bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental Investigation of Natural Circulating Solar Energy System Including a Parabolic Trough Solar Collector
Authors: Bayhan Burhan , Arslan Gökhan
Published: August 2024

The most common natural flow water heating systems are in one-ended inclined pipes today. This study aims to investigate the natural circulation solar energy system experimentally with a parabolic trough solar collector. For this purpose, a natural circulation solar energy system including a parabolic trough solar collector that follows the sun in one dimension on the N–S axis in the outdoor environment has been established. Experiments were conducted on different dates. The radiation values coming into the opening of the moving collector were calculated. With the soltrace program, it has been found that 56% of this radiation can reach the vacuum tube glass pipe in the focus of the collector. In addition, the Rayleigh number was calculated for each experiment for the section of the glass tube close to the tank inlet, and it was monitored whether there was natural circulation throughout the experiment. As a result, the average Rayleigh number in the experiments conducted on February13, March 31, April 24, May 23, June 9, and July 6 was 1.4E + 06, 7.6E + 05, 7.8E + 04, 2.2E + 04, 3.1E + 05, respectively. and calculated as 2.8E + 05. In the experiments on May 23 and April 24, when the cooling system was open, it was observed that the Rayleigh number constantly dropped below the critical value. In other experiments, the situation is the opposite, and the natural flow is continuous.
Factor Analysis-Based Selection of Xanthoceras sorbifolia Bunge Oil as a Promising Bio-Based Lubricant
Authors: Liu Jianfang , Zhang Rongrong , Peng Shuai , Liu Ting , Yang Sicheng , Yi Chenglingzi , Zhang Yaoyun , Jia Dan , Yang Qing
Published: August 2024

With increasing environmental awareness, the demand for bio-based lubricants is escalating, positioning vegetable oils as viable alternatives to traditional industrial lubricants. This study employs comprehensive factor scores to assess and rank the antiwear property and oxidation stability of 53 vegetable oils with diverse fatty acid compositions. Xanthoceras sorbifolia Bunge oil (XSBO), derived from woody oil plants renowned for their economic and environmental benefits, emerges as a standout candidate following the exclusion of previously reported lubricant types. Comparative evaluations via four-ball friction tests and pressurized differential scanning calorimeter (PDSC) analyses reveal that XSBO’s antioxidant property is slightly inferior to the mineral oil, poly-alpha-olefin, and synthetic ester. However, XSBO exhibits superior tribological property and viscosity characteristics. Supported by computational modeling and laboratory validation, XSBO demonstrates significant promise as a bio-based lubricant, advocating its potential as an ideal replacement for conventional base oils.
Mechanical Behavior Analysis of a Functionally Graded Porous Dental Implant
Authors: Dabaja Rana , Sayeed Khan Abdul , Banu Mihaela
Published: August 2024

Medically compromised patients causing severe amounts of bone loss in the maxillary/mandibula experience low success rates with dental implants. The bone loss is caused by a weak interfacial connection between the implant and the maxillary/mandibula and because of a stiffness mismatch between bone and titanium. To address this challenge, functionally graded porous dental implants are proposed as a promising solution to mimic the natural tooth by matching the stiffness of the titanium support with the maxillary/mandibula. In this paper, we employed functionally graded materials to design a triply periodic minimal surface (TPMS) gyroid-graded porous structure with five distinct connected porosities leading to a solid core. The study aimed to develop a structure with mechanical properties similar to bone while maintaining mechanical strength to withstand physiological loading. An analytical model for a functionally graded porous structure was utilized to calculate a theoretical elastic modulus in relation to five different porosities along the gradient. The target porosities were determined as 10%, 20%, 30%, 40%, and 50%, with corresponding elastic modulus ranging from 103.94 GPa to 35.25 GPa. Five TPMS solid gyroid samples made of Ti-6Al-4V were designed for a specific stiffness corresponding to the bone, using an analytical model considering an exponential relationship between stiffness and porosity. These structures were then manufactured through selective laser melting, resulting in final porosities of 6.64%, 11.56%, 18.40%, 28.74%, and 36.23%, with corresponding pore sizes of 130 μm, 185 μm, 280 μm, 360 μm, and 420 μm. The stiffness of the designed and manufactured porous structures was validated through uniaxial compressive experiments. Digital Image Correlation (DIC) accurately recorded displacements to calculate strain during compression experiments up to failure. Microscopic analysis of the compression samples’ failure provided insights into the role of pores in sample damage. Results confirmed that the elastic modulus of the porous structures was reduced to the designed values between 21.7–65.3 GPa, compatible with bone. This represents a significant drop in stiffness compared to solid Ti-6Al-4V, for which stiffness is 114 GPa. Through this matching of stiffness between bone and the implant, the so-called stress shielding effect caused by a weak interfacial connection can be reduced, decreasing the risk of implant failure.
Investigation of Distributed Additive Manufacturing for 3D Printed Headband Component During Global Supply Chain Disruptions
Authors: Mamros Elizabeth M. , Kantipudi Saketh , Eaton Matthew C. , Ha Jinjin , Kinsey Brad L.
Published: August 2024

