Embodiments of welding work cells are disclosed. One embodiment includes a workpiece positioning system, a welding power source, and a welding job sequencer. The workpiece positioning system powers an elevating motion and a rotational motion of a workpiece mounted between a headstock and a tailstock to re-position the workpiece for a next weld to be performed. The welding power source generates welding output power based on a set of welding parameters of the power source. The welding job sequencer commands the workpiece positioning system to re-position the workpiece from a current position to a next position in accordance with a next step of a welding sequence of a welding schedule. The welding job sequencer also commands the welding power source to adjust a current set of welding parameters to a next set of welding parameters in accordance with the next step of the welding sequence of the welding schedule.

A board inspection apparatus system includes a first apparatus, a second apparatus, a third apparatus and an information transfer section. The first apparatus acquires first three-dimensional information of a solder paste on a board, and inspects whether the solder paste is formed good by a first tolerance based on the first three-dimensional information. The second apparatus mounts an electronic component on the board to join the electronic component and the solder paste. The third apparatus acquires second three-dimensional information of a solder joint, and inspects whether the electronic component is mounted good by a second tolerance based on the second three-dimensional information. The information transfer section transfers the first three-dimensional information to the third apparatus, or transfers the second three-dimensional information to the first apparatus. Thus, a more effective inspection condition may be established, and a rate of defect for each apparatus may be greatly reduced.

Various systems and methods are provided that allow a weld sequencer to use a statistical analysis of generated reports to automatically determine weld parameter limits for the welds defined by various functions in a sequence file. For example, the weld sequencer can take reports generated for a specific type of part and statistically analyze the weld data included in the reports according to a set of analysis parameters provided by a user. The weld sequencer can use the statistical analysis to identify and remove outlier data and define a set of weld parameter limits based on the remaining data. The weld parameter limits can define a low limit and/or a high limit for one or more weld parameters associated with a function. The weld sequencer can then update the sequence file to include the weld parameter limits.

An example welding system includes a power supply configured to output welding power; a weld parameter feedback sensor configured to produce a weld feedback parameter corresponding to an actual weld condition during welding; and a welding program comprising: a first weld having first weld parameters; a second weld having second weld parameters, wherein the second weld follows the first weld; a controller configured to, in response to selection of the weld program for performing a welding job on a part: control the power supply to provide the welding power to a first weld operation based the first weld parameters; monitor first feedback from the power supply; control the power supply to provide the welding power to a second weld operation based the second weld parameters; monitor second feedback from the power supply; and determine whether at least one of the welding job or the part is acceptable.

A spot welding system comprises a robot which changes a relative position of a spot welding gun and a workpiece. A control device drives an electrode drive motor so that a movable electrode of the spot welding gun abuts on the workpiece, and is formed so as to perform a position detection control which detects a position of the workpiece based on a position of the movable electrode when a state value of the electrode drive motor deviates from a predetermined range. An operation program includes a workpiece detection parameter for performing the position detection control. The workpiece detection parameter is set at each of welding points in the operation program.

According to one embodiment, a processing system sets a detector to a prescribed position. The detector includes a plurality of detection elements arranged along a first direction and a second direction. The second direction crosses the first direction. The processing system causes the detector to perform a probe of a weld portion of a joined body. The probe includes a transmission of an ultrasonic wave and a detection of a reflected wave. The processing system calculates a center position of the weld portion in a first plane along the first and second directions based on intensity data. The intensity data is of an intensity of the reflected wave obtained by the probe. The processing system performs a position adjustment of moving the detector along the first plane to reduce a distance between the center position and a position of the detector in the first plane.

A method inspects weld quality in-situ. The method obtains a plurality of sequenced images of an in-progress welding process and generates a multi-dimensional data input based on the plurality of sequenced images and/or one or more weld process control parameters. The parameters may include: (i) shield gas flow rate, temperature, and pressure; (ii) voltage, amperage, wire feed rate and temperature (if applicable); (iii) part preheat/inter-pass temperature; and (iv) part and weld torch relative velocity). The method generates defect probability and analytics information by applying one or more computer vision techniques on the multi-dimensional data input. The analytics information includes predictive insights on quality features of the in-progress welding process. The method then generates a 3-D visualization of one or more as-welded regions, based on the analytics information, and the plurality of sequenced images. The 3-D visualization displays the quality features for virtual inspection and/or for determining weld quality.