Manufacturing Commons^™

Thermal Monitoring Of Solidification In Molded Casting Of Drone Landing Leg, Sadettin Cem Altıparmak, Maher Zayed, Samuel Hawk, Mohamed Baddi, Jesus Degollado, Ahmed Bendaouia, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications

This paper presents the design, fabrication, and thermal characterization of an acrylonitrile butadiene styrene (ABS) mold produced by fused deposition modeling (FDM) extrusion-based additive manufacturing used for the wax casting of a drone landing leg. A thermal monitoring framework, consisting of four K-type thermocouples logged at 1 s intervals, was deployed across six casting trials to capture the complete solidification cycle, yielding 84,717 time-stamped measurements. The study focuses on thermal data analysis and materials science interpretation through descriptive statistics, normality diagnostics, inter-trial Kruskal–Wallis tests, phase-duration analysis, rolling-variance monitoring, and inter-channel Pearson correlation. Key findings include a persistent spatial temperature hierarchy …

A Novel Hexagonal-Zigzag Cellular Infill Structure For Additive Manufacturing, Md. Saidur R Roney, Amm Nazmul Ahsan, Prosenjit Barua

Manufacturing & Industrial Engineering Faculty Publications

The rigidity of the Additively Manufactured objects can be tailored by manipulating the infill lattice type and density. In this research, an island type novel infill structure termed as Hexagonal-Zigzag pattern is introduced, and its mechanical performance is investigated. In this pattern, the zigzag raster reflects the repeating hexagonal shaped cell constituting the parallel-oriented islands and 90° rotation of the pattern in each layer distributes the island span along both transverse and longitudinal directions of the printing contour. A mathematical model is established to illustrate the effect of the infill parameters on hexagon unit cell size and relative infill density. …

Investigation Of Process Parameters To Fabricate Tiwmo Refractory Medium Entropy Alloy Via Laser Powder Bed Fusion, Abdullah Al Masum Jabir, Lindsey A. Salazar, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications

This paper presents an experimental study on the fabrication of a TiWMo refractory medium-entropy alloy (RMEA) using laser powder bed fusion (PBF-LB/M, commonly known as selective laser melting) from elemental powders as well as successful alloy formation on titanium substrates. The effects of tungsten particle size and process parameters on successful TiWMo RMEA fabrication have been explored using scanning electron microscopy (SEM), x-ray diffraction, hardness measurement and microstructural analysis. Scanning electron microscope (SEM) analysis revealed that the lowest percentage (0.01%) of unmelted tungsten particles was observed at a laser power of 350 W and scanning speed of 250 mm/s, particularly …

Data Driven Estimation Of Pore Size Using 1d Light Emissions For Laser Powder Bed Fusion Additive Manufacturing, Jose Galarza, Jorge Barron, Luis Jimenez, Tamer Oraby, Jianzhi Li, Farid Ahmed

Manufacturing & Industrial Engineering Faculty Publications

The quality assurance of the Laser Powder Bed Fusion Process (LPBF) has been extensively investigated over the last decade for in-situ monitoring of metal additive manufacturing. The process inherently generates voids within the bulk of the part, which can detrimentally affect the quality of the printed part. The characterization of these voids by estimating their size and identifying their geometrical features remains a challenge. This study introduces a Machine Learning (ML) based framework for estimating void sizes of varying geometries using layer-wise one-dimensional (1D) average light intensity signal obtained from the optical tomography system during the 3D printing of metallic …

Layer-Wise Printing Parameter Optimization For Laser Powder Bed Fusion, Chaoran Dou, Rongxuan Wang, Raghav Gnanasambandam, Jianzhi Li, Zhenyu James Kong

Manufacturing & Industrial Engineering Faculty Publications

Additive manufacturing (AM) is a transformative technology that enables the fabrication of complex geometries layer by layer. However, metal parts produced via AM processes such as laser powder bed fusion (LPBF) are prone to various defects, including porosity and deformation. These defects often result from suboptimal printing parameter settings. Traditional approaches typically aim to reduce defects by optimizing a fixed set of parameters for the entire part. However, such methods do not account for layer-wise variations in printing conditions caused by changes in geometry, heat transfer, and re-heating effects. While optimizing parameters for each layer could improve part quality, it …

