Manufacturability is vital for product design and production, with accessibility being a key element, especially in subtractive manufacturing. Traditional methods for geometric accessibility analysis are time-consuming and struggle with scalability, while existing deep learning approaches in manufacturability analysis often neglect geometric challenges in accessibility and are limited to specific model types. In this paper, we introduce DeepMill, the first neural framework designed to accurately and efficiently predict inaccessible and occlusion regions under varying machining tool parameters, applicable to both CAD and freeform models. To address the challenges posed by cutter collisions and the lack of extensive training datasets, we construct a cutter-aware dual-head octree-based convolutional neural network (O-CNN) and generate an inaccessible and occlusion regions analysis dataset with a variety of cutter sizes for network training. Experiments demonstrate that DeepMill achieves 94.7% accuracy in predicting inaccessible regions and 88.7% accuracy in identifying occlusion regions, with an average processing time of 0.04 seconds for finely-tessellated geometries. Based on the outcomes, DeepMill implicitly captures both local and global geometric features, as well as the complex interactions between cutters and intricate 3D models. Code is publicly available at https://github.com/fanchao98/DeepMill.

Remanufacturing effectively extends component lifespans by restoring used or end-of-life parts to like-new or even superior conditions, with an emphasis on maximizing reutilized material, especially for high-cost materials. Hybrid manufacturing technology combines the capabilities of additive and subtractive manufacturing, with the ability to add and remove material, enabling it to remanufacture complex shapes and is increasingly being applied in remanufacturing. How to effectively plan the process of additive and subtractive hybrid remanufacturing (ASHRM) to maximize material reutilization has become a key focus of attention. However, current ASHRM process planning methods lack strict consideration of collision-free constraints, hindering practical application. This paper introduces a computational framework to tackle ASHRM process planning for general shapes with strictly considering these constraints. We separate global and local collision-free constraints, employing clipping planes and graph to tackle them respectively, ultimately maximizing the reutilized volume while ensuring these constraints are satisfied. Additionally, we also optimize the setup of the target model that is conducive to maximizing the reutilized volume. Extensive experiments and physical validations on a 5-axis hybrid manufacturing platform demonstrate the effectiveness of our method across various 3D shapes, achieving an average material reutilization of 69% across 12 cases. Code is publicly available at https://github.com/fanchao98/Waste-to-Value.

Wire sculptures are important in both industrial applications and daily life. We introduce a novel fabrication strategy for wire sculptures with complex geometries by tuning the target shape to a collision-free shape for the wire-bending machine and then bending it back to the target by a human. The key challenge lies in tuning the least number of bending points, which is formulated as an "Optimizing Wire Reconfiguration" problem. We first fit the input target wire with consecutive line segments and circular segments to ensure the bending manufacturing constraints for each segment, then generate tuned wire through a bilevel optimization. This involves selecting the bending points at the upper level with a beam search strategy and determining the specifically tuned angles at the lower level. We perform a thorough physical evaluation using a DIY wire-bending machine. The results show the effectiveness of our proposed approach in realizing a wide range of intricate and complex wire sculptures.

Simultaneous four-axis machining involves a cutter that moves in all degrees of freedom during carving. This strategy provides higher-quality surface finishing compared to positional machining. However, it has not been well-studied in research. In this study, we propose the first end-to-end computational framework to optimize the toolpath for fabricating complex models using simultaneous four-axis subtractive manufacturing. In our technique, we first slice the input 3D model into uniformly distributed 2D layers. For each slicing layer, we perform an accessibility analysis for each intersected contour within this layer. Then, we proceed with over-segmentation and a bottom-up connecting process to generate a minimal number of fabricable segments. Finally, we propose post-processing techniques to further optimize the tool directionand the transfer path between segments. Physical experiments of nine models demonstrate our significant improvements in both fabrication quality and efficiency, compared to the positional strategy and two simultaneous tool paths generated by industry-standard CAM systems. This work introduces a general computational framework for simultaneous four-axis CNC machining, which aims to minimize the variation of tool direction while machining continuously as much as possible, and to ensure that the fabrication process is always collision-free. image

