bluuebunny/crossref_metadata_2025 huggingface dataset:
Data Requirements for Digital Twins in Additive Manufacturing
Authors: Feng Shaw C. , Jones Albert T. , Shao Guodong
Published: September 2023

The number and types of sensors used to monitor additive manufacturing (AM) processes and parts in real time are growing. The emerging digital twins (DTs) associated with the data collected by those sensors and the functions that use that data as inputs are becoming increasingly important research topics. There are fast growing demands across several industry sectors to develop software tools that can create, fuse, and measure both AM DTs and digital threads across the entire AM part lifecycle. While some tools are available, they are not well correlated to part-qualification functions in that lifecycle. The accuracy of the DT tools, the fidelity of their inputs, and the ability to create digital threads are still open research questions. The goal of this paper is to identify the data requirements and technical barriers that are limiting the ability to qualify real AM parts using DTs and digital threads. The data requirements can be used as a guide for AM users to create both. This paper uses laser-based powder bed fusion AM for metals as a case study to help identify those requirements and create those digital twins and threads.
Normalizing Flows for Intelligent Manufacturing
Authors: Russell Matthew , Wang Peng
Published: September 2023

Monitoring machine health and product quality enables predictive maintenance that optimizes repairs to minimize factory downtime. Data-driven intelligent manufacturing often relies on probabilistic techniques with intractable distributions. For example, generative models of data distributions can balance fault classes with synthetic data, and sampling the posterior distribution of hidden model parameters enables prognosis of degradation trends. Normalizing flows can address these problems while avoiding the training instability or long inference times of other generative Deep Learning (DL) models like Generative Adversarial Networks (GAN), Variational Autoencoders (VAE), and diffusion networks. To evaluate normalizing flows for manufacturing, experiments are conducted to synthesize surface defect images from an imbalanced data set and estimate parameters of a tool wear degradation model from limited observations. Results show that normalizing flows are an effective, multi-purpose DL architecture for solving these problems in manufacturing. Future work should explore normalizing flows for more complex degradation models and develop a framework for likelihood-based anomaly detection. Code is available at https://github.com/uky-aism/flows-for-manufacturing.
Tunable Stiffness in Material Extrusion of Thermoplastic Urethane
Authors: Van Domelen Ryan , Le Duy , Broman Andrew , Hawley Sandra , Wentz John
Published: September 2023

Thermoplastic polyurethanes (TPU) are increasingly being used in additive manufacturing design due to their abilities to exhibit extreme elastic properties under an applied stress. In this work, processing parameters in material extrusion (ME) of TPU filaments were investigated to provide a model for component stiffness as a function of the printing conditions. This model allows designers to target processing parameters and conditions to meet constraints of stiffness within flexible components. In this study, a full factorial design of experiments methodology was employed to provide a systematic method for experimentally analyzing the influence and effect of number of outer shells, infill percentage, and infill pattern on compressive strength. Based on the data collected from these experiments, a statistical regression model is presented that can be used to predict rigidity in TPU parts manufactured through material extrusion. Based on the results of the initial model, additional investigations were carried out into impact of number of infill line intersections, exterior corners, and TPU hardness (shore 85A and 95A). It was found that shore hardness and infill percentage had the largest impact with respect to stiffness but that all factors were significant and the only interaction not significant at α = 0.05 was the two-factor interaction of infill pattern and number of external shells. The effect of exterior corners were highlighted due to their additional stiffness as they essentially act as thicker columns in the perimeter of the parts.
Computational Modeling of Nanosecond Laser Ablation of Ti-6Al-4V
Authors: Shim Sally , Aguilar Lesly , Ma Jianfeng , Jahan Muhammad
Published: September 2023

Ti-6Al-4V is an alpha-beta titanium alloy having excellent strength, low modulus of elasticity, high corrosion resistance, good weldability and heat treatability. Consequently, it is the most commonly used titanium alloy with a wide use for applications in aerospace, automotive, and biomedical industries. However, Ti-6Al-4V is very difficult to be machined using traditional manufacturing processes. Laser machining is one nontraditional manufacturing process to machine Ti-6Al-4V. However, the laser-machined surface usually experiences phase transformation during the laser machining process because of the heating and cooling in laser machining. In this paper, the commercial Finite Element Method (FEM) software package ABAQUS is employed to assess the effect of nanosecond laser machining conditions and operating temperature on crater size, phase transformation in the Heat Affected Zone (HAZ), and residual stress distribution in laser machining of Ti-6Al-4V. The energy levels: 60mJ, 121mJ, 201mJ, 309mJ, 407mJ, 621mJ, 667mJ were tested. For the predictive modeling, three energy levels: 1000mJ, 2000mJ, and 4000mJ were tested. The phase transformation of Ti-6Al-4V at different temperatures was investigated to see material property change. The temperature used were: 200°C, 400°C, 600°C, 800°C, and 100C. Phase transformation kinetics is used to model the phase transformation of Ti-6Al-4V in laser machining process and rule of mixtures is employed to describe flow stress. Based on the results, the increasing the temperature will induce more HAZ. This research can provide insightful guidance for laser machining of Ti-6Al-4V.
A Study of the Laser Powder Bed Fusion Manufactured Surface Roughness Prediction and Optimization Based on Artificial Neural Network
Authors: Yan Dongqing , Lee Eddie Taewan , Pasebani Somayeh , Fan Zhaoyan
Published: September 2023

