Packaging simulation apparatus and method for producing secondary battery

Abstract

The present invention relates to a packaging simulation device for producing a secondary battery. The packaging simulation device for producing a secondary battery includes a memory configured to store at least one instruction, and at least one processor configured to execute the at least one instruction stored in the memory. The at least one instruction includes an instruction for performing a device action part including a 3D packaging associated with production of a secondary battery and a tool for confirming quality of a substance generated by the 3D packaging, and a device operation part including a plurality of adjustment parameters for determining an action of the 3D packaging; obtaining at least one of first user behavior information obtained through the device action part and first user condition information obtained through the device operation part; determining at least one action of a raw material inspection, a 3D packaging operation, and an autonomous inspection based on at least one of the obtained first user behavior information and the first user condition information; and executing the determined action.

Description

Technical Field

[0001] This invention relates to a packaging simulation apparatus and method for producing secondary batteries, and more specifically, to a packaging simulation apparatus and method for training secondary battery production operators. Background Technology

[0002] Recently, with the growth of the electric vehicle market, the demand for the development and production of secondary batteries has increased dramatically. To meet this increased demand, the number of manufacturing plants for secondary batteries has also increased. However, there is a significant shortage of skilled operators to operate these secondary battery manufacturing plants.

[0003] On the other hand, in the past, training and education for newly hired operators was typically conducted through a learn-by-doing approach, having them observe and learn from experienced operators. However, the busy production schedule for secondary batteries makes it impossible to provide extended training and education for new operators. Furthermore, frequent operator turnover makes it difficult to ensure a sufficient number of skilled operators. Moreover, even with training, operators cannot immediately handle the various types of adverse situations that may occur during factory startup, even with standard factory operating methods. Summary of the Invention

[0004] The technical problem to be solved by the present invention

[0005] The present invention provides a packaging simulation apparatus (system), method for producing secondary batteries, a computer program stored in a computer-readable medium, and a computer-readable medium storing the computer program for solving the problems described above.

[0006] Technical solution

[0007] The present invention can be implemented in a variety of ways, including apparatus (system), method, computer program stored in a computer-readable medium or computer-readable medium storing a computer program.

[0008] An embodiment of the present invention provides a packaging simulation apparatus for producing secondary batteries, comprising: a memory configured to store at least one instruction; and at least one processor configured to execute the at least one instruction stored in the memory. The at least one instruction includes instructions for: executing a device action unit comprising tools for 3D packaging associated with the production of secondary batteries and for verifying the quality of materials generated by 3D packaging; and a device operation unit comprising a plurality of adjustment parameters for determining the action of 3D packaging; obtaining at least one of first user behavior information obtained by the device action unit and first user condition information obtained by the device operation unit; determining at least one action among raw material inspection, 3D packaging operation, and autonomous inspection based on at least one of the obtained first user behavior information and first user condition information; and executing the determined action.

[0009] According to one embodiment of the present invention, at least one instruction further includes instructions for inspecting at least one of the leads, aluminum bags, and insulating tape.

[0010] According to one embodiment of the present invention, at least one instruction further includes instructions for performing at least one of tab welding, aluminum forming, cell assembly, electrolyte filling, and V-sealing.

[0011] According to one embodiment of the present invention, at least one instruction further includes instructions for checking at least one of the following: weld tensile strength, tab condition, tab position, lead film protrusion position, lead center, sealing position, sealing thickness, platform width, and cup sealing gap.

[0012] According to one embodiment of the present invention, at least one instruction further includes instructions for: determining one or more quality parameters for determining the quality of the material generated by 3D packaging; calculating, based on the performed 3D packaging operation, values ​​corresponding to the determined one or more quality parameters based on the performed 3D packaging operation; and outputting quality information associated with the quality of the material generated by 3D packaging based on the calculated values ​​corresponding to the one or more quality parameters.

[0013] According to one embodiment of the present invention, at least one instruction further includes instructions for: determining one or more defective scenarios among a plurality of defective scenarios associated with the quality of the material generated by 3D packaging; and modifying at least one of the 3D packaging operation and quality information associated with the quality of the material based on the determined one or more defective scenarios.

[0014] According to an embodiment of the present invention, the defective scenarios include at least one of the following: a sealing groove defective scenario in which the position of the x-axis groove of the material deviates from the boundary of a preset specification; a first sealing thickness defective scenario in which the sealing thickness of at least one of the plurality of measurement points of the material deviates from the upper or lower limit of the preset specification and the deviation of the sealing thickness between the plurality of measurement points is below a preset reference value; and a second sealing thickness defective scenario in which the sealing thickness of at least one of the plurality of measurement points of the material deviates from the upper or lower limit of the preset specification and the deviation of the sealing thickness between the plurality of measurement points exceeds a preset reference value.

[0015] According to one embodiment of the present invention, at least one instruction further includes instructions for: executing at least one of a sealing groove defect scenario, a first sealing thickness defect scenario, and a second sealing thickness defect scenario; obtaining at least one of second user behavior information of touching or dragging at least a portion of the 3D package and second user condition information of changing the adjustment parameters of the device operating unit; correcting the 3D package based on at least one of the obtained second user behavior information and second user condition information; calculating values ​​corresponding to one or more quality parameters associated with and the quality of the material generated by the corrected 3D package; and correcting quality information associated with the quality of the material generated by the corrected 3D package based on the calculated values ​​corresponding to the one or more quality parameters.

[0016] According to one embodiment of the present invention, at least one instruction further includes instructions for: obtaining third user behavior information corresponding to touching or dragging at least a portion of a region corresponding to quality confirmation of a material produced by 3D packaging; and outputting the cause of the material's defect based on the third user behavior information.

[0017] According to one embodiment of the present invention, at least one instruction further includes instructions for outputting guidance information including conditional information and behavioral information required to resolve one or more adverse scenarios.

