A robotic electric arc welding system includes a welding torch, a welding robot configured to manipulate the welding torch during a welding operation, a robot controller operatively connected to the welding robot to control weaving movements of the welding torch along a weld seam and at a weave frequency and weave period, and a welding power supply operatively connected to the welding torch to control a welding waveform, and operatively connected to the robot controller for communication therewith. The welding power supply is configured to sample a plurality of weld parameters during a sampling period of the welding operation and form an analysis packet, and process the analysis packet to generate a weld quality score, wherein the welding power supply obtains the weave frequency or the weave period and automatically adjusts the sampling period for forming the analysis packet based on the weave frequency or the weave period.

A system and method of electric arc welding that includes a welding apparatus having an electric arc welder torch with sensors to determine the absolute position of the torch tip and the relative position of the torch tip to the weld joint during automatic welding. Combining absolute and relative positional data can be used to adjust the path of the robot during automated or robotic welding in response to variations in the weld joint.

Embodiments of systems and methods for supporting predictive and preventative maintenance are disclosed. One embodiment includes manufacturing cells within a manufacturing environment, where each manufacturing cell includes a cell controller and welding equipment, cutting equipment, and/or additive manufacturing equipment. A communication network supports data communications between a central controller and the cell controller of each of the manufacturing cells. The central controller collects cell data from the cell controller of each of the manufacturing cells, via the communication network. The cell data is related to the operation, performance, and/or servicing of a same component type of each of the manufacturing cells to form a set of aggregated cell data for the component type. The central controller also analyzes the set of aggregated cell data to generate a predictive model related to future maintenance of the component type.

Embodiments of systems and methods for supporting weld quality across a manufacturing environment are disclosed. One embodiment includes a manufacturing cell supporting welding of a sequence of welds to manufacture a workpiece. The manufacturing cell includes robotic welding equipment to make robotic welds as at least a portion of manufacturing a workpiece. The manufacturing cell also includes non-robotic welding equipment configured to allow a human operator to make non-robotic welds as at least a portion of manufacturing the workpiece. The manufacturing cell further includes a weld sequence controller configured to control timing associated with making the robotic welds and the non-robotic welds as a sequence of welds to manufacture the workpiece.

A cell controller includes a plurality of sensors for detecting the state of a plurality of manufacturing machines, a state storing unit for storing the state of each manufacturing machine, a breakdown information acquiring unit for acquiring breakdown information of each manufacturing machine, an input unit for inputting recovery operation information when each manufacturing machine stops, a recovery operation information storing unit for storing the recovery operation information of each manufacturing machine, and a correlation data generating unit. The correlation data generating unit generates correlation data obtained by correlating the breakdown information acquired by the breakdown information acquiring unit with the recovery operation information stored by the recovery operation information storing unit in each manufacturing machine, and transmits the same to the database. These configurations enable an operator to easily acquire, when a manufacturing machine in a manufacturing cell stops, a recovery operation most appropriate to the manufacturing machine.

A system and method of electric arc welding that includes a welding apparatus having an electric arc welder torch with sensors to determine the absolute position of the torch tip and the relative position of the torch tip to the weld joint during automatic welding. Combining absolute and relative positional data can be used to adjust the path of the robot during automated or robotic welding in response to variations in the weld joint.

A robotic electric arc welding system includes a welding torch, a welding robot configured to manipulate the welding torch during a welding operation, a robot controller operatively connected to the welding robot to control weaving movements of the welding torch along a weld seam and at a weave frequency and weave period, and a welding power supply operatively connected to the welding torch to control a welding waveform, and operatively connected to the robot controller for communication therewith. The welding power supply is configured to sample a plurality of weld parameters during a sampling period of the welding operation and form an analysis packet, and process the analysis packet to generate a weld quality score, wherein the welding power supply obtains the weave frequency or the weave period and automatically adjusts the sampling period for forming the analysis packet based on the weave frequency or the weave period.

Embodiments of systems and methods for supporting weld quality across a manufacturing environment are disclosed. One embodiment includes manufacturing cells within a manufacturing environment, where each manufacturing cell includes a cell controller and welding equipment. A communication network supports data communications between a central controller and the cell controller of each of the manufacturing cells. The central controller collects actual weld parameter data from the cell controller of each manufacturing cell, via the communication network, to form aggregated weld parameter data for a same type of workpiece being welded in each of the manufacturing cells. The central controller analyzes the aggregated weld parameter data to generate updated weld settings. The updated weld settings are communicated from the central controller to the cell controller of each of the manufacturing cells via the communication network.

Embodiments of systems and methods for supporting predictive and preventative maintenance are disclosed. One embodiment includes manufacturing cells within a manufacturing environment, where each manufacturing cell includes a cell controller and welding equipment, cutting equipment, and/or additive manufacturing equipment. A communication network supports data communications between a central controller and the cell controller of each of the manufacturing cells. The central controller collects cell data from the cell controller of each of the manufacturing cells, via the communication network. The cell data is related to the operation, performance, and/or servicing of a same component type of each of the manufacturing cells to form a set of aggregated cell data for the component type. The central controller also analyzes the set of aggregated cell data to generate a predictive model related to future maintenance of the component type.

A cell controller includes a plurality of sensors for detecting the state of a plurality of manufacturing machines, a state storing unit for storing the state of each manufacturing machine, a breakdown information acquiring unit for acquiring breakdown information of each manufacturing machine, an input unit for inputting recovery operation information when each manufacturing machine stops, a recovery operation information storing unit for storing the recovery operation information of each manufacturing machine, and a correlation data generating unit. The correlation data generating unit generates correlation data obtained by correlating the breakdown information acquired by the breakdown information acquiring unit with the recovery operation information stored by the recovery operation information storing unit in each manufacturing machine, and transmits the same to the database. These configurations enable an operator to easily acquire, when a manufacturing machine in a manufacturing cell stops, a recovery operation most appropriate to the manufacturing machine.