Laser powder bed fusion (L-PBF) is one of the most popular additive manufacturing methods in metal additive manufacturing. The surface roughness of the L-PBF manufactured parts is significantly influenced by major process parameters adopted, such as laser power, laser scanning speed, laser hatch space, and layer thickness of powder. This paper presented a machine-learning approach to determine the control parameters for reducing the surface roughness of the L-PBF products. In this study, a three-level full factorial experiment was designed with four major process parameters to examine the corresponding influence of surface roughness. The roughness of the fabricated samples was acquired by a laser profilometer. An artificial neural network model was trained to establish the relationship between the controllable parameters and finished surface roughness. The trained model was validated through additional experiments. The study provided an effective model for predicting the surface quality of L-PBF fabricated parts and a guideline for the process parameter selection.
Implementation of a Picosecond Laser for Micromachining the Cathode of Pulse Electrochemical Machining (PECM) and a Case Study
Authors: Fang Shiqi , Frank Alexander , Schäfer Mareike , Bähre Dirk
Published: September 2023

Defined topographic features may be produced on the workpiece surface of difficult-to-machine materials through the pulse electrochemical machining (PECM). Due to the contactless feature of PECM, mechanical influences and their side effects become ignorable. In this study, a picosecond laser, which induces little thermal impact, was applied to micromachine the cathode of PECM with groove patterns, and replication of the patterns on the anode of PECM was carried out using an industrial PECM installation. The results of the case study show that the picosecond laser achieved high machining precision (< 6.5% to the target size) with excellent surface integrity on the cathode of PECM, and the groove patterns were successfully replicated on the anode of PECM, although deviations of certain geometric parameters were detected between the two PECM electrodes. These deviations may be resulted from the rounding and widening effects during the PECM processing.
PEDOT: PSS Modified Laser Scribed Graphene for Flexible and Wearable Bioelectronics
Authors: Zhang Suheng , Yao Yao , Wang Yi
Published: September 2023

The rapid development of flexible and wearable electronic devices has increased the demand for highly flexible, conductive, and durable materials for device circuits. Over the past decade, laser-scribed graphene (LSG) has been widely employed for the contact-free and mask-free fabrication of conductive carbon circuits or patterns from polyimide or other precursors due to its excellent physiochemical properties. On the other hand, conducting polymer PEDOT: PSS has also been extensively studied for fabricating flexible electronics thanks to its excellent electronic/ionic conductivity and flexibility. However, both materials have their limitations, making them still difficult to use directly for manufacturing high-performance electronic devices. For example, the LSG is fragile and easily damaged, and PEDOT: PSS is easily clustered in aqueous solutions, reducing the conductivity. To overcome the limitations, in this paper, we report a facile and cost-effective LSG modifying method with PEDOT:PSS to enhance the performance, which combines the exceptional sensing properties of the PEDOT:PSS with the electronic advantages of the LSG. The modification method can be readily extended using inkjet printing or screen printing. The characterization and comparison experiments demonstrate that the electric conductivity can be improved to three times as that of the original LSG by PEDOT: PSS modification. The modified LSG has better flexibility, which is more suitable for flexible and wearable electronics.
Emissions Avoidance Quantification and Allocation Framework for Secondary Materials Marketplaces Supporting the Circular Economy
Authors: Hapuwatte Buddhika M. , Mathur Nehika , Morris K. C.
Published: September 2023

Many manufacturers are striving to reduce the negative impacts of their business activities, particularly with respect to greenhouse gas (GHG) emissions, also called “carbon emissions.” Estimates of such emissions are ubiquitously used in evaluating overall impacts of manufacturing activities. Additionally, regulations and corporate voluntary goals toward carbon emissions reductions are notably increasing. One area that still lacks methods and consensus on carbon emissions quantification is in the secondary materials marketplaces (SMMs), where more clarity is required on matters such as the allocation of these emissions given that their transactions involve multiple stakeholders. These marketplaces enable material recovery by bringing together organizations with excess and scrap materials with those that can use those materials. The SMMs are integral to implementing a circular economy (CE), as they prolong the longevity of materials in the economy further amortizing their impacts and fulfilling a fundamental premise of CE. In this work, we propose a framework to estimate the “Carbon Avoidance Measurement” (CAM) for transactions in SMMs. Then, we examine why each stakeholder’s CAM values may or may not be eligible for GHG reduction credits based on the GHG Protocol. We apply the framework to two different cases of materials transacted in an established SMM. Through this work, we also highlight the importance of such a measurement for broader CE system-level decisions, as well as the major standardization and industry-specific consensus needs for implementing such a framework.
Fluid Flow Analysis for Suitable 3D Bio-Printed Scaffold Architectures to Incubate in a Perfusion Bioreactor: A Simulation Approach
Authors: Clark Scott , Quigley Connor , Mankowsky Jack , Habib MD Ahasan
Published: September 2023

