bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficient Cutting Tool Wear Segmentation Based on Segment Anything Model
Authors: Li Zongshuo , Huo Ding , Meurer Markus , Bergs Thomas 
Published: August 2024

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.
The Impact of the Printed Part Size on the Shrinkage and Density in Binder Jetting Additive Manufacturing of Ceramics Powder
Authors: Obeidat Suleiman , Smith Chris , Basith Iftekhar , Dakeev Ulan , Ma Junkun 
Published: August 2024

Abstract
The additive manufacturing method discussed in this work is the binder jetting additive manufacturing process where a liquid-based binder is deposited on the powder bed to fabricate the part layer by layer. Binder Jetting 3D printing is capable of printing different types of materials such as metals, ceramics, and polymers. While the selective laser melting process can be used to make metal parts, the same process can’t be used to make ceramic parts. For this reason, in terms of 3D printing, the binder jetting additive manufacturing process is ideal for ceramic parts. In this work, ceramic particles are used to investigate the impact of the part size on the shrinkage percentage, and the apparent and relative density of the printed part. Four different shapes including cylinders, rectangular blocks, cones, and spheres of different sizes are printed at 100 %, 75%, core saturation limit at 0 seconds, and 10 seconds delay using a binder jetting 3D printer at 0.2 mm layer thickness. We print multiple samples of these different shapes. After the fabrication process, the parts are left for 6 - hours in the printer and then moved carefully to the de-powdering station where the parts are dried, and the binder is cured at 35°C for 6–8 hours to prevent any cracks during the sintering process. This process is followed by the sintering process to improve the density of the part fabricated and to make it stronger. The shrinkage percentage and the apparent and relative density of the printed parts are calculated after the sintering process for each geometry at two different sizes. A density and shrinkage comparison is conducted for the four shapes at two different sizes for the green and sintered parts at different printing parameters We use ceramic powder of particle size range 50–200 μm to print the parts. The ceramics powders consist of 50% crystalline silica (quartz), 25% kaolinite, and 25% of potassium feldspar. The binder consists of 8% Diethylene glycol, 2% Surfactant, and 90% water. It is found that the big samples at 100 % and 75 % core saturation with the number of prints one at different time delays of zero and 10 seconds, provide 11–18 % higher relative density, for cone samples, compared to the small samples. The big samples at 100 % core saturation provide bigger shrinkage than the small samples at 0 (about 27 % for the cone samples) and 10 seconds delay (17 % for the cone samples).
Multi-Facility Location Optimization to Analyze the Economics of Plastic Recycling Systems: A Study Integrating K-Means and Monte Carlo Methods
Authors: Nandimandalam Hariteja , Mendis Gamini P. 
Published: August 2024

Abstract
Plastic waste recycling is essential for sustainable practices, but it suffers from inefficiency due to a lack of a secondary market and difficulties in separating the plastic resins. Plastic recycling is improving substantially as technology (especially sensing technology) advances and the need for post-consumer plastic resin grows. The economics and logistics of plastic recycling plants, on the other hand, are uncertain, due to feedstock availability, logistics, and market price availability. Furthermore, pyrolysis and chemical recycling facilities are entering the market for post-consumer plastics, which has the potential to change the economics of the system and create additional demand for clean streams of waste plastic. This study combines plastic recycling facility logistics (sorting technology) to examine economic viability and determine how transportation and facility size (i.e., clusters) affect profitability under a variety of scenarios.
To achieve these objectives, the study leverages available data on the number of post-consumer plastics suppliers to locate central sorting locations by employing a K-means clustering method. This work aims to identify the optimum number of recycling facilities and their locations in the United States to make a recycling system economically viable. Monte Carlo simulations are performed to evaluate the effects of the price of plastic resin, plastic composition, the end-of-life fate of different resins, and the number of centroids on the profitability of the recycling facility. Depending on the scenario, the profit generated by recycling facilities can vary from −$197 million to $112 million.
Key factors such as the sale price of resin in the secondary recycling market, transportation type and cost, and whether polypropylene is sent to secondary recycling or pyrolysis facilities are critical variables influencing the profitability of the recycling system. The plastic composition and fate of polypropylene (recycling vs pyrolysis) strongly affect the profitability of the recycling facility. The amount of HDPE and PET, both resins with existing recycling markets are key factors for economic viability. The introduction of additional recycling centers (or clusters) results in a substantial reduction in transportation costs. However, the creation of additional recycling centers results in increased operating and capital costs per ton of plastic waste processed. The optimal number of facilities is then driven by the tradeoff between capital costs and the total transportation distance and mode of transportation used. It was identified that shipping waste plastic via train dramatically decreased transportation costs over conventional semi-truck transportation. This work is aimed at identifying potential opportunities for better plastic end of life fates and identifying the circumstances in which the recycling facilities will be viable over the long term.
Reducing Warping in ABS 3D Printed Parts Through Infill Modification
Authors: Shen Weijun , Veeramani Dharmaraj , Qin Hantang 
Published: August 2024

Abstract
Additive Manufacturing (AM), or 3D printing, has transformed traditional manufacturing by allowing the layer-by-layer construction of objects from digital models. This study addresses warping in Acrylonitrile Butadiene Styrene (ABS) Fused Filament Fabrication (FFF) by proposing infill structure modification. Using CR-ABS filament and a Prusa i3 MK3+ printer, we investigate three geometric shapes — strip, square, and leaf — via advanced 3D scanning for surface curvature analysis. By intentionally altering infill patterns, we analyze warping mechanisms such as non-uniform shrinkage and anisotropic thermal stress. Auto-leveling and curvature calculations evaluate the impact of modified infill strategies on warpage. Results demonstrate significant reductions in surface warpage, with modified infill structures surpassing default patterns. Improved dimensional stability is evidenced by average and maximum surface deviations alongside curvature measurements. This research offers a robust approach, highlighting the potential of infill modification to enhance reliability and stability in 3D-printed parts. While limited to ABS material and specific shapes, this study marks a substantial advancement in ABS 3D printing precision. The proposed methodology not only effectively reduces warpage but also holds promise for diverse applications across materials and printing technologies. Further research is urged to explore scalability and broader implications, which are essential for a comprehensive understanding and application of infill structure modification in 3D printing. In addressing warping challenges, this study contributes to the evolution of modern manufacturing processes, underscoring the importance of advancing warpage reduction strategies for realizing 3D printing’s full potential.