Operations Research, Systems Engineering and Industrial Engineering Commons^™

Combined Optimisation Of Machining Parameters, Tool Wear, Dimensional Errors And Quality Deviations In Multi-Pass Turning Operations, Mussa I. Mgwatu

Tanzania Journal of Engineering and Technology (TJET)

Measurements of on-line tool wear and part dimensional accuracy in machining operations are not readily available in machining shop floor because they involve higher investment such that the decisions of tool wear and part quality for intermediate cutting passes cannot be justified. This paper demonstrates how the optimisation of machining parameters can be made together with tool wear and part quality for turning operations. Two optimisation models were developed for maximum material removal rate and minimum production cost. A theoretical framework was initially presented before the two models were formulated. Input data for the models were adopted from previous studies …

Design Of A Sequential Logic Control System For Water Recycling In Car Wash Operations For Minimising Utility Costs, Enock W. Nshama, Mussa Iddi Mgwatu

Tanzania Journal of Engineering and Technology (TJET)

The car wash sector in Tanzania is expected to expand in the next few years, since the trend of imported cars is increasing. However, the traditional method of washing cars is subjected to water overuse and environmental pollution. This study presents a design of water recycling sequential logic control system to come up with a cost-effective car wash operation aimed at effectively utilising water and electricity resources. Data were collected at 78 car wash stations in Dar es Salaam region to determine water and electricity costs. Data were analysed using MS Excel and Minitab to establish the trend of utility …

Design Of A Fuzzy Set-Point Tracking Controller Based On The State-Dependent Control Characteristics Of Fuzzy Logic And Pid For Temperature Control Systems In Electrical Equipment, Rahim Mammadzada

Chemical Technology, Control and Management

This paper presents a Fuzzy-SPT (Fuzzy Set-Point Tracking) controller designed to combine the strengths of FLC (Fuzzy Logic Control) and PID (Proportional-Integral-Derivative) control while mitigating their limitations across varying operating conditions. Inspired by state-dependent reasoning but implemented within a single controller, the method uses internal logic to adapt the control effort across different operating regions. FLC handles rapid changes and nonlinear transients, enabling fast system response without overshoot, while PID-like integral action is activated when the FLC reaches steady state or enters a threshold region near the set point, eliminating residual errors and maintaining stable performance. By applying each behavior …

Vibrissae-Inspired Vision-Based Magnetic-Actuated Whisker, Zhixian Hu, Yi Cheng, Juan P. Wachs, Yu She

School of Industrial Engineering Faculty Publications

Tactile perception is significant for robotic operation in unstructured environments. Whisker-based sensors offer lightweight bio-inspired solutions, yet most rely on single-whisker sensing and are limited by passive interaction and constrained functionality. Here we present a circular array of eight independently actuated whiskers, each driven by a pulse-switchable permanent magnet and tracked by a camera. This design enables simultaneous multi-point sensing and coordinated actuation, supporting diverse functions. Quantitative analyses demonstrate accurate pixel-to-physical mapping, consistent pixel-to-force characterization, and long-term repeatability. In this work, we show that an vibrissae-inspired vision-based magnetic-actuated whisker array integrating distributed perception with active interaction achieves reliable physical mapping, …

From Test Tracks To Carbon Tracks: Evaluating The Carbon Emissions Of Autonomous Vehicle Development, Sarah Deniz

The Journal of Purdue Undergraduate Research

Autonomous vehicle (AV) development has seen a sharp increase in the past 10 years, and there is a significant energy cost of training AVs to meet safety regulations. The training process includes virtual simulation training as well as physical training on public roads and within private testing facilities. The high energy expenditure associated with AV training has a respective environmental cost that can be quantified as a lifetime “carbon debt” of released carbon emissions. The environmental sustainability of AVs has not been thoroughly studied in currently available literature, and this paper showcases a model that quantifies the total “carbon debt” …

Optimizing Military Fighter Jet Selection: A Decision Analysis Approach For Nuclear-Capable Aircraft, Eni Kelechi Ofong

