Search results

The purpose of this research is to develop a new slicing scheme for the emerging cooperative three-dimensional (3D) printing platform that has multiple mobile 3D printers working together on one print job.

Because the traditional lay-based slicing scheme does not work for cooperative 3D printing, a chunk-based slicing scheme is proposed to split the print job into chunks so that different mobile printers can print different chunks simultaneously without interfering with each other.

A chunk-based slicer is developed for two mobile 3D printers to work together cooperatively. A simulator environment is developed to validate the developed slicer, which shows the chunk-based slicer working effectively, and demonstrates the promise of cooperative 3D printing.

For simplicity, this research only considered the case of two mobile 3D printers working together. Future research is needed for a slicing and scheduling scheme that can work with thousands of mobile 3D printers.

The research findings in this work demonstrate a new approach to 3D printing. By enabling multiple mobile 3D printers working together, the printing speed can be significantly increased and the printing capability (for multiple materials and multiple components) can be greatly enhanced.

The chunk-based slicing algorithm is critical to the success of cooperative 3D printing, which may enable an autonomous factory equipped with a swarm of autonomous mobile 3D printers and mobile robots for autonomous manufacturing and assembly.

This work presents a new approach to 3D printing. Instead of printing layer by layer, each mobile 3D printer will print one chunk at a time, which provides the much-needed scalability for 3D printing to print large-sized object and increase the printing speed. The chunk-based approach keeps the 3D printing local and avoids the large temperature gradient and associated internal stress as the size of the print increases.

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.

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.

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.

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.

Process parameters in Fused Filament Fabrication (FFF) can affect mechanical and surface properties of printed parts. Numerous studies have reported parametric studies of various materials using full factorial and Taguchi design of experiments (DoEs). However, a comparison between the two are not well-established in literature. The purpose of this study is to compare full factorial and Taguchi DoEs to determine the effects of FFF process parameters on mechanical and surface properties of Nylon 6/66 copolymer. In addition, perform in-depth failure mechanism analysis to understand why the process parameters affect the responses.

A full factorial DoE was used to determine the effects of FFF process parameters, such as infill density, infill pattern, layer height and raster angle on responses, such as compressive strength, impact strength, surface roughness and manufacturing time of Nylon 6/66. Micro-computed tomography was used to analyse the impact test samples before and after impact and scanning electron microscope was used to understand the failure mechanism of infill and top layers. Differential scanning calorimetry (DSC) scans of infill and top layers were then taken to determine if a variation in crystallinity existed in different regions of the build.

Analysis of variance and main effects plots reveal that infill density has the greatest effect on mechanical and surface properties while manufacturing time is most affected by layer height for the polymer used. A 20% reduction in infill increased impact strength by 19% on average, X-ray images of some of the samples before and after impact tests are presented to understand the reason behind the difference. Moreover, DSC revealed a difference in the degree of crystallinity between the infill and top layers for 80% infill density samples. In addition, Taguchi DoE is realized to be a more efficient technique to determine optimum process parameters for responses that vary linearly as it reduces experimental effort significantly while providing mostly accurate results.

To the author’s knowledge, no published paper has reported a comparison between predictive DoE method with full factorial DoE to verify their accuracy in determining the effects of FFF process parameters on properties of printed parts. Also, a theory was developed based on DSC results that as the infill is printed faster, it cools slowly compared to the top layers, and hence the infill is in a less crystalline state when compared to the top layers. This increased the ductility of the infill (of 80% infill samples) and thus improved impact absorption.