Due to the three-dimensional nature of the 3D bio-printed scaffolds, typical stagnant cell culturing methods don’t ensure entering medium inside areas or passing through the scaffolds. The bioreactor has frequently provided the required growth medium to encapsulated- and seeded-cells in 3D bio-printed scaffolds. To address this issue, we developed a customized perfusion bioreactor to supply the growth medium dynamically to the cells encapsulated or seeded in the scaffolds. The dynamic supply of fresh growth medium may help improve cell viability and proliferation. Because of its uniform nutrition distribution and flow-induced shear stress within the tissue-engineering scaffold, perfusion bioreactors have been used in a variety of tissue engineering applications. Including a modified setup of our designed bioreactor may improve the in vivo stimuli and conditions, eventually enhancing the overall performance of tissue regeneration. In this paper, we explored the response of fluid flow to certain types of scaffold pore geometries and porosities. We used a simulation technique to determine fluid flow turbulence through various pore geometries such as uniform triangular, square, diamond, circular, and honeycomb. We used variable pore sizes of the scaffold maintaining constant porosity to analyze the fluid flow. Based on the results, optimum designs for scaffolds were determined.
Evaluation of Bonding Performance of Laser Welding Between Glass and Aluminum
Authors: Ho Yi-Mo , Yang Chun-Wei , Ho Jeng-Rong , Lin Chih-Kuang , Tung Pi-Cheng , Lee Yuan-Shin
Published: September 2023

Glass is one of the commonly used materials with exceptional properties such as high mechanical strength, high chemical resistance, and low dielectric coefficient. Over the past decade, laser has been developed as a promising tool for welding between similar and dissimilar materials, especially glass and metals. Aluminum is also a commonly used material, which is known for its light weight, high conductivity, and high specific strength.

In this study, we conducted a glass-to-aluminum welding experiment using lasers, reported the welding results, and analyzed the influential factors of the welding strength caused by the laser system, including power, repetition rate, scanning speed, and scanning cycles. From the analysis, we found that power, scanning cycles, and interactions of the laser parameters are significantly important to the welding strength. Moreover, we built a logistic regression model to predict whether a welding sample can have a strong connection between glass and aluminum given the laser parameters. The results indicate that our model can achieve maximum accuracy of 81.2% for the prediction task. Therefore, our findings can fill the gap from previous studies that were lack of statistical data analysis and prediction tasks in glass-to-aluminum welding, and further enhance the welding quality in future studies.
In-Situ Detection and Prediction of WAAM Cross Feature Geometry
Authors: Thien Austen , Hussein Zaky , Saldana Christopher
Published: September 2023

Wire arc additive manufacturing (WAAM) is increasingly used by manufacturers due to its relatively low cost and high deposition rate compared to other metal AM methods, but the parts produced by WAAM can be subject to localized variations in part quality. One such variation is the cross-feature defect, whereby a localized part height increase occurs due to the crossing of deposition toolpaths. Mitigation of this defect is typically achieved using manual path planning strategies, but closed-loop control is underutilized. Since the nature of this defect and of the WAAM process is such that the previous layer’s geometry influences that of the subsequent layer’s, the cross-feature defect geometry changes throughout the deposition. Therefore, any closed-loop control strategy will need to incorporate the dynamic trait of this defect. The present work seeks to implement an in-situ process modeling approach where a regression model can be continuously updated to predict the defect geometry of the subsequent deposition layer based on the historical process data. Several multi-layer cross-feature geometries are deposited and current, voltage, and optical camera data is taken for each layer. The resulting cross-feature geometries are characterized using 3D scanning and the performance and accuracy of the in-situ modeling approach is evaluated.
Grinding Mechanism Evolution Based on Grain-Bond Dynamic Contact Behavior
Authors: Li Xin , Zhang Xueping , Yao Zhenqiang , Shivpuri Rajiv
Published: September 2023

To achieve the satisfied dimensional accuracy, surface integrity and grinding efficiency, the grinding parameters and conditions should be thoroughly considered in order to control the grain motion as well as material removal process. In previous studies, the grain was regarded as a rigid body attached on the edge of grinding wheel and its motion trajectory was determined by the geometric shape of the grinding wheel and the grinding parameters. However, the grinding tool and bond undergo elastic and plastic deformation under the grinding loads and thus those deformations lead to the occurrence of grain displacement. Correspondingly, the cutting depth reduction and the self-rotation resulted in the deformed abrasive-bond zone will change the interaction behavior as well as the material removal mechanism. Numerous published papers had investigated into the cutting depth reduction by considering the deformation of the grinding wheel at macroscopic scale, whereas few researches focused on the depth reduction caused by the grain-bond contact deformation at microscopic scale. Analytical model was insufficient to address the grain displacement mechanism and effects. Thus, this research aims to develop a methodology to address the evolution mechanism on the displacement and rotation of grain by considering the grain-bond dynamic contact behavior during grinding process. To validate the capability and accuracy of the proposed model, several types of grain-resin structures are designed to perform the realistic motion trajectory connected with the bond matrix under the specific loads. The predicted cutting depths are compared with those from simulations and experiment. It confirms that the proposed model provides a novel approach to investigate surface formation process and grinding mechanism evolution during the actual grain motion trajectory in grinding.
An Experimental Investigation on Nanosecond Laser Ablation of Single Crystalline Silicon Wafers
Authors: Francis Esha , Ma Charles , Ma Jianfeng , Nafi Muhammad Abdun , Karim Mahmud , Jahan Muhammad P.
Published: September 2023