During the COVID-19 global pandemic, a shortage of personal protective equipment (PPE) occurred. Manufacturers of these critical products were unable to keep up with the growing demands as the situation evolved. Most face shields, a common type of PPE, include a headband component to provide the appropriate fit for the user and curvature for the clear face shield attachment. To mitigate this shortage in the local region, the Portsmouth Naval Shipyard (PNSY) generated a computer-aided design (CAD) file for the headband component and asked the University of New Hampshire (UNH) to manufacture it with all available 3D printers, including printers housed off-campus. Despite using the same part file, the headbands exhibited inconsistencies, particularly in part quality and performance. These variations in manufactured products can be attributed to the different machines, locations, materials, printing parameters, and personnel utilized in their production. This disparity in part quality resulted in the scrapping of approximately 5% of the 2000+ headbands printed at UNH, an unacceptable manufacturing metric. To address quality concerns, the 3D printer operators manually altered the original part file’s cross-sectional area in CAD software through a trial-and-error approach until the printed parts from each printer met the quality specification. This process of manual adjustment hindered the fast setup times and low costs attributed to distributed manufacturing resulted in essential PPE being scrapped.

Ideally, using smart manufacturing, the part file geometry could be updated automatically, without further user inputs, based on the material properties used in the 3D printing. This could be accomplished by the implementation of an analytical model into a script for the CAD software that would calculate and update the part dimensions.

In this paper, a case study to support distributed additive manufacturing for a simplified PPE headband during a global supply chain crisis, e.g., pandemic, is presented. Headbands were printed using four different material filaments and the original part file from PNSY to collect preliminary data. A finite element model was created to predict the force-displacement curves exhibited by headband parts produced using the different materials. An analytical model was derived to determine the geometry modifications required to achieve the desired part quality, i.e., force-displacement curve. Experimental validation was conducted and revealed good agreement with the analytical model predictions. In future work, these updates to the part geometry will be completed autonomously, using cyber manufacturing, by implementing the analytical model into CAD software via a script. This analytical model allows for distributed manufacturing to get past the hindrances of 3D printing manufacturing variances, advancing towards Industry 4.0.
Physical, Mechanical, and Thermal Characterization of Unfilled and Carbon Fiber Filled Polyamide (PA) Filaments and Corresponding Fused Deposition Modelling Fabricated Samples
Authors: Shah Adarsh Kumar , Jain Atul
Published: August 2024

Fused deposition modelling (FDM) represents a promising domain in 3D printing techniques that fabricates objects layer by layer from 3D CAD data. While FDM excels in fabricating pure polymer composite parts, the limitations of matrix polymers necessitate the development of fiber-reinforced polymer composites. Despite polyamide’s superior mechanical properties as a composite matrix, there’s limited research on short carbon fiber-reinforced polyamide (PA) in FDM. Moreover, previous studies typically focus solely on evaluating the tensile properties of FDM printed parts, neglecting feedstock filament properties. Understanding and enhancing the material properties of commercially available carbon fiber polyamide (CF/PA) filament remains a challenge.

This study renders a thorough examination of the microstructural changes and property evaluation pre and post-FDM printing. In this work, raster angles were examined, with a focus on their direct influence on mesostructure, solid-state sintering mechanics, and resulting composite part characteristics through inter-bead and inter-layer bonding, affecting voids, fibers, and the base material matrix. Results show significant fiber breakage, leading to a 31.30% reduction in the average length of fibers from filament to printed parts. While the filament maintains high fiber alignment, printing occasionally leads to misalignment. Tensile tests reveal anisotropic properties in FDM samples with varied raster angles. Short carbon fibers decrease strength but boost Young’s modulus in filament-to-FDM conversion. Examination of fractured surfaces reveals distinct failure modes for filament and printed test coupons. TGA confirms nearly 20 wt.% carbon fiber in the filament, with pure PA filament and samples yielding minimal residue. DSC results indicate enhanced thermal stability with carbon fiber reinforcement, while XRD reveals distinct amorphous behavior in both filament and printed parts.
Finite Element Modeling of Laser Powder Bed Fusion Process Used for Consolidating W-25 Wt.%Re Alloy Pin Tool for Friction Stir Welding
Authors: Alshami Ali , Shuaib Abdelrahman
Published: August 2024

