Manufacturing Commons^™

Evaluation Of Peening Intensity With Nozzle-Mounted Sensor During Processing, Akinori Matsui, Shuji Hayashida, Yuji Kobayashi

15th International Conference on Shot Peening

In recent years, digital technologies have been increasingly applied in manufacturing, including visualization and anomaly detection in production equipment. In shot peening, Peening Intensity is a key process control indicator, but its measurement requires significant manual effort. This study aims to evaluate the possibility of using an AE-sensor-mounted nozzle to estimate Peening Intensity. We conducted experiments comparing sensor outputs with experimented Intensity under controlled conditions. A strong correlation (R² ≥ 0.95) was observed, suggesting that Peening Intensity can be estimated via AE sensing. This approach may contribute to labor-saving and automation in shot peening processes.

Comparison Of Anti-Fouling Performance Of Textured Glass Surface Fabricated By Ductile-Mode Peening And Precision Grinding, Hayato Tagaya, Yutaka Kameyama, Shuhei Kodama, Hideaki Sato, Kento Shinagawa, Ayumu Sekiguchi, Seiji Hirai, Hitoshi Ohmori

15th International Conference on Shot Peening

Recently, there has been a growing demand for precision processing glass. In addition to dimensional accuracy, surface texturing to impart functional properties has attracted increasing attention. For example, anti-fouling performance against powder adhesion is required for cover glasses of solar cells. Powder adhesion is governed by van der Waals forces, which depend on the surface texture of the substrate, suggesting that surface structures influence adhesion behavior. Our previous study demonstrated that angled fine particle peening (FPP) could fabricate a nanoscale fine texture on glass surfaces through ductile-mode peening—glass processing without brittle fracture. In this study, the effect of surface texturing …

Microstructural Changes And Residual Stress Generation On The Periodically Patterned Surface Texture Fabricated By Angled Fine Particle Peening, Yutaka Kameyama, Hideaki Sato, Ryokichi Shimpo

15th International Conference on Shot Peening

Focusing on the potential of peening technology as a surface texturing technique, angled fine particle peening (angled-FPP) has been proposed to fabricate a specific periodical surface structure, which possibly provides various surface functions. It is necessary to further characterize the textured surface to earn more advantages from angled-FPP. Thus, in this paper, texture formation phenomena, residual stress, and microstructural changes were investigated on the angled-FPP specimens.

Improving Fatigue Strength And Life Of Single Crystal Cmsx-4, Jochen Peter Fuhr, Lloyd Hackel, Nicolau I. Morar, Noah Holtham, Keivan Davami, Montu Sharma, Rajkumar Roy

15th International Conference on Shot Peening

The deep penetration of laser peening (LP) and retention of residual stress at high temperature by LP is significant in improving fatigue life and strength of superalloys exposed to high temperature and corrosion. Single crystal CMSX-4, was evaluated for stress relaxation and both fatigue life and fatigue strength of material that was LP-treated compared to non-LP and shot-peened (SP) specimens. LP was done with multiple layers using a 20 J/pulse laser where the laser high energy enabled using a 5 mm spot size on the metal surface. Stress measurements by the slitting technique showed the plastic penetration depth exceeded SP …

Optimization Of Surface Integrity And Fatigue Life In Hard Turning Of K110 Tool Steel, Y. A. Mashal, Mohamed G. Yousef, M. H. El-Axir

Journal of Engineering Research

The influence of various machining process parameters on surface integrity elements (e.g. surface roughness and surface residual stress) and fatigue life of hard metals is an important area of engineering. This study investigates the effect of various turning parameters on the surface integrity and fatigue life of K110 hard tool steel. The determination of residual stress was performed by a non-destructive testing technique using X-ray diffraction analysis (XRD). The experimental work extended to perform fatigue experiments using rotary bending machine which was designed and manufactured to assess the fatigue behavior under rotating bending stresses. In this investigation, single optimization of …

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 …

Recent Progress And Scientific Challenges In Wire-Arc Additive Manufacturing Of Metallic Multi-Material Structures, Sainand M. Jadhav, Sambhaji Kusekar, Akash Belure, Satyavan Digole, Abhijeet Mali, Muralimohan Cheepu, Manoj Mugale, Suhas Alkunte, Duckbong Kim

