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Humans Vs. Ai: Comparing Approaches To Disaster Response Interface Design, Kelly Nguyen, Olivia Hartmann, Kailey Hrbek, Madeline Nees, Gabrielle Roth, Emily Silliman Aug 2026

Humans Vs. Ai: Comparing Approaches To Disaster Response Interface Design, Kelly Nguyen, Olivia Hartmann, Kailey Hrbek, Madeline Nees, Gabrielle Roth, Emily Silliman

Discovery Day - Daytona Beach

Amphibious emergency support operations involve rapidly changing information, high stress, and significant cognitive demands, which can make decision-making and situation awareness more difficult for operators. When interfaces are poorly designed, they can contribute to issues such as alarm flooding, confusion from incomplete information, and delayed responses, all of which increase operational risk during time-critical disaster situations. This study explores whether using generative AI to assist with interface design will improve performance (output quality and effort) and usability compared to a manual sketch mock-up. Participants were asked to design a dashboard interface to support disaster relief operations following a Category 5 …

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Evaluating The Impact Of Ai-Assisted Tools On Novice Interface Design For Combat Search And Rescue Operations, Louis Pandolfo, Kaylee H. Akerlund, Cassidi Ellison, Sierra Martinez Aug 2026

Evaluating The Impact Of Ai-Assisted Tools On Novice Interface Design For Combat Search And Rescue Operations, Louis Pandolfo, Kaylee H. Akerlund, Cassidi Ellison, Sierra Martinez

Discovery Day - Daytona Beach

Combat Search and Rescue (CSAR) operations are specialized military missions with the goal of rescuing personnel from hostile territory, often involving helicopters and elite teams tasked with locating and stabilizing survivors. It is imperative to a mission's success that any interface used by rescuers is efficient and usable, as they work under high risk, high stress, and time limited conditions. This study examined how access to artificial intelligence (AI) design tools influence novice interface design under a time constraint. Participants completed an interface design exercise based on a simulated U.S. Navy maritime disaster and CSAR mission. The overall aim of …

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An Innovative Approach To Real-Time Noise Monitoring And Detection In Airport Ramp Operations, Grace Hamilton, Nicole E. Egan, Anderson Peralta, Deyaneira Rodriguez, Maria G. Valentinez Aug 2026

An Innovative Approach To Real-Time Noise Monitoring And Detection In Airport Ramp Operations, Grace Hamilton, Nicole E. Egan, Anderson Peralta, Deyaneira Rodriguez, Maria G. Valentinez

Discovery Day - Daytona Beach

Airport ramp personnel are routinely exposed to hazardous noise levels exceeding occupational safety thresholds, increasing the risk of permanent hearing loss, degraded communication, and operational incidents. Traditional ramp noise management relies primarily on periodic monitoring and personnel protective equipment (PPE), which limits real-time hazard recognition and a proactive risk mitigation strategy. The purpose of this study is to evaluate the safety and financial effectiveness of implementing a real-time noise monitoring and detection system within airport ramp operations in alignment with Safety Management System (SMS) principles. A literature review, Preliminary Hazard Analysis (PHA), and financial cost-benefit analysis were conducted to compare …

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Mob-Air: Sensing Package Development For Maritime Search And Rescue Uav, Rachel Jacobsen, Liam Abraham, Ethan Thomas, Madeline Thomson, Nikolaos Triantafilloy Aug 2026

Mob-Air: Sensing Package Development For Maritime Search And Rescue Uav, Rachel Jacobsen, Liam Abraham, Ethan Thomas, Madeline Thomson, Nikolaos Triantafilloy

Discovery Day - Daytona Beach

Man-overboard (MOB) search and rescue (SAR) operations present a persistent maritime challenge, where rapid and reliable detection of a person in the water is critical to mission success. MOB-Air is developing a modular sensing package for an unmanned aerial system (UAS) to enhance SAR missions through autonomous human detection in maritime environments. This capability directly supports Navy maritime operations by improving overboard recovery, reducing search timelines, and enabling persistent aerial monitoring in contested or resource-constrained environments. The system evaluates thermal and visual imaging sensors using a custom horizontal-rail testing frame with a mobile payload. A ROS 2–based software architecture supports …