Reinforcement Learning For Imbalanced Data In Robotic Anomaly Detection Within Autonomous Manufacturing, Salma Messaoudi, Ahmed Bendaouia, El Hassan Abdelwahed, Mohammed Ameksa, Hajar Mousannif, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications

Ensuring reliable anomaly detection in industrial robots is critical for safe and autonomous manufacturing operations. However, it remains challenging due to temporal dependencies and class imbalance in sensor data. This study presents a reinforcement learning approach using Deep Q-Network (DQN) enhanced with Long Short-Term Memory (LSTM) and Gradient Boosting Machine (GBM) for robust anomaly detection in robotic systems. The proposed framework integrates an LSTM into the DQN policy to capture temporal patterns. It also introduces a novel GBM-based reward mechanism that mitigates class imbalance by applying SMOTE (Synthetic Minority Over-sampling Technique) after removing temporal dependencies. Experimental results demonstrate that this …

Thermal Management And Lubrication Characteristics Of Tungsten Disulfide (Ws2) Vegetable-Based Nanolubricants, Jaime Taha-Tijerina, Dyana De Leon-Elizondo, Jade Mendieta, Leonardo Taha-Soto

Informatics and Engineering Systems Faculty Publications

Recent innovations with the aid of nanotechnology are more frequently seen in the industrial sectors. Lubricants are a high-end commodity resource used in many manufacturing processes; unfortunately, most of these lubricants are petroleum-based, which come with certain drawbacks, such as environmental aspects, handling issues and high costs. With the incorporation of nanostructures within fluids and lubricants, novel material alternatives are replacing conventional lubrication systems, maintaining the required thermophysical and tribological characteristics. This research provides an analysis of vegetable lubricant, castor oil (CO), and the effects of the incorporation of WS2 nanofiller at diverse filler fractions. A TEMPOS thermal analyzer device …

Enhancement Of Plastic Deformation In Ultrasound-Assisted Cold Spray Of Tungsten: A Molecular Dynamics Study, Md Tusher Ahmed, Farid Ahmed, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications

Tungsten (W) is widely valued for its exceptional thermal stability, mechanical strength, and corrosion resistance, making it an ideal candidate for high-performance military and aerospace applications. However, its high melting point and limited room-temperature plasticity pose significant challenges for processing W using additive manufacturing (AM). Cold spray (CS), a solid-state AM process that relies on high-velocity particle impact and plastic deformation, offers a promising route for additive manufacturing of W, yet conventional CS fails to induce sufficient plastic deformation for effective bonding. In this study, we employ atomistic simulations to investigate the effect of ultrasonic perturbation in …

Artificial Intelligence And Additive Manufacturing As A Coupled Design System: Rethinking Inference, Manufacturability, And Design Education, Charul Chadha, Garth Crosby, Sabit Ekin, Mohamed Gharib, Eman Hammad, Congrui Jin, Ali Ahmad Malik, Noemi Mendoza Diaz, Calahan Mollan, Monsuru Ramoni

Manufacturing & Industrial Engineering Faculty Publications

Artificial intelligence (AI) is becoming deeply integrated into additive manufacturing (AM) workflows, reshaping how designers approach geometry, materials, and process constraints. AI holds significant potential by accelerating design exploration, revealing complex patterns in AM behavior, and supporting earlier assessment of manufacturability. At the same time, it introduces new risks related to model transparency, data quality, physical validity, and the potential for overreliance by students and practitioners. This perspective examines these issues through four guiding questions that address the role of AI in AM-enabled design, the gaps that limit or enable AI contribution, the implications for engineering education, and the responsibilities …

Reinforced Scan: A Reinforcement Learning Enabled Optimal Laser Scan Path Planning In Laser Powder Bed Fusion Additive Manufacturing, Chaoran Dou, Jihoon Chung, Raghav Gnanasambandam, Yuhao Wu, Jianzhi Li, Zhenyu James Kong