This work investigates the occurrence of heat-affected zones and texture when performing laser machining and explores ways to reduce the prevalence of both. A reduced prevalence will lead to better performance of silicon wafers in nanotechnology within the semiconductor industry with fewer heat-affected zones (HAZs) and less surface texture. Varying parameters such as pulse energy, spot size, and scanning speed, created the conditions in which laser machining was performed on the silicon wafer sample. Data were collected at three different levels of each of the three different machining parameters (pulse energy, spot size, and scanning speed (active laser time are inversely related to counting as one parameter). 27 different combinations (conditions) were tested with each having three trials, and a total of 31 experiments were performed. It was found that laser pulse energy, spot size determined by the lens-to-sample distance and scanning speed influences the dimensions of the slots, heat affected zone (HAZ), and surface roughness of the slots. The results show that the range of laser pulse energy used in this study has not made significant influence on the ablation performance. Rather the spot size (lens-to-sample distances) played a major role in deciding both the dimensions, and HAZ of the features. Laser pulse energy has influenced the HAZ. Laser scanning speed has mostly influenced the surface roughness with higher scanning speed increasing the number of overlaps, thus increasing the average surface roughness. Understanding the effects of parameters for laser ablation of silicon wafer can be helpful to the semiconductor industry. This study aims to provide a plausible solution to the issue of heat-affected zones and surface texture on silicon wafers that the semiconductor industry faces when manufacturing these wafers.
Operational Feasibility of Maglev EDM Using Different Non-Conductive Powder Mixed Dielectric for Machining Inconel 625 Alloy
Authors: Singh Nirmal Kumar , Sahoo Rajesh , Bajpai Vivek
Published: September 2023

Currently, powder mixed dielectric application in electro-discharge machining (EDM) is an emerging field to enhance process efficiency and achieve better surface quality along with surface modification. The current investigation utilizes two non-conductive powder mixed dielectrics i.e., urea mixed distilled water and silica mixed distilled water for feasibility analysis by machining Inconel 625 alloy in Maglev EDM. The study emphasizes on the effect of both the dielectrics on material removal rate (MRR), tool wear rate (TWR) and surface roughness (Ra) achieved during Maglev EDM operation. The investigation has been performed using a cylindrical brass tool at discharge voltage (26V) and discharge current (200mA) for both dielectrics. The voltage-current (V-I) waveform acquired during machining operation illustrates better stability and consistency in discharge. The surface topology of the processed workpiece have been inspected using 3D surface profiles and scanning electron microscopy (SEM) for both the dielectric conditions to analyze the presence of surface anomalies and debris particles. The elemental analysis of machined surface examines the surface alloying phenomena due to material migration effect. Maximum MRR (961.5 μg/min) and lower Ra (4.71 μm) were observed using urea mixed dielectric condition, and low TWR (144 μg/min) was achieved using silica powder mixed condition.
Stress-Free Micro-Gluing Method for Thin-Walled Wolter-I Focusing Telescopes
Authors: Lee Erbo , Chen Xiao , Su Taiyu , Saren Qimuge , Zhang Zhijing
Published: September 2023

Wolter-I focusing telescope is one of the important equipment for space exploration, and its mirror shells are mainly assembled by gluing connection, since the mirror shell is a typical ultra-precise component with thin wall of easy deformation and nanometer-level surface accuracy, the stress caused by micro-gluing will have an important impact on the surface accuracy of the shell, which will reduce its optical focusing performance. In this paper, we propose a stress-free micro-gluing method for thin-walled Wolter-I focusing telescopes, in which the fixing clip is fixed by free bonding, and then screwed to the base after the adhesive layer has cured. Firstly, finite element simulation was conducted to analyze the gluing force state of the mirror shell in two forms, and then micro gluing experiments were carried out for the mirror shell in fixed and free forms, and the gluing strain of the mirror shell was measured by curing GHJ-01(Z) epoxy at constant temperature to verify the validity of the simulation results. The experimental and simulation results show that there is a significant difference between the gluing force state of the mirror shell in the two forms, the strain value and the surface shape error of the mirror shell are lower in the free bonding state than in the fixed bonding state. This method can provide a reference for the bonding method of the assembly structure of Wolter-I type focusing telescope.
Toolmarks-Driven Surface Texture for Coating Attachment With Drag Reduction and Anti-Biofouling Performance
Authors: Kang Putong , Huang Shengke , Beckle Brandon , Saavedra Cifuentes Edwin , Feng Leyun , Park Kyoo-Chul , Ehmann Kornel , Cao Jian
Published: September 2023