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Analytical And Numerical Solutions For The Hydrogen Atom, Kassidy Myers Aug 2026

Analytical And Numerical Solutions For The Hydrogen Atom, Kassidy Myers

Discovery Day - Daytona Beach

The Schrödinger equation is the foundational equation of non-relativistic quantum mechanics. The hydrogen atom is the simplest system for solving this equation, as it consists of only one proton and one electron. In this project, we work on the Schrödinger equation that models the spherically symmetric states of the hydrogen atom that depend only on the radial coordinate. We simplified and nondimensionalized the radial equation and solved the resulting equation using a power series (Frobenius) method. This approach revealed the physically meaningful solutions and led to quantized energy levels. In addition to finding the analytical solution, we numerically solve the …

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Ai-Driven Scheduling Algorithms For Private Aviation, Tayan Benson, Jessica Buskey, Gabriel Camacho, Caitlyn A. Gabrinowitz Aug 2026

Ai-Driven Scheduling Algorithms For Private Aviation, Tayan Benson, Jessica Buskey, Gabriel Camacho, Caitlyn A. Gabrinowitz

Discovery Day - Daytona Beach

Private aviation scheduling is complex and dynamic, requiring frequent aircraft repositioning based on demand and operational constraints, unlike fixed commercial airline schedules. As fleets grow beyond 300 aircraft, traditional deterministic methods become too slow, leading to the use of approaches such as genetic algorithms, but neural network-based methods have not seen in-depth exploration. This project models aircraft scheduling as a network, where airports and flights form a graph. It explores advanced AI methods, including graph neural networks and spatio-temporal graph neural networks (STGNNs), to capture both network structure and time constraints. The goal is to generate efficient daily schedules from …

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Evaluating Engagement-Based Learning Opportunities In Undergraduate Manufacturing Education, Salil Bapat, Ajay P. Malshe Aug 2026

Evaluating Engagement-Based Learning Opportunities In Undergraduate Manufacturing Education, Salil Bapat, Ajay P. Malshe

MMRL-XMO Industrial Seminar

This paper presents an engagement-based learning framework implemented in an undergraduate mechanical engineering course on additive manufacturing, with a specific focus on metal additive manufacturing (AM). The course integrated in-class discussion of AM fundamentals, discussing processes, materials, and designs with parallel semester-long team-based activities for encouraging and increasing hands-on student engagement. The paper specifically elaborates on the implementation of the project activity, focused on the design and manufacturing of bio-inspired lightweight lattice structures. The outcomes and reflections demonstrate the effectiveness of this approach in enhancing student engagement and complement the in-class lectures while also presenting future opportunities for improvements. This …

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Bioinspired Lightweight Lattices For Thermal Management And Structural Stiffness: A Simulation Study, Shivani Pandit, Vinay Kenny, Salil Bapat, Ajay Malshe Aug 2026

Bioinspired Lightweight Lattices For Thermal Management And Structural Stiffness: A Simulation Study, Shivani Pandit, Vinay Kenny, Salil Bapat, Ajay Malshe

MMRL-XMO Industrial Seminar

The evolution of lightweight biological structures for thermal regulation and structural stiffness, driven by multifunctionality requirements and ecological environments, provides a valuable blueprint for the development of lattice structures capable of both heat dissipation and mass reduction. Biological systems such as butterfly wing scales, weevil exoskeleton, toucan beak, pomelo peel, and other hierarchical porous morphologies exhibit highly optimized geometries that balance thermal management, mechanical performance, and lightweighting. Engineering lattice structures, including both strut-based and surface-based lattice topologies, offer analogous design strategies that can replicate these biological functionalities while remaining tailorable to not only the functionality and application-specific requirements but also …

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Microstructure And Mechanical Behavior Of High Strength Additive Alloys With Nanoscale Precipitates, Hyeongseob Kim, Emiliano Flores, Xinghang Zhang Aug 2026

