Digital Twin and web services for robotic deburring in intelligent manufacturing

Area of Science:

• Robotics and Automation
• Manufacturing Engineering
• Industry 4.0

Background:

• Modern manufacturing demands intelligent solutions like digitalization and real-time monitoring.
• Smart robotic manufacturing requires efficient and energy-aware robot programming and process planning.
• Optimization during design and manufacturing is critical and achieved through digital tools.

Purpose of the Study:

• To develop a Digital Twin for a robotic deburring workcell, integrating Industry 4.0 principles.
• To implement novel robot programming and process planning for enhanced efficiency and energy awareness.
• To create a web platform for remote monitoring, alerting, and control of the robotic workcell.

Main Methods:

• Development of a Digital Twin for a robotic deburring workcell.
• Implementation of an image processing-based robot programming solution for targeted re-machining.
• Creation of a web platform utilizing RESTful web services for remote monitoring and control.
• Integration of energy consumption strategies and energy-efficient motion planning.

Main Results:

• A functional Digital Twin for a robotic deburring workcell was successfully developed.
• A new robot programming method using image processing was implemented for efficient burr removal.
• A web platform enabling remote monitoring and control of the robotic cell was established.
• Energy-efficient motion planning and scheduling optimizations were achieved.

Conclusions:

• The integration of Digital Twin technology with Industry 4.0 concepts enhances smart robotic manufacturing.
• The developed system offers a project-based model for experiencing Cyber-Physical Systems and intelligent solutions.
• The research demonstrates effective strategies for energy-aware robotic manufacturing through optimized planning and control.