[0018] According to an embodiment of the present invention, a packaging simulation method for producing secondary batteries is provided. The method is executed by at least one processor. The method includes: executing a device action unit comprising tools for verifying the quality of materials generated by 3D packaging and 3D packaging associated with the production of secondary batteries, and a device operation unit comprising a plurality of adjustment parameters for determining the operation of 3D packaging; obtaining at least one of first user behavior information obtained by the device action unit and first user condition information obtained by the device operation unit; determining at least one of raw material inspection, 3D packaging operation, and autonomous inspection based on at least one of the obtained first user behavior information and first user condition information; and executing the determined operation.

[0019] According to one embodiment of the present invention, when the determined action is raw material inspection, the steps for performing the determined action include: inspecting at least one of the lead wire, aluminum bag, and insulating tape.

[0020] According to an embodiment of the present invention, when the determined action is 3D packaging operation, the steps of performing the determined action include: performing at least one of the following steps: tab welding, aluminum forming, cell assembly, electrolyte filling, and V-sealing.

[0021] According to an embodiment of the present invention, when the determined action is an autonomous inspection, the steps of performing the determined action include: checking at least one of the following: welding tensile strength, tab condition, tab position, lead film protrusion position, lead center, sealing position, sealing thickness, platform width, and cup sealing gap.

[0022] According to one embodiment of the present invention, the method further includes: determining one or more quality parameters for determining the quality of the material generated by 3D packaging; calculating, based on the performed 3D packaging operation, values ​​corresponding to the determined one or more quality parameters during the 3D packaging operation; and outputting quality information associated with the quality of the material generated by 3D packaging based on the calculated values ​​corresponding to the one or more quality parameters.

[0023] According to one embodiment of the present invention, the method further includes: determining one or more defective scenarios among a plurality of defective scenarios associated with the quality of the material generated by 3D packaging; and modifying at least one of the 3D packaging operation and quality information associated with the quality of the material based on the determined one or more defective scenarios.

[0024] According to an embodiment of the present invention, the defective scenarios include at least one of the following: a sealing groove defective scenario in which the position of the x-axis groove of the material deviates from the boundary of a preset specification; a first sealing thickness defective scenario in which the sealing thickness of at least one of the plurality of measurement points of the material deviates from the upper or lower limit of the preset specification and the deviation of the sealing thickness between the plurality of measurement points is below a preset reference value; and a second sealing thickness defective scenario in which the sealing thickness of at least one of the plurality of measurement points of the material deviates from the upper or lower limit of the preset specification and the deviation of the sealing thickness between the plurality of measurement points exceeds a preset reference value.

[0025] According to one embodiment of the present invention, the method further includes: the steps of executing at least one of a sealing groove defect scenario, a first sealing thickness defect scenario, and a second sealing thickness defect scenario; obtaining at least one of second user behavior information for touching or dragging at least a portion of the 3D package and second user condition information for changing adjustment parameters of the device operating unit; correcting the 3D package based on at least one of the obtained second user behavior information and second user condition information; calculating values ​​corresponding to one or more quality parameters associated with the quality of the material generated by the corrected 3D package; and correcting the quality information associated with the quality of the material generated by the corrected 3D package based on the calculated values ​​corresponding to one or more quality parameters.

[0026] According to an embodiment of the present invention, after executing at least one of the following defect scenarios: a sealing groove defect scenario, a first sealing thickness defect scenario, and a second sealing thickness defect scenario, the method further includes: obtaining third user behavior information corresponding to at least a portion of the area touched or dragged by the material produced by 3D packaging for quality confirmation; and outputting the cause of the material's defect based on the third user behavior information.

[0027] According to one embodiment of the present invention, the method further includes the step of outputting guidance information that includes conditional information and behavioral information required to resolve one or more adverse scenarios.

[0028] The present invention provides a computer program stored in a computer-readable medium, the computer program being used to perform the method described in an embodiment of the present invention in a computer.

[0029] Beneficial effects

[0030] In various embodiments of the present invention, users performing secondary battery production can undergo training related to the operation of the secondary battery production equipment and the response methods when malfunctions occur through a simulation device before engaging in business. By training users in this way, losses caused by malfunctions can be significantly reduced, thereby effectively improving the efficiency of secondary battery production operations.

[0031] In various embodiments of the present invention, adverse scenarios are generated based on error information in the actual device, thereby enabling the simulation device to effectively generate training content optimized for the actual working environment.

[0032] In various embodiments of the present invention, the simulation device can generate adverse scenarios with a variety of values ​​associated with malfunctions in a secondary battery production device and provide them to the user, thereby enabling the user not only to resolve malfunctions that may occur in the actual device, but also to effectively learn the corresponding solutions for each situation.

[0033] In various embodiments of the present invention, users can easily learn the operation method of a secondary battery production device by performing simulations in different steps according to their operational proficiency.

[0034] In various embodiments of the present invention, users can easily identify and address poorly trained scenarios, thereby enabling focused training only on poorly trained scenarios with low proficiency.

[0035] In various embodiments of the present invention, users can train using adverse scenarios generated based on erroneous operations that occur in real-world work environments, thereby effectively improving their ability to respond to adverse situations.

[0036] The effects of the present invention are not limited to those mentioned above. Those skilled in the art to which this invention pertains ("Skilled Persons") can clearly understand other effects not mentioned from the description of the claims. Attached Figure Description

[0037] Embodiments of the present invention will be described with reference to the accompanying drawings, wherein similar reference numerals denote similar elements, but are not limited thereto.

[0038] Figure 1 This is a diagram illustrating an example of a user using a simulation device according to an embodiment of the present invention.

[0039] Figure 2 This is a block diagram illustrating the internal configuration of a simulation device according to an embodiment of the present invention.

[0040] Figure 3 This is a block diagram illustrating an example of the operation of a simulation device according to an embodiment of the present invention.

[0041] Figure 4 This is a diagram illustrating an example of a display screen shown or output by the device's operating section according to an embodiment of the present invention.

[0042] Figure 5 This is a diagram illustrating an example of a display screen shown or output by the device's operating section according to another embodiment of the present invention.

[0043] Figure 6 This is an example of a display screen shown or output by the device's operating section according to another embodiment of the present invention.

[0044] Figure 7 This is an example diagram illustrating the sealing position of a battery cell in a scenario where a sealing groove malfunction occurs, according to an embodiment of the present invention.