Theses and Dissertations

This research investigates the strategic decision-making process involved in selecting a nuclear-capable fighter aircraft for NATO (North Atlantic Treaty Organization) nations in Europe. In adaptation to the continuously changing technology landscape and the necessity for enhanced deterrence capabilities, this study evaluates three potential aircraft: the legacy Panavia Tornado (PA-200), the widely deployed F-16 Fighting Falcon (F-16), and the advanced F-35 Lightning II (F-35). Each platform presents distinct advantages and limitations regarding operational performance, mission adaptability, cost-effectiveness, and long-term sustainability. To systematically assess these alternatives, the study employs various decision analysis frameworks, including Multi-Criteria Decision Analysis (MCDA), single dimensional value function …

Lecun-Pso Hybrid Initialization Of Neural Network Using Asymmetric Gait Features For Classification Of Parkinson’S Disease, Michael Joseph Carter

Theses and Dissertations

Parkinson's disease (PD) is a complex condition with a wide range of clinical symptoms. It is a progressive neurological disorder that has afflicted an estimated 1 million people in the US and 10 million worldwide. The diagnosis of PD is typically based on the presence of clinical features, with no specific diagnostic test or biomarker. The methods of assessment for PD are also used, in whole or in part, for similar symptom diseases such as Multiple Sclerosis, Essential Tremors, Multiple System Atrophy, Supranuclear Palsy, Dementia with Lewy bodies and Huntington’s disease. Many of the current clinical tests have low sensitivity …

Exploring The Impact Of Incorporating Artificial Intelligence Integrated Systems In The Workplace, Catherine Cruz Agosto Noda

Theses and Dissertations

This study focuses on assessing the impact of incorporating systems integrated with in the workplace by assessing the constructs of usability, cognitive load, and trust. The constructs are assessed by generation and experience level to determine which factors are relevant in a workplace setting. A workplace scenario was simulated by asking participants to complete tasks where they assumed the role of a warehouse manager assigned with assessing two scheduling systems – one with artificial intelligence and one without artificial intelligence. The participants were presented with three tasks of increasing difficulty for each prototype. Both quantitative and qualitative measures were used …

Warehouse Reconfiguration With Ats Lab, Ed Cantor, Dana Pazhouhesh, Mathew Oshinski, Samantha Sanchez

Senior Design Project For Engineers

The ATS Lab Warehouse Reconfiguration project is a collaborative effort between Kennesaw State University’s Department of Industrial and Systems Engineering and ATS Lab, located in Marietta, GA. The goal of this project is to redesign the current warehouse layout to enhance operational efficiency, reduce travel time, and implement sustainable inventory management practices, including 5S and Kanban. Aaron Roob, ATS Operations Manager, and Franklin Hungerford, Continuous Improvement Manager, led this initiative. Our team, “Sick Sigma’s,” is composed of Ed Cantor, our Project Manager, who is working as an intern at ATS during this process; Dana Pazhouhesh (Process Engineer); Matthew Oshinski (Quality …

Workstation Redesign, Mclean Dowell, Anna Seville, Luz Corral Parra, Farah Talib

Senior Design Project For Engineers

Tellerex is a leading ATM refurbishing and repair company operating from Atlanta, Georgia. Due to its rapid growth, the company is facing challenges pertaining to their parts repair and refurbishing lab. Tellerex aims to fulfill orders by 4:00 pm on the day they are placed, guaranteeing their clients same-day shipping. Orders often build up throughout the day, causing lab technicians to stress, rush through orders, and lose organization.