Microstructure And Mechanical Behavior Of High Strength Additive Alloys With Nanoscale Precipitates, Hyeongseob Kim, Emiliano Flores, Xinghang Zhang

MMRL-XMO Industrial Seminar

This review highlights how additive manufacturing (AM) enables the formation of metastable nanoscale precipitates through rapid nonequilibrium solidification and cyclic thermal histories, leading to mechanical properties unattainable by conventional processing. Recent advances in AM Al- and Ni-based alloys are discussed with emphasis on the relationship between nanoscale heterogeneity and deformation behavior. In Al alloys, nanolamellar intermetallic architectures generate strong heterostructure-induced back stresses and enable ultrahigh compressive strengths approaching 1 GPa while maintaining deformability. In Ni-based systems, in situ oxide nanoprecipitates improve high-temperature mechanical behavior of 718 Ni alloys, while nanoprecipitate evolution in Haynes 230 Ni alloys promotes deformation twinning. These …

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Powder Metal Characterization For Additive Manufacturing, Paul Mort, Donovan Stumpf, Rajeshree Varma, Dina Khattab, Xiaoling Shen, Michael Titus, Michael Sealy, Jeff Jaworek, Jake Kim, Langdon Feltner Aug 2026

Powder Metal Characterization For Additive Manufacturing, Paul Mort, Donovan Stumpf, Rajeshree Varma, Dina Khattab, Xiaoling Shen, Michael Titus, Michael Sealy, Jeff Jaworek, Jake Kim, Langdon Feltner

MMRL-XMO Industrial Seminar

Powder characterization is important for specification and qualification of powder feedstock materials used in powder-bed additive manufacturing.  Characteristics include both distributed properties (i.e., particle morphology, size, shape, curvature distributions) as well as ensemble behavior including flow, spread-ability, and packing.  Ensemble behavior is highly sensitive to boundary conditions in thin-layer processing, for example as required for additive manufacturing, thin-layer calendaring for dry-cathode processing, and many tribology-related applications.  Particulate flow and packing are inherently multi-body ensemble processes; the distributed characteristics of particulates comprise said multi-body effects. Characterization of powder feedstock is important for manufacturing process control, resource efficiency, and product quality.  This …

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Generative Ai For Decision Making In The Manufacturing Systems, Xingyu Li Aug 2026

Generative Ai For Decision Making In The Manufacturing Systems, Xingyu Li

MMRL-XMO Industrial Seminar

Manufacturing systems increasingly demand real-time, multi-objective, and human-aligned decision-making that existing approaches cannot provide. In this study, we introduce the Generative Manufacturing System (GMS), a paradigm that reframes manufacturing decisions as samples from a learned conditional distribution, replacing inference-time search in the existing optimization-based approaches. Two instantiation examples are presented in manufacturing decision-making, including layout design and production scheduling, using domain-adapted diffusion models conditioned on operational constraints and human preferences. Experiments demonstrate 100% feasibility, near-zero objective matching error, and 25x decision making speed gain, establishing generative AI as a scalable, efficient, and human-centric decision-making engine for modern manufacturing systems.

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Hybrid Bio-Inspired Design Approach For Lightweighting In Additive Manufacturing: A Feasibility Study, Ryan Capstick, Shivani P. Pandit, Salil Bapat Aug 2026

Hybrid Bio-Inspired Design Approach For Lightweighting In Additive Manufacturing: A Feasibility Study, Ryan Capstick, Shivani P. Pandit, Salil Bapat

MMRL-XMO Industrial Seminar

This paper explores the feasibility of extracting biological design information from multiple species for manufacturing functional lightweight architectures. Biology offers a vast range of designs, materials, and organizational strategies to achieve these goals. Over the past few years, additive manufacturing (AM) has been increasingly applied to manufacture various bio-inspired lattice geometries. Commonly, this approach involves taking inspiration from one specific biological example for manufacturing and testing. However, converging multiple biological design ideas into a single engineering structure for manufacturing is rarely reported. In this work, design inspirations from two biological species (cuttlefish and mantis shrimp) are combined to model various …

