WO2023101128A1 - 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 장치 및 방법 - Google Patents
이차전지 생산을 위한 레이저 노칭기 시뮬레이션 장치 및 방법 Download PDFInfo
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- WO2023101128A1 WO2023101128A1 PCT/KR2022/010319 KR2022010319W WO2023101128A1 WO 2023101128 A1 WO2023101128 A1 WO 2023101128A1 KR 2022010319 W KR2022010319 W KR 2022010319W WO 2023101128 A1 WO2023101128 A1 WO 2023101128A1
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- laser
- notching machine
- quality
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- laser notching
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- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
- B23K26/00—Working by laser beam, e.g. welding, cutting or boring
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- H01M4/02—Electrodes composed of, or comprising, active material
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- H—ELECTRICITY
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- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
- B23K26/00—Working by laser beam, e.g. welding, cutting or boring
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- B23K26/362—Laser etching
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
Definitions
- the present invention relates to a laser notching machine simulation device and method for secondary battery production, and more particularly, to a laser notching machine simulation device and method for training secondary battery production workers.
- the present invention provides a laser notching machine simulation device (system) for secondary battery production, a method, a computer program stored in a computer readable medium, and a computer readable medium in which the computer program is stored to solve the above problems.
- the present invention may be implemented in a variety of ways, including an apparatus (system), a method, a computer program stored in a computer readable medium, or a computer readable medium in which a computer program is stored.
- a simulation apparatus for producing a secondary battery includes a memory configured to store at least one command and at least one processor configured to execute the at least one command stored in the memory.
- the at least one command includes a device operation unit including a 3D laser notching machine associated with production of a secondary battery, a facility operation unit including a plurality of adjustment parameters for determining the operation of the 3D laser notching machine, and a material produced by the 3D laser notching machine.
- a quality confirmation unit including quality information related to the quality of the laser setting unit including a plurality of laser parameters for determining the operation of the 3D laser notching machine, first user behavior information obtained through the device operation unit, facility operation At least one of first user condition information obtained through the unit and first laser setting information obtained through the laser setting unit is obtained, and at least one of the obtained first user behavior information, the first user condition information, and the first laser setting information is obtained. It includes instructions for determining an operation of the 3D laser notching machine based on and executing an operation of punching an electrode associated with the 3D laser notching machine based on the determined operation.
- the at least one command executes a 3D laser notching machine training scenario based on the operation process of the 3D laser notching machine, drives the 3D laser notching machine according to the 3D laser notching machine training scenario, and operates the device.
- Execute at least one of displaying a user behavior guide on the equipment operating unit, displaying a user condition guide on a moving unit, and displaying a laser setting guide on a laser setting unit, and performing first user behavior information based on the display of the user behavior guide and first based on the display of the user condition guide.
- the 3D laser notching machine training scenario includes a material replacement training scenario
- the material replacement training scenario includes at least one of a supply unit state check step, an electrode remaining amount removal step, an electrode connection step, and a sample collection step.
- the 3D laser notching machine training scenario includes a facility operation training scenario
- the facility operation training scenario includes at least one of an operation readiness check step, a notching facility operation step, and a punching state check step.
- the at least one instructions determine one or more quality parameters for determining the quality of material produced by the 3D laser notching machine, and while the operation of the 3D laser notching machine is running, the executed A value corresponding to each of the one or more quality parameters determined based on the operation of the 3D laser notching machine is calculated, and the quality of the material produced by the 3D laser notching machine is calculated based on the value corresponding to each of the one or more quality parameters. It further includes instructions for generating associated quality information.
- At least one instruction determines one or more failure scenarios among a plurality of failure scenarios associated with the operation of the 3D laser notching machine, and drives the 3D laser notching machine based on the determined one or more failure scenarios. and instructions for changing at least one of quality information associated with the quality of the material.
- the plurality of defect scenarios include a shoulder line defect scenario in which the positions of the front and rear shoulder lines of the electrode punched out by the 3D laser notching machine are changed to a predetermined abnormal range, and the electrode punched by the 3D laser notching machine.
- An electrode length defect scenario in which the length is changed to a preset abnormal range
- a tab height defect scenario in which the height of an electrode tab punched out by a 3D laser notching machine is changed to a preset abnormal range
- a specific period of an electrode punched out by a 3D laser notching machine It includes at least one of a pitch defect scenario in which the pitch interval is changed to a preset abnormal range and a vision position defect scenario in which the measurement position of the vision measurement item is changed to the preset abnormal location.
- the at least one command executes at least one defect scenario of a shoulder line defect scenario and an electrode length defect scenario, and second user behavior information for driving at least a partial region of the 3D laser notching machine, and Acquiring at least one of the second user condition information for changing the adjustment parameter of the equipment moving unit, correcting the driving of the 3D laser notching machine based on at least one of the acquired second user behavior information and the second user condition information, and correcting A value corresponding to each of the one or more quality parameters associated with the quality of the material produced by the 3D laser notching machine is calculated, and the value corresponding to each of the one or more quality parameters calculated is calibrated by the 3D laser notching machine. It further includes instructions for correcting the quality information associated with the quality of the material being processed.
- the at least one command executes at least one failure scenario of a tap height failure scenario and a pitch failure scenario, and second user behavior information for driving at least a partial region of the 3D laser notching machine, and Acquiring at least one of the second laser setting information for changing the laser parameter of the laser setting unit, correcting the driving of the 3D laser notching machine based on at least one of the obtained second user behavior information and the second laser setting information, and correcting A value corresponding to each of the one or more quality parameters associated with the quality of the material produced by the 3D laser notching machine is calculated, and the value corresponding to each of the one or more quality parameters calculated is calibrated by the 3D laser notching machine. It further includes instructions for correcting the quality information associated with the quality of the material being processed.
- At least one instruction executes a vision position failure scenario, obtains measurement position offset value change information of a vision program associated with the 3D laser notching machine, and adds information to the obtained measurement position offset value change information. and correcting the vision position based on the corrected vision position, and correcting quality information related to the quality of the material produced by the 3D laser notching machine based on the corrected vision position.
- the at least one command further includes instructions for outputting guide information including information required to solve one or more failure scenarios.
- a simulation method of a laser notching machine for secondary battery production performed by at least one processor includes a device operation unit including a 3D laser notching machine associated with secondary battery production, and a 3D laser notching machine.
- a facility moving part including a plurality of adjustment parameters for determining operation, a quality checking unit including quality information related to the quality of a material produced by the 3D laser notching machine, and a plurality of laser parameters for determining operation of the 3D laser notching machine
- Executing a laser setting unit including, obtaining at least one of first user behavior information obtained through a device operation unit, first user condition information obtained through a facility operation unit, and first laser setting information obtained through a laser setting unit.
- the 3D laser notching machine training scenario includes a material replacement training scenario
- the material replacement training scenario includes at least one of a supply unit state check step, an electrode remaining amount removal step, an electrode connection step, and a sample collection step.
- the 3D laser notching machine training scenario includes a facility operation training scenario
- the facility operation training scenario includes at least one of an operation readiness check step, a notching facility operation step, and a punching state check step.
- Calculating a value corresponding to each of the one or more quality parameters determined based on the operation, and quality information associated with the quality of the material produced by the 3D laser notching machine based on the calculated value corresponding to each of the one or more quality parameters It further includes the step of generating.
- the plurality of defect scenarios include a shoulder line defect scenario in which the positions of the front and rear shoulder lines of the electrode punched out by the 3D laser notching machine are changed to a predetermined abnormal range, and the electrode punched by the 3D laser notching machine.
- An electrode length defect scenario in which the length is changed to a preset abnormal range
- a tab height defect scenario in which the height of an electrode tab punched out by a 3D laser notching machine is changed to a preset abnormal range
- a specific period of an electrode punched out by a 3D laser notching machine It includes at least one of a pitch defect scenario in which the pitch interval is changed to a preset abnormal range and a vision position defect scenario in which the measurement position of the vision measurement item is changed to the preset abnormal location.
- the step of executing at least one failure scenario of a shoulder line failure scenario and an electrode length failure scenario, second user behavior information for driving at least a partial area of the 3D laser notching machine, and an adjustment parameter of a facility moving unit Acquiring at least one of second user condition information that changes , correcting driving of the 3D laser notching machine based on at least one of the obtained second user behavior information and second user condition information, correcting the 3D laser Calculating a value corresponding to each of the one or more quality parameters associated with the quality of the material produced by the notching machine, and the material produced by the 3D laser notching machine calibrated based on the value corresponding to each of the one or more quality parameters calculated. Further comprising correcting quality information associated with the quality of .
- the step of executing at least one of the tab height defect scenario and the pitch defect scenario, the second user behavior information for driving at least a partial region of the 3D laser notching machine and the laser parameter of the laser setting unit Obtaining at least one of second laser setting information that changes , correcting driving of the 3D laser notching machine based on at least one of the obtained second user behavior information and second laser setting information, correcting the 3D laser Calculating a value corresponding to each of the one or more quality parameters associated with the quality of the material produced by the notching machine, and the material produced by the 3D laser notching machine calibrated based on the value corresponding to each of the one or more quality parameters calculated.
- the step of correcting the quality information associated with the quality of is further included.
- the step of executing a vision position failure scenario the step of acquiring measurement position offset value change information of a vision program associated with a 3D laser notching machine, and the vision position based on the acquired measurement position offset value change information and correcting quality information associated with the quality of the material produced by the 3D laser notching machine based on the corrected vision position.
- the step of outputting guide information including information required to solve one or more failure scenarios is further included.
- a computer program stored in a computer readable medium is provided to execute the above-described method according to an embodiment of the present invention on a computer.
- a user who produces a secondary battery may perform training related to how to operate the secondary battery production device, how to deal with defects, etc. through a simulation device before being put into work.
- training the loss due to the occurrence of defects is significantly reduced, and the efficiency of the secondary battery production operation can be effectively improved.
- the simulation device can effectively create training content optimized for an actual working environment.
- the simulation device may generate and provide a bad scenario having various values related to the malfunction of the secondary battery production device to the user, and accordingly, the user may solve the malfunction situation that may occur in the actual device by himself. You can effectively learn how to respond according to each situation.
- the user can easily learn how to operate the secondary battery production apparatus through a simulation conducted step by step according to the user's work skill level.
- the user can intensively train only poor scenarios with low job skill by simply identifying and processing bad scenarios in which training is insufficient.
- a user can effectively improve his ability to respond to defects by training using a failure scenario generated based on a malfunction occurring in an actual working environment.
- FIG. 1 is a diagram showing an example of a user using a simulation device according to an embodiment of the present invention.
- Figure 2 is a functional block diagram showing the internal configuration of the simulation device according to an embodiment of the present invention.
- Figure 3 is a block diagram showing an example of the operation of the simulation apparatus according to an embodiment of the present invention.
- FIG. 4 is a diagram illustrating an example of a display screen displayed or output to a device operation unit according to an embodiment of the present invention.
- FIG. 5 is a diagram illustrating an example of a display screen displayed or output to a device operation unit according to another embodiment of the present invention.
- FIG. 6 is a diagram illustrating an example of a display screen displayed or output to a device operation unit according to another embodiment of the present invention.
- FIG. 7 is a diagram illustrating an example of a display screen displayed or output on a facility moving unit associated with a 3D laser notching machine according to an embodiment of the present invention.
- FIG. 8 is a diagram showing an example of a display screen displayed or output to a laser setting unit associated with a 3D laser notching machine according to an embodiment of the present invention.
- FIG. 9 is a diagram illustrating an example in which a bad shoulder line scenario is generated in a quality check unit according to an embodiment of the present invention.
- FIG. 10 is a diagram illustrating an example in which an electrode length failure scenario is generated in a quality check unit according to an embodiment of the present invention.
- FIG. 11 is a diagram illustrating an example in which a tap height defect scenario is generated in a quality check unit according to an embodiment of the present invention.
- FIG. 12 is a diagram illustrating an example in which a pitch defect scenario is generated in a quality check unit according to an embodiment of the present invention.
- FIG. 13 is a diagram illustrating an example of generating a bad scenario according to an embodiment of the present invention.
- FIG. 14 is a diagram illustrating an example in which operational capability information and test results are generated according to an embodiment of the present invention.
