Operations Research, Systems Engineering and Industrial Engineering Commons^™

Trajectory Planning And Tracking For Multi-Quadcopter In Dynamic Obstacle Environments, Haosheng Jiang, Fangfang Wu, Zexian Huang, Ziyue Ma, Chunyun Dong, Xubin Ping

Journal of System Simulation

Abstract: Multi-quadrotor UAV systems face challenges when performing complex tasks in dynamic obstacle environments. Therefore, a comprehensive particle swarm optimization-based task allocation method, a trajectory planning integrating the traditional Informed-RRT* and A* algorithms, and a trajectory tracking method based on model predictive control were designed. The multi-quadrotor task allocation problem was constructed as a classical multiple traveling salesman problem, and then, the particle swarm optimization was used to assign the task to multi-quadrotor UAVs. A fusion algorithm that combined the advantages of traditional Informed-RRT* and A* algorithms for quadrotor UAV trajectory planning was designed, so as to ensure that a …

Research On Non-Singular Fast Integral Terminal Sliding Mode Trajectory Tracking Control Of Six-Axis Robotic Arm, Tao Chen, Lizhong Wang, Xiangjun Zou, Xiaojuan Li

Journal of System Simulation

Abstract: To address the trajectory tracking control challenges caused by modeling parameter inaccuracies and disturbance uncertainties in robotic arms, a non-singular fast integral terminal sliding mode control scheme was developed. A new type of non-singular fast integral terminal sliding mode controller was designed. The non-singular fast terminal sliding mode ensured the rapid convergence of the system while avoiding the singularity during convergence. The integral term was used to enhance the suppression ability of disturbances and ensure the rapid response of the controller to errors. Lyapunov stability theory was applied to analyze the controller's convergence. The simulation results show that the …

Lightweight Driver Face Object Detection Algorithm Based On Yolov8-Df, Mingyu Li, Jiaquan Lin

Journal of System Simulation

Abstract: The YOLOv8n detection algorithm has a large amount of computation and parameters in the driving environment. To address this issue, a lightweight driver facial object detection algorithm YOLOv8-DF was proposed. A lightweight multi-scale convolution module (LMCM) was proposed to replace the Conv module in the network, and the dual-channel design could reduce the computation and parameter quantity of the algorithm; the multi-scale design could enrich the feature information inside the network. The lightweight convolutional GhostConv, Fasterblock module, and C2f module were fused, and a dual-channel lightweight convolution module (DLCM) was fused with the SPPF module. The experimental results show …

Optimal Scheduling Of An Integrated Energy System Considering Demand Response And Two-Stage P2g, Xinhui Duan, Zelong Cheng, Dongchao Zhang, Xiaochong Duan

Journal of System Simulation

Abstract: In the context of carbon peaking and carbon neutrality goals, this study aims to improve the energy utilization rate and further explore the role of user-side flexible loads and P2G equipment in energy saving and emission reduction. An optimal scheduling model for integrated energy systems considering demand response and two-stage P2G was proposed. A regional integrated energy system coupled with electricity, heating, cooling, gas, storage, and hydrogen was taken as the research object. Models for system equipment and two-stage P2G were established. Based on load characteristics, a multi-load demand response model for electricity, heating, and cooling was constructed using …

Advancing Autonomous Swarm Behavior In A Simulated Anti-Access Area Denial Environment, Chad Macwilkinson, Lance E. Champagne, Phillip M. Lacasse

Faculty Publications

This study proposes the application of a four dimensional framework of autonomy to a weapon swarm of high subsonic cruise missiles.