The main challenge to researchers in friction stir welding (FSW) steels and high temperature alloys, using pin tools from refractory metal alloys such as W-25wt.%Re alloys, is to develop the tools that stand the process harsh conditions. Most recently, laser powder sintering to consolidate W-25wt.%Re alloys have shown promising results in producing pin tools for FSW. These results are the motivation for the authors of this paper to consider using a laser powder bed fusion additive manufacturing (LPBF-AM) process for consolidating W-25wt% Re powder alloys, in two steps. First, use finite element modeling to identify the levels of the LPBF-AM process parameters that will produce a pin tool that has the desired mechanical and physical properties for FSW welding steels and high temperature alloys. Second, use the identified process parameters to produce an experimental pin tool and evaluate its suitability for welding steels and high temperature alloys, with respect to tool mechanical and physical properties. The results of the finite element modeling, which are reported in this paper, include effects of the LPBF parameters on the resulting melting pool formation and geometry, as well as on the residual stresses that develop during the laser powder sintering process.
Impact of Heat Input and Step Over Distance on Part Geometry for Multi-Bead WAAM Components
Authors: Hussein Zaky , Goodwin Jesse , McCoy Matthew , Bose-Bandyopadhyay Shohom , Saleeby Kyle , Saldaña Christopher
Published: August 2024

This study investigates the impact of heat input and overlap ratio or stepover distance on part geometry in wire arc additive manufacturing (WAAM). In this work, an experimental approach was taken to quantify the variation in height and aspect ratio of walls at different combinations of overlap and heat input. Multi-bead walls were deposited with the overlap ratio varying from ½, ⅔, and 1 at a low, medium, and high-power set point on the welding power supply. A relationship between heat input, overlap ratio, and the resultant part geometry is established.

Trials with an overlap ratio of one and low to medium heat input exhibited greater lack of fusion defects than the high heat input trials. At higher heat input levels, the as-deposited geometry was found to have less variation in height and an increase in aspect ratio compared to lower heat input trials. The aspect ratio of deposited walls ranged from approximately 1, for the low-power trial with an overlap ratio of ½, to approximately 7, for the high-power trial with an overlap ratio of 1. Additionally, the low and medium power trials with an overlap ratio of ⅔ exhibited the least height variation in the top surface for those heat input levels with an average range of 2.9 mm and 1.8 mm respectively. For the high heat input trials, an overlap ratio of 1 was observed to have the least variation in height with a standard deviation of 0.42 mm and an average range of 1.7 mm; however, lack of fusion defects were present in the top surface and the part cross section.
Brief Paper: Geometric Determinants of Material Jetting-Enabled Bi-Material Interface Integrity Using Polyjet 3D Printing
Authors: Aberdeen Nolan J. , Forghani Kimia , Sochol Ryan D.
Published: August 2024

Among the wide range of additive manufacturing — or “three-dimensional (3D) printing” — technologies, “material jetting” approaches are distinctively suited for multi-material fabrication. Because material jetting strategies, such as “PolyJet 3D printing”, harness inkjets that allow for multiple photopolymer droplets (and sacrificial support materials) to be dispensed in parallel to build 3D objects, distinct materials with unique properties can be readily unified in a single print akin to combining multiple-colored inks using a conventional 2D color printer. Although researchers have leveraged this multi-material capability to achieve, for example, 3D functionally graded and bi-material composite systems, there are cases in which the interface between distinct materials can become a key region of mechanical failure if not designed properly. To elucidate potential design factors that contribute to such failure modes, here we investigate the relationship between the interface design and tensile mechanical failure dynamics for PolyJet-printed bi-material coupons. Experimental results for a select set of bi-material sample designs that were 3D printed using a Stratasys Objet500 Connex3 PolyJet 3D printer and subjected to uniaxial tensile testing using a Tinius Olsen H25K-T benchtop universal testing machine under uniaxial strain revealed that increasing the surface contact area between two distinct materials via changes in geometric design does not necessarily increase the interface strength based on the length scales and loading conditions investigated in the current study and that further studies of the role of multi-material geometric designs in interface integrity are warranted to understand potential mechanisms underlying these results. Given the increasing interest in material jetting — and PolyJet 3D printing in particular — as a pathway to multi-material manufacturing in fields including robotics and fluidic circuitry, this study suggests that multi-material interface geometry should be considered appropriately for future applications.
An Investigation of the Effects of Vibration Compensation on Print Quality of High-Speed Metal Extrusion Based Additive Manufacturing
Authors: Shirzad Sajad , Chou Cheng-Hao , Versin Alexandru , Habbal Osama , Okwudire Chinedum , Pannier Christopher
Published: August 2024

Metal paste extrusion is an emerging metal additive manufacturing process at the intersection of fused filament fabrication and binder jet printing categories. It produces parts using extruded beads of a metal-and-binder paste and achieves final densification in a sintering furnace cycle. In the metal paste extrusion process, reducing build time is crucial for improving process economics. Similar to fused filament fabrication, the toolhead positioning in metal paste extrusion can induce vibrations in the printer frame and components, especially at high acceleration and speed needed to reduce build time. These vibrations can lead to defects in the deposited part.

