Operations Research, Systems Engineering and Industrial Engineering Commons^™

Intelligent Air Defense Task Assignment Based On Assignment Strategy Optimization Algorithm, Jiayi Liu, Gang Wang, Qiang Fu, Xiangke Guo, Siyuan Wang

Journal of System Simulation

Abstract: Aiming at the insufficient solving speed of assignment strategy optimization algorithm in largescale scenarios, deep reinforcement learning is combined with Markov decision process to carry out the intelligent large-scale air defense task assignment. According to the characteristics of large-scale air defense operations, Markov decision process is used to model the agent and a digital battlefield simulation environment is built. Air defense task assignment agent is designed and trained in digital battlefield simulation environment through proximal policy optimization algorithm. The feasibility and advantage of the method are verified by taking a large-scale ground-to-air countermeasure mission as an example.

Intelligent Path Planning For Mobile Robots Based On Sac Algorithm, Laiyi Yang, Jing Bi, Haitao Yuan

Journal of System Simulation

Abstract: Aiming at the high dimension, slow convergence and complex modelling of traditional path planning algorithms for mobile robots, a new intelligent path planning algorithm is proposed, which is based on deep reinforcement learning soft actor-critic (SAC) algorithm to save the poor performance of robot in complicated environments with static and dynamic obstacles. An improved reward function is designed to enable mobile robots to quickly avoid obstacles and reach targets by using state dynamic normalization and priority experience pool techniques. To evaluate the performance, a pygame-based simulation environment is constructed. Compared with proximal policy optimization(PPO) algorithm, experimental …

Robot Path Planning By Fusing Particle Swarm Algorithm And Improved Grey Wolf Algorithm, Menglong Cao, Wenbin Zhao, Zhiqiang Chen

Journal of System Simulation

Abstract: Aiming at the long paths and slow convergence speed of GWO algorithm in robot path planning, a hybrid PSO-GWO algorithm based on PSO algorithm and the improved GWO algorithm is proposed. By running PSO algorithm for many times, the initial wolf group size and initial fitness value are determined. A nonlinear convergence factor is introduced to balance the exploration and development capabilities of GWO algorithm, and a dynamic inertia weight factor is proposed to ensure the leadership system of alpha wolf and to promote the population communication. Levy flight and greedy strategy are used to effectively avoid the local …

Research On Modeling And Optimization Method Of Torpedo Anti-Jamming Attack Based On Game Confrontation, Liqiang Guo, Ma Liang, Zhang Hui, Yang Jing, Fan Xueman, Cheng Zhuo

Journal of System Simulation

Abstract: Aiming at the strong adversarial characteristics of underwater attack and defense operations and the time-consuming problem of traditional Monte Carlo method, a model of torpedo anti-jamming attack based on game confrontation is designed and an improved genetic simulated annealing algorithm for optimal model is proposed. Through the research method of simulation analysis, on the basis of the models of two torpedo salvo attack and submarine acoustic resistance defense, the attack-defense confrontation model is constructed according to the Nash equilibrium theory under zero-sum game. The initial population, fitness function, and evolutionary strategy of GA are improved by the ideas of …

Study And Policy Suggestions On International Competitive Advantage Of Manufacturing Industry Among China, United States, Japan, And Germany, Xin Guo, Jingjing Zhang, Kangwei Chi, Jingjing Guo

Bulletin of Chinese Academy of Sciences (Chinese Version)

Strengthening the competitive advantage of manufacturing and promoting its high-quality development are the key points to build a modern industrial system. This study uses international market share (MS), revealed comparative advantage (RCA), trade competition index (TCI), and price index (PI) from 2005 to 2020 to analyze the evolution of manufacturing competitive advantage and its main sources in major countries. The main findings are as follows. China's labor-intensive industries maintain a strong international competitive advantage, and the international competitive advantage of some capital and technology-intensive industries is increasing. The capital and technology intensive industries in Germany, Japan, and United States have …

An Examination Of The Role Of Industry 4.0 In Supply Chain Management: Critical Success Factors And A Roadmap, Alper Senol

Electronic Theses and Dissertations, 2020-2023

Global supply chain management aims to enhance efficiency and profitability for suppliers, manufacturers, logistics providers, and warehouses. It faces challenges due to the complexity involved. To stay competitive, organizations in the industry are leveraging Industry 4.0 technologies, but some struggle with implementation due to limited expertise. The primary challenge of Global Supply Chain Management now is to integrate Industry 4.0 tools and technologies to maintain high-quality standards and optimized processes. This study focused on identifying the key factors that directly affect the success of integrating Industry 4.0 into the supply chain. It examined both tangible and intangible business resources and …

