1,720,964 research outputs found
In Reference to Real‐World Adverse Events After Type 2 Biologic use in Chronic Rhinosinusitis with Nasal Polyps
Full text linkSurrogate-based optimization of FFF build orientation for enhanced tensile strength, flatness, and surface roughness
No full textThe performance of parts produced using fused filament fabrication, a widely adopted additive manufacturing technology, is significantly influenced by build orientation. While previous studies have explored the effects of part orientation on mechanical and geometrical properties individually, their simultaneous interactions remain underexplored. This study addresses this gap by investigating the combined impact of build orientation, defined by three angles (
), on tensile strength, flatness deviation, and surface roughness of PET-G (Polyethylene Terephthalate Glycol) specimens. The methodology consists of two stages: (i) an experimental campaign to establish the relationships between orientation angles and the output variables, and (ii) a surrogate-based optimization approach, employing the weighted-sum method and genetic algorithm to identify configurations that achieve optimal compromises between mechanical and geometrical properties. Results demonstrate a strong dependency of all outputs on the orientation angles, particularly the out-of-plane rotation, and a negative correlation between tensile strength and geometrical quality metrics. Optimal performance is confined to specific regions of the input space, emphasizing the importance of a precise orientation control. A graphical approach, inspired by Voronoi-like regions, illustrates the interdependencies among outputs and maps achievable compromises in the output space. These optimal zones correspond to limited regions in the input space. Moving away from these configurations results in a rapid decline in performance, underscoring the sensitivity of the process to build orientation and the need for tightly defined parameters to ensure high-quality parts
Simultaneous impact of build orientation on mechanical properties, geometrical measurements and surface roughness in material extrusion manufacturing
No full textPurpose
This paper aims to investigate how the build orientation simultaneously affects the tensile properties, geometrical measurements and surface roughness in material extrusion (MEX) produced parts.
Design/methodology/approach
An extensive experimental campaign was designed and carried out to elucidate the relationship between the rotation angles (input), defining the part orientation within the build volume, and the (output) variables measured by using 3D models reconstruction, roughness tester and tensile testing machine. Response surface methodology is used to capture the trend of each output relative to the input, while principal component analysis is used to identify relationships among outputs, providing a holistic understanding of how build orientation simultaneously influences mechanical properties, geometrical measurements and surface characteristics.
Findings
The study reveals that build orientation significantly affects nearly all output variables, with a pronounced dependency on the out-of-plane rotation angle. A key finding is the inverse correlation between mechanical strength and both geometrical measurements and surface roughness. This indicates that optimizing build orientation can enhance mechanical strength while minimizing geometrical defects.
Originality/value
This research, a newer addition to the existing literature, contributes to the field of additive manufacturing (AM) by offering an innovative analysis of the interaction between mechanical properties, geometric precision and surface roughness in relation to build orientation. It enhances the understanding of MEX processes and provides valuable insights into optimizing build orientation, thereby improving the competitiveness of AM over traditional production methods
On the Prediction of Mechanical and Aesthetical Behavior of AM Specimens Through Machine Learning: A Preliminary Study
No full textComplexity-driven product design: part 1—methodological framework and geometrical complexity index
No full textModern industries are experiencing radical changes due to the introduction of high technological innovations. In this context, even more highly complex and customized products are required, increasing the need of tending towards the concept of complexity for free. In addition, new products are conceived with the circular economy in mind, considering possible multi life-cycle at the early design stage to reduce time and costs while ensuring high quality standards. To evaluate the overall product complexity, this research combines geometrical, manufacturing, assembly, and disassembly complexity features, typically treated separately in the literature. The research is divided into two parts and proposes a novel methodological framework for assessing product complexity with an overall view, integrating many aspects of product life cycle. The framework aims to create a rank of product configurations, on the base of complexity. Making complexity assessment procedures objective is essential to effectively support decision-making processes, especially when introducing advanced manufacturing technologies such as Additive Manufacturing (AM). Additionally, it is necessary to know the complexity of the individual components before the overall assembly. This paper deals with the first part of the research, proposing the aforementioned novel methodological framework, with a great focus on geometrical complexity. A geometrical complexity index is defined through experimental and numerical surveys, involving CAD modeling experts and considering numerous metrics found in the technical literature. The proposed methodological framework and the geometrical complexity metric can provide useful tools for businesses looking to evaluate their product complexity and identify areas for improvement
