Manufacturing Commons^™

3d Semi-Analytical Thermo-Elasto-Plastic Model For Additive Manufacturing, Tao Liu, Ming C. Leu, Edward C. Kinzel, Chinedum Okwudire

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In additive manufacturing (AM), stress field drives distortion and warping and promotes delamination and cracking. Fast, accurate stress prediction is therefore essential for AM process planning and control, including real-time adaptive control, AM digital twins, data-driven and physics-driven workflows. However, spot-wise thermo-elasto-plastic finite element method (FEM) are often too slow for design iteration or real time use. Existing semi-analytical thermo-elasto-plastic approaches achieve high speed but are largely limited to 2D. In this paper, a full 3D semi-analytical thermo-elasto-plastic model for AM is built. The method uses a spot-wise analytical thermal field as the load and computes displacements and stresses via …

Magnetic Field-Induced Transformation In Polycrystalline Ni2mnal Heusler Type Magnetic Shape Memory Alloy, Choji J. Daches, Joseph W. Newkirk, Mario Buchely, Laura N. Bartlett

Materials Science and Engineering Faculty Research & Creative Works

The martensitic and magnetic transformations, as well as the mechanical properties, of Ni₂MnAl alloys in as-cast (AC) and heat-treated (HT) conditions were investigated. Magnetic-field-induced strain was evaluated via magnetostriction, with reversible strains of 0.14% and 0.2% achieved in the martensitic phase at 2 K for the AC and HT alloys, respectively. Transformation temperatures and Curie temperatures were determined under constant applied magnetic field, revealing that γ-phase inclusions in the AC microstructure suppress antiferromagnetic domain response, yielding a lower magnetization (∼8.4 emu g⁻¹) compared to the HT alloy (∼13.4 emu g⁻¹). Both alloys exhibited hysteretic behavior in the martensitic state and …

Using Machine-Learning-Based Process Map To Guide Evaluation Of Inconel 625 Mechanical Properties In Laser Foil Printing, Yu Hsiang Wang, Sung Heng Wu, Hung Chu Chiang, Pen Ning Yu, Chia Hung Hung, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Inconel 625 is widely studied in powder-based additive manufacturing, but its processing characteristics and mechanical performance in foil-feedstock laser foil printing (LFP) remain largely unexplored. In this study, a gradient boosting regression (GBR)-based process map was developed for LFP of Inconel 625 using 32 single-track experiments. The GBR model achieved R² values of 0.859 and 0.793 and mean absolute errors of 22.25 μm and 19.83 μm for melt-pool depth and width, respectively, outperforming second- and third-order polynomial regressions in capturing nonlinear melt-pool responses and distinguishing lack-of-fusion, conduction, and keyhole regimes. Three conduction-mode conditions with target depth-to-foil thickness ratios (D/T) …

A Federated Learning Framework For Data-Sovereign Predictive Maintenance In Distributed Smart Manufacturing, Md Sazol Ahmmed, Sriram Praneeth Isanaka, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Featured Application: The proposed federated learning framework can be applied in distributed smart manufacturing environments where multiple factories or production facilities collaboratively develop predictive maintenance models without sharing sensitive operational data. This approach is particularly useful for industrial networks involving geographically distributed plants, contract manufacturing partners, and multi-site production systems where data sovereignty and avoidance of raw data sharing are critical. Predictive maintenance enables early detection of machine failures and reduces unexpected production downtime. However, conventional approaches typically rely on centralized data collection and model training which introduce challenges related to data sovereignty, communication overhead and data ownership. To address …

Quantitative Phase-Field Modeling Of Nonequilibrium Microstructural Evolution In Rapid Solidification For Additive Manufacturing, Leiji Li, Fei Xiao, Ying Zhou, Xiaorong Cai, Chongfeng Zhang, Jinzhong Gao, Xiaopeng Shen, Tianchi Zhu, Sihan Wang, Yijia Gu, Xuejun Jin

