A Definition Formalism of Machining Features for DFM

Benefiting from advances in feature technology for design and manufacture can not be expected before a formal methodology is established. This paper makes attempt to establish a definition formalism of machining features in design for manufacturability from two aspects: formal definition and manufacturability analysis. Some definitions for machining feature based upon the selection and sequencing of material removal operations for component in accordance with the design geometry are presented and a framework of feature based design for manufacturability is outlined correspondingly. The proposed scheme contributes to several aspects of feature based CAD/CAM integration, especially to encourage potentially a more generic approach to the automation of design.

A review of the techniques for the mold manufacturing of micro/nanostructures for precision glass molding

Micro/nanostructured components play an important role in micro-optics and optical engineering,tribology and surface engineering,and biological and biomedical engineering,among other fields.Precision glass molding technology is the most efficient method of manufacturing micro/nanostructured glass components,the premise of which is meld manufacturing with complementary micro/nanostructures.Numerous mold manufacturing methods have been developed to fabricate extremely small and high-quality micro/nanostructures to satisfy the demands of functional micro/nanostructured glass components for various applications.Moreover,the service performance of the mold should also be carefully considered.This paper reviews a variety of technologies for manufacturing micro/nanostructured molds.The authors begin with an introduction of the extreme requirements of mold materials.The following section provides a detailed survey of the existing micro/nanostructured mold manufacturing techniques and their corresponding mold materials,including nonmechanical and mechanical methods.This paper concludes with a detailed discussion of the authors recent research on nickel-phosphorus(Ni-P)mold manufacturing and its service performance.

AI-Based Modeling and Data-Driven Evaluation for Smart Manufacturing Processes

Smart manufacturing refers to optimization techniques that are implemented in production operations by utilizing advanced analytics approaches. With the widespread increase in deploying industrial internet of things(IIOT) sensors in manufacturing processes, there is a progressive need for optimal and effective approaches to data management.Embracing machine learning and artificial intelligence to take advantage of manufacturing data can lead to efficient and intelligent automation. In this paper, we conduct a comprehensive analysis based on evolutionary computing and neural network algorithms toward making semiconductor manufacturing smart.We propose a dynamic algorithm for gaining useful insights about semiconductor manufacturing processes and to address various challenges. We elaborate on the utilization of a genetic algorithm and neural network to propose an intelligent feature selection algorithm. Our objective is to provide an advanced solution for controlling manufacturing processes and to gain perspective on various dimensions that enable manufacturers to access effective predictive technologies.

Principal Face-based Recognition Approach for Machining Features of Aircraft Integral Panels

Feature recognition aims at extracting manufacturing features with geometrical information from solid model and is considered to be an efficient way of changing the interactive NC machining programming mode.Existing recognition methods have some disadvantages in practical applications.They can essentially handle prismatic components with regular shapes and are difficult to recognize the intersecting features and curved surfaces.Besides,the robustness of them is not strong enough.A new feature recognition approach is proposed based on the analysis of aircraft integral panels＇ geometry and machining characteristics.In this approach,the aircraft integral panel is divided into a number of local machining domains.The machining domains are extracted and recognized first by finding the principal face of machining domain and extracting the sides around the principal face.Then the machining domains are divided into various features in terms of the face type.The main sections of the proposed method are presented including the definition,classification and structure of machining domain,the relationship between machining domain and principal face loop,the rules of machining domains recognition,and the algorithm of machining feature recognition.In addition,a robotic feature recognition module is developed for aircraft integral panels and tested with several panels.Test results show that the strategy presented is robust and valid.Features extracted can be post processed and linked to various downstream applications.The approach is able to solve the difficulties in recognizing the aircraft integral panel＇s features and automatic obtaining the machining zone in NC programming,and can be used to further develop the automatic programming of NC machining.

