Adaptive human-robot collaboration in wind turbine manufacturing using digital twins

Area of Science:

• Manufacturing Automation
• Robotics in Industry
• Renewable Energy Technology

Background:

• The wind energy sector is experiencing rapid growth, with turbines increasing in capacity and size.
• Conventional automation is challenging for large-scale wind turbine manufacturing due to frequent design changes and complex assembly tasks.
• Manual assembly of large wind turbine components presents significant challenges to human capabilities.

Purpose of the Study:

• To propose and develop a hybrid automation approach for wind turbine manufacturing using collaborative robots (cobots).
• To reduce manufacturing costs, increase production speed, and enhance working conditions in wind turbine assembly.
• To introduce a framework for robot design, commissioning, and operation using digital twin technology.

Main Methods:

• Integration of mobile collaborative robots (cobots) into the wind turbine assembly process.
• Development of a case study with a leading global wind turbine manufacturer.
• Implementation of a digital twin framework for robot lifecycle management.
• Creation of a human-robot interface utilizing smartwatches for seamless interaction.

Main Results:

• Demonstrated the feasibility of a hybrid human-robot system for automating wind turbine manufacturing.
• Identified key areas within the manufacturing process suitable for collaborative automation.
• Successfully developed and tested a mobile robotic assistant for collaboration with human operators.
• Showcased the scalability of the developed system for other large-component manufacturing industries.

Conclusions:

• Collaborative robots offer a viable solution to automate complex and labor-intensive tasks in wind turbine manufacturing.
• The digital twin framework and smartwatch interface facilitate efficient design, operation, and human-robot interaction.
• The proposed hybrid automation approach can be adapted for various large-scale manufacturing applications, improving efficiency and safety.