Virtual reality and real welding training system and method

Information

  • Patent Grant
  • 10083627
  • Patent Number
    10,083,627
  • Date Filed
    Wednesday, October 29, 2014
    9 years ago
  • Date Issued
    Tuesday, September 25, 2018
    5 years ago
Abstract
A virtual welding station includes a virtual sequencer for simulating different welding techniques and non-welding operations. The virtual welding station can be used to train an operator on the production of complete assemblies.
Description
FIELD

The present invention relates to the art of welding station simulation and more particularly to a virtual sequencer that simulates semi-automatic welding of complex assemblies.


BACKGROUND

Learning how to perform all of the steps required in a welding station, including the steps that are in addition to welding, traditionally takes many hours of instruction, training, and practice.


There are many different types of operations that can be learned, including various welding and non-welding operations. Typically, the steps of a welding station are learned by a student operator at a real welding station performing welding operations on real metal pieces. Such real-world training can tie up scarce welding resources and use up limited welding materials. Training while welding on real production parts can be costly as an operator learns the assembly operation. Training time on real production parts typically requires two operators (costly) and potentially generates scrap, rework, or low quality assemblies.


Recently, however, the idea of training using welding simulations has become more popular. Some welding simulations are implemented via personal computers, on-line via the Internet, or even as virtual welders. However, conventional welding simulations tend to be limited to single welds in their training focus and typically involve one welding technique at a time. Conventional virtual reality training generally only involves individual welds and does not prepare, or train, the operator how to produce a complete assembly that involves multiple welding and/or assembly steps. In practice, unlike in these simulators, there are many different welding techniques and non-welding operations required at a welding station that are needed to create an entire, complete welded assembly. Thus, there is an unmet need for welding simulation systems and methods that can effectively simulate the production of complete assemblies.


SUMMARY

The general inventive concepts encompass virtual welding systems (and related methods), including the illustrative systems and methods disclosed and suggested herein.


In one exemplary embodiment, a virtual welding system comprises: a logic processor based subsystem operable to execute coded instructions for generating an interactive welding environment that emulates welding activity on a virtual weld joint defined by at least one of a welding coupon and a sample part; a virtual sequence controller operatively connected to the logic processor based subsystem for implementing a virtual sequence; displaying means operatively connected to the logic processor based subsystem for visually depicting the interactive welding environment including the virtual weld joint; an input device for performing virtual welding activity on the virtual weld joint in real time; and a spatial tracker comprising one or more sensors adapted to track movement of the input device in real time for communicating data about the movement of the input device to the logic processor based subsystem.


In one exemplary embodiment, the virtual welding system further comprises a user interface for a user to provide input to the virtual welding system.


In one exemplary embodiment, the logic processor based subsystem is housed within a simulated welding console that is sized and shaped to approximate a welding power source.


In one exemplary embodiment, the logic processor based subsystem implements the virtual sequence controller.


In one exemplary embodiment, the virtual sequence controller comprises a microprocessor, a sequence control program, and a memory. The memory stores one or more state table files.


In one exemplary embodiment, the virtual welding system further comprises a virtual sequence configuration tool. The virtual sequence configuration tool allows a user to modify one of the existing state table files. The virtual sequence configuration tool allows a user to create a new state table file, for storing in the memory.


In one exemplary embodiment, the virtual sequence is defined by at least one of the state table files.


In one exemplary embodiment, a user selects one of the state table files based on a task to be performed. In one exemplary embodiment, the task is production of a complete virtual assembly.


In one exemplary embodiment, the virtual sequence includes a plurality of operations to be performed in order, each operation intended to achieve a particular state.


In one exemplary embodiment, at least one of the operations is a manual operation to be performed by the user. In one exemplary embodiment, the manual operation is one of providing user information, retrieving a part, providing part information, placing a part, securing a part, and providing assembly information.


In one exemplary embodiment, the virtual welding system further comprises a virtual sequence display means. The virtual sequence display means displays information on the manual operation.


In one exemplary embodiment, at least one of the operations is an automatic operation to be performed by the virtual welding system. In one exemplary embodiment, the automatic operation is one of specifying a weld process, specifying a gas type, specifying a gas flow rate, specifying a stick electrode type, specifying a flux cored wire type, specifying a wire feed speed, specifying a voltage level, specifying an amperage, specifying a polarity, and specifying a background environment for the interactive welding environment.


In one exemplary embodiment, at least one of the operations is a manual operation to be performed by the user; and at least one of the operations is an automatic operation to be performed by the virtual welding system.


In one exemplary embodiment, each state is associated with a condition. In one exemplary embodiment, the sequence controller performs an action if the condition is not met. In one exemplary embodiment, the action is waiting a predetermined duration. In one exemplary embodiment, the action is repeating the operation for the state. In one exemplary embodiment, the action is restarting the virtual sequence.


In one exemplary embodiment, the virtual sequence includes a simulated function selected from the group consisting of: a Quality Check function, a Repeat function, a Notify Welder function, an Enter Job function, a Job Report function, a System Check function, a Perform Welding Operation function, and combinations thereof.


In one exemplary embodiment, the displaying means comprises an LCD screen.


In one exemplary embodiment, the displaying means is a face-mounted display. In one exemplary embodiment, the face-mounted display is integrated in a welding helmet. In one exemplary embodiment, the welding helmet includes at least one speaker.


In one exemplary embodiment, the displaying means comprises a first display and a second display. The first display is a face-mounted display, while the second display is not a face-mounted display.


In one exemplary embodiment, the first display and the second display are operable to present different views of the interactive welding environment (at the same time).


In one exemplary embodiment, the displaying means is operable to communicate over a network. In one exemplary embodiment, the network is a wireless network.


In one exemplary embodiment, the input device is a mock welding tool.


In one exemplary embodiment, the input device is operable to communicate over a network. In one exemplary embodiment, the network is a wireless network.


In one exemplary embodiment, the spatial tracker generates a magnetic field. The spatial tracker is operable to determine the location of the one or more sensors within the magnetic field.


In one exemplary embodiment, the virtual welding system further comprises a support structure.


In one exemplary embodiment, the support structure is a stand. In one exemplary embodiment, the stand comprises a base, a vertical post, an adjustable table, and an adjustable arm. In one exemplary embodiment, the welding coupon is operable to be attached to the stand. In one exemplary embodiment, at least one clamp is used to attach the welding coupon to the stand.


In one exemplary embodiment, the support structure is an assembly fixture. In one exemplary embodiment, the assembly fixture holds the sample part.


In one exemplary embodiment, the virtual welding system further comprises means for collecting and storing welding and operational data from the virtual sequence controller.


In one exemplary embodiment, the virtual welding system further comprises means for assigning a quality score to the virtual welding activity.





BRIEF DESCRIPTION OF THE DRAWINGS

In the accompanying drawings, which are incorporated in and constitute a part of the specification, various exemplary embodiments of the invention are illustrated, which, together with a general summary of the invention given above and the detailed description given below, serve to exemplify embodiments of this invention.



FIG. 1 is a block diagram that illustrates a system providing arc welding training in a real-time virtual reality environment, according to an exemplary embodiment;



FIG. 2 is a block diagram that illustrates a simulated welding console and observer display device (ODD) of the system of FIG. 1, according to an exemplary embodiment;



FIG. 3 is a diagram that illustrates a simulated welding console and sequencer display/user interface (SDUI) of the system of FIG. 1, according to an exemplary embodiment;



FIG. 4 is a diagram that illustrates a table/stand (T/S) of the system of FIG. 1, according to an exemplary embodiment;



FIG. 5 is a drawing that illustrates a sample part (weldment) in an assembly fixture of the system of FIG. 1, according to an exemplary embodiment;



FIG. 6 is a drawing that illustrates various elements of the spatial tracker (ST) of FIG. 1, according to an exemplary embodiment;



FIG. 7 is a block diagram that further illustrates the system of FIG. 1, according to an exemplary embodiment;



FIG. 8 is a flow chart that illustrates sequencer logic, according to an exemplary embodiment;



FIG. 9 is a system diagram that illustrates a virtual system with a reprogrammable virtual sequencer controller, according to an exemplary embodiment;



FIG. 10 is a schematic diagram that further illustrates the exemplary reprogrammable virtual sequencer controller of FIG. 9;



FIG. 11 is a flow chart that illustrates conditional checks in the exemplary virtual sequence controller of FIGS. 9 and 10;



FIG. 12 is a flow chart that illustrates operation of a sequence control program in the exemplary virtual sequencer controller of FIGS. 9 and 10;



FIG. 13 is a flow diagram that illustrates exemplary operations included in a virtual sequence utilizing a semi-automatic welding work cell, according to an exemplary embodiment;



FIG. 14 is a flow chart that illustrates a training routine, according to an exemplary embodiment;



FIG. 15 is a flow chart that illustrates a training routine using a virtual score, according to an exemplary embodiment;



FIG. 16 is a flow chart that illustrates a hiring process using a virtual performance measure, according to an exemplary embodiment;



FIG. 17 is a flow chart that illustrates an optimization routine using a virtual weld station, according to an exemplary embodiment;



FIG. 18 is a flow chart that illustrates a training routine using a virtual score and a real-world score, according to an exemplary embodiment;



FIG. 19 is a flow chart that illustrates a training routine using a virtual score and a real-world score, according to an exemplary embodiment; and



FIG. 20 is a flow chart that illustrates a routine using a virtual score and a real-world score to determine how well the virtual station predicts real-world performance, according to an exemplary embodiment.





DETAILED DESCRIPTION

In an exemplary embodiment, a virtual (simulated) weld station includes a virtual welding job sequencer. The virtual welding job sequencer simulates a real-world welding job sequencer (e.g., Lincoln Electric's Weld Sequencer) in a virtual environment or using one or more virtual components, such as a virtual welder. A real-world welding job sequencer can control the operations of a semi-automatic work cell, including instructing the operator on what to do next and automatically changing certain parameters of the welding cell, including, for example, welding parameters. The real-world welding job sequencer can provide the operator with an array of commands and instructions that relate to welding and non-welding aspects of the operations associated with the welding station.


A virtual welding station, including the virtual sequencer, can include Lincoln Electric's VRTEX® (virtual reality arc welding training machine) and Weld Sequencer technologies integrated into the virtual welding station to create a unique training/testing environment. In the virtual welding station, a welding sequence is used with the VRTEX system for virtual reality training to produce a given assembly. This requires a series of virtual welds on a virtual assembly, which trains the operator on the welding processes, operations, and procedures required to produce a real assembly (individual welds plus complete work instructions). Once the virtual training has been completed, an operator will be prepared for the real-world welding processes and the sequence of events required to create a real assembly. After training with the Virtual Sequencer, the operator now uses the Weld Sequencer to produce real assemblies, and the same welding sequence is repeated. Real welding operations are controlled and monitored by the Weld Sequencer while WeldScore is used to monitor the welding processes. The WeldScore monitor includes, but is not limited to, the embodiments disclosed in U.S. Ser. No. 12/775,729 filed May 7, 2010, now U.S. Pat. No. 8,569,646, which is incorporated herein by reference in its entirety.


In an exemplary embodiment, all training data (from VRTEX and Weld Sequencer) is collected in a production monitoring system. Comprehensive lesson plans (with virtual assembly creation and real assembly creation) are supplied with this technology. This includes a common welding sequence that is used in the virtual (VRTEX) environment and the real Weld Sequencer controller along with a kit of parts for the real welding portion of the training. The final outcome of an individual lesson is a complete report of all training welds/operations, assembly cycle time, and a real part from the kit.


The operational sequence (used in both the virtual and real-world environments) can contain validation checks on parameters like part placement, travel speed (welding duration), average amperage, and other welding variables. Use of these common requirements reinforces the real requirements that are first learned in the virtual weld station and then repeated on real assemblies (while the Virtual Sequencer and Weld Sequencer direct and monitor the operations in the same manner, respectively).


Successful completion of the virtual training may include an overall score for all welding operations, total cycle time limits, total arc time limits, number of arc starts/stops, and other welding variables. Once minimum requirements are achieved (e.g., once a performance score reaches a predetermined threshold), an operator would be approved for the next training step involving real welding.


During real welding, the Weld Sequencer will use the same welding sequence with the same requirements as the Virtual Sequencer for successfully completing a real assembly.


Welding and operational data from the Virtual Sequencer and Weld Sequencer operations can be collected in a common production monitoring system (e.g., Lincoln Electric's CHECKPOINT™ system). Data can be summarized by operator, welding operations (virtual and real), number of assemblies created, quality scores, cycle time metrics, etc.


In an exemplary embodiment, as with a real-world sequencer, a virtual sequencer can automatically select and implement functions of a virtual welding work cell. For example, a function could include a particular virtual weld schedule to be used within the virtual work cell. In other words, the virtual sequencer can select a virtual weld schedule to be used for a particular virtual weld, and modify the settings of the virtual work cell in accordance with the selected virtual weld schedule, automatically for the operator (i.e., without the operator's specific intervention).


Additionally, in the exemplary embodiment, the virtual sequencer may automatically indicate a sequence of operations, steps or different welds that the operator should follow to create a final virtual assembly. In conjunction with the automatic selection of virtual welding schedules, this indicated sequence allows an operator to follow the sequence to create a final virtual assembly, just like the operator would be expected to do in the real world weld station.


Accordingly, since the virtual sequencer sets up the virtual welding equipment and organizes the workflow, just like a real-world sequencer, the virtual sequencer can be used to train operators before they begin to operate in a real-world welding cell or station. In this manner, the chance for error in the real-world welding station is greatly reduced and productivity and quality are improved.


In an exemplary embodiment, a virtual reality welding station (VRWS) comprises a programmable processor-based subsystem, a spatial tracker operatively connected to the programmable processor-based subsystem, at least one mock welding tool capable of being spatially tracked by the spatial tracker, and at least one display device operatively connected to the programmable processor-based subsystem. The VRWS is capable of simulating, in a virtual reality space, operations associated with a real-world welding station. The operations can include various different types of welds and non-welding operations. For welding operations, the VRWS is capable of displaying the simulated weld puddle on the display device in real-time. As used herein, the term “real-time” means perceiving and experiencing in time in a simulated environment in the same way that a user would perceive and experience in a real-world welding scenario. For non-welding operations, such as, for example, operator identification entering/scanning, part identification entering/scanning, part fixturing, fixture manipulation/control, inspections, etc., the system is capable of replicating and/or simulating the steps that the operator needs to complete for the welding operation at a particular welding station. Generally, the VRWS may include any or all of the features and capabilities disclosed in the following patent applications, each of which is incorporated herein by reference in its entirety: U.S. Ser. No. 11/227,349 filed Sep. 15, 2005, now U.S. Pat. No. 8,692,157; U.S. Ser. No. 11/613,652 filed Dec. 20, 2006; U.S. Ser. No. 12/501,257 filed Jul. 10, 2009, now U.S. Pat. No. 8,747,116; U.S. Ser. No. 12/501,263 filed Jul. 10, 2009; U.S. Ser. No. 12/504,870 filed Jul. 17, 2009; U.S. Ser. No. 12/719,053 filed Mar. 8, 2010, now U.S. Pat. No. 8,274,013; U.S. Ser. No. 13/081,725 filed Apr. 7, 2011, now U.S. Pat. No. 8,657,605; U.S. Ser. No. 13/364,489 filed Feb. 2, 2012; U.S. Ser. No. 13/720,300 filed Dec. 19, 2012, now U.S. Pat. No. 8,787,051; U.S. Ser. No. 13/792,288 filed Mar. 11, 2013, now U.S. Pat. No. 8,834,168; U.S. Ser. No. 13/792,309 filed Mar. 11, 2013; U.S. Ser. No. 13/792,294 filed Mar. 11, 2013, now U.S. Pat. No. 8,851,896; U.S. Ser. No. 13/792,280 filed Mar. 11, 2013; and U.S. Ser. No. 13/545,058 filed Jul. 10, 2012.