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A Generalized Real-Time Geometric Virtualization Of Material Removal Processes For A Factory Digital Twin Platform, Jongwoo Han, Chang Hyeon Mun, Martin Byung-Guk Jun, Hyung Wook Park Aug 2026

A Generalized Real-Time Geometric Virtualization Of Material Removal Processes For A Factory Digital Twin Platform, Jongwoo Han, Chang Hyeon Mun, Martin Byung-Guk Jun, Hyung Wook Park

MMRL-XMO Industrial Seminar

As the transition toward autonomous smart factories and Cyber-Physical Production Systems (CPPS) accelerates, real-time digital twin implementation of manufacturing processes has emerged as a critical enabling technology. However, existing virtualization approaches present fundamental limitations: mesh-based Boolean methods are computationally infeasible for real-time processing due to their CPU-bound operations, while pure voxel-based methods suffer from staircase artifacts at geometric boundaries and exhibit exponentially increasing computational demands as resolution improves. To overcome these limitations, this paper proposes a GPU-accelerated real-time geometric virtualization method combining Signed Distance Field (SDF) with the Marching Cubes algorithm. The proposed method executes massively parallel SDF subtractive operations …

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Programmable Hybrid And Gradient Constant Mean Curvatures For High-Performance Multifunctional Mechanical Metamaterials, Ajith Annavajhula, Gary J. Cheng Aug 2026

Programmable Hybrid And Gradient Constant Mean Curvatures For High-Performance Multifunctional Mechanical Metamaterials, Ajith Annavajhula, Gary J. Cheng

MMRL-XMO Industrial Seminar

Architected solids that combine high stiffness, strength, toughness, and ductility in one geometry are difficult to manufacture without specialised feedstocks or sequential consolidation. Two complementary architectures are built here from a single curvature-programmed building-block library of four constant-mean-curvature (CMC) shell topologies — Schwarz Primitive (SP), Schwarz Diamond (SD), Schoen's I-WP, and FRD — that share commensurate cubic facets and admit C0 /C1 /C2 continuity at every interface. Multi-objective hybridisation gives an open-cell metamaterial with specific axial stiffness E*/ρ* = 63.6 GPa·cm3 ·g-1 and specific peak compressive stress σpeak/ρ* = 416.9 MPa·cm3 ·g-1, exceeding the I-WP single family by 40% in …

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An Automated Construction Framework For Immersive Digital Twins With Ground-Based Cad Pose Estimation, Huichan Park, Yuseop Sim, Byoungkwon Yoon, Asif Tanveer, Martin Byung-Guk Jun, Sang Won Lee Aug 2026

An Automated Construction Framework For Immersive Digital Twins With Ground-Based Cad Pose Estimation, Huichan Park, Yuseop Sim, Byoungkwon Yoon, Asif Tanveer, Martin Byung-Guk Jun, Sang Won Lee

MMRL-XMO Industrial Seminar

This paper presents an automated workflow for constructing an immersive digital twin by combining multimodal field sensing, ground-based CAD-to-point-cloud registration, and physics engine-based scene generation. To reduce human intervention during digital twin construction, the proposed pipeline estimates machine poses by registering CAD-derived point clouds to a colorized point cloud map. Instead of relying on unconstrained six-degree-of-freedom point cloud registration algorithms, such as Iterative Closest Point (ICP) or TEASER++, the proposed method detects the ground plane, reduces the search space to planar translation and yaw, and applies coarse-to-fine slicing followed by 3-DoF planar ICP refinement. The method was evaluated using two …

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Real-Time Two-Stage Machine Sound Monitoring For Wire-Edm State Recognition, Yuseop Sim, Yonghyun Lee, Edgar James Yother, Duju Lee, Hojun Lee, Byoungkwon Yoon, Asif Tanveer, Martin Byung-Guk Jun Aug 2026

Real-Time Two-Stage Machine Sound Monitoring For Wire-Edm State Recognition, Yuseop Sim, Yonghyun Lee, Edgar James Yother, Duju Lee, Hojun Lee, Byoungkwon Yoon, Asif Tanveer, Martin Byung-Guk Jun