Though modern mass production has the advantages of low production costs and high efficiency, it cannot meet the needs of low-volume production with the agile demand for point-of-need manufacturing. Here, we aim at the construction of the hull of unmanned underwater vehicles (UUVs). UUVs provide safe and convenient solutions for underwater exploration, but the market and unique features of UUVs call for rapid digital manufacturing technologies. In this work, we propose a novel manufacturing method rooted in Double-Sided Incremental Forming (DSIF) for rapidly producing shell structures with riblet textures to aid drag reduction and anti-biofouling without the burden of specially designed tools or dies. First, a base hull structure is formed using the DSIF method. Then, the same setup is used for surface texturing with a different toolpath strategy utilizing the tool marks/textures on the surface for drag reduction. A coating based on Slippery Liquid Infused Porous Surfaces (SLIPS) technology is applied afterward to the textured surface. Finally, the drag coefficient and anti-biofouling performance are examined in experiments. Results show that with the combination of texture and SLIPS coating, the best drag reduction performance is achieved. The SLIPS coating is very effective in anti-biofouling and remains firmly attached to the surface under different flowing conditions. We anticipate that our method can be used in a broad range of functional shell structure applications with flexibility and cost efficiency.
A Fast and Cost-Effective Imaging System for Fine-Scale Tool Condition Monitoring in Ultrasonic Metal Welding
Authors: Dong Zhiqiao , Chen Qianmeng , Lu Kuan-Chieh , Shao Chenhui
Published: September 2023

In industrial-scale applications of ultrasonic metal welding (UMW), tool condition monitoring (TCM) is one of the most important maintenance tasks because tool health degrades quickly, and tool condition impacts the process physics and joint quality significantly. Moreover, tool replacement constitutes a notable portion of maintenance costs. In UMW, tool health degradation occurs mainly in the form of changes in tool surface geometry. Online TCM, which uses in-situ sensing data to indirectly classify tool conditions, has demonstrated to be effective; however, such indirect methods cannot provide a detailed characterization of tool surface profiles. On the other hand, direct measurements of tool surfaces require expensive and time-consuming high-resolution 3D metrology, which substantially increases the cost of quality and delays maintenance decision-making. To overcome these challenges, this paper develops a fast and cost-effective imaging system for fine-scale TCM in UMW. The imaging system mainly consists of a macro lens and a Raspberry Pi (RPI) high quality camera mounted over a linear rail driven by a stepper motor, and the full system is controlled through RPI GPIO (general-purpose input/output). The imaging system is used in conjunction with coaxial illumination, which enhances tool surface features, to capture a photo of a cast reproducing tool surface geometry. Then, image processing techniques are developed to characterize tool surface profiles and features. We demonstrate the effectiveness of the proposed TCM strategy using tools in three distinct conditions. Results show that the TCM imaging system can effectively reconstruct critical fine-scale geometric features of tools, thus enabling more responsive, interpretable, and reliable TCM for UMW.
Modeling of Laser Powder Bed Fusion of Inconel-718 Towards Relating Processing to Properties
Authors: Vest Alexandra , Hu Ruixiong , Maniatty Antoinette
Published: September 2023

In this work experimental and modeling methods are used to relate the processing parameters of laser power, velocity, and hatch spacing to thermal-mechanical history in a LPBF process, and first steps are made to relate to mechanical properties. Experimental work including tensile testing, microscopy, and density measurements are completed. Physics-based thermal simulations modeling the melting and re-solidification of layers of IN-718 powder are accomplished with consideration of powder consolidation on evolving geometry. Meltpool geometry results from the thermal simulations are compared alongside the experimental results with a proposed porosity indicator parameter that is expected to correlate to the level of porosity in a LPBF IN-718 part. Initial results show a linear relationship between the proposed porosity indicator parameter and the porosity percentage in LPBF IN-718 samples.
Novel STL-Free Design Paradigm for High-Resolution Multi-Scale Architected Cellular Materials in Additive Manufacturing
Authors: Rastegarzadeh Sina , Huang Jida
Published: September 2023

In recent years, advances in additive manufacturing (AM) techniques have called for a scalable fabrication framework for high-resolution designs. Despite several process-specific handful design approaches, there is a gap to fill between computer-aided design (CAD) and the manufacturing of highly detailed multi-scale materials, especially for composite design. This gap ought to be filled with an avenue capable of efficiently slicing multi-scale intricate designs. Most existing methods depend on the mesh representation, which is time-consuming and memory-hogging to generate. This paper proposes a mesh-free slicing pipeline that exploits the function representation (FRep) for hierarchical architected materials design. To explore the capabilities of the presented approach, several sample structures with delicate architectures are fabricated using an 8K Stereolithography (SLA) printer. The computational efficiency of the proposed slicing algorithm is studied. Furthermore, the geometry frustration problem brought by the connection of distinct structures between functionally graded unit cells at the micro-scale level is also investigated.
Anomaly Detection of Laser-Based Metal Additive Manufacturing Using Neural-Variational Auto-Encoder
Authors: Rescsanski Sean , Yadollahi Aref , Khanzadeh Mojtaba , Imani Farhad
Published: September 2023