In this study, a commercially available vibration compensation algorithm, initially developed for fused filament fabrication, is applied to metal paste extrusion for the first time to reduce build time. The algorithm uses the natural frequencies and damping ratios of the machine’s motion system to predict and compensate for vibrations. Three test conditions are employed to produce sample parts in stainless steel 316L for geometric, material, and mechanical property evaluation: nominal printing settings without vibration compensation (print speed 40 mm/s), faster printing settings without vibration compensation (print speed 70 mm/s), and the same fast settings with vibration compensation.

The test part consists of three sections: a solid (∼100% infill) section, a low-infill section (∼40%) where the infill and meshing are visible, and another low-infill section with two top layers. The resulting samples are analyzed for geometric error, density, and hardness effects. Geometrical errors are observed using macro photography, particularly in the outer perimeters at the corners. Voids (gaps between beads) within the top layer are observed using 3D scanning. Density following ASTM B311 standards and subsequently porosity are measured. The final test involves Rockwell B hardness testing at three specified points on the samples.

Without vibration compensation, the outer perimeter exhibits ringing. Faster printing with vibration compensation demonstrates savings in build time without negatively affecting the quantified geometric, material, or mechanical properties.
Data Efficient Modeling for Prediction and Forecasting of WAAM Process Conditions
Authors: Thien Austen , Van Handel Nicole , Hu Helen , Saleeby Kyle , Saldana Christopher
Published: August 2024

Wire arc additive manufacturing (WAAM) utilizes conventional welding processes and wire-feedstock to deposit material layer by layer until a near net-shape geometry has been achieved. This approach gives WAAM great potential among metal additive manufacturing processes for its ability to produce larger scale components much faster than powder-based processes. The selection of certain initial WAAM process parameters, such as input power and interlayer dwell time, can often impact the stability of the contact-tip-to-workpiece distance (CTWD), current, voltage, and linear energy density during deposition. The resulting process stochasticity can cause variations in part geometry, microstructure, and mechanical properties. Therefore, it is desirable to create process models that can predict these WAAM process condition values for a variety of initial process parameter settings. These predictions can then be used to optimize initial WAAM process parameter settings or forecast when process condition instability is expected to occur. In the present work, single-bead multi-layer walls are deposited using a variety of input power and interlayer dwell time settings. Two different modeling approaches are then investigated: multilayer perceptron (MLP) regression and time series forecasting. An artificial neural network (ANN) is trained to predict process condition values based on the initial WAAM process parameters and a given time in the deposition process. Autoregressive integrated moving average (ARIMA) and long-short term memory (LSTM) time series models are trained to forecast subsequent process condition values based solely on the previous process condition values with no prior knowledge of the initial WAAM process parameters. The models are evaluated and compared based on their accuracy in predicting data streams of CTWD, current, voltage, and linear energy density. Additionally, the effect of training data quantity on model accuracy is examined for each model approach. For the ANN model, the training data size is decreased by reducing the resolution of the time series data as a whole and by reducing the number of layers that are used in the training dataset. For the ARIMA and LSTM models, the training data size is limited by reducing the resolution of the time series process data. Additionally, the lag order or “lookback” period, which is a key hyperparameter of both models that represents that number of previous data points needed to forecast a subsequent data point, is optimized via a grid search when the models are trained. Overall, this study will seek to provide modeling techniques to minimize process condition instability by optimizing initial WAAM process parameters and to forecast process condition instability so that it can potentially be mitigated.
Irradiation and Hip Impact on Microstructure and Small-Scale Mechanical Properties of AM Nuclear Reactor Materials
Authors: Nipa Lutfun , Siller Hector R. , Sharma Mohin , Rout Bibhudutta , Mirshams Reza A.
Published: August 2024