[0045] Figure 8This is a diagram illustrating an example of a sealing unit in a scenario where a sealing groove malfunctions according to an embodiment of the present invention.

[0046] Figure 9 This is a diagram illustrating an example of a scenario where the sealing thickness is poor and the deviation is below the reference value, according to an embodiment of the present invention.

[0047] Figure 10 This is a diagram illustrating an example of a scenario where the sealing thickness deviates beyond a reference value according to an embodiment of the present invention.

[0048] Figure 11 This is a diagram illustrating an example of generating a defective scene according to an embodiment of the present invention.

[0049] Figure 12 This is a diagram illustrating an embodiment of the present invention, showing the generation of operational capability information and test results.

[0050] Figure 13 This is a diagram illustrating an example of a simulation method for producing secondary batteries according to an embodiment of the present invention.

[0051] Figure 14 This is a diagram illustrating an example of a packaging simulation method for producing secondary batteries according to an embodiment of the present invention.

[0052] Figure 15 This is a diagram illustrating an example of a test result calculation method according to an embodiment of the present invention.

[0053] Figure 16 This is an illustration of an embodiment of the method for generating undesirable scenes according to the present invention.

[0054] Figure 17 An exemplary computing device is shown for performing the methods and / or embodiments described above.

[0055] Explanation of reference numerals in the attached figures

[0056] 100: Simulation device

[0057] 110: User

[0058] 120: Equipment Operation Department

[0059] 130: Device Action Section Detailed Implementation

[0060] Hereinafter, specific embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, if there is any concern that the following description may unnecessarily obscure the essence of the present invention, specific descriptions of known functions or configurations will be omitted.

[0061] In the accompanying drawings, the same or corresponding constituent elements are given the same reference numerals. Furthermore, in the following description of embodiments, repeated descriptions of the same or corresponding constituent elements may be omitted. However, even if the description of a constituent element is omitted, it does not mean that such a constituent element is not included in a particular embodiment.

[0062] The following detailed description of embodiments with reference to the accompanying drawings will make the advantages, features, and methods of achieving these advantages and features of the present invention more apparent. However, the present invention is not limited to the embodiments disclosed below and can be implemented in a variety of different ways. These embodiments are only intended to enable those skilled in the art to fully understand the scope of the present invention.

[0063] The terminology used in this specification is briefly explained, and the disclosed embodiments are described in detail. The terminology used in this specification has been chosen as much as possible to reflect both its function in this invention and its widespread use; however, this may vary depending on the intent of those skilled in the art, precedents, or the emergence of new technologies. Furthermore, in certain cases, terms arbitrarily chosen by the applicant may be used, in which case their meanings will be described in detail in the relevant description section of the invention. Therefore, the terminology used in this invention is not simply the name of a term, but should be defined based on its meaning and its content within the overall scope of this invention.

[0064] In this specification, a singular expression includes a plural expression unless explicitly specified in the context. Conversely, a plural expression includes a singular expression unless explicitly specified in the context. Throughout the specification, when it is stated that a part includes a certain constituent element, this means that other constituent elements are included, and are not excluded, unless specifically stated otherwise.

[0065] In this invention, terms such as "comprising" or "including" may indicate the presence of features, steps, operations, elements and / or constituent elements, but do not exclude the addition of other functions, steps, operations, elements, constituent elements and / or combinations thereof.

[0066] In this invention, when referring to a specific constituent element being "combined," "linked," "associated," or "reacted" with any other constituent element, the specific constituent element may be directly combined, linked, and / or associated with or reacted with other constituent elements, but is not limited thereto. For example, there may be more than one intermediate constituent element between the specific constituent element and other constituent elements. Furthermore, in this invention, "and / or" may include a combination of each or at least a portion of each of the more than one listed items.

[0067] In this invention, terms such as "first" and "second" are used to distinguish specific constituent elements from other constituent elements, and the constituent elements are not limited by such terms. For example, a "first" constituent element can be used to refer to an element with the same or similar form as a "second" constituent element.

[0068] In this invention, a "secondary battery" can refer to a battery made using materials that can undergo repeated redox processes between current and matter. For example, to produce a secondary battery, processes such as mixing, coating, rolling, slitting, notching and drying, lamination, folding and stacking, encapsulation, charging and discharging, degassing, double-side folding / single-side folding, and characteristic testing (end of line) can be performed. In this case, separate production equipment (devices) can be used to perform each process. Each piece of production equipment can be operated by adjusting parameters and setting values ​​that are set or changed by the user.

[0069] In this invention, "user" can refer to an operator who performs the production of secondary batteries and runs the secondary battery production equipment, and may include users who are trained through a simulation device of the secondary battery production equipment. Furthermore, "user account" is an ID generated or assigned to each user in a manner that enables the use of such a simulation device. Users can log in to the simulation device using their user account and perform simulations, but are not limited to this.

[0070] In this invention, "equipment operation unit", "device operation unit" and "quality verification unit" are software programs included in the simulator device or displayed on the input / output device and / or input / output device associated with the simulator device. They can refer to devices and / or programs used to output images or videos of 3D model devices, or to receive various inputs from users and transmit them to the simulator device.

[0071] In this invention, the "3D model device" serves as a virtual device for realizing actual secondary battery production equipment. It can perform actions by executing, modifying, and / or correcting images, videos, animations, etc., of the virtual device based on user input information (e.g., user input information and / or user behavior information). That is, the "actions of the 3D model device" can include the images, videos, animations, etc., of the virtual device being executed, modified, and / or corrected. For example, the 3D model device can include devices for performing mixing, coating, rolling pressing, slitting, notching and drying, lamination, folding and stacking, encapsulation, charging and discharging, degassing, double-side folding / single-side folding, characteristic detection (end of line), etc. Alternatively or additionally, the 3D model device can be implemented as a 2D model device. In other words, in this invention, the 3D model device is not limited to a three-dimensional model but can include a two-dimensional model. Therefore, 3D model devices can include terms such as 2D model devices, animation model devices, and virtual model devices.