HISTORICAL PROCEDURES AND G-DSG METHOD BASED MANUFACTURING PLANNING

Oriented to CAD/CAM seamless integration, this paper presents an idea for synthetically considering the qualitative history model, which represents the whole course of modeling, and the quantitative geometry model, which contains the extended Brep model, CSG and feature pedigree. History model building captures in background the dynamic interactive definition of engineering requirement and then explicitly conveys the original intention to successive application layers, which is conductive to the decision support of manufacturing planning in not only automatic geometry re constructing but also machining set up. G DSG theory as an earlier achievement is applied to generate the topology independent generalized mid model as an input to manufacturing planning, which is therefore simplified and its accuracy is simultaneously improved. Manufacturing planning lays emphasis on optimizing the mapping in both geometry and function from part itself to detail machining scheme. Comparatively, process planning pays more attention to the mapping to those items like tool, fixture, etc. Theoretically, such an idea is also beneficial to realizing the parametric NC machining trajectory generation and maintaining its dynamic consistency with the update of the design model.[WT5”HZ]

THE RESEARCH OF MANUFACTURING TOOLS(FIXTURES) PLANNING FOR ARMOURED FLEXIBLE CONVEYOR (AFC) USING CAD TECHNIQUE

The deepth and width of CAD application in coal mining equipments need promote furtherly. The information stream method is applied as the main clue to deal with the related technology and problems in research of manufacturing tools (Fixtures) planning for AFC (mining scraper bars conveyor) using CAD technique.

制造业众包平台服务资源的特征构建及聚合匹配

针对制造业众包平台中服务资源的特征构建缺乏规范、聚合匹配不准确的问题,提出了基于双向编码表示(BERT)模型的特征构建方法和基于多粒度特征交互的聚合匹配模型(MFIM)。前者改进了经典的BERT模型,采用停止符掩码操作和基于分类任务的学习策略,实现了服务资源所具有的语义特征建模,精准衡量了平台商所具有的服务资源能力水平,为大规模的语义特征体系的构建提供了有力支撑。后者针对服务资源的语义粒度差异较大的问题,采用了多层次的扩张卷积结构,并构建了跨粒度信息交互的关联矩阵。这有效解决了服务资源的聚合匹配及语义辨识问题。实验表明,所提出的一系列研究方法能够有效地建模服务资源文本,为服务资源的深入挖掘和精准的匹配检索提供了一种新的思路和手段。

增材制造成形件中位错的研究进展

增材制造是通过逐层堆积的方法制造实体零件的一种革命性技术,其成形性能受成形工艺、微观结构、沉积路径等影响,其中,位错作为晶体微观结构中广泛存在的一种线缺陷,是决定金属性能的一个重要因素。为深层次理解增材制造性能影响的本质机制,需进一步了解增材制造成形件中的位错特点。本文基于近年来增材制造成形件中位错的研究成果,梳理了位错的起源、特征和密度,分析了位错对强度等性能的影响。与传统制造相比,增材制造成形过程中因固有的循环加热-冷却而造成的压缩-拉伸应力循环使得增材制造成形件中的位错具有独特的结构和性质。在塑性变形中,位错随应变变化明显,不同的初始位错影响成形件对应变的响应;增材制造成形件中测量的位错密度高于锻件或铸件,不同位置、不同形状的位错密度也存在一定的差异;位错强化是增材制造成形件中的主要强化作用,与此同时,在钢的成形件中,位错还可诱发马氏体相变,促使再结晶,另外还影响成形件的腐蚀、蠕变和氢脆等。

基于特征的零件制造成本测算

由于零件制造成本测算过于依赖传统人工经验,为提升零件制造阶段对于动态需求变更响应的能力,提出了一种基于特征的零件制造成本测算方法。通过对加工特征的分类,分析影响制造成本主要因素,定义了板类零件制造成本模型,并建立了制造资源数据库;针对材料成本和加工成本的关键信息,深度分析基于加工特征的加工工时计算方法,确定了加工成本,结合企业实例验证该方法的可行性。