Materials Science and Engineering Faculty Research & Creative Works

Fusion-based metal additive manufacturing (AM) relies on layer-by-layer deposition and rapid solidification, where the material transitions swiftly from liquid to solid. A key phenomenon during this process is solute trapping, a nonequilibrium effect governed by a velocity-dependent partition coefficient, which critically influences microstructure kinetics, morphology, and phase formation. In this study, we employ a recently proposed quantitative phase field (PF) model to systematically explore solute trapping, solute drag, and their impacts on pattern formation during rapid solidification at AM-relevant velocities, in both one and two dimensions. Our simulations reveal a growth mode transition from planar to cellular to dendritic, and …

Corrigendum To “3d Semi-Analytical Thermo-Elasto-Plastic Model For Additive Manufacturing”(Additive Manufacturing, (2026), 127, C, (105308), (S2214860426002344), 10.1016/J.Addma.2026.105308), Tao Liu, Ming C. Leu, Edward C. Kinzel, Chinedum Okwudire

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The author regret about the correction in the Equation B(1) in original article. The corrected version of the Equation B(1) is given below,(1.1)∂uxxx,ξ∂x=116πμ1−ν4ν−1x−ξxR3−3x−ξx3R5−8ν−5x−ξxR13+34ν−3x−ξx3R15−18x−ξxzξzR15+30x−ξx3zξzR17−12ν−12ν−1x−ξxR1R1+z+ξz2+4ν−12ν−1x−ξx3R13R1+z+ξz2+8ν−12ν−1x−ξx3R12R1+z+ξz3 The authors would like to apologise for any inconvenience caused. DOI of original article: < 10.1016/j.addma.2026.105308>

Thermal Transformations And Mechanical Properties Of All-D-Metal Mn2fecu Heusler-Type Shape Memory Alloy, Choji J. Daches, Joseph W. Newkirk, Mario Buchely

Materials Science and Engineering Faculty Research & Creative Works

All-d-metal Heusler alloys are emerging functional materials in which magnetic ordering, lattice distortion, and mechanical behavior are strongly coupled through d–d electronic interactions. This study systematically investigates the structural, thermal, magnetic, and mechanical properties of Mn₂FeCu synthesized within a Heusler-type compositional framework. SEM/EDS revealed a dual-phase FCC-based microstructure consisting of Mn–Fe–rich and Mn–Cu–rich domains, while XRD confirmed FCC symmetry with compositional partitioning rather than full L2₁ ordering. Differential scanning calorimetry identified partial melting of the Cu-rich phase near ~ 900 °C. Dilatometry showed a thermoelastic FCC → FCT transformation at ~ 770–780 °C with a recoverable strain of ~ 0.067%. …

The Effects Of Mold Flux Contamination On Oxide Scale Formation And Hydro-Descaling Efficiency During Steel Processing, Tochukwu Princewill Ojiako, Richard Osei, Mario Buchely, Haiming Wen, Simon Lekakh, Ronald O'Malley

Materials Science and Engineering Faculty Research & Creative Works

Oxide scale formation during thin-slab continuous casting has a complex structure, which is influenced by mold flux contamination, that modifies interfacial reactions during solidification, subsequent reheating, and descaling. While individual aspects of the oxidation behavior of carbon steel have been previously examined, the synergetic effects of mold flux contamination during continuous casting and subsequent reheating on scale modification and the efficiency of hydraulic descaling remain inadequately studied. This study quantitatively examines the effect of flux composition on oxide scale evolution, adhesion, and hydraulic removal in low-carbon steel under simulated industrial conditions. Slab samples with as-cast, cleaned, and flux-coated surfaces were …

Modeling Of Transformation Temperatures In Cast Martensitic Stainless Steels-Ca6nm: Effects Of Composition, Heating Rate, And Grain Size, Ugochukwu Agbedo, Mario Buchely, Laura Bartlett, Caelan Kennedy