[0072] In this invention, "user condition information" can be user input including at least some conditions and / or values ​​for setting or changing adjustment parameters, or information generated based on the user input by any predetermined algorithm.

[0073] In this invention, "user behavior information" can be user input such as touch input, drag input, pinch input, rotation input, etc., performed in at least a portion of the 3D model device, or information generated by any predetermined algorithm based on the user input.

[0074] In this invention, a "defect scenario" can be a scenario that includes values, conditions, etc., used to change the operation of the 3D model device to a range of malfunction or to change the quality information of a substance determined by the operation of the 3D model device to a defective range. For example, if a defect scenario occurs during the operation of the simulation device, the operation and quality information of the 3D model device can be changed based on the defect scenario. Furthermore, if the operation and quality information of the 3D model device changed due to the defect scenario are corrected to the normal range, it can be determined that the defect scenario has been resolved.

[0075] In this invention, a "training scenario" can include scenarios for operating secondary battery production equipment. For example, when the secondary battery production equipment is a package, the training scenario can include raw material inspection training, equipment operation training, autonomous inspection training, equipment shutdown training, battery cell data deletion training, batch termination, and batch exchange training. Furthermore, the training scenario can include training on inspecting each component constituting the 3D model device and changing its state, as well as training on adjusting adjustment parameters. The training scenario can also include defective scenarios.

[0076] In this invention, the "mixing process" can be the process of mixing active materials, binders, and other additives with a solvent to prepare a slurry. For example, the user can determine or adjust the proportions of active materials, conductive materials, additives, binders, etc., to prepare a slurry of a specific quality. Furthermore, in this invention, the "coating process" can be the process of applying the slurry onto a foil in a predetermined amount and shape. For example, the user can determine or adjust the die, slurry temperature, etc., to perform coating with a specific quality in terms of amount and shape.

[0077] In this invention, the "rolling process" can be a process in which the electrode to be coated is passed between two rotating upper and lower rollers and pressed to a predetermined thickness. For example, the user can determine or adjust the spacing between the rollers to increase electrode density and maximize battery capacity through the rolling process. Furthermore, in this invention, the "cutting process" can be a process in which the electrode is passed between two rotating upper and lower blades to cut the electrode with a constant width. For example, the user can determine or adjust various adjustment parameters to maintain a constant electrode width.

[0078] In this invention, the "grooving and drying process" can be a process of removing moisture after punching the electrode into a predetermined shape. For example, the user can determine or adjust the cutting height, length, etc., to perform punching to achieve a specific quality shape. Furthermore, in this invention, the "lamination process" can be a process of sealing and cutting the separation membrane. For example, the user can determine or adjust the values ​​corresponding to the x-axis, the y-axis, etc., to perform cutting to achieve a specific quality.

[0079] In this invention, the "encapsulation process" can be the process of attaching leads and tape to the assembled battery cell and encapsulating it in an aluminum pouch. The battery cell, after the encapsulation process, will undergo a charging / discharging process, during which gas will be generated within the battery cell. The "degassing process" can be the process of resealing the battery cell by venting the gas generated within it during such a charging / discharging process to the outside. In this invention, the "double-sided folding" process can be the process of folding the aluminum pouch of the completed battery cell twice on both sides or one side, and the "single-sided folding" process can be the process of folding the aluminum pouch of the completed battery cell once on both sides or one side.

[0080] Furthermore, in this invention, the "characteristic testing process" can be a process that uses measuring instruments to determine the thickness, weight, width, length, insulation voltage, and other characteristics of a battery cell before it leaves the factory. In such a process, the user can adjust the conditions and values ​​of various adjustment parameters, or change the setting values ​​corresponding to the device, so that each process can be performed with specific quality within the normal range.

[0081] Figure 1 This diagram illustrates an example of a user 110 using a simulation device 100 according to an embodiment of the present invention. As shown, the simulation device 100, serving as a device for training secondary battery production operators (e.g., user 110), may include an equipment operation unit 120, a device actuation unit 130, etc. For example, user 110 can operate the simulation device 100, which virtually (e.g., 2D, 3D) simulates the actual secondary battery production equipment, to learn how to use the secondary battery production equipment, or to train for coping methods when problems with low product quality occur.

[0082] According to one embodiment, the device operation unit 120 may include multiple adjustment parameters used to determine the operation of the 3D model device displayed on the device operation unit 130. The user 110 can change at least some of the conditions in the adjustment parameters to execute, modify, and / or correct the operation of the 3D model device. That is, the operation of the 3D model device can be adaptively changed or corrected based on changes in the adjustment parameters input by the user 110.

[0083] The device actuation unit 130 may include a 3D model device associated with the production of secondary batteries. This 3D model device may include, but is not limited to, 3D models associated with mixing, coating, rolling, slitting, notching and drying, lamination, folding and stacking, encapsulation, charging and discharging, degassing, double-side folding / single-side folding, and characteristic testing devices used as production equipment for secondary batteries. It may also include 3D models of any other devices used for producing secondary batteries.

[0084] According to one embodiment, user 110 can operate the 3D model device (at least a portion of the 3D model device) included in the device action unit 130 by performing touch input, drag input, pinch input, etc., or change the configuration of the 3D model device. Furthermore, user 110 can select or zoom in / out of any area of ​​the 3D model device by switching views, etc., and operate the 3D model device or change its configuration by performing touch input, etc. While described as displaying a 3D model device associated with the production of secondary batteries on the device action unit 130, this is not a limitation; devices associated with specific processes can also be implemented as 2D model devices according to the secondary battery production process and displayed.

[0085] The device operation unit 130 may include a tool for verifying the quality of the substance generated by the 3D model device. After changing at least one of the multiple adjustment parameters of the device operation unit 120, the user can verify the quality of the substance from the device operation unit 130 and learn the changes in the quality of the substance based on the adjustments of each adjustment parameter.