Referring now to the drawings, which are provided for the purpose of illustrating the various exemplary embodiments disclosed or otherwise suggested herein and not for the purpose of limiting same, FIG. 1 illustrates an exemplary embodiment of a system block diagram of a system 100 for providing welding station training in a real-time virtual reality environment. The system 100 includes a programmable processor-based subsystem (PPS) 110. The system 100 further includes a spatial tracker (ST) 120 operatively connected to the PPS 110. The system 100 also includes a physical welding user interface (WUI) 130 operatively connected to the PPS 110 and a face-mounted display device (FMDD) 140 operatively connected to the PPS 110 and the ST 120. The system 100 may also include an observer display device (ODD) 150 operatively connected to the PPS 110. The system 100 also includes at least one mock welding tool (MWT) 160 operatively connected to the ST 120 and the PPS 110. The system 100 may include a table/stand (T/S) 170. The system 100 may also include at least one welding coupon (WC) 180 capable of being attached to the T/S 170. The system 100 may include an assembly fixture (AF) 182. The system 100 may also include at least one sample part (SP) 184. The system 100 also includes a virtual sequencer (VS) 186 and a sequencer display/user interface (SDUI) 188. In other exemplary embodiments, the VS 186 may be combined with the PPS 110 and/or the SDUI 188 may be combined with the WUI 130 and/or other interfaces, displays, etc., to simulate the number and type of interfaces and/or displays that the station operator will be required to interact with in the real-world welding station.


The system 100 may also include various other devices, such as, for example, operational devices 190, that simulate the real-world welding station devices needed for certain operations. As shown in FIG. 1, an operational device 190 may be associated with the AF 182, for example, to verify SP 184 placement within the AF 182, manipulate the position of the AF 182, actuate one or more clamps to hold the SP 184 in the AF 182, etc. Other devices (not shown) may include, for example, scanners, readers, user interfaces, displays (including, e.g., configurable visual aids), visual/audible indicators (e.g., for sequence error, weld out-of-limits, WeldScore defect detection), PLC interfaces, interlocks (e.g., preheat and/or interpass temperature, position of automatic positioners, part detection/part loaded, clamps closed/open), control panels, assembly tools, inspection tools, operator position sensors (e.g., weight-sensing mat), part position/proximity sensors, safety/lock-out devices, lighting control, material handling devices, part and/or assembly gauges (e.g., for quality control), etc. In accordance with other exemplary embodiments, a mock gas bottle is provided (not shown) simulating a source of shielding gas and having an adjustable flow regulator. Some of the above elements of the system 100 may be real-world components that are used in the virtual weld station. For example, a real-world assembly fixture 182 may be used to hold the sample part 184. Any combination of virtual and real-world components may comprise the virtual weld station.



FIG. 2 illustrates an exemplary embodiment of a simulated welding console 135 (simulating a welding power source user interface) with an observer display device (ODD) 150 of the system 100 of FIG. 1. The physical WUI 130 resides on a front portion of the console 135 and provides knobs, buttons, and a joystick for user selection of various modes and functions. The optional ODD 150 is attached to a top portion of the console 135. The MWT 160 rests in a holder attached to a side portion of the console 135. Internally, the console 135 can hold, or otherwise house, various components of the system 100, for example, the PPS 110, VS 186, and/or a portion of the ST 120.



FIG. 3 illustrates an exemplary embodiment of a simulated welding console 135 (simulating a welding power source user interface) and a SDUI 188 of the system 100 of FIG. 1. A zoomed-in view of an exemplary screenshot 189 of the SDUI 188 is also shown. The physical SDUI 188 can provide a display screen, knobs, buttons, and/or a joystick for user selection of various modes and functions. The VS 186 may be integrated with the SDUI 188 or may be included with the PPS 110, which may be included in the console 135.



FIG. 4 illustrates an exemplary embodiment of a table/stand (T/S) 170 of the system 100 of FIG. 1. The T/S 170 includes an adjustable table 171, a stand or base 172, an adjustable arm 173, and a vertical post 174. The table 171, the stand 172, and the 173 are each attached to the vertical post 174. The table 171 and the arm 173 are each capable of being manually adjusted upward, downward, and rotationally with respect to the vertical post 174. The arm 173 is used to hold various welding coupons (e.g., welding coupon 175) and/or sample parts 184, and a user may rest his/her arm on the table 171 when training. The vertical post 174 is indexed with position information such that a user may know exactly where the arm 173 and the table 171 are vertically positioned on the post 174. This vertical position information may be entered into the system by a user using the WUI 130, the ODD 150, and/or the SDUI 188.



FIG. 5 illustrates an exemplary assembly fixture (AF) 182, shown as a single adjustable support structure. The support structure is depicted holding (i.e., supporting) a sample part (SP) 184, i.e., a weldment having spaced rails 514, 516. The support structure 182 includes an upper movable platform 518, on which is held a top surface 520 of the weldment 184. Movable platform 518 is adjusted to a desired position or orientation, for a particular area of the weldment 184 for simulated welding. The weldment 184 is boxed around frame 522 by elongated strips 524 (only short pieces of which are shown in FIG. 5). Top surface 520 of weldment 184 is the upper side of the rail section when incorporated into the rail system. Brace structures 526 are at spaced positions along the length of weldment 184. As illustrated in this figure, brace structures 526 are positioned to have rails 514, 516 positioned between the braces 526 and outer portions of frame 522 of weldment 184. With further attention to the support structure 182, a lower fixed support base 528 is in operable connection with movable upper platform 518 through transversely spaced multi-positionable hinges 530, 532. In one embodiment, the multi-positionable hinges may be 2-bar linkages, and the following discussion primarily refers to components or elements 530, 532 as 2-bar linkages. It is, however, to be appreciated that other hinges or other appropriate structures which permit suitable movement of movable platform 518 may be used without departing from the scope and intent of the general inventive concepts. The moveable platform 518 may be controlled by an operational device 190 from the system 100 of FIG. 1. In addition, the support structure 182 (as the AF) and the weldment 184 (as the SP), as depicted in FIG. 5, are merely exemplary. The AF 182 and the SP 184 may consist of any shape, construction, number of parts, type of parts, and size of parts as required for any welding operation.


As mentioned, the support structure 182 may be adjusted to locate the weldment 184 to an orientation or position appropriate for a desired simulated welding operation. To adjust the position of movable upper platform 518 with respect to fixed support base 528, actuators, such as length adjusting members 550, 552, are connected between pintles or pivot elements 540, 542 and pintles or pivot elements 554 and 556, respectively, the latter of which are positioned generally near the center of fixed base 528. In addition, an actuator, such as length adjusting member 560, is connected between fixed support base 528 via pintle or pivot element 556 and pintle or pivot element 562 to movable platform 518. Positioning of length adjusting members 550, 552, and 560 determine the position of movable platform 518 and therefore the location of weldment 184 being carried thereon. Pivot elements 530c, 532c, 530d, 532d, 540, 542, 554, 556, and 562 provide the support structure 182 with 3-degrees of freedom, i.e., capable of moving in the x and z directions, as well as tilting in the x-z plane. The physical size and operational characteristics of the individual length adjusting members 550, 552, 560 act to determine the envelope of motion for the support structure 182. While in one exemplary embodiment, the length adjusting members are hydraulic actuators, they may also represent other actuators such as pneumatic, ball-and-screw actuators, and/or any type of electrically controlled actuators. Any or all of these movable components may be controlled by one or more operational devices 190 from the system 100 of FIG. 1.


Other exemplary embodiments may include any combination of one or more of tables 171, arms 173, assembly fixtures 182, coupons 180, and/or sample parts 184 to best simulate the real-world weld station operations being simulated.


In accordance with other exemplary embodiments, the positions of the table 171, the arm 173, and/or the AF 182 may be automatically set by the PSS 110 and/or the VS 186 via preprogrammed settings, or via the WUI 130, the ODD 150, and/or the SDUI 188 as commanded by a user. In such embodiments, the T/S 170 and/or AF 182 typically includes, for example, motors and/or servo-mechanisms, and signal commands from the devices mentioned above activate the motors and/or servo-mechanisms.


In accordance with further exemplary embodiments, the positions of the table 171, the arm 173, the AF 182, the WC 180, and/or the SP 184 are detected by the system 100. In this way, a user does not have to manually input the position information via a user interface. In such embodiments, the T/S 170 and/or the AF 182 include position and orientation detectors and send signal commands to the PPS 110 and/or the VS 186 to provide position and orientation information. The WC 175 and/or the SP 184 may include position detecting sensors (e.g., coiled sensors for detecting magnetic fields). A user is able to see a rendering of the T/S 170 and/or the AF 182 on the ODD 150, the FMDD 140, and/or the SDUI 188 as the adjustment parameters are changed, in accordance with an exemplary embodiment.


In accordance with further exemplary embodiments, the positions of the table 171, the arm 173, the AF 182, the WC 180, and/or the SP 184 are dictated and monitored by the system 100. In various exemplary embodiments, positions of the table 171, the arm 173, the AF 182, the WC 180, and/or the SP 184 may be controlled by operational devices 190 based on commands from the PPS 110 and/or the VS 186. In other exemplary embodiments, a user may be provided with the position information via a user interface and manually position the table 171, the arm 173, the AF 182, the WC 180, and/or the SP 184. Automatic and manual positioning determinations are made based on the real-world weld station operations being simulated.


Various other operational devices 190 may be included in the VRWS in order to simulate the real-world welding station. Control and communication with these devices is designed to mimic the real-world welding environment, using virtual and/or real-world devices and components, similar to the exemplary AF 182 described herein.



FIG. 6 illustrates various elements of an exemplary embodiment of the spatial tracker (ST) 120 of FIG. 1. The ST 120 is a magnetic tracker that is capable of operatively interfacing with the PPS 110 of the system 100. The ST 120 includes a magnetic source 121 and source cable, at least one sensor 122 and associated cable, host software on disk 123, a power source 124 and associated cable, USB and RS-232 cables 125, and a processor tracking unit 126. The magnetic source 121 is capable of being operatively connected to, or otherwise interfaced with, the processor tracking unit 126 (e.g., via a cable). The sensor 122 is capable of being operatively connected to, or otherwise interfaced with, the processor tracking unit 126 (e.g., via a cable). The power source 124 is capable of being operatively connected to, or otherwise interfaced with, the processor tracking unit 126 (e.g., via a cable). The processor tracking unit 126 is capable of being operatively connected to, or otherwise interfaced with, the PPS 110 via a USB or RS-232 cable 125. The host software on disk 123 is capable of being loaded onto the PPS 110 and allows functional communication between the ST 120 and the PPS 110.


As shown in FIG. 4, the magnetic source 121 of the ST 120 is mounted on, or otherwise interfaced with, a first portion of the arm 173. Referring to FIG. 5, the magnetic source 121 of the ST 120 is mounted on, or otherwise interfaced with, the back portion of the upper platform 18. In other exemplary embodiments, multiple magnetic sources 121 are mounted in various locations and may be used to provide proper tracking. The magnetic source 121 creates a magnetic field around the magnetic source 121, including the space encompassing the WC 175 and/or the SP 184, which establishes a 3D spatial frame of reference. The T/S 170 and/or the assembly fixture 182 may be largely non-metallic (non-ferric and non-conductive) so as not to distort the magnetic field created by the magnetic source 121. The sensor 122 can include three induction coils orthogonally aligned along three spatial directions. The induction coils of the sensor 122 can each measure the strength of the magnetic field in each of the three directions and provide that information to the processor tracking unit 126. As a result, the system 100 is able to know where any portion of the WC 175 and/or the SP 184 is with respect to the 3D spatial frame of reference established by the magnetic field. The sensor 122 may be attached to the MWT 160 or the FMDD 140, allowing the MWT 160 or the FMDD 140 to be tracked by the ST 120 with respect to the 3D spatial frame of reference in both space and orientation. When two sensors 122 are provided and operatively connected to the processor tracking unit 126, both the MWT 160 and the FMDD 140 may be tracked. In this manner, the system 100 is capable of creating a virtual WC, a virtual SP, a virtual MWT, a virtual T/S, and/or a virtual AF in virtual reality space and displaying the virtual WC, the virtual SP, the virtual MWT, the virtual T/S, and/or the virtual AF on the FMDD 140, the ODD 150, and/or the SDUI 188 as the MWT 160 and the FMDD 140 are tracked with respect to the 3D spatial frame of reference.


In accordance with another exemplary embodiment, the sensor(s) 122 may wirelessly interface to the processor tracking unit 126, and the processor tracking unit 126 may wirelessly interface to the PPS 110. In accordance with other exemplary embodiments, other types of spatial trackers 120 may be used in the system 100 including, for example, an accelerometer/gyroscope-based tracker, an optical tracker (active or passive), an infrared tracker, an acoustic tracker, a laser tracker, a radio frequency tracker, an inertial tracker, and augmented reality based tracking systems. Other types of trackers may be possible as well. In some exemplary embodiments, a combination of two or more different tracking technologies can be employed.



FIG. 7 illustrates an exemplary embodiment of the system 100 of FIG. 1. The various functional blocks of the system 100 as shown in FIG. 7 are implemented largely via software instructions and modules running on the PPS 110 and/or the VS 186. The various functional blocks of the system 100 include a physical interface 701, torch and clamp models 702, environment models 703, sound content functionality 704, welding sounds 705, assembly fixture/stand/table model 706, internal architecture functionality 707, calibration functionality 708, operational device models 709, sample part/coupon models 710, welding physics 711, internal physics adjustment tool (tweaker) 712, graphical user interface functionality 713, graphing functionality 714, student reports functionality 715, renderer 716, bead rendering 717, 3D textures 718, visual cues functionality 719, scoring and tolerance functionality 720, tolerance editor 721, special effects 722, and sequence models 723.


The functionality of the various blocks shown in FIG. 7 operates similarly to the functionality disclosed in U.S. Ser. No. 12/501,257, which, as noted above, is incorporated herein by reference in its entirety. Modeling of the AF 182 may be similar to the T/S 170 in block 706. Modeling of the SP 184 may be similar to the WC 180 in block 710. The graphical user interface functionality 713 may also include the SDUI 188 to set up/display the operations and steps of a simulated weld station scenario. In accordance with an exemplary embodiment, the set up of a welding scenario includes selecting a language, entering a user name, and selecting a weld station to simulate. In accordance with the selected weld station, the VS 186 can select the appropriate sequence models from block 723. The sequence models 723 will include the various aspects associated with the selected weld station's operations, specifying the process steps, including, for example, specifying the WC 180 and/or the SP 184; specifying the T/S 170 configuration and/or the AF 182; specifying one or more welding processes (e.g., FCAW, GMAW, SMAW) and associated axial spray, pulse, or short arc methods; specifying a gas type and flow rate; specifying a type of stick electrode; specifying a type of flux cored wire (e.g., self-shielded, gas-shielded); specifying an environment (e.g., a background environment in virtual reality space); specifying a wire feed speed; specifying a voltage level; specifying an amperage; specifying a polarity; and turning particular visual cues on or off. In other exemplary embodiments, the user may be prompted to specify certain options and/or parameters in accordance with the decisions an operator will have to specify in the real-world weld station processes that are being simulated.


