Richkus, F. Leron Shults, Wesley J. Wildman

VMASC Publications

Land-use planning for modern societies requires technical competence as well as social competence. We therefore propose an integrative solution enabling better land-use planning and management through better-informed decision-making. We adapt a method developed for cross-disciplinary team building to identify the stakeholders and their various objectives and value systems. We use these results to populate artificial societies embedded into a dynamic data analytics framework as a tool to identify, explore, and visualize the challenges resulting from the different objectives and value systems in land-use planning and management. To prove the feasibility of the proposed solution, we present two use cases from …

A New Course In Defense Manufacturing – An Introduction To Shipbuilding, Alley C. Butler

Manufacturing & Industrial Engineering Faculty Publications and Presentations

This paper discusses the development and deployment of a new course in DMEI (Defense Manufacturing Engineering Innovation) titled, “Introduction to Shipbuilding.” This course has been taught using Zoom since 2021 at both the University of Texas Rio Grande Valley, a Hispanic Serving Institution, and Virginia State University, a Historically Black University. After a brief literature review, an outline of the course is presented with topics including the maritime market for shipbuilding, economics of shipbuilding, the classification agencies, metallurgy and welding processes, ship structure and assembly, shipyard layout, accuracy control, and shipbuilding planning and scheduling. Difficulties in obtaining an appropriate textbook …

Show-Me Resilience: Assessing And Reconciling Rural Leaders’ Perceptions Of Climate Resilience In Missouri, Zachary J. Miller, Caleb O'Brien, Casey I. Canfield, Lauren Sullivan

Engineering Management and Systems Engineering Faculty Research & Creative Works

Rural areas of the United States play a vital role in coping with, adapting to and mitigating climate change, yet they often lag urban areas in climate planning and action. Rural leaders—e.g., policymakers, state/federal agency professionals, non-profit organization leadership, and scholars – are pivotal for driving the programs and policies that support resilient practices, but our understanding of their perspectives on climate resilience writ large is limited. We conducted semi-structured interviews with 23 rural leaders in Missouri to elucidate their conceptualizations of climate resilience and identify catalysts and constraints for climate adaptation planning and action across rural landscapes. We investigated …

Deep Reinforcement Learning For Approximate Policy Iteration: Convergence Analysis And A Post-Earthquake Disaster Response Case Study, Abhijit Gosavi, L. (Lesley) H. Sneed, L. A. Spearing

Engineering Management and Systems Engineering Faculty Research & Creative Works

Approximate Policy Iteration (API) is a Class of Reinforcement Learning (RL) Algorithms that Seek to Solve the Long-Run Discounted Reward Markov Decision Process (MDP), Via the Policy Iteration Paradigm, Without Learning the Transition Model in the Underlying Bellman Equation. Unfortunately, These Algorithms Suffer from a Defect Known as Chattering in Which the Solution (Policy) Delivered in Each Iteration of the Algorithm Oscillates between Improved and Worsened Policies, Leading to Sub-Optimal Behavior. Two Causes for This that Have Been Traced to the Crucial Policy Improvement Step Are: (I) the Inaccuracies in the Policy Improvement Function and (Ii) the Exploration/exploitation Tradeoff Integral …

Modeling Of A Microstrip Line Referenced To A Meshed Return Plane, Zeyi Sun, Jian Liu, Xiaoyan Xiong, Yuan Liu, Victor Khilkevich, Donghyun Kim, Daryl G. Beetner

Engineering Management and Systems Engineering Faculty Research & Creative Works

Transmission Lines Referenced to Meshed Return Planes Are Widely Used Because of the Physical Flexibility Imparted by the Meshed Plane. Poor Accounting for the Meshed Ground, However, Can Lead to Severe Signal Integrity and Radio Frequency Interference Issues. Full-Wave Simulation Can Characterize the Electrical Performance at an Early Design Stage, But It is Both Time and Computational Resource Consuming. to Make the Simulation More Efficient, a Method is Proposed in This Study to Model Transmission Lines with a Meshed Reference Ground using 2D Analysis. the 2D Analysis is Performed at Several Locations Along the Length of the Trace above the …