The requirement for advanced materials in nuclear reactor applications highlights the necessity for a profound understanding of their behavior under challenging conditions, including radiation exposure. Until nuclear energy remains a significant source of energy production worldwide, 17-4 PH SS holds a crucial role in safeguarding the reliability and efficiency of nuclear reactors. This study delves into the optimization of 17-4 Precipitated Hardened Stainless Steel (17-4 PH SS) through a combination of Additive Manufacturing (AM) and postprocessing techniques. Hot Isostatic Pressing (HIP) is utilized to mitigate flaws such as pores, voids, and microcracks. Simultaneously, irradiation is harnessed to simulate the microstructural and mechanical properties enhancing reliability and efficiency of nuclear reactors. To comprehend the influence of HIP and irradiation techniques to improve the material’s compatibility for high-temperature & high-radiation settings; microstructural characterization in aspects of surface morphology, texture, and fractography is undertaken. Additionally, small-scale mechanical testing using nanoindentation process is used to evaluate the mechanical characteristics for hardness and modulus, offering important insights into the endurance of the material in radiation-intensive conditions. A thorough evaluation of the material’s response to these treatments in the context of nuclear reactor applications is provided by comparing these properties between specimens in different orientations subjected to HIP and irradiation and as-received LPBF-manufactured material. The results indicate that LPBF-fabricated 17-4 PH SS at optimized process parameters in both parallel & perpendicular orientations to the build direction provides distinctive microstructural & mechanical responses, which are notably enhanced by applying HIP treatment and irradiation serving as a hardening mechanism for as-printed samples.
Measuring Overhang Down-Skin Dross Depth and the Inter-Dependency on Melt Pool for Laser Powder Bed Fusion Additive Manufacturing
Authors: Yang Zhuo , Kim Jaehyuk , Lane Brandon , Lu Yan
Published: August 2024

The overhang down-skin surface exhibits distinct behaviors compared to the regular up-skin surface in the powder bed fusion process. Evidence suggests that weak support could be the primary cause of these differences. Previous studies by the authors have indicated that the unique features on the overhang down-skin surface may result from a series of abnormal melting conditions. This paper measures the dross depth of overhang down-skin surface using registered micro-x-ray computed tomography (XCT) data. In addition, it extracts features of the melt pool related to the overhang from overhang 1,000,000 in-situ melt pool images. Four overhang parts with identical geometry and process parameters were fabricated using a powder bed fusion testbed in this study. The results demonstrate that the behavior of the overhang down-skin surface is repeatable across all four parts. The depth of dross is influenced by geometric factors such as the overhang angle and position. The study also reveals that the weak support provided to overhang surface can affect melting in multiple layers, including both the current and future layers. Additionally, this study finds the dross depth and top-surface melt pool size do not have significant statistical correlations. However, a preliminary finding suggests users may identify the extremely large overhang dross formation by monitoring melt pool features in multiple layers above the overhang.
Brief Paper: Understanding the Role of Print Bed Thermal Behavior on Defect Formation in Fused Filament Fabrication
Authors: Keim Anna O. , Young Jaylen A. , Hanson Cyra A. , Collins Megan N. , McClain Monique S.
Published: August 2024

Fused Filament Fabrication (FFF) has become increasingly popular due to its accessibility and rapid fabrication abilities. However, FFF cannot reliably reproduce prints and often suffers from low print quality, which negates many of its benefits. Most previous work in improving FFF has focused on optimizing print parameters, yet results still vary from print to print and printer to printer. Recently, there has been an emphasis on detecting the formation of anomalies using nondestructive methods such as infrared (IR) thermography and other imaging techniques that monitor the part in-situ. While these approaches can identify the formation of geometric anomalies, they are limited to surface and subsurface observations. Furthermore, analyzing images for anomalies is computationally expensive compared to integrated thermocouples that can be used to flag thermal anomalies. This research aims to investigate the unstudied heat transfer interactions between the print bed and cooling fan that impact part quality (e.g., warping, shrinkage, etc.) and local polymer properties (e.g., crystallinity) via thermocouples integrated into the print bed. This is accomplished by printing 1 cm PLA cubes at bed temperatures from 60 to 110°C, and by conducting no-extrusion experiments to measure the bed thermal behavior without printing. It was found that the measured bed temperatures varied spatially across the print bed, and significant interactions between the cooling fan and print bed were measured at the print location. At 100% fan speed, the central thermocouple temperature decreased by 18.53°C and 8.71°C at given bed setpoint temperatures of 110°C and 60°C, respectively. These interactions often led to print failure at high bed temperatures, as excessive cooling near the built-in thermistor caused increasing print bed temperatures at other locations. This cooling is suspected to have triggered a bed thermal runaway error at high temperatures (∼120°C). Lastly, the effect of the cooling fan on print geometry was observed by varying the layer at which the fan turned on. Turning the fan on later in the process led to severe geometric anomalies in the upper layers of the print. Ultimately, this work shows the importance of including the effect of the cooling fan on the print bed in models of the FFF process. Understanding this relationship will allow for the development of fan cooling strategies that will not interfere with printer performance or print quality, leading to consistent fabrication of higher-quality parts.
Numerical Analysis of the Melt Pool Kinetics in Selective Laser Melting Based Additive Manufacturing of Thermoelectric Powders
Authors: Suresh Jagannath , Goyal Gagan K. , Wang Haozheng , Zuo Lei
Published: August 2024