Techno-Enviro-Economic Approach For Electrification Of Rural And Shrimp Farming Regional Development Of An Isolated Island In Indonesia By Utilizing Hybrid Renewable Energy Systems, Fiqih Akbar Wijaya, Mohammad Akita Indianto

Journal of Materials Exploration and Findings

One of the challenges in developing and archipelagic countries such as Indonesia is maintaining energy demand in rural and isolated areas due to difficulties in electrical distribution. For instance, in areas like Bawean Island, no additional electricity capacity has been introduced in the past year, leading to an unmet potential customer demand. One of the possible options is by utilizing Hybrid Renewable Energy Systems (HRES) that are integrated with existing fossil fuel-based energy systems to support the growing energy demand in the remote island. A case study in Bawean Island is conducted with the projected energy demand covers the energy …

Remaining Life Assessment And Fitness For Service Evaluation Of Aging Chemical Reactors In Polyethylene Terephthalate Resin Industry, Aditya Pahlawan Munthe, Donanta Dhaneswara, Wahyuaji Narottama Putra, Gama Widyaputra

Journal of Materials Exploration and Findings

Aging chemical reactors in the polyethylene terephthalate (PET) resin industry require comprehensive evaluation to ensure safe continued operation. This study conducts a remaining life assessment (RLA) and fitness-for-service (FFS) evaluation on five 30-year-old reactors, based on API 510, API 579/ASME FFS-1, and ASME BPVC Section VIII Div. 1 standards. The analysis involves corrosion rate measurement, future corrosion allowance (FCA) projection, and minimum thickness verification. Among the reactors, R-120 was found to have the shortest remaining life less than 15 years. FFS assessments using three criteria Average Measured Thickness, MAWP from Point Thickness Readings, and Minimum Measured Thickness confirm that R-120 …

A Study Of Wear Measurement And Life Prediction Of Insert Chute Liner On Gold Ore Processing, Ferry Ardika Natanael, Nony Maulidya, Dedi Priadi

Journal of Materials Exploration and Findings

Chutes are critical materials handling assets to transport solid particles from one process step to another in mineral processing, coal mining and cement industries. The material transport, because of material characteristics, cause severe wear on internal lining of chutes or bins’ structure. The wear problem on internal lining of bins or chutes needs to be checked to keep production efficiency. Therefore, not checked wear rate causes liner replacement schedule becomes unpredictable. It leads to production loss and highly cost maintenance in industry. This study shows that condition-based maintenance through regular thickness measurement using Ultrasonic Transducer (UT) to predict life service …

Analysis Of Leak Testing Planning For Carbon Dioxide Piping Systems In The Development Of Carbon Capture, Utilization, And Storage Facilities In The Bintuni Basin, Devi Sentiani, Akhmad Herman Yuwono Professor

Journal of Materials Exploration and Findings

Carbon Capture, Utilization, and Storage (CCUS) technologies have become a key strategic response to global efforts to reduce CO₂ emissions. This study presents a leak testing strategy designed for a carbon dioxide (CO₂) piping system as part of a Carbon Capture, Utilization, and Storage (CCUS) project in the Bintuni Basin, West Papua, Indonesia. This study aims to ensure the system is properly prepared before commissioning by designing a leak test plan that is both practical and technical, based on ASME B31.3, ASME PCC-2, and API STD 520 Part 1. We conducted the process, which involves identifying the system boundaries, …

Using Large Language Models For Enhanced Fraud Analysis And Detection In Blockchain Based Health Insurance Claims, Ruba Islayem, Senay Gebreab, Walaa Alkhader, Ahmad Musamih, Khaled Salah, Raja Jayaraman, Muhammad Khurram Khan

Industrial Engineering: Faculty & Staff Publications

Traditional health insurance claim processing systems are plagued by inefficiencies and vulnerabilities, often resulting in significant financial losses due to fraudulent activities. Existing fraud detection methods are largely manual, time-consuming, and inadequate for handling the complexity and scale of modern fraudulent schemes. Moreover, the trust-based relationships between insurers and healthcare providers lack mechanisms to ensure data integrity and prevent manipulation. While several blockchain-based systems have been proposed to improve transparency and tamper resistance, they typically focus on structured data and predefined fraud types, offering limited adaptability and analytical insight. This paper proposes a novel solution leveraging blockchain technology and Large …