Materials Science and Engineering Faculty Research & Creative Works

Accurate prediction of the critical transformation temperatures Ac1 and Ac3 is one of the essential factors in the heat treatment of CA6NM cast martensitic stainless steel. In this study, the influence of alloy composition, heating rate, and prior austenite grain size on the critical temperatures was quantified using dilatometric measurements and statistical modeling. Six heat treatment conditions produced prior austenite grain sizes ranging from ~75 to 247 µm. Experimental results showed that grain size variations produced only minor changes in Ac1 and Ac3, indicating a weak dependence of transformation temperatures on prior austenite grain size within the investigated range. In …

Multiphysics Simulation And Experimental Validation Of Phase Transformation And Hardness In Jominy End-Quenched Low-Alloy Steels, J. S. Alabi, E. Heidari, M. F. Buchely, K. Chandrashekhara, S. N. Lekakh, R. J. O'Malley, V. A. Athavale, A. Kumar

Materials Science and Engineering Faculty Research & Creative Works

High-volume industrial continuous hot-rolled steel heat treatment processes involve sophisticated multi-phase modeling. The performance of a given process can be optimized by coupling phase transformation kinetics with the cooling conditions of the process. This study develops a multiphysics model to simulate an intensive quenching process for steel, which is inherently transient and highly dependent on numerous parameters. The simulated object was a Jominy end-quenched specimen geometry using two commercial steels, AISI 4130 and AISI 4140, with the goal of transferring a verified methodology to the heat treatment process for industrial heavy-section products (bars, slabs). The simulation employs thermal, mechanical, and …

Critical Parameters Controlling Oxide Scale Formation And Hydro-Descaling Efficiency During Steelmaking, Tochukwu Princewill Ojiako

Doctoral Dissertations

In modern steelmaking, cast slabs are exposed to high-temperature oxidizing environments during secondary cooling, reheating, and hot rolling, resulting in the formation of multilayer oxide scales on the steel surface. These scales interact with mold-flux residues originating from the casting process (CC). The morphology, chemistry, and adhesion of oxide scale strongly influence its removability during high-pressure hydraulic descaling and ultimately determine the surface quality of hot-rolled products. However, the mechanistic relationship between oxide scale evolution, scale-steel interfacial structure, and hydraulic descaling performance remains poorly understood.

This dissertation investigates oxide scale formation, modification, and removal in low-carbon thin-slab steels produced by …

Design For Extrusion-Based Additive Manufacturing: Generation Of Guidelines For Ceramics With Comparison To Thermoplastics, Hollis Hervey Waites

Masters Theses

"Design for Additive Manufacturing (DfAM) has made much progress for polymer material extrusion processes (MEX-P), like Fused Deposition Modeling (FDM), but very little progress for ceramic MEX processes (MEX-C) like Direct Ink Writing (DIW). This thesis leverages MEX-P design guidelines to create an initial set of design guidelines for DIW. FDM and DIW processes and material properties are compared, and the effect of these factors on the differences in rules is discussed. Five design guidelines are identified as applying to all MEX. For three of these, an exact limit for DIW of alumina is studied: minimum corner radius in the …

Overcoming Resolution Vs. Throughput Trade-Offs In Ceramic Material Extrusion Additive Manufacturing Via Viscoelastic Filament Stretching, Abid H. Rafi, David W. Lipke, Jeremy L. Watts, Gregory E. Hilmas, Ming C. Leu

Materials Science and Engineering Faculty Research & Creative Works

Fabricating large, monolithic ceramic parts using material-extrusion additive manufacturing remains challenging due to difficulty maintaining uniform moisture content during printing, which can lead to drying-induced defects such as warping and cracking, especially as part size and print time increase. Fabricated parts have trade-offs among print resolution, high throughput, and structural fidelity. Our study has shown that increasing the ratio of nozzle traverse speed vs. material extrusion speed increases filament stretching in viscoelastic ceramic paste, helping to overcome the trade-offs between resolution and throughput. Using aqueous ZrB2–SiC (70/30 vol.%) as a representative ultra-high temperature ceramic paste, rheological characterisation revealed viscoelastic yield-stress …

