Technology processor for enhancing CAD/CAM-systems for robot-based incremental sheet metal forming

用于增强 CAD/CAM 系统的技术处理器,用于基于机器人的渐进式金属板材成型

基本信息

项目摘要

Roboforming is a kinematically controlled robot-based incremental sheet metal forming process where two cooperating industrial robots lead a forming and a supporting tool to form sheet metals. It is characterized by the use of simple, universal tools and the abandonment of geometry-specific dies. The forming of sheet metal components can be realized by means of two strategies: using a forming tool combined with either a peripherally acting supporting tool or a locally acting supporting tool. For this purpose, only two CAD-model-based tool paths are needed. Thus, Roboforming is particularly suitable for the fast and low-cost manufacturing of small batch sizes and prototypes. The currently remaining geometrical deviations mainly result from the non-optimal forming force absorption due to deficits in the positioning of the supporting tool. In addition, there is a conflict between the surface quality of the formed sheet metals and the process time. The aim of this research project is to further develop existing forming strategies and to individually consider areas of the CAD-model during the path planning in order to successfully increase the geometric accuracy and to solve the conflict described. A variable adjustment of the infeed and the speed of the robots to the characteristics of the different areas will already reduce the process time and, at the same time, improve the surface quality. An increase in the geometric accuracy will be reached by exploiting the flexibility and potential of the tools that can be freely placed to each other. Changing the tasks of 'supporting' and 'forming' in the forming area will lead to a better forming result of convex-concave structures. A further development of the peripheral strategy by an individual positioning of the supporting tool on the sheet will also improve the forming force absorption and reduce the subsequent deformation of already formed areas. The above-listed necessary technology-specific parameters of a Roboforming process need to be considered and implemented in the path planning process. However, the available CAD/CAM solutions are not able to satisfactorily meet these requirements. For this reason, a Roboforming-specific technology processor is to be developed as an extension of available CAD/CAM solutions as part of the research project. The technology processor is to have suitable algorithms to realize the optimizations of the forming strategies and possibilities to assign an individual infeed and speed to different areas of the component. It is now possible to gain a previously unattainable increase in the complexity and quality of formed components and a reduction of the process time by the described optimizations and the integrated CAD/CAM approach in the form of an extending technology processor.
RoboForming是一种基于运动学的基于机器人的增量钣金形成过程,其中两个合作的工业机器人会导致形成和支撑工具形成薄板金属。它的特征是使用简单的通用工具和放弃了特定的模具。可以通过两种策略来实现钣金组件的形成:使用形成工具与外围表演支撑工具或本地作用支持工具相结合。为此,仅需要两个基于CAD模型的工具路径。因此,roboforming特别适合小批量和原型的快速和低成本制造。当前剩余的几何偏差主要是由于支持工具的定位缺陷引起的非最佳形成力吸收。此外,形成的钣金的表面质量与过程时间之间存在冲突。该研究项目的目的是进一步制定现有的形成策略,并在路径计划期间单独考虑CAD模型的区域,以便成功提高几何准确性并解决所描述的冲突。侵蚀和机器人对不同区域特征的速度的可变调整将已经减少过程时间,同时提高了表面质量。通过利用可以自由放置的工具的灵活性和潜力来达到几何精度的提高。更改组合区域中“支撑”和“形成”的任务将导致凸孔结构的更好形成结果。通过在表上的支撑工具的个别定位对外围策略的进一步发展也将改善形成力的吸收并减少随后形成的区域的变形。在路径规划过程中需要考虑和实施roboforming过程的上述必要的技术特定参数。但是,可用的CAD/CAM解决方案无法令人满意地满足这些要求。因此,作为研究项目的一部分,将开发一个针对特定于RoboForming的技术处理器作为可用CAD/CAM解决方案的扩展。该技术处理器应具有合适的算法,以实现形成策略和可能性的优化,以将单个进发和速度分配到组件的不同领域。现在,可以通过所描述的优化和以扩展技术处理器的形式通过所描述的优化和集成的CAD/CAM方法来获得以前无法实现的成分复杂性和质量的提高,并减少过程时间。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Professor Dr.-Ing. Bernd Kuhlenkötter, since 9/2016其他文献

Professor Dr.-Ing. Bernd Kuhlenkötter, since 9/2016的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Professor Dr.-Ing. Bernd Kuhlenkötter, since 9/2016', 18)}}的其他基金

Local heating in robot-based incremental sheet metal forming
基于机器人的增量金属板材成形中的局部加热
  • 批准号:
    186246236
  • 财政年份:
    2011
  • 资助金额:
    --
  • 项目类别:
    Research Grants

相似国自然基金

基于形式化方法的处理器安全验证
  • 批准号:
    62372258
  • 批准年份:
    2023
  • 资助金额:
    50 万元
  • 项目类别:
    面上项目
面向国产处理器的数值计算程序超优化编译技术研究
  • 批准号:
    62372046
  • 批准年份:
    2023
  • 资助金额:
    50 万元
  • 项目类别:
    面上项目
铌酸锂可编程光子处理器原理和器件研究
  • 批准号:
    12304418
  • 批准年份:
    2023
  • 资助金额:
    30 万元
  • 项目类别:
    青年科学基金项目
基于指令集的类脑处理器体系结构和编译优化关键技术研究
  • 批准号:
    62372461
  • 批准年份:
    2023
  • 资助金额:
    50.00 万元
  • 项目类别:
    面上项目
面向多核混合关键实时系统的高性能资源共享技术研究
  • 批准号:
    62302533
  • 批准年份:
    2023
  • 资助金额:
    30.00 万元
  • 项目类别:
    青年科学基金项目

相似海外基金

CAREER: Frequency Agile Real-Time Reconfigurable RF Analog Co-Processor Design Leveraging Engineered Nanoparticle and 3D Printing
职业:利用工程纳米颗粒和 3D 打印进行频率捷变实时可重构射频模拟协处理器设计
  • 批准号:
    2340268
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Continuing Grant
Scalable semiconductor quantum processor with flip chip bonding technology
采用倒装芯片接合技术的可扩展半导体量子处理器
  • 批准号:
    IM230100396
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
    Mid-Career Industry Fellowships
Elements: MVP: Open-Source AI-Powered MicroVessel Processor for Next-Generation Vascular Imaging Data
要素:MVP:用于下一代血管成像数据的开源人工智能微血管处理器
  • 批准号:
    2311245
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
256-channel Digital Neural Signal Processor Real-Time Data Acquisition System
256通道数字神经信号处理器实时数据采集系统
  • 批准号:
    10630883
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
Integrated Event-Based SoC: Revolutionizing Sensor and AI Processor Performance with Low-Latency, Energy-Efficient Neuromorphic Computing
基于事件的集成 SoC:通过低延迟、节能的神经拟态计算彻底改变传感器和 AI 处理器的性能
  • 批准号:
    10072308
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
    Grant for R&D
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了