Faculty Articles

Metallic multi-material structures are heterogeneous structures characterized by changing composition, microstructures, and site-specific characteristics, advantageous for numerous applications where multifunctionality is desired. Metallic multi-material structures are known as bimetallic structures (BSs), which are functionally graded materials (FGMs). In recent years, wire-arc additive manufacturing (WAAM) advanced as a promising additive manufacturing process to realize the fabrication of these structures due to its high deposition rate, cost-effectiveness, and material utilization efficiency. This review presents a comprehensive overview of the recent progress, processing strategies, and scientific challenges in WAAM of multi-material structures. The paper begins with an introduction to multi-material structures, followed by …

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 …

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 …

Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan

All Dissertations

A dissertation is proposed to explore human comfort in human-robot collaboration (HRC) through modeling, prediction, and enhancement methodologies. Human comfort is a crucial yet underexplored factor in HRC, directly influencing task efficiency, trust, and overall collaboration effectiveness. Understanding the influential factors, developing computational models, and refining methods to improve human comfort in HRC are essential steps toward advancing the field of collaborative robotics. To address these challenges, multiple studies have been conducted. A series of experimental studies were performed to investigate how robot motion-based parameters affect human comfort in HRC. These studies examined both analytical comfort modeling approaches and physiological …

Material Extrusion 3d Printing Of Metal Alloy: Material, Methods And Application., Sihan Zhang

Electronic Theses and Dissertations

Material extrusion (MEX) additive manufacturing presents a promising pathway for producing metal components with complex geometries while avoiding the safety hazards associated with loose powder handling in conventional metal additive manufacturing processes. This dissertation investigates the development and optimization of MEX processes for aluminum alloys, addressing critical challenges in feedstock formulation, printing parameter optimization, and post-processing strategies. Three distinct approaches were explored to advance the capabilities of aluminum MEX: filament-based processing of 6061 aluminum, paste-based extrusion of 6061 aluminum, and development of a novel aluminum-magnesium-tin alloy system for space manufacturing applications. The filament-based approach successfully demonstrated the production of 6061 …

Microstructural Investigation Of Graphene Reinforced Nickel Aluminum Bronze Prepared Via Laser Powder Bed Fusion, Wen Qian, Maxwyll Mcconnell, Jazmin Ley, Luke Schwaninger, Xin Chen, Bai Cui, Joseph A. Turner

Mechanical Engineering Faculty Publications

Nickel aluminum bronze (NAB) powders coated with reduced graphene oxide (RGO) were successfully fabricated using additive manufacturing (AM) via laser powder bed fusion. The resulting samples were characterized using a suite of complementary techniques, including x-ray diffraction, scanning electron microscopy, energy-dispersive x-ray spectroscopy, nanoindentation, x-ray computed tomography, and electron backscatter diffraction. These methods were employed to reveal the micro- and nanoscale features within the fine dendritic microstructure. The as-fabricated microstructures were observed to deviate significantly from typical as-cast configurations. In the AM RGO-coated NAB specimens, the formation of the κ_I phase was notably suppressed and is attributed to the …

Predicting Leakage From Nuclear Material Containers At Los Alamos National Laboratory Through Drop Testing, Leak Testing, Finite Element Analysis And Digital Image Correlation, Jude M. Oka, Yu-Lin Shen, Osman Anderoglu, Pankaj Kumar, Rajendra Vaidya

Mechanical Engineering ETDs

Los Alamos National Laboratory (LANL) relies on containment vessels to safely manage special nuclear material. These containers are subject to rigorous testing—such as drop, fire, and water ingress testing—to ensure integrity under adverse conditions. While elastomer-based seals are well studied, metal-to-metal sealing mechanisms remain under investigation, particularly under dynamic loading. This research focuses on the relationship between container mating surfaces and impact loading through drop testing. Finite Element Analysis (FEA) models were developed and validated using Digital Image Correlation (DIC) to measure strain during impact. Drop tests at varying heights showed strong correlation between FEA and DIC results, confirming the …

Research On Technology Opportunity Identification By Integrating Technology Attribute Analysis And Competitive Environment Scanning —— A Case Study Of Industrial Robots, Daobin Gao

Journal of Scientific Information Research

[Purpose/significance] Placing technology opportunity identification in the perspective of technology attribute analysis and competitive environment scanning provides intelligence support for enterprises to select technology opportunities and formulate technology competitive strategies in complex and changing market competition environments.