The system 100 is capable of analyzing and displaying the results of virtual weld station activity. By analyzing the results, it is meant that the system 100 is capable of determining when, during the specified process steps, including welding and non-welding operations, the user has deviated from the acceptable limits of the specified processes. A score may be attributed to the user's performance. In one exemplary embodiment, the score may be a function of missed operations; improperly fixtured parts; and deviation in position, orientation, and speed of the mock welding tool 160 through ranges of tolerances, which may extend from an ideal welding pass to marginal or unacceptable welding activity, missed quality checks, or any other operations associated with the selected weld station.


Visual cues functionality 719 can provide immediate feedback to the user by displaying overlaid colors and indicators on the FMDD 140, the ODD 150, and/or the SDUI 188. Visual cues may be provided for each, or portions of each, of the operations associated with the selected weld station.



FIG. 8 is a flow diagram of sequencer logic, according to an exemplary embodiment. In this exemplary embodiment, the virtual sequencer can instruct the operator to perform any number of operations to simulate the real-world weld station. For example, the virtual sequencer can instruct the operator to perform operation 1 to achieve a particular state. Completion of operation 1 may also be associated with a condition check. If the condition is not met (e.g., part number not entered, part not placed in fixture, weld duration not long enough, etc.), the sequence may take an action, such as, for example, waiting, re-instructing, stopping, or any other action. These actions may be designed to mimic the desired action in the real-world weld station or may deviate from the real-world weld station to provide a better training experience for the operator (e.g., re-instruction). The sequence is complete when all of the operations are completed (and associated conditions are met) for the virtual weld station.



FIGS. 9-12 describe a control system, according to an exemplary embodiment. Referring now to FIGS. 9-11, an exemplary control system 902 for system 100 of FIG. 1 is shown. In various embodiments, the control system 902 may be embodied in the PPS 110, the VS 186, the simulated welding console 135, and/or other components. The system 902 includes a plurality of welding system components 950, which are typically virtual components, including a power source 951, a wire feeder 952, a travel carriage 953, a gas solenoid 954, a coolant solenoid 955, a fume extraction system 956, and a robot or programmable logic controller (PLC) 957, where the illustrated system components 950 are merely examples, and a system may be provided with more or fewer components in accordance with the general inventive concepts. The virtual welding components may be included in a simulated welding console 135, as shown in FIG. 2. Real-world welding or non-welding components may be used in the virtual weld station if certain components cannot be simulated adequately.


As shown in FIG. 10, system 902 further comprises a virtual sequencer controller 910 with a microprocessor 912, a sequence control program 922, and one or more state table files 924, 926, 928, where the virtual sequencer controller 910 also provides various interfaces including a network interface 914 for operatively coupling the sequencer 910 with a network 930, one or more dedicated communications interfaces 916 providing direct communications connectivity with one or more of the system components 950 via cables 940, as well as a user interface 918 (such as, e.g., the SDUI 188 from FIG. 1) that provides operator or user access to the sequencer 910 for setting parameters, values, etc., and/or for rendering operational information to a user.


As shown in FIG. 8, the network 930 may couple one or more of the system components 950 and the controller 910 with one another and may also provide for data sharing and other information exchange between any of the components 910, 950, and external devices or other networks (not shown). This includes connecting to the same network as real-world weld stations.


Alternatively or in combination, moreover, dedicated cabling 940 may be used to interconnect the sequencer 910 with some or all of the welding system components 950, such as power source control cable 941, wire feeder cable 942, travel carriage cable 943, gas control cable 944, coolant solenoid control cable 945, fume extractor control cable 946, and/or a robot or PLC cable 947, wherein the interfacing via the network 930 (and the network interface 914) and/or the cables 940 (and the interfaces 916) provides for exchange of data or other information, signaling, messages, etc., by which sequence control inputs 921 can be obtained from one or more system components 950 and sequence control outputs 923 can be provided to one or more of the components 950.


In one exemplary implementation, the processor 912 is a microprocessor, microcontroller, DSP, programmable logic device, etc., although any form of computational processing component may be employed within the scope of the general inventive concepts, whether hardware, software, firmware, or combinations thereof, and which may be a single device or may be implemented in multiple components. It is further noted that the controller 910 may be integrated into one of the system components 950, such as the power source 951, the wire feeder 952, etc., wherein the user interface 918 may include one or more display devices, user control knobs, switches, keypads, etc., and may interface a user with aspects of the system component 950 as well as those of the sequencer controller 910. The controller 910, moreover, includes a memory 920, which may be any suitable data store, integrated or distributed, which is operatively coupled with the processor 912 to allow access by the processor 912 to files, programs, instructions, routines, data, etc. stored in the memory 920. It is noted that while the processing component 912 and the memory 920 may be integrated in one component, such as a unitary circuit board, these elements may be separately provided or distributed across multiple system components to provide a controller 910 within the scope of the general inventive concepts. The memory 920 stores the sequence control program 922 and the state table files 924, 926, 928 providing access thereto by the processor 912. The memory 920 may also include a sequence configuration tool 929, such as a software program that may also be executed by the processor 912. States may be used to define various stages of the assembly process, including semi-automatic or manual states expected at the end of individual operations (e.g., part in fixture, weld time, etc.) and/or automatic states occurring during an operation that are automatically controlled (e.g., changes in the welding parameters that occur during a single weld).


In an exemplary embodiment, the exemplary power source 951 and other components are state table based, wherein certain of the controller outputs 923 are provided as inputs 996 to the components. In operation, controller 910 provides a desired output level or levels as one or more controller outputs 923 and to the various virtual components, which employ the output level(s) to define and regulate the desired state of the component. For example, the controller 910 may regulate a particular welding state, a particular fixture state, etc. The microprocessor 912 executes a standard routine in accordance with the sequence control program, which simulates all of the operations (and their associated parameters) associated with the specified weld station. The controller can read each state, regulating the instruction(s) associated with the current state, and determining whether a series of conditional checks is true and if so, branching to the next state (or operation).


In some exemplary embodiments, certain checks can be made to ensure that the sequence is ready to advance to the next operation. FIG. 11 illustrates the operation of an exemplary control program 962 including conditional checks, wherein a first state table and data table are loaded at 1150 and input values are obtained at 1152. Parameters are calculated and state instructions are executed at 1154, whereafter a first conditional check is loaded at 1156 and tested (e.g., TRUE or FALSE) at 1158. If the first condition is true (YES at 1158), the program 962 executes the associated instruction at 1160, updates timers at 1162, and jumps to the corresponding next state at 1164, after which the outputs are updated at 1166, and the program 962 returns to 1152. If the first tested condition is not true (NO at 1158), a determination is made at 1170 as to whether more checks are specified for the current state, and if so (YES at 1170), the next conditional check is loaded at 1172, and the program tests the new condition at 1158 as described above. Once all conditional checks have been found untrue for the current state (NO at 1170), the program 962 updates the timers at 1174, updates the outputs at 1166, and then returns again to 1152 as described above.


Referring to FIG. 12, the processor 912 executes an exemplary virtual sequence control program 922 according to the sequence controller inputs 921 and according to a selected sequence control state table file 924, 926, 928 to provide the sequence controller outputs 923 to perform a virtual operation by implementing the designated functions or instructions in state-by-state (or step-by-step) fashion, where the condition checks provide for branching to an appropriate next state based on the inputs, timers, etc. In operation, a user selects from the available state table files 924, 926, 928 (e.g., a virtual weld station sequence), using a selection feature on the sequencer user interface 918. Execution of the sequence control program 922 begins at 1202 in FIG. 12, where the processing component 912 obtains a current sequence control state table file entry at 1204 from the sequence control state table file 924, and obtains current sequence controller inputs 921 from at least one of the virtual system components at 1206. At 1208, the processor 912 executes one or more executable instructions or routines of the control program 922 identified by the instruction identifier(s) of the current entry using one or more instruction parameters thereof and provides the sequence controller outputs 923 at 1210. The virtual system condition(s) identified by one or more exit condition identifiers of the state table file entry are checked at 1212 and a determination is made at 1214 as to whether any identified exit conditions are satisfied according to the current sequence controller inputs 921, including any timers associated with the current state. If not, the current state is continued (NO at 1214), and the program execution returns to 1206-1212 as described above. In this manner, the sequence controller 910 implements a state of a given virtual sequence according to the state definition in the corresponding table file entry until one or more of the specified exit conditions have been met. Once an exit condition is satisfied (YES at 1214), the processor 912 obtains the next sequence control state table file entry at 1216 that corresponds to the satisfied exit condition identifier. Also, instructions or routines corresponding to any specified action identifiers for the satisfied condition are executed at 1216. Execution of the control program 922 then returns to obtain the current system inputs 921 at 1206 to execute the instructions identified in the new state table file entry and generate corresponding outputs 923 at 1208 and 1210, respectively, and to check the new state exit conditions at 1212 and 1214 as described above.


It is noted that the sequence control program 922 is fairly generic with respect to interoperation with the selected state table file 924, wherein the hard coded instructions and routines of program 922 are those appropriate to interface with and control the various system components and to obtain inputs therefrom, whereas the specific logic of a given virtual sequence is provided by the state table file entries and the elements thereof. In this manner, the embodiments essentially decouple the virtual sequence logic in the table files 924, 926, 928 from the hard coded executable instructions and routines of the control program 922. Consequently, reconfiguration of an entire virtual system can be accomplished without recompiling and installing software or firmware and without hardware modification (e.g., no need to modify or recompile the sequence control program 922). Instead, a state table file 924, 926, 928 can be constructed and simply stored in memory 920 (or in any suitable data store accessible by the processing component 912) in order to implement a new virtual operational sequence. Furthermore, existing state table files 924, 926, 928 can be used as a starting point or template, with state table file entries being changed, added, or removed therefrom to implement new or modified virtual operations using the sequence controller 910. If sequencer state table files 924, 926, 928 are created outside of memory 920, moreover, such files may be easily downloaded to a data store accessible by the processing component 912. In this regard, virtual system operators or service personnel may configure the sequence controller 910 and hence an entire virtual system from a remote location, according to the general inventive concepts, where the state table files 924, 926, 928 can be downloaded via the network 930 and other networks operationally connected thereto, including LANS, WANS, Internet connections, etc. Furthermore, it is noted that the elements of state table file entries can be any tags, strings, pointers, addresses, etc. that provide an indication of instructions, routines, numeric values, states, or actions that can be understood by processor 912 when executing the sequence control program 922. Thus, sequence configuration tool 929 (FIG. 10) can be any suitable hardware, software, firmware, or combinations thereof that can obtain the elements and logic of a virtual sequence and create a state table file 924, 926, 928 and entries thereof, and which can then be used in performing a virtual operation.


An exemplary embodiment of a virtual sequence including various welder (operator) and non-welder operations is diagrammatically represented in FIG. 13. In FIG. 13, at operation 1310, the virtual sequencer begins operation and can instruct the operator to enter the operator's identification number, proper part identification number, assembly identification number, etc. The virtual sequencer may also set the virtual welding equipment to use weld schedule A (operation 1320) and instruct the operator to virtually perform welds #1, #2, and #3. Then, the operator virtually performs welds #1, #2, and #3 using weld schedule A (operations 1322, 1324, and 1326). Next, the virtual sequencer sets the virtual welding equipment to use weld schedule B (operation 1330) and instructs the operator to perform weld #4. Then, the operator performs weld #4 using weld schedule B (operations 1332). After completion of weld schedule B, the virtual sequencer sets the virtual welding equipment to use weld schedule C (operation 1350) and instructs the operator to perform welds #5 and #6 and to visually inspect the part. Then, the operator performs welds #5 and #6 (operations 1352, and 1354) using weld schedule C and inspects the completed part or assembly to confirm that it is correct (operation 1360). This inspection may include dimensional verification, visual defect confirmation, or any other type of check that might be needed. Further, operation 1360 may include a requirement that the operator affirmatively indicate that the inspection is complete, such as by pressing an “OK” button, before it is possible to proceed to the next operation. Lastly, the virtual sequencer indicates that the virtual welding operation is at an end (operation 1370) and re-sets for the next operation. Data, including production data, can be gathered during all operations.


Accordingly, as noted above, the sequencing and scheduling of virtual welding operations is completed, or otherwise facilitated, by the sequencer, simulating the real-world welding station. Other operations automatically performed by the virtual sequencer could include, for example, changing the position of a fixture, actuating operational devices, displaying visual aids, controlling audible and visual indicators, verifying certain checks, etc. Other operations directed by the virtual sequencer for the welder operator could include, for example, retrieving a sample part, entering a sample part ID, placing the sample part in a fixture, actuating fixture clamps, performing a test, etc.


The virtual sequencer may select and implement a new function, such as the selection and implementation of weld schedules A, B and C shown in FIG. 13, based upon various variables or inputs. For example, the virtual sequencer may simply select new weld schedules based upon a monitoring of elapsed time since the beginning of the welding operations or since the cessation of welding (such as the time after weld #3 in FIG. 13 above). Alternatively, the virtual sequencer may monitor the actions of the operator, compare the actions to the identified sequence of welds, and select new weld schedules appropriately.


Still further, various combinations of these methods, or any other effective method, may be implemented, as long as the end effect is to simulate the real-world sequence and environment in the real-world weld station. By way of example, and not by way of limitation, the following real-world functions may be simulated in the virtual weld station and included in the virtual sequence.


A Quality Check function requires that a quality check of the weld be performed (either during welding or after the weld is completed) before allowing the job sequence to continue. The quality check can monitor various virtual welding parameters and can pause the welding operation and alert the operator if an abnormality is detected. An example of a welding parameter measurable by this function would be arc data.


Another exemplary function is a Repeat function. This function would instruct the operator to repeat a particular virtual weld or weld sequence. An example of the use of this function includes when the Quality Check function shows an abnormality, or when multiple instances of the same weld are required.


Another exemplary function is a Notify Welder function, which communicates information to the welder. This function would display information, give an audible signal, or communicate with the welder by some other means. Examples of use of this function include an indication to the operator that he is free to begin virtual welding or an indication that the operator should check some portion of the welded part for quality purposes.


Another exemplary function is an Enter Job Information function. This function will require the welder to enter information, such as the sample part serial number, a personal ID number, or other special conditions before the virtual sequencer can continue. This information could also be read from a sample part or inventory tag itself through RFID, bar code scanning, or the like. The virtual sequencer could then utilize the entered information for the virtual welding operations. An example of the use of this function would be as a predicate to the entire virtual welding operation, so as to indicate to the virtual sequencer which schedules and/or sequences should be selected.


Another exemplary function is a Job Report function. This function will create a report on the virtual welding job, which could include information such as: the number of virtual welds performed, total and individual arc timing, sequence interruptions, errors, faults, wire usage, arc data, and the like. An example of the use of this function would be to report to a manufacturing quality department on the efficiency and quality of the virtual processes.


Another exemplary function is a System Check function. This function will establish whether the virtual welding job can continue and could monitor such parameters as: wire supply, gas supply, time left in the shift (as compared to the required time to finish the job), and the like. The function could then determine whether the parameters indicate that there is enough time and/or material for the virtual welding job to continue. This function simulates efforts to prevent down-time due to material depletion and would prevent work-in-process assemblies from being delayed, which can lead to quality problems due to thermal and scheduling issues.