Thermoelectric generators convert heat energy to electricity and can be used for waste heat recovery, enabling sustainable development. Selective Laser Melting (SLM) based additive manufacturing process is a scalable and flexible method that has shown promising results in manufacturing high zT Bi2Te3 material and is possible to be extended to other material classes such as Mg2Si. The physical phenomena of melting and solidification were investigated for SLM-based manufacturing of thermoelectric (Mg2Si) powders through comprehensive numerical models developed in MATLAB. In this study, Computational Fluid Dynamics (CFD)-based techniques were employed to solve conservation equations, enabling a detailed understanding of temperature evolution within the molten pool. This approach was critical for optimizing processing parameters in our investigation, which were also used for printing the Mg2Si powders using SLM. Additionally, a phase field-based model was developed to simulate the directional solidification of the Mg2Si in MATLAB. Microstructural parameters were studied to correlate the effects of processing parameters to the microstructure of Mg2Si.
Sustainability Evaluation of Traditional and Additive Manufacturing for Mold Insert Application
Authors: Zhao Jing , Riggle Zayda , Mendis Gamini , Yang Yiran
Published: August 2024

The exceptional speed and quality achieved through injection molding have made it a great tool for high-volume production. However, the time-consuming process of debugging molds makes it expensive and leads to resource wastage. In response to the fast-growing demand for low-cost and fast production, additive manufacturing (AM) emerges as a promising candidate for cost-effective mold design and fabrication. This innovative approach not only circumvents the high initial investment of tooling associated with traditional injection molding but also offers significant advantages in terms of flexibility in design and manufacturing. Moreover, it provides the potential for creating customized molds on demand, allowing for reduced lead times and enabling rapid production. In this study, a comparative analysis is conducted to evaluate an injection mold insert produced using traditional machining processes and AM. An injection mold insert is designed for pharmaceutical applications and then manufactured using a computer numerical control (CNC) machine tool and two popular AM processes — fused deposition modeling and stereolithography. A combination of three critical AM process parameters (i.e., layer thickness, build angle, and infill rate or post-curing time) is selected and used for fabricating the injection mold inserts; meanwhile, sustainability and quality are evaluated. More specifically, the total energy consumption is quantified and compared for the three manufacturing processes, and the unit manufacturing cost is computed comprising energy cost, labor cost, and materials cost. In addition to sustainability measures, the mechanical strength in terms of hardness of the mold inserts is also investigated as their ability to withstand the high pressures encountered during the injection molding process affects the number of molding cycles before a failure. The dimensional accuracy is also experimentally analyzed to evaluate whether the injection molded products will be manufactured to appropriate tolerances. The results of this study confirmed the feasibility of adopting AM techniques as a viable alternative for injection mold insert manufacturing with lowered unit manufacturing costs and reduced energy consumption. The lower mechanical performance of additive-manufactured mold inserts compared with CNC-machined metal parts suggests a reduced number of molding cycles it can withstand, necessitating further research efforts. Addressing this challenge underscores the need for future studies to enhance the mechanical properties of additive-manufactured molds for expanded applicability of AM techniques in the field of rapid tooling used for mold production. The findings of this work present promising cost and energy-saving possibilities through the adoption of AM techniques, providing broader implications for sustainability and circular economy practices.
Efficient Cutting Tool Wear Segmentation Based on Segment Anything Model
Authors: Li Zongshuo , Huo Ding , Meurer Markus , Bergs Thomas
Published: August 2024

Tool wear conditions impact the surface quality of the work-piece and its final geometric precision. In this research, we propose an efficient tool wear segmentation approach based on Segment Anything Model, which integrates U-Net as an automated prompt generator to streamline the processes of tool wear detection. Our evaluation covered three Point-of-Interest generation methods and further investigated the effects of variations in training dataset sizes and U-Net training intensities on resultant wear segmentation outcomes. The results consistently highlight our approach’s advantage over U-Net, emphasizing its ability to achieve accurate wear segmentation even with limited training datasets. This feature underscores its potential applicability in industrial scenarios where datasets may be limited.
Robust Layer Time Optimization for Large Scale Additive Manufacturing
Authors: Liu Lu , Jo Eonyeon , Vaidya Uday , Ozcan Soydan , Kim Seokpum , Ju Feng
Published: August 2024

