覆盖件成形缺陷的数值仿真实例分析

为研究汽车大型覆盖件成形规律,并分析其缺陷成因,介绍了板料成形动态显式有限元数值仿真技术的应用现状、基本理论及应用步骤.通过实例研究了采用有限无数值仿真技术进行覆盖件成形缺陷成因仿真分析的途径.仿真结果表明,采用数值仿真可以分析覆盖件变形规律,了解冲压过程中应力、应变分布及方向,成形极限图分布及缺陷情况,进而改进模具结构和冲压工艺,消除成形缺陷、提高产品质量.数值仿真技术是解决大型汽车覆盖件成形缺陷问题的有效工具.     

JSTAMP/NV在多工位级进模冲压仿真中的应用

级进模作为一种复杂、精密的冲压模具,具有高效率、高精度和高寿命的优点,广泛应用于各个行业的冲压生产中。随着技术的发展,对级进模的成形质量要求越来越高,但传统的级进模设计中主要依靠经验,在制造过程需要反复修模,产品制造周期长。本文简述了级进模设计的特点,并对多工位级进模冲压成形数值模拟的方法及操作流程进行了探讨。最后,以某汽车结构件的多工位级进冲压为例,应用JSTAMP/NV软件对其成形过程进行数值模拟,并将该仿真结果与试模结果进行比较,结果表明仿真结果与试模结果吻合良好。     

薄壁铝合金半球壳塑性成型与基于MSC.Marc的模拟技术应用研究

薄壁件如汽车覆盖件、机翼、导弹壳体等在汽车、航空、航天、船舶、家电、机械等行业有着广泛的应用,薄壁件的制造精度和质量也是制造工艺研究的重点对象之一.计算机辅助设计制造与工艺仿真等先进的手段为薄壁件的设计制造工艺提供了有利的保障,如在国外先进工业国家,板料成型的过程与回弹分析已应用于产品设计与模具制造的前期工作,在设计阶段通过仿真手段不断修正产品设计和模具的制造,避免了传统制造周期长、试验成本高的许多缺陷,缩短了产品研制周期的同时创造了较好的经济效益.     

车身开发过程中的成形仿真

对于车身的内外覆盖件 ,拉深及拉延工艺的成形仿真尤为重要。它与产品设计、工艺规划和材料选择息息相关。车身制件的成形仿真分为两类 :概念设计阶段的单步法和生产阶段的精确有限元增量仿真法。若将仿真方法的使用集成在开发过程中 ,能大幅度地缩短总体开发周期 ,提高产品质量。该文讨论了车身开发过程中钣金成形仿真技术的应用 ,分析了汽车开发中的不同阶段 ,不同仿真方法的应用。     

NURBS曲面重构方法在板料模面修型中的应用

给出汽车覆盖件成形过程中处理回弹影响的NURBS曲面几何补偿算法。该算法基于NURBS曲面重构技术,依据有限元网格模型的回弹数值仿真结果对原本用NURBS曲面表达的模具型面进行反向位移补偿修整,使修整后的模具型面仍然保持NURBS曲面表达。并且这些曲面在光滑性、精度等方面都满足工程实际要求的品质。     

对金属薄板成形的计算机仿真

本文介绍一种能在设计成形模具的初始阶段便能用计算机对成形过程进行动态仿真的软件系统，并且给出应用实例。通过该仿真系统能及早地发现成形过程中出现的缺陷，例如起皱失稳、破裂报废以及不合要求的回弹等。系统包括图形和分析功能，能与ＣＡＭ一起构成一个完整的模具设计制造系统。     

基于 PowerMILL的汽车覆盖件模具的数控编程

作者在文中对汽车覆盖件模具的特点进行了详细分析，并以哈飞松花江HF10车尾门外板模具制造为例介绍了PowerMILL软件的具体应用过程。文章给出了该模具数控加工工艺的规划及其数控编程中加工策略选择和参数的设置，对其他汽车覆盖件模具的加工有一定的指导意义。     

面向汽车覆盖件的拉延模快速设计及其实现

覆盖件的设计与生产是汽车制造业的重要组成部分,以覆盖件拉延模的快速设计为 研究目标,具体产品为导向,在设计模板的基础上,智能化修改与替换部分关键组件而形成新的 设计方案,以达到最小化工作量的目的。首先根据汽车覆盖件拉延模的实际模型和工艺,对拉延 模组成零件进行合理分类并建立嵌入设计知识的模板,新的设计替换模板中关键组件,系统自动 根据需要加入工艺信息,修整模型曲面以适应实际需要。实践证明,该方法可以有效地重用既往 设计经验,减少设计错误,提高设计质量。     