Manufacturing & Industrial Engineering Faculty Publications

Additive Manufacturing is an innovative technology that fabricates parts layer by layer. However, in Laser Powder Bed Fusion (LPBF), printed metal parts often exhibit residual stresses, deformations, and other defects due to non-uniform temperature distribution during the printing process. To mitigate these issues, an optimized scan sequence within each layer can improve thermal uniformity. Traditional optimization methods, which rely on domain knowledge and employ trial-and-error or heuristic approaches, often fail to achieve optimal solutions due to the complex nature of the problem. One major challenge in improving scan strategies lies in the vast search space required to optimize the scan …

Direct Ink Writing Of Shear Exfoliated Two-Dimensional Nanomaterial- Elastomeric Multifunctional Nanocomposite, Md Abdur Rahman Bin Abdus Salam, Asif Hasan Ridoy, A K M Abirul Haque, Muhammad Shahbaz Rafique, Md Arafat Hossain, Md Shahriar Forhad, Matthew G. Boebinger, Farid Ahmed, Karen Lozano, Ali Ashraf

Manufacturing & Industrial Engineering Faculty Publications

Direct ink writing (DIW) of polymer nanocomposites with high loadings of two-dimensional (2D) nanofillers (graphene and hexagonal boron nitride (hBN)) is challenging because of potential clogging, use of hazardous solvents, and agglomeration. Here, in this work, a shear exfoliation and sieving method to prepare DIW ink with high loading of nanofillers produced from low-cost bulk layered materials such as graphite and bulk hBN powder for successful DIW printing without the use of any solvents, binders, or plasticizers. The single-step exfoliation technique resulted in a composite with substantial layer reduction along the c-axis, as confirmed by SEM, TEM, XRD, and Raman …

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 …

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 …

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 …

  ---

  Go to article

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 …

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 …

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 …

Advanced Porosity Control Of Cp780 Galvanized Steel During Gas Metal Arc Welding With Pulsed Arc, Carlos Adrián García Ochoa, Jorge Alejandro Verduzco Martínez, Francisco Fernando Curiel-López, Víctor Hugo López-Morelos, Jaime Taha-Tijerina, Ariosto Medina Flores, Maleni García Gómez

Informatics and Engineering Systems Faculty Publications

This study investigated the control of porosity during gas metal arc welding with pulsed arc (GMAW-P) of complex-phase 780 (CP780) galvanized steel. Due to the Zn coating on this type of steel, porosity forms during welding as a result of Zn vaporization. The objective was to optimize the welding parameters to minimize porosity with a design of experiments using an L9 orthogonal array to analyze the effects of peak current (Ip), pulse time (tp), and pulse frequency (f) in high-speed welding conditions. The results showed that porosity was significantly reduced with a peak current of 313 A, a frequency of …

Additive Manufacturing Applications In Mission-Critical Operations: A Review, Arup Dey, Olusanmi Adeniran, Monsuru Ramoni

Manufacturing & Industrial Engineering Faculty Publications

Additive manufacturing (AM) is used to fabricate complex components from a wide variety of materials in an additive manner. AM brings several benefits, such as reduced lead times, on-demand production, creation of complex customized designs without tooling requirements, and remote design sharing. However, the use of AM for critical components is limited in large missions due to quality and reliability concerns, as is the case with many manufacturing technologies. Enhancing the acceptance of AM-built parts for mission-critical components can be achieved by producing highly reliable parts, establishing robust quality standards, and continually improving part properties. This review article comprehensively explores …

Significance Of Multi-Level Fusion In Multi-Component Fault Diagnosis Under Speed Varying Condition In Rotational Machinery, S. Sowmya, M. Saimurugan, Immanuel A. Edinbarough