- 15 is a diagram showing an example of a simulation method for producing a secondary battery according to an embodiment of the present invention.
- 16 is a diagram showing an example of a simulation method of a laser notching machine for producing a secondary battery according to an embodiment of the present invention.
- 17 is a diagram illustrating an example of a test result calculation method according to an embodiment of the present invention.
- FIG. 18 is a diagram illustrating an example of a bad scenario generation method according to an embodiment of the present invention.
- FIG 19 illustrates an example computing device for performing the methods and/or embodiments and the like described above.
- the terms 'comprise', 'comprising' and the like may indicate that features, steps, operations, elements and/or components are present, but may indicate that such terms include one or more other functions, It is not excluded that steps, actions, elements, components, and/or combinations thereof may be added.
- a specific element when a specific element is referred to as 'binding', 'combining', 'connecting', 'associating', or 'reacting' to any other element, the specific element is directly coupled to the other element. , can be combined, linked and/or associated, reacted, but not limited thereto.
- one or more intermediate components may exist between certain components and other components.
- “and/or” may include each of one or more items listed or a combination of at least a part of one or more items.
- 'first' and 'second' are used to distinguish a specific component from other components, and the above-described components are not limited by these terms.
- a 'first' element may be used to refer to an element having the same or similar shape as a 'second' element.
- a 'secondary battery' may refer to a battery made using a material in which an oxidation-reduction process between current and material can be repeated several times.
- a secondary battery mixing, coating, roll pressing, slitting, notching and drying, lamination, folding and stacking ), lamination and stacking, packaging, charging and discharging, degas, and characteristics inspection may be performed.
- separate production equipment devices for performing each process may be used. here. Each production equipment can operate according to adjustment parameters and set values set or changed by the user.
- a 'user' may refer to a worker who performs secondary battery production and operates secondary battery production equipment, and may include a user who trains through a simulation device for secondary battery production equipment.
- a 'user account' is an ID created to use such a simulation device or assigned to each user, and a user can log in on the simulation device using the user account and perform simulation, Not limited to this.
- 'facility operating unit', 'device operating unit', and 'quality confirmation unit' are software programs included in a simulator device or displayed on an input/output device associated with the simulator device and/or an input/output device, and include images such as 3D model devices. , It may refer to a device and/or program that outputs an image, etc., or receives various inputs from a user and transfers them to a simulator device.
- a '3D model device' is a virtual device that implements actual secondary battery production equipment, and an image or video of the virtual device is obtained by information input by a user (e.g., user input information and/or user behavior information).
- animations, etc. can be operated, such as being executed, changed and/or corrected. That is, the 'operation of the 3D model device' may include an image, video, animation, etc. of a virtual device that is executed, changed, and/or corrected.
- a 3D model apparatus may be used for mixing, coating, roll pressing, slitting, notching and drying, lamination, folding and stacking, It may include a device for performing each of lamination and stack, package, charge and discharge, degas (degas), property test, and the like.
- the 3D model device may be implemented as a 2D model device or implemented together with a 2D model device.
- the 3D model device is not limited to a 3D model and may include a 2D model.
- the 3D model device may include terms such as a 2D model device, an animation model device, and a virtual model device.
- 'user condition information' includes user input for setting or changing conditions and/or values of at least some of the adjustment parameters, or is information generated by a predetermined algorithm based on the user input.
- 'laser setting information' includes user input for setting or changing conditions and/or values of at least some of the laser parameters, or is information generated by a predetermined algorithm based on the user input.
- 'user behavior information' includes user input such as a touch input, a drag input, a pinch input, and a rotation input performed on at least some area of a 3D model device, or , may be information generated by a predetermined algorithm based on a corresponding user input.
- a 'defect scenario' is a value, condition, etc. for changing the operation of a 3D model device to a malfunction range or changing the quality information of a material determined by the operation of a 3D model device to a defect range. It may be a scenario that includes For example, when a bad scenario occurs during operation of the simulation device, the operation and quality information of the 3D model device may be changed based on the bad scenario. In addition, when the operation and quality information of the 3D model device changed by the bad scenario are corrected to a normal range, it may be determined that the bad scenario is solved.
- a 'training scenario' may include a scenario for operating secondary battery production equipment.
- the training scenario may include a notching facility operation training scenario, a material replacement training scenario, a condition adjustment training scenario, and the like.
- the condition adjustment training scenario includes the step of changing values, conditions, etc. for changing the operation of the 3D model device to the malfunctioning range. can learn That is, the condition adjustment training scenario may be a process of learning how to solve various defective situations that may occur in the laser notching equipment.
- the 'mixing process' may be a process of preparing a slurry by mixing an active material, a binder, and other additives with a solvent.
- a user may determine or adjust addition ratios of an active material, a conductive material, an additive, a binder, and the like in order to prepare a slurry of a specific quality.
- the 'coating process' may be a process of applying the slurry on a foil in a predetermined amount and shape.
- the user may determine or adjust the die, slurry temperature, etc. of the coater device to achieve a coating having a specific quality, quantity and shape.
- the 'rolling process' may be a process of pressing the coated electrode to a certain thickness by passing it between two rotating upper and lower rolls. For example, a user may determine or adjust a gap between rolls in order to maximize battery capacity by increasing electrode density through a rolling process.
- the 'slitting process' may be a process of passing an electrode between two rotating upper and lower knives to cut the electrode into a predetermined width. For example, a user may determine or adjust various adjustment parameters to maintain a constant electrode width.
- the 'notching and drying process' may be a process of removing moisture after punching an electrode into a predetermined shape.
- the user may determine or adjust the position of the shoulder line, the pitch interval, etc. in order to perform punching in a shape of a specific quality.
- the 'lamination process' may be a process of sealing and cutting the electrode and the separator.
- a user may determine or adjust a value corresponding to an x-axis and a value corresponding to a y-axis in order to perform a specific quality of cutting.
- the 'package process' may be a process of attaching a lead and tape to an assembled cell and packaging it in an aluminum pouch
- the 'degas process' may be a process of It may be a process of re-sealing after removing the gas inside.
- the 'characteristic inspection process' may be a process of checking characteristics such as thickness, weight, insulation voltage, etc. of a cell using a measuring device before shipment of the cell. In the case of such a process, a user may adjust conditions, values, etc. of various adjustment parameters or change a set value corresponding to a device so that each process can be performed with a specific quality within a normal range.
- the simulation device 100 is a device for training secondary battery production workers (eg, the user 110), and includes a facility operation unit 120, a device operation unit 130, and a quality check unit. 140, a laser setting unit 150, and the like.
- the user 110 manipulates the simulation device 100 that virtually implements actual secondary battery production equipment (eg, 2D, 3D, etc.) to determine how to use the secondary battery production equipment (eg, laser notching machine). can be learned, or how to respond in case of product quality degradation can be trained.
- actual secondary battery production equipment eg, 2D, 3D, etc.
- the facility operation unit 120 may include a plurality of adjustment parameters for determining the operation of a 3D model device (eg, a 3D laser notching machine) displayed on the device operation unit 130 .
- the user 100 may execute, change, and/or correct the operation of the 3D model device by changing conditions of at least some of the plurality of adjustment parameters. That is, the operation of the 3D model device may be adaptively changed or corrected by a change in the adjustment parameter input by the user 110 .
- the device operating unit 130 may include a 3D model device related to the production of secondary batteries.
- the 3D model device is a mixer, coater, slitter, roll pressing device, mold notching device, and laser notching, which are secondary battery production equipment. It may include, but is not limited to, virtual models (eg, 2D models, 3D models, etc.) related to devices, lamination devices, L&S (lamination & stack) devices, etc., and other devices used for the production of secondary batteries It can contain models of any device.
- the user 110 may perform a touch input, a drag input, or a pinch to the 3D model device (at least a portion of the 3D model device) included in the device operation unit 130.
- the 3D model device may be manipulated or the configuration of the 3D model device may be changed by performing an input or the like.
- the user 110 may check or enlarge/reduce an arbitrary area of the 3D model device through view switching, etc., operate the 3D model device by performing touch input, or configuration can be changed.
- the 3D model device associated with secondary battery production is displayed on the device operation unit 130, it is not limited thereto, and a device related to a specific process according to the secondary battery production process is implemented as a 2D model device and displayed. can
- the quality confirmation unit 140 may include quality information related to the quality of the material generated by the 3D model device.
- the quality information may be generated by performing an operation on a quality parameter based on a predetermined criterion and/or algorithm. That is, the user 110 may check the quality information generated in response to changing the adjustment parameter or manipulating the 3D model device through the quality checking unit 140 .
- the quality check unit 140 of a specific process according to the secondary battery production process may be included in the device operation unit 130 .
- the quality information may be displayed in association with the 3D model device of the device operating unit 130 or may be confirmed by a specific operation of the 3D model device. For example, when a button for checking quality displayed on the device operation unit 130 is selected, quality information may be displayed or output. In another example, quality information may be displayed or output by changing the color of at least a portion of the 3D model device.
- the laser setting unit 150 may include a plurality of laser parameters for determining the operation of a 3D model device (eg, a 3D laser notching machine) displayed on the device operating unit 130 .
- the user 100 may execute, change, and/or correct the operation of the 3D model device by changing setting information of at least some of a plurality of laser parameters. That is, the operation of the 3D model device may be adaptively changed or corrected by a change in a laser parameter input by the user 110 .
- the simulation device 100 is illustrated as including one facility moving unit 120 and one quality checking unit 140, but is not limited thereto, and the facility moving unit 120 and the quality checking unit 140 Any number may be determined according to the type of 3D model device associated with the simulation device 100 .
- the user 110 who produces the secondary battery can use the simulation device 100 to operate the secondary battery production device (e.g., laser notching machine) before starting work, and how to deal with defects.
- the secondary battery production device e.g., laser notching machine
- FIG. 2 is a functional block diagram showing the internal configuration of the simulation device 100 according to an embodiment of the present invention.
- the simulation device 100 eg, at least one processor of the simulation device 100
- the simulation device 100 includes a 3D model device operation unit 210, a quality determination unit 220, a scenario management unit 230, a test It may include an execution unit 240, a user management unit 250, and the like, but is not limited thereto.
- the simulation device 100 communicates with the facility operation unit 120, the device operation unit 130, the quality confirmation unit 140, and the laser setting unit 150, and can send and receive data and / or information related to the 3D model device. there is.
- the 3D model device operating unit 210 may execute, change, and/or correct the operation of the 3D model device displayed on the device operating unit 120 according to a user's manipulation.
- the 3D model device operation unit 210 obtains or receives user behavior information, user condition information, and/or laser setting information by using information input from a user (eg, a secondary battery production worker). can Then, the 3D model device operating unit 210 may determine or change the operation of the 3D model device using the obtained or received user behavior information, user condition information, and/or laser setting information.
- the user behavior information is information generated based on a user input such as touching at least a partial area of the 3D model device included in the device operating unit 120, and the setting of the 3D model device according to the user input Information on the amount of change in value may be included.
- the 3D model device is a laser notching device for secondary battery production
- the user selects a specific area of the laser notching device through the device operation unit 130 with a touch input to operate the laser notching device, or the electrode remaining amount
- the electrode material may be replaced by removing and connecting a new electrode. In this case, user behavior information based on the replaced electrode material may be generated.
- the user condition information is information generated based on a user input for changing the condition and/or value of at least some parameters among a plurality of adjustment parameters included in the facility moving unit 120.
- it may include information about a change amount of a condition value for determining an operation of a 3D model device according to a user input.
- the 3D model device is a laser notching device for producing a secondary battery
- the user may change the cutting height offset value to a specific value through the facility moving unit 120. In this case, the changed cutting height User condition information based on the offset value may be generated.
- the laser setting information is generated based on a user input for changing the condition and/or value of at least some of the plurality of laser parameters included in the laser setting unit 150.
- information may include information about a change amount of a set value for determining the operation of a 3D model device according to a user input.
- the 3D model device is a laser notching device for producing secondary batteries
- the user may change the pitch interval offset value to a specific value through the laser setting unit 150, and in this case, the changed pitch interval offset value Based laser setting information can be generated.