MMRL-XMO Industrial Seminar

Operational state monitoring is critical for assessing machine utilization and reducing downtime in smart manufacturing. However, many Wire Electrical Discharge Machining (Wire EDM) systems remain legacy machines with limited access to controller-level data, making non-invasive sensing approaches necessary. This study proposes a lightweight two-stage sound-based operational state monitoring framework using an Internal Sound Sensor (ISS) and a 1D convolutional neural network (CNN). The ISS, built around a stethoscope-inspired bell structure, captures machine-specific acoustic signatures while suppressing ambient machine-shop noise and spark-related acoustic interference. The proposed framework classifies machine states in two stages: Stage 1 identifies coarse states such as beep, …

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Development Of Scalable Fsr Sensor Array-Based Human Footprint Acquisition Module For Manufacturing Automation, Hangyeom Lee, Yuseop Sim, Hojun Lee, Byoungkwon Yoon, Martin Byung-Guk Jun Aug 2026

Development Of Scalable Fsr Sensor Array-Based Human Footprint Acquisition Module For Manufacturing Automation, Hangyeom Lee, Yuseop Sim, Hojun Lee, Byoungkwon Yoon, Martin Byung-Guk Jun

MMRL-XMO Industrial Seminar

As human-robot collaboration becomes increasingly prevalent in modern industrial automation, optimizing mobile robot navigation to align with human spatial preferences is essential for efficient workflows. Conventional spatial tracking modalities, such as vision, LiDAR, and Inertial Measurement Units (IMUs), face several limitations in factory environments due to visual occlusion, variable lighting, and accumulated signal drift. To overcome these environmental interferences, this paper proposes a scalable and versatile human footprint acquisition module based on a Force Sensitive Resistor (FSR) sensor array. This presented architecture utilizes a modular grid of FSR sensors integrated with embedded Microcontroller Units (MCUs) and Data Acquisition (DAQ) modules, …

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Development Of A Cold Spray-Based Dry Manufacturing Process For Lfp Battery Cathode, Hayoung Jeong, Martin Byung-Guk Jun Aug 2026

Development Of A Cold Spray-Based Dry Manufacturing Process For Lfp Battery Cathode, Hayoung Jeong, Martin Byung-Guk Jun

MMRL-XMO Industrial Seminar

Conventional lithium-ion battery cathodes are typically fabricated through slurry-based processing, which requires organic solvents, coating, drying, and post-processing steps. Although this process is widely used, the use of toxic solvents such as N-methyl-2-pyrrolidone and the long drying process increases manufacturing complexity, energy consumption, and environmental burden. In this work, a cold spray-based solvent-free process was investigated as a one-step route for fabricating lithium iron phosphate cathode layers. A representative cathode composite powder consisting of lithium iron phosphate, carbon black, and polyvinylidene fluoride was prepared with a weight ratio of 10:1:1. To improve powder feeding behavior, 0.1 wt% fumed silica was …

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Rgb-D Object Pose Estimation Via Sam2 Segmentation And Coarse-To-Fine Point Cloud Registration, Daniel Sungwoo Bae, Changheon Han, Hangyeom Lee, Hojun Lee, Martin Byung-Guk Jun Aug 2026

Rgb-D Object Pose Estimation Via Sam2 Segmentation And Coarse-To-Fine Point Cloud Registration, Daniel Sungwoo Bae, Changheon Han, Hangyeom Lee, Hojun Lee, Martin Byung-Guk Jun

MMRL-XMO Industrial Seminar

Precise estimation of a workpiece’s position and orientation is indispensable for advanced robotic automation in a smart manufacturing setting, where robotic manufacturing tasks such as welding, spraying, and assembly must be performed on complex three-dimensional components with higher adaptability and guaranteed repeatability. In response to such requirements, this paper presents an integrated vision-based pipeline for object 6D pose estimation using an RGB-D camera mounted on a collaborative robot arm (FANUC CRX-10iA/L). The proposed system applies the Segment Anything Model 2 (SAM2) to isolate the target object from a single RGB frame via a single point prompt, generating a segmentation mask …

