Research and implementation of a non-supporting 3D printing method based on 5-axis dynamic slice algorithm

Wang, Mingqian; Zhang, Haiguang; Hu, Qingxi; Liu, Di; Lammer, Herfried

doi:10.1016/j.rcim.2019.01.007

Cited by 63 publications

(22 citation statements)

References 15 publications

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“…Novel hardware capabilities are also being applied such as multi-axis 3D printing [85][86][87] and reusable supports' [88] innovative part production methods such as object partitioning [89] and support slimming [90].…”

Section: Avoiding Supportsmentioning

confidence: 99%

“…The range and variety of materials available for material extrusion is too vast to be covered here in detail, but they are comprehensively mentioned. Novel hardware capabilities are also being applied such as multi-axis 3D printing [84][85][86] and reusable supports' [87] innovative part production methods such as object partitioning [88] and support slimming [89].…”

Section: Materials Extrusionmentioning

confidence: 99%

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Polymer-Based Additive Manufacturing: Process Optimisation for Low-Cost Industrial Robotics Manufacture

2021

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The robotics design process can be complex with potentially multiple design iterations. The use of 3D printing is ideal for rapid prototyping and has conventionally been utilised in concept development and for exploring different design parameters that are ultimately used to meet an intended application or routine. During the initial stage of a robot development, exploiting 3D printing can provide design freedom, customisation and sustainability and ultimately lead to direct cost benefits. Traditionally, robot specifications are selected on the basis of being able to deliver a specific task. However, a robot that can be specified by design parameters linked to a distinctive task can be developed quickly, inexpensively, and with little overall risk utilising a 3D printing process. Numerous factors are inevitably important for the design of industrial robots using polymer-based additive manufacturing. However, with an extensive range of new polymer-based additive manufacturing techniques and materials, these could provide significant benefits for future robotics design and development.

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Section: Avoiding Supportsmentioning

confidence: 99%

Section: Materials Extrusionmentioning

confidence: 99%

Polymer-Based Additive Manufacturing: Process Optimisation for Low-Cost Industrial Robotics Manufacture

2021

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“…Each subpart is sliced by a five-axis dynamic slicing algorithm [22]; by extracting the skeleton curve of the subpart, the equations of the skeleton curves are achieved, and these are used for the construction curve. Then, the model is sliced by a series of dynamic planes calculated by the construction curve.…”

Section: Model Slicingmentioning

confidence: 99%

Oriented to Multi-Branched Structure Unsupported 3D Printing Method Research

Feng

Zhang

et al. 2020

Materials

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For the traditional three-axis (3D) configuration of the additive manufacturing (AM) platform, when printing the target model with a multi-branched structure, it is imperative to construct adequate support structures. To eliminate the use of support during the printing process, a non-directional unsupported 3D printing method for five-axis AM is proposed in this paper. By carrying out the K-means clustering algorithm, the coarse partition of the model is obtained, and then the fine decomposition represented by a sequence of separating planes is determined by a local dynamic search adjustment algorithm according to manufacturing constraints. The multi-branched structure of the model is divided into simple subparts so that the general model can be built in different directions and be printed with its own parts as the support. Two case studies were carried out for verification. The experimental results showed that the branch-model can be printed without support using the non-directional unsupported 3D printing method, and the non-directional unsupported 3D printing can save 18.72–20.60% of materials and 20.60–23.33% of time compared to conventional 3D printing.

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“…Shen et al [4] proposed a toolpath interpolation method for 5-degree-of-freedom (5-DoF) parallel kinematic machines which can realize the smoothness of acceleration in all toolpath components, decrease the shock to the system, and reduce the surface error after cutting. Wang et al [5] proposed a novel 5-axis dynamic slicing algorithm to achieve non-supporting material printing.…”

Section: Introductionmentioning

confidence: 99%

Thermal Deformation Defect Prediction for Layered Printing Using Convolutional Generative Adversarial Network

Wang

Zhang

et al. 2020

Applied Sciences

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This paper presents a Thermal Deformation defect prediction method for layered printing using Convolutional Generative Adversarial Network (CGAN). Firstly, the original manifold mesh is converted into layered image in Printing Coordinate System (PCS). The trajectory inside layered image with various infill patterns are generated for making comparisons. Inspired by monocular vision and even binocular vision, the mathematical model of thermal defect prediction via infrared thermogram is built via virtual printing of Digital Twins to preset the initial parameters of Artificial Neural Network (ANN). Particularly, the depth convolution is used to extract multi-scale features of layered image. By using transfer learning techniques to identify small sample data, the CGAN is employed to build the nonlinear implicit relations between thermal deformation and multi-scale features. The binocular stereo vision laser scanner is used to determine the actual thermal deformation of the target printed objects. The shape deformation dissimilarity can be succinctly calculated by evaluating the surface profile error via mesh registration between the original source and target mesh model. The proposed method is verified by physical experiments. The experiment proved that the proposed method can deal with the thermal deformation with more optimal parameters, which contributes to performance forward design of irregular complex parts regarding diversified customized requirements.

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Research and implementation of a non-supporting 3D printing method based on 5-axis dynamic slice algorithm

Cited by 63 publications

References 15 publications

Polymer-Based Additive Manufacturing: Process Optimisation for Low-Cost Industrial Robotics Manufacture

Polymer-Based Additive Manufacturing: Process Optimisation for Low-Cost Industrial Robotics Manufacture

Oriented to Multi-Branched Structure Unsupported 3D Printing Method Research

Thermal Deformation Defect Prediction for Layered Printing Using Convolutional Generative Adversarial Network

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