基于组合结构的逻辑回归点击预测算法

随着互联网和广告平台的飞速发展,面对海量的广告信息,为了提升用户点击率,提出一种改进的基于组合结构的逻辑回归点击预测算法LRCS(Logical Regression of Combination Structure)。该算法基于不同类别特征广告受众可能不同的特点,首先,采用FM进行特征组合,产生两类组合特征;其次,将一类特征组合作为聚类算法的输入进行聚类;最后,将另一类特征组合输入由聚类产生的分段GBDT+逻辑回归组合的模型中进行预测。在两个公开数据集中进行了多角度验证,结果表明与其他几类常用的点击预测算法相比,LRCS在点击预测上有一定的性能提升。

激光选区熔化成形金刚石复合材料特征几何结构的工艺约束研究

多孔金刚石磨具是一种能在磨削加工过程中提供容屑和冷却液流通空间的新型工具,激光选区熔化(selective laser melting,SLM)成形技术是制造多孔金刚石磨具的有效手段。受激光增材制造的光斑尺寸约束、逐层成形等技术特征的影响,所设计的多孔金刚石磨具难以精准成形,因此有必要对金刚石复合材料特征几何结构的可成形性进行研究。基于SLM125HL设备,以CuSn20/金刚石复合材料为研究对象,采用SLM成形技术成形了不同成形方向、不同尺寸的悬垂结构、薄壁、圆孔和尖角等特征几何结构,并对其可成形性、成形误差及产生原因进行分析。结果表明:金刚石复合材料悬垂结构的最佳可成形尺寸为1.00~2.00 mm,薄壁结构的最小可成形尺寸为0.70 mm;垂直于成形方向的圆孔结构的最小可成形直径尺寸为0.50 mm,平行于成形方向的圆孔结构的最佳成形直径尺寸为1.00~4.00 mm;尖角结构的可成形角度需>10°。这些特征几何结构的成形误差主要受激光对复合粉末的热吸附、激光光斑热影响区扩散以及复合粉末的弱支撑等作用影响。

在VLSI制造中基于辅助图形的灰度光刻形成三维结构

半导体器件从单一的二维尺度微缩转向更复杂的三维物理结构,而其传统的制造方法与以硅基逻辑或存储器为主的超大规模集成电路(VLSI)制造工艺的兼容性越来越差。灰度光刻是一种实现三维结构的可行技术方案,但因物理尺寸受限和大规模制造成本过高,无法被直接应用于超大规模集成电路制造。提出了一种基于辅助图形的灰度光刻技术,通过辅助图形而非传统灰度光刻调整光源或透过介质的方法来调整光强分布,并结合光刻胶筛选方法,实现了仅通过调整单一光刻工艺模块,就使现有超大规模集成电路制造工艺生产线可低成本地兼容三维结构器件制造。制作了三维结构的微电子机械系统(MEMS)运动传感器,从而验证了所提出工艺的可行性。

铝合金车体加工部件加工特征识别方法研究

为提高铝合金车体加工部件加工效率,减少加工工艺准备时间,提高车体加工部件加工特征识别准确率,研究铝合金车体加工部件加工特征识别方法。以车体加工部件为研究对象,通过分析其加工特征与结构特点,采用基于图像的特征识别方法和基于特征提取面与特征边界环的分步特征搜索方法,分别提取车体加工部件加工特征,构建属性邻接图和特征面集。针对车体加工部件相交特征的特点,提出非加工实体面的概念,设计相应的相交特征识别与处理准则,为后续车体加工部件加工的自动化编程提供理论支撑。

Modeling of Additive Manufacturing Process Relevant Feature in Layer Based Manufacturing Process Planning

Compared with general machining processes,additive manufacturing(AM) process has stabler planning route and limited process variables and this makes it to be more easily designed and planned with knowledge based systems and computer aided techniques.Case based reasoning approach is applied to the process planning of additive manufacturing in this paper.The concept of "AM process relevant design features" is proposed after the analysis of the characteristics of AM processes.The concept is used as the basis of the knowledge representation,and AM relevant feature graph is used as the case representation schema.The case retrieval method is discussed based on this graph.The case representation of a machine arm is given to illustrate the brief process of the proposed approach.