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An Llm-Based Multi-Agent System For Manufacturing Decision Support: Material–Process Recommendation And Process Parameter Optimization, Geonhwi Lee, Yulseok Byun, Seungjae Han, Martin Byung-Guk Jun, Hae-Jin Choi Aug 2026

An Llm-Based Multi-Agent System For Manufacturing Decision Support: Material–Process Recommendation And Process Parameter Optimization, Geonhwi Lee, Yulseok Byun, Seungjae Han, Martin Byung-Guk Jun, Hae-Jin Choi

MMRL-XMO Industrial Seminar

As product fabrication environments become increasingly diverse, there is a growing need for decision support that connects users’ fabrication intents and requirements to appropriate manufacturing conditions. In this study, we propose an LLM-based multi-agent system for manufacturing decision support that systematically supports material and process recommendation, equipment selection, process parameter optimization, and result prediction. The proposed system utilizes manufacturing literature and technical documents through RAG-based manufacturing knowledge retrieval and excludes low-relevance documents before response generation by verifying the relevance of retrieved documents to the user query. In addition, it explores support relationships among materials, processes, and equipment based on a …

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Multi-Scale In-Situ Powder Stream Characterization For Laser Directed Energy Deposition, Guang Yang, Clara Mock, Salil Bapat, Ajay Malshe Aug 2026

Multi-Scale In-Situ Powder Stream Characterization For Laser Directed Energy Deposition, Guang Yang, Clara Mock, Salil Bapat, Ajay Malshe

MMRL-XMO Industrial Seminar

Powder stream quality in laser directed energy deposition (L-DED) is a critical determinant of deposition consistency and final part quality, yet it remains largely uncharacterized in real-time during operation. This paper presents a dual-scale, vision-based in-situ characterization framework that addresses powder stream monitoring at two complementary levels: macro-scale flow quality assessment for real-time process monitoring and micro-scale particle tracking for digital twin data acquisition. Both scales are implemented on a single high-speed camera reconfigured between two resolution and frame-rate settings, eliminating the need for dedicated multi-camera infrastructure. At the macro scale, an OpenCV-based image processing pipeline operating at 1280 × …

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Challenges And Opportunities For Advanced Manufacturing To Deliver War-Winning Technology To The Warfighter, Clara Mock, Jian Yu, Eric Wetzel, Isaac Nault, Robert Jensen, James Snyder, Megan Lynch, Christopher Hoppel Aug 2026

Challenges And Opportunities For Advanced Manufacturing To Deliver War-Winning Technology To The Warfighter, Clara Mock, Jian Yu, Eric Wetzel, Isaac Nault, Robert Jensen, James Snyder, Megan Lynch, Christopher Hoppel

MMRL-XMO Industrial Seminar

Global supply chain vulnerabilities and contested logistics environments necessitate a paradigm shift in military production and sustainment. Advanced Manufacturing (AdvM) offers the critical agility required to rapidly produce and repair components. This report reviews the current state of AdvM technology and its dual role in supercharging the domestic Defense Industrial Base (DIB) while enabling distributed, Point-of-Need (PoN) manufacturing directly on the battlefield. First, we identify persistent challenges hindering widespread AdvM adoption, including material limitations, process transferability, and arduous certification pathways. To address these barriers, this paper highlights emerging solutions across four key domains: (1) the formulation of novel feedstocks, ranging …

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U.S. Army Allied Trades Specialist Workforce Development For Advanced Manufacturing, Christopher Bolton, Moises Chavez, Matthew Robert Patterson, Kaitlyn Toth Aug 2026

U.S. Army Allied Trades Specialist Workforce Development For Advanced Manufacturing, Christopher Bolton, Moises Chavez, Matthew Robert Patterson, Kaitlyn Toth