Tellerex has requested our help regarding one of their repair/refurbishment labs. Our goal is to redesign the lab workspace through human ergonomics and Lean Six-Sigma principles. The company wants us to create …

Optimizing Xo Throughput At Imerys, Derek Beasley, Brennan Chandler, Baris Erarslan, Cynthia Grogin

Senior Design Project For Engineers

This project is conducted in collaboration with Imerys to optimize the performance of the VSI (Vertical Shaft Impactor) system at their Plant 4 facility, focusing on improving the production of XO, a fine material used in products such as textured coatings, acid neutralization, and water filtration systems. The VSI operates continuously, producing several materials at the Marble Hill, Georgia location, including #1 Chip, #2 Chip, OZ, XO, Z, and 30–50. The main focus of this project is to increase the throughput of XO, as it requires both throughput improvement and product quality consistency to meet growing market demand. Imerys’ quality …

Optimal Network Maintenance And Restoration: Applications And Algorithms, Nayan Chakrabarty

Graduate Theses and Dissertations

In this dissertation, we consider three types of network optimization problems. In Chapter 1, we consider a network maintenance problem which focuses on time-based redeployment of multi-class nodes for reliable wireless sensor network coverage. Whereas previous research on time-based node redeployment assumes nodes are identical with respect to time to failure, we use multiple classes of sensor nodes to represent a scenario where nodes’ times to failure are dependent on positioning in the network. We propose a partial survival signature (PSS) approach for estimating area coverage reliability under a given time-based redeployment policy, where the PSS is estimated by Monte …

Barriers To Modernizing Aviation Maintenance Technician Education To Meet Emerging Industry Needs, Durwa Chavan

All Theses

Modernizing aviation maintenance education is essential to keep pace with emerging technologies, including electric propulsion systems and advanced avionics. As aircraft systems become more digitized and interconnected, there is a growing demand for qualified technicians who can conduct advanced diagnostics and maintenance. However, training programs have not kept pace with these technological shifts, creating a gap between workforce preparation and industry needs.

Using a qualitative research approach, this study conducted semi-structured interviews with industry professionals, educators, and regulatory personnel to identify gaps in existing training programs and Airman Certification Standards (ACS). This study addresses the disconnect between current aviation maintenance …

Detecting Non-Axisymmetric Instabilities In Fluid-Based Manufacturing Via Multi-View Tensor Analysis., Bidusi Khadka

Electronic Theses and Dissertations

Fluid-based manufacturing processes, such as inkjet printing and electrospinning, fabricate micro- and nano-scale structures with high precision, but are prone to complex fluid dynamics exhibiting axisymmetric and non-axisymmetric instabilities. Conventional monitoring often relies on single-camera inputs and symmetry assumptions, limiting the detection of three-dimensional anomalies like jet deflection. This study presents a novel multi-view streaming video-based anomaly detection framework to address this gap. The framework employs a modified Tensor Sequential Sampling (TSS) algorithm with edge-based sampling to capture geometric spatiotemporal features of each camera view using the videos obtained from an orthogonally positioned dual-camera setup. These features are fused with …

Full Factorial Design Of Carbon Content And Heating Temperature On Height Reduction In Bonnell Springs, Yurida Ekawati, Cendana Anggun Sasmitha, Mochamad Syamsul Ma’Arif

Journal of Mechanical Engineering Science and Technology (JMEST)

The durability of Bonnell springs, which are widely used in the manufacture of spring beds, is often compromised by height reduction during use, which negatively impacts product comfort and quality. This study aims to minimize spring height reduction by investigating the effects of heating temperature and carbon content in the spring steel. A full factorial experimental design was applied using two factors: heating temperature (250°C, 260°C, and 270°C) and carbon content (0.72%, 0.73%, and 0.74%). Nine treatment combinations were tested, with five replicates each, and the height reduction values were measured after 100 compression cycles. The data were analyzed using …

Exploring The Link Between Emotional States And Coding Task Quality: A Pilot Study, Aquib Reshad, Valentina Nino, Maria Valero, Adriane Randolph, Yang Shi