In the realm of large-scale additive manufacturing, the deposition time for each layer, often termed ‘layer time’, plays a pivotal role in shaping the temperature of the layer. This, in turn, has a profound impact on the overall quality and performance of the manufactured product. Hence, the optimization and precise control of layer time emerge as critical challenges. Striking a balance is essential because both excessively high and low layer temperatures can adversely affect the manufacturing process. Traditional layer time optimization models typically introduce constraints on upper and lower temperature limits. However, the imposition of strict, hard constraints on these temperature bounds may lead to infeasible solutions, depending on factors like geometric design, material properties, and size. In response to these challenges, our study introduces a novel layer time control model that incorporates chance constraints, also known as soft constraints. These chance constraints offer a higher degree of flexibility, enhancing the robustness of the control approach. Our proposed model is validated through comprehensive case studies, demonstrating notable improvements in efficiency and feasibility.
Pyramid Learning Based Part-to-Part Consistency Analysis in Laser Powder Bed Fusion
Authors: Ziad Erfan , Ju Feng , Yang Zhuo , Lu Yan
Published: August 2024

With the rapid growth of the manufacturing industry, laser-based metal additive manufacturing, such as laser powder bed fusion, has the potential to usher in a revolution. However, its widespread adoption is contingent on the resolution of several challenges. A significant challenge is the uncertainty associated with part consistency when standardized materials are used in additive manufacturing processes. To ensure the quality and reproducibility of AM parts, it is essential to ensure that consistency is maintained. This study delves into an assessment of part-to-part consistency, leveraging a Pyramid learning-based technique that utilizes X-ray computed tomography (XCT) images for four nominally identical parts. Employing machine learning, this approach adopts a hierarchical feature system to enhance model performance. Pyramid Learning not only improves the accuracy of part-to-part consistency scanning but also reduces noise, bolstering overall robustness. The findings showcased the efficacy of pyramid learning in enhancing performance metrics when sufficient detail is present. It also provides guidance on locating defects and deformations for the AM parts.
Material Extrusion Infill Strength Under Different Toolpaths
Authors: Clemon Lee , Edwards Rhys , Rizvi Danial
Published: August 2024

Additive manufacturing continues to change many aspects of the manufacturing industry. Although widely implemented in industry for the design and prototype stages of product development, printing speed is the critical factor that prevents the technology from being implemented in medium and large-scale production environments. Recent work developed a novel algorithm using greedy search to reduce extrusionless travel and thus reduces the total print time. The greedy algorithm reorders contour deposition between the slicing and printing processes. The impacts of this reordering of printed line segments is expected to impact mechanical properties in the fabricated parts by affecting the cooling time between layers in different regions differentially. This work evaluates the effect of these toolpath changes on the mechanical properties of 3D printed parts. The new toolpath is compared to a standard toolpath generated from Cura. Of keen interest in additive manufacturing is that of lattice structures for lightweight and strength optimized components. We test three lattice structures under default and improved deposition plans using the same hardware and material. In a lattice structure, defects in individual lattices has a more pronouced impact on macrostructural properties, thus the mechanical properties of lattices fabricated using this local search ordering is tested. We find the local search algorithm, in addition to generating up to 21% quicker prints with 66% less wasted motion, also increases absorbed energy in compression for some structures and has little or no impact on peak force.
Brief Paper: Long-Range Mass Transport Mechanisms in Solid State Sintering for Additive Manufacturing
Authors: Cruze Xavier Hebol D. , Gan Zhengtao
Published: August 2024

Recent advancements in additive manufacturing (AM) such as binder jetting, vat photopolymerization and direct ink writing have made it possible to fabricate complex ceramic and metal structures ranging from simple geometry to complex lattice structures. The postprocessing step of sintering is crucial across numerous AM processes to attain the targeted mechanical properties and achieve precise resolution of the final geometry. Incorrect sintering process parameters and sintering schedule can lead to various defects within the sintered part such as shape distortion and high porosity which essentially lead to damage. Recent studies have shown that nonhomogeneous temperature in the green body arising from non-uniform heating and high temperature ramping is the main contributing factor in causing shape distortion and subsequent cracking. According to more studies, temperature gradients activate long-range mass transport mechanisms such as particle squeezing and biased diffusion which accumulate in the grain-scale and contribute to shape distortion of the printed part in the part-scale. Hence, it is of great interest to explore the mechanisms underlying shape distortion because of its potential in creating models for accurate prediction. Such models would allow control of the degree of distortion of parts to either preserve the initial shape or for applications in 4D printing, which will allow parts to change shape in response to external stimuli.