Further, as mentioned above, the virtual sequencer may select and implement a new function, based upon various variables or inputs. These variables and inputs are not particularly limited and can even be another function. For example, another exemplary function compatible with the virtual sequencer is a Perform Welding Operation function. This function is designed to detect the virtual welding performed by the operator and to report that welding so that the virtual sequencer can determine whether to proceed with further operations. For example, this function can operate by starting when the operator pulls the trigger to start the virtual welding operation and finishing when the operator releases the trigger after the virtual welding is complete, or after a predetermined period of time has lapsed. This function could end when the trigger is released or it could be configured to automatically turn off after a period of time, a quantity of wire, or an amount of energy is delivered. This function may be used to determine when to select a new function, such as a new weld schedule, as discussed above.


Still further, various semi-automatic and/or robotic work cells can be integrated together on a single network, and the sequencing of virtual welding steps at a single work-cell can be fully integrated into a virtual complete production schedule, which itself can be modified as needed to track variations in the virtual production schedule. Sequencing and/or scheduling information can also be stored in a database, be stored by date as archival information, and be accessed to provide various virtual production reports.


The exemplary virtual weld station embodiments described above and in the figures, including the exemplary virtual sequencer embodiments, can be used for a variety of training and operational optimization techniques, including lesson plans based on the following procedures. Production monitoring data may be gathered, compared, and manipulated in one or more common or separate databases from both virtual and real-world operations.


For example, FIG. 14 is a flow chart illustrating an exemplary training routine. An operator can perform virtual weld station operations before proceeding to real-world welding operations.



FIG. 15 is a flow chart illustrating an exemplary training routine using a virtual score. In this embodiment, the operator must achieve a certain score before proceeding to operate in the real-world weld station.



FIG. 16 is a flow chart illustrating an exemplary hiring process using a virtual performance measure. In this embodiment, the applicant (operator) must achieve a certain performance using the virtual weld station to be hired.



FIG. 17 is a flow chart illustrating an exemplary optimization routine using a virtual weld station. In this embodiment, the virtual weld station is used to optimize some aspect of the proposed sequence of operations. The virtual operations are modified until one or more aspects are acceptable (e.g., exceed some predetermined threshold or satisfy one or more quality parameters). Then, the virtual sequence is used as the real-world sequence.



FIG. 18 is a flow chart illustrating an exemplary training routine using a virtual score and a real-world score. In this embodiment, the operator must achieve a certain score before proceeding to operate in the real-world weld station. Then, a real-world sequencer (e.g., Lincoln Electric's Weld Sequencer) is used by the same operator on the same operation, and a real-world score is determined.



FIG. 19 is another flow chart illustrating an exemplary training routine using a virtual score and a real-world score. In this embodiment, the operator must achieve a certain score before proceeding to operate in the real-world weld station. Then, a real-world score is determined, and if the real-world score falls below a threshold, the operator can be further trained using the virtual weld station.



FIG. 20 is another flow chart illustrating a routine using a virtual score and a real-world score to determine how well the virtual station predicts real-world performance. In this embodiment, the virtual and real-world performance scores are compared to determine how well the virtual simulation predicts the real-world performance. If the correlation is not sufficient, the virtual simulation may be modified.


As can be seen, the virtual weld station and virtual sequencer can be used to gather and store a wealth of data that can be used to calculate and ultimately increase productivity. This data can be stored in a data “cloud” and then accessed for analysis and manipulation. The virtual sequencer can monitor and instruct the user to prevent missing welds, missing welding steps, missing other operations, excessive use of welding consumables, and other undesirable activities. The virtual sequencer can also be used to train users in the proper time for accomplishing or completing various welding or non-welding steps on a particular assembly. The virtual sequencer also leads to a consistent process order for making a particular weldment assembly. The virtual sequencer also reduces training time and scrap. The number of times each user had to be trained on certain assemblies to flag problematic parts for a particular user can also be determined. All of these items lead to increased productivity and less waste of time and resources.


While the general inventive concepts have been illustrated by the description of various embodiments thereof, and while the embodiments have been described in some detail, it is not the intention of the applicant to restrict, or in any way limit, the scope of the appended claims to such detail. Additional advantages and modifications will be readily apparent to those skilled in the art. Therefore, the invention in its broader aspects is not limited to the specific details, representative apparatus and methods, and illustrative examples shown and described. Accordingly, departures may be made from such details without departing from the spirit or scope of the applicant's general inventive concepts.

Claims
  • 1. A virtual welding system comprising: a logic processor based subsystem operable to execute coded instructions for generating an interactive welding environment that emulates welding activity on a virtual weld joint defined by at least one of a welding coupon and a sample part;a virtual sequence controller operatively connected to the logic processor based subsystem for implementing a virtual sequence;a display operatively connected to the logic processor based subsystem for visually depicting the interactive welding environment including the virtual weld joint;an input device for performing virtual welding activity on the virtual weld joint in real time; anda spatial tracker comprising one or more sensors adapted to track movement of the input device in real time for communicating data about the movement of the input device to the logic processor based subsystem,wherein the virtual sequence includes a plurality of operations to be performed in order, each operation intended to achieve a particular state,wherein at least one of the operations is a manual operation to be performed by a user, andwherein the manual operation is one of providing user information, retrieving a part, providing part information, placing a part, securing a part, and providing assembly information.
  • 2. The virtual welding system of claim 1, further comprising a user interface for the user to provide input to the virtual welding system.
  • 3. The virtual welding system of claim 1, wherein the virtual sequence controller comprises a microprocessor, a sequence control program, and a memory, and wherein the memory stores one or more state table files.
  • 4. The virtual welding system of claim 3, wherein the virtual sequence is defined by at least one of the state table files.
  • 5. The virtual welding system of claim 3, wherein the user selects one of the state table files based on a task to be performed; and wherein the task is production of a complete virtual assembly.
  • 6. The virtual welding system of claim 1, further comprising a virtual sequence display; wherein the virtual sequence display displays information on the manual operation.
  • 7. The virtual welding system of claim 1, wherein at least one of the operations is an automatic operation to be performed by the virtual welding system.
  • 8. The virtual welding system of claim 7, wherein the automatic operation is one of specifying a weld process, specifying a gas type, specifying a gas flow rate, specifying a stick electrode type, specifying a flux cored wire type, specifying a wire feed speed, specifying a voltage level, specifying an amperage, specifying a polarity, and specifying a background environment for the interactive welding environment.
  • 9. The virtual welding system of claim 1, wherein each particular state is associated with a condition.
  • 10. The virtual welding system of claim 9, wherein the virtual sequence controller performs an action if the condition is not met.
  • 11. The virtual welding system of claim 1, wherein the display is a face-mounted display.
  • 12. The virtual welding system of claim 1, further comprising a support structure.
  • 13. The virtual welding system of claim 12, wherein the support structure is a stand comprising a base, a vertical post, an adjustable table, and an adjustable arm.
  • 14. The virtual welding system of claim 12, wherein the support structure is an assembly fixture for holding the sample part.
  • 15. The virtual welding system of claim 1, wherein the virtual welding system is operable to assign a quality score to the virtual welding activity.
  • 16. A virtual welding system comprising: a logic processor based subsystem operable to execute coded instructions for generating an interactive welding environment that emulates welding activity on a virtual weld joint defined by at least one of a welding coupon and a sample part;a virtual sequence controller operatively connected to the logic processor based subsystem for implementing a virtual sequence;a display operatively connected to the logic processor based subsystem for visually depicting the interactive welding environment including the virtual weld joint;an input device for performing virtual welding activity on the virtual weld joint in real time; anda spatial tracker comprising one or more sensors adapted to track movement of the input device in real time for communicating data about the movement of the input device to the logic processor based subsystem,wherein the virtual sequence includes a plurality of operations to be performed in order, each operation intended to achieve a particular state,wherein at least one of the operations is an automatic operation to be performed by the virtual welding system, andwherein the automatic operation is one of specifying a weld process, specifying a gas type, specifying a gas flow rate, specifying a stick electrode type, specifying a flux cored wire type, specifying a wire feed speed, specifying a voltage level, specifying an amperage, specifying a polarity, and specifying a background environment for the interactive welding environment.
  • 17. The virtual welding system of claim 16, further comprising a user interface for the user to provide input to the virtual welding system.
  • 18. The virtual welding system of claim 16, wherein the virtual sequence controller comprises a microprocessor, a sequence control program, and a memory, and wherein the memory stores one or more state table files.
  • 19. The virtual welding system of claim 18, wherein the virtual sequence is defined by at least one of the state table files.
  • 20. The virtual welding system of claim 18, wherein a user selects one of the state table files based on a task to be performed; and wherein the task is production of a complete virtual assembly.
  • 21. The virtual welding system of claim 16, further comprising a virtual sequence display; wherein the virtual sequence display displays information on the automatic operation.
  • 22. The virtual welding system of claim 16, wherein each particular state is associated with a condition.
  • 23. The virtual welding system of claim 22, wherein the virtual sequence controller performs an action if the condition is not met.
  • 24. The virtual welding system of claim 16, wherein the display is a face-mounted display.
  • 25. The virtual welding system of claim 16, further comprising a support structure.
  • 26. The virtual welding system of claim 25, wherein the support structure is a stand comprising a base, a vertical post, an adjustable table, and an adjustable arm.
  • 27. The virtual welding system of claim 25, wherein the support structure is an assembly fixture for holding the sample part.
  • 28. The virtual welding system of claim 16, wherein the virtual welding system is operable to assign a quality score to the virtual welding activity.
RELATED APPLICATION

The present application is being filed as a non-provisional patent application claiming priority/benefit under 35 U.S.C. § 119(e) from U.S. Provisional Patent Application No. 61/900,136 filed on Nov. 5, 2013, the entire disclosure of which is incorporated herein by reference.

