1,720,974 research outputs found
Efficient toolpath planning for collaborative material extrusion machines
Full text linkPurpose: Timing constraints affect the manufacturing of traditional large-scale components through the material extrusion technique. Thus, researchers are exploring using many independent and collaborative heads that may work on the same part simultaneously while still producing an appealing final product. The purpose of this paper is to propose a simple and repeatable approach for toolpath planning for gantry-based n independent extrusion heads with effective collision avoidance management. Design/methodology/approach: This research presents an original toolpath planner based on existing slicing software and the traditional structure of G-code files. While the computationally demanding component subdivision task is assigned to computer-aided design and slicing software to build a standard G-code, the proposed algorithm scans the conventional toolpath data file, quickly isolates the instructions of a single extruder and inserts brief pauses between the instructions if the non-priority extruder conflicts with the priority one. Findings: The methodology is validated on two real-life industrial large-scale components using architectures with two and four extruders. The case studies demonstrate the method's effectiveness, reducing printing time considerably without affecting the part quality. A static priority strategy is implemented, where one extruder gets priority over the other using a cascade process. The results of this paper demonstrate that different priority strategies reflect on the printing efficiency by a factor equal to the number of extrusion heads. Originality/value: To the best of the authors’ knowledge, this is the first study to produce an original methodology to efficiently plan the extrusion heads' trajectories for a collaborative material extrusion architecture
Structural Analysis of Voxel-Based Lattices Using 1D Approach
Full text linkLightweight bioinspired structures are extremely interesting in industrial applications for their known advantages, especially when Additive Manufacturing technologies are used. Lattices are composed of axial elements called ligaments: several unit cells are repeated in three directions to form bodies. However, their inherent structure complexity leads to several problems when lattices need to be designed or numerically simulated. The computational power needed to capture the overall component is extremely high. For this reason, some alternative methodologies called homogenization methods were developed in the literature. However, following these approaches, the designers do not have a local visual overview of the lattice behavior, especially at the ligament level. For this reason, an alternative mono-dimensional (1D) modeling approach, called lattice-to-1D is proposed in this work. This method approximates the ligament element with its beam axis, uses the real material characteristics, and gives the cross-sectional information directly to the solver. Several linear elastic simulations, involving both stretching and bending dominated unit cells, are performed to compare this approach with other alternatives in the literature. The results show a comparable agreement of the 1D simulations compared with homogenization methods for real tridimensional (3D) objects, with a dramatic decrease of computational power needed for a 3D analysis of the whole body
Investigating slicing parameters in FFF for time and mass estimation: a statistical approach
No full textFused filament fabrication (FFF) is one of the additive manufacturing methods used to transform digital models cost-effectively into prototypes, mockups, and functional parts for industrial customized applications, mainly aerospace, automotive, and biomedicine. In an industrial standard design-to-manufacturing workflow, the slicing software is responsible for translating the digital model of the object into a set of instructions for the FFF machine. However, setting printing profiles for FFF machines is a painstaking process in the operative environment due to the long time needed to carry out the required tests and tuning phases. Moreover, the scientific literature needs to include the influence of digital model topologies on the more influencing manufacturing parameters. Thus, this paper proposes a reproducible methodology to understand how the choice of the manufacturing parameters affects the time estimation and mass of the production process. Through a half-factorial Design of Experiment approach, the manufacturing parameters that most significantly affect the time required are identified; furthermore, the methodology aims to suggest adjustments to enhance the accuracy of build time predictions in commercial slicing software. Several case studies in the paper provide empirical support for the findings, highlighting that proper configuration of commercial slicing software can substantially enhance manufacturing process accuracy. In particular, the results show that the best configuration cannot be chosen a priori since the topology of the component affects the optimal choice of parameters. Moreover, a rigorous statistical approach allows for producing functional components with excellent printing times and optimal material consumption, compared to a more random approach that may lead to non-functional components. The methodology suits the industrial environment where processes must be set up quickly with satisfying results
Proposal of a standard for 2D representation of bio-inspired lightweight lattice structures in drawings
Full text linkThe interest of industrial companies for the Additive Manufacturing (AM) technology is growing year after year due to its capability of producing components with complex shapes that fit industrial engineering necessities better than traditionally manufactured parts. However, conventional Computer-Aided Design (CAD) software are often limited for the design and representation of complex geometries, especially when dealing with lattice structures: these are bio-inspired structures composed of repeated small elements, called struts, which are combined to shape a unit cell that is repeated across a domain. This design method generates a lightweight but stiff component. The scope of this work is to analyse the problem of the lattice structures representation in 2 D technical drawings and propose some contributions to support the development of Standards for their 2 D representation. This work is focused on the proposal of rules useful to represent such hierarchic structures. Python language and the open-source software FreeCadTM are used as a software platform to evaluate the suitability and usability of the proposed representation standard. This is based on simplified symbols to describe complex lattice structures instead of representing all the elements which constitute the lattice. The standard is thought to be used in technical 2 D drawings where assemblies are represented and lattice components are used (e.g. parts assembly, maintenance, parts catalogues). A case study is included to describe how the proposed standard could be integrated into a 2 D assembly drawing, following technical product documentation production typical workflow
A design of experiment approach to 3D-printed mouthpieces sound analysis