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。

基于注意力机制—门控循环单元—BP神经网络的智能多工序工艺参数关联预测

鉴于流程制造工序间能质流耦合严重,性能指标影响因素众多,工艺参数时序特征显著,现有制造模式下难以精准预测产品质量,在分析流程制造工艺性能指标多维、强时序、关联耦合特征的基础上,提出一种基于注意力机制—门控循环单元-BP神经网络(Attention AM-GRU-BPNN)的多工序耦合参数关联预测方法。首先采用互信息方法筛选多态异构生产数据作为输入,建立ConvGRU自编码器,通过无监督学习对过程数据、工艺参数、操作参数等进行时序特征提取,同时引入时序注意力机制提取不同工序的耦合关联特征并进行向量嵌入,为不同工序的工艺参数分配注意力权重。在此基础上,设计Attention网络自学习不同时刻下工艺关联特征对质量性能指标的影响差异,再通过门控循环单元网络对重要的关联特征进行增强,并按照时序特征对单工序预测模型进行聚合,实现多工序时序特征融合,最后通过输出层BPNN神经网络精准预测产品工艺质量。实验表明,AM-GRU-BPNN有效提高了预测精度,从多工序角度为生产线工序的加工过程控制提供了依据。

激光增材制造零部件故障自动分类方法

不同状态下的零部件故障特征不同,为了准确分辨零部件故障,为解决故障提供依据,提出了激光增材制造零部件故障自动分类方法。基于阶次分析原理提取了激光增材制造零部件的故障特征,并获取了零部件故障特征向量;利用支持向量机中的一对一分类方法,对获取的零部件故障特征进行分类,基于分类结果对其进行校正,达到提高故障分类精度的目的,最终实现激光增材制造零部件故障自动分类。通过对该方法进行内圈故障和外圈故障两种不同状态下进行分类识别效果测试,验证了该方法具有较高的激光增材制造零部件故障分类准确性。

面向MBD模型的特征信息自动识别算法研究

针对特征识别技术对产品制造信息识别的缺失以及匹配算法的复杂性问题,提出了一种基于MBD模型的特征信息自动识别算法。首先,通过EXPRESS和Java映射,构建STEP文件解析器解析MBD模型信息。其次,建立基于图和提示的几何特征识别算法,用表征面邻接图作为匹配算法的数据结构,以提示作为搜索与特征库进行匹配。然后,提出基于关系树的产品制造信息识别方法识别产品制造信息。最后,以轴和机匣作为测试对象,在Intellij IDEA平台中对所提方法进行了验证,分析了匹配算法时间复杂度。结果表明,该方法能够识别几何特征信息和产品制造信息,本匹配算法时间复杂度为O(n),优于时间复杂度为O(n2)的传统匹配算法。

基于点云深度学习的加工特征识别方法

在计算机辅助设计与制造系统中,加工特征识别是一项关键技术。针对传统的特征识别技术可扩展性差、鲁棒性差等问题,提出一种基于点云深度学习的加工特征识别方法。通过对加工特征表面进行均匀点采样,构建加工特征的点云数据集。使用K近邻算法构建点云的旋转不变表示,提出一种融入几何先验知识的点云分类网络。对于多特征模型的点云数据,提出一种加工特征点集的提取方法和相交特征的分离方法。通过具体实例验证了所提方法的有效性,表明该方法能识别CAD模型中的单一特征和相交特征。

在轨制造现状及金属材料在轨制造方法研究

在轨制造技术在深空探测领域有广泛的应用前景,是各航天大国竞相发展的先进技术。目前,非金属材料的在轨制造已经实现,而金属材料在轨制造仍面临很多困难。文章介绍了国内外在轨制造技术的发展现状,着重介绍欧洲和美国金属材料在轨制造的技术路径,分析了发展金属材料在轨制造技术面临的困境和难点。针对这些难点,提出利用非晶合金材料的热塑性加工特性来实现金属材料在轨制造技术的突破,对有望应用于在轨制造的基于非晶合金的制造技术进行介绍,并对其未来发展方向进行探讨,以期为金属材料在轨制造技术的发展提供参考。