- the quality determination unit 220 determines the quality of the material generated by the operation of the 3D model device.
- Quality information associated with may be determined or generated. That is, when the 3D model device is operating (animation, video, etc. in which the 3D model device operates), quality information may be determined or generated differently according to setting values and condition values of the corresponding 3D model device.
- the user may change or adjust the quality of a material generated by the 3D model device by changing an adjustment parameter or setting at least a portion of the 3D model device through a touch input.
- the quality determination unit 220 determines or extracts one or more quality parameters for determining the quality of the material produced by the 3D model device, and while the operation of the 3D model device is being executed, the 3D model being executed A value corresponding to each of one or more quality parameters determined based on the operation of the model device may be calculated.
- a value corresponding to the quality parameter may be calculated by a predetermined algorithm.
- the quality determiner 220 may generate quality information related to the quality of the material created by the 3D model device based on values corresponding to each of the calculated one or more quality parameters.
- the quality determination unit 220 may generate or output quality information including the calculated electrode shoulder line position.
- a bad scenario associated with a malfunction of a corresponding 3D model device may occur during operation of the 3D model device or before the operation of the 3D model device.
- the abnormal range may refer to a range in which quality information associated with the quality of a material deviates from an upper or lower limit of a preset specification.
- the scenario management unit 230 determines one or more failure scenarios among a plurality of failure scenarios associated with the malfunction of the 3D model device, and determines the operation of the 3D model device and the quality of the material based on the determined one or more failure scenarios. At least one of the associated quality information may be changed.
- the plurality of defect scenarios may include a defect in an electrode shoulder line, a defect in pitch, a defect in electrode length, a defect in tab height, and a defect in vision position.
- the scenario management unit 230 extracts at least one of electrode shoulder line defects, pitch defects, electrode length defects, tab height defects, and vision position defects to determine a defect scenario, and according to the extracted or determined defect scenario, the 3D model device Adjustment parameters, laser parameters, operation, quality information, etc. can be changed.
- a user may change an adjustment parameter, change a laser parameter, or change settings of a 3D model device to solve the bad scenario.
- the scenario manager 230 receives at least one of user behavior information, user condition information, and laser setting information for resolving one or more determined bad scenarios, and receives at least one of the received user behavior information, user condition information, and laser setting information.
- the operation of the 3D model device changed based on at least one may be corrected.
- the scenario management unit 230 corresponds to each of a plurality of quality parameters related to the quality of the material generated by the 3D model device based on the operation of the 3D model device being executed while the corrected operation of the 3D model device is being executed. It is possible to calculate a value to be calculated, and correct the quality information associated with the quality of the material created by the calibrated 3D model device based on the value corresponding to each of the calculated plurality of quality parameters.
- the scenario management unit 230 may determine whether one or more bad scenarios have been resolved using the corrected quality information. For example, if the quality of the material is within a predetermined normal range, the scenario management unit 230 may determine that the bad scenario is resolved, but is not limited thereto, and the value of each quality parameter included in the quality information is determined in advance. If it corresponds to the determined normal range or a specific value, the scenario management unit 230 may determine that the bad scenario is resolved. Additionally or alternatively, when a value calculated by providing each quality parameter to an arbitrary algorithm falls within a predetermined normal range, the scenario management unit 230 may determine that the bad scenario is resolved.
- setting values, condition values, etc. of the 3D model device that are changed to a range of malfunctions due to bad scenarios may be predetermined for each bad scenario, but are not limited thereto.
- a bad scenario may be generated based on error information generated when an actual secondary battery production equipment malfunctions.
- the scenario manager 230 obtains error information related to the malfunction when a malfunction occurs in an external device (eg, actual secondary battery production equipment) associated with the 3D model device, and based on the obtained error information, the 3D model device can create bad scenarios associated with the malfunctioning of For example, when a malfunction occurs in a slitting process, which is the entire process of a laser notching machine in a secondary battery production line, the scenario management unit 230 converts the value and set value of each adjustment parameter when the slitting equipment malfunctions as error information. can be obtained The scenario management unit 230 may generate a bad scenario by changing the value of each adjustment parameter obtained in this way and the setting value of the device to correspond to the 3D model device. With this configuration, a bad scenario is generated based on error information in an actual device, so that the simulation device 100 can effectively generate training content optimized for an actual working environment.
- an external device eg, actual secondary battery production equipment
- the test performing unit 240 determines whether one or more bad scenarios are resolved using the corrected quality information, and when it is determined that the one or more bad scenarios are solved, the one or more bad scenarios proceed. It is possible to calculate the progress time, loss value, etc. of one or more failure scenarios during the process.
- the loss value may include a coating loss value, a material loss value, and the like, and may be calculated through a predetermined algorithm based on a user's response time, a user-input value, and the like.
- the test execution unit 240 may generate operational capability information for the 3D model device of the user account based on the calculated running time and loss value.
- the user account may refer to an account of a worker using the simulation device 100
- the operation capacity information is information indicating the user's work proficiency, such as work speed, time required for bad action, number of NGs, It may include a degree of proximity to a target value, an evaluation score, and the like.
- the test execution unit 240 may determine whether the user passes the simulation training based on operational capability information for each failure scenario when the corresponding user solves all predetermined types of failure scenarios.
- the user management unit 250 may perform management such as registration, modification, and deletion of a user account associated with a user using the simulation device 100 .
- the user may use the simulation device 100 using his or her registered user account.
- the user management unit 250 may store and manage whether or not each bad scenario for each user account has been resolved and operating capability information corresponding to each bad scenario in an arbitrary database.
- the scenario management unit 230 extracts information associated with a specific user account stored in the database, and extracts at least one of a plurality of bad scenarios based on the extracted information. or you can decide.
- the scenario management unit 230 may extract and generate only bad scenarios in which the work speed is lower than the average work speed based on information associated with the user account, or provide the bad scenarios to the user, but is not limited thereto. It may be extracted or determined by any other criterion or any combination of criterion.
- each functional configuration included in the simulation device 100 has been separately described, but this is only to aid understanding of the invention, and one arithmetic device may perform two or more functions.
- the simulation device 100 is shown to be distinguished from the facility moving unit 120, the device operating unit 130, the quality checking unit 140, and the laser setting unit 150, but is not limited thereto, and the equipment The moving unit 120, the device operation unit 130, the quality check unit 140, and the laser setting unit 150 may be included in the simulation device 100.
- the simulation device 100 may generate and provide training scenarios and failure scenarios having various values associated with the operation of the secondary battery production equipment to the user, and thus the user may learn how to operate the secondary battery production equipment. and effectively learn countermeasures according to each situation while resolving malfunctions that may occur in actual devices on their own.
- Figure 3 is a block diagram showing an example of the operation of the simulation apparatus according to an embodiment of the present invention.
- the simulation device (100 in FIG. 1) includes a process and facility guide step 310, facility operation training step 320, material replacement training step 330, condition adjustment training step 340, and bad case training. It can operate through processes such as step 350 and test step 360. In other words, the user may train how to operate the secondary battery production equipment through steps 310, 320, 330, 340, 350, and 360.
- Process and equipment guide step 310 may be a step of explaining a secondary battery production process or equipment. If the 3D model device is a laser notching device, a description of the laser notching process, a description of the main parts of the laser notching device, a description of the vision measurement items (shoulder line, pitch, electrode length, etc.) of the vision equipment, and each vision measurement item A description of the location of the measurement may be included.
- This process and equipment guide step 310 may be a step of learning the types of various adjustment parameters included in the equipment operating unit and how to operate the adjustment parameters. For example, a work instruction (image, video, animation, etc.
- a portion of the screen may be turned on or activated so that the user can perform a task corresponding to the work instruction.
- the user can train how to use the moving parts of the equipment by manipulating conditions and/or values of arbitrary adjustment parameters corresponding to the work instructions.
- the next step proceeds, or a button that allows the user to proceed to the next step (eg NEXT button, etc.) may be displayed or activated.
- the facility operation training step 320 is a step in which the user trains the operation of the laser notching device, and may include an operation readiness check step, a notching facility start operation step, and a punching state check step.
- the 3D model device is driven, and guide information is displayed on the types of adjustment parameters to be operated for confirmation and adjustment, the value of the adjustment parameters, the type of laser parameters, the value of the laser parameters, and the 3D model device. or can be output. That is, guide information may be displayed or output on a facility moving unit or a device operating unit, and a partial area of the screen may be turned on or activated so that a user may perform a task corresponding to the guide information.
- the user can manipulate the facility moving part and the device operating part corresponding to the guide information and input a set value, and when one task is completed, the next step proceeds or a button (e.g., NEXT button, etc.) may be displayed or activated. Accordingly, the user can train the operating process of the laser notching device for secondary battery production based on the displayed information.
- a button e.g., NEXT button, etc.
- the material replacement training step 330 is a step in which the user trains how to replace the electrode material of the laser notching device, and may include a supply state check step, an electrode remaining amount removal step, an electrode connection step, a sample collection step, and the like.
- the 3D model device is driven, and guide information such as the type of adjustment parameter to be manipulated for confirmation and adjustment, the value of the adjustment parameter, and the 3D model device may be displayed or output. That is, guide information may be displayed or output on a facility moving unit or a device operating unit, and a partial area of the screen may be turned on or activated so that a user may perform a task corresponding to the guide information.
- the user can manipulate the facility moving part and the device operating part corresponding to the guide information and input a set value, and when one task is completed, the next step proceeds or a button (e.g., NEXT button, etc.) may be displayed or activated. Accordingly, the user may train a material replacement process of the laser notching device for secondary battery production based on the displayed information.
- a button e.g., NEXT button, etc.
- Condition adjustment training step 340 may be a step of learning the quality change of the material produced by the 3D model device according to the value of the adjustment parameter of the facility moving unit, the laser parameter value of the laser setting unit, and the state of the device operating unit.
- one of material information related to the operation of the 3D laser notching machine associated with the secondary battery production device and the quality of the material produced by the 3D laser notching machine may be changed to an abnormal range, and the user may change this abnormal range. It may be a step of learning how to check the state and correct it to a normal state.
- condition adjustment training step 340 is a step in which the user learns how to check and take measures for defects that occur during the operation of the secondary battery production device, and defects generated in the 3D laser notching machine may occur.
- the type of adjustment parameter to be manipulated to solve the defect the value of the adjustment parameter, the type of laser parameter, the value of the laser parameter, the setting value of the 3D model device, etc. may be displayed or output. The user can process defects based on the displayed information and train how to solve the defects.
- the positions of the front and rear shoulder lines of the electrodes may be changed to an abnormal range outside the upper or lower limit of the preset specification, and in the pitch defect training, the pitch interval of the electrode exceeds the upper or lower limit of the preset specification.
- the length of the electrode may be changed into an abnormal range that is outside the upper or lower limit of the preset specification, and in the poor tap height training, the tap height of the electrode is within the upper limit of the preset specification.
- it may be changed to an abnormal range outside the lower limit, and in the vision position defect training, the measurement position for each vision measurement item may be changed to a predetermined specific abnormal position.
- the measurement position of the vision measurement item is changed to an abnormal position in this way, even if the punching state of the actual electrode is normal, quality information obtained through the vision equipment may be displayed as an abnormal state outside the upper or lower limit of the specification. That is, when the vision position is defective, even if the punching state of the electrode is normal, it may be displayed or output as a defective punching state such as a defective shoulder line or a defective pitch.
- the values of adjustment parameters, the types of laser parameters, the values of laser parameters, and the operation of 3D model devices is provided in the equipment operating part, device operating part, and laser setting part. It can be displayed or output, etc., and a part of the screen can be turned on or activated so that the user can perform a task corresponding to the guide information.
- the user can manipulate the facility moving part, the device operating part, and the laser setting part corresponding to the guide information and input the setting value, and when one task is completed, the next step can proceed or the next step
- a button eg NEXT button, etc.
- the user can train how to correct the abnormal range to the normal range based on the displayed information.
- the bad case training step 350 may be a step in which a user learns a method for solving defects by repeatedly processing or solving each or a combination of a plurality of defect scenarios associated with the secondary battery production apparatus. For example, a user may directly select one of a plurality of bad scenarios for training, but is not limited thereto, and may train a bad scenario arbitrarily determined by a simulator device.
