Efficient toolpath planning for collaborative material extrusion machines

Purpose: 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

Optimization with artificial intelligence in additive manufacturing: a systematic review

In 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

A design of experiment approach to 3D-printed mouthpieces sound analysis

Nowadays 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

Conformal 3D Material Extrusion Additive Manufacturing for Large Moulds

Industrial engineering applications often require manufacturing large components in composite materials to obtain light structures; however, moulds are expensive, especially when manufacturing a limited batch of parts. On the one hand, when traditional approaches are carried out, moulds are milled from large slabs or laminated with composite materials on a model of the part to produce. In this case, the realisation of a mould leads to adding time-consuming operations to the manufacturing process. On the other hand, if a fully additively manufactured approach is chosen, the manufacturing time increases exponentially and does not match the market’s requirements. This research proposes a methodology to improve the production efficiency of large moulds using a hybrid technology by combining additive manufacturing and milling tools. A block of soft material such as foam is milled, and then the printing head of an additive manufacturing machine deposits several layers of plastic material or modelling clay using conformal three-dimensional paths. Finally, the mill can polish the surface, thus obtaining a mould of large dimensions quickly, with reduced cost and without needing trained personnel and handcraft polishing. A software tool has been developed to modify the G-code read by an additive manufacturing machine to obtain material deposition over the soft mould. The authors forced conventional machining instructions to match those of an AM machine. Thus, additive deposition of new material uses 3D conformal trajectories typical of CNC machines. Consequently, communication between two very different instruments using the same language is possible. At first, the code was tested on a modified Fused Filament Fabrication machine whose firmware has been adapted to manage a milling tool and a printing head. Then, the software was tested on a large machine suitable for producing moulds for the large parts typical of marine and aerospace engineering. The research demonstrates that AM technologies can integrate conventional machinery to support the composite materials industry when large parts are required

Structural Analysis of Voxel-Based Lattices Using 1D Approach

Lightweight 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

Evaluation of 3D printed mouthpieces for musical instruments

Purpose: 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

Proposal of a standard for 2D representation of bio-inspired lightweight lattice structures in drawings

The 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 FreeCad\u2122 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

Methodology for Image Analysis in Airborne Search and Rescue Operations

Nowadays, 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

Surface smoothing for topological optimized 3D models

The 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\u2019s 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\u2019s intervention is not required to guide the procedure to get proper results

FDM Printing Time Prediction Tuning Through a DOE Approach

Additive Manufacturing is widely applied in aerospace, automotive and marine engineering. Indeed, large-scale components are often required in these applications, such as for non-structural parts of aircraft, spare parts or small lots of cars or marine components. Fused Deposition Modelling is one of the Additive Manufacturing processes used to affordably convert digital models into mockups, prototypes, and functional parts: a slicing software converts the object’s digital model into a list of instructions for the machine. However, commercial slicing software packages often fail to accurately estimate the time required to produce models, especially when their size is significant: the errors could be up to several hours, which cannot be adequate in a real-life industrial context where production must be scheduled in a precise way. This manuscript compares the build time estimation of several commercial slicing software considering a real-life part. Furthermore, the evaluation of the manufacturing setting mainly affects the error in estimating the build time achieved through a Design of Experiment approach. The more time-impacting printing parameters have been detected, allowing fine helpful tuning to increase the accuracy of the build time in commercial slicing software. A case study included in the manuscript supports the analyses. Proper setting of the commercial slicing software can significantly improve the accuracy of the printing time