Improving Basic Cadet Training For Changing Environment: Case Study At The Korea Air Force Academy, Yoojin Kwon

Electronic Theses and Dissertations, 2020-2023

Increasing uncertainty, such as Covid-19 and weather changes, threatens BCT (Basic Cadet Training) at ROKAFA (Republic of Korea Air Force Academy). In preparation for the changing and adverse environment, this study carried out the following steps to propose a system improvement utilizing LVC (Live, Virtual, Constructive) in BCT system at ROKAFA; 1) Researching the examples of BCT and LVC by advanced countries, 2) Analyzing BCT (ROKAFA) through systems approach (document analysis, survey of 140 cadets and officers, written interviews with military experts), 3) Applying LVC to BCT. BCT is a vital step in the transition from civilian to military status …

Optimal Sequencing And Scheduling Algorithm For Traffic Flows Based On Extracted Control Actions Near The Airport, Sharmistha Chakrabarti

Electronic Theses and Dissertations, 2020-2023

This dissertation seeks to design an optimization algorithm, based on naturalistic flight data, with emphasis on safety to perform a benefits' analysis when sequencing and scheduling aircraft at the runway. The viability of creating a decision-support tool to aid air traffic controllers in sequencing and optimizing airport operations is evaluated through the benefits' analysis. Air traffic control is a complex and critical system that ensures the safe and efficient movement of aircraft within the airspace. This is particularly true in the immediate vicinity of an airport. Unlike in en-route or terminal area airspace where aircraft usually traverse well established routes …

Assessing And Predicting The Students’ Systems Thinking Preference: Multi-Criteria Decision Making And Machine Learning, Siham Tazzit

Theses and Dissertations

The 21st century is marked by a technological revolution that features digital implementation and high interconnectivity between systems across different domains, such as transportation, agriculture, education, and health. Although these technological changes resulted in modern systems capable of easing individuals’ lives, these systems are increasingly complex, and that increased complexity is only expected to continue. The increased system complexity is due to the rapid exchange of information between subsystems, which creates high interconnectivity and interdependence between the subsystems and their elements. Workforce skill sets, as a result, must be modified appropriately to ensure the systems’ success. Systems Thinking is an …

Ruggedness Test Of A New Standardized Test Method For Abrasion Resistance Of E-Textiles, Erin Parker

Theses and Dissertations

Standard test methods provide product developers with information regarding materials' suitability for different purposes. Typically, current standards are suitable for determining the mechanical properties of new materials. However, in the case of electronic textiles (E-Textiles) and wearable technology (wearables), adding conductive components with added functionality makes utilizing textile standards difficult, and these standards will not provide information on mechanical and electrical properties of conductive elements. New standards for E-Textile and wearables testing are needed to ensure product developers can obtain the information necessary to make informed decisions about new products. Standards organizations such as the American Society for Testing and …

Ai Methods For Identifying Process Defects In Advanced Manufacturing With Rare Labeled Data, Ayantha Umesh Senanayaka Mudiyanselage

Theses and Dissertations

This dissertation aims to provide efficient process defect identification methods for advanced manufacturing environments using AI tools/algorithms with limited labeled data availability. Asset and equipment quality become highly sensitive in sustaining virtuous performance and safety in various manufacturing domains. Internally generated process imperfections degrade finished products' optimum performance and mechanical attributes. The evolution of big data and intelligent sensing systems leverage data-driven defect identification in advanced manufacturing environments. Widely adopted data-driven process anomaly detection methods assume that the training (source) and testing (target) data follow the same distribution and that labeled data are available in both source and target domains. …

Distributionally Robust Unsupervised Domain Adaptation And Its Applications In 2d And 3d Image Analysis, Yibin Wang

Theses and Dissertations

Obtaining ground-truth label information from real-world data along with uncertainty quantification can be challenging or even infeasible. In the absence of labeled data for a certain task, unsupervised domain adaptation (UDA) techniques have shown great accomplishment by learning transferable knowledge from labeled source domain data and adapting it to unlabeled target domain data, yet uncertainties are still a big concern under domain shifts. Distributionally robust learning (DRL) is emerging as a high-potential technique for building reliable learning systems that are robust to distribution shifts. In this research, a distributionally robust unsupervised domain adaptation (DRUDA) method is proposed to enhance the …

