基于环形邻域的增材制造分层自适应正向设计方法

为了提升多特征成形的表面精度与制造效率,提出一种基于环形邻域的增材制造分层自适应正向设计方法。构建模型多阶环形邻域,基于变尺度的平均曲率高斯加权平均值计算模型显著度,运用动态聚类确定显著特征。以递归获取的形态显著线的变化确定初始分层厚度,建立自洽的分层规划正向设计数学模型。进一步运用数字孪生技术实现增材制造虚拟打印。以虚拟打印模型在打印坐标系正平面和侧平面的分层投影面积为材料热塑约束,并通过双向循环链表和八叉树计算投影面域集合的布尔并,实现多特征迭代的分层规划正向设计。采用接触式轮廓仪对打印模型不同特征区域进行了表面粗糙度测量。实例表明,该方法能够有效地对多特征流形模型进行自适应分层,有助于提升3D打印与4D打印层积制造品质与效率。     

增材制造技术中的自适应分层研究

增材制造技术是一种先进的智能化制造技术,分析了其"分层—叠加"的制造原理,其制造过程中必然会存在原理性误差,即"阶梯效应";通过对制造过程的几何分析,建立了表示原理性误差的理论公式,该公式具有普遍适用性;分析了原理性误差与其影响因素—三维模型表面的法向方向、曲率、分层厚度之间的相互关系,为分层提供了理论依据;提出了一种基于三维模型表面几何特征直接对三维模型进行自适应分层的算法,该算法根据三维模型表面的曲率、法向方向以及给定的精度要求来自动的调整分层厚度;并对该算法进行了实验分析,结果表明,该算法满足自适应分层的要求。     

增材制造中STL模型的自适应分层算法研究

增材制造技术是一种先进的智能加工技术,并且通过其制造原理"分层—叠加"来加工实体。为了满足增材制造成型实体阶梯误差的要求,提出一种基于STL三角形网格法向量的自适应分层算法。首先根据三维实体成型后出现正、负偏差原理,得到统一正偏差截面轮廓的选择方法;其次以阶梯效应为依据,根据三角形网格法向量以及所允许的阶梯高度,确定自适应分层的分层厚度;最后对该算法进行实例验证。结果表明该算法符合自适应分层的要求,可有效减少阶梯效应并使得后处理工序更为方便。     

摩擦搅拌增材制造发展概述

针对目前国内外增材制造技术做了归纳与总结,重点分析研究了摩擦搅拌增材制造(Friction Stir Additive Manufacturing,FSAM)技术在国外研究的发展状况。FSAM最早在美国提出,并在美国掀起研究热潮。FSAM可以分为两大类,即:损耗型搅拌针的FSAM和非损耗型搅拌针的FSAM;又根据制造过程的工艺特点分为3种典型模式,即:损耗沉积模式、以板材为进料模式及以粉末为进料模式。这些不同模式的FSAM在美国和印度取得了突破性进展,为摩擦搅拌增材制造的产业化发展奠定了基础。同时,国内也成功实现了颗粒料的增材制造,且成型件有较好的机械性能。最后,给出了FSAM技术的发展趋势和应重点关注的内容。     

基于增材制造的液压阀块流道过渡区优化研究

器件小型化和集成化发展趋势,对液压阀块设计提出了更高的要求.传统工艺加工阀块体内部流道,不但工艺复杂难加工,而且成形的流道流动特性有待提高.新型制造工艺增材制造一体化成形的特点使其在流道加工方面表现出很大的优越性.基于增材制造,对某一液压集成阀块的流道过渡区进行优化设计,利用Fluent仿真,对直线过渡、圆弧过渡、B样...     