[0086] At least one of the equipment operation unit 120 and the device action unit 130 may include quality information associated with the quality of the substance generated by the 3D model device. This quality information can be generated by performing calculations on quality parameters, etc., based on pre-determined benchmarks and / or algorithms. The user 110 can confirm the quality information of the substance generated in response to changes in adjustment parameters or operation of the 3D model device through at least one of the equipment operation unit 120 and the device action unit 130. Alternatively, depending on the secondary battery production process, a separate quality confirmation unit displaying the quality information of the substance may also be independently configured in a specific process.

[0087] According to one embodiment, quality information can be displayed in association with the 3D model device of the device operation unit 130, or confirmed by a specific action of the 3D model device, or additionally displayed on a portion of the screen of the 3D model device, or displayed as a change in the parameter setting value of the equipment operation unit 120. For example, when the button for confirming quality displayed on the device operation unit 130 is selected, quality information can be displayed or output in at least one of the device operation unit 130 and the equipment operation unit 120. In another example, quality information can be displayed or output through color changes or alarms in at least a portion of the 3D model device. In yet another example, if the operation of the 3D model device malfunctions or the quality of the material produced by the 3D model device is poor, the malfunction / poor quality area can be immediately displayed or output in the 3D model device. In yet another example, parameter values ​​associated with the quality of the material generated in the 3D model device can be displayed or output in the equipment operation unit 120. For example, in secondary battery production equipment, when the equipment is a sealing device, leads and tape are attached to the assembled battery cells, and then sealed in aluminum bags for packaging. At this point, the sealing position and thickness are crucial factors in determining the quality of the material. Factors affecting the sealing position include the location of the sealing unit, while factors affecting the sealing thickness include contamination of sealing tools, loose bolts, heating rod temperature (sealing temperature), sealing pressure, contact time, sealing blocks, and feeler gauges. When malfunctions or incorrect parameter input occur, defects in sealing position and thickness can be displayed or alarms can be output in at least one of the 3D model device and the equipment operation unit. Optionally, for more accurate quality confirmation, users can visually understand the location and cause of defects through the quality confirmation process of the 3D model device.

[0088] exist Figure 1 Although the simulation device 100 is shown as including a device operation unit 120 and a device action unit 130, it is not limited thereto. The number of the device operation unit 120 and the device action unit 130 can be determined according to the type of 3D model device associated with the simulation device 100, and any number of separate quality verification units may also be included. With the configuration described above, the user 110 who performs secondary battery production can undergo training related to the operation method of the secondary battery production equipment and the response method when defects occur through the simulation device 100 before starting business. By training the user 110 in this way, losses caused by defects can be significantly reduced, thereby effectively improving the efficiency of secondary battery production operations.

[0089] Figure 2This is a functional block diagram illustrating the internal configuration of a simulation device 100 according to an embodiment of the present invention. As shown, the simulation device 100 (e.g., at least one processor of the simulation device 100) may include a 3D model device action unit 210, a quality determination unit 220, a scene management unit 230, a test execution unit 240, a user management unit 250, etc., but is not limited thereto. The simulation device 100 can communicate with the device operation unit 120 and the device action unit 130, and send and receive data and / or information associated with the 3D model device.

[0090] The 3D model device action unit 210 can execute, modify, and / or correct the actions of the 3D model device displayed on the device action unit 130 based on user operations. Furthermore, it executes, modifies, and / or corrects the actions of the equipment operation unit 120 based on the execution, modification, and / or correction of the model device's actions. According to one embodiment, the 3D model device action unit 210 can obtain or receive user behavior information and / or user condition information using information input by a user (e.g., a secondary battery production operator). Then, the 3D model device action unit 210 can use the obtained or received user behavior information and / or user condition information to determine or modify the actions of the 3D model device.

[0091] According to one embodiment, user behavior information is generated based on user input, such as at least a portion of the 3D model device included in the touch and / or drag device action unit 130, and may include information related to changes in the set values ​​of the 3D model device based on user input. For example, when the 3D model device is a sealing device for producing secondary batteries, the user can touch or drag the entire sealing unit and its lower part to move it to its position, remove contaminants attached to the sealing tool by touching or dragging the sealing tool area, add or remove washers to adjust the height of the sealing tool stop by touching or dragging the sealing tool stop area, tighten or loosen bolts by touching or dragging the bolt area, insert or remove feeler gauges by touching or dragging the feeler gauge area, and zoom in or out of a specific area of ​​the 3D model device by touching or dragging it. In this case, user behavior information based on the sealing unit, sealing tool, sealing tool stop, bolt, feeler gauge, specific area, etc., can be generated.

[0092] According to one embodiment, the user condition information is generated based on user input that changes the conditions and / or values ​​of at least a portion of the multiple adjustment parameters included in the device operation unit 120. This information may include information related to the amount of change in the condition values ​​used to determine the operation of the 3D model device based on the user input. For example, when the 3D model device is a sealing device for producing secondary batteries, the user can change sealing temperature parameters, sealing pressure parameters, contact time parameters, etc., to specific values ​​through the device operation unit 120. In this case, user condition information based on the changed sealing temperature parameter value, sealing pressure parameter value, and contact time parameter value can be generated.

[0093] As described above, when the 3D modeling device is operated based on user condition information and / or user behavior information, the quality determination unit 220 can determine or generate quality information related to the quality of the substance generated by the operation of the 3D modeling device. That is, when the 3D modeling device is operating (in the case of executing animations, videos, etc., showing the operation of the 3D modeling device), quality information can be determined or generated in different ways based on the setting values, condition values, etc., of the 3D modeling device. In other words, the user can change or adjust the quality of the substance generated by the 3D modeling device by changing adjustment parameters or setting at least a portion of the 3D modeling device through touch input or other means.

[0094] According to one embodiment, the quality determination unit 220 can determine or extract one or more quality parameters for determining the quality of a substance generated by a 3D modeling device, and during the execution of the operation of the 3D modeling device, can calculate values ​​corresponding to each of the one or more quality parameters determined based on the executed operation of the 3D modeling device. The values ​​corresponding to the quality parameters can be calculated using any pre-determined algorithm. Furthermore, the quality determination unit 220 can generate quality information associated with the quality of the substance generated by the 3D modeling device based on the calculated values ​​corresponding to each of the one or more quality parameters. For example, when the 3D modeling device is a sealing device for producing secondary batteries, if the user adjusts the sealing temperature parameter, sealing pressure parameter, and / or contact time parameter, a value corresponding to the sealing thickness can be calculated. In this case, the quality determination unit 220 can generate or output quality information including the calculated sealing thickness.

