Project Code: 34246
Start date and planned duration: February 2021, 12 months
- Implement numerical models for welding process parameter optimisation along with the integration with the robot control system, using robotic MIG/MAG welding and AM.
- Develop an automated process monitoring system (laser scanning) along with the integration with the numerical models.
- Develop a system which integrates the developed numerical modelling and process monitoring units with the arc welding robot.
This project is a continuation of the work carried out in Project 31011, “Automated Process Parameter Optimisation for Robotic Arc Welding” which was placed on hold in 2020 due to disruption caused by the COVID-19 pandemic.
Robots are widely used in arc welding production, providing the benefits of increased productivity and improved quality. Robotic arc welding has played an important role in the automotive, off-road vehicle and ship building sectors for decades. Applications have rapidly developed in aerospace, rail, power generation and oil and gas structures. Besides welding, additive manufacturing (AM) using arc processes, which applies robotic technology, has become increasingly popular due to strong interest from industry.
Owing to the complex physics behind the arc processes, when introducing a new welded product, the majority of time is often spent on developing suitable welding parameters. Identification of parameters is typically based on trial-and-error, incorporating the welding engineers’ knowledge and experience. Correct weld parameters not only dominate the weld formation, welding quality, mechanical properties and other key aspects of the joints, but also directly influence productivity and cost. The cost of this process for robotic welding has been identified as a barrier to the industrial exploitation of robotic arc welding.
The project concept is a robotic arc process with the capability of automatic parameter optimisation based on numerical modelling and real-time process monitoring. Validated numerical finite element (FE) and computational fluid dynamics (CFD) models will be applied to calculate and optimise the welding sequence and parameters for specified welds or AM deposits. This information will be used by the robot controller to perform the arc process, which will be monitored and measured autonomously. If an unsatisfactory weld or deposit is detected, the monitoring data will be fed into the numerical models to update the process parameters in order to deliver the desired weld or deposit.
The proposed concept represents an important step towards intelligent automation for welding and additive manufacture. The project will develop the concept to a physical demonstrator system, and produce a novel approach fully utilising the benefits of welding automation, significantly reducing material wastage and effort during parameter development. This will enable intelligent and adaptive control for robotic arc welding and AM, representing a step forward in robotic fabrication. It is anticipated that the concept can be adapted to other robotic welding and material processing processes, e.g. laser beam welding, surfacing and laser additive manufacturing.
Equipment, Consumables and Materials
Construction and Engineering
Oil and Gas
Benefits to Industry
A successful outcome will significantly reduce the requirements for welding trials and manual input during development and qualification of new arc welding processes. Industry will benefit from significantly reduced materials wastage and effort during parameter development, as well as reduced lead times. Intelligent and adaptive control for robotic arc welding and AM, will advance the state-of-the-art of robotic fabrication and allow industry to exploit the benefits of increased productivity and reproducibility.
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