Informatics and Engineering Systems Faculty Publications

Most well-known challenging effects of identifying multiple defects in a rotational machine when speed is varied, are illustriously inspected by many researchers. However, different fusion logics are evolved in the series of research attempt, but not paid much attention in interrogating it for unsteady speed signals.Addressing this literature void, this paper focusses on multi-level fusion strategy with the help of sensor-centric feature integration and Dempster Shafer’s (D-S) theory of evidence for uncovering multi-faults in bearings, shafts and gears of rotational machines under speed variational condition. Primarily, instantaneous frequency and envelope from the acquired vibration and sound signals of complex system …

Potential Effects Of Statistical Complexity Measure In Improving The Fault Diagnosis Performance Under Speed Fluctuations, S. Sowmya, M. Saimurugan, N. Kannan, Immanuel A. Edinbarough

Informatics and Engineering Systems Faculty Publications

Many research studies are performed in extracting non-stationary signal properties such as instantaneous frequency (IF) and envelope to diagnose machinery faults under time-varying speed conditions. But accurate IF extraction is difficult from such complex fluctuating signals to identify the faults efficiently. Therefore, this paper proposes the Statistical Complexity Measure (SCM) as a feature that evaluates the randomness and complexity without any additional requirement, providing an outstanding result in multi-component fault detection under speed fluctuations. Primarily, the influence of SCM is proved by ranking the features with the help of the Random Forest (RF) algorithm. The fault classification of individual signal …

Flow And Heat Transfer Experimental Study For 3d-Printed Solar Receiving Tubes With Helical Fins At Internal Surface, Fouad Haddad, Naznin Nuria Afrin, Jianzhi Li, Peiwen Li, Bharath Pidaparthi, Samy Missoum, Ben Xu

Manufacturing & Industrial Engineering Faculty Publications

3D-printing technology was applied to fabricate novel solar thermal collection tubes that have internal heat transfer enhancement fins and external surfaces with high solar absorptivity and low emissivity due to the ability to use different materials in one tube. Helical fins were selected to introduce circumferential flow and thus minimize the circumferential temperature difference of the tube that receives sunlight on one side. The structures of the helical fins were previously optimized from computational fluid dynamics (CFD) analysis with the objective of low entropy production rate by looking for high heat transfer coefficient and relatively lower pressure loss. High-temperature alloy, …

Molecular Dynamics-Based Two-Dimensional Simulation Of Powder Bed Additive Manufacturing Process For Unimodal And Bimodal Systems, Yeasir Mohammad Akib, Ehsan Marzbanrad, Farid Ahmed

Manufacturing & Industrial Engineering Faculty Publications

The trend of adapting powder bed fusion (PBF) for product manufacturing continues to grow as this process is highly capable of producing functional 3D components with micro-scale precision. The powder bed’s properties (e.g., powder packing, material properties, flowability, etc.) and thermal energy deposition heavily influence the build quality in the PBF process. The packing density in the powder bed dictates the bulk powder behavior and in-process performance and, therefore, significantly impacts the mechanical and physical properties of the printed components. Numerical modeling of the powder bed process helps to understand the powder spreading process and predict experimental outcomes. A two-dimensional …

Data-Driven Roughness Estimation Of Additively Manufactured Samples Using Build Angles, Jose Galarza, Jose Barron Jr., Farid Ahmed, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications

Achieving control of Laser Powder Bed Fusion (L-PBF) over the quality of the print is the main motivation for finding an optimum set of parameters in the process. Surface roughness is one of the characteristics of the print that impacts the performance of the desired functionality. This research focus is to relate the build angle with the surface roughness on the L-PBF printed specimens and utilize machine learning methods for roughness estimation of geometric features with varying build angles. The EOS M290 L-PBF printer was used to print Inconel-718 coupons using standard process parameters while varying build angles from 20 …

Prediction Of Tool Wear And Surface Finish Using Anfis Modelling During Turning Of Carbon Fiber Reinforced Plastic (Cfrp) Composites, Anil K. Srivastava, Md. Mofakkirul Islam