Castrip Process Technology: Non-Grain Oriented (Ngo) Si Steels Extension And Carbide-Free Bainitic (Cfb) For Flat Products, Naram Naidu Meesala

Masters Theses

"This research explores the development of advanced steel grades manufactured through Castrip® twin-roll thin strip casting technology, with particular attention to non-grain-oriented electrical Si-Steels (NGOES) and carbide-free bainitic (CFB) steels. The Castrip® process offers a near-net-shape route for producing thin steel strips, which greatly decreases the number of processing stages, lowers energy demand, and reduces carbon dioxide emissions when compared with traditional steel production methods.

In the NGOES part of the study, several industrial Fe–Si steel compositions were cold rolled to final thicknesses ranging from 0.35 mm to 0.15 mm. These materials were then exposed to short-duration continuous annealing at …

Effect Of Complex Alloying Elements On Oxide Scale Formation And Water-Jet Descaling Performance On Continuously Cast Low-Carbon Steels, Tochukwu P. Ojiako, Tsvetkov Dmitry, Mario Buchely, Haiming Wen, Simon N. Lekakh, Ronald J. O'Malley

Materials Science and Engineering Faculty Research & Creative Works

The formation and evolution of oxide scale in contact with mold flux during continuous casting, subsequent reheating, and hydraulic descaling are strongly governed by steel chemistry. To elucidate the effect of complex alloying elements (Si, Mn, and Cr), two industrially produced continuously cast low-carbon steel grades for manufacturing stamped parts (a base and alloyed steel grade) were investigated. The objective was to determine how alloying elements influence oxidation behavior, scale morphology, interfacial adhesion, and water-jet descaling efficiency. Continuously cast slab specimens were subjected to controlled thermal and atmospheric oxidation cycles simulating multistage industrial practice. Three initial surface conditions (industrial as-cast, …

Bending Fatigue In Additively Manufactured Metals: A Review Of Current Research And Future Directions, Md Bahar Uddin, Sriram Praneeth Isanaka, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Metal additive manufacturing (MAM), also referred to as 3D printing, has proven remarkable in the fabrication of complex metal components in multiple sectors. However, the assessment of this revolutionary process through bending fatigue is frequently impeded due to concerns about mechanical and physical conditions of the printed components. The unique layer-by-layer production process results in varied microstructures, anisotropy, and intrinsic defects that considerably differ from traditionally manufactured wrought metals. This review article aims to integrate and evaluate historical and contemporary research on the bending fatigue of additively manufactured materials. More specifically, the impact of process parameters, build orientation, surface conditions, …

Fabrication Of Ultra High-Temperature Compact Heat Exchanger By Extrusion-Based Ceramic Additive Manufacturing, Abid Hasan Rafi, David W. Lipke, Jeremy Lee Watts, Greg Hilmas, Ming-Chuan Leu

Miners Solving for Tomorrow Research Conference

No abstract provided.

Additive Manufacturing Of Thermoplastic Composites, Matik Heskin, K. Chandrashekhara, Richard Billo, Ming-Chuan Leu, Thomas P. Schuman

Miners Solving for Tomorrow Research Conference

No abstract provided.

Image-Based Stage Prediction Of Pressure Injuries Using Deep Learning, Mehedi Tusar, Fateme Fayyazbakhsh, Ming-Chuan Leu

Miners Solving for Tomorrow Research Conference

No abstract provided.

Automated Tool Recognition And Retrieval, Tyler Rowden, Niloofar Zendedhel, Ming-Chuan Leu

Miners Solving for Tomorrow Research Conference

No abstract provided.