The presence of anomalies in components generated using laser-based Additive Manufacturing (AM) processes greatly affects mechanical properties, making anomaly detection and prevention significant for the improvement of AM. Melt pool thermal imaging of laser-based AM processes such as Direct Energy Deposition (DED) provide rich data from which anomalies can be detected. Although through feature-based learning methods (e.g., support vector machine and k-nearest neighbor) or end-to-end deep learning models (e.g., self organizing map) the anomalies can be identified, the sparsity of defective instances and lack of interpretable analysis, together with high dimensionality and velocity of melt pool images further increase the difficulty of anomaly detection. We propose implementing Neural Vector Quantized Variational Autoencoder (Neural-VAE) to analyze thermal images from a DED process to determine where and when anomalies occur, indicating a flaw in the generated component. A Vector Quantized VAE is designed to represent high-dimensional images as low-dimensional vectors. Then, hyperdimensional computing is introduced to leverage the low-dimensional representation of image data and determine defective and non-defective images. Our proposed methodology can detect anomalies with an accuracy, sensitivity, specificity, and f-score of 99.2%, 99.6%, 98.8%, and 99.2%, respectively, while successfully generating anomalous images.
Design of 3D Printable Led Heat Sink Inspired by Firefly Wings
Authors: Sotoodeh Ali , Yang Yiran , Di Lei
Published: September 2023

Due to their high reliability, efficiency, and long lifespan, light-emitting diodes (LEDs) have gained massive popularity as a replacement for traditional light sources like fluorescent and high-intensity discharge lamps. Research has been dedicated to enhancing the thermal management of LED by improving heat transfer through innovating the heat sink design, where complex geometries have shown better performance than simple conventional geometries. In this study, experimental and finite element analysis techniques are used to examine a collection of complex heat sink designs, including one that is bio-inspired and made possible by 3D printing manufacturing capabilities. This research demonstrates that the intricate heat sink designs are 3D printable. Six distinct fin types are specifically examined, including traditional, cylindrical, rectangular, triangular, spiral, and fins inspired by firefly wings. Case studies compare some crucial factors like the weight and surface area of various designs and the performance that results. As a result of their ability to transfer an equivalent amount of heat over a smaller surface area, complex geometries are likely more efficient at transferring heat than conventional designs. With a smaller junction temperature on the heat sink and 32% less weight than the standard design, the firefly wing-inspired design outperforms the other complex geometries. The case study results also demonstrate the potential for further modifying the designs to better suit various applications, such as altering the number and thickness of fins. A bioinspired design, such as the one examined in this paper, can be used to create pole-mounted light fixtures, which typically need a high light output but smaller sizes.
Rapidly Reconfigurable Suction Gripper for Sheet Pick and Place Operations
Authors: Sagare Meghana , Wilson Victoria , Yu Zhao , Gupta Satyandra K.
Published: September 2023

Sheet-like materials such as composite prepreg fabrics are widely applicable in a variety of industries, especially the automotive and aerospace industries. During manufacturing, several of these applications require such sheets to be transported from one location to another. The use of robotic arms and suction grippers provides a reliable and flexible method for transportation operations. Since they are compliant, each sheet of varying size and shape requires a unique robot or end effector to ensure proper transportation and layup. This can quickly lead to increased hardware costs, increased cycle time, and the introduction of unnecessary components. To alleviate this, one robot can control one end effector that can be rapidly reconfigured to accommodate multiple sheet shapes. This paper presents a novel solution for sheet transport that leverages the motion of a 6 DOF (degree-of-freedom) robotic arm to reposition suction cups along linear tracks in a timely manner. We employ motion planning techniques to assist in process automation and aid in the accuracy and consistency of suction cup placement. Our design and method offer rapid reconfigurability while being cost-effective and lightweight. Experiments conducted in the lab validated the reconfigurability and accuracy of our design.
Control Modelling and Design for Time-Varying Dynamical Systems due to External Force in Human-Robot Interaction
Authors: Wei Bin
Published: September 2023

When there is a physical interaction between human operators and robotic systems in the manufacturing, there will be addition of external force component in the dynamical equation of the robotic system coming from the human operators. Different operators might place different forces onto the robotic system and therefore, a control system is required to control such time-varying dynamical systems due to the external force coming from the human operators in the manufacturing. A design process for the control system gears to such robotic systems in the human-robot interaction of manufacturing is presented and analyzed. The study proceeds from the simple one degree of freedom robotic arm to multi degrees of freedom robotic arms in the manufacturing. The designed control system can handle a range of robotic dynamical systems with varying external forces.
A Prediction Method for Catchment Efficiency Loss due to Coaxial Nozzle Wear in Powder Fed Directed Energy Deposition Systems
Authors: DeWitte Lisa , Fu Katherine
Published: September 2023

