Digital Twin and web services for robotic deburring in intelligent manufacturing

被引:30
作者
Stan, Liliana [1 ]
Nicolescu, Adrian Florin [1 ]
Pupaza, Cristina [1 ]
Jiga, Gabriel [2 ]
机构
[1] Univ Politehn Bucuresti, Robots & Mfg Syst Dept, Bucharest, Romania
[2] Univ Politehn Bucuresti, Strength Mat Dept, Bucharest, Romania
基金
芬兰科学院;
关键词
Digital twin; Industrial robot; Web services; Robotic deburring; CYBER-PHYSICAL SYSTEMS; INDUSTRIAL ROBOTS;
D O I
10.1007/s10845-022-01928-x
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:2765 / 2781
页数:17
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