Impact Of Delayed Artificial Aging On Tensile Properties And Microstructural Evolution Of Directed Energy Deposited Scalmalloy®, Rachel Boillat-Newport, Sriram Praneeth Isanaka, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Scalmalloy® is a novel alloy designed to work with the unique processing inherent in additive manufacturing (AM). This alloy is post-processed using a single artificial aging treatment rather than a multistep heat treatment, as often noted in traditional manufacturing processes. Much of the literature details the impact of direct aging treatments around the temperature and time recommended by the manufacturer, 325 °C for 4 h; however, few studies have explored the impact of delayed artificial aging on the resulting mechanical and microstructural behavior. This study explored this missing link and determined the impact that the time between the fabrication of …

A Gaze-Driven Manufacturing Assembly Assistant System With Integrated Step Recognition, Repetition Analysis, And Real-Time Feedback, Haodong Chen, Niloofar Zendehdel, Ming C. Leu, Zhaozheng Yin

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Modern manufacturing faces significant challenges, including efficiency bottlenecks and high error rates in manual assembly operations. To address these challenges, we implement artificial intelligence (AI) and propose a gaze-driven assembly assistant system that leverages artificial intelligence for human-centered smart manufacturing. Our system processes video inputs of assembly activities using a Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network for assembly step recognition, a Transformer network for repetitive action counting, and a gaze tracker for eye gaze estimation. The application of AI integrates the outputs of these tasks to deliver real-time visual assistance through a software interface that displays …

Intelligent Turning Cyber-Physical Systems Modeling Using Sysml, Prithbey Raj Dey, David Lee Enke, Mario F. Buchely

Engineering Management and Systems Engineering Faculty Research & Creative Works

Cyber-Physical Systems (CPS) support industrial automation that incorporates people, hardware, signal, computation, and control using networking to achieve desired results. The complex automated CPS design demands a standard and comprehensive approach to appropriately identify the system requirements, define the architecture, and model the relationships among the software and hardware components. Systems Modeling Language (SysML) provides the capability for a comprehensive modeling to capture the desired design requirements in the systems architecture. SysML enables performance estimation of the model by analyzing constraints while identifying interactions among the components through various behavioral diagrams. In this paper, SysML is applied to the design …

Experiment-Based Superposition Thermal Modeling Of Laser Powder Bed Fusion, Cody S. Lough, Tao Liu, Robert G. Landers, Douglas A. Bristow, James A. Drallmeier, Ben Brown, Edward C. Kinzel

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Parts experience significant local thermal variations during the Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) process, providing a potential source of defects. Near real-time thermal predictions can enable better process planning and facilitate corrections on subsequent layers to enable the engineering of laser parameter and scan path combinations that avoid defect inducing scenarios. This paper considers an experiment-based Discrete Green's Function (DGF) thermal model for temperature field prediction in LPBF. An analytical framework is developed and used to calculate an experimental DGF (i.e., powder bed's single pulse temperature response) from spatiotemporal Short-Wave Infrared (SWIR) camera data. The extracted …

Predicting The High Temperature Deformation Behavior Of Haynes282 By A Dislocation-Density Based Crystal Plasticity Model, Tianju Chen, Huadong Fu, Shujing Dong, Yue Zhou, Yijia Gu, Caizhi Zhou, Ridwan Sakidja

Materials Science and Engineering Faculty Research & Creative Works

Mechanical behavior of Haynes282 is heavily dependent upon the microstructure state, calling for mesoscale model to study the relationship between the underlying microstructure and macroscopic performance. In this work, we employ crystal plasticity finite element method (CPFEM) to explore the deformation mechanisms of Hanyes282 subjected to tensile (short-term) and creep (long-term) tests. Haynes282 is a newly developed Ni-based superalloy, containing relatively low volume fraction (≤20%) of spherical γ′ precipitate phase. A dislocation-density based model is developed to describe the tensile and the creep behavior, where a dimension reduction algorithm is proposed to obtain more accurate inter-particle spacing. Furthermore, dislocation-particle interaction …