Faculty Articles

Emotions play a crucial role in shaping cognitive performance, yet their influence on programing remains understudied. This pilot study investigates the relationship between emotional states and coding task quality. Ten participants completed a programing task while their brain activity was recorded using electroencephalography (EEG), with frontal alpha asymmetry (FAI) applied as a neural marker of emotional valence. Emotional self-reports were collected using the Scale of Positive and Negative Experience (SPANE), and coding quality was evaluated through a structured rubric. Preliminary findings indicate a potential association between FAI and coding performance, whereas self-reported affect showed weaker or inconsistent patterns. Given the …

Diffog: Differentiable Policy Trajectory Optimization With Generalizability, Zhengtong Xu, Zichen Miao, Qiang Qiu, Zhe Zhang, Yu She

School of Industrial Engineering Faculty Publications

Imitation-learning-based visuomotor policies excel at manipulation tasks but often produce suboptimal action trajectories compared to model-based methods. Directly mapping camera data to actions via neural networks can result in jerky motions and difficulties in meeting critical constraints, compromising safety and robustness in real-world deployment. For tasks that require high robustness or strict adherence to constraints, ensuring trajectory quality is crucial. However, the lack of interpretability in neural networks makes it challenging to generate constraint-compliant actions in a controlled manner. This article introduces differentiable policy trajectory optimization with generalizability (DiffOG), a learning-based trajectory optimization framework designed to enhance visuomotor policies. By …

Exploring The Effectiveness Of Virtual Reality Learning Through Use Of Visual Eye-Tracking Analytics (Veta) And Biological Measurements, Mckinley Anne Sherman

Master's Theses

Virtual Reality (VR) offers an immersive and interactive platform for experiential learning. The purpose of this thesis was to evaluate the relationship between physiological responses and cognitive workload within a VR learning environment and to explore VR as an effective instructional tool. This research compared participant engagement, stress, and learning performance within a 6th-grade science module developed in VR by incorporating biometric data collected via Polar H10 heart rate monitor and Varjo Areo VR headset eye-tracking. Thirty-three participants completed a pre-lesson demographic survey, post-lesson survey, VR sickness questionnaire, and the NASA Task Load Index (NASA-TLX). While completing the lesson, the …

Intelligent Real-Time Flotation Froth Stability Monitoring Using Embedded Computer Vision: Lead (Pb) Processing Case Study, Ahmed Bendaouia, Taha Ismaili, Ismail Najib, Oussama Hasidi, Intissar Benzakour, Jianzhi Li, El Hassan Abdelwahed

Manufacturing & Industrial Engineering Faculty Publications

Froth stability in flotation refers to the ability of the froth layer to remain intact and avoid collapsing during the flotation process. A stable froth layer is crucial to maximizing mineral recovery and ensuring the efficient operation of flotation cells. Several factors influence the stability of the froth, including the depth of the froth, the crowding, the size of the bubbles, and the rate of movement of the froth. In this study, our main objective is to analyze and evaluate froth stability in real time, since it plays a critical role in process optimization for flotation-based mineral processing. We propose …

Use Of Polymer Fiber To Improve Mechanical Properties Of Hma Containing Recycled Asphalt Pavement (Rap), Ashraf Rahim, Shadi Saadeh, Hani Al Zaraiee

Mineta Transportation Institute

A great percentage of highways and roads in California are constructed with Hot Mix Asphalt (HMA), and, as California infrastructure ages, these highways and roads must be maintained and rehabilitated. Reclaimed Asphalt Pavement (RAP) is considered an excellent alternative to virgin (raw, unprocessed) materials because it reduces the use of virgin aggregate and binder. Also, the use of RAP decreases the amount of construction waste placed into landfills. This laboratory study investigated the effect of two different commercial polymer fibers on the mechanical properties of HMA with RAP. Three different HMA with RAP mixes were used in the study. One …

Process-Driven Manufacturability Constraints In Design For Wire Arc Additive Manufacturing, Monsuru Ramoni, Sampson Gholston, Albert E. Patterson

