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 …

Sla Elastic Resin Curing Test Data, Richard Amesimenu, Johnson Nwogu, Haijun Gong

Datasets

3D printing via stereolithography (SLA) enables high-resolution polymer components, but as-printed parts may exhibit incomplete polymerization and reduced mechanical performance. This study investigates the effects of UV post-curing time on SLA-printed elastic photopolymer resin. Specimens were evaluated using Differential Scanning Calorimetry (DSC), uniaxial tensile testing (ASTM D412 Type C), and Durometer Type M hardness testing. Results show that increased post-curing enhances crosslink density, tensile strength, elastic modulus, and hardness, while extended curing may reduce ductility. An optimal post-curing window balancing stiffness and flexibility was identified. Testing datasets include DSC (dsc/), tensile testing (tensile/), and hardness testing (hardness/) results for uncured …

0905: American Car And Foundry (Acf) Collection, 1916-2019, Marshall University Special Collections

Guides to Manuscript Collections

The collection includes only documents that were found in the plant in 2021. These primarily consist of files on capital projects from the 1970s through the 1990s. Also included are notebooks with job descriptions and classifications; ledger books containing maintenance purchase orders; quality assurance manuals; visitors register books from 1973-2019; drawings of plant machinery and operations; slides and photographs; and miscellaneous materials.

The forerunner to ACF was Ensign Manufacturing Company, founded in 1871 at Huntington, West Virginia, by William H. Barnum and Ely Ensign, both from prominent families of Lime Rock, Connecticut. It was chartered (incorporated) on November 1, 1872, …

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 …

Production Of Seismic-Resistant Steel From Scrap With Up To 0.6% Copper, Iman El-Mahallawi, Ahmed Ramadan Seada Dr.

Mechanical Engineering

Earthquake-resistant steel grades of characteristic value defined by the ratio (UTS/YS) greater than 1.25 are verified through controlling the proportion of alloying elements in steel. This work illustrates a novel idea to produce earthquake-resistant steel grade utilizing steel scrap. Different heats were produced containing varying levels of copper, manganese, and silicon, along with deep desulfurization. The heats were hot rolled to diameters of 10, and 16 mm, followed by Tempcore process. JMatPro software was used to predict the formed phases. The chemical composition was determined by optical emission spectrometry. The tensile properties were determined by tensile testing, and bend testing …

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 …

On The Application Of Machine Learning Techniques For Quality Assurance In An Automobile Paint Shop, Anis Fatima, Shakeel Ahmed, Muhammad Akif Shan

Michigan Tech Publications

The automotive industry depends on high-quality paint coatings for both aesthetic appeal and functional performance. However, surface imperfections such as scratches, paint runs, and orange peel can arise from process and environmental variations. This study employs machine learning (ML) and exploratory data analysis (EDA) to identify key factors that influence surface defect formation in automotive painting. Using historical production data from Lucky Motor Corporation Limited, models based on linear regression, support vector machines (SVM), and random forests were developed and validated under various process conditions. The best-performing model achieved an R² of 0.94, with a mean absolute error (MAE) of …

Effects Of Niobium On The Mechanical And Oxidation Properties Of Additively Manufactured Tungsten, Alexander Lesieur, Cayla Eckley, Ryan A. Kemnitz

Faculty Publications

Although additive manufacturing presents a novel and customizable approach to fabricating tungsten (W) alloys, the layer-by-layer production technique presents a unique set of processing challenges which are further exacerbated by the metal’s refractory properties. In this study, additions of niobium (Nb) were found to improve the mechanical properties and oxidation resistance of additively manufactured W. Microstructural investigation revealed the effect of Nb on the cracking, grain size, and texture in the as-built material. Mechanical compression testing showed significant improvement in ductility with increasing Nb content. The low concentrations of Nb used did not induce large changes in the yield strength …