- the bad case training step 350 may be a step of training various bad scenarios trained in the condition adjustment training step 340 without guide information.
- the operation of the 3D model device and the quality of the material associated with the 3D model device may be changed in real time. . By checking the quality that is changed in this way, the user can solve defects in the form of repetitive training, and can improve proficiency in coping with defects.
- the test step 360 may be a step of evaluating the operating ability of the user by testing a process of solving the bad scenario by the user. For example, when a user solves each bad scenario, the operation speed of each bad scenario, the time taken for bad actions, the number of NGs, the degree of proximity to the target value, the loss value, etc. Ability can be measured or evaluated. The user can additionally learn or train on insufficient bad scenarios by checking such operational capability and test pass or not.
- each step is illustrated as sequentially progressing, but is not limited thereto, and some of the steps may be omitted. Also, the order of each step may be changed. For example, after the test step 360, the bad case training step 350 to the condition adjustment training step 340 may be performed again. With this configuration, the user can easily learn how to operate the secondary battery production device and how to deal with malfunctions through simulations performed step by step according to the user's work skill level.
- the device operation unit 130 includes text, images, An image or the like may be displayed or output on the display screen.
- the mini-map 410, the 3D model device 420, the user guide 430, the NEXT button 440, the work instructions 450, etc. are shown displayed in a specific area on the display screen, but are limited to this.
- Each text, image, video, etc. may be displayed in an arbitrary area of the display screen or overlapped.
- the mini-map 410 schematically displays the entire laser notching device for secondary battery production, and displays a schematic position of a region displayed on the 3D model device 420 among all laser notching devices as a rectangular box.
- the position and size of the rectangular box displayed on the minimap 410 may also be changed in real time.
- the mini-map 410 may serve as a location guidance map for a laser notching device.
- the 3D model device 420 may be a 3D image or video in which secondary battery production equipment is implemented in a 3D form.
- the 3D model device 420 may operate based on user condition information and/or user behavior information input from the user.
- the user guide 430 includes information required to operate the 3D model device 420, user condition information required to solve training scenarios, user behavior information, laser setting information, etc., and guides the user's next action. It may be information for That is, even if the user does not know how to operate the simulation device, the user guide 430 can be used to train how to operate the simulation device and how to respond to defects.
- the condition value, setting value, etc. of the 3D model device is determined using the user guide 430 displayed as described above, or when the 3D model device 420 is operated, the corresponding step is solved and NEXT to proceed to the next step Button 440 may be activated.
- the user may select the activated NEXT button 440 with a touch input or the like to perform training corresponding to the next step.
- the work instruction 450 is a document including initial setting values and condition values of the 3D model device 420, and may be predetermined or generated by an arbitrary algorithm.
- the simulation device receives and provides the contents of work instructions used to operate actual secondary battery production equipment, or provides initial setting values and condition values of the 3D model device 420 based on a plurality of input work instructions. etc. can be calculated to create a new work order.
- the device operation unit 130 may display or output text, images, videos, etc. including a plurality of failure scenarios 510, 520, and 530 on a display screen.
- the first bad scenario 510, the second bad scenario 520, the third bad scenario 530, etc. are shown to be displayed on a specific area on the display screen, but are not limited thereto, and each text and image , images, etc. may be displayed on an arbitrary area of the display screen.
- each bad scenario may include content and difficulty of the bad scenario.
- the first bad scenario 510 may be a shoulder line defect under difficulty level
- the second bad scenario 520 may be a pitch defect under difficulty level
- the third bad scenario 530 may be a vision position defect under difficulty level.
- the user may select at least some of the plurality of bad scenarios 510 , 520 , and 530 displayed on the display screen through a touch input, etc., and perform training on the selected bad scenario.
- one of the plurality of failure scenarios 510 , 520 , and 530 may be determined by a predetermined algorithm or the like.
- the simulation device may determine a bad scenario or a combination of bad scenarios with a low task skill level through a user account (or information associated with the user account) of a user performing training.
- the user's work skill level may be calculated or determined as a test result for each failure scenario, but is not limited thereto. With this configuration, the user can intensively train only the bad scenarios with low work proficiency by simply identifying and processing bad scenarios in which training is insufficient.
- the device operation unit 130 includes guide information 610 including state information according to each measurement item, defect type, user condition information required to solve the corresponding defect, user behavior information, and laser setting information.
- 620 and 630 may display or output text, images, videos, etc. related to the display screen.
- the first guide information 610, the second guide information 620, the third guide information 630, etc. are shown to be displayed in a specific area on the display screen, but are not limited thereto, and each text and image , images, etc. may be displayed on an arbitrary area of the display screen.
- the guide information 610 , 620 , and 630 may indicate a state as bad or good for each measurement item, and may include a defect type and action method for the measurement item corresponding to the defect.
- the first guide information 610 is guide information for a shoulder line item, and may include action items related to a defect in which the shoulder line is biased toward the upper limit line.
- the second guide information 620 is guide information for a pitch item and may indicate that it is in a good state
- the third guide information 630 is guide information for a tab height item and may indicate that it is in a good state.
- the second guide information to the third guide information may include a defect type and action items related to each defect when the pitch item and the tab height item are in a defective state, respectively.
- the user checks the type of defect and the action method corresponding to each type of defect, manipulates the condition and/or value of the adjustment parameter, manipulates the condition and/or value of the laser parameter, or manipulates the operation of the 3D model device to make it normal. Training can be performed so that a material with a quality within the range is produced.
- the guide information 610 , 620 , and 630 has been described above as being displayed or output on the device operation unit 130 , but is not limited thereto, and the guide information may be displayed on a separate display device.
- FIG. 7 is a view showing an example of a display screen displayed or output on a facility moving unit 120 associated with a 3D laser notching machine according to an embodiment of the present invention
- FIG. 8 is a 3D laser notching machine according to an embodiment of the present invention. It is a diagram showing an example of a display screen displayed or output on the associated laser setting unit 150.
- a laser notching machine may refer to a device for punching a slitted electrode into a predetermined shape.
- it may be important to punch to have a constant and uniform shoulder line position, electrode length, pitch interval, tab height, etc. in order to produce a good quality material.
- the shoulder line position, electrode length, pitch interval, tab height, etc. may be changed by setting values such as cutting height offset, electrode length offset, pitch length offset, tab height offset, and/or condition values.
- the cutting height offset and the electrode length offset can be set by adjusting the condition parameters through the equipment moving unit 120 as shown in FIG. 7, and the tap height offset and pitch length offset can be set by laser setting as shown in FIG.
- the laser parameters may be adjusted and set through the unit 150 .
- quality information related to the quality of the material produced by the 3D laser notching machine may be displayed or output to the quality confirmation unit.
- the simulator device determines one or more quality parameters for determining the quality of the material produced by the 3D laser notching machine, and while the operation of the 3D laser notching machine is being executed, the 3D laser notching machine being executed A value corresponding to each of the one or more quality parameters determined based on the operation of the notching machine may be calculated. Then, the simulation device may generate and output quality information related to the quality of the material produced by the 3D laser notching machine based on values corresponding to each of the calculated one or more quality parameters.
- the quality check unit may include quality information (or quality parameters) for checking a shoulder line position, an electrode length, a pitch interval, a tap height, and the like.
- the plurality of adjustment parameters for determining the operation of the 3D laser notching machine may include a cutting height offset 710 and an electrode length offset 720 as shown in FIG. 7 .
- the cutting height offset 710 may be a parameter for adjusting the y-axis punching position
- the electrode length offset 720 may be a parameter for adjusting the length between the upper end and the lower end of the y-axis of the electrode.
- the plurality of laser parameters for determining the operation of the 3D laser notching machine may include a tap height offset 810 and a pitch length offset 820 as shown in FIG. 8 .
- the tap height offset 810 may be a parameter for adjusting the height of the tap
- the pitch length offset 820 may be a parameter for adjusting the pitch interval.
- vision position offset may be included, and the vision position offset may be a parameter for adjusting a measurement position for each vision measurement item with respect to the punched electrode.
- This vision position offset can be adjusted through the vision program offset adjustment screen, and when the vision position offset of a specific measurement item is changed by the user, the value of the quality parameter related to the measurement item can be changed or adjusted.
- FIG. 9 is a diagram illustrating an example in which a bad shoulder line scenario is generated in the quality checking unit 140 according to an embodiment of the present invention.
- the simulation device (100 in FIG. 1 ) determines one or more failure scenarios among a plurality of failure scenarios associated with the malfunction of the 3D laser notching machine in condition adjustment training or failure case training, and determines the one or more failure scenarios determined. At least one of the quality information associated with the operation of the 3D laser notching machine and the quality of the material may be changed based on the above.
- the plurality of bad scenarios may include bad shoulder line scenarios.
- the shoulder line defect scenario may refer to a scenario in which a defective material whose positions of front and rear shoulder lines of an electrode deviate from an upper or lower limit of a predetermined specification is generated.
- the front and rear shoulder lines show defects that are biased toward the upper limit of the specification.
- the quality confirmation unit 140 includes a vision graph 900, and when a bad shoulder line scenario occurs, the vision graph 900 includes the positions of the front and rear shoulder lines measured from the normal measurement position by the vision equipment for measuring the position of the shoulder line. can be output or displayed.
- the simulation device when the one or more determined bad scenarios include a bad shoulder line scenario, the simulation device, as shown in FIG. 910 and 930) are displayed biased toward the upper limit of the specification (a defect displayed biased toward the lower limit may occur), and defective items are displayed in at least some areas of the 3D laser notching machine included in the device operation unit 130.
- an action guide may be additionally displayed on at least a portion of the device operation unit 130 .
- the user can correct the shoulder line position by adjusting the cutting height offset 710 of the equipment movable unit 120 as shown in FIG. 7 .
- the simulation device may correct the position of the shoulder line of the material in response to receiving user condition information corresponding to the cutting height offset from the user.
- the simulation device may correct the changed shoulder line position of the electrode in response to receiving user action information of touching or dragging a specific mechanical unit region for resolving a shoulder line defect from the user.
- the simulation device may determine whether the shoulder line defect scenario is resolved based on the corrected shoulder line position of the electrode. For example, at least one of user behavior information and user condition information is generated based on a touch input, a drag input, etc. for a predetermined area in a predetermined order that can be used in solving a shoulder line defect scenario, or a predetermined offset setting value is input In this case, the simulation device may determine that the shoulder line defect scenario is resolved. In other words, the simulation device may determine that the shoulder line defect scenario is solved when the shoulder line position of the electrode is corrected based on at least one of the corresponding user behavior information and user condition information. When it is determined that the bad scenario is solved, the front and rear shoulder lines may be moved to the center between the upper and lower limit lines in the vision graph 900 displaying the quality information of the electrode and output (920, 940).
- the simulation device determines one or more failure scenarios among a plurality of failure scenarios associated with the malfunction of the 3D laser notching machine in condition adjustment training or failure case training, and determines the one or more failure scenarios determined. At least one of the quality information associated with the operation of the 3D laser notching machine and the quality of the material may be changed based on the above.
- the plurality of failure scenarios may include an electrode length failure scenario.
- the electrode length defect scenario may refer to a scenario in which a defective material in which the length between the upper end and the lower end of the y-axis of the electrode deviates from the upper or lower limit of a preset specification is generated.
- a defect in which the length of the electrode is biased toward the upper limit of the specification is shown.
- the quality confirmation unit 140 includes a vision graph 1000, and when a bad electrode length scenario occurs, in the vision graph 1000, the electrode length measured by the vision equipment for measuring the electrode length at the normal measurement position is output or can be displayed
- the simulation device determines the electrode length 1010 in the vision graph 1000 of the quality checking unit 140, as shown in FIG. 10, when the determined one or more failure scenarios include the electrode length failure scenario. is displayed biased toward the upper limit of the specification (a defect displayed biased toward the lower limit may occur), and defective items are displayed in at least a portion of the 3D laser notching machine included in the device operation unit 130.
- an action guide may be additionally displayed on at least a portion of the device operation unit 130 .
- the user may correct the electrode length by adjusting the electrode length offset 720 of the facility moving unit 120 as shown in FIG. 7 .