To investigate the long-range mass transport mechanisms at the grain scale, a mesoscopic approach using phase-field modelling is applied in this study because of its ability to handle grain boundaries, grain morphology and incorporate mass diffusion mechanisms involved in the sintering process. The long-range mass transport mechanisms are studied by solving the Cahn-Hillard and Allen-Cahn Equations with rigid body motion for the sintering of particles in a representative volume element (RVE) of a part-scale geometry exposed to an initial temperature gradient. The mobility coefficients are assumed to be deformed Arrhenius type functions of temperature to capture the effects of sintering activation and temperature. The degree of distortion of RVEs will be investigated for initial temperature gradients and temperature ramp rate to study the mechanisms underlying shape distortion that reflect in the part-scale. This study aims to examine the influence of long-range mass transport under different particle configurations to provide further insights into the mechanisms of shape distortion in the sintering process, whether particle squeezing or biased diffusion or both is the mode of long-range mass transport laying foundations for the development of better predictions and design of the sintering process for digital twins.
Simulating Current Profiles in Fused Deposition Modeling
Authors: Aziz Md Shahriar , Purdy Gregory
Published: August 2024

Integration of Additive Manufacturing (AM) into connected systems increases the chances of potential cyber-physical attacks. One way to detect potential cyber-physical attacks is using side channels such as current, sound, or vibration. This approach involves comparing a process-driven signal to a known reference signal. Obtaining a reference signal for each different print can be time-consuming. This work aims to simulate the current delivered to each printer motor using G-code in a Fused Deposition Modeling (FDM) process. First, the relationship between motors and the current signal is studied. Second, the code segments responsible for the signal are identified, and the relevant information acquired is recorded. Finally, the information obtained in the previous stages are combined to generate the simulated signal. Case studies conducted to simulate the current signal demonstrate that the proposed method outputs a signal that closely resembles a real-life signature. The simulated signal conveys similar information about the printed object using the FDM process.
Dimensional Integrity of 4D Printed Parts: A Multi-Cycle Analysis for Quality Assurance
Authors: Valenzuela Lucia , Han Muyue , Li Lin
Published: August 2024

4D printing is a promising additive manufacturing technology due to its capability to prolong service life and enhance the life cycle performance of manufactured structures. This study analyzes the dimensional integrity of 4D printed parts along several programming and recovery cycles; specifically, this investigation comprises a comparative study to characterize the dimensional variations along the length, width, and height, where the effects of different stimulus conditions, such as temperature and time, are also investigated. An in-depth analysis using the design of experiments technique was also performed to investigate further the impact of different factors on the cyclical dimensional integrity. The results suggest that temperature is a critical factor leading to material-dependent changes in the length and width, with the highest temperatures leading to thermal expansion since the initial programming and recovery cycle. Holding time changes were found to have a minor impact on the dimensions, while variations in deformation angle did not affect the results significantly. The outcome also suggests that mechanical loading and constant exposure to moisture could degrade the polymer, creating stress-induced mechanical fatigue or swelling changes, which consequently affects the samples’ integrity after repeated exposure.
A Review of Contemporary Approaches to Identify Influential Parameters on Surface Roughness in Incremental Sheet Forming
Authors: Rafat Md Tahjib , Haapala Karl R. , Fan Zhaoyan
Published: August 2024

Incremental sheet forming (ISF) is a versatile and innovative sheet metal forming technology which can readily produce asymmetrical, symmetrical, and complex geometric parts using a simple machine tool. However, limitations of the process include surface roughness, formability, and process throughput. Surface finish influences the quality, functionality, and aesthetics of the formed parts. Thus, ISF should be able to achieve an obligatory level of surface quality to be considered a competitive solution relative to other manufacturing processes. A variety of forming parameters have been investigated as primary causes of surface roughness variation in ISF. As a result, several forming parameters have been reported to be more influential to surface roughness than others. Further, surface roughness may differ based on a combination of parameter values while forming a workpiece rather than a single parameter alone. These influential forming parameters also have differing effects on surface roughness based on the workpiece material and the final part geometry. In addition, ISF can be divided into various categories, such as single-point incremental sheet forming (SPIF), two-point incremental sheet forming (TPIF) and multi-stage incremental sheet forming. The same set of forming parameters applied to these processes can yield a range of surface roughness values. Researchers have attempted different approaches to measure, analyze, and optimize the parameters that influence surface quality in ISF processes. However, the findings of these studies are sometimes contradictory. Most approaches consider a few forming parameters as variables in order to sort out the relationships between surface roughness and the selected forming parameters, while keeping other parameters constant. The forming parameters considered by prior research also vary from approach to approach, depending on researcher preferences and their perspective of influential ISF parameters on surface roughness. As the research of measuring, analyzing, and optimizing forming parameters to obtain desired surface quality is in the early stages of development, strong evidence on which researchers can agree is limited and lacks coherence. No prior reports summarizing the approaches used by researchers have been found in the literature, nor have comparative analyses been conducted to evaluate efficacy. A synthesis of the extant literature is provided herein to highlight the various approaches and practices that have been employed to study the effect of ISF process parameters on surface roughness. With the help of previous research findings, the outcomes reveal how various approaches compare and differ in terms of the identified influential forming parameters and offer potential directions for future study.