Higher-Order Effects In Biaxial Flexure Of Gfrp I-Section Beams, Zia Razzaq, Faridoon Z. Razzaq

Civil & Environmental Engineering Faculty Publications

A theoretical study of Glass Fiber Reinforced Polymer (GFRP) beams subjected to biaxial bending moments is presented with a focus on the influence of higher-order effects on maximum normal stresses. It is shown that the biaxial bending type of loading causes a dramatic increase in the maximum normal stress for a GFRP beam when induced torsional effects are included. The study demonstrates that the traditional first-order theory can grossly underestimate the maximum normal stress in a GFRP beam. Based on the numerical results presented using a higher-order theory which also accounts for induced warping normal stresses, the maximum normal stress …

Machine Learning Prediction Of Dod Personal Property Shipment Costs, Tiffany Tucker [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

U.S. Department of Defense (DoD) personal property moves account for 15% of all domestic and international moves - accurate prediction of their cost could draw attention to outlier shipments and improve budget planning. In this work 136,140 shipments between 13 personal property shipment hubs from April 2022 through March 2023 with a total cost of $1.6B were analyzed. Shipment cost was predicted using recursive feature elimination on linear regression and XGBoost algorithms, as well as through neural network hyperparameter sweeps. Modeling was repeated after removing 28 features related to shipment hub location and branch of service to examine their influence …

Critical Space Infrastructure: A Complex System Governance Perspective, Adrian V. Gheorghe, James C. Pyne, Joseph Sisti, Charles B. Keating, Polinpapilinho F. Katina, William Edmonson

Engineering Management & Systems Engineering Faculty Publications

This paper examines the applicability of Complex System Governance (CSG) to advance the Critical Space Infrastructure field (CSI). CSI encompasses space related hardware, workforce, environment, facilities, and businesses that are necessary for societal well-being. CSI is increasing in importance as more societal serving systems are becoming dependent on CSI to operate. Given this increasing dependence on CSI, societal sectors are increasingly at risk should something go wrong with CSI upon which they depend. CSI has been developing is a fragmented way and lacks coherent organization. CSG is focused on design, execution, and evolution of system functions that provide for communications, …

Enablers And Barriers Of Communication In Virtual Engineering Teams: The Role Of Teamwork Skills And Emergent Conflict, Pilar Pazos, Francisco Cima

Engineering Management & Systems Engineering Faculty Publications

Communication is a critical process that facilitates team members' coordination, expertise exchange, decision-making, and, consequently, team elfectiveness. A focus on effective communication is critical in virtual teams due to their lack of face-to-face interactions and social presence. Communication becomes challenging in remote settings, and specific skills emerge as more essential to success. It is known that effective teams rely on planning, execution, and interpersonal skills to be successful. Still, the specific impact of these skills on virtual team effectiveness is not well understood. Additionally, conflict can emerge as a significant barrier to collaboration for remote teams that can hinder their …

Ant Colony-Based Approach For Solving An Unmanned Aerial Vehicle Routing Problem, Youssef Harrath Dr., Jihene Kaabi Dr.

Research & Publications

Waste management issues are affecting the economic and environmental aspects of modern societies. Thus, growing the interest of academic and industrial research and development in optimizing the process of waste management. As these issues greatly impact human health and environmental aspects and impose a threat, hazardous waste management requires even much more attention. The problem studied in this research is a variant of the vehicle routing problem using an unmanned aerial vehicle (UAV). The focus of this research is on planning the routes for waste collection and disposal using a UAV. The aim is to collect all the waste as …

Cybersecurity And Digital Privacy Aspects Of V2x In The Ev Charging Structure, Umit Cali, Murat Kuzlu, Onur Elma, Osman Gazi Gucluturk, Ahmet Kilic, Ferhat Ozgur Catak

Engineering Technology Faculty Publications

With the advancement of green energy technology and rising public and political acceptance, electric vehicles (EVs) have grown in popularity. Electric motors, batteries, and charging systems are considered major components of EVs. The electric power infrastructure has been designed to accommodate the needs of EVs, with an emphasis on bidirectional power flow to facilitate power exchange. Furthermore, the communication infrastructure has been enhanced to enable cars to communicate and exchange information with one another, also known as Vehicle-to-Everything (V2X) technology. V2X is positioned to become a bigger and smarter system in the future of transportation, thanks to upcoming digital technologies …