Additive and subtractive hybrid manufacturing (ASHM) involves the alternating use of additive and subtractive manufacturing techniques, which provides unique advantages for fabricating complex geometries with otherwise inaccessible surfaces. However, a significant challenge lies in ensuring tool accessibility during both fabrication procedures, as the object shape may change dramatically, and different parts of the shape are interdependent. In this study, we propose a computational framework to optimize the planning of additive and subtractive sequences while ensuring tool accessibility. Our goal is to minimize the switching between additive and subtractive processes to achieve efficient fabrication while maintaining product quality. We approach the problem by formulating it as a Volume-And-Surface-CO-decomposition (VASCO) problem. First, we slice volumes into slabs and build a dynamic-directed graph to encode manufacturing constraints, with each node representing a slab and direction reflecting operation order. We introduce a novel geometry property called hybrid-fabricability for a pair of additive and subtractive procedures. Then, we propose a beam-guided top-down block decomposition algorithm to solve the VASCO problem. We apply our solution to a 5-axis hybrid manufacturing platform and evaluate various 3D shapes. Finally, we assess the performance of our approach through both physical and simulated manufacturing evaluations.

In this study, we propose a computational framework for optimizing the continuity of the toolpath in fabricating surface models on an extrusion-based 3D printer. Toolpath continuity is a critical issue that influences both the quality and the efficiency of extrusion-based fabrication. Transfer moves lead to rough and bumpy surfaces, where this phenomenon worsens for materials with large viscosity, like clay. The effects of continuity on the surface models are even more severe in terms of the quality of the surface and the stability of the model. We introduce a criterion called the one–path patch (OPP) to represent a patch on the surface of the shell that can be traversed along one path by considering the constraints on fabrication. We study the properties of the OPPs and their merging operations to propose a bottom-up OPP merging procedure to decompose the given shell surface into a minimal number of OPPs, and to generate the “as-continuous-as-possible” (ACAP) toolpath. Furthermore, we augment the path planning algorithm with a curved-layer printing scheme that reduces staircase defects and improves the continuity of the toolpath by connecting multiple segments. We evaluated the ACAP algorithm on ceramic and thermoplastic materials, and the results showed that it improves the fabrication of surface models in terms of both efficiency and surface quality.

针对陶瓷3D打印的特点,提出基于放样曲面与周期参数曲线嵌入的双尺度轻量化交互式建模和制造工具.对于用户输入的2条封闭曲线,首先在它们之间插值生成中间截面采样点,并在免支撑、路径无干涉等陶瓷3D打印制造约束下对当前曲面形状进行调整,完成基于放样曲面的大尺度曲面建模;然后将采样点之间的直线路径用周期性曲线路径代替,通过调整曲线函数的周期和振幅完成小尺度几何纹理建模;最后按螺旋方式逐层连接各个截面采样点,直接生成单一连续的打印路径并制造.为验证文中方法的有效性,基于绘制的3组曲线进行建模并利用CERAMBOT Plus陶瓷3D打印机制造模型.实验结果表明,该工具为用户提供了充足的建模空间且模型生成效率高,能够有效地生成可直接进行陶瓷3D打印的带纹理放样曲面的G-code文件.

Ceramic 3D printing has gained rapid development in recent years. Especially, desktop ceramic 3D printers get more and more popular for designers, artists, and makers to work with clays. As a highly viscous pseudoplastic liquid, the printing material clay produces featured aesthetics, and also indicates several manufacturing constraints. There are barely customized modeling tools for ceramic printing. Targeting for ceramic printing, we present a user-interactive modeling and fabricating framework using sweeping lines as the design tool. We integrate the ceramic printing constraints like self-supporting and collision-free in the modeling stage. Then we propose a customized method for generating the printing file, with the guarantee that the extruder traces a single continuous path without starts and stops. To fulfill this goal, we compute an adaptive zig-zag path along the sweeping surface. During the fabrication, our continuous path avoids the potential collision between the printing head and the physical model. Moreover, we optimize the extrusion amount along with the extruder movement, such that overlap between neighboring layers is appropriate in terms of both model stability and cost-effectiveness. We demonstrate the fabrication process and physical results to validate our method. (C) 2020 Elsevier Ltd. All rights reserved.