汽车薄钢板不均匀拉伸试验和仿真研究

研究汽车覆盖件拉伸优化问题,针对汽车覆盖件容易出现起皱,传统研究方法没有考虑其成形过程中与模具接触,预测精度不高的现状。根据起皱预测理论,研究单面接触对起皱的影响。提出了高强度薄钢板的对角拉伸试验仿真。首先建立了标准的YBT(Yoshida Buckling Test)仿真模型,在有限元软件LS_DYNA上验证了仿真模型的正确性。进一步考虑冲压过程中板料与模具的接触状况,建立了带有单面接触的YBT仿真模型。结果表明,标准YBT试验中的起皱的高度较大,起皱原因是压应力导致的失稳。单面接触情况下压应力的释放得到抑制,起皱高度明显减小,明确了起皱的原因是卸载回弹,为设计提供了依据。     

汽车高强钢大通风孔车轮轮辐成形工艺优化仿真

为满足汽车车轮强度要求,大通风孔钢制车轮轮辐需采用高强度钢材进行冲压成形,因此更容易产生各种成形不良问题.用PAM STAMP对某大通风孔钢制车轮轮辐成形过程中的2道关键拉延工序进行有限元仿真和优化,通过改变模具结构和参数降低轮辐成形后的减薄量,有效防止轮辐成形过程中的开裂现象.对仿真结果和实际加工结果的对比和分析验证该仿真方法的有效性.     

基于ECA-SSD模型的汽车零件缺陷检测

Automobile parts have great influence on the appearance, performance and safety of automobile. Due to the large number of automobile parts, small volume and high accuracy requirements, there are certain requirements for the accuracy and speed of parts detection. Using image processing technology, based on SSD model, the VGG module is replaced by deep separable convolution and linear bottleneck inverse residual structure. An effective attention mechanism ECA module is introduced to avoid dimensionality reduction. At the same time the computational complexity of the model parameters is reduced, and the channel is increased to improve the accuracy of the model. And this paper focuses on the image target, ignores the interference of the background to achieve fast and accurate defect detection of automotive parts. In addition, the proposed model in this paper is used to detect the outer wall defects of automobile parts provided by SAIC. The experimental results show that the size of the model is only 15.9 MB, the mAPis 94.64%, and the detection time of each image is 0.013 s, which meets the requirements of speed and accuracy in the automotive industry. Compared with other target detection algorithms such as VGG-SSD、MobileNetv2-SSD and YOLO v3, the detection accuracy, speed and size of the proposed model are improved.     

基于机器视觉的汽车精密零件缺陷检测

本文针对汽车精密零件外观质量检测的需求,利用机器视觉系统采集零件外观图像,建立数据平台。基于中值滤波和图像复杂度,提出了改进OTSU算法提取图像的外观缺陷特征,与样本库进行对比,以识别可能的外观缺陷,提高缺陷检测效率。并且,针对缺陷类型分析其影响因素,从而找到产生缺陷的原因,为零件加工过程的改善提供理论依据。同时,搭建了缺陷视觉检测平台,以汽车转向器内部套筒为对象,实现了精密零件外观缺陷在线缺陷检测。     

Improvement of quality performance in manufacturing organizations by minimization of production defects

The work in this paper will present a developed methodology for quality improvement in manufacturing organizations. This methodology comprises a model for the identification of various sources of quality defects on the product; this model would include an analysis tool in order to calculate defect probability, a statistical measurement of quality, and a lean manufacturing tool to prevent the presence of defects on the product. The attribution of defects to their source will lead to a fast and significant definition of the root cause of defects. The techniques described in this paper were developed for an improvement project in a plastic parts painting manufacturing facility of a first-tier supplier to the automotive industry. Data were collected from the manufacturing plant, which indicated that the daily defect rates were significant, ranging between 10% and 15%. These figures gave a clear indication that the number of defects could be significantly reduced to a few parts within the total production. This could be achieved if appropriate manufacturing practices were adopted with the aim of reducing the effect of manufacturing system variables that affect overall quality. A process attribute chart (H-PAC) has been introduced to monitor the defects every hour. Upper and lower control limits were given and an SPC graph is plotted every hour for the three major defects. If the defects go above the upper control limits, the team meets to solve the issues. Over ten weeks’ study after implementing changes, there was a 9% reduction in defects.     