Powder fed laser directed energy deposition systems show significant promise and their widespread adoption could greatly advance manufacturing technology; however, a significant amount of gas atomized metal powder is wasted during material deposition. As contaminated powder must be collected and disposed of as hazardous waste, this process is often criticized for its low catchment efficiency. This presents potential implementation and scaling issues, as widespread use of this technology would directly increase the amount of contaminated powder in need of safe disposal. A direct contribution to this waste issue was identified in past work as wearing exterior and interior surfaces on a replaceable nozzle component within the additive head of such a system integrated into a hybrid manufacturing machine tool. A computational fluid dynamics simulation is developed specifically for use within the manufacturing process by predicting catchment efficiency losses before a deposition operation is performed. The model is robust enough to calculate a catchment efficiency estimate within a reasonable transition time before deposition and is designed to replace visual estimation of nozzle deterioration by the machine operator. Both of two previously identified wear modes are represented in the simulation. Their effects on powder stream geometry are discussed in detail and the results are compared with in-situ measurements of powder stream geometry and concentrations. The resulting work contributes to the growing understanding of using prediction and prevention methods on catchment efficiency related part defects within these systems.
Mathematical Analysis of the Tensile Behavior of DP 980 Steel Using Digital Image Correlation (DIC)
Authors: Seidi Ebrahim , Miller Scott , Huang Lu , Stoughton Thomas
Published: September 2023

This paper presents an analysis tool and preliminary, high-resolution results of material behavior and surface features during the tensile test of DP 980 steel specimen. The ultimate goal is a method for detection of localized through-thickness necking in stamping and welding samples based on measurement of the sample geometry and analyzing the evolution of surface features. It is thought that the onset of necking can be detected more precisely through characterization of the changes in the geometry of surface coordinate measurements than strain-based metrics. In this work, a MATLAB-based analysis tool was created to extract information from the ample data generated by DIC in tension testing. The results shown highlight the level of detail and granularity possible from DIC data. Several analysis results, such as the evolution of strains in x, y, and z directions, development of stress-strain cures, temporal surface profile, and curvature evolution, were presented for 201 surface points along the sample. The nature of the stress-strain behavior was plotted for every 0.25 mm along the sample, showing the increase in stress and strain at varying degrees in the diffuse neck. Surface profile and curvature evolution were shown at each 0.5-second time step. Comparing the temporal results of all points revealed the location of the diffuse neck on the sample.
Acoustic Assembly Photopolymerization of Bioinspired Multifunctional Devices With Programmable Adhesion
Authors: Lichade Ketki M. , Pan Yayue
Published: September 2023

Devices with stimuli-responsiveness, programmable and reversible adhesion, and adaptability to uneven surfaces have attracted extensive attention for applications such as micro-gripper and soft robots. Despite advances in design and manufacturing, challenges still exist in rapid shape morphing, non-contact control, and reversible switching between attachment and detachment. Fundamentally, those challenges are owing to the material limitation, manufacturing constraints, and design complexity involved in the production of those devices. To overcome these challenges, we report a simple and rapid manufacturing approach, acoustic assembly photopolymerization (AAP), for the production of magnetic-responsive devices with programmable and reversible adhesion. The proposed AAP process provides an environmentally sustainable approach to fabricating micro- to macro-scale multimaterial films within seconds. The locally controlled multimaterial composition enables precise magnetic control, while the flexible hierarchical surface structures allow rapid attachment and detachment. The combined effects of material and structural composition enable remarkable control over the adhesive property without requiring any complicated treatment and power source. In this work, a photocurable magnetic composite material was developed, and the adhesion and magnetic responsive characteristics of the printed films were further investigated. As a proof-of-concept, two test cases were performed using the as-printed films. The first test case is soft magnetic robots made of AAP-printed films. Effects of the film surface structures on the adhesive properties and hence the robot crawling locomotion are analyzed. The second test case is a gripper for lifting and releasing objects. Capability of the AAP-printed films on gripping objects of different sizes in different environments (i.e., in air and in water) are demonstrated. Experimental results validated the effectiveness of the novel AAP process on fabricating films with spatially varied compositions and hierarchical surface features. The test cases indicated the promising applications of such AAP-printed films, with advantages of programmable adhesion, locally-engineered flexibility, rapid and remote non-contact magnetic actuation. The AAP manufacturing capability and the proposed multimaterial hierarchical surface design possess a broad range of applications, including surface engineering, soft robotics, and microfluidics.
Electropulsing-Assisted Ultrasonic Nanocrystal Surface Modification on Microstructures and Mechanical Properties of Additive Manufactured Inconel 718
Authors: Zhang Chaoyi , Gao Le , Peng Lan , Liu Gang , Ye Yixuan , Zhang Yu , Tang Chao , Huang Tao , Ye Chang
Published: September 2023