US Referenced Citations (452)
Number Name Date Kind
317063 Wittenstrom May 1885 A
428459 Coffin May 1890 A
483428 Goppin Sep 1892 A
1159119 Springer Nov 1915 A
1288529 Cave Dec 1918 A
2326944 Holand et al. Aug 1943 A
2333192 Mobert Nov 1943 A
D140630 Garibay Mar 1945 S
D142377 Dunn Sep 1945 S
D152049 Welch Dec 1948 S
2681969 Burke Jun 1954 A
D174208 Abidgaard Mar 1955 S
2728838 Barnes Dec 1955 A
D176942 Cross Feb 1956 S
2894086 Rizer Jul 1959 A
3035155 Hawk May 1962 A
3059519 Stanton Oct 1962 A
3356823 Waters et al. Dec 1967 A
3555239 Kerth Jan 1971 A
3562927 Moskowitz Feb 1971 A
3562928 Schmitt Feb 1971 A
3621177 McPherson et al. Nov 1971 A
3654421 Streetman et al. Apr 1972 A
3690020 McBratnie Sep 1972 A
3739140 Rotilio Jun 1973 A
3866011 Cole Feb 1975 A
3867769 Schow et al. Feb 1975 A
3904845 Minkiewicz Sep 1975 A
3988913 Metcalfe et al. Nov 1976 A
D243459 Bliss Feb 1977 S
4024371 Drake May 1977 A
4041615 Whitehill Aug 1977 A
D247421 Driscoll Mar 1978 S
4124944 Blair Nov 1978 A
4132014 Schow Jan 1979 A
4237365 Lambros et al. Dec 1980 A
4280041 Kiessling et al. Jul 1981 A
4280137 Ashida et al. Jul 1981 A
4314125 Nakamura Feb 1982 A
4354087 Osterlitz Oct 1982 A
4359622 Dostoomian et al. Nov 1982 A
4375026 Kearney Feb 1983 A
4410787 Kremers et al. Oct 1983 A
4429266 Traadt Jan 1984 A
4452589 Denison Jun 1984 A
D275292 Bouman Aug 1984 S
D277761 Korovin et al. Feb 1985 S
4525619 Ide et al. Jun 1985 A
D280329 Bouman Aug 1985 S
4555614 Morris et al. Nov 1985 A
4611111 Baheti et al. Sep 1986 A
4616326 Meier et al. Oct 1986 A
4629860 Lindborn Dec 1986 A
4677277 Cook et al. Jun 1987 A
4680014 Paton et al. Jul 1987 A
4689021 Vasiliev et al. Aug 1987 A
4707582 Beyer Nov 1987 A
4716273 Paton et al. Dec 1987 A
D297704 Bulow Sep 1988 S
4812614 Wang et al. Mar 1989 A
4867685 Brush et al. Sep 1989 A
4877940 Bangs et al. Oct 1989 A
4897521 Burr Jan 1990 A
4907973 Hon Mar 1990 A
4931018 Herbst et al. Jun 1990 A
4973814 Kojima Nov 1990 A
4998050 Nishiyama et al. Mar 1991 A
5034593 Rice et al. Jul 1991 A
5061841 Richardson Oct 1991 A
5089914 Prescott Feb 1992 A
5192845 Kirmsse et al. Mar 1993 A
5206472 Myking et al. Apr 1993 A
5266930 Ichikawa et al. Nov 1993 A
5283418 Bellows et al. Feb 1994 A
5285916 Ross Feb 1994 A
5288968 Cecil Feb 1994 A
5305183 Teynor Apr 1994 A
5320538 Baum Jun 1994 A
5337611 Fleming et al. Aug 1994 A
5360156 Ishizaka et al. Nov 1994 A
5360960 Shirk Nov 1994 A
5362962 Barborak et al. Nov 1994 A
5370071 Ackermann Dec 1994 A
D359296 Witherspoon Jun 1995 S
5424634 Goldfarb et al. Jun 1995 A
5436638 Bolas et al. Jul 1995 A
5464957 Kidwell et al. Nov 1995 A
5465037 Huissoon et al. Nov 1995 A
D365583 Viken Dec 1995 S
5493093 Cecil Feb 1996 A
5547052 Latshaw Aug 1996 A
5562843 Yasumoto Oct 1996 A
5662822 Tada et al. Sep 1997 A
5670071 Tomoyuki et al. Sep 1997 A
5676503 Lang Oct 1997 A
5676867 Allen Oct 1997 A
5708253 Bloch et al. Jan 1998 A
5710405 Solomon et al. Jan 1998 A
5719369 White et al. Feb 1998 A
D392534 Degan et al. Mar 1998 S
5728991 Takada et al. Mar 1998 A
5751258 Fergason et al. May 1998 A
D395296 Kaya et al. Jun 1998 S
5774110 Edelson Jun 1998 A
D396238 Schmitt Jul 1998 S
5781258 Debral et al. Jul 1998 A
5823785 Matherne Oct 1998 A
5835077 Dao et al. Nov 1998 A
5835277 Hegg Nov 1998 A
5845053 Watanabe et al. Dec 1998 A
5877777 Colwell Mar 1999 A
5963891 Walker et al. Oct 1999 A
6008470 Zhang et al. Dec 1999 A
6037948 Liepa Mar 2000 A
6049059 Kim Apr 2000 A
6051805 Vaidya et al. Apr 2000 A
6114645 Burgess Sep 2000 A
6155475 Ekelof et al. Dec 2000 A
6155928 Burdick Dec 2000 A
6230327 Briand et al. May 2001 B1
6236013 Delzenne May 2001 B1
6236017 Smartt et al. May 2001 B1
6242711 Cooper Jun 2001 B1
6271500 Hirayama et al. Aug 2001 B1
6301763 Pryor Oct 2001 B1
6330938 Herve et al. Dec 2001 B1
6330966 Eissfeller Dec 2001 B1
6331848 Stove et al. Dec 2001 B1
D456428 Aronson et al. Apr 2002 S
6373465 Jolly et al. Apr 2002 B2
6377011 Ben-Ur Apr 2002 B1
D456828 Aronson et al. May 2002 S
6396232 Haanpaa et al. May 2002 B2
D461383 Blackburn Aug 2002 S
6427352 Pfeiffer et al. Aug 2002 B1
6441342 Hsu Aug 2002 B1
6445964 White et al. Sep 2002 B1
6492618 Flood et al. Dec 2002 B1
6506997 Matsuyama Jan 2003 B2
6552303 Blankenship et al. Apr 2003 B1
6560029 Dobbie et al. May 2003 B1
6563489 Latypov et al. May 2003 B1
6568846 Cote et al. May 2003 B1
D475726 Suga et al. Jun 2003 S
6572379 Sears et al. Jun 2003 B1
6583386 Ivkovich Jun 2003 B1
6593540 Baker et al. Jul 2003 B1
6621049 Suzuki Sep 2003 B2
6624388 Blankenship et al. Sep 2003 B1
D482171 Vui et al. Nov 2003 S
6647288 Madill et al. Nov 2003 B2
6649858 Wakeman Nov 2003 B2
6655645 Lu et al. Dec 2003 B1
6660965 Simpson Dec 2003 B2
6679702 Rau Jan 2004 B1
6697701 Hillen et al. Feb 2004 B2
6697770 Nagetgaal Feb 2004 B1
6703585 Suzuki Mar 2004 B2
6708835 Lemelson Mar 2004 B1
6710298 Eriksson Mar 2004 B2
6710299 Blankenship et al. Mar 2004 B2
6715502 Rome et al. Apr 2004 B1
D490347 Meyers May 2004 S
6730875 Hsu May 2004 B2
6734393 Friedl et al. May 2004 B1
6744011 Hu et al. Jun 2004 B1
6750428 Okamoto et al. Jun 2004 B2
6765584 Matthias Jul 2004 B1
6772802 Few Aug 2004 B2
6788442 Potin et al. Sep 2004 B1
6795778 Dodge et al. Sep 2004 B2
6798974 Nakano et al. Sep 2004 B1
6857533 Hartman et al. Feb 2005 B1
6858817 Blankenship et al. Feb 2005 B2
6865926 O'Brien et al. Mar 2005 B2
D504449 Butchko Apr 2005 S
6920371 Hillen et al. Jul 2005 B2
6940039 Blankenship et al. Sep 2005 B2
6982700 Rosenberg et al. Jan 2006 B2
7021937 Simpson et al. Apr 2006 B2
7024342 Waite Apr 2006 B1
7110859 Shibata et al. Sep 2006 B2
7126078 Demers et al. Oct 2006 B2
7132617 Lee et al. Nov 2006 B2
7170032 Flood Jan 2007 B2
7194447 Harvey Mar 2007 B2
7233837 Swain et al. Jun 2007 B2
7247814 Ott Jul 2007 B2
D555446 Picaza Ibarrondo Nov 2007 S
7298535 Kuutti Nov 2007 B2
7315241 Daily et al. Jan 2008 B1
D561973 Kinsley et al. Feb 2008 S
7353715 Myers Apr 2008 B2
7363137 Brant et al. Apr 2008 B2
7375304 Kainec et al. May 2008 B2
7381923 Gordon et al. Jun 2008 B2
7414595 Muffler Aug 2008 B1
7465230 LeMay et al. Dec 2008 B2
7474760 Hertzman et al. Jan 2009 B2
7478108 Townsend et al. Jan 2009 B2
7487018 Afshar et al. Feb 2009 B2
D587975 Aronson et al. Mar 2009 S
7516022 Lee et al. Apr 2009 B2
7580821 Schirm Aug 2009 B2
D602057 Osicki Oct 2009 S
7621171 O'Brien Nov 2009 B2
D606102 Bender et al. Dec 2009 S
7643890 Hillen et al. Jan 2010 B1
7687741 Kainec et al. Mar 2010 B2
D614217 Peters et al. Apr 2010 S
D615573 Peters et al. May 2010 S
7817162 Bolick Oct 2010 B2
7853645 Brown et al. Dec 2010 B2
D631074 Peters et al. Jan 2011 S
7874921 Baszucki et al. Jan 2011 B2
7970172 Hendrickson Jun 2011 B1
7972129 O'Donoghue Jul 2011 B2
7991587 Ihn Aug 2011 B2
8069017 Hallquist Nov 2011 B2
8224881 Spear et al. Jul 2012 B1
8248324 Nangle Aug 2012 B2
8265886 Bisiaux et al. Sep 2012 B2
8274013 Wallace Sep 2012 B2
8287522 Moses et al. Oct 2012 B2
8301286 Babu Oct 2012 B2
8316462 Becker et al. Nov 2012 B2
8363048 Gering Jan 2013 B2
8365603 Lesage et al. Feb 2013 B2
8512043 Choquet Aug 2013 B2
8569646 Daniel et al. Oct 2013 B2
8592723 Davidson et al. Nov 2013 B2
8657605 Wallace et al. Feb 2014 B2
8692157 Daniel et al. Apr 2014 B2
8747116 Zboray et al. Jun 2014 B2
8777629 Kreindl et al. Jul 2014 B2
8787051 Chang et al. Jul 2014 B2
8834168 Peters et al. Sep 2014 B2
8851896 Wallace et al. Oct 2014 B2
8911237 Postlewaite et al. Dec 2014 B2
8915740 Zboray et al. Dec 2014 B2
RE45398 Wallace Mar 2015 E
8992226 Leach et al. Mar 2015 B1
9011154 Kindig et al. Apr 2015 B2
9293056 Zboray Mar 2016 B2
9293057 Zboray Mar 2016 B2
9468988 Daniel Oct 2016 B2
9779635 Zboray et al. Oct 2017 B2
20010045808 Heitmann et al. Nov 2001 A1
20010052893 Jolly et al. Dec 2001 A1
20020032553 Simpson et al. Mar 2002 A1
20020039138 Edelson et al. Apr 2002 A1
20020046999 Veikkolainen et al. Apr 2002 A1
20020050984 Roberts May 2002 A1
20020054211 Edelson et al. May 2002 A1
20020085843 Mann Jul 2002 A1
20020094026 Edelson Jul 2002 A1
20020098468 Barrett et al. Jul 2002 A1
20020111557 Madill et al. Aug 2002 A1
20020132213 Grant et al. Sep 2002 A1
20020135695 Edelson et al. Sep 2002 A1
20020175897 Pelosi Nov 2002 A1
20020178038 Grybas Nov 2002 A1
20020180761 Edelson et al. Dec 2002 A1
20030000931 Ueda et al. Jan 2003 A1
20030002740 Melikian Jan 2003 A1
20030023592 Modica et al. Jan 2003 A1
20030025884 Hamana et al. Feb 2003 A1
20030075534 Okamoto Apr 2003 A1
20030106787 Santilli Jun 2003 A1
20030111451 Blankenship et al. Jul 2003 A1
20030172032 Choquet Sep 2003 A1
20030186199 McCool Oct 2003 A1
20030228560 Seat et al. Dec 2003 A1
20030234885 Pilu Dec 2003 A1
20040009462 McElwrath Jan 2004 A1
20040020907 Zauner et al. Feb 2004 A1
20040035990 Ackeret Feb 2004 A1
20040050824 Samler Mar 2004 A1
20040088071 Kouno May 2004 A1
20040140301 Blankenship et al. Jul 2004 A1
20040167788 Birimisa et al. Aug 2004 A1
20040181382 Hu Sep 2004 A1
20050007504 Fergason Jan 2005 A1
20050017152 Fergason Jan 2005 A1
20050029326 Henrikson Feb 2005 A1
20050046584 Breed Mar 2005 A1
20050050168 Wen et al. Mar 2005 A1
20050101767 Clapham et al. May 2005 A1
20050103766 Iizuka et al. May 2005 A1
20050103767 Kainec et al. May 2005 A1
20050109735 Flood May 2005 A1
20050128186 Shahoain et al. Jun 2005 A1
20050133488 Blankenship et al. Jun 2005 A1
20050159840 Lin et al. Jul 2005 A1
20050163364 Beck Jul 2005 A1
20050189336 Ku Sep 2005 A1
20050199602 Kaddani et al. Sep 2005 A1
20050230573 Ligertwood Oct 2005 A1
20050233295 Chiszar et al. Oct 2005 A1
20050252897 Hsu et al. Nov 2005 A1
20050275913 Vesely et al. Dec 2005 A1
20050275914 Vesely et al. Dec 2005 A1
20060014130 Weinstein Jan 2006 A1
20060076321 Maev Apr 2006 A1
20060136183 Choquet Jun 2006 A1
20060149502 Tseng et al. Jun 2006 A1
20060154226 Maxfield Jul 2006 A1
20060163227 Hillen et al. Jul 2006 A1
20060163228 Daniel Jul 2006 A1
20060166174 Rowe Jul 2006 A1
20060169682 Kainec et al. Aug 2006 A1
20060173619 Brant et al. Aug 2006 A1
20060189260 Sung Aug 2006 A1
20060207980 Jocovetty et al. Sep 2006 A1
20060213892 Ott Sep 2006 A1
20060214924 Kawamoto et al. Sep 2006 A1
20060226137 Huismann et al. Oct 2006 A1
20060241432 Herline et al. Oct 2006 A1
20060252543 Van Noland et al. Nov 2006 A1
20060258447 Baszucki et al. Nov 2006 A1
20070034611 Drius et al. Feb 2007 A1
20070038400 Lee et al. Feb 2007 A1
20070045488 Shin Mar 2007 A1
20070088536 Ishikawa Apr 2007 A1
20070112889 Cook et al. May 2007 A1
20070188606 Atkinson et al. Aug 2007 A1
20070198117 Wajhuddin Aug 2007 A1
20070211026 Ohta et al. Sep 2007 A1
20070221797 Thompson et al. Sep 2007 A1
20070256503 Wong et al. Nov 2007 A1
20070264620 Maddix et al. Nov 2007 A1
20070277611 Portzgen et al. Dec 2007 A1
20070291035 Vesely et al. Dec 2007 A1
20080021311 Goldbach Jan 2008 A1
20080027594 Jump et al. Jan 2008 A1
20080031774 Magnant et al. Feb 2008 A1
20080038702 Choquet Feb 2008 A1
20080061049 Albrecht Mar 2008 A1
20080078811 Hillen et al. Apr 2008 A1
20080078812 Peters et al. Apr 2008 A1
20080107345 Melikian May 2008 A1
20080117203 Gering May 2008 A1
20080120075 Wloka May 2008 A1
20080128398 Schneider Jun 2008 A1
20080135533 Ertmer et al. Jun 2008 A1
20080140815 Brant et al. Jun 2008 A1
20080149686 Daniel et al. Jun 2008 A1
20080203075 Feldhausen et al. Aug 2008 A1
20080233550 Solomon Sep 2008 A1
20080249998 Dettinger et al. Oct 2008 A1
20080303197 Paquette et al. Dec 2008 A1
20080314887 Stoger et al. Dec 2008 A1
20090015585 Klusza Jan 2009 A1
20090021514 Klusza Jan 2009 A1
20090045183 Artelsmair et al. Feb 2009 A1
20090050612 Serruys et al. Feb 2009 A1
20090057286 Ihara et al. Mar 2009 A1
20090109128 Nangle Apr 2009 A1
20090152251 Dantinne et al. Jun 2009 A1
20090173726 Davidson et al. Jul 2009 A1
20090184098 Daniel et al. Jul 2009 A1
20090197228 Afshar et al. Aug 2009 A1
20090200281 Hampton Aug 2009 A1
20090200282 Hampton Aug 2009 A1
20090231423 Becker et al. Sep 2009 A1
20090257655 Melikian Oct 2009 A1
20090259444 Dolansky et al. Oct 2009 A1
20090298024 Batzier et al. Dec 2009 A1
20090312958 Dai et al. Dec 2009 A1
20090325699 Delgiannidis Dec 2009 A1
20100012017 Miller Jan 2010 A1
20100012637 Jaeger Jan 2010 A1
20100021051 Melikian Jan 2010 A1
20100048273 Wallace et al. Feb 2010 A1
20100062405 Zboray et al. Mar 2010 A1
20100062406 Zboray Mar 2010 A1
20100096373 Hillen et al. Apr 2010 A1
20100121472 Babu et al. May 2010 A1
20100133247 Mazumder et al. Jun 2010 A1
20100133250 Sardy et al. Jun 2010 A1
20100176107 Bong Jul 2010 A1
20100201803 Melikian Aug 2010 A1
20100224610 Wallace Sep 2010 A1
20100276396 Cooper Nov 2010 A1
20100299101 Shimada et al. Nov 2010 A1
20100307249 Lesage et al. Dec 2010 A1
20100314362 Albrecht Dec 2010 A1
20110006047 Penrod Jan 2011 A1
20110048273 Colon Mar 2011 A1
20110052046 Melikian Mar 2011 A1
20110060568 Goldfine Mar 2011 A1
20110082728 Melikian Apr 2011 A1
20110091846 Kreindl Apr 2011 A1
20110011752 Conrardy May 2011 A1
20110114615 Daniel et al. May 2011 A1
20110116076 Chantry et al. May 2011 A1
20110117527 Conrardy May 2011 A1
20110122495 Togashi May 2011 A1
20110183304 Wallace et al. Jul 2011 A1
20110187746 Suto Aug 2011 A1
20110187859 Edelson Aug 2011 A1
20110229864 Short et al. Sep 2011 A1
20110248864 Becker et al. Oct 2011 A1
20110316516 Schiefermuller et al. Dec 2011 A1
20120189993 Kinding et al. Jul 2012 A1
20120291172 Wills et al. Nov 2012 A1
