Intelligent 3D seam tracking and adaptable weld process control for robotic TIG welding

Tungsten Inert Gas (TIG) welding is extensively used in aerospace applications, due to its unique ability to produce higher quality welds compared to other shielded arc welding types. However, most TIG welding is performed manually and has not achieved the levels of automation that other welding techniques have. This is mostly attributed to the lack of process knowledge and adaptability to complexities, such as mismatches due to part fit-up. Recent advances in automation have enabled the use of industrial robots for complex tasks that require intelligent decision making, predominantly through sensors. Applications such as TIG welding of aerospace components require tight tolerances and need intelligent decision making capability to accommodate any unexpected variation and to carry out welding of complex geometries. Such decision making procedures must be based on the feedback about the weld profile geometry. In this thesis, a real-time position based closed loop system was developed with a six axis industrial robot (KUKA KR 16) and a laser triangulation based sensor (Micro-Epsilon Scan control 2900-25). [Continues.

Integrated sensors for robotic laser welding

A welding head is under development with integrated sensory systems for robotic laser welding applications. Robotic laser welding requires sensory systems that are capable to accurately guide the welding head over a seam in three-dimensional space and provide information about the welding process as well as the quality of the welding result. In this paper the focus is on seam tracking. It is difficult to measure three-dimensional parameters of a ream during a robotic laser welding task, especially when sharp corners are present. The proposed sensory system is capable to provide the three dimensional parameters of a seam in one measurement and guide robots over sharp corners

Robotic and automatic welding development at the Marshall Space Flight Center

Welding automation is the key to two major development programs to improve quality and reduce the cost of manufacturing space hardware currently undertaken by the Materials and Processes Laboratory of the NASA Marshall Space Flight Center. Variable polarity plasma arc welding has demonstrated its effectiveness on class 1 aluminum welding in external tank production. More than three miles of welds were completed without an internal defect. Much of this success can be credited to automation developments which stabilize the process. Robotic manipulation technology is under development for automation of welds on the Space Shuttle's main engines utilizing pathfinder systems in development of tooling and sensors for the production applications. The overall approach to welding automation development undertaken is outlined. Advanced sensors and control systems methodologies are described that combine to make aerospace quality welds with a minimum of dependence on operator skill

Sensor integration for robotic laser welding processes

The use of robotic laser welding is increasing among industrial applications, because of its ability to weld objects in three dimensions. Robotic laser welding involves three sub-processes: seam detection and tracking, welding process control, and weld seam inspection. Usually, for each sub-process, a separate sensory system is required. The use of separate sensory systems leads to heavy and bulky tools, in contrast to compact and light sensory systems that are needed to reach sufficient accuracy and accessibility. In the solution presented in this paper all three subprocesses are integrated in one compact multipurpose welding head. This multi-purpose tool is under development and consists of a laser welding head, with integrated sensors for seam detection and inspection, while also carrying interfaces for process control. It can provide the relative position of the tool and the work piece in three-dimensional space. Additionally, it can cope with the occurrence of sharp corners along a three-dimensional weld path, which are difficult to detect and weld with conventional equipment due to measurement errors and robot dynamics. In this paper the process of seam detection will be mainly elaborated

Supporting robotic welding of aluminium with a laser line scanner-based trigger definition method

Automation and the use of robots for welding operations is an important research topic. Being able to automate and, thus, save time for setting up and using robotic welding for complex, large-scale structures made of reflective materials, such as aluminium, will provide clear economic and competitive advantages. However, challenges coming from the ability to accurately detect and calibrate the robot for a given physical workpiece in addition to noises, such as the reflections, make it hard to develop and demonstrate a feasible automation solution. This paper proposes combining laser line scanning technology with CAD-based analysis of a workpiece geometry to support the identification of relevant elements of the workpiece in the physical world and thus support welding operations. An extendable trigger definition method is proposed to identify features of interest in a workpiece. The method can potentially support the execution of welding sequences, which in our case can be represented as a sequence of triggers that have to be observed and followed at the robot runtime to weld the workpiece together.acceptedVersio

Robotic friction stir welding—Seam-tracking control, force control and process supervision

Purpose – This study aims to enable robotic friction stir welding (FSW) in practice. The use of robots has hitherto been limited, because of the large contact forces necessary for FSW. These forces are detrimental for the position accuracy of the robot. In this context, it is not sufficient to rely on the robot’s internal sensors for positioning. This paper describes and evaluates a new method for overcoming this issue.Design/methodology/approach – A closed-loop robot control system for seam-tracking control and force control, running and recording data in real-time operation, was developed. The complete system was experimentally verified. External position measurements were obtained from a laser seam tracker and deviations from the seam were compensated for, using feedback of the measurements to a position controller.Findings – The proposed system was shown to be working well in overcoming position error. The system is flexible and reconfigurable for batch and short production runs. The welds were free of defects and had beneficial mechanical properties.Research limitations/implications – In the experiments, the laser seam tracker was used both for control feedback and for performance evaluation. For evaluation, it would be better to use yet another external sensor for position measurements, providing ground truth.Practical implications – These results imply that robotic FSW is practically realizable, with the accuracy requirements fulfilled.Originality/value – The method proposed in this research yields very accurate seam tracking as compared to previous research. This accuracy, in turn, is crucial for the quality of the resulting material.Keywords Friction stir welding, Robotics, Force control, Seam-tracking control, Control, Sensors, Robot weldin