Ai-Enabled Modeling And Monitoring Of Data-Rich Advanced Manufacturing Systems, Abdullah Al Mamun

Theses and Dissertations

The infrastructure of cyber-physical systems (CPS) is based on a meta-concept of cybermanufacturing systems (CMS) that synchronizes the Industrial Internet of Things (IIoTs), Cloud Computing, Industrial Control Systems (ICSs), and Big Data analytics in manufacturing operations. Artificial Intelligence (AI) can be incorporated to make intelligent decisions in the day-to-day operations of CMS. Cyberattack spaces in AI-based cybermanufacturing operations pose significant challenges, including unauthorized modification of systems, loss of historical data, destructive malware, software malfunctioning, etc. However, a cybersecurity framework can be implemented to prevent unauthorized access, theft, damage, or other harmful attacks on electronic equipment, networks, and sensitive data. The …

Smart Cities-A Structured Literature Review, Jose Sanchez Gracias, Gregory S. Parnell, Eric Specking, Edward A. Pohl, Randy Buchanan

Industrial Engineering Faculty Publications and Presentations

Smart cities are rapidly evolving concept-transforming urban developments in the 21st century. Smart cities use advanced technologies and data analytics to improve the quality of life for their citizens, increase the efficiency of infrastructure and services, and promote sustainable economic growth. Smart cities integrate multiple domains, including transportation, energy, health, education, and governance, to create an interconnected and intelligent urban environment. Our research study methodology was a structured literature review using Web of Science and Google Scholar and ten smart city research questions. The research questions included smart city definitions, advantages, disadvantages, implementation challenges, funding, types of applications, quantitative techniques …

Health-Care And Supportive Services In General Population Disaster Shelters, Ashlea Bennett Milburn, Charleen C. Mcneill, Lauren Clay, Janice Springer, Mary Casey-Lockyer

Industrial Engineering Faculty Publications and Presentations

Objectives:

The Communication (C), Maintaining Health (M), Independence (I), Services, Support and Self-Determination (S), and Transportation (T) is a framework (C-MIST) for identifying functional needs in an emergency response. A C-MIST documentation tool provides shelter staff with a list of potential client needs and actions to address them. This retrospective review describes the needs and actions indicated on completed C-MIST documentation tools (ie, records) within domestic general population shelters following Hurricane Florence in 2018.

Methods:

A convenience sample of 1209 records completed by shelter disaster health services personnel was provided by the American Red Cross. The records correspond to client …

Enhancing Experiential Learning Through Virtual Reality: A Case Study In System Design And Hazard Analysis, Rafia Rahman Rafa

Industrial, Manufacturing, and Systems Theses - Archive

ABSTRACT: The recent advancement of additive manufacturing (AM) technologies leads to an extensive need for an industrial workforce. Training in AM requires expensive capital investment to install and maintain this technology and proper knowledge about potential safety hazards. Experiential, immersive training platforms like Virtual Reality (VR) can overcome this challenge by providing opportunities for effective learning in a safe and controlled environment. VR can teach students through active participation and immersive, hands-on experiences, which is especially important for manufacturing processes involving high-risk conditions. VR can expose students to manufacturing hazards and allow them to learn through trial and error without …

Topics In Optimization For Sustainable Energy Planning, Bahareh Nasirian

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

ABSTRACT: Due to the current trend of rising energy demand, finding alternate energy sources is vital. Many cities consider renewable energy as a component of a sustainable future. Typically, organic wastes are considered renewable energy sources. Wastes can be converted to proper energy forms using waste-to-energy technologies. On the other hand, more renewable energy sources in the power system may increase energy market stochasticity, alter system operation, and pose new problems for the current supply and demand equilibrium, which consequently requires new control methods. Hence, taking into account the issues mentioned above, in this research, we address organic waste conversion …

Increasing The Safety Of Bicyclists Using A Cyclist Behavior Questionnaire And A Smartphone Based Application, Anika Jannat Rimu

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

ABSTRACT: Bicycling is beneficial for health, the environment, road users’ flexibility, and personal expenses. Compared to motor vehicles, they are an active mode of transport, cause minimum pollution, are affordable, and can easily navigate through the increasing traffic all over the world. This increase in traffic, however, also increases the possibility of crashes with motor vehicles. Bicyclists, being more exposed to traffic than drivers, suffer fatal consequences from a crash. Therefore, a standard tool is required to understand bicyclist behavior on the road. This tool can provide insights into bicyclists’ behavior so that appropriate infrastructure or policy changes can be …