- the electrode length failure scenario can be responded to by touching or dragging a specific area of the 3D laser notching machine displayed on the device operating unit 130 .
- the simulation device may correct the electrode length of the material in response to receiving user condition information corresponding to the electrode length offset from the user.
- the simulation device may correct the electrode length of the changed electrode in response to receiving user action information of touching or dragging a specific mechanical part region for resolving a defective electrode length from the user.
- the simulation device can determine whether the electrode length failure scenario has been resolved based on the electrode length of the calibrated electrode. For example, at least one of user behavior information and user condition information is generated based on a touch input, a drag input, etc. for a predetermined area in a predetermined order that can be used when solving an electrode length failure scenario, or a predetermined offset setting value is input. , the simulation device may determine that the electrode length failure scenario has been resolved. In other words, when the electrode length is corrected based on at least one of corresponding user behavior information and user condition information, the simulation device may determine that the electrode length failure scenario has been resolved. If it is determined that the bad scenario is solved, the length of the electrode may be moved to the center between the upper limit line and the lower limit line in the vision graph 1000 displaying the quality information of the electrode and output (1020).
- FIG. 11 is a diagram illustrating an example in which a tab height defect scenario is generated in the quality checker 140 according to an embodiment of the present invention.
- the simulation device (100 in FIG. 1 ) determines one or more failure scenarios among a plurality of failure scenarios associated with the malfunction of the 3D laser notching machine in condition adjustment training or failure case training, and determines the one or more failure scenarios determined. At least one of the quality information associated with the operation of the 3D laser notching machine and the quality of the material may be changed based on the above.
- the plurality of failure scenarios may include a tap height failure scenario.
- the tab height defect scenario may refer to a scenario in which a defective material having a height of an electrode tab deviating from an upper limit or a lower limit of a preset specification is generated.
- a defect in which the tap height is biased toward the lower limit of the specification is shown.
- the quality confirmation unit 140 includes a vision graph 1100, and when a bad tap height scenario occurs, the vision equipment for measuring the tap height in the vision graph 1100 displays the tap height measured at the normal measurement position. can be displayed
- the simulation device determines the tap height 1110 in the vision graph 1100 of the quality checking unit 140, as shown in FIG. is displayed biased toward the lower limit of the specification (a defect displayed biased toward the upper limit may occur), and defective items are displayed in at least a portion of the 3D laser notching machine included in the device operation unit 130.
- an action guide may be additionally displayed on at least a portion of the device operation unit 130 .
- the user may correct the tab height by adjusting the tab height offset 810 of the laser setting unit 150 as shown in FIG. 8 .
- a tap height failure scenario can be responded to by touching or dragging a specific area of the 3D laser notching machine displayed on the device operation unit 130 .
- the simulation device may correct the tap height of the material in response to receiving laser setting information corresponding to the tap height offset from the user.
- the simulation device may correct the tab height that is changed in response to receiving user action information of touching or dragging a specific mechanical unit region for resolving the tab height defect from the user.
- the simulation device can determine whether the tap height failure scenario has been resolved based on the corrected tap height. For example, at least one of user behavior information and laser setting information is generated based on a touch input, a drag input, etc. to a predetermined area in a predetermined order that can be used in solving a tap height defective scenario, or a predetermined offset setting value is input. If so, the simulation device may determine that the tap height failure scenario has been resolved. In other words, when the tap height is corrected based on at least one of the corresponding user behavior information and laser setting information, the simulation device may determine that the tap height defect scenario is resolved. If it is determined that the bad scenario is solved, the tap height may be moved to the center between the upper and lower limit lines in the vision graph 1100 displaying the quality information of the electrode and output (1120).
- the simulation device determines one or more failure scenarios among a plurality of failure scenarios associated with the malfunction of the 3D laser notching machine in condition adjustment training or failure case training, and determines the one or more failure scenarios determined. At least one of the quality information associated with the operation of the 3D laser notching machine and the quality of the material may be changed based on the above.
- the plurality of bad scenarios may include pitch bad scenarios.
- the pitch defect scenario may refer to a scenario in which a defective material in which a pitch interval between two arbitrary electrodes deviates from an upper or lower limit of a predetermined specification is generated.
- the quality checking unit 140 includes a vision graph 1200, and when a bad pitch scenario occurs, the vision graph 1200 outputs or displays the pitch distance measured by the vision equipment for measuring the pitch distance from the normal measurement position. It can be.
- the pitch interval 1210 of the quality confirmation unit 140 is displayed skewed to the lower limit of the specification, and (Defects may be displayed that are biased toward the upper limit line.) Defective items are displayed in at least some areas of the 3D laser notching machine included in the device operation unit 130.
- an action guide may be additionally displayed on at least a portion of the device operation unit 130 .
- the user can correct the pitch interval by adjusting the pitch length offset 820 of the laser setting unit 150 as shown in FIG. 8 .
- a pitch failure scenario may be responded to by touching or dragging a specific area of the 3D laser notching machine displayed on the device operation unit 130 .
- the simulation device may correct the pitch interval of the material in response to receiving laser setting information corresponding to the pitch length offset from the user.
- the simulation device may correct the pitch interval of the changed electrodes in response to receiving user action information of touching or dragging a specific mechanical part region for resolving the pitch defect from the user.
- the simulation device can determine whether or not the pitch failure scenario has been resolved based on the corrected electrode pitch spacing. For example, at least one of user behavior information and laser setting information is generated based on a touch input, a drag input, etc. to a predetermined area in a predetermined order that can be used in solving a pitch failure scenario, or a predetermined offset setting value is input. If so, the simulation device may determine that the pitch failure scenario is resolved. In other words, the simulation device may determine that the pitch failure scenario is resolved when the pitch interval of the electrodes is corrected based on at least one of the corresponding user behavior information and laser setting information. If it is determined that the bad scenario is solved, the pitch interval may be moved to the center between the upper limit line and the lower limit line in the vision graph 1200 displaying the quality information of the electrode and output (1220).
- the simulation device determines one or more failure scenarios among a plurality of failure scenarios associated with the malfunction of the 3D laser notching machine in condition adjustment training or failure case training, and performs a 3D laser furnace operation based on the determined one or more failure scenarios. At least one of the quality information associated with the operation of the ting machine and the quality of the material may be changed.
- the plurality of failure scenarios may include vision position failure scenarios.
- the vision graph 900 of FIG. 9 may be a front and rear shoulder line position graph measured in a state in which the vision equipment for measuring the shoulder line position is changed to a predetermined specific abnormal measurement position
- the vision graph 1000 of FIG. 10 is the electrode length. It may be a graph of the electrode length measured in a state in which the vision equipment for measurement is changed to a specific abnormal measurement position set in advance
- the vision graph 1200 of FIG. 12 may be a pitch interval graph measured in a state in which the vision equipment for pitch interval measurement is changed to a predetermined specific abnormal measurement position.
- the quality information obtained through the vision equipment is As shown in the vision graphs 900, 1000, 1100, and 1200 of FIGS. 9 to 12, it may be displayed or output as poor punching conditions such as poor shoulder line position, poor electrode length, poor tab height, and poor pitch interval.
- the simulation device determines the front and rear shoulder line positions 910 and 930 of the quality checking unit 140, as shown in FIG. is displayed biased toward the upper limit of the specification (defects displayed biased toward the lower limit may occur), and defective items may be displayed in at least some areas of the 3D laser notching machine included in the device operation unit 130.
- the one or more determined failure scenarios include the electrode length measurement vision position failure scenario, as shown in FIG. 10
- the electrode length 1010 of the quality confirmation unit 140 is displayed biased toward the upper limit of the specification, (Defects may be displayed that are biased toward the lower limit line.)
- Defective items may be displayed in at least some areas of the 3D laser notching machine included in the device operation unit 130 .
- the tap height 1110 of the quality confirmation unit 140 is biased toward the lower limit of the specification, as shown in FIG. 11, and is displayed. (Defects may be displayed that are biased toward the upper limit line.) Defective items may be displayed in at least some areas of the 3D laser notching machine included in the device operation unit 130 .
- the pitch interval 1210 of the quality confirmation unit 140 is displayed biased toward the lower limit of the specification, as shown in FIG. 12 ( Defective items may be displayed that are biased toward the upper limit), and defective items may be displayed in at least some areas of the 3D laser notching machine included in the device operation unit 130 .
- the user may correct the vision position by adjusting the vision position offset value for each measurement item in the vision program.
- a vision position failure scenario can be responded to by touching or dragging a specific area of the 3D laser notching machine displayed on the device operation unit 130 .
- the simulation device may correct the vision position for measuring the corresponding measurement item in response to receiving user condition information corresponding to the vision position offset from the user.
- the simulation device may correct the changed vision position in response to receiving user action information of touching or dragging a specific mechanical part region for resolving a vision position defect from the user.
- an action guide may be additionally displayed on at least a portion of the device operation unit 130 .
- the simulation device can determine whether the vision position failure scenario has been resolved based on the corrected vision position. For example, at least one of user behavior information and user condition information is generated based on a touch input, a drag input, etc. for a predetermined area in a predetermined order that can be used in resolving a vision position failure scenario, or a predetermined vision position offset setting. If the value is entered, the simulation device can determine that the vision position failure scenario has been resolved. In other words, when the vision position is corrected based on at least one of corresponding user behavior information and user condition information, the simulation device may determine that the vision position failure scenario is resolved.
- the front and rear shoulder lines are moved to the center between the upper and lower limit lines in the vision graphs (900, 1000, 1100, and 1200) displaying the quality information of the electrodes and output (920, 940), or the electrode
- the length may be moved to the center between the upper and lower limits (1020)
- the tab height may be moved to the center between the upper and lower limits (1120)
- the pitch interval may be moved to the center between the upper and lower limits and output (1120). Yes (1220).
- FIG. 13 is a diagram illustrating an example of generating a bad scenario 1322 according to an embodiment of the present invention.
- the simulation device 100 communicates with an external device (eg, secondary battery production equipment, etc.) 1310 and a bad scenario DB 1320, and data and/or information necessary for generating a bad scenario 1322. can be exchanged.
- an external device eg, secondary battery production equipment, etc.
- the simulation device 100 may receive or obtain error information 1312 related to the malfunction occurring from the external device 1310.
- the error information 1312 may include operation information of the external device 1310 at the time of occurrence of the malfunction and a quality change amount of a material generated by the external device 1310 .
- the simulation device 100 determines the value of each quality parameter of the condition value, setting value and / or quality information of the 3D model device (eg, 3D laser notching machine) to correspond to the corresponding error information 1312,
- a bad scenario 1322 having determined condition values, setting values, and/or quality parameter values of the 3D model device may be created.
- the bad scenario 1322 generated in this way may be stored and managed in the bad scenario DB 1320 .
- the simulation device 100 uses an arbitrary algorithm and/or a learned machine learning model to generate a bad scenario 1322 to correspond to the error information 1312, condition values and set values of the 3D model device And/or a value of each quality parameter of the quality information may be determined, and a bad scenario 1322 may be generated.
- the processor converts operation information of the external device 1310 into a first set of parameters related to the operation of the 3D model device, and converts the amount of quality change of the material generated by the external device 1410 into a 3D model device. into a second set of parameters associated with quality information associated with the quality of the material produced by Then, the processor determines a category of the malfunction occurring in the external device 1310 using the converted first set of parameters and the second set of parameters, and the determined category, the first set of parameters and the second set of parameters.
- a failure scenario can be created based on a set of parameters.
- a bad scenario is generated when a malfunction occurs in the external device 1310, but is not limited thereto, and for example, the bad scenario may be predetermined by a user. In another example, the bad scenario may be generated by randomly determining setting values, condition values, and quality information associated with the 3D model device within a predetermined abnormal range. With this configuration, the user can effectively improve his ability to respond to defects by training using a failure scenario generated based on a malfunction occurring in an actual working environment.
- the simulation device 100 receives user condition information 1410, user behavior information 1420, laser setting information 1430, etc. from the user, and the received user condition information ( 1410), user behavior information 1420, laser setting information 1430, etc., it may be determined whether the bad scenario is resolved.
