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智能制造中用于机器人去毛刺的数字孪生与网络服务。

Digital Twin and web services for robotic deburring in intelligent manufacturing.

作者信息

Stan Liliana, Nicolescu Adrian Florin, Pupăză Cristina, Jiga Gabriel

机构信息

Robots and Manufacturing Systems Department, Politehnica University of Bucharest, Bucharest, Romania.

Strength of Materials Department, Politehnica University of Bucharest, Bucharest, Romania.

出版信息

J Intell Manuf. 2023;34(6):2765-2781. doi: 10.1007/s10845-022-01928-x. Epub 2022 May 26.

Abstract

The development of modern manufacturing requires key solutions to enhance the intelligence of manufacturing such as digitalization, real-time monitoring, or simulation techniques. For smart robotic manufacturing, the modern approach regarding robot programming and process planning aims for both high efficiency and energy-awareness. During the design and manufacturing stages, optimization becomes crucial and can be fulfilled by means of appropriate digital manufacturing tools. This paper presents the development of a Digital Twin for a robotic deburring workcell along with the process planning and robot programming. Considering a large size workpiece, a new robot programming solution was implemented, based on image processing to safely re-machine only areas where burrs could not be completely removed in the main deburring routine. The work also covers the development of a new web platform to remotely monitor the robotic workcell, to trigger alerts for unexpected events and to allow the control to authorized personnel enabled by the employment of robot web services following an architectural RESTful style which establishes a communication link to the robot virtual controller. The aim of this research is to integrate the Digital Twin with the innovative proposals of Industry 4.0, offering a project-based model of smart robotic manufacturing and experience concepts such as Cyber-Physical System, digitalization, data acquisition, continuous monitoring, and intelligent solutions in a novel approach. Furthermore, the work covers energy consumption strategies for energy-aware robotic manufacturing. Finally, the results of an energy-efficient motion planning along with signal-based scheduling optimization of the robotic deburring cell are discussed.

摘要

现代制造业的发展需要关键解决方案来提升制造的智能化水平,如数字化、实时监测或仿真技术。对于智能机器人制造而言,关于机器人编程和工艺规划的现代方法旨在实现高效率和能源意识。在设计和制造阶段,优化变得至关重要,并且可以通过适当的数字制造工具来实现。本文介绍了用于机器人去毛刺工作单元的数字孪生体的开发以及工艺规划和机器人编程。考虑到大型工件,实施了一种基于图像处理的新机器人编程解决方案,以便仅对在主要去毛刺程序中毛刺无法完全去除的区域进行安全的再加工。这项工作还包括开发一个新的网络平台,用于远程监控机器人工作单元、触发意外事件警报,并通过采用遵循RESTful架构风格的机器人网络服务,允许授权人员进行控制,该架构风格建立了与机器人虚拟控制器的通信链接。本研究的目的是以新颖的方式将数字孪生体与工业4.0的创新理念相结合,提供基于项目的智能机器人制造模型以及诸如网络物理系统、数字化、数据采集、持续监测和智能解决方案等体验概念。此外,该工作还涵盖了能源感知型机器人制造的能耗策略。最后,讨论了机器人去毛刺单元的节能运动规划结果以及基于信号的调度优化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ecf/9135312/b029fd03ae88/10845_2022_1928_Fig1_HTML.jpg

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