20120298640 Conrardy Nov 2012 A1
20130026150 Chantry et al. Jan 2013 A1
20130040270 Albrecht Feb 2013 A1
20130049976 Maggiore Feb 2013 A1
20130075380 Albrech et al. Mar 2013 A1
20130119040 Suraba et al. May 2013 A1
20130170259 Chang et al. Jul 2013 A1
20130182070 Peters et al. Jul 2013 A1
20130183645 Wallace et al. Jul 2013 A1
20130189657 Wallace et al. Jul 2013 A1
20130189658 Peters et al. Jul 2013 A1
20130203029 Choquet Aug 2013 A1
20130206740 Pfeifer et al. Aug 2013 A1
20130209976 Postlewaite et al. Aug 2013 A1
20130230832 Peters et al. Sep 2013 A1
20130231980 Elgart Sep 2013 A1
20130252214 Choquet Sep 2013 A1
20130260261 Kotani et al. Oct 2013 A1
20130288211 Patterson et al. Oct 2013 A1
20130327747 Dantinne Dec 2013 A1
20130342678 McAninch et al. Dec 2013 A1
20140038143 Daniel Feb 2014 A1
20140042136 Daniel et al. Feb 2014 A1
20140065584 Wallace et al. Mar 2014 A1
20140134580 Becker May 2014 A1
20140263224 Becker Sep 2014 A1
20140272835 Becker Sep 2014 A1
20140272836 Becker Sep 2014 A1
20140272837 Becker Sep 2014 A1
20140272838 Becker Sep 2014 A1
20140312020 Daniel Oct 2014 A1
20140346158 Matthews Nov 2014 A1
20150056584 Boulware Feb 2015 A1
20150056585 Boulware Feb 2015 A1
20150056586 Penrod Feb 2015 A1
20150072323 Postlethwaite Mar 2015 A1
20150194073 Becker et al. Jul 2015 A1
20150235565 Postlethwaite Aug 2015 A1
20150248845 Postlethwaite Sep 2015 A1
20160093233 Boulware Mar 2016 A1
20160125763 Becker May 2016 A1
20160203734 Boulware Jul 2016 A1
20160203735 Boulware Jul 2016 A1
20160331592 Stewart Nov 2016 A1
20160343268 Postlethwaite Nov 2016 A1
20170053557 Daniel Feb 2017 A1
Foreign Referenced Citations (112)
Number Date Country
2698078 Sep 2011 CA
1665633 Sep 2005 CN
201083660 Jul 2008 CN
201149744 Nov 2008 CN
101406978 Apr 2009 CN
101419755 Apr 2009 CN
201229711 Apr 2009 CN
101571887 Nov 2009 CN
101587659 Nov 2009 CN
101661589 Mar 2010 CN
102053563 May 2011 CN
102083580 Jun 2011 CN
102202836 Sep 2011 CN
202053009 Nov 2011 CN
202684308 Jan 2013 CN
203503228 Mar 2014 CN
103871279 Jun 2014 CN
2833638 Feb 1980 DE
3046634 Jan 1984 DE
3244307 May 1984 DE
3522581 Jan 1987 DE
4037879 Jun 1991 DE
19615069 Oct 1997 DE
19739720 Oct 1998 DE
19834205 Feb 2000 DE
20009543 Aug 2001 DE
102005047204 Apr 2007 DE
102006048165 Jan 2008 DE
102010038902 Feb 2012 DE
0008527 Mar 1980 EP
108599 May 1984 EP
127299 Dec 1984 EP
145891 Jun 1985 EP
319623 Oct 1990 EP
852986 Jul 1998 EP
1527852 May 2005 EP
1905533 Apr 2008 EP
2274736 May 2007 ES
1456780 Mar 1965 FR
2827066 Jan 2003 FR
2926660 Jul 2009 FR
1455972 Nov 1976 GB
1511608 May 1978 GB
2254172 Sep 1992 GB
2435838 Sep 2007 GB
2454232 May 2009 GB
02-224877 Sep 1990 JP
05-329645 Dec 1993 JP
07-047471 Feb 1995 JP
07-232270 Sep 1995 JP
08-505091 Apr 1996 JP
08-150476 Jun 1996 JP
108221107 Aug 1996 JP
08-132274 May 1998 JP
2000-167666 Jun 2000 JP
2000-237872 Sep 2000 JP
2001-071140 Mar 2001 JP
2002278670 Sep 2002 JP
2003-200372 Jul 2003 JP
2003-326362 Nov 2003 JP
2004025270 Jan 2004 JP
2006006604 Jan 2006 JP
2006-175205 Jul 2006 JP
2006-281270 Oct 2006 JP
2007290025 Nov 2007 JP
2009500178 Jan 2009 JP
2009160636 Jul 2009 JP
2010-231792 Oct 2010 JP
2012024867 Feb 2012 JP
100876425 Dec 2008 KR
20090010693 Jan 2009 KR
20110068544 Jun 2011 KR
527045 Jul 1995 RU
2317183 Feb 2008 RU
2008108601 Nov 2009 RU
10388963 Aug 1983 SU
1998045078 Oct 1998 WO
200112376 Feb 2001 WO
2001043910 Jun 2001 WO
2001058400 Aug 2001 WO
2004029549 Apr 2004 WO
2005102230 Nov 2005 WO
2005110658 Nov 2005 WO
2006034571 Apr 2006 WO
2007039278 Apr 2007 WO
2009060231 May 2009 WO
2009120921 Oct 2009 WO
2009149740 Dec 2009 WO
2010000003 Jan 2010 WO
2010044982 Apr 2010 WO
2010091493 Aug 2010 WO
2011045654 Apr 2011 WO
2011058433 May 2011 WO
2011059502 May 2011 WO
2011067447 Jun 2011 WO
2011097035 Aug 2011 WO
2012016851 Feb 2012 WO
2012082105 Jun 2012 WO
2012143327 Oct 2012 WO
2013014202 Jan 2013 WO
2013025672 Feb 2013 WO
2013061518 May 2013 WO
2013114189 Aug 2013 WO
2013119749 Aug 2013 WO
2013175079 Nov 2013 WO
2013186413 Dec 2013 WO
2014007830 Jan 2014 WO
2014019045 Feb 2014 WO
2014020386 Feb 2014 WO
2014140720 Sep 2014 WO
2014184710 Nov 2014 WO
2016137578 Sep 2016 WO
Non-Patent Literature Citations (285)
Entry
International Search Report and Written Opinion from PCT/IB2009/00605 dated Feb. 12, 2010.
International Search Report and Written Opinion from PCT/IB10/02913 dated Apr. 19, 2011.
International Search Report and Written Opinion from PCT/IB2014/002346 dated Feb. 24, 2015.
International Search Report and Written Opinion from PCT/IB2015/000161 dated Jun. 8, 2015.
International Search Report and Written Opinion from PCT/IB2015/000257 dated Jul. 3, 2015.
Notice of Allowance from U.S. Appl. No. 13/543,240 dated Jun. 3, 2015.
16th International Ship and Offshore Structures Congress : Aug. 20-25, 2006; Southhampton, U.K. vol. 2 Specialist Committee V.3 Fabrication Technology Committee Mandate: T. Borzecki, G. Bruce, Y.S. Han, M. Heinermann, A. Imakita, L. Josefson, W. Nie, D. Olsen, F. Roland and Y. Takeda. Naval Ship Design, ABS Papers 2006.
Abbas et al., Code Aster (Software) EDF (France), 14 pages, Oct. 2001.
Abbas et al.; Code_Aster; Introduction to Code_Aster; User Manual; Booklet U1.0-: Introduction to Code_Aster; Document: U1.02.00; Version 7.4; Jul. 22, 2005.
Abid, et al., “Numerical Simulation to study the effect of tack welds and root gap on welding deformations and residual stresses of a pipe flange joint” Intl. J. of Pressure Vessels and Piping, 82, pp. 860-871 (2005).
Abida et al., Numerical simulation to study the effect of tack welds and root gap on welding deformations and residual stresses of a pipe-flange joint, Faculty of Mechanical Engineering, GIK Institute of Engineering Sciences and Technology, Topi, NWFP, Pakistan, 12 pages, Available on-line Aug. 25, 2005.
Agren; Sensor Integration for Robotic Arc Welding; 1995; vol. 5604C of Dissertations Abstracts International p. 1123; Dissertation Abs Online (Dialog® File 35): © 2012 ProQuest Info& Learning: http://dialogweb.com/cgi/dwclient?req=1331233317524; one (1) page; printed Mar. 8, 2012.
Aidun et al., “Penetration in Spot GTA Welds during Centrifugation,” Journal of Materials Engineering and Performance vol. 7(5) Oct. 1998—597-600.
ANSI/A WS D 10.11 MID 10. 11 :2007 Guide for Root Pass Welding of Pipe without Backing Edition: 3rd American Welding Society / Oct. 13, 2006 /36 pages ISBN: 0871716445, 6 pages.
Antonelli et al., “A Semi-Automated Welding Station Exploiting Human-robot Interaction”, Dept. of Production Systems and Economics, pp. 249-260, 2011.
Arc+ simulator; 2 pgs., http://www.123arc.com/en/depliant_ang.pdf; 2000.
Asciencetutor.com, A division of Advanced Science and Automation Corp., VWL (Virtual Welding Lab), 2 pages, 2007.
ASME Definitions, Consumables, Welding Positions, dated Mar. 19, 2001. See http://www.gowelding.com/wp/asme4.htm.
B. Virtual Reality Welder Trainer, Session 5, joining Technologies for Naval Applications, earliest date Jul. 14, 2006 (Nancy Porter of EWI).
Balijepalli et al., Haptic Interfaces for Virtual Environment and Teleoperator Systems, Haptics 2003, 7-.,Department of Mechanical & Aerospace Engineering, State University of New York at Buffalo, NY.
Borzecki et al., Specialist Committee V.3 Fabrication Technology Committee Mandate, Aug. 20-25, 2006, 49 pages, vol. 2, 16th International Ship and Offshore Structures Congress, Southampton, UK.
Boss (engineering), Wikipedia, 1 page, printed Feb. 6, 2014.
ChemWeb.com, Journal of Materials Engineering and Performance (v.7, #5), 3 pgs., printed Sep. 26, 2012.
Chen et al., Self-Learning Fuzzy Neural Networks and Computer Vision for Control of Pulsed GTAW, Welding Research Supplement, pp. 201-209, dated May 1997.
Choquet, “ARC+: Today's Virtual Reality Solution for Welders” Internet Page, Jan. 1, 2008, 6 pages.
Code Aster (Software) EDF (France), Oct. 2001.
Cooperative Research Program, Virtual Reality Welder Training, Summary Report SR 0512, 4 pages, Jul. 2005.
CS Wave, The Virtual Welding Trainer, 6 pages, 2007.
CS Wave, A Virtual learning tool for welding motion, 10 pages, Mar. 14, 2008.
CS Wave, Product Description, 2 pages, printed Jan. 14, 2015.
Desroches; Code-Aster, Note of use for calculations of welding; Instruction manual U2.03 booklet: Thermomechanical; Document: U2.03.05; Oct. 1, 2003.
D'Huart et al.; Virtual Environment for Training: An Art of Enhancing Reality, 6th International Conference, ITS 20002, Biarritz, France and San Sebastian, Spain, 6 pages, Jun. 2002.
Dotson, Augmented Reality Welding Helmet Prototypes How Awesome the Technology Can Get, Sep. 26, 2012, Retrieved from the Internet: URL:http://siliconangle.com/blog/2012/09/26/augmented-reality-welding-helmet-prototypes-how-awesome-the-technology-can-get/,1 page, retrieved on Sep. 26, 2014.
Echtler et al., “The Intelligent Welding Gun: Augmented Reality of Experimental Vehicle Construction”, Virtual and Augmented Reality Applications in Manufacturing, 17, pp. 1-27, Springer Verlag, 2003.
Edison Welding Institute, E-Weld Predictor, 3 pages, 2008.
Eduwelding+, Weld Into the Future; Online Welding Seminar—A virtual training environment; 123arc.com; 4 pages, 2005.
Eduwelding+, Training Activities with arc+ simulator; Weld Into the Future, Online Welding Simulator—A virtual training environment; 123arc.com; 6 pages, May 2008.
Erden, “Skill Assistance with Robot for Manual Welding”, Marie Curie Intra-European Fellowship, Project No. 297857, 3 pgs., printed Apr. 27, 2015.
EWM Virtual Welding Trainer, 2 pages, printed Jan. 14, 2015.
The Fabricator, Virtually Welding, Training in a virtual environment gives welding students a leg up, 4 pages, Mar. 2008.
Fast et al., “Virtual Training for Welding”, Mixed and Augmented Reality, 2004, ISMAR 2004, Third IEEE and CM International Symposium on Arlington, VA, Nov. 2-5, 2004.
Fillet weld, Wikipedia, 3 pgs. Printed Feb. 6, 2014.
Fronius, ARS Electronica Linz GMBH, High-speed video technology is applied to research on welding equipment, and the results are visualized in the CAVE, 2 pages, May 18, 1997.
Fronius, Virtual Welding, 8 pages, printed Jan. 14, 2015.
Joanneum, Fronius—virtual welding, 2 pages, May 12, 2008.
Fronius, Virtual Welding/The Welder Training of the Future/, 8 page brochure, 2011.
Garcia-Allende et al.; Defect Detection in Arc-Welding Processes by Means of the Line-to-Continuum Method and Feature Selection; www.mdpi.com/journal/sensors; Sensors 2009, 9, 7753-7770; doi; 10.3390/s91007753.
International Search Report and Written Opinion from International Application No. PCT/US10/60129 dated Feb. 10, 2011.
International Search Report and Written Opinion from International Application No. PCT/US12/45776 dated Oct. 1, 2012.
Office Action from U.S. Appl. No. 12/499,687 dated Oct. 16, 2012.
“Numerical Analysis of Metal Transfer in Gas Metal Arc Welding,” G. Wang, P.G. Huang, and Y.M. Zhang. Departments of Mechanical and Electrical Engineering. University of Kentucky, Dec. 10, 2001.
Numerical Analysis of Metal Transfer in Gas Metal Arc Welding Under Modified Pulsed Current Conditions, G. Wang, P.G. Huang, and Y.M. Zhang. Metallurgical and Materials Transactions B, vol. 35B, Oct. 2004, pp. 857-866.
Wang et al., Study on welder training by means of haptic guidance and virtual reality for arc welding, 2006 IEEE International Conference on Robotics and Biomimetics, ROBIO 2006 ISBN-10: 1424405718, p. 954-958.
Weld nut, Wikipedia, 2 pgs. Printed Feb. 6, 2014.
Weldplus, Welding Simulator, 2 pages, printed Jan. 14, 2015.
White et al., Virtual welder training, 2009 IEEE Virtual Reality Conference, p. 303, 2009.
Chuansong Wu, “Microcomputer-based welder training simulator”, Computers in Industry, vol. 20, No. 3, Oct. 1992, pp. 321-325, XP000205597, Elsevier Science Publishers, Amsterdam, NL.
Wuhan Onew Technology Co., Ltd., “Onew Virtual Simulation Expert”, 16 pgs., printed Apr. 16, 2015.
Yao et al., ‘Development of a Robot System for Pipe Welding’. 2010 International Conference on Measuring Technology and Mechatronics Automation. Retrieved from the Internet: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5460347&tag=1; pp. 1109-1112, 4 pages.
EnergynTech Inc.; website printout; http://www.energyntech.com./; Advanced Metals Processing Technology & Flexible Automation for Manufacturing; Virtual Welder; Virtual training system for beginning welders; 2 page; 2014.
EnergynTech Inc.; website printout; http://www.energyntech.com/Zipper.html; Zipper Robot Performing a HiDep Weld; 1 page; 2014.
Terebes; Institute of Automation; University of Bremen; Project Motivation Problems Using Traditional Welding Masks; 2 page; 2015.
WeldWatch Software/Visible Welding; website printout; http://visiblewelding.com/weldwatch-software/4 pages; 2015.
Products/Visible Welding; Weldwatch Video Monitoring System; website prinout http://visiblewelding.com/products; 4 pages; 2015.
NSRP—Virtual Welding—A Low Cost Virtual Reality Welder Training System—Phase II—Final Report; Feb. 29, 2012; Kenneth Fast, Jerry Jones, Valerie Rhoades; 53 pages.
Corrected Notice of Allowance from U.S. Appl. No. 12/966,570 dated Feb. 23, 2015.
Office Action from U.S. Appl. No. 14/444,173 dated Mar. 18, 2015.
Response to Office Action dated Mar. 18, 2015 from U.S. Appl. No. 14/444,173 dated Jun. 11, 2015.
