The automated welding industry is experiencing significant growth, with a predicted value of USD 10.8 billion by 2026. This growth is driven by sectors such as automotive, marine, nuclear, petrochemical, and defense. The demands of Industry 4.0 have also led to the development of intelligent and flexible sensor-enabled robotic welding systems.
As production rates increase, there is a need for fast and accurate Non-Destructive Evaluation (NDE) methods to replace time-consuming manual inspections. This article explores the development and deployment of a sensor-enabled multi-robot system for automated welding and in-process ultrasonic NDE.
The system is based on a National Instruments cRIO 9038 real-time embedded controller, which features a real-time processor and a Field-Programmable Gate Array (FPGA) for parallel computations. The system includes two industrial manipulators: a KUKA KR5 Arc HW as the Welding Robot (WR) and a KUKA AGILUS KR3 as the Inspection Robot (IR).
Additional hardware components include a welding power source, a welding torch, a wire feeder, a laser profiler, a weld monitoring camera, and thermocouples for temperature measurement. The software is developed in LabVIEW, utilizing the JKI state machine and parallel real-time Timed Loops for flexibility and fast response times.
The system employs full external positional control of the robots, using a correction-based Robot Sensor Interface (RSI) motion. The robot controller does not hold any pre-programmed path; instead, the end-effector position is updated on-the-fly through positional corrections. Trajectory planning is done in real-time, with linear motion controller (LMC) and adaptive motion controller (AMC) algorithms working together.
The LMC generates a straight-line trajectory between the current position and the target position, while the AMC provides instantaneous adaptive corrections based on sensory input. This approach allows for flexible and adaptive robotic motion, mimicking manual welding techniques such as weaving.
The system’s inspection capabilities are demonstrated at three different stages of the manufacturing process: after all welding passes are complete, between individual welding passes, and during live-arc welding deposition. The system utilizes a high-temperature Phased Array Ultrasonic Transducer (PAUT) roller probe for ultrasonic inspection.
It allows for the inspection of multi-pass welded samples and can detect artificially induced defects in real-time. The system offers early defect detection, reducing the delay between defect formation and discovery. This enables in-process weld repair, leading to higher production efficiency, reduced rework rates, and lower production costs.
The sensor-enabled multi-robot system offers several advantages over conventional inspection methods. It provides greater positional accuracy, repeatability, and inspection rates compared to human operators. The system can be deployed in hazardous environments and limited-access areas, improving safety and reducing the risk of workplace injuries.
The real-time control of the welding process through live-arc ultrasonic methods allows for immediate adjustments and ensures consistent weld quality. However, there are challenges to overcome, such as accurate position tracking, integration of different sensors, and optimizing the system for different welding geometries and materials.
The sensor-enabled multi-robot system has the potential for wide adoption in the welding industry. By integrating NDE into the manufacturing process, early defect detection can be achieved, reducing production inefficiencies and costs.
The system enables in-process weld repair, leading to higher production efficiency and improved component quality. It has applications in various sectors, including automotive, marine, aerospace, and construction. The system’s flexibility and adaptability make it well-suited for different welding geometries and materials.
The development of a sensor-enabled multi-robot system for automated welding and in-process ultrasonic NDE offers significant advancements in the welding industry. The system provides real-time control, adaptive motion, and early defect detection capabilities, leading to higher production efficiency and improved weld quality.
With further research and development, this technology has the potential to revolutionize the welding industry by reducing production costs, improving safety, and enabling right-first-time welds.
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