Component Maintenance Strategies And Risk Analysis For Random Shock Effects Considering Maintenance Costs, Chao Zhang, Yadong Zhang, Hongyan Dui, Shaoping Wang, Mileta Tomovic

Engineering Technology Faculty Publications

Maintenance can improve a system’s reliability in a long operation period or when a component has failed. The reliability modeling method that uses the stochastic process degradation model to describe the system degradation process has been widely used. However, the existing reliability models established using stochastic processes only consider the internal degradation process, and do not fully consider the impact of external random shocks on their reliability modeling. Furthermore, the existing theory of importance does not consider the actual factors of maintenance cost. In this paper, based on the reliability modeling of random processes, the degradation rate under the influence …

An Ioe Blockchain-Based Network Knowledge Management Model For Resilient Disaster Frameworks, Amir Javadpour, Farinaz Sabz Ali Pour, Arun Kumar Sangaiah, Weizhe Zhang, Forough Ja'far, Ashish Singh

Engineering Management & Systems Engineering Faculty Publications

The disaster area is a constantly changing environment, which can make it challenging to distribute supplies effectively. The lack of accurate information about the required goods and potential bottlenecks in the distribution process can be detrimental. The success of a response network is dependent on collaboration, coordination, sovereignty, and equal distribution of relief resources. To facilitate these interactions and improve knowledge of supply chain operations, a reliable and dynamic logistic system is essential. This study proposes the integration of blockchain technology, the Internet of Things (IoT), and the Internet of Everything (IoE) into the disaster management structure. The proposed disaster …

Strengthening Urban Resilience: Understanding The Interdependencies Of Outer Space And Strategic Planning For Sustainable Smart Environments, Ulpia-Elena Botezatu, Olga Bucovetchi, Adrian V. Gheorghe, Radu D. Stanciu

Engineering Management & Systems Engineering Faculty Publications

The conventional approach to urban planning has predominantly focused on horizontal dimensions, disregarding the potential risks originating from outer space. This paper aims to initiate a discourse on the vertical dimension of cities, which is influenced by outer space, as an essential element of strategic urban planning. Through an examination of a highly disruptive incident in outer space involving a collision between the Iridium 33 and Cosmos 2251 satellites, this article elucidates the intricate interdependencies between urban areas and outer space infrastructure and services. Leveraging the principles of critical infrastructure protection, which bridge the urban and outer space domains, and …

Embok 5.0 - Industry 4.0/5.0 Manifest And Latent Dimensions Mapping To The Asem Embok, T. Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

Industry 3.0 automation emerged replacing human labor with high volume processes and robotics. Industry 4.0, cyber-physical systems, and Industry 5.0, mass customization and cognitive systems, are in the early stages of emergence. Research into the impact of Industry 4.0 and 5.0 is focused at the strategic or organizational levels or on the technological challenges. Research into the impact of Industry 4.0 and 5.0 on engineering management has been limited to their impact on project management. This leaves open the question of the directions in which ASEM should evolve the Engineering Management Body of Knowledge (EMBOK) under the emergence of Industry …

Creating Portfolio Management Concepts For Highly Agile And Innovative Government Research Programs Using Design Thinking And Learn Start Up Methodologies, Vanessa Aubuchon, Resit Unal, Pilar Pazos, Holly Handley, Cindy Daniels

Engineering Management & Systems Engineering Faculty Publications

Managing a research and development (R&D) portfolio presents numerous challenges, such as prioritizing research areas, remaining agile, strategic workforce planning, and measuring return on investment, impact, and innovation. One government R&D program is charged with producing a high degree of innovative, transformational breakthroughs in aviation technology. A practical, structured methodology for strategically prioritizing emerging aviation R&D in such an environment is lacking. The existing multi-criteria decision aid tools are primarily utilized at an enterprise level, take months to set up and collect data, require large teams of experts, are used on an infrequent basis, and are not conducive to a …