Manufacturing & Industrial Engineering Faculty Publications

Carbon fiber-reinforced plastics (CFRP) are widely used in various industries due to their high strength to weight ratio, corrosion resistance, durability, and excellent thermo-mechanical properties. The machining of CFRP composites has always been a challenge for the manufacturers. In this study, CNC turning operation with coated carbide tool is used to machine a specific CFRP and the relationship between the cutting parameters (Speed, Feed, Depth of Cut) and response parameters (Vibration, Surface Finish, Cutting Force and Tool Wear) are investigated. An adaptive-network-based fuzzy inference system (ANFIS) model with two multi-input–single-output (MISO) system has been developed to predict the tool wear …

Enhancing Resilience In Complex Energy Systems Through Real-Time Anomaly Detection: A Systematic Literature Review, Ali Aghazadeh Ardebili, Oussama Hasidi, Ahmed Bendaouia, Adem Khalil, Sabri Khalil, Dalila Luceri, El Hassan Abdelwahed, Sara Qassimi, Antonio Ficarella

Manufacturing & Industrial Engineering Faculty Publications

As real-time data sources expand, the need for detecting anomalies in streaming data becomes increasingly critical for cutting edge data-driven applications. Real-time anomaly detection faces various challenges, requiring automated systems that adapt continuously to evolving data patterns due to the impracticality of human intervention. This study focuses on energy systems (ES), critical infrastructures vulnerable to disruptions from natural disasters, cyber attacks, equipment failures, or human errors, leading to power outages, financial losses, and risks to other sectors. Early anomaly detection ensures energy supply continuity, minimizing disruption impacts, an enhancing system resilience against cyber threats. A systematic literature review (SLR) is …

Gaze Tracking Embedded Collaborative Robots For Automated Metrology And Reverse Engineering, Sachithra H. Karunathilake, Md Shahriar Forhad, Zhaohui Geng

Manufacturing & Industrial Engineering Faculty Publications

Conventional geometric metrology, or three-dimensional (3D) scanning, and reverse engineering heavily rely on the experience of the operators. With an increasing need for automation, robot arms have been adopted for this task. However, due to the large variety of parts and designs, automated path planning could provide a scanning solution that may overlook the critical area, which could potentially deteriorate the scan results. This article explores the integration of collaborative robotics (cobots) with eye-tracking technology to improve the autonomous 3D scanning process. The primary objective of this study is to enhance the accuracy and efficiency of cobots in 3D scanning, …

A Survey On Fused Filament Fabrication To Produce Functionally Gradient Materials, Arup Dey, Monsuru Ramoni, Nita Yodo

Manufacturing & Industrial Engineering Faculty Publications

Fused filament fabrication (FFF) is a key extrusion-based additive manufacturing (AM) process for fabricating components from polymers and their composites. Functionally gradient materials (FGMs) exhibit spatially varying properties by modulating chemical compositions, microstructures, and design attributes, offering enhanced performance over homogeneous materials and conventional composites. These materials are pivotal in aerospace, automotive, and medical applications, where the optimization of weight, cost, and functional properties is critical. Conventional FGM manufacturing techniques are hindered by complexity, high costs, and limited precision. AM, particularly FFF, presents a promising alternative for FGM production, though its application is predominantly confined to research settings. This paper …

Spectral Behavior Of Fiber Bragg Gratings During Embedding In 3d-Printed Metal Tensile Coupons And Cyclic Loading, Farid Ahmed, Md Shahriar Forhad, Mahmudul Hasan Porag

Manufacturing & Industrial Engineering Faculty Publications

Additive manufacturing (AM) enables the spatially configurable 3D integration of sensors in metal components to realize smart materials and structures. Outstanding sensing capabilities and size compatibility have made fiber optic sensors excellent candidates for integration in AM components. In this study, fiber Bragg grating (FBG) sensors were embedded in Inconel 718 tensile coupons printed using laser powder bed fusion AM. On-axis (fiber runs through the coupon’s center of axis) and off-axis (fiber is at 5° and 10° to the coupon’s center of axis) sensors were buried in epoxy resin inside narrow channels that run through the coupons. FBGs’ spectral evolutions …