Full text linkNowadays additive manufacturing is affected by a rapid expansion of possible applications. It is defined as a set of technologies that allow the production of components from 3D digital models in a short time by adding material layer by layer. It shows enormous potential to support wind musical instruments manufacturing because the design of complex shapes could produce unexplored and unconventional sounds, together with external customization capabilities. The change in the production process, material and shape could affect the resulting sound. This work aims to compare the music performances of 3D-printed trombone mouthpieces using both Fused Deposition Modelling and Stereolithography techniques, compared to the commercial brass one. The quantitative comparison is made applying a Design of Experiment methodology, to detect the main additive manufacturing parameters that affect the sound quality. Digital audio processing techniques, such as spectral analysis, cross-correlation and psychoacoustic analysis in terms of loudness, roughness and fluctuation strength have been applied to evaluate sounds. The methodology herein applied could be used as a standard for future studies on additively manufactured musical instruments
Voxel-based evolutionary topological optimization of connected structures for natural frequency optimization
Full text linkThe topology optimization methodology is widely utilized in industrial engineering for designing lightweight and efficient components. In this framework, considering natural frequencies is crucial for adequately designing components and structures exposed to dynamic loads, as in aerospace or automotive applications. The scientific community has shown the efficiency of Bi-directional Evolutionary Structural Optimization (BESO), showcasing its ability to converge towards optimal solid-void or bi-material solutions for a wide range of frequency optimization problems in continuum structures. However, these methods show limits when the complexity of the domain volume increases; thus, they are well-suited for academic case studies but may fail when dealing with industrial applications that require more complex shapes. The connectivity of the structures resulting from the optimization also plays a fundamental role in choosing the best optimization approach, as some available commercial and open-source codes nowadays return unfeasible sparse structures. An improved voxel-based BESO algorithm has been developed in this work to cope with current limits in lightweight structure optimization. A significant case study has been developed to evaluate the performances of the new methodology and compare it with existing algorithms. In contrast to previous studies, the method we developed guarantees that the final structure respects constraints on the initial design volume and that the structure’s connection is preserved, thus enabling the manufacturing of the component with Additive Manufacturing technologies. The proposed approach can be complemented by smoothing algorithms to obtain a structure with externally appealing surfaces
Optimization with artificial intelligence in additive manufacturing: a systematic review
Full text linkIn situations requiring high levels of customization and limited production volumes, additive manufacturing (AM) is a frequently utilized technique with several benefits. To properly configure all the parameters required to produce final goods of the utmost quality, AM calls for qualified designers and experienced operators. This research demonstrates how, in this scenario, artificial intelligence (AI) could significantly enable designers and operators to enhance additive manufacturing. Thus, 48 papers have been selected from the comprehensive collection of research using a systematic literature review to assess the possibilities that AI may bring to AM. This review aims to better understand the current state of AI methodologies that can be applied to optimize AM technologies and the potential future developments and applications of AI algorithms in AM. Through a detailed discussion, it emerges that AI might increase the efficiency of the procedures associated with AM, from simulation optimization to in-process monitoring
Evaluation of 3D printed mouthpieces for musical instruments
Full text linkPurpose: The purpose of this study is the evaluation of advantages and criticalities related to the application of addtive manufacturing (AM) to the production of parts for musical instruments. A comparison between traditional manufacturing and AM based on different aspects is carried out. Design/methodology/approach: A set of mouthpieces produced through different AM techniques has been designed, manufactured and evaluated using an end-user satisfaction-oriented approach. A musician has been tasked to play the same classical music piece with different mouthpieces, and the sound has been recorded in a recording studio. The mouthpiece and sound characteristics have been evaluated in a structured methodology. Findings: The quality of the sound and comfort of 3D printed mouthpieces can be similar to the traditional ones provided that an accurate design and proper materials and technologies are adopted. When personalization and economic issues are considered, AM is superior to mouthpieces produced by traditional techniques. Research limitations/implications: In this research, a mouthpiece for trombone has been investigated. However, a wider analysis where several musical instruments and related parts are evaluated could provide more data. Practical implications: The production of mouthpieces with AM techniques is suggested owing to the advantages which can be tackled in terms of customization, manufacturing cost and time reduction. Originality/value: This research is carried out using a multidisciplinary approach where several data have been considered to evaluate the end user satisfaction of 3D printed mouthpieces
Surface smoothing for topological optimized 3D models
Full text linkThe topology optimization methodology is widely applied in industrial engineering to design lightweight and efficient components. Despite that, many techniques based on structural optimization return a digital model that is far from being directly manufactured, mainly because of surface noise given by spikes and peaks on the component. For this reason, mesh post-processing is needed. Surface smoothing is one of the numerical procedures that can be applied to a triangulated mesh file to return a more appealing geometry. In literature, there are many smoothing algorithms available, but especially those based on the modification of vertex position suffer from high mesh shrinkage and loss of important geometry features like holes and surface planarity. For these reasons, an improved vertex-based algorithm based on Vollmer’s surface smoothing has been developed and introduced in this work along with two case studies included to evaluate its performances compared with existent algorithms. The innovative approach herein developed contains some sub-routines to mitigate the issues of common algorithms, and confirms to be efficient and useful in a real-life industrial context. Thanks to the developed functions able to recognize the geometry feature to be frozen during the smoothing process, the user’s intervention is not required to guide the procedure to get proper results
Methodology for Image Analysis in Airborne Search and Rescue Operations
No full textNowadays, Search and Rescue operations can be performed using manned or unmanned Aerial Vehicles. In this latter case, compact cameras are mounted onboard and a bird’s eye view is available to find the missing person. However, the analysis of the video frames can be very challenging and dull for the operators. In this context, the use of graphical methodologies can boost the searching operations and improve the process. In this study, a methodology based on the object detector Yolov5 is introduced: the performances in detecting small objects such as persons in aerial images are evaluated. These algorithms implement shallow layers of the feature extractor to increase the spatial-rich features and help the detector to find small objects. Finally, detection algorithms are tested using a video simulating a scenario for Search and Rescue operations. The filtering of frames containing false positives, is carried out using a classical graphical tool such as the Hamming distance
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