Manufacturing & Industrial Engineering Faculty Publications

Wire arc additive manufacturing (WAAM) has emerged as a useful option for large-scale metal additive manufacturing. It has gained widespread use in the aerospace industry and other applications that require large and complex custom parts. The process is a combination of a precise control system and a welding process, typically GTAW or MIG welding. It is a member of the directed energy deposition (DED) family of AM processes. Compared with many metal AM processes, it is relatively simple and cost-effective but almost always requires a significant amount of postprocessing before parts can be used. The AM-based nature of the process …

Tacscope: A Miniaturized Vision-Based Tactile Sensor For Surgical Applications, Md Rakibul Islam Prince, Sheeraz Athar, Pokuang Zhou, Yu She

School of Industrial Engineering Faculty Publications

The lack of tactile feedback in robot-assisted minimally invasive surgery (RMIS) limits surgeons’ ability to palpate tissues, a critical technique for locating abnormalities such as tumors. To address this challenge, we introduce TacScope, a novel, vision-based tactile sensor leveraging the magnification properties of a spherical-surface elastomer to provide tactile feedback for advanced clinical applications. TacScope features a robust, low-cost, and easyly fabricate design, enabling seamless integration into surgical robotic setups. It reconstructs high-resolution 3D geometry from variations in particle-density distribution across its elastomer surface, requiring only a single image for calibration. The curved elastomer membrane alters particle-density distribution under …

Multi-Material Printer Development, Jessica Hu, Phoebe Eplett

College of Engineering Summer Undergraduate Research Program

Surgeons require pre-surgical models to practice procedures and improve success rates. However, the current process of creating physical models for practice using 3D printing is limited to producing homogeneous mimics of the human body, while the human body is a heterogeneous structure composed of multiple materials with varying properties, including bones, muscles, and skin. Additive manufacturing methods cannot easily print multiple materials simultaneously, as current AM machines only print homogeneous material, unlike the human body. In this proposal, we aim to develop a multi-material additive manufacturing system, from software to hardware, to manufacture pre-surgical models. We will investigate multi-material AM …

Evaluating The Accuracy Of Gen Ai Detecting Misinformation, Alan Sebastian

College of Engineering Summer Undergraduate Research Program

This research project will investigate the ability of advanced Large Language Models (LLMs) to identify and assess misinformation across diverse forms of media, including text, images, and video. In an age where misleading content spreads rapidly across digital platforms, evaluating the reliability and integrity of AI systems tasked with fact-checking is critical. We will develop a comprehensive dataset composed of factual and misleading examples drawn from various well-known and reliable fact-checking organizations. Each item will be independently reviewed and transparently labeled to ensure reproducibility. We will then prompt a curated group of state-of-the-art LLMs—including GPT-4, Claude, Gemini, Perplexity, Grok, and …

3d Printing Scoliosis Braces, Zak Neddo, Jaylan Mo

College of Engineering Summer Undergraduate Research Program

As 3D printing technology continues to transform the healthcare industry, the need for FDA-compliant additive manufacturing facilities in public universities has become increasingly important. While private companies and medical research institutions have successfully integrated 3D printing for medical device prototyping and surgical planning, public universities—including Cal Poly—lack the dedicated infrastructure needed to support FDA-regulated medical manufacturing and research. This project aims to bridge that gap by researching, designing, and implementing a dedicated FDA-compliant section within Cal Poly’s multi-purpose 3D Printing Facility. Over the course of eight weeks, student researchers will study FDA regulations, design an optimized facility layout, and implement …

Deepseek, Chatgpt, Or Gemini? A Multi-Method Investigation Of Neural And Behavioral User Experience (Ux), Keziah Gopalla

College of Engineering Summer Undergraduate Research Program

As artificial intelligence tools become integral to everyday tasks, understanding how users interact with these systems is essential for improving user experience and system design. This research aims to investigate and compare the interface usability and emotional responses elicited by three prominent AI tools—ChatGPT, DeepSeek, and Google Gemini—using the Emotiv Insight EEG headset. By combining usability testing with emotional biometrics, this study offers a novel approach to evaluating conversational AI systems. The study will capture both subjective usability metrics and objective emotional markers such as arousal, valence, and engagement. Participants will complete standardized tasks using each AI tool, while their …