A Comprehensive Study Of Cooling Rate Effects On Diffusion, Microstructural Evolution, And Characterization Of Aluminum Alloys, Atiqur Rahman, Sriram Praneeth Isanaka, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Cooling Rate (CR) definitively influences the microstructure of metallic parts manufactured through various processes. Factors including cooling medium, surface area, thermal conductivity, and temperature control can influence both predicted and unforeseen impacts that then influence the results of mechanical properties. This comprehensive study explores the impact of CRs in diffusion, microstructural development, and the characterization of aluminum alloys and the influence of various manufacturing processes and post-process treatments, and it studies analytical models that can predict their effects. It examines a broad range of CRs encountered in diverse manufacturing methods, such as laser powder bed fusion (LPBF), directed energy deposition …

Ai-Powered Image-Based Assessment Of Pressure Injuries Using You Only Look Once (Yolo) Version 8 Models, Mehedi Hasan Tusar, Fateme Fayyazbakhsh, Niloofar Zendehdel, Eduard Mochalin, Igor Melnychuk, Lisa Gould, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Objective: The primary objective of this study is to enhance the detection and staging of pressure injuries using machine learning capabilities for precise image analysis. This study explores the application of the You Only Look Once version 8 (YOLOv8) deep learning model for pressure injury staging. Approach: We prepared a high-quality, publicly available dataset to evaluate different variants of YOLOv8 (YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and YOLOv8x) and five optimizers (Adam, AdamW, NAdam, RAdam, and stochastic gradient descent) to determine the most effective configuration. We followed a simulation-based research approach, which is an extension of the Consolidated Standards of Reporting Trials …

Hands-Free Uav Control: Real-Time Eye Movement Detection Using Eog And Lstm Networks, Niloofar Zendehdel, Khosro Ghorbani Zadeh, Haodong Chen, Yun Seong Song, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Industry 4.0 has created a growing need for effective human-robot collaboration (HRC). As robots and humans work more closely together, efficient communication becomes essential for coordinating their actions seamlessly. While speech may seem like the obvious choice for communication, noisy factory environments can render it impractical. Additionally, workers often have their hands occupied with assembly tasks, making hand-controlled interfaces less practical for controlling robots. To address these challenges, this paper presents a novel, hands-free method for robot control using electrooculography (EOG) signals–specifically, eye movements and blinks–with unmanned aerial vehicles (UAVs) used as the demonstration platform. We developed a real-time system …

Designing Robust Quasi-2d Perovskites Thin Films For Stable Light-Emitting Applications, Sharmistha Khan, Reshna Shrestha, Mengru Jin, Doyun Kim, Guan Lin Chen, Ruipeng Li, Yijia Gu, Qing Tu, Namyoung Ahn, Wanyi Nie

Materials Science and Engineering Faculty Research & Creative Works

Quasi-2D perovskite made with organic spacers co-crystallized with inorganic cesium lead bromide inorganics is demonstrated for near unity photoluminescence quantum yield at room temperature. However, light emitting diodes made with quasi-2D perovskites rapidly degrade which remains a major bottleneck in this field. In this work, It is shown that the bright emission originates from finely tuned multi-component 2D nano-crystalline phases that are thermodynamically unstable. The bright emission is extremely sensitive to external stimuli and the emission quickly dims away upon heating. After a detailed analysis of their optical and morphological properties, the degradation is attributed to 2D phase redistribution associated …

Controlling Nitrogen Pickup During Induction Melting Of Ultrahigh-Strength Cr-Ni-Mo-V Steels, Kingsley T. Amatanweze, Viraj A. Athavale, Mario F. Buchely, Laura N. Bartlett, Ronald J. O'Malley, Daniel M. Field

Materials Science and Engineering Faculty Research & Creative Works

Nitrogen pickup during air induction melting can result in porosity and a loss of fracture toughness in ultrahigh-strength quenched and tempered steel castings. Nitrogen atoms are easily adsorbed into liquid steel upon exposure to the air, and argon shrouding alone has limited effectiveness. Previous studies have shown that proper charge sequencing and maintaining a high amount of dissolved oxygen in the melt prior to tapping and deoxidation can limit nitrogen pickup in the melt. In the current study, the effect of melt practice and charging procedure on nitrogen pickup was studied as a function of hold time in a series …