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 …

Construction Of A Deffi Sprayer: Using 3d Printer Methodology And Techniques For Cost-Effective Analysis Using Desi Mass Spectrometry Imaging, Ryan Karst, Savvy Stevens, Luke Amos, Logan Koester, Ethan Newbold, Karson Whitaker

Symposium Projects

Using 3D Printer Methodology and Techniques for Cost-Effective Analysis using DESI Mass Spectrometry Imaging

Optimizing Warranty Policies For Remanufactured Products: When Should They Be Longer, Shorter, Or Identical To New Product Warranties?, Kunpeng Li, Jun-Yeon Lee

Faculty Publications

Manufacturers adopt different warranty strategies for remanufactured products, offering shorter, identical, or longer warranty periods compared to new products. However, prior research has only focused on manufacturers offering either shorter or identical warranties. In addition, the existing literature has not captured the diminishing returns of warranties, i.e., as the warranty coverage increases, its incremental benefits begin to decrease but the costs continue to increase. To address these gaps, we develop an optimization model that jointly considers pricing and warranty decisions while accounting for warranty’s diminishing effect on consumer’s willingness to pay for remanufactured products. We show that all three observed …

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 …

An Autonomous Robotic System For Object Retrieval And Delivery: Enhancing Independence For Users Living With Disability And Older Adults, Jincheng Li, Chenghao Lin, Amna Mazen, Youssef A. Bazzi

Michigan Tech Publications

As the global population ages, there is a growing need for assistive technologies to help older adults maintain their independence. This work presents a cost-effective autonomous socially assistive robot designed for object retrieval and delivery, enhancing accessibility in home environments. The system is built on the Robot Operating System (ROS) framework and integrates three key components: the Pioneer P3-DX mobile robot for autonomous navigation, the ReactorX-200 robotic arm for pick-and-place operations, and the Kinect v2 RGB-D camera for object detection and localization. Users interact with the robot through natural language processing by issuing voice commands to retrieve various objects. Microsoft …

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 …

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%. …

A Full Polymer Piezoelectric Flextensional Energy Harvester, Nadia Ahbab, Sidra Naz, Bingqi Zhao, Tian-Bing Xu

Mechanical & Aerospace Engineering Faculty Publications

This study presents a full polymer piezoelectric flextensional energy harvester (FPPFEH) comprising a single-layer poly(vinylidene fluoride) (PVDF) film bonded to a 3D-printed polylactic acid (PLA) flextensional frame. For an arm inclination angle of θ=10°, the free-body model gives a theoretical geometric force-amplification factor of M_F=cot θ ≈ 5.67; this value represents an ideal upper bound and was not independently validated by local force or strain measurements. During assembly, the film was tensioned only to remove visible slack and maintain a flat configuration. No intentional pretension was applied, and any residual tension was not measured. Off-resonance force-controlled tests showed …

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 …

The Efficacy Of Hybrid Manufacturing For High Stress Automotive Parts, Logan Trimmer

Harrisburg University Other Works

Presentation covering the broad strokes of the project. The goal was to prove the viability of hybrid/additive manufacturing for high stress automotive applications. This project focused on recreating a piston from an old engine to examine if hybrid manufacturing could be used for such applications. On a small scale, hybrid manufacturing was able to be more cost effective if the costs of the equipment and electricity were ignored. The decision to ignore those costs came from the inability to find accurate prices for industrial casting.

The Efficacy Of Hybrid Manufacturing For High Stress Automotive Components, Logan Trimmer

Harrisburg University Other Works

The goal of this research was to establish the viability of using hybrid manufacturing for automotive applications. By verifying that high-stress components can be created, it can be assumed that any other lower stress part could be made to match the strength requirements. A limiting factor of adoption for hybrid manufacturing is how new the technology is. Studies on time and cost were performed allowing for comparisons with traditional manufacturing technologies (casting, forging, milling) used in automotive applications. This research utilized a Haas Automation UMC750 5-axis CNC mill with a Meltio laser wire direct energy deposition attachment. Fusion 360 was …