Tool path planning for compound surfaces in spray forming processes

Spray forming is an emerging manufacturing process. The automated tool planning for this process is a nontrivial problem, especially for geometry-complicated parts consisting of multiple freeform surfaces. Existing tool planning approaches are not able to deal with this kind of compound surface. This paper proposes a tool-path planning approach which optimizes the tool motion performance and the thickness uniformity. There are two steps in this approach. The first step partitions the part surface into flat patches based on the topology and normal directions. The second step determines the tool movement patterns and the sweeping directions for each flat patch. Based on the above two steps, optimal tool paths can be calculated. Experimental tests are carried out on automotive body parts and the results validate the proposed approach. Note to Practitioners-This paper was motivated by the problem of automatically planning tool paths for spray forming using Programmable Powdered Preforming Process (P4) technology. However, the proposed approach can be applied to other surface manufacturing applications such as spray painting, spray cleaning, rapid tooling, etc. Existing tool planning approaches are not able to handle complicated, multi-patch surfaces. This paper proposes a methodology to partition complicated surfaces into easy-to-handle patches and generate tool paths with optimized thickness uniformity and tool motion performance. We tested the approach using simulation on sample automotive body parts and proved its feasibility. However, this approach requires that the parts to be sprayed belong to the sheet-metal type so that the part geometry can be analyzed on a plane. In our future research, we will run physical tests on actual parts and investigate the deposition effects on the thickness uniformity.     

基于改进YOLOv4的汽车钢铁零件表面缺陷检测

针对YOLOv4在自建的汽车钢铁零件表面缺陷数据集中检测精度不足的问题,利用深度学习的优势,提出一种基于改进YOLOv4的汽车钢铁零件表面缺陷检测方法。首先采用加权K-means算法确定初始anchors预选框,增强anchors框和特征图尺寸的匹配精度,提高检测效率;然后在YOLOv4主干网络的残差单元中引入SE模块,增加有用特征的权重,抑制无效特征的权重来提高检测精度;最后在76×76的特征图后连接RFB-s模块,增强对小目标信息的特征提取能力。实验结果表明,针对自建汽车零件表面缺陷数据集有无缺陷单类检测问题,改进算法比原始YOLOv4的mAP50值提高了4.3个百分点,对小目标具有更好的检测效果。这说明改进算法能满足针对特定的汽车钢铁零件表面缺陷检测问题下的检测速度和精度要求,有效解决了实际问题。针对COCO数据集多分类问题,改进后模型的mAP50值比原始YOLOv4提高了0.2个百分点,FPS值达到20,说明改进算法能够迁移到其他数据集,验证了该算法的泛化性。     

二层以太网网络体系结构在汽车涂装生产中的应用

当前分析面向汽车生产线网络控制系统的设计规划,对提升汽车行业企业信息化水平具有重大的意义。本文结合汽车涂装生产工艺特点的基础上,提出汽车涂装网络控制系统的框架结构,研究了基于以太网技术的二层网络体系结构在汽车涂装生产中的应用。     

汽车制造生产线上RFID应用模式研究

从企业管理和生产环节两方面对无线射频识别(RFID)的应用需求进行分析,研究RFID在汽车制造生产线上的应用模式,构造一个基于RFID的汽车制造生产线垂直分布式应用模型体系框架,给出各功能模块的实现流程。应用结果证明,该模型可以解决生产过程中存在的信息采集数据缺失和遗漏、人工操作效率低下等问题,满足汽车制造生产线数据信息采集的实时性和准确性要求。     

Expert system to match robots and to synchronize their operations to pick and place large parts

The operation of pick and place large parts is a very common operation on the manufacturing floor. The efficiency of the pick and place operation affects the efficiency of the entire manufacturing floor. Large parts in terms of this research are parts which must be transported by two robots.This paper concludes the development of an expert system and a numerical simulation to assign two available robots to perform the pick and place operations of large parts.The developed expert system consists of a knowledge-base structured in interrelated frames to define large manufacturing systems and an inference-engine to perform the robots matching and their performances monitoring. Matching robots considerations can not be performed by numerical algorithms in real time systems, because they are major computation time consumers. Therefore, unmatched robots can be assigned by the numerical algorithms to perform inefficient pick and place operations. The expert system and the numerical simulation were programmed, and many computer runs were performed to explore the efficiency of the two systems in a large variety of manufacturing systems.The achieved results show that the expert system has no advantage in assigning matched robots to perform the pick and place operations in systems characterized by very short machine process times (0.5 moment to 1 moment). If such short machine process times are relevant, the knowledge-base is updated very frequently, and the inference-engine reasoning processes can not be initiated. For longer machine process times, the frequency of knowledge-base changes is reduced, and the inference-engine reasoning processes can be initiated without delays. Therefore, the advantages of the expert system become significant if machine process times are extended.