Real-Time Analysis of Geometric Variations in AM Parts Across Different Printing Orientations Using Reduced-Order Modelling
No full textThe Simultaneous Effect of FFF Build Orientation on Tensile Strength, Flatness and Roughness
No full textBuild orientation significantly influences the overall performance of products realized with Fused Filament Fabrication (FFF) - based Additive Manufacturing (AM) technology. Based on an extensive experimental campaign, this study aims to investigate the simultaneous effect of build orientation on tensile strength, flatness, and surface roughness of PET-G (PolyEthylene Terephtalate Glycol) samples realized via FFF. A thorough analysis was conducted to clarify the connection between the rotation angles, which define the part orientation within the build volume, and the output variables. The results indicated a significant dependency of all the measured outputs on the out-of-plane rotation angle. The printing process tends to generate specimens with tensile strength negatively correlated to flatness and roughness, offering precious cues toward optimizing build orientation to improve the overall performance of FFF parts
Towards real-time physics-based variation simulation of assembly systems with compliant sheet-metal parts based on reduced-order models
Full text linkVariation Simulation (VS) allows early validation and certification of the assembly process before parts are built. State-of-the-art VS models of assembly systems with compliant sheet-metal parts are based on Finite Element Method (FEM) integrated with statistical approaches (i.e., Monte Carlo simulation). A critical technical barrier is the intense computational cost. This paper proposes a novel real-time physics-based VS model of assembly systems with compliant sheet-metal parts based on Reduced-Order Model (ROM). Compared to the literature on the topic, this study reports the first application of a ROM, developed for VS by using both intrusive and non-intrusive techniques. The capability of the proposed method is illustrated in a case study concerning the assembly process of the vertical stabiliser for commercial aircrafts. Results have shown that the accuracy of ROM (based on proper orthogonal decomposition) depends on the sampling strategy as well as on the number of reduced modes. Whilst a large CPU time reduction by several orders of magnitude is achievable by non-intrusive techniques (based on radial basis functions for interpolation), intrusive models provide more accurate results compared to the full-order models
The Effects of Mepolizumab on CRSwNP: Real-Life Evidence
Full text linkBackground: This study aims to evaluate the efficacy and safety of mepolizumab in the treatment of severe uncontrolled CRSwNP with or without comorbid asthma in a real-life setting over the first six months of therapy. Methods: A total of 45 patients with nasal polyps with or without comorbid asthma were treated with mepolizumab (100 mg q4w) for 6 months. The following outcomes were assessed before therapy (V0), and after 6 months (V1): endoscopic nasal polyp score (NPS), nasal congestion score (NCS), sinonasal outcome test (SNOT-22), visual analog scale (VAS), nasal flow rate (PNIF), olfactory test (SS-I), and asthma control test (ACT). Blood eosinophil count, oral steroid intake, and rescue surgery were also measured. Results: We found a statistically significant improvement in NPS, NCS, SNOT-22, overall VAS, PNIF, SS-I, and ACT. In addition, we observed a decrease in blood eosinophils count. Mepolizumab was well tolerated, and no patients interrupted the treatment during the follow up. Conclusions: Our real-life study confirmed the efficacy and tolerance of mepolizumab prescribed for CRSwNP with or without asthma. The safety profile of mepolizumab was consistent with previous reports
Crop Growth Analysis Using Automatic Annotations and Transfer Learning in Multi-Date Aerial Images and Ortho-Mosaics
No full textGrowth monitoring of crops is a crucial aspect of precision agriculture, essential for optimal yield prediction and resource allocation. Traditional crop growth monitoring methods are labor-intensive and prone to errors. This study introduces an automated segmentation pipeline utilizing multi-date aerial images and ortho-mosaics to monitor the growth of cauliflower crops (Brassica Oleracea var. Botrytis) using an object-based image analysis approach. The methodology employs YOLOv8, a Grounding Detection Transformer with Improved Denoising Anchor Boxes (DINO), and the Segment Anything Model (SAM) for automatic annotation and segmentation. The YOLOv8 model was trained using aerial image datasets, which then facilitated the training of the Grounded Segment Anything Model framework. This approach generated automatic annotations and segmentation masks, classifying crop rows for temporal monitoring and growth estimation. The study’s findings utilized a multi-modal monitoring approach to highlight the efficiency of this automated system in providing accurate crop growth analysis, promoting informed decision-making in crop management and sustainable agricultural practices. The results indicate consistent and comparable growth patterns between aerial images and ortho-mosaics, with significant periods of rapid expansion and minor fluctuations over time. The results also indicated a correlation between the time and method of observation which paves a future possibility of integration of such techniques aimed at increasing the accuracy in crop growth monitoring based on automatically derived temporal crop row segmentation masks
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