[0095] According to one embodiment, during or before the operation of the 3D modeling device, an undesirable scenario associated with the malfunction of the 3D modeling device may occur. As described above, in the event of an undesirable scenario, at least a portion of the setting values, condition values, and corresponding quality information of the 3D modeling device may change to an abnormal range based on the undesirable scenario.

[0096] According to one embodiment, the scene management unit 230 can determine one or more defective scenarios from multiple defective scenarios associated with malfunctions of the 3D model device and multiple defective scenarios associated with the quality of the material, and modify at least one of the actions of the 3D model device and the quality information associated with the quality of the material based on the determined defective scenario. For example, when the 3D model device is a sealed encapsulated device, the multiple defective scenarios may include sealing groove defects, sealing thickness defects, etc. Sealing thickness defects may include sealing thickness defects with deviations below a reference value, sealing thickness defects with deviations exceeding a reference value, etc., and the causes of such defects may vary. In this case, the scene management unit 230 can extract at least one of the sealing groove defect scenario and the sealing thickness defect scenario to determine the defective scenario, and modify the adjustment parameters, actions, quality information, etc. of the 3D model device based on the determined defective scenario.

[0097] According to one embodiment, in the event of an adverse scenario, the user can change or adjust parameters or switch the settings of the 3D model device to resolve the adverse scenario. In this case, the scenario management unit 230 can receive at least one of user behavior information and user condition information for resolving one or more determined adverse scenarios, and correct the changed operation of the 3D model device based on at least one of the received user behavior information and user condition information. Furthermore, during the execution of the corrected operation of the 3D model device, the scenario management unit 230 can calculate values ​​corresponding to multiple quality parameters associated with the quality of the substance generated by the 3D model device based on the executed operation of the 3D model device, and correct the quality information associated with the quality of the substance generated by the corrected 3D model device based on the calculated values ​​corresponding to the multiple quality parameters.

[0098] Then, the scenario management unit 230 can use the corrected quality information to determine whether one or more defective scenarios have been resolved. For example, if the quality of the material is within the normal range of a predetermined specification, the scenario management unit 230 can determine that the defective scenario has been resolved. However, it is not limited to this; if the values ​​of each quality parameter included in the quality information correspond to the normal range or specific values ​​of the predetermined specification, the scenario management unit 230 can determine that the defective scenario has been resolved. Additionally or alternatively, if the values ​​obtained by providing each quality parameter to any algorithm are within the predetermined normal range, the scenario management unit 230 can also determine that the defective scenario has been resolved.

[0099] According to one embodiment, the setting values ​​and condition values ​​of the 3D model device, which are changed from a defective scenario to a misoperation range, can be determined in advance according to different defective scenarios, but are not limited to this. For example, a defective scenario can be generated based on error information generated when a misoperation occurs in actual secondary battery production equipment. That is, when a misoperation occurs in an external device (e.g., actual secondary battery production equipment) associated with the 3D model device, the scenario management unit 230 can obtain error information associated with the misoperation and generate a defective scenario associated with the misoperation of the 3D model device based on the obtained error information. For example, when a misoperation occurs in the folding and stacking, layering and stacking processes, which are pre-packaging processes, the scenario management unit 230 can obtain the values ​​of each adjustment parameter and the device setting value at the time of the misoperation as error information. The scenario management unit 230 can change the values ​​of each adjustment parameter and the device setting value obtained from the external device in this way to correspond to the 3D model device, thereby generating a defective scenario. With this configuration, by generating adverse scenarios based on error information from the actual device, the simulation device 100 can effectively generate training content optimized for the working environment.

[0100] According to one embodiment, the test execution unit 240 can use corrected quality information to determine whether one or more defective scenarios have been resolved. If one or more defective scenarios are resolved, the test execution unit 240 can calculate the processing time, loss value, etc., of one or more defective scenarios during their processing. For example, the loss value may include material loss value, etc., and is calculated using a pre-determined arbitrary algorithm based on the user's response time, user input value, etc. Furthermore, the test execution unit 240 can generate operational capability information for the 3D model device for a user account based on the calculated processing time and loss value. Here, the user account may refer to the account of the operator using the simulation device 100, and the operational capability information, as information representing the user's work proficiency, may include work speed, target value proximity, evaluation score, etc. Moreover, if the user resolves all pre-determined types of defective scenarios, the test execution unit 240 can determine whether the user's simulation training has passed based on the operational capability information for each defective scenario.

[0101] User management unit 250 can perform management tasks such as logging in, modifying, and deleting user accounts associated with users utilizing simulation device 100. According to one embodiment, a user can use their logged-in user account to use simulation device 100. In this case, user management unit 250 can store and manage information such as the resolution status of each defective scenario for each user account and the corresponding operational capabilities for each defective scenario in any database. Using the information stored by user management unit 250, scenario management unit 230 can extract information associated with a specific user account stored in the database and extract or determine at least one scenario from a plurality of defective scenarios based on the extracted information. For example, scenario management unit 230 can extract only defective scenarios where the operation speed is lower than the average operation speed based on information associated with the user account, and cause them to occur or provide them to the user, but it is not limited to this; defective scenarios can also be extracted or determined using any other arbitrary criteria or any combination of criteria.

[0102] exist Figure 2 Although the various functional configurations included in the analog device 100 are described in a differentiated manner, this is only to aid in understanding the invention; more than two functions can also be executed in a single computing device. Furthermore, in Figure 2Although the simulation device 100 is shown separately from the equipment operation unit 120 and the device actuation unit 130, this is not a limitation; the equipment operation unit 120 and the device actuation unit 130 may be included in the simulation device 100. With the configuration described above, the simulation device 100 can generate and provide users with adverse scenarios having various values ​​associated with malfunctions in secondary battery production equipment. This allows users not only to resolve potential malfunctions that may occur in actual equipment but also to effectively learn corresponding solutions for each scenario.