[Method/process] Using patents as the data source, first, the BERTopic model is used to explore potential technical topics, Secondly, starting from the technical attributes, and from both global and local perspectives, we propose indicators of technical importance and technical attention, and use their cross screening to select candidate sets of technical opportunities, Finally, a market competition intensity index that takes into account market …

Aerospace Fastener Installation Tool, Anthony I. Berghout, Matthew K. Eggers, Liam Dunsmore, Jose Pardo

Mechanical Engineering

Contamination, particularly in aerospace manufacturing environments, is a significant concern, especially with fastener designs that incorporate torque-rated breakaway pieces for easier installation. These breakaway pieces are also known as pintails. Howmet has tooling that can collect loose pintails during installation, but they have small capacities and are not ergonomic for aerospace technicians. Their current need is for a light and ergonomic tool capable of installing a wide variety of Ergo-Tech® fasteners while having a large capacity to collect pintails and improve aerospace manufacturing methods. For this Critical Design Stage, we have finalized a design that allows Pintails to pass through …

Aluminum Boat Rotation Fixture, Kevin W. Heiskell, Nathaniel M. Conway, James S. Knowles, Austin J. Kehl

Mechanical Engineering

Aluminum fishing boats are widely used for various water-based activities, including fishing, transportation, and recreation. Their lightweight construction makes them ideal for maneuverability, particularly in regions like Australia. However, the manufacturing process presents challenges, specifically the need to weld both the interior and exterior seams of the hull. As the boat’s weight increases during assembly, flipping it becomes difficult and potentially hazardous. Traditional methods such as cranes or forklifts are inefficient and pose safety risks. To address this, our team developed a rotating fixture that secures the boat at two connection points, one at the bow and one at the …

In-Situ Defect Detection In Selective Laser Melting Using Convolutional Neural Networks, Ethan Gaigalas

Master's Theses

This thesis develops and trains a convolutional neural network (CNN) to classify defects in metal parts produced by selective laser melting (SLM) using acoustic emission (AE) data. The model successfully identified porosity and standard build layers with high accuracy but consistently struggled to classify lack of fusion (LOF) defects, regardless of input type, normalization, or class count. These results suggest that while AE signals contain distinguishable features for certain defect types, LOF signals may be too subtle or inconsistent for reliable detection. The study addresses the ongoing challenge of in-situ quality monitoring in metal additive manufacturing, where defects like cracks, …

7lr-C Upper Limb Dancing Prosthetic, Victor Ochoa, Zoe Kelemen, Ged Mulingtapang, Marley Paltiel

Mechanical Engineering

Ella Wallis, a student at Cal Poly and performer in the Cal Poly Drag Club with a trans humeral upper limb difference, wants a prosthetic device that allows for a large range of motion and high degree of articulation to help them better dance in the style of voguing, allowing them to express themselves further while performing. The prosthetic arm is body-driven and relies on momentum to reposition. It attaches to the user through a harness, which is clipped to a socket with elastic straps to not impede the shoulder’s range of motion. The design contains urethane resin, aluminum, stainless …

Llnl Raft Flash Pole Redesign, Jack Stangel, Evan Wolfson, Jake Borden, Alexander Meeter

Mechanical Engineering

During research exercises in the ocean, Lawrence Livermore deploys a fleet of rafts outfitted with flash modules affixed to tall poles (in tandem called flash poles) that flash while a photo is taken to act as datums for data collection. The current flash pole design that the LIDSS (Lawrence Livermore Independent Diagnostic Scoring System) team uses is too short to be visible in high seas, not mechanically suited to be made taller, too susceptible to the elements and blunt impact and too difficult to service. We aim to solve these issues.