Laser-Induced Forward Transfer (Lift) Based Bioprinting Of The Collagen I With Retina Photoreceptor Cells, Md Shakil Arman, Ben Xu, Andrew Tsin, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications

This study focuses on the 3D bioprinting of retina photoreceptor cells using a laser-induced forward transfer (LIFT) based bioprinting system. Bioprinting has a great potential to mimic and regenerate the human organoid system, and the LIFT technique has emerged as an efficient method for high-resolution micropatterning and microfabrication of biomaterials and cells due to its capability of creating precise, controlled microdroplets. In this study, the parameters for an effective femtosecond laser-based LIFT process for 3D bioprinting of collagen biomaterial were studied. Different concentrations of collagen I solutions were tested and 0.75 mg/ml to 1 mg/ml collagen Ⅰ was identified as …

Machine Learning-Based Seismic Damage Assessment Of Residential Buildings Considering Multiple Earthquake And Structure Uncertainties, Xinzhe Yuan, Liujun Li, Haibin Zhang, Yanping Zhu, Genda Chen, Cihan H. Dagli

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Wood-frame structures are used in almost 90% of residential buildings in the United States. It is thus imperative to rapidly and accurately assess the damage of wood-frame structures in the wake of an earthquake event. This study aims to develop a machine-learning-based seismic classifier for a portfolio of 6,113 wood-frame structures near the New Madrid Seismic Zone (NMSZ) in which synthesized ground motions are adopted to characterize potential earthquakes. This seismic classifier, based on a multilayer perceptron (MLP), is compared with existing fragility curves developed for the same wood-frame buildings near the NMSZ. This comparative study indicates that the MLP …

Towards Sustainable Additive Manufacturing: Assessment Of Cost, Greenhouse Gas Emission, And Recyclability, Lei Di

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Additive Manufacturing technologies fabricate 3D objects layer by layer following a predesigned CAD model. Owing to the unique layer-wise production method, additive manufacturing offers competitive advantages in comparison with traditional subtractive manufacturing, such as shortened production time, increased design freedom, improved manufacturing capability and complexity, and reduced manufacturing waste. Numerous research studies have been conducted to design, understand, and improve additive manufacturing technologies in order to facilitate the implementation in the supply chain. On the other hand, with the rapid growth of additive manufacturing, sustainability issues that exist on both process level and supply chain level have started to receive …

Modeling And Solution Methodologies For Mixed-Model Sequencing In Automobile Industry, Ibrahim Ozan Yilmazlar

All Dissertations

The global competitive environment leads companies to consider how to produce high-quality products at a lower cost. Mixed-model assembly lines are often designed such that average station work satisfies the time allocated to each station, but some models with work-intensive options require more than the allocated time. Sequencing varying models in a mixed-model assembly line, mixed-model sequencing (MMS), is a short-term decision problem that has the objective of preventing line stoppage resulting from a station work overload. Accordingly, a good allocation of models is necessary to avoid work overload. The car sequencing problem (CSP) is a specific version of the …

Visibility Based Hospital Inpatient Unit Design., Uttam Karki

Electronic Theses and Dissertations

Patient fall is one of the adverse events in an inpatient unit of a hospital that can lead to disability and/or mortality. Healthcare literature suggests that increased visibility of patients by unit nurses is essential to improve patient monitoring and, in turn, reduce falls. However, such research has been descriptive in nature and does not provide an understanding of the characteristics of an optimal inpatient unit layout from a visibility-standpoint. This dissertation fills significant voids in this domain and adds much-needed realism to develop insights that hospital decision-makers can use to design their inpatient unit layout. Our first contribution (Chapter …

Experimental And Numerical Studies Of Laser Powder-Bed Fusion Process With Ti-6al-4v Powder: (1) Porosity And Mechanical Properties, And (2) Transient Phenomena In One- And Two-Dimensional Fabrications., Santosh K. Rauniyar

Electronic Theses and Dissertations

Laser powder bed fusion (L-PBF) process represents a form of metal additive manufacturing (AM) where micron-level powdered material is selectively melted and fused layer by layer to create intricate three-dimensional parts. This process involves rapid melting and solidification, leading to intense thermocapillary convection within the molten pool. The melt pool is a crucial element of the L-PBF process and refers to the localized region where the powder particles are melted and solidified to form each layer of the printed part. The shape and dimensions of the melt pool directly influence the accuracy and surface finish of the printed part. Precise …