[0103] Figure 3 This is a block diagram illustrating an example of the operation of a simulation device 100 according to an embodiment of the present invention. As shown in the figure, the simulation device ( Figure 1 The steps 100 in the diagram can be performed through a Human-Machine Interface (HMI) guided process, including steps 310, 320, 330, 340, 350, and 360. In other words, users can train themselves on how to operate the secondary battery production equipment through steps 310, 320, 330, 340, 350, and 360. For novice users, a level test step can be added and performed before the HMI guided step 310 to assess the operational capabilities before simulation learning.

[0104] HMI guidance step 310 can be a step to learn the various types of adjustment parameters included in the equipment operation section, and the operation methods for these adjustment parameters. For example, work instructions and / or guidance information indicating the type of adjustment parameter and the operation method for the adjustment parameter can be displayed or output in the equipment operation section, device action section, etc. Furthermore, a portion of the screen can be illuminated or activated so that the user can perform operations corresponding to the work instructions and / or guidance information. In this case, the user can operate any adjustment parameter condition and / or value corresponding to the work instructions and / or guidance information to train the user on how to use the equipment operation section. If the user touches any button or inputs the correct value corresponding to any parameter within a pre-specified time according to the operation and work instructions and / or guidance information, the next step can be performed, or a button that enables the next step (e.g., the NEXT button) can be displayed or activated.

[0105] Process and equipment guidance step 320 can be a step that describes the secondary battery production process or equipment. When the 3D model device is a packaging device, process and equipment guidance step 320 can include descriptions of the loading process, tab welding process, aluminum bag forming process, cell assembly process, electrolyte filling process, V-sealing process, and unloading process.

[0106] Equipment operation step 330 can be a step for training the 3D model device's drive. When the 3D model device is a packaging device, equipment operation step 330 can be a step that executes at least one of the following: raw material inspection step, 3D packaging operation step, autonomous inspection step, equipment stop step, battery cell data deletion step, and batch termination / batch exchange step. In the raw material inspection step, operations such as inspecting packaging materials such as leads, aluminum pouches, and insulating tape can be performed. In the 3D packaging operation step, the 3D model device can be run to train operations such as loading, tab welding, aluminum pouch forming, battery cell assembly, electrolyte filling, V-sealing, and unloading. The autonomous inspection step is an operation to confirm the quality of the material produced by the 3D model device. After the tabs are welded, the welding tensile strength, tab condition, and tab position are checked. After filling the electrolyte and sealing the device, the lead film protrusion, lead center, sealing position, sealing thickness, platform width, and cup sealing gap are checked.

[0107] In equipment operation step 330, the raw material inspection step can provide guidance information to the device action unit 130 to inspect raw materials such as leads, aluminum bags, and insulating tape, and confirm whether the user has inspected the leads, aluminum bags, and insulating tape by obtaining user behavior information. In equipment operation step 330, the 3D packaging operation step can provide guidance information to the device action unit 130 to perform a series of operations such as loading, tab welding, aluminum bag forming, cell assembly, electrolyte filling, V-sealing, and unloading, and confirm whether the corresponding operation has been performed by obtaining at least one of user behavior information and user condition information. Furthermore, in the equipment operation step 330, the autonomous inspection step can provide guidance information to the device action unit 130 to confirm the quality of weld tensile strength, tab condition, tab position, lead film protrusion position, lead center, sealing position, sealing thickness, platform width, cup sealing gap, etc., and confirm whether the user has checked the steps of weld tensile strength, tab condition, tab position, lead film protrusion position, lead center, sealing position, sealing thickness, platform width, cup sealing gap, etc. by obtaining at least one of user condition information and user behavior information.

[0108] Condition adjustment step 340 can be a step for learning the quality changes of a substance generated by a 3D model device corresponding to the values ​​of adjustment parameters of the equipment operation unit and the state of the device action unit. In the autonomous inspection step of equipment operation step 330, the quality of the substance is confirmed, and in condition adjustment step 340, the adjustment parameter values ​​are adjusted or the mechanism of the 3D model device is inspected and calibrated. Afterwards, training can be performed to repeatedly execute a portion of the equipment operation steps. For example, condition adjustment step 340 can be a step for learning the position adjustment of a sealing unit that determines the sealing groove position of the substance in relation to the sealing operation. Furthermore, it can be a step for learning to clean the sealing tool used to determine the sealing thickness of the substance, check for bolt looseness, check and adjust the heating rod temperature (sealing temperature), adjust the sealing pressure, adjust the contact time, adjust the height of the sealing tool stop, insert / remove feeler gauges, etc. In condition adjustment step 340, during each learning period, guidance information is displayed on the screen of the device action unit, and a portion of the screen of the equipment operation unit and / or the device action unit can be illuminated or activated. In this case, the user can learn how to input or operate the settings of the equipment operation unit and / or the 3D model device corresponding to the guidance information. After a user performs an operation, a button that allows them to proceed to the next step (e.g., the NEXT button) is displayed or activated. Furthermore, in condition adjustment step 340, after adjusting and inputting the settings of the device operation unit, or adjusting and correcting the mechanism of the device actuation unit, the system returns to device operation step 330 to run the device again. A quality reconfirmation check, similar to the autonomous check, can be performed to confirm the results of this re-run.

[0109] Example training step 350 can be a step for the user to learn methods such as identifying defects that occur during the operation of the secondary battery production equipment and taking measures to address them. For example, in the case of sealing operations, defects in the sealing groove and defects in the sealing thickness may occur, and the causes of each defect may be different. That is, even for the same defect in sealing thickness, the corresponding defect solutions may differ depending on the cause. In example training step 350, when a defect occurs, the type of adjustment parameter, the adjustment parameter value, the setting value of the 3D model device, and the mechanical measures of the 3D model device that need to be taken to resolve the defect can be displayed or output. The user can handle the defect based on the information displayed in this way and train the defect solution method.