Notice of Allowance from U.S. Appl. No. 14/444,173 dated Jun. 24, 2015.
Response from U.S. Appl. No. 12/499,687 dated Apr. 10, 2013.
Office Action from U.S. Appl. No. 12/499,687 dated Jun. 26, 2013.
Response from U.S. Appl. No. 12/499,687 dated Nov. 25, 2013.
Office Action from U.S. Appl. No. 12/499,687 dated Mar. 6, 2014.
Response from U.S. Appl. No. 12/499,687 dated Sep. 5, 2014.
Office Action from U.S. Appl. No. 12/499,687 dated Nov. 6, 2014.
Office Action from U.S. Appl. No. 12/966,570 dated May 8, 2013.
Response from U.S. Appl. No. 12/966,570 dated Oct. 8, 2013.
Notice of Allowance from U.S. Appl. No. 12/966,570 dated Apr. 29, 2014.
Office Action from U.S. Appl. No. 13/543,240 dated Nov. 14, 2014.
Notice of Allowance from U.S. Appl. No. 13/543,240 dated Sep. 3, 2015.
International Search Report and Written Opinion from PCT/IB2015/000777 dated Sep. 21, 2015.
International Search Report and Written Opinion from PCT/IB2015/000814 dated Nov. 5, 2015.
International Search Report and Written Opinion from PCT/IB2015/001711 dated Jan. 4, 2016.
Narayan et al., “Computer Aided Design and Manufacturing,” pp. 3-4, 14-15, 17-18, 92-95, and 99-100, Dec. 31, 2008.
International Preliminary Report on Patentability from PCT/IB2014/001796 dated Mar. 15, 2016.
Office action from U.S. Appl. No. 15/077,481 dated May 23, 2016.
Response from U.S. Appl. No. 15/077,481 dated Jun. 23, 2016.
Office Action from Chinese Application No. 201280075678.5 dated Jul. 5, 2016.
Notice of Allowance from U.S. Appl. No. 15/077,481 dated Aug. 10, 2016.
Office Action from Chinese Application No. 201480027306.4 dated Aug. 3, 2016.
Office Action from Chinese Application No. 201380017661.9 dated Aug. 22, 2016.
International Preliminary Report on Patentability from PCT/IB2015/000161 dated Aug. 25, 2016.
International Preliminary Report on Patentability from PCT/IB2015/000257 dated Sep. 15, 2016.
Office Action from Chinese Application No. 201480025359.2 dated Sep. 26, 2016.
Office Action from U.S. Appl. No. 14/190,812 dated Nov. 9, 2016.
Office Action from Chinese Application No. 201480025614.3 dated Nov. 28, 2016.
Office Action from U.S. Appl. No. 14/293,700 dated Dec. 28, 2016.
Office Action from U.S. Appl. No. 14/293,826 dated Dec. 30, 2016.
Juan Vicenete Rosell Gonzales, “RV-Sold: simulator virtual para la formacion de soldadores”; Deformacion Metalica, Es. vol. 34, No. 301, Jan. 1, 2008.
The Goodheart-Wilcox Co., Inc., Weld Joints and Weld Types, Chapter 6, pp. 57-68, date unknown.
Graham, Texture Mapping, Carnegie Mellon University Class 15-462 Computer Graphics, Lecture 10, 53 pages, dated Feb. 13, 2003.
Guu et al.,Technique for Simultaneous Real-Time Measurements of Weld Pool Surface Geometry and Arc Force, Welding Research Supplement—pp. 473-482, Dec. 1992.
Hills et al.; “Data Parallel Algorithms”, Communications of the ACM, Dec. 1986, vol. 29, No. 12, p. 1170.
Hirche et al., Hardware Accelerated Per-Pixel Displacement Mapping, 8 pages, 2004.
Hu et al., Heat and mass transfer in gas metal arc welding. Part 1: the arc, found in ScienceDirect, International Journal of Heat and Mass Transfer 50 (2007), 14 pages, 833-846 Available online on Oct. 24, 2006, http://www.web.mst.edu/˜tsai/publications/HU-IJHMT-2007-1-60.pdf.
Aidun, Influence of Simulated High-g on the Weld Size of Al—Li Alloy, Acta Astronautica, vol. 48, No. 2-3, pp. 153-156, 2001.
Jonsson et al., Simulation of Tack Welding Procedures in Butt Joint Welding of Plates Welding Research Supplement, Oct. 1985, pp. 296-302.
Kemppi ProTrainer, product data, 3 pages, printed Jan. 14, 2015.
Konstantinos Nasios (Bsc), Improving Chemical Plant Safety Training Using Virtual Reality, Thesis submitted to the University of Nottingham for the Degree of Doctor of Philosophy, 313 pages, Dec. 2001.
Leap Motion, Inc., product information, copyright 2013, 14 pages.
Learning Labs, Inc., Seabery, Soldamatic Augmented Reality Welding Trainers, 4 pgs., printed Mar. 20, 2014.
Lim et al., “Automatic classification of weld defects using simulated data and MLP neural network”, Insight, vol. 49, No. 3, Mar. 2007.
Wade, Human uses of ultrasound: ancient and modern Department of Electrical and Computer Engineering, University of California at Santa Barbara 93106, USA. Ultrasonics (Impact Factor: 1.81). Apr. 2000; 38(1-8):1-5.
Production Monitoring 2 brochure, four (4) pages, The Lincoln Electric Company, May 2009.
The Lincoln Electric Company; CheckPoint Production Monitoring brochure; four (4) pages; http://www.lincolnelectric.com/assets/en_US/products/literature/s232.pdf; Publication S2.32; Issue Date Feb. 2012.
Lincoln Electric, Vrtex Virtual Reality Arc Welding Trainer, 9 pgs. Printed Feb. 2, 2014.
Lincoln Electric, Vrtex 360 Virtual Reality Arc Welding Trainer, 4 pgs., Oct. 2014.
Linholm et al., “NVIDIA Testla: A Unifired Graphics and Computing Architecture”, IEEE Computer Society, 2008.
Mahrle et al., “The influence of fluid flow phenomena on the laser beam welding process”, Intl. J. of Heat and Fluid Flow, 23, pp. 288-297 (2002).
Mann et al., Realtime HDR (High Dynamic Range) Video for Eyetap Wearable Compuerts, FPGA-based Seeing Aids, and Glasseyes (Eyetaps), 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), pp. 1-6, 6 pages, Apr. 29, 2012.
Yosh Mantinband et al., Autosteroscopic, field-sequential display with full freedom of movement or Let the display were the shutter-glasses, yosh@3ality.com, (Israel) Ltd., 8 pages, 2002.
Mavrikios et al., A prototype virtual reality-based demonstrator for immersive and interactive simulation of welding processes, International Journal of Computer Integrated manufacturing, Taylor and Francis, Basingstoke, GB, vol. 19, No. 3, Apr. 1, 2006, pp. 294-300.
Mechanisms and Mechanical Devices Sourcebook, Chironis, McGraw Hill, Neil Sclater, 2nd Ed. 1996.
Miller Electric Mfg. Co., “LiveArc Welding Performance Management System”, 4 pg. brochure, Dec. 2014.
Miller Electric, Owner's Manual, Live Arc, Welding Performance Management System, Owners's Manual—OM-267 357A; 64 pgs., Jul. 2014.
Miller Electric Mgf. Co.; MIG Welding System features weld monitoring software; NewsRoom 2010 (Dialog® File 992); © 2011 Dialog. 2010; http://www.dialogweb.com/cgi/dwclient?reg=1331233430487; three (3) pages; printed Mar. 8, 2012.
N. A. Tech., P/NA.3 Process Modeling and Optimization, 11 pages, Jun. 4, 2008.
NSRP ASE, Low-Cost Virtual Reality Welder Training System, 1 Page, 2008.
NVIDIA Tesla: A Unified Graphics and Computing Architecture, IEEE Computer Society 0272-1732, Mar.-Apr. 2008.
O'Brien, “Google's Project Glass gets some more details”,Jun. 27, 2012 (Jun. 27, 2012), Retrieved from the Internet: http://www.engadget.com/2012/06/27/googles-project-glass-gets-some-more-details/, 1 page, retrieved on Sep. 26, 2014.
Porter et al., Virtual Reality Training, Paper No. 2005-P19, 14 pages, 2005.
Porter et al., Virtual Reality Welder Training, 29 pages, dated Jul. 14, 2006.
Porter, Virtual Reality Welder Trainer, Session 5: Joining Technologies for Naval Applications: earliest date Jul. 14, 2006 (http://weayback.archive.org), Edision Welding Institute; J. Allan Cote, General Dynamics Electric Boat; Timothy D. Gifford, VRSim, and Wim Lam, FCS Controls.
Praxair, “The RealWeld Trainer System”, two page brochure, 2013.
Ratnam et al., “Automatic classification of weld defects using simulated data and an MLP neutral network.” Insight vol. 49, No. 3; Mar. 2007.
Reeves, “Particles Systems—A Technique for Modeling a Class of Fuzzy Objects”, Computer Graphics 17:3 pp. 359-376, 1983, 17 pages.
Rodjito, Position tracking and motion prediction using Fuzzy Logic, 81 pages, 2006, Colby College, Honors Theses, Paper 520.
Russell et al., “Artificial Intelligence: A Modern Approach”, Prentice-Hall (Copyright 1995).
Schoder, “Design and Implementation of a Video Sensor for Closed Loop Control of Back Bead Weld Puddle Width,” Massachusetts Institute of Technology, Dept. of Mechanical Engineering, May 27, 1983.
Seabury Soluciones, Soldamatic Welding Trainer Simulator, 30 pages, printed Jan. 14, 2015.
SIMFOR / CESOL, “RV-Sold” Welding Simulator, Technical and Functional Features, 20 pages, no date available.
Sim Welder, Train better welders faster, retrieved on Apr. 12, 2010 from: http://www.simwelder.com.
Training in a virtual environment gives welding students a leg up, retrieved on Apr. 12, 2010 from: http://www.thefabricator.com/article/arcwelding/virtually-welding.
Teeravarunyou et al., “Computer Based Welding Training System”, Intl J of Industrial Engineering, 16 (2), pp. 116-125 (2009).
Veiga, Simulation of a Work Cell in the IGRIP Program, dated 2006, 50 pages.
ViziTech USA, Changing the Way America Learns, retrieved on Mar. 27, 2014 from http://vizitechusa.com/, 2 pages.
Response to Office Action dated Nov. 14, 2014 from U.S. Appl. No. 13/543,240 dated Mar. 13, 2015.
Office Action from U.S. Appl. No. 14/190,812 dated Feb. 23, 2017.
Office Action from U.S. Appl. No. 14/552,739 dated Feb. 17, 2017.
Office Action from U.S. Appl. No. 14/615,637 dated Apr. 27, 2017.
Office Action from Chinese Application No. 201480025359.2 dated Feb. 28, 2017.
Office Action from Chinese Application No. 201380076368.X dated Mar. 1, 2017.
Yaoming, “Applications of Microcomputer in Robot Technology,” Scientific and Technical Documentation Press, Sep. 1987, pp. 360-365.
Adams et al., “Adaptively Sampled Particle Fluids,” ACM Transactions on Graphics, vol. 26, No. 3, Article 48, Jul. 2007, pp. 48.1-48.7.
Bargteil et al., “A Texture Synthesis Method for Liquid Animations,” Eurographics/ ACM SIGGRAPH Symposium on Computer Animation, 2006, pp. 345-351.
Bargteil et al., “A Semi-Lagrangian Contouring Method for Fluid Simulation,” ACM Transactions on Graphics, vol. 25, No. 1, Jan. 2006, pp. 19-38.
Chentanez et al., “Liquid Simulation on Lattice-Based Tetrahedral Meshes,” Eurographics/ACM SIGGRAPH Symposium on Computer Animation, 2007, 10 pages.
Chentanez et al., “Simultaneous Coupling of Fluids and Deformable Bodies,” Eurographics/ ACM SIGGRAPH Symposium on Computer Animation, 2006, pp. 83-89.
Clausen et al., “Simulating Liquids and Solid-Liquid Interactions with Lagrangian Meshes,” ACM Transactions on Graphics, vol. 32, No. 2, Article 17, Apr. 2013, pp. 17.1-17.15.
Feldman et al., “Animating Suspended Particle Explosions,” Computer Graphics Proceedings, Annual Conference Series, Jul. 27-31, 2003, pp. 1-8.
Feldman et al., “Fluids in Deforming Meshes,” Eurographics/ACM SIGGRAPH Symposium on Computer Animation, 2005, pp. 255-259.
Foster et al., “Practical Animation of Liquids,” ACM SIGGRAPH, Aug. 12-17, 2001, Los Angeles, CA, pp. 23-30.
Foster et al., “Realistic Animation of Liquids,” Graphical Models and Image Processing, vol. 58, No. 5, Sep. 1996, pp. 471-483.
Goktekin et al., “A Method for Animating Viscoelastic Fluids,” Computer Graphics Proceedings, Annual Conference Series, Aug. 8-12, 2004, pp. 1-6.
Holmberg et al., “Efficient Modeling and Rendering of Turbulent Water over Natural Terrain,” Proceedings of the 2nd International Conference on Computer Graphics and Interactive Techniques in Australasia and South East Asia, Singapore, Jun. 15-18, 2004, pp. 15-22.
Irving et al., “Efficient Simulation of Large Bodies of Water by Coupling Two and Three Dimensional Techniques,” ACM Transactions on Graphics (TOG), vol. 25, Issue 3, Jul. 2006, pp. 805-811.
Kass et al., “Rapid, Stable Fluid Dynamics for Computer Graphics,” Computer Graphics, vol. 24, No. 4, Aug. 1990, pp. 49-57.
Klinger et al., “Fluid Animation with Dynamic Meshes,” Computer Graphics Proceedings, Annual Conference Series, Jul. 30-Aug. 3, 2006, pp. 820-825.
Muller et al., “Particle-Based Fluid Simulation for Interactive Applications,” Eurographics/SIGGRAPH Symposium on Computer Animation (2003), pp. 154-159 and 372.
O'Brien et al., “Dynamic Simulation of Splashing Fluids,” Proceedings of Computer Animation, Apr. 19-21, 1995, Geneva, Switzerland, pp. 198-205.
Premoze et al., “Particle-Based Simulation of Fluids,” Eurographics, vol. 22, No. 3, 2003, 10 pages.
Rasmussen et al., “Directable Photorealistic Liquids,” Eurographics/ACM SIGGRAPH Symposium on Computer Animation, 2004, pp. 193-202.
Stam, “Stable Fluids,” SIGGRAPH 99 Conference Proceedings, Annual Conference Series, Aug. 1999, pp. 121-128.
Thurey et al., “Real-time Breaking Waves for Shallow Water Simulations,” Proceedings of the Pacific Conference on Computer Graphics and Applications, Maui, HI Oct. 29-Nov. 2, 2007, 8 pages.
Notice of Allowance from U.S. Appl. No. 14/293,700 dated May 10, 2017.
Xie et al., “A Real-Time Welding Training System Base on Virtual Reality,” Wuhan Onew Technology Co., Lid, IEEE Virtual Reality Conference Mar. 23-27, 2015, Arles France, pp. 309-310.
International Preliminary Report on Patentability from PCT/IB2015/001084 dated Jan. 26, 2017.
Grahn et al., “Interactive Simulation of Contrast Fluid using Smoothed Particle Hydrodynamics,” Jan. 1, 2008, Masters Thesis in Computing Science, Umea University, Department of Computing Science, Umea Sweden, 69 pages.
Vesterlund et al., “Simulation and Rendering of a Viscous Fluid using Smoothed Particle Hydrodynamics,” Dec. 3, 2004, Master's Thesis in Computing Science, Umea University, Department of Computing Science, Umea Sweden; 46 pages.
