An official website of the United States government
Additive manufacturing (AM) has the potential to improve productivity especially processing time, cost and surface roughness. In similar lines, part separation for assembly-based design in additive manufacturing can help in improving productivity. This paper discusses an optimization technique for part separation in assembly based part design in additive manufacturing. The technique improves productivity by decreasing the processing time of printed parts, which is the sum of the build time and the assembly time. The technique uses optimal cutting planes for part separation that has distinct advantages compared to random cutting planes. The work discusses a Genetic Algorithm (GA) technique for part separation using planar cuts. The optimization technique provides the optimal number of parts for assembly and their corresponding build orientations for the minimum processing time. Three examples have been provided to demonstrate the application of the proposed method. Finally, the results from two examples are compared to the already established hill climbing optimization method for part separation.
more »
« less
AddLat2D the 2D Lattice Generator
This work addresses the challenges of acquiring additive manufacturing data, given the complexities and design possibilities of such structures. Researchers in additive manufacturing struggle with scarcity and unsuitability of 2D datasets which pose further difficulties. To overcome these concerns, this research presents an application, AddLat2D, for generating 2D lattice structure datasets tailored to user specifications. Building upon a previous version of the application (Baldwin et al., 2023, 2022), this work highlights our development and usage of AddLat2D to generate datasets that have custom image size and pixel intensity values.
more »
« less
- Award ID(s):
- 2309250
- PAR ID:
- 10496758
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Software Impacts
- Volume:
- 17
- Issue:
- C
- ISSN:
- 2665-9638
- Page Range / eLocation ID:
- 100567
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)Solution-processed semiconducting main-group chalcogenides (MMCs) have attracted increasing research interest for next-generation device technologies owing to their unique nanostructures and superior properties. To achieve the full potential of MMCs, the development of highly universal, scalable, and sustainable synthesis and processing methods of chalcogenide particles is thus becoming progressively more important. Here we studied scalable factors for the synthesis of two-dimensional (2D) V–VI chalcogenide nanoplates (M 2 Q 3 : M = Sb, Bi; Q = Se, Te) and systematically investigated their colloidal behaviour and chemical stability. Based on a solvent engineering technique, we demonstrated scale-up syntheses of MMCs up to a 900% increase of batch size compared with conventional hydrazine-based gram-level syntheses, and such a scalable approach is highly applicable to various binary and ternary MMCs. Furthermore, we studied the stability of printable chalcogenide nanoparticle inks with several formulation factors including solvents, additives, and pH values, resulting in inks with high chemical stability (>4 months). As a proof of concept, we applied our solution-processed chalcogenide particles to multiple additive manufacturing methods, confirming the high printability and processability of MMC inks. The ability to combine the top-down designing freedom of additive manufacturing with bottom-up scalable synthesis of chalcogenide particles promises great opportunities for large-scale design and manufacturing of chalcogenide-based functional devices for broad application.more » « less
-
null (Ed.)Geometric accuracy control is critical for precision additive manufacturing (AM). To learn and predict the shape deformation from a limited number of training products, a fabrication-aware convolution learning framework has been developed in our previous work to describe the layer-bylayer fabrication process. This work extends the convolution learning framework to broader categories of 3D geometries by constructively incorporating spherical and polyhedral shapes into a unified model. It is achieved by extending 2D cookiecutter modeling approach to 3D case and by modeling spatial correlations. Methodologies demonstrated with real case studies show the promise of prescriptive modeling and control of complicated shape quality in AM.more » « less
-
This paper aims to advance the field of additive manufacturing by producing multimaterial objects with intricate topological features and polylithic material distribution through an integrated approach. First, we develop a Single-Nozzle Multi-Filament (SNMF) system equipped with active mixing to blend multiple filaments and deposit a programmable mixture. The system can also deposit gradient transitions between different materials within a single print. Second, we establish a numerical model to represent the material transitional behavior and validated it with experiments. The model enables the precise control of the material transitional interface to ensure high material fidelity. Third, we propose three strategies for designing and modeling multimaterial objects catering to different application scenarios, including image sampling, 2D discrete patches, and 3D surface division. The system’s capabilities were validated through six case studies designed and fabricated through the above approaches for distinct application scenarios, demonstrating the successful materialization of complex designs with multiple functionalities.more » « less
-
Additive Manufacturing (AM) provides the advantage of producing complex shapes that are not possible through traditional cutting processes. Along with this line, assembly-based part design in AM creates some opportunities for productivity improvement. This paper proposes an improved optimization algorithm for part separation (OAPS) in assembly-based part design in additive manufacturing. For a given object, previous studies often provide the optimal number of parts resulting from cutting processes and their corresponding orientation to obtain the minimum processing time. During part separation, the cutting plane direction to generate subparts for assembly was often selected randomly in previous studies. The current work addresses the use of random cutting planes for part separation and instead uses the hill climbing optimization technique to generate the cutting planes to separate the parts. The OAPS provides the optimal number of assemblies and the build orientation of the parts for the minimum processing time. Two examples are provided to demonstrate the application of OAPS algorithm.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.simpa.2023.100567