MMRL-XMO Industrial Seminar

Under different titles - Machinist, Metal Worker, and now Allied Tradesman - the U.S. Army has employed soldiers to maintain equipment using traditional machining, welding and fabricating technologies. Recent advancements in metal and polymer additive manufacturing, subtractive manufacturing, computer-aided design, and reverse engineering provide capabilities that enable warfighters to sustain, adapt, and modify existing systems, directly enhancing combat effectiveness. However, soldiers in fabrication-focused roles currently receive limited training in the application of these novel advanced manufacturing technologies to mission-relevant tasks. The training provided through Advanced Individual Training pipelines has not kept pace with the state-of-the-art technologies used in industry, leaving …

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Experimental Study Of Mechanical Performance Of Fused Filament Fabricated Thin Walls Via Stress-Oriented Toolpath Planning Under Concentrated Compressive Load, Siying Chen, Xingyu Fu, Fengfeng Zhou, Martin Byung-Guk Jun Aug 2026

Experimental Study Of Mechanical Performance Of Fused Filament Fabricated Thin Walls Via Stress-Oriented Toolpath Planning Under Concentrated Compressive Load, Siying Chen, Xingyu Fu, Fengfeng Zhou, Martin Byung-Guk Jun

MMRL-XMO Industrial Seminar

This paper investigates the mechanical performance of fused filament fabricated (FFF) thin-walled structures with stress-oriented toolpath planning. Specifically, the failure of 3D printed thin walls via stress-oriented toolpath planning were experimentally characterized under concentrated compressive load. The thin wall structure was generated using the dense infill toolpath generation algorithm via an improved Depth-First Search (DFS) framework proposed in our previous work [1]. With the algorithm, the toolpaths were planned according to the principal stress direction, which helped improve compressive strength, improving buckling resistance. Stress-oriented toolpath that aligned along the principal stress direction (S1) was proposed to fabricate the thin wall. …

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Resource Efficient Hybrid Manufacturing: Integration Of Reconfigurable Tooling, Flexible Deformation And Non-Planar Deposition, Shivaprasad Cherukupally, Venkata Reddy Aug 2026

Resource Efficient Hybrid Manufacturing: Integration Of Reconfigurable Tooling, Flexible Deformation And Non-Planar Deposition, Shivaprasad Cherukupally, Venkata Reddy

MMRL-XMO Industrial Seminar

Flexible and hybrid processes play an important role in smart manufacturing by enabling adaptable, resource-efficient and eco-friendly fabrication strategies. In this work a hybrid combination of Double Sided Incremental Forming (DSIF), Reconfigurable Tooling (RT) and Wire-based Directed Energy Deposition (WDED) is proposed to utilize non-planar sheet metal substrates during metal additive manufacturing. The approach aimed to explore the geometrical freedom offered by DSIF and tailored thermal and mechanical support provided by RT to reduce support structure requirements, substrate deformation and component distortion. Experimental studies demonstrate successful fabrication of complex geometries, improved dimensional accuracy and enhanced surface quality through suitable process …

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The Effect Of Particle Fillers On The Adhesion Of Co-Printed Thermoplastics And Photopolymers Using Dissimilar Material Printing, Jean Carlos Corraliza-Rodriguez, Christopher John Steines, James John Plotzke, Monique Suzanne Mcclain Aug 2026

The Effect Of Particle Fillers On The Adhesion Of Co-Printed Thermoplastics And Photopolymers Using Dissimilar Material Printing, Jean Carlos Corraliza-Rodriguez, Christopher John Steines, James John Plotzke, Monique Suzanne Mcclain

MMRL-XMO Industrial Seminar

The demand for multi-material additive manufacturing (AM) is increasing due to the complex design requirements needed to make advanced devices for a variety of fields.[MM1.1] Dissimilar Material Printing (DMP) is an extreme form of multi-material printing that involves combining materials that have dissimilar properties (i.e. mechanical, thermal, etc.) and processing requirements. On version of DMP includes integrating Fused Filament Fabrication (FFF) with Direct Ink Write (DIW) to co-print polymers such as thermoplastics and glass bead reinforced photopolymers. Previous research has focused in understanding the effect of print bed holding temperature on interfacial adhesion in FFF/DIW DMP. However, there is still …