Muller et al., “Point Based Animation of Elastic, Plastic and Melting Objects,” Eurographics/ACM SIGGRAPH Symposium on Computer Animation (2004), 11 pages.
Nealen, “Point-Based Animation of Elastic, Plastic, and Melting Objects,” CG topics, Feb. 2005, 2 pages.
Tonnesen, “Modeling Liquids and Solids using Thermal Particles,” Proceedings of Graphics Interface 1991, pp. 255-262, Calgary, Alberta, 1991.
Cuda, “Programming Guide Version 1.1,” Nov. 29, 2007, 143 pages.
Websters II new college dictionary, 3rd ed., Houghton Mifflin Co., copyright 2005, Boston, MA, p. 1271, definition of Wake, 3 pages.
Da Dalto et al., “CS Wave: Learning welding motion in a virtual environment,” published in Proceedings of the IIW International Conference, Jul. 10-11, 2008, 19 pages.
CS Wave-Manual, “Virtual Welding Workbench User Manual 3.0,” 2007, 25 pages.
Choquet, “ARC+®: Today's Virtual Reality Solution for Welders,” published in Proceedings of the IIW International Conference, Jul. 10-11, 2008, 19 pages.
Welding Handbook, Welding Science & Technology, American Welding Society, Ninth Ed., Copyright 2001, Appendix A, “Terms and Definitions,” 54 pages.
“Virtual Welding: A Low Cost Virtual Reality Welder Training System,” NSRP RA 07-01—BRP Oral Review Meeting in Charleston, SC at ATI, Mar. 2008, 6 pages.
Aiteanu, “Virtual and Augmented Reality Supervisor for a New Welding Helmet,” Dissertation Nov. 15, 2005, 154 pages.
Screen Shot of CS Wave Exercise 135.FWPG Root Pass Level 1 https://web.archive.org/web/20081128081858/http:/wave.c-s.fr/images/english/snap_evolution2.Jpg, 1 page.
Screen Shot of CS Wave Control Centre V3.0.0 https://web.archive.org/web/20081128081915/http:/wave.c-s.fr/images/english/snap_evolution4.jpg, 1 page.
Screen Shot of CS Wave Control Centre V3.0.0 https://web.archive.org/web/20081128081817/http:/wave.c-s.fr/images/english/snap_evolution6.jpg, 1 page.
Da Dalto et al. “CS Wave A Virtual learning tool for the welding motion,” Mar. 14, 2008, 10 pages.
Nordruch et al., “Visual Online Monitoring of PGMAW Without a Lighting Unit,” Jan. 2005, 14 pages.
Tamasi, “The Evolution of Computer Graphics,” NVIDIA, 2008, 36 pages.
VRSim Powering Virtual Reality, www.lincolnelectric.com/en-us/eguipment/lraining-eguipment/Pages/powered-by-'rsim.aspx, 2016, 1 page.
Hillers et al., “Direct welding arc observation without harsh flicker,” 8 pages, allegedly FABTECH International and AWS welding show, 2007.
Declaration of Dr. Michael Zyda, May 3, 2016, exhibit to IPR 2016-00905, 72 pages.
Declaration of Edward Bohnart, Apr. 27, 2016, exhibit to IPR 2016-00905, 23 pages.
Declaration of Dr. Michael Zyda, May 3, 2016, exhibit to IPR 2016-00904, 76 pages.
Declaration of Edward Bohnart, Apr. 27, 2016, exhibit to IPR 2016-00904, 22 pages.
Declaration of Axel Graeser, Apr. 17, 2016, exhibit to IPR 2016-00840, 88 pages.
ARC+ -Archived Press Release from WayBack Machine from Jan. 31, 2008-Apr. 22, 2013, https://web.3rchive.org/web/20121006041803/http://www.123certification.com/en/article_press/index.htm, downloaded on Jan. 21, 2016, 3 pages.
Tschirner et al., “Virtual and Augmented Reality for Quality Improvement of Manual Welds,” National Institute of Standards and Technology, Jan. 2002, Publication 973, 24 pages.
Wang et al., “Impingement of Filler Droplets and Weld Pool During Gas Metal Arc Welding Process,” International Journal of Heat and Mass Transfer, Sep. 1999, 14 pages.
Jeffus, “Welding Principles and Applications,” Sixth Edition, 2008, 10 pages.
Renwick et al., “Experimental Investigation of GTA Weld Pool Oscillations,” Welding Research—Supplement to the Welding Journal, Feb. 1983, 7 pages.
Phar, “GPU Gems 2 Programming Techniques for High-Performance Graphics and General-Purpose Computation,” 2005, 12 pages.
Notice of Allowance from U.S. Appl. No. 15/077,481 dated Feb. 3, 2017.
International Preliminary Report on Patentability from PCT/IB2015/000158 dated Jan. 26, 2017.
Exhibit B from Declaration of Morgan Lincoln in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-cv-01575-DCN, dated Dec. 20, 2016, 5 pages.
International Search Report and Written Opinion from PCT/IB2015/000777 dated Dec. 15, 2016.
International Search Report and Written Opinion from PCT/IB2015/000814 dated Dec. 15, 2016.
“High Performance Computer Architectures: A Historical Perspective,” downloaded May 5, 2016, http://homepages.inf.ed.ac.uk/cgi/mi/comparch. pl?Paru/perf.html,Paru/perf-f.html,Paru/menu-76.html, 3 pages.
Aiteanu et al., “Generation and Rendering of a Virtual Welding Seam in an Augmented Reality Training Environment,” Proceedings of the Sixth IASTED International Conference on Visualization, Imaging and Image Processing, Aug. 28-30, 2006, 8 pages, allegedly Palma de Mallorca, Spain. Ed. J.J. Villaneuva. ACTA Press.
Tschirner et al., “A Concept for the Application of Augmented Reality in Manual Gas Metal Arc Welding,” Proceedings of the International Symposium on Mixed and Augmented Reality; 2 pages; 2002.
Penrod, “New Welder Training Tools,” EWI PowerPoint presentation, 16 pages, allegedly 2008.
Fite-Georgel, “Is there a Reality in Industrial Augmented Reality?” 10th IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 10 pages, allegedly 2011.
Hillers et al., “Real time Arc-Welding Video Observation System,” 62nd International Conference of IIW, Jul. 12-17, 2009, 5 pages, allegedly Singapore 2009.
Advance Program of American Welding Society Programs and Events, Nov. 11-14, 2007, 31 pages, Chicago.
Terebes, examples from http://www.terebes.uni-bremen.de., 6 pages.
Sandor et al., “PAARTI: Development of an Intelligent Welding Gun for BMW,” PIA2003, 7 pages, Tokyo, 2003.
Arvika Forum Vorstellung Projekt PAARI, BMW Group Virtual Reality Center, 4 pages, Nuernberg, 2003.
Sandor et al., “Lessons Learned in Designing Ubiquitous Augmented Reality User Interfaces,” 21 pages, allegedly from Emerging Technologies of Augmented Reality: Interfaces Eds. Haller, M.; Billinghurst, M.; Thomas, B. Idea Group Inc., 2006.
Impact Welding: examples from current and archived website, trade shows, etc. See, e.g., http://www.impactwelding.com, 53 pages.
http://www.nsrp.org/6-Presentations/WDVirtual_Welder.pdf (Virtual Reality Welder Training, Project No. SI051, Navy ManTech Program, Project Review for ShipTech 2005), 22 pages, Biloxi, MS.
https://app.aws_org/w/r/www/wj/2005/031WJ_2005_03.pdf (AWS Welding Journal, Mar. 2005 (see, e.g., p. 54))., 114 pages.
https://app.aws.org/conferences/defense/live index.html (AWS Welding in the Defense Industry conference schedule, 2004), 12 pages.
https://app.aws.org/wj/2004/04/052/njc (AWS Virtual Reality Program to Train Welders for Shipbuilding, workshop Information, 2004), 7 pages.
https://app.aws.org/wj/2007/11WJ200711.pdf (AWS Welding Journal, Nov. 2007), 240 pages.
American Welding Society, “Vision for Welding Industry,” 41 pages.
Energetics, Inc. “Welding Technology Roadmap,” Sep. 2000, 38 pages.
Aiteanu et al., “Computer-Aided Manual Welding Using an Augmented Reality Supervisor,” Sheet Metal Welding Conference XII, Livonia, MI, May 9-12, 2006, 14 pages.
Hillers et al., “Augmented Reality—Helmet for the Manual Welding Process,” Institute of Automation, University of Bremen, Germany, 21 pages.
Aiteanu et al., “A Step Forward in Manual Welding: Demonstration of Augmented Reality Helmet” Institute of Automation, University of Bremen, Germany, Proceedings of the Second IEEE and ACM International Symposium on Mixed and Augmented Reality; 2003, 2 pages.
ArcSentry, “Weld Quality Monitoring System,” Native American Technologies, allegedly 2002, 5 pages.
P/NA.3, “Process Modelling and Optimization,” Native American Technologies, allegedly 2002, 5 pages.
Hillers et al., “TEREBES: Welding Helmet with AR Capabilities,” Institute of Automatic University Bremen; Institute of Industrial Engineering and Ergonomics, 10 pages, allegedly 2004.
Sheet Metal Welding Conference XII, American Welding Society Detroit Section, May 2006, 11 pages.
Fast et al., “Virtual Training for Welding,” Proceedings of the Third IEEE and ACM International Symposium on Mixed and Augmented Reality (ISMAR 2004), 2 pages.
Amended Answer to Complaint with Exhibit A filed by Seabery North America Inc. in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-cv-01575-DCN, doc. No. 44, filed Mar. 1, 2016, in the U.S. District Court for the Northern District of Ohio, 19 pages.
Amended Answer to Complaint with Exhibit A filed by Seabery Soluciones SL in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-cv-01575-DCN, doc. No. 45, filed Mar. 1, 2016, in the U.S. District Court for the Northern District of Ohio, 19 pages.
Reply to Amended Answer to Complaint for Patent Infringement filed by Lincoln Electric Co., Lincoln Global, Inc. In Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-cv-01575-DCN, doc. No. 46, filed Mar. 22, 2016, in the U.S. District Court for the Northern District of Ohio, 5 pages.
Answer for Patent Infringement filed by Lincoln Electric Company, Lincoln Global, Inc. In Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-cv-01575-DCN, doc No. 47, filed Mar. 22, 2016, in the U.S. District Court for the Northern District of Ohio, 5 pages.
Petition for Inter Partes Review of U.S. Pat. No. 8,747,116, IPR 2016-00749, Apr. 7, 2016; 70 pages.
Petition for Inter Partes Review of U.S. Pat. No. RE45,398, IPR 2016-00840, Apr. 18, 2016, 71 pages.
Petition for Inter Partes Review of U.S. Pat. No. 9,293,056, IPR 2016-00904, May 9, 2016, 91 pages.
Petition for Inter Partes Review of U.S. Pat. No. 9,293,057, IPR 2016-00905, May 9, 2016, 87 pages.
http://www.vrsim.net/history, downloaded Feb. 26, 2016, 10:04:37 pm.
Complaint for Patent Infringement in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-av-01575-DCN, doc. No. 1, filed Aug. 10, 2015, in the U.S. District Court for the Northern District of Ohio, 81 pages.
Kobayashi et al., “Simulator of Manual Metal Arc Welding with Haptic Display,” Proc. of the 11th International Conf. on Artificial Reality and Telexistence (ICAT), Dec. 5-7, 2001, pp. 175-178, Tokyo, Japan.
Wahi et al., “Finite-Difference Simulation of a Multi-Pass Pipe Weld,” vol. L, paper 3/1, International Conference on Structural Mechanics in Reactor Technology, San Francisco, CA, Aug. 15-19, 1977.
Declaration of Dr. Michael Zyda, May 3, 2016, exhibit to IPR 2016-00749.
Declaration of Edward Bohnert, Apr. 27, 2016, exhibit to IPR 2016-00749.
Swantec corporate web page downloaded Apr. 19, 2016, http://www.swantec.com/technology/numerical-simulation/.
Catalina et al., “Interaction of Porosity with a Planar Solid/Liquid Interface,” Metallurgical and Materials Transactions, vol. 35A, May 2004, pp. 1525-1538.
Fletcher Yoder Opinion re RE45398 and U.S. Appl. No. 14/589,317, Sep. 9, 2015, 41 pages.
Kobayashi et al., “Skill Training System of Manual Arc Welding by Means of Face-Shield-Like HMD and Virtual Electrode,” Entertainment Computing, vol. 112 of the International Federation for Information Processing (IFIP), Springer Science + Business Media, New York, copyright 2003, pp. 389-396.
G.E. Moore, “No exponential is forever: but Forever can be delayed!,” IEEE International Solid-State Circuits Conference, 2003, 19 pages.
Office Action in CN Application No. 201710087175A dated Feb. 1, 2018.
Office Action in JP Application No. 2015-562352 dated Feb. 6, 2018.
Office Action in JP Application No. 2015-562353 dated Feb. 6, 2018.
Office Action in JP Application No. 2015-562354 dated Feb. 6, 2018.
Office Action in JP Application No. 2015-562355 dated Feb. 6, 2018.
Communication Pursuant to Article 94(3) EPC in EP Application No. 14732357.0 dated Feb. 12, 2018.
Notice of Allowance from U.S. Appl. No. 15/077,532 dated Mar. 28, 2018.
Office Action from CN Application No. 201480060353.9 dated Mar. 30, 2018.
Office Action from U.S. Appl. No. 15/077,532 dated Dec. 29, 2017.
Office Action from U.S. Appl. No. 14/827,657 dated Jan. 16, 2018.
Office Action from U.S. Appl. No. 15/228,524 dated Feb. 5, 2018.
Communication Pursuant to Article 94(3) EPC in EP Application No. 13753204.0 dated Mar. 9, 2017.
Office Action in CN Application No. 201480012861.X dated Jul. 18, 2017.
Office Action in CN Application No. 201610179195.X dated Jul. 19, 2017.
Office Action in CN Application No. 201480025985.1 dated Aug. 10, 2017.
Office Action from U.S. Appl. No. 14/293,826 dated Jul. 21, 2017.
Office Action from Chinese Application No. 201480025614.3 dated Jun. 9, 2017.
Office Action from U.S. Appl. No. 14/829,161 dated Jul. 28, 2017.
Notification of Reason for Refusal from KR Application No. 10-2015-7002697 dated Sep. 25, 2017.
The Lincoln Electric Company, Checkpoint Operator's Manual, 188 pages, issue date Aug. 2015.
Extended European Search Report from EP Application No. 10860823.3 dated Jun. 6, 2017.
Office Action from U.S. Appl. No. 14/827,657 dated May 26, 2017.
Decision of Rejection in CN Application No. 201380047141.2 dated Sep. 7, 2017.
Communication pursuant to Article 94(3) EPC from EP Application No. 15732934.3 dated Apr. 24, 2018.
Communication pursuant to Article 94(3) EPC from EP Application No. 15731664.7 dated Jul. 13, 2018.
Related Publications (1)
Number Date Country
20150125836 A1 May 2015 US
Provisional Applications (1)
Number Date Country
61900136 Nov 2013 US