陶瓷零件的增材制造技术

增材制造技术是９０年代发展起来的新技术，具有许多突出的优点，本文简要介绍了常用的增材制造技术，着重介绍了陶瓷元件的增材制造技术，并对与之相关的问题进行了讨论。     

一种电弧增材制造系统及沉积层性能研究

为了跟上国内外电弧增材制造技术迅猛发展势头,采用从设备研制到实验验证的方法路线,介绍了一种基于机器人的增材制造系统的硬件选择及软件设计,并利用该增材制造系统增材制造出耐磨钢直臂件,对增材件性能进行测试。结果表明,该制造系统具有修改增材制造工艺参数方便、成形效果良好、成型精度较高等优点。项目开展的基础性研究对于金属丝材电弧直接制造系统的开发和技术的推广及应用具有重要的理论参考和实际指导意义。     

复合式增材制造技术研究现状及发展

形性问题制约金属增材制造技术的发展与应用,复合式增材制造在解决制件形性问题方面效果显著。高度概括了复合式增材制造技术分类方式与主体类别;简要总结了增减材复合制造在制件成形精度和表面质量控制方面的研究进展和技术发展状况;重点评述了增等材复合制造技术类别、成形原理、制造特征和关键问题,以及在制件显微组织、应力状态、宏观性能调控方面的研究现状和主体结论;系统介绍了超声、电磁、激光三类特种辅助能场对增材熔池流动、结晶、固态相变的作用机制,以及特种能场作用下,增材层显微组织状态、力学性能、成形精度的演化规律;展望了复合式增材制造技术未来的发展趋势。     

增材制造中STL模型三角面片法向量自适应分层算法研究

本文提出了增材制造技术中STL模型三角面片法向量自适应分层新算法。该方法寻找与层厚t相交的三角面片的最小法向量,应用三维模型体素中x-y分辨率和STL模型中三角面片法向量与制造方向间夹角变化关系,实现STL模型的自适应分层。用此方法分层,减少了分层参数处理的复杂性,使自适应分层变得更加简单且易实现,得到的分层厚度值更加准确。由于自适应分层是在允许的误差范围内得到的分层厚度,因此在STL模型轮廓变化明显的区域分层更加精细。     

基于增减材制造的复合加工技术研究

基于增减材制造的复合加工技术融合了增材制造(RP技术)和减材制造技术优势,具有高精度、高效率、高自动化的特点,但国内外针对该技术开展的研究较少。详细阐述了基于增减材制造的复合加工技术原理及特点,并系统分析了国内外基于增减材制造的复合加工技术最新研究进展,最后指出其发展方向。     

螺旋罗茨转子四轴加工刀路规划

通过分析螺旋罗茨转子的成型规律,建立了球头刀加工螺旋转子的加工模型,规划了刀具路径,通过等弧长平分法和控制残留高度的等参数法两种方式处理转子端面型线数据点,比较了两种数据点处理优缺点,在此基础上定制了一种规律化的四轴编程模版,采用该模版不需太多编程经验可以快速编制加工程序,从而高效加工螺旋转子,在实际加工中,取得了较好的社会经济效益.     

Nonplanar slicing and path generation methods for robotic additive manufacturing

Additive manufacturing (AM, generally called 3D printing) has attracted great research interests due to its ability to build complex shapes. It transforms design files to functional products through slicing and material accumulation. Typically, the planar slicing strategy is used in AM to convert CAD model into accumulating layers. However, when building overhang structures and curved parts, it often needs support structures and generates a large number of planar layers, which lead to the fact that it spends more time in manufacturing. To reduce the need for support structures and decrease the number of layers, this paper presents two nonplanar slicing approaches: a decomposition-based curved surface slicing strategy and a transformation-based cylinder surface slicing method. The former is implemented based on STEP models and the latter is capable of slicing mesh models. The feasibility of the proposed methods are validated by printing two parts with a robotic fused deposition modelling system.     