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Controllable Failure In 3d Printed Carbon Fiber Petg Using Programmable Cooling Conditions, Anna Keim, Monique Mcclain Aug 2026

Controllable Failure In 3d Printed Carbon Fiber Petg Using Programmable Cooling Conditions, Anna Keim, Monique Mcclain

MMRL-XMO Industrial Seminar

The tensile properties of 3D printed specimens using fused filament fabrication (FFF) are the subject of extensive research. Forced convection from print cooling fans has been shown to have a measurable effect on print quality and tensile performance because the cooling rate of the polymer strongly controls interlayer adhesion. Print fan speeds are typically kept constant throughout a print, but changing the fan cooling throughout a print has the potential to locally tune interlayer strength and therefore, the location of break. This work shows the effect of selectively cooling printed regions, with the goal of repeatably inducing failure in these …

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A Semantic Evaluation Approach For Improving The Reliability Of Llm Outputs In Manufacturing, Dongjun Yun, Martin Byung-Guk Jun Aug 2026

A Semantic Evaluation Approach For Improving The Reliability Of Llm Outputs In Manufacturing, Dongjun Yun, Martin Byung-Guk Jun

MMRL-XMO Industrial Seminar

Large Language Models (LLMs) have recently shown strong performance across various domains, including manufacturing, where they are increasingly used with multi-agent systems for semi-autonomous tasks such as real-time machine monitoring and operator support. However, their reliability remains a concern due to hallucination, where outputs may appear plausible but contain incorrect or inconsistent information. To address this issue, this study proposes a semantic evaluation methodology for assessing the reliability of LLM-generated content in machining  environments. The approach is based on the embedding model BGE-M3 and focuses on capturing semantic consistency between machine observations and LLM-generated operational recommendations by comparing them against …

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A Practical Digital Twin Framework For Safe Human-Robot Collaboration In Resilient In-House Manufacturing, Harshkumar K. Parmar, Shivakumar Raman Aug 2026

A Practical Digital Twin Framework For Safe Human-Robot Collaboration In Resilient In-House Manufacturing, Harshkumar K. Parmar, Shivakumar Raman

MMRL-XMO Industrial Seminar

Recent supply-chain disruptions and growing interest in domestic production have renewed attention to in-house manufacturing systems that are flexible, practical, and easier to deploy. Human-robot collaboration (HRC) is a promising option in such settings because it combines human adaptability and judgment with robotic precision and repeatability [1], [2]. Still, broader use of HRC in smaller or resource-constrained manufacturing environments is often limited by safety concerns, coordination challenges, and the cost and complexity of implementation. This paper presents a practical digital twin framework for safe human-robot collaboration in resilient in-house manufacturing. The contribution of the paper is not a generic three-layer …

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Convergent Manufacturing Of Metal-Ceramic Architectures For High-Temperature Environments, Sk Shamim Hasan Abir, Joni C. Dhar, Sandipan Mishra, Daniel Lewis, Johnson Samuel Aug 2026

Convergent Manufacturing Of Metal-Ceramic Architectures For High-Temperature Environments, Sk Shamim Hasan Abir, Joni C. Dhar, Sandipan Mishra, Daniel Lewis, Johnson Samuel

MMRL-XMO Industrial Seminar

High-temperature thermal barrier systems require a graded architecture that transitions from a metallic substrate to a ceramic top coat to mitigate damage caused by mismatches in coefficients of thermal expansion (CTE). This study presents a convergent manufacturing strategy that integrates twisted wire gas tungsten arc (GTA) surfacing with cold sintering (CS), followed by CO₂ laser sintering, to fabricate a robust thermal barrier. High entropy alloy (HEA) bond coats with Al-Cr-Fe-Ni-based compositions were deposited onto Inconel 625 substrates using semi-automatically twisted commercial welding wires (Inconel 625, SS308Lsi, and Al ER4043) via GTA surfacing, resulting in HEA layers predominantly composed of >60 …

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