Characterizing Logistics Operations Within A Federal Staging Area For Hurricane Response: A Qualitative Analysis Of Federal, State And Local Perspectives, Jannatul Shefa

Graduate Theses and Dissertations

A successful deployment of logistics operations following a disaster is a collective contribution of federal, state, and local entities to ascertain an efficient and effective response. This research analyzes data from interviews with disaster response logistics experts from these entities. The objective is to investigate the information sources and planning processes used in these organizations to plan vehicle routes for critical resource deliveries to impacted areas. Special attention is directed to the impacts of incomplete knowledge of infrastructure status, such as road disruptions due to debris or flooding. Supported by both qualitative and quantitative evidence, the study finds that incomplete …

A Novel Approach For Defect Detection Of Wind Turbine Blade Using Virtual Reality And Deep Learning, Md Fazle Rabbi

Open Access Theses & Dissertations

Wind turbines are subjected to continuous rotational stresses and unusual external forces such as storms, lightning, strikes by flying objects, etc., which may cause defects in turbine blades. Hence, it requires a periodical inspection to ensure proper functionality and avoid catastrophic failure. The task of inspection is challenging due to the remote location and inconvenient reachability by human inspection. Researchers used images with cropped defects from the wind turbine in the literature. They neglected possible background biases, which may hinder real-time and autonomous defect detection using aerial vehicles such as drones or others. To overcome such challenges, in this paper, …

Learning To Send Reinforcements: Coordinating Multi-Agent Dynamic Police Patrol Dispatching And Rescheduling Via Reinforcement Learning, Waldy Joe, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We address the problem of coordinating multiple agents in a dynamic police patrol scheduling via a Reinforcement Learning (RL) approach. Our approach utilizes Multi-Agent Value Function Approximation (MAVFA) with a rescheduling heuristic to learn dispatching and rescheduling policies jointly. Often, police operations are divided into multiple sectors for more effective and efficient operations. In a dynamic setting, incidents occur throughout the day across different sectors, disrupting initially-planned patrol schedules. To maximize policing effectiveness, police agents from different sectors cooperate by sending reinforcements to support one another in their incident response and even routine patrol. This poses an interesting research challenge …

Applications Of Probability Of Success In The Well Delivery Process To Improve Risk, Opportunity, And Cost Assurance, Romar Alexandra Gonzalez Luis

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Oil and Gas (O&G) well drilling is risky and expensive. The cost of drilling is typically underestimated, and there is little understanding of the certainty or Probability of Success (POS) of achieving the well objectives within the estimated cost. This dissertation presents, for the first time, a publicly available POS Cost method/tool that enables O&G operators to estimate the cost of well drilling substantially more accurately and improve the POS of accomplishing the drilling for the estimated cost. This POS Cost method employs a comprehensive, expert-based assessment of risks and risk mitigations that are incorporated into a Monte-Carlo-based simulation of …

Examining Individuals' Use Of The Internet For Healthcare Activities Over Time: Statistical Analysis Of Nhis Data, Zachary Junkins

All Theses

Telehealth is an increasingly important component of healthcare services. Telehealth services may present an opportunity to increase the equity, accessibility, and effectiveness of healthcare. As such, it is critical that telehealth design focus on reducing the barriers to access and usability that may impair some telehealth users. I utilized data from the National Health Interview Survey (NHIS) and multiple logit regression models focused on different aspects of telehealth in order to determine demographic characteristics, behaviors, or opinions which may predict groups that are likely to face a barrier to using telehealth services. This analysis provides an exploratory look at the …

Generalization Through Diversity: Improving Unsupervised Environment Design, Wenjun Li, Pradeep Varakantham, Dexun Li

Research Collection School Of Computing and Information Systems

Agent decision making using Reinforcement Learning (RL) heavily relies on either a model or simulator of the environment (e.g., moving in an 8x8 maze with three rooms, playing Chess on an 8x8 board). Due to this dependence, small changes in the environment (e.g., positions of obstacles in the maze, size of the board) can severely affect the effectiveness of the policy learned by the agent. To that end, existing work has proposed training RL agents on an adaptive curriculum of environments (generated automatically) to improve performance on out-of-distribution (OOD) test scenarios. Specifically, existing research has employed the potential for the …