[0110] The example training step 350 allows users to repeatedly process or resolve multiple defect scenarios or combinations thereof associated with the secondary battery production device to familiarize themselves with defect resolution procedures. For example, a user can directly select one defect scenario from multiple scenarios for training, but is not limited to this; they can also train on defect scenarios arbitrarily determined by the simulator device. In this case, the example training step 350 can display or output guidance information including conditional and behavioral information required to resolve each defect corresponding to the defect scenario. Specifically, when the user operates specific adjustment parameters or changes the settings of the 3D model device, or operates the 3D model device, the actions of the 3D model device and the quality of the materials associated with the 3D model device can be changed in real time. The quality changes in this manner can be confirmed, and the user can resolve defects and improve their proficiency in handling defects through repeated training.

[0111] Test step 360 can be a step to evaluate a user's operational ability by testing their process of solving adverse scenarios. For example, when a user solves various adverse scenarios, their operational ability can be measured or evaluated based on factors such as the time taken to complete each scenario and the resulting loss. Users can then further learn or train on areas where their operational ability is lacking by confirming these performance indicators and by determining whether the test passed or failed. Furthermore, in test step 360, the user's proficiency level can be further assessed by comparing their performance with an assessment score prior to simulated learning, measured in a previous level-testing step.

[0112] Although Figure 3 The diagram illustrates the sequential execution of each step, but is not limited to this; some steps may be omitted. Furthermore, the order of the steps can be changed or repeated. For example, the instance training step 350 can be re-executed after test step 360. With the configuration described above, users can easily learn the operation of a secondary battery production device through simulations performed step-by-step according to their skill level.

[0113] Figure 4 This diagram illustrates an example of a display screen displayed or output by the device action unit 130 according to an embodiment of the present invention. As shown, the device action unit 130 can display or output text, images, videos, etc., including a small map 410, a 3D model device 420, a user guide 430, and a NEXT button 440, on the display screen. Figure 4 Although the small map 410, 3D model device 420, user guide 430, NEXT button 440 and other elements are displayed in specific areas on the display screen, they are not limited to this. Text, images, videos and any area that can be displayed on the display screen can also be displayed over each other.

[0114] The minimap 410 roughly displays the entire packaging assembly used for producing secondary batteries, and uses rectangles to indicate the approximate locations of areas within the packaging assembly displayed on the 3D model device 420. If the components displayed on the 3D model device 420 change, the position and size of the rectangles displayed on the minimap 410 can also be changed in real time. For example, the minimap 410 can function as a location guide for the packaging assembly.

[0115] The 3D modeling device 420 can realize three-dimensional images and videos of secondary battery production equipment in 3D form. The 3D modeling device 420 can operate based on user-inputted condition information and / or user behavior information.

[0116] User guidance 430 includes information needed to operate the 3D model device 420, conditional information required to resolve adverse scenarios, and behavioral information, which can serve as information to guide the user's next action. That is, the user can use user guidance 430 to train the user on how to operate the simulation device and how to deal with adverse scenarios, even if they are not familiar with how the simulation device operates.

[0117] When the user guide 430, displayed in this manner, is used to determine the condition values, settings, etc. of the 3D model device, or to run the 3D model device 420, this step is completed, and the NEXT button 440 for proceeding to the next step can be activated. The user can select the activated NEXT button 440 by touch input or the like, and perform training corresponding to the next step.

[0118] Although not illustrated, the device operation unit 130 can also display a document, i.e., a work instruction, including the initial settings and condition values ​​of the 3D model device 420. The work instruction can be predetermined or generated by any algorithm. For example, the simulation device can receive and provide the content of a work instruction used to operate actual secondary battery production equipment, or it can calculate the initial settings and condition values ​​of the 3D model device 420 based on multiple input work instructions, thereby generating a new work instruction. The 3D model device 420 can be a three-dimensional image or video representation of the secondary battery production equipment. The device operation unit 130 can also display self-inspection and quality confirmation results in a pop-up format, and can further display a set of tools (e.g., a wiping cloth for cleaning sealing tools) for operating the 3D model device as needed.

[0119] Figure 5This diagram illustrates an example of a display screen displayed or output by the device operation unit 130 according to another embodiment of the present invention. As shown, the device operation unit 130 can display or output text, images, videos, etc., including multiple adverse scenes 510, 520, 530, etc., on the display screen. Figure 5 Although the first defective scene 510, the second defective scene 520, the third defective scene 530, etc. are shown in specific areas on the display screen, they are not limited to this. Text, images, videos, etc. can be displayed in any area of ​​the display screen.

[0120] According to one embodiment, each defect scenario can include the content and difficulty level of the defect scenario. For example, the first defect scenario 510 can be a sealing groove defect with a difficulty level of "low"; the second defect scenario 520 can be a sealing thickness defect with a difficulty level of "medium" and a deviation below the reference value; and the third defect scenario 530 can be a sealing thickness defect with a difficulty level of "high" and a deviation exceeding the reference value. Users can select at least a portion of the multiple defect scenarios 510, 520, and 530 displayed on the screen using touch input or other methods, and perform training on the selected defect scenarios.

[0121] Alternatively or additionally, one of the multiple defective scenarios 510, 520, and 530 can be determined using a pre-specified algorithm. For example, the simulation device can determine defective scenarios or combinations of defective scenarios indicating low proficiency based on the user's account (or information associated with the user account) during training. The user's proficiency can be calculated or determined by the test results for each different defective scenario, but is not limited to this. With this configuration, the user can easily identify and address undertrained defective scenarios, allowing for focused training only on defective scenarios indicating low proficiency.

[0122] Figure 6This is an example of a display screen displayed or output by the device operation unit 130 according to another embodiment of the present invention. As shown, the device operation unit 130 can display or output on the display screen information 611 for confirming a defective sealing position associated with the sealing position, text guidance information 612 in text form including condition information and behavior information required to resolve the defective sealing position associated with the confirmed defect, and image guidance information 613 in image form including condition information and behavior information required to resolve the defective sealing position associated with the confirmed defect. Furthermore, the device operation unit 130 can display or output on the display screen information 631 for confirming a defective sealing thickness associated with the sealing thickness, text guidance information 632 in text form including