Scalable And Adaptive Agile Framework For Semiconductor Foundry: Advanced Packaging And Heterogeneous Integration Perspective, Pravin Thorat

Harrisburg University Dissertations and Theses

This research addressed the critical requirement for a scalable and adaptive agile framework specifically designed for the unique demands of semiconductor foundries specializing in advanced packaging and heterogeneous integration (HI). The semiconductor industry was encountering growing pressure to innovate and respond quickly to rapidly evolving demands, yet traditional manufacturing processes often struggled to adapt. Existing agile frameworks, mainly developed for the software industry, lacked the necessary adaptations to address the complexities of semiconductor manufacturing, including extended lead times, high capital investment, rigorous quality requirements, and the integration of various technologies. This research gap hindered the ability of semiconductor foundries to …

Enhanced Global Oil Spill Dataset From 1967 To 2023 Based On Text-Form Incident Information, Yiming Liu, Zhuoli Yin, Hua Cai

The School of Sustainability Engineering and Environmental Engineering (SEE) Faculty Publications

Knowing how much oil was released into the environment in each incident is critical to studying the environmental, ecological, and economic impacts of oil spills. However, the release amounts (RAs) for numerous oil spill incidents remain unavailable in a structured format for large-scale analysis. The most extensive global oil spill database, managed by NOAA’s Office of Response and Restoration, only documents the worst-case scenario estimations in the machine-readable dataset, while more accurate values are embedded within unstructured incident descriptions and subsequent updates. To enhance the dataset with more accurate RAs, we developed a framework to extract the actual RAs from …

Neural Architecture Search-Driven Unsupervised Domain Adaptation For Enhanced Wood Chip Quality Evaluation In Forest Industries, Abdur Rahman

Theses and Dissertations

Reliable and efficient measurement of wood chip moisture content is crucial for forest-reliant industries, including biofuel production, pulp and paper manufacturing, and bio-refineries, as it directly influences product quality and energy output. Traditional methods like the oven-drying technique, despite their widespread use, are time-consuming and impractical for real-time applications, while modern alternatives such as NIR spectroscopy, electrical capacitance, and microwave analysis are often costly, less portable, and require specialized expertise. This dissertation addresses these limitations by leveraging deep learning and machine vision to develop a scalable, accurate, and portable method for moisture content measurement using RGB images of wood chips. …

Transforming Movement Assessment In Physical Therapy Through Subaquatic Data Collection, Kaitlyn Mcdonald

Theses and Dissertations

This study explored the interest and perceived barriers to integrating subaquatic diagnostic technologies (SDTs) into hydrotherapy among licensed physical therapists. Seventeen semi-structured interviews were conducted using a mixed-methods design, with 15 interviews included in the final analysis. Quantitative data were analyzed using chi-square tests, while qualitative responses were coded thematically. Results indicated no statistically significant relationships between SDT interest and career stage or hydrotherapy access, though qualitative data highlighted concerns about cost, limited access, and usability. Despite mixed interest in adoption, participants identified several potential benefits of SDTs, including improved treatment tailoring, increased patient buy-in, and enhanced outcome monitoring. Functional …

A Machine Learning Approach To Detect Pores In Laser Powder Bed Fusion Additive Manufacturing, Jose Galarza, Jose Barron Jr., Luis Jimenez, Tamer Oraby, Jianzhi Li, Farid Ahmed

Manufacturing & Industrial Engineering Faculty Publications

Real-time detection of pores in the Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) process is proposed in this study and can be utilized for in-situ process monitoring and quality control. The average light emission data from the process captured by an optical tomography camera can be integrated into a defect detection module to characterize defects after the deposition of a layer. The light emission contains information on the process zone which could be extracted with the appropriate data techniques. In this paper, we proposed a machine-learning approach that utilizes the mean light intensity data from the melt-pool monitoring …