Additive manufacturing technology can process parts with complex shapes and has great application potential in the biomedical and aerospace industries. However, additively manufactured parts have a poor surface finish, high porosity, and large tensile residual stresses and thus have poor mechanical properties compared with traditional cast or forged parts. To address this issue, an innovative surface enhancement technology, namely electropulsing-assisted ultrasonic nanocrystal surface modification (EP-UNSM) technology, is proposed. A pulsed current is exerted on the sample to improve the metal plasticity during the UNSM processing, thereby further enhancing the strengthening effect. The results have demonstrated that EP-UNSM can further improve the surface integrity and surface hardness of the samples. In addition, compared with continuous current, pulsed current can more effectively improve the plasticity of Inconel 718, even though the effective current density and thus the thermal heating effect are the same. This enhancement effect is more significant at higher peak current density, proving the athermal effect of electroplasticity.
Spatial-Terminal Iterative Learning Control for Registration Error Elimination in High-Precision Roll-to-Roll Printing Systems
Authors: Wang Zifeng , Jin Xiaoning
Published: September 2023

Roll-to-roll (R2R) printing techniques are promising for high-volume continuous production of substrate-based electronic products, as opposed to the sheet-to-sheet approach suited for low-volume work. However, one of the major challenges in R2R flexible electronics printing is achieving tight alignment tolerances, as specified by the device resolution (usually at micrometer level), for multi-layer printed electronics. The alignment of the printed patterns in different layers, known as registration, is critical to product quality. Registration errors are essentially accumulated positional or dimensional deviations caused by un-desired variations in web tensions and web speeds. Conventional registration control methods rely on model-based feedback controllers, such as PID control, to regulate the web tension and the web speed. However, those methods can not guarantee that the registration error always converges to zero due to lagging problems. In this paper, we propose a Spatial-Terminal Iterative Learning Control (STILC) method combined with PID control to enable the registration error to converge to zero iteratively, which achieves unprecedented control in the creation, integration and manipulation of multi-layer microstructures in R2R processes. We simulate the registration error generation and accumulation caused by axis mismatch between roller and motor that commonly exists in R2R systems. We show that the STILC-PID hybrid control method can eliminate the registration error completely after a reasonable number of iterations. We also compare the performances of STILC with a constant-value basis and a cosine-form basis. The results show that the control model with a cosine-form basis provides a faster convergence speed for R2R registration error elimination.
Polymer-Derived SiC Ceramic With Triply Period Minimal Surface Structure Fabrication Through Digital Light Processing
Authors: Liu Haiyu , Wang Yancheng , Qian Senyu , Mei Deqing
Published: September 2023

The ceramic-based porous structures and components have received considerable attention in biomedical and biological fields. This paper presents a method by using digital light processing (DLP) 3D printing technology to fabricate polymer-derived SiC ceramic components with triply period minimal surface (TPMS) porous structure. The photosensitive preceramic polymer resin with low viscosity was prepared by dissolving polycarbosilane (PCS) into photosensitive resin and organic solvent, and its optimal resin composition are studied to print the TPMS structural green bodies. Then, five different types of TPMS structural SiC ceramic components with high porosity of 80% were successfully designed, printed and pyrolyzed at 600–1400 °C with uniform shrinkage. The fabricated porous SiC ceramic components almost have no deformation, damage, or obvious cracks on the surface. The weight loss, linear shrinkage, density, and mechanical properties of the TPMS SiC ceramic components with different pyrolysis temperatures were characterized. The results showed that the prepared TPMS SiC ceramic components exhibited high-resolution microstructure and excellent mechanical properties, which would have great application prospects in future tissue engineering and biological scaffolds.
Fiber-Reinforced Polymer Composites Fabrication Through Acoustic-Assisted 3D Printing Process
Authors: Xu Chengyao , Wang Yancheng , Liu Jiawei , Han Shuo , Mei Deqing
Published: September 2023

Multifunctional composites have been widely utilized in aerospace, biomedical and electronic devices. Fiber-reinforced composites are characterized by lightweight, tough, and with high energy absorption capabilities, they have received considerable attentions. Honeycomb structure is one of the typical lightweight structures of fiber-reinforced composites, it features a two-dimensional polygon array with periodic topological organization in the plane, and brings technical challenges to fabricate fiber-reinforced composites. Herein, we present a novel acoustic-assisted 3D printing method to fabricate fiber-reinforced composites with simplified honeycomb structures. Firstly, the surface acoustic wave (SAW) assisted printing system was developed, and its working principle for fiber-reinforced composites printing was introduced. Both carbon fibers and carbon nanofibers can be patterned into fine patterning with the assistance of SAW-induced pressure fields. With a layer-by-layer process, fiber-reinforced composites with simplified honeycomb structures were successfully printed. The compression tests showed that the specific energy absorption of the fiber-reinforced composite was about 168 J/kg and its ultimate stress was 1840 kPa, these values were 75.0 % and 102 % higher than that of the pure resin printed structures, respectively.