A path planning and sharp corner correction strategy for wire and arc additive manufacturing of solid components with polygonal cross-sections

Pores can easily form in the geometric center and sharp corner lap joints of solid components with polygonal cross-sections fabricated by wire and arc addi     

STEP-NC compliant process planning of additive manufacturing: remanufacturing

Additive manufacturing is becoming one of the key methods for reproducing repair sections in remanufacturing processes. The major advantage of using additive processes is to minimize production time and waste. However, the surface quality and shape accuracy are usually insufficient for the final product because the approximated representation format causes the accumulation of the error during the geometric operations of the process planning. This limitation is a barrier to utilize additive processes as finishing processes, such as general metal cutting. There is need to improve the final quality of parts obtained with additive manufacturing. In this paper, STEP-based numerical control (STEP-NC)-based process planning is applied to the additive manufacturing. ISO 14649 (STEP-NC) describes part programs with geometric data directly and also contains the information necessary for the intelligent process planning. This paper proposes the STEP-NC-based representation method of additive manufacturing and the series of geometric reasoning to automate the derivation of the repair section. The proposed representation has the benefits to provide a high accuracy for the final surface and to describe multiple materials. Topological data maintain low error during the series of process planning through the CAD-CAM-CNC chain. The proposed platform supports consideration of the process tolerance and comparison of the selected plan with alternative processes. In order to show the practical advantages, an analysis of the remanufacturing process is carried out. The case study of remanufacturing a pocket part is presented in order to validate the proposed process plan. The result of the case study shows the improvement in terms of automatic process planning and surface quality accuracy.     

层切法模具粗加工中自适应刀轨规划方法

目前,模具粗加工方法是制约模具数控加工效率提高的重要因素,为此,深入探讨了基于层切法的零件模具数控粗加工方法,简述了层切法中计算机辅助设计3维模型分层方法,详细论述了截面上数控加工轨迹生成和规划方法。研究了目前层切法刀具轨迹生成算法的不足,提出了刀具环形轨迹的自适应规划方法。根据层面边界曲率在已有粗加工刀具中自动选择粗加工刀具规格,实现了刀具优化选择的目的。应用该方法可以减少粗加工余量,提高粗加工速度,进一步提高零件模具数控加工效率。     

Temporal design for additive manufacturing

The International Journal of Advanced Manufacturing Technology - Additive manufacturing (AM) is expected to generate huge economic revenue by 2025; however, this will only be realised by overcoming...     

Identifying the directions of a set of 2D contours for additive manufacturing process planning

Additive Manufacturing (AM) is a process in which material is added layer by layer to build a physical part. In AM process planning, a stack of 2D closed contours is obtained when a 3D stereolithography (STL) model is sliced. Each slice may have a set of closed contours or polygons, each of which needs to be classified (oriented) as internal (clockwise) or external (counterclockwise) to identify where material should be added. This is not a straightforward task as the STL format does not ensure correct surface orientation of the 3D model. This work describes two methods for identifying the direction of each contour in a set, i.e., for sorting them into internal and external contours. Three alternative tests to check whether a point is inside or outside a polygon were evaluated. The tests are based on the ray-tracing principle and the classical point-in-polygon test. The proposed algorithms were devised and implemented in an AM process planning system. The methods were validated using 3D models with a variety of geometries, and the computing time for the alternative tests was compared. The results showed that the method based on the point-in-polygon tests has some advantages.     

Modeling process-structure-property relationships for additive manufacturing

This paper presents our latest work on comprehensive modeling of process-structure-property relationships for additive manufacturing (AM) materials, including using data-mining techniques to close the cycle of design-predict-optimize. To illustrate the process-structure relationship, the multi-scale multi-physics process modeling starts from the micro-scale to establish a mechanistic heat source model, to the meso-scale models of individual powder particle evolution, and finally to the macro-scale model to simulate the fabrication process of a complex product. To link structure and properties, a high-efficiency mechanistic model, self-consistent clustering analyses, is developed to capture a variety of material response. The model incorporates factors such as voids, phase composition, inclusions, and grain structures, which are the differentiating features of AM metals. Furthermore, we propose data-mining as an effective solution for novel rapid design and optimization, which is motivated by the numerous influencing factors in the AM process. We believe this paper will provide a roadmap to advance AM fundamental understanding and guide the monitoring and advanced diagnostics of AM processing.