- the simulation device 100 determines the work speed of the bad scenario while the bad scenario is in progress, the time required for bad action, the number of NGs, and the target A value proximity degree and a loss value may be calculated, and operating capability information 1440 for a 3D model device of a user account may be generated based on the calculated running time and loss value.
- the test result 1450 may be output together with the operational capability information 1440 .
- a user associated with a corresponding user account may perform a test on any bad scenario, and if all bad scenarios associated with a specific 3D model device are solved according to predetermined criteria, the simulation device 100 It may be determined that the user has passed a simulation test for a specific 3D model device.
- the simulation method for secondary battery production may be performed by a processor (eg, at least one processor of a simulation device).
- the simulation method for secondary battery production (S1500) includes a processor operating unit including a 3D model device associated with secondary battery production, and a plurality of adjustment parameters for determining the operation of the 3D model device. It may be started by outputting a quality confirmation unit including quality information related to the quality of the material produced by the facility moving unit and the 3D model device (S1510).
- the processor may obtain at least one of first user behavior information obtained through the device operation unit and first user condition information obtained through the facility operation unit (S1520).
- the first user condition information may include information related to a value corresponding to at least one adjustment parameter among a plurality of adjustment parameters.
- the processor may determine the operation of the 3D model device based on at least one of the obtained first user behavior information and first user condition information (S1530). Also, the processor may execute the operation of the 3D model device included in the device operating unit based on the determined operation (S1540). When receiving the first user behavior information, the processor determines whether the received first user behavior information corresponds to a predetermined operating condition of the 3D model device, and determines whether the first user behavior information corresponds to the predetermined operating condition of the 3D model device. If it is determined to correspond to , the operation of the 3D model device may be permitted.
- the processor determines one or more quality parameters for determining the quality of the material produced by the 3D model device, and while the operation of the 3D model device is being executed, based on the operation of the 3D model device being executed. A value corresponding to each of the determined one or more quality parameters may be calculated. In addition, the processor may generate quality information associated with the quality of the material created by the 3D model device based on values corresponding to each of the one or more quality parameters calculated.
- the processor determines one or more failure scenarios among a plurality of failure scenarios associated with the malfunction of the 3D model device, and among the quality information associated with the operation of the 3D model device and the quality of the material, based on the determined one or more failure scenarios. At least one can be changed. Then, the processor receives at least one of second user behavior information and second user condition information for solving the determined one or more bad scenarios, and based on the received at least one of second user behavior information and second user condition information. Thus, the operation of the changed 3D model device can be corrected.
- the processor calculates a value corresponding to each of a plurality of quality parameters related to the quality of the material produced by the 3D model device based on the operation of the 3D model device being executed. can do.
- the processor corrects quality information associated with the quality of the material generated by the calibrated 3D model device based on the value corresponding to each of the calculated quality parameters, and uses the corrected quality information to detect one or more defects. It can be determined whether the scenario has been resolved.
- 16 is a diagram showing an example of a simulation method (S1600) of a laser notching machine for producing a secondary battery according to an embodiment of the present invention.
- the laser notching machine simulation method for producing a secondary battery may be performed by a processor (eg, at least one processor of a simulation device).
- a processor includes a device operating unit including a 3D laser notching machine related to secondary battery production, and a plurality of devices for determining the operation of the 3D laser notching machine.
- the processor may obtain at least one of first user behavior information obtained through the device operation unit, first user condition information obtained through the facility operation unit, and first laser setting information obtained through the laser setting unit (S1620). Also, the processor may determine an operation of the 3D laser notching machine based on at least one of the obtained first user behavior information, first user condition information, and first laser setting information (S1630). Also, the processor may execute an operation of punching an electrode associated with the 3D laser notching machine based on the determined operation (S1640).
- the operation of the 3D laser notching machine may include a notching facility operation training operation and a material replacement training operation
- the notching facility operation training operation includes operation readiness check, notching facility operation
- the replacement training operation may include checking the state of the supply unit, removing the remaining amount of the electrode, connecting the electrode, taking a sample, and the like.
- the processor determines one or more quality parameters for determining the quality of the material produced by the 3D laser notching machine, and while the operation of the 3D laser notching machine is being executed, the one determined based on the operation of the 3D laser notching machine being executed. A value corresponding to each of the above quality parameters can be calculated. Then, the processor may generate quality information associated with the quality of the material produced by the 3D laser notching machine based on values corresponding to each of the calculated one or more quality parameters.
- the processor determines one or more failure scenarios among a plurality of failure scenarios associated with malfunction of the 3D laser notching machine, and based on the determined one or more failure scenarios, quality associated with the operation of the 3D laser notching machine and the quality of the material. At least one of the information may be changed.
- the plurality of defect scenarios may include a defective shoulder line scenario, a defective electrode length scenario, a defective tab height scenario, a defective pitch scenario, and a defective vision position scenario.
- each bad scenario can be solved by arbitrary user condition information, user behavior information, and/or laser setting information input from the user.
- test result calculation method ( S1700 ) may be performed by a processor (eg, at least one processor of a simulation device). As shown, the test result calculation method ( S1700 ) may be initiated by receiving at least one of second user behavior information, second user condition information, and second laser setting information for solving one or more failure scenarios determined by the processor. Yes (S1710).
- a processor eg, at least one processor of a simulation device.
- the test result calculation method ( S1700 ) may be initiated by receiving at least one of second user behavior information, second user condition information, and second laser setting information for solving one or more failure scenarios determined by the processor. Yes (S1710).
- the processor may correct the changed operation of the 3D model device based on at least one of the received second user behavior information, second user condition information, and second laser setting information (S1720).
- the processor calculates a value corresponding to each of a plurality of quality parameters related to the quality of the material produced by the 3D model device based on the operation of the 3D model device being executed. It can be done (S1730).
- the processor may correct the quality information associated with the quality of the material generated by the calibrated 3D model device based on the value corresponding to each of the calculated quality parameters (S1740).
- the processor may determine whether one or more bad scenarios are resolved using the corrected quality information and/or setting values and condition values of the 3D model device (S1750). When it is determined that the bad scenario is not resolved, the processor may generate or obtain second user behavior information, second user condition information, and second laser setting information again using information input by the user.
- the processor may calculate progress times and loss values of the one or more bad scenarios while the one or more bad scenarios are in progress (S1760).
- the processor may generate operational capability information for the 3D model device of the user account based on the calculated running time and loss value (S1770).
- the operating capability information may include, but is not limited to, the work speed and accuracy calculated using the time taken to take action against defects, the number of NGs, the degree of proximity to a target value, and the loss value. It may further include a test score, whether the test passed or not, and the like.
- one user account may be assigned to each user who produces secondary batteries, and the corresponding user's work speed for bad scenarios, the time taken for bad actions, the number of NGs, the degree of proximity to the target value, and the loss value Operation capability information generated based on the above may be stored or managed in association with a corresponding user account.
- FIG. 18 is a diagram illustrating an example of a bad scenario generating method ( S1800 ) according to an embodiment of the present invention.
- the method of generating a bad scenario ( S1800 ) may be performed by a processor (eg, at least one processor of a simulation device).
- the bad scenario generation method ( S1800 ) may be initiated by obtaining error information associated with the malfunction when a malfunction occurs in an external device associated with a 3D model device (S1810).
- the processor may generate a bad scenario associated with a malfunction of the 3D model device based on the obtained error information (S1820).
- the error information may include values and setting values of each adjustment parameter of the production equipment when actual secondary battery production equipment associated with the 3D model device malfunctions. For example, if the quality of the material produced by the secondary battery production equipment is out of a predetermined normal range, it may be determined that a malfunction has occurred, and if it is determined that a malfunction has occurred, the processor obtains error information related to the malfunction. And, based on the obtained error information, a bad scenario related to the malfunction of the 3D model device may be generated.
- computing device 1900 may be implemented using hardware and/or software configured to interact with a user.
- the computing device 1900 may include the aforementioned simulation device ( 100 in FIG. 1 ).
- the computing device 1900 may be configured to support a virtual reality (VR), augmented reality (AR), or mixed reality (MR) environment, but is not limited thereto.
- the computing device 1900 includes a laptop, a desktop, a workstation, a personal digital assistant, a server, a blade server, a main frame, and the like. It may include, but is not limited to.
- the components of the computing device 1900 described above, their connections, and their functions are intended to be illustrative, and are not intended to limit implementations of the invention described and/or claimed herein.
- Computing device 1900 includes a processor 1910, memory 1920, storage 1930, communication device 1940, memory 1920 and a high-speed interface 1950 connected to a high-speed expansion port, and a low-speed bus and storage devices. and a low-speed interface 1960 coupled to.
- Each of the components 1910, 1920, 1930, 1940, 1950 and 1960 can be interconnected using various buses, mounted on the same main board, or mounted and connected in other suitable ways. there is.
- the processor 1910 may be configured to process commands of a computer program by performing basic arithmetic, logic, and input/output operations.
- the processor 1910 processes instructions stored in the memory 1920, the storage device 1930, and/or instructions executed in the computing device 1900, and displays the device coupled to the high-speed interface 1950.
- Graphic information may be displayed on an external input/output device 1970 such as
- the communication device 1940 may provide a configuration or function for the I/O device 1970 and the computing device 1900 to communicate with each other through a network, and the I/O device 1970 and/or the computing device 1900 may be connected to another external device.
- a configuration or function may be provided to support communication with a device or the like. For example, a request or data generated by a processor of an external device according to an arbitrary program code may be transmitted to the computing device 1900 through a network under the control of the communication device 1940 . Conversely, a control signal or command provided under the control of the processor 1910 of the computing device 1900 may be transferred to another external device via the communication device 1940 and a network.
- the computing device 1900 is illustrated as including one processor 1910 and one memory 1920, but is not limited thereto, and the computing device 1900 includes a plurality of memories, a plurality of processors, and/or Alternatively, it may be implemented using a plurality of buses.
- the present invention is not limited thereto, and a plurality of computing devices may interact with each other and perform operations required to execute the above-described method.
- Memory 1920 may store information within computing device 1900 .
- the memory 1920 may include a volatile memory unit or a plurality of memory units. Additionally or alternatively, memory 1920 may be comprised of a non-volatile memory unit or a plurality of memory units. Also, the memory 1920 may be comprised of other forms of computer readable media, such as magnetic disks or optical disks. Also, an operating system and at least one program code and/or command may be stored in the memory 1920 .
- Storage device 1930 may be one or more mass storage devices for storing data for computing device 1900 .
- the storage device 1930 may include a hard disk, a magnetic disk such as a removable disk, an optical disk, an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable PROM (EEPROM), and a flash memory.
- EPROM Erasable Programmable Read-Only Memory
- EEPROM Electrically Erasable PROM
- flash memory It may be a computer readable medium including a semiconductor memory device such as a device, a CD-ROM and a DVD-ROM disk, or the like, or may be configured to include such a computer readable medium.
- a computer program may be tangibly implemented in such a computer readable medium.
- High-speed interface 1950 and low-speed interface 1960 may be means for interacting with input/output device 1970.
- the input device may include a device such as a camera, keyboard, microphone, mouse, etc. including an audio sensor and/or image sensor
- the output device may include a device such as a display, speaker, haptic feedback device, or the like.
- the high-speed interface 1950 and the low-speed interface 1960 may be means for interface with a device in which a configuration or function for performing input and output is integrated into one, such as a touch screen.
- high-speed interface 1950 manages bandwidth-intensive operations for computing device 1900, while low-speed interface 1960 may manage less bandwidth-intensive operations than high-speed interface 1950.
- the high-speed interface 1950 may be coupled to high-speed expansion ports capable of accommodating the memory 1920, the input/output device 1970, and various expansion cards (not shown).
- low-speed interface 1960 can be coupled to storage 1930 and low-speed expansion port.
- a low-speed expansion port which may include various communication ports (e.g., USB, Bluetooth, Ethernet, wireless Ethernet), supports one or more input/output devices such as a keyboard, pointing device, and scanner.
- Device 1970 or may be coupled to a networking device such as a router, a switch, or the like through a network adapter or the like.