Multi-Stage Stochastic Programming For Disaster Relief Logistics Under Forecast Uncertainty, Sudhan Bhattarai

All Dissertations

Hurricanes are among the most destructive annual disasters in the United States, presenting interdependent challenges for evacuation planning and relief-supply logistics. Coordinating evacuation and relief operations is crucial to ensure the timely and effective movement of at-risk populations and the delivery of essential supplies. This dissertation develops and evaluates three progressively advanced multi-stage stochastic programming (MSSP) frameworks that integrate evacuation and relief-item pre-positioning while explicitly accounting for uncertainty in hurricane forecasts.

Chapter 1 introduces a fully adaptive MSSP model for the integrated hurricane relief logistics and evacuation planning (IHRLEP) problem. The model simultaneously optimizes evacuation flows and inventory pre-positioning over …

Machine Learning And Clinical Eeg Data For Multiple Sclerosis: A Systematic Review, Badr Mouazen, Ahmed Bendaouia, El Hassan Abdelwahed, Giovanni De Marco

Manufacturing & Industrial Engineering Faculty Publications

Multiple Sclerosis (MS) is a chronic neuroinflammatory disease of the Central Nervous System (CNS) in which the body’s immune system attacks and destroys the myelin sheath that protects nerve fibers, leading to a wide range of debilitating symptoms and causing disruption of axonal signal transmission. Accurate prediction, diagnosis, monitoring and treatment (PDMT) of MS are essential to improve patient outcomes. Recent advances in neuroimaging technologies, particularly electroencephalography (EEG), combined with machine learning (ML) techniques — including Deep Learning (DL) models — offer promising avenues for enhancing MS management. This systematic review synthesizes existing research on the application of ML and …

Effects Of Variation In Altitude And Temperature On The Restraining Force And Internal Gauge Pressure Of Constrained Dunnage Airbags, Charles R. Weaver

All Theses

Dunnage airbags are an increasingly popular choice for securing cargo. During transit, changes in ambient temperature and pressure can cause airbags to expand generating damaging horizontal compressive forces in the trailer or container. Previous studies have developed numerical models for the behavior of Kraft paper and woven polypropylene fabric dunnage airbags under standard conditions but do not account for the behavior of airbags under varied altitudes and temperatures. This study provides empirical data on the internal gauge pressure and restraining force dynamics of 4-ply Kraft, woven polypropylene, and polyvinyl chloride airbags under simulated altitude and temperature conditions. Tensile testing characterizes …

Understanding The Elements Of Sterile Processing Workflow: Or, Sterilization And Personnel, Sayed Rezwanul Islam

All Dissertations

The Sterile Processing Department (SPD), also known as the Central Sterile Services Department (CSSD), is an essential part of hospitals and healthcare facilities and is responsible for ensuring the cleanliness, sterility, and proper functioning of medical instruments. Sterile processing departments (SPDs) are key drivers of productivity, effectiveness, safety, and infection control in hospitals. A well-designed SPD workflow can enhance patient safety, reduce operating room (OR) delays, and improve productivity. To understand the flow of sterile processing and interactions between the OR and SPD, process maps and task analyses were developed through direct observations of the basic SPD functions: decontamination, assembly, …

Data-Driven Stochastic Programming For Disaster Housing Logistics Planning, Sheng-Yin Chen

All Dissertations

This dissertation develops an integrated modeling and solution framework for direct temporary disaster housing logistics under demand uncertainty. The proposed framework addresses the problem from short-term, long-term, and computational perspectives. First, a two-stage chance-constrained stochastic programming (TSCC) model is developed for short-term housing logistic planning, with demand scenarios generated via a data-driven spatial regression model that captures the relationship between housing demand, hazard exposure, and socioeconomic factors. A case study based on Hurricane Ian demonstrates that the TSCC model outperforms deterministic and traditional scenario-based models in both solution quality and robustness. Second, to address long-term housing logistics planning, a multi-horizon …