Resilience Engineering Via Bifurcation And Ecological Network Analysis: Demonstrated In An Electric Power Case Study, Rogelio Gracia Otalvaro

Doctoral Dissertations and Master's Theses

Modern systems are increasingly complex, interconnected cyber-physical systems that combine digital controls with physical infrastructure. This integration, along with the constant introduction of new technologies and actors into the network, enables reliable operation but introduces vulnerabilities to unexpected and varied disruptions and cascading failures, making resilience a critical concern. Traditional risk management and resilience assessment methods often struggle with the nonlinearity and dynamic behavior of these systems. This dissertation proposes a novel approach combining Bifurcation Analysis (BA) and Ecological Network Analysis (ENA) to enhance the understanding and improvement of system resilience. BA, a mathematical method from dynamical systems theory, is …

Robotic System With Tactile-Enabled Leaf Tracking For High-Resolution Hyperspectral Imaging Device For Autonomous Corn Leaf Phenotyping In Controlled Environments, Xuan Li, Ziling Chen, Raghava Uppuluri, Pokuang Zhou, Tianzhang Zhao, Darrell Zachary Good, Yu She, Jian Jin

School of Industrial Engineering Faculty Publications

Hyperspectral imaging of individual corn leaves provides valuable data for analyzing nutrient content and diagnosing diseases. However, existing leaf-level imaging techniques face challenges such as low spatial resolution and labor-intensive processes. To address these limitations, this study developed a robotic system integrated with a high-resolution line-scanning hyperspectral imaging device to autonomously scan a corn leaf. The hyperspectral imaging device used a vision-based tactile sensor for active leaf tracking throughout the scanning process, ensuring high image quality. Additionally, the device incorporated an in-hand leaf manipulation mechanism that ensured the leaf was properly positioned on the tactile sensing area at the start …

Transparent Eeg Analysis: Leveraging Autoencoders, Bi-Lstms, And Shap For Improved Neurodegenerative Diseases Detection, Badr Mouazen, Ahmed Bendaouia, Omaima Bellakhdar, Khaoula Laghdaf, Aya Ennair, El Hassan Abdelwahed, Giovanni De Marco

Manufacturing & Industrial Engineering Faculty Publications

Highlights

• Novel hybrid architecture: Combined autoencoders with bidirectional LSTM networks for enhanced EEG signal classification, achieving 98% accuracy in distinguishing AD, FTD, and healthy controls.

• Explainable AI integration: Implemented SHAP (SHapley Additive exPlanations) framework to enhance model transparency and identify entropy as the most influential feature for neurodegenerative disease detection.

• Optimal temporal segmentation: Demonstrated that 5-s EEG windows with 50% overlap provide the best balance between classification accuracy and computational efficiency.

• Comprehensive feature extraction: Utilized Power Spectral Density (PSD) analysis across standard frequency bands (Delta, Theta, Alpha, Beta, Gamma) following autoencoder-based dimensionality reduction.

• Superior performance validation: Outperformed traditional machine learning …

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Using Statistical Clustering Of Trajectory Data To Support Analysis Of Subject Movement In A Virtual Environment, Martin Galicia Avila, Douglas Timmer, Alley C. Butler

Manufacturing & Industrial Engineering Faculty Publications

Gracia de Luna conducted experiments with an HMD virtual environment in which human subjects were presented with surprise distractions. His collected data for head, dominant hand, and non-dominant hand included 6 DOF human subject trajectories. This paper examines this data from 57 human subject responses to those surprise virtual environment distractions using statistical trajectory clustering algorithms. The data is organized and processed with a Dynamic Time Warping (DTW) algorithm and then analyzed using the Density Based Spatial Clustering (DBSCAN) algorithm. The K-means method was used to determine the appropriate number of clusters. Chi Squared goodness of fit was used to …