- Computing device 1900 may be implemented in many different forms. For example, computing device 1900 may be implemented as a standard server, or a group of such standard servers. Additionally or alternatively, computing device 1900 may be implemented as part of a rack server system or a personal computer such as a laptop computer. In this case, components from computing device 1900 may be combined with other components in any mobile device (not shown). This computing device 1900 may include one or more other computing devices or be configured to communicate with one or more other computing devices.
- the input/output device 1970 is not included in the computing device 1900, but is not limited thereto, and the computing device 1900 and the computing device 1900 may be configured as one device.
- the high-speed interface 1950 and/or the low-speed interface 1960 are shown as separate components from the processor 1910, but are not limited thereto, and the high-speed interface 1950 and/or the low-speed interface 1960 It may be configured to be included in the processor 1910.
- the above methods and/or various embodiments may be realized with digital electronic circuits, computer hardware, firmware, software, and/or combinations thereof.
- Various embodiments of the present invention may be executed by a data processing device, eg, one or more programmable processors and/or one or more computing devices, or implemented as a computer readable medium and/or a computer program stored on a computer readable medium.
- a data processing device eg, one or more programmable processors and/or one or more computing devices, or implemented as a computer readable medium and/or a computer program stored on a computer readable medium.
- the above-described computer program may be written in any form of programming language, including a compiled language or an interpreted language, and may be distributed in any form such as a stand-alone program, module, or subroutine.
- a computer program may be distributed over one computing device, multiple computing devices connected through the same network, and/or distributed over multiple computing devices connected through multiple different networks.
- the methods and/or various embodiments described above may be performed by one or more processors configured to execute one or more computer programs that process, store, and/or manage certain functions, functions, or the like, by operating on input data or generating output data.
- processors configured to execute one or more computer programs that process, store, and/or manage certain functions, functions, or the like, by operating on input data or generating output data.
- the method and/or various embodiments of the present invention may be performed by a special purpose logic circuit such as a Field Programmable Gate Array (FPGA) or an Application Specific Integrated Circuit (ASIC), and the method and/or various embodiments of the present invention may be performed.
- Apparatus and/or systems for performing the embodiments may be implemented as special purpose logic circuits such as FPGAs or ASICs.
- the one or more processors that execute the computer program may include general purpose or special purpose microprocessors and/or one or more processors of any kind of digital computing device.
- the processor may receive instructions and/or data from each of the read-only memory and the random access memory, or receive instructions and/or data from the read-only memory and the random access memory.
- components of a computing device performing methods and/or embodiments may include one or more processors for executing instructions, and one or more memories for storing instructions and/or data.
- a computing device may exchange data with one or more mass storage devices for storing data.
- a computing device may receive/receive data from and transfer data to a magnetic or optical disc.
- a computer readable medium suitable for storing instructions and/or data associated with a computer program includes any semiconductor memory device such as an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable PROM (EEPROM), and a flash memory device. It may include a non-volatile memory in the form of, but is not limited thereto.
- the computer readable medium may include a magnetic disk such as an internal hard disk or a removable disk, a photomagnetic disk, a CD-ROM, and a DVD-ROM disk.
- a computing device includes a display device (eg, a cathode ray tube (CRT), a liquid crystal display (LCD), etc.) It may include a pointing device (eg, a keyboard, mouse, trackball, etc.) capable of providing input and/or commands to, but is not limited thereto. That is, the computing device may further include any other type of device for providing interaction with a user.
- a computing device may provide any form of sensory feedback to a user for interaction with the user, including visual feedback, auditory feedback, and/or tactile feedback.
- the user may provide input to the computing device through various gestures such as visual, voice, and motion.
- a computing device including a back-end component (eg, a data server), a middleware component (eg, an application server), and/or a front-end component.
- the components may be interconnected by any form or medium of digital data communication, such as a communication network.
- the communication network is a wired network such as Ethernet, a wired home network (Power Line Communication), a telephone line communication device and RS-serial communication, a mobile communication network, a wireless LAN (WLAN), Wi-Fi, and Bluetooth. and a wireless network such as ZigBee or a combination thereof.
- the communication network may include a local area network (LAN), a wide area network (WAN), and the like.
- a computing device based on the example embodiments described herein may be implemented using hardware and/or software configured to interact with a user, including a user device, user interface (UI) device, user terminal, or client device.
- the computing device may include a portable computing device such as a laptop computer.
- the computing device may include personal digital assistants (PDAs), tablet PCs, game consoles, wearable devices, internet of things (IoT) devices, virtual reality (VR) devices, AR (augmented reality) device, etc. may be included, but is not limited thereto.
- PDAs personal digital assistants
- tablet PCs tablet PCs
- game consoles wearable devices
- IoT internet of things
- VR virtual reality
- AR augmented reality
- a computing device may further include other types of devices configured to interact with a user.
- the computing device may include a portable communication device (eg, a mobile phone, smart phone, wireless cellular phone, etc.) suitable for wireless communication over a network, such as a mobile communication network.
- a computing device communicates wirelessly with a network server using wireless communication technologies and/or protocols such as radio frequency (RF), microwave frequency (MWF) and/or infrared ray frequency (IRF). It can be configured to communicate with.
- RF radio frequency
- MMF microwave frequency
- IRF infrared ray frequency
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Abstract
Description
Claims (23)
- 이차전지 생산을 위한 시뮬레이션 장치로서,적어도 하나의 명령어들을 저장하도록 구성된 메모리; 및상기 메모리에 저장된 상기 적어도 하나의 명령어들을 실행하도록 구성된 적어도 하나의 프로세서를 포함하고,상기 적어도 하나의 명령어들은,이차전지의 생산과 연관된 3D 레이저 노칭기를 포함하는 장치 동작부, 상기 3D 레이저 노칭기의 동작을 결정하기 위한 복수의 조정 파라미터를 포함하는 설비 가동부, 상기 3D 레이저 노칭기에 의해 생성되는 물질의 품질과 연관된 품질 정보를 포함하는 품질 확인부 및 상기 3D 레이저 노칭기의 동작을 결정하기 위한 복수의 레이저 파라미터를 포함하는 레이저 설정부를 실행하고,상기 장치 동작부를 통해 획득되는 제1 사용자 행동 정보, 상기 설비 가동부를 통해 획득되는 제1 사용자 조건 정보 및 상기 레이저 설정부를 통해 획득되는 제1 레이저 설정 정보 중 적어도 하나를 획득하고,상기 획득된 제1 사용자 행동 정보, 제1 사용자 조건 정보 및 제1 레이저 설정 정보 중 적어도 하나에 기초하여 상기 3D 레이저 노칭기의 동작을 결정하고,상기 결정된 동작을 기초로 상기 3D 레이저 노칭기와 연관된 전극을 타발하는 동작을 실행하기 위한 명령어들을 포함하는, 이차전지 생산을 위한 레이저 노칭기의 시뮬레이션 장치.
- 제1항에 있어서,상기 적어도 하나의 명령어들은,상기 3D 레이저 노칭기의 가동 과정에 기반한 3D 레이저 노칭기 훈련 시나리오를 실행하고,상기 3D 레이저 노칭기 훈련 시나리오에 따라 상기 3D 레이저 노칭기를 구동, 상기 장치 동작부에 사용자 행동 가이드 표시, 상기 설비 가동부에 사용자 조건 가이드 표시 및 상기 레이저 설정부에 레이저 설정 가이드 표시 중 적어도 하나를 실행하고,상기 사용자 행동 가이드 표시에 기반한 상기 제1 사용자 행동 정보, 상기 사용자 조건 가이드 표시에 기반한 상기 제1 사용자 조건 정보 및 상기 레이저 설정 가이드 표시에 기반한 상기 제1 레이저 설정 정보 중 적어도 하나를 획득하고,상기 획득된 제1 사용자 행동 정보, 상기 제1 사용자 조건 정보 및 상기 제1 레이저 설정 정보 중 적어도 하나를 기반으로 상기 장치 동작부 및 상기 설비 가동부 중 적어도 하나를 변경하기 위한 명령어들을 더 포함하는 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 장치.
- 제2항에 있어서,상기 3D 레이저 노칭기 훈련 시나리오는 재료 교체 훈련 시나리오를 포함하고,상기 재료 교체 훈련 시나리오는 공급부 상태 확인 단계, 전극 잔량 제거 단계, 전극 연결 단계 및 샘플 채취 단계 중 적어도 하나를 포함하는 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 장치.
- 제2항에 있어서,상기 3D 레이저 노칭기 훈련 시나리오는, 설비 가동 훈련 시나리오를 포함하고,상기 설비 가동 훈련 시나리오는 가동 준비 상태 확인 단계, 노칭 설비 가동 단계 및 타발 상태 확인 단계 중 적어도 하나를 포함하는 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 장치.
- 제1항에 있어서,상기 적어도 하나의 명령어들은,상기 3D 레이저 노칭기에 의해 생성되는 물질의 품질을 결정하기 위한 하나 이상의 품질 파라미터를 결정하고,상기 3D 레이저 노칭기의 동작이 실행되는 동안에, 상기 실행되는 3D 레이저 노칭기의 동작을 기초로 상기 결정된 하나 이상의 품질 파라미터의 각각에 대응하는 값을 산출하고,상기 산출된 하나 이상의 품질 파라미터의 각각에 대응하는 값을 기초로 상기 3D 레이저 노칭기에 의해 생성되는 물질의 품질과 연관된 품질 정보를 생성하기 위한 명령어들을 더 포함하는 이차전지 생산을 위한 레이저 노칭기의 시뮬레이션 장치.
- 제5항에 있어서,상기 적어도 하나의 명령어들은,상기 3D 레이저 노칭기의 작동과 연관된 복수의 불량 시나리오 중 하나 이상의 불량 시나리오를 결정하고,상기 결정된 하나 이상의 불량 시나리오에 기초하여 상기 3D 레이저 노칭기의 구동 및 상기 물질의 품질과 연관된 품질 정보 중 적어도 하나를 변경하기 위한 명령어들을 더 포함하는 이차전지 생산을 위한 레이저 노칭기의 시뮬레이션 장치.
- 제6항에 있어서,상기 복수의 불량 시나리오는,상기 3D 레이저 노칭기에서 타발되는 전극의 전면 및 후면 어깨선 위치를 기설정된 비정상 범위로 변경하는 어깨선 불량 시나리오, 상기 3D 레이저 노칭기에서 타발되는 전극의 길이를 기설정된 비정상 범위로 변경하는 전극 길이 불량 시나리오, 상기 3D 레이저 노칭기에서 타발되는 전극 탭의 높이를 기설정된 비정상 범위로 변경하는 탭 높이 불량 시나리오, 상기 3D 레이저 노칭기에서 타발되는 전극의 특정 주기의 피치 간격을 기설정된 비정상 범위로 변경하는 피치 불량 시나리오 및 비전 계측 항목의 측정 위치를 기설정된 비정상 위치로 변경하는 비전 위치 불량 시나리오 중 적어도 하나를 포함하는 이차전지 생산을 위한 레이저 노칭기의 시뮬레이션 장치.
- 제7항에 있어서,상기 적어도 하나의 명령어들은,상기 어깨선 불량 시나리오 및 전극 길이 불량 시나리오 중 적어도 하나의 불량 시나리오를 실행하고,상기 3D 레이저 노칭기의 적어도 일부 영역을 구동하는 제2 사용자 행동 정보 및 상기 설비 가동부의 조정 파라미터를 변경하는 제2 사용자 조건 정보 중 적어도 하나를 획득하고,상기 획득된 제2 사용자 행동 정보 및 제2 사용자 조건 정보 중 적어도 하나에 기초하여 상기 3D 레이저 노칭기의 구동을 보정하고,상기 보정된 3D 레이저 노칭기에 의해 생성되는 물질의 품질과 연관된 하나 이상의 품질 파라미터의 각각에 대응하는 값을 산출하고,상기 산출된 하나 이상의 품질 파라미터의 각각에 대응하는 값을 기초로 상기 보정된 3D 레이저 노칭기에 의해 생성되는 물질의 품질과 연관된 품질 정보를 보정하기 위한 명령어들을 더 포함하는 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 장치.
- 제7항에 있어서,상기 적어도 하나의 명령어들은,상기 탭 높이 불량 시나리오 및 피치 불량 시나리오 중 적어도 하나의 불량 시나리오를 실행하고,상기 3D 레이저 노칭기의 적어도 일부 영역을 구동하는 제2 사용자 행동 정보 및 상기 레이저 설정부의 레이저 파라미터를 변경하는 제2 레이저 설정 정보 중 적어도 하나를 획득하고,상기 획득된 제2 사용자 행동 정보 및 제2 레이저 설정 정보 중 적어도 하나에 기초하여 상기 3D 레이저 노칭기의 구동을 보정하고,상기 보정된 3D 레이저 노칭기에 의해 생성되는 물질의 품질과 연관된 하나 이상의 품질 파라미터의 각각에 대응하는 값을 산출하고,상기 산출된 하나 이상의 품질 파라미터의 각각에 대응하는 값을 기초로 상기 보정된 3D 레이저 노칭기에 의해 생성되는 물질의 품질과 연관된 품질 정보를 보정하기 위한 명령어들을 더 포함하는 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 장치.
- 제7항에 있어서,상기 적어도 하나의 명령어들은,상기 비전 위치 불량 시나리오를 실행하고,상기 3D 레이저 노칭기와 연관된 비전 프로그램의 측정 위치 오프셋 값 변경 정보를 획득하고,상기 획득된 측정 위치 오프셋 값 변경 정보에 기초하여 상기 비전 위치를 보정하고,상기 보정된 비전 위치를 기반으로 상기 3D 레이저 노칭기에 의해 생성되는 물질의 품질과 연관된 품질 정보를 보정하기 위한 명령어들을 더 포함하는 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 장치.
- 제8항 내지 제10항 중 어느 한 항에 있어서,상기 적어도 하나의 명령어들은,상기 하나 이상의 불량 시나리오를 해결하기 위해 요구되는 정보를 포함하는 가이드 정보를 출력하기 위한 명령어들을 더 포함하는 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 장치.
- 적어도 하나의 프로세서에 의해 수행되는 이차전지 생산을 위한 레이저 노칭기의 시뮬레이션 방법으로서,이차전지의 생산과 연관된 3D 레이저 노칭기를 포함하는 장치 동작부, 상기 3D 레이저 노칭기의 동작을 결정하기 위한 복수의 조정 파라미터를 포함하는 설비 가동부, 상기 3D 레이저 노칭기에 의해 생성되는 물질의 품질과 연관된 품질 정보를 포함하는 품질 확인부 및 상기 3D 레이저 노칭기의 동작을 결정하기 위한 복수의 레이저 파라미터를 포함하는 레이저 설정부를 실행하는 단계;상기 장치 동작부를 통해 획득되는 제1 사용자 행동 정보, 상기 설비 가동부를 통해 획득되는 제1 사용자 조건 정보 및 상기 레이저 설정부를 통해 획득되는 제1 레이저 설정 정보 중 적어도 하나를 획득하는 단계;상기 획득된 제1 사용자 행동 정보, 제1 사용자 조건 정보 및 제1 레이저 설정 정보 중 적어도 하나에 기초하여 상기 3D 레이저 노칭기의 동작을 결정하는 단계; 및상기 결정된 동작을 기초로 상기 3D 레이저 노칭기와 연관된 전극을 타발하는 동작을 실행하는 단계;를 포함하는 이차전지 생산을 위한 레이저 노칭기의 시뮬레이션 방법.
- 제12항에 있어서,상기 3D 레이저 노칭기의 가동 과정에 기반한 3D 레이저 노칭기 훈련 시나리오를 실행하는 단계;상기 3D 레이저 노칭기 훈련 시나리오에 따라 상기 3D 레이저 노칭기를 구동, 상기 장치 동작부에 사용자 행동 가이드 표시, 상기 설비 가동부에 사용자 조건 가이드 표시 및 상기 레이저 설정부에 레이저 설정 가이드 표시 중 적어도 하나를 실행하는 단계;상기 사용자 행동 가이드 표시에 기반한 상기 제1 사용자 행동 정보, 상기 사용자 조건 가이드 표시에 기반한 상기 제1 사용자 조건 정보 및 상기 레이저 설정 가이드 표시에 기반한 상기 제1 레이저 설정 정보 중 적어도 하나를 획득하는 단계; 및상기 획득된 제1 사용자 행동 정보, 상기 제1 사용자 조건 정보 및 상기 제1 레이저 설정 정보 중 적어도 하나를 기반으로 상기 장치 동작부 및 상기 설비 가동부 중 적어도 하나를 변경하는 단계;를 더 포함하는, 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 방법.
- 제13항에 있어서,상기 3D 레이저 노칭기 훈련 시나리오는 재료 교체 훈련 시나리오를 포함하고,상기 재료 교체 훈련 시나리오는 공급부 상태 확인 단계, 전극 잔량 제거 단계, 전극 연결 단계 및 샘플 채취 단계 중 적어도 하나를 포함하는, 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 방법.
- 제13항에 있어서,상기 3D 레이저 노칭기 훈련 시나리오는 설비 가동 훈련 시나리오를 포함하고,상기 설비 가동 훈련 시나리오는 가동 준비 상태 확인 단계, 노칭 설비 가동 단계 및 타발 상태 확인 단계 중 적어도 하나를 포함하는, 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 방법.
- 제12항에 있어서,상기 3D 레이저 노칭기에 의해 생성되는 물질의 품질을 결정하기 위한 하나 이상의 품질 파라미터를 결정하는 단계;상기 3D 레이저 노칭기의 동작이 실행되는 동안에, 상기 실행되는 3D 레이저 노칭기의 동작을 기초로 상기 결정된 하나 이상의 품질 파라미터의 각각에 대응하는 값을 산출하는 단계; 및상기 산출된 하나 이상의 품질 파라미터의 각각에 대응하는 값을 기초로 상기 3D 레이저 노칭기에 의해 생성되는 물질의 품질과 연관된 품질 정보를 생성하는 단계;를 더 포함하는, 이차전지 생산을 위한 레이저 노칭기의 시뮬레이션 방법.
- 제16항에 있어서,상기 3D 레이저 노칭기의 작동과 연관된 복수의 훈련 시나리오 중 하나 이상의 불량 시나리오를 결정하는 단계; 및상기 결정된 하나 이상의 불량 시나리오에 기초하여 상기 3D 레이저 노칭기의 구동 및 상기 물질의 품질과 연관된 품질 정보 중 적어도 하나를 변경하는 단계;를 더 포함하는 이차전지 생산을 위한 레이저 노칭기의 시뮬레이션 방법.
- 제17항에 있어서,상기 복수의 불량 시나리오는,상기 3D 레이저 노칭기에서 타발되는 전극의 전면 및 후면 어깨선 위치를 기설정된 비정상 범위로 변경하는 어깨선 불량 시나리오, 상기 3D 레이저 노칭기에서 타발되는 전극의 길이를 기설정된 비정상 범위로 변경하는 전극 길이 불량 시나리오, 상기 3D 레이저 노칭기에서 타발되는 전극 탭의 높이를 기설정된 비정상 범위로 변경하는 탭 높이 불량 시나리오, 상기 3D 레이저 노칭기에서 타발되는 전극의 특정 주기의 피치 간격을 기설정된 비정상 범위로 변경하는 피치 불량 시나리오 및 비전 계측 항목의 측정 위치를 기설정된 비정상 위치로 변경하는 비전 위치 불량 시나리오 중 적어도 하나를 포함하는 이차전지 생산을 위한 레이저 노칭기의 시뮬레이션 방법.
- 제18항에 있어서,상기 어깨선 불량 시나리오 및 전극 길이 불량 시나리오 중 적어도 하나의 불량 시나리오를 실행하는 단계;상기 3D 레이저 노칭기의 적어도 일부 영역을 구동하는 제2 사용자 행동 정보 및 상기 설비 가동부의 조정 파라미터를 변경하는 제2 사용자 조건 정보 중 적어도 하나를 획득하는 단계;상기 획득된 제2 사용자 행동 정보 및 제2 사용자 조건 정보 중 적어도 하나에 기초하여 상기 3D 레이저 노칭기의 구동을 보정하는 단계;상기 보정된 3D 레이저 노칭기에 의해 생성되는 물질의 품질과 연관된 하나 이상의 품질 파라미터의 각각에 대응하는 값을 산출하는 단계; 및상기 산출된 하나 이상의 품질 파라미터의 각각에 대응하는 값을 기초로 상기 보정된 3D 레이저 노칭기에 의해 생성되는 물질의 품질과 연관된 품질 정보를 보정하는 단계;를 더 포함하는, 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 방법.
- 제18항에 있어서,상기 탭 높이 불량 시나리오 및 피치 불량 시나리오 중 적어도 하나의 불량 시나리오를 실행하는 단계;상기 3D 레이저 노칭기의 적어도 일부 영역을 구동하는 제2 사용자 행동 정보 및 상기 레이저 설정부의 레이저 파라미터를 변경하는 제2 레이저 설정 정보 중 적어도 하나를 획득하는 단계;상기 획득된 제2 사용자 행동 정보 및 제2 레이저 설정 정보 중 적어도 하나에 기초하여 상기 3D 레이저 노칭기의 구동을 보정하는 단계;상기 보정된 3D 레이저 노칭기에 의해 생성되는 물질의 품질과 연관된 하나 이상의 품질 파라미터의 각각에 대응하는 값을 산출하는 단계; 및상기 산출된 하나 이상의 품질 파라미터의 각각에 대응하는 값을 기초로 상기 보정된 3D 레이저 노칭기에 의해 생성되는 물질의 품질과 연관된 품질 정보를 보정하 하는 단계;를 더 포함하는, 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 방법.
- 제18항에 있어서,상기 비전 위치 불량 시나리오를 실행하는 단계;상기 3D 레이저 노칭기와 연관된 비전 프로그램의 측정 위치 오프셋 값 변경 정보를 획득하는 단계;상기 획득된 측정 위치 오프셋 값 변경 정보에 기초하여 상기 비전 위치를 보정하는 단계; 및상기 보정된 비전 위치를 기반으로 상기 3D 레이저 노칭기에 의해 생성되는 물질의 품질과 연관된 품질 정보를 보정하는 단계;를 더 포함하는, 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 방법.
- 제19항 내지 제21항 중 어느 한 항에 있어서,상기 하나 이상의 불량 시나리오를 해결하기 위해 요구되는 정보를 포함하는 가이드 정보를 출력하는 단계를 더 포함하는, 이차전지 생산을 위한 레이저 노칭기 시뮬레이션 방법.
- 제12항 내지 제22항 중 어느 한 항에 따른 방법을 컴퓨터에서 실행하기 위해 컴퓨터 판독 가능한 매체에 저장된 컴퓨터 프로그램.
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CN206541535U (zh) * | 2017-03-06 | 2017-10-03 | 武汉弗莱茵科技有限公司 | 双光路远程激光雕刻切割加工维修综合实训装置 |
KR102008871B1 (ko) * | 2018-12-06 | 2019-10-21 | (주)하나기술 | 진공롤링부를 구비하는 이차전지 전극 노칭시스템 |
KR102181983B1 (ko) * | 2019-08-13 | 2020-11-24 | (주)디이엔티 | 레이저 노칭 장치 |
CN213211381U (zh) * | 2020-09-25 | 2021-05-14 | 邢台职业技术学院 | 一种用于教学实验室的激光加工教学实训设备 |
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CN201429926Y (zh) * | 2009-03-31 | 2010-03-24 | 武汉楚天数控设备制造有限公司 | 教学专用激光切割机 |
CN206541535U (zh) * | 2017-03-06 | 2017-10-03 | 武汉弗莱茵科技有限公司 | 双光路远程激光雕刻切割加工维修综合实训装置 |
KR102008871B1 (ko) * | 2018-12-06 | 2019-10-21 | (주)하나기술 | 진공롤링부를 구비하는 이차전지 전극 노칭시스템 |
KR102181983B1 (ko) * | 2019-08-13 | 2020-11-24 | (주)디이엔티 | 레이저 노칭 장치 |
CN213211381U (zh) * | 2020-09-25 | 2021-05-14 | 邢台职业技术学院 | 一种用于教学实验室的激光加工教学实训设备 |
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