Systems and methods for welding asset tracking are disclosed. In some examples, a welding asset tracking system may comprise an asset tracking network of tags, hubs, and/or gateways retained by welding assets within a welding area. The asset tracking network may obtain and/or communicate to an asset tracking server welding data related to one or more of the welding assets, as well as position data obtained via an internal and/or external positioning system. In this way, the welding asset tracking server may continually receive updated information regarding each welding assets identity, location, and/or use. The asset tracking server may additionally send a command to a selected welding asset that causes an interface of the selected welding asset to emit an output that enables an operator to physically identify the welding asset.

A robot system is configured to fabricate three-dimensional (3D) objects using closed-loop, computer vision-based control. The robot system initiates fabrication based on a set of fabrication paths along which material is to be deposited. During deposition of material, the robot system captures video data and processes that data to determine the specific locations where the material is deposited. Based on these locations, the robot system adjusts future deposition locations to compensate for deviations from the fabrication paths. Additionally, because the robot system includes a 6-axis robotic arm, the robot system can deposit material at any locations, along any pathway, or across any surface. Accordingly, the robot system is capable of fabricating a 3D object with multiple non-parallel, non-horizontal, and/or non-planar layers.

A device adjustment instrument is provided with a storage unit for storing standard test piece data corresponding to each of a plurality of standard test pieces which can be manufactured by additive manufacturing devices and a standard parameter set for when the standard test pieces are manufactured, a selection unit for selecting standard test piece data that match modeling specification data of a specified object from a plurality of standard test piece data on the basis of the modeling specification data, and an adjustment unit for generating a modeling parameter set for adjusting an operating condition of the additive manufacturing devices on the basis of the selected standard test piece data and the test modeling result data manufactured by the additive manufacturing devices using the standard parameter set corresponding to the standard test piece data.

Apparatus, systems, and/or methods are disclosed relating to welding systems that monitor welds performed by an operator. In some examples, the welding system monitors one or more welds performed using a welding tool, evaluates characteristics of the one or more welds in comparison to certain predetermined criteria, and determines a performance score for the operator based on the evaluation. In some examples, the characteristics of the one or more welds include the location of each of the one or more welds and/or the order in which the one or more welds are executed. In such an example, the predetermined criteria may include target locations for each of the one or more welds and/or a target order of execution. In some examples, the welding system may respond to deviations from the target locations and/or target order, such as by reducing a performance score, disabling weld operations, providing guidance to the operator, etc.

A laser processing head emits a laser beam to a workpiece that moves during laser processing and includes: optical path changing members that reflect, toward the workpiece, the laser beam emitted from a laser beam output section; a driver that changes posture of each of the optical path changing members; a control unit that controls the driver; and a memory device that stores target path information indicating a target path of the laser processing, in which the control unit receives information relating to a relative position of the workpiece with respect to the laser processing head, and controls the driver on the basis of the received information relating to the relative position and the target path information to perform the laser processing along the target path.

Systems and methods for weld monitoring systems with unknown downtime disabling are described. In some examples, a local monitoring station may perform activity tracking as part of a larger weld monitoring system. A welding device may send welding data to the local monitoring system, which may be used to determine a current activity. A user may also manually input an activity to use as the current activity. If the local monitoring station is unable to determine a current activity from the welding data or user input, then the local monitoring station determines that an unknown downtime has occurred. If the local monitoring station cannot determine a reason for the unknown downtime, the welding device may be disabled until the user provides a reason for the unknown downtime.

A method for automatically determining optimum welding parameters for carrying out a weld on a workpiece carries out test welds on test workpieces along test welding tracks, and at each test weld a welding parameter is changed automatically along the test welding track from a predefined initial value to a predefined final value. Each resulting test weld seam is measured along the test welding track with a sensor, and a sensor signal is received. A quality parameter characterizing each test weld seam is calculated from the sensor signal. A quality function for characterizing the test weld seam quality in accordance with the changed weld parameters is calculated from the quality parameter. An optimum quality function is ascertained, and the values for the optimum welding parameters are defined based on each quality parameter at this quality function optimum and the corresponding test weld track locations and saved.

An automated welding system includes a mounting platform configured to receive an object, a welding tool, an imaging device configured to acquire at least one image associated with the object, and a controller. The controller is configured to receive the at least one acquired image, analyze at least one pixel in the at least one acquired image, identify, based upon the analyzing, an area to be welded in the at least one acquired image, wherein the area to be welded includes a defect, and generate, based upon the identifying, control instructions for controlling at least one of the mounting platform and the welding tool to weld the area to be welded.

A method for establishing welding parameters for a welding process guides a welding torch along a predetermined welding path over the workpiece to be worked and sets welding parameters based on the respective path position for workpiece working. Before establishing the parameters, ideal parameters are determined by test welding processes on test workpieces along test welding paths, with a respective specific test workpiece position and arrangement relative to the gravitational acceleration vector and a specific tangential vector of the test path, and are stored. The parameters at the respective path position are established based on workpiece position and arrangement at the time relative to the welding path gravitational acceleration vector and tangential vector at the time by interpolation of the stored ideal parameter values for the determined positions and arrangements of the test workpieces relative to the gravitational acceleration vector and the specific tangential vectors of the test paths.

An automated welding system includes a mounting platform, a welding tool, an imaging device configured to acquire data associated with an object, and a controller. The controller is configured to receive the acquired data, determine an area to be welded in the acquired data, retrieve stored master model data associated with the object, and compare the acquired data to the stored master model data to identify a master model area in the acquired data. The controller is also configured to mask the master model area in the acquired data, such that the master model area is excluded from the area to be welded, and generate control instructions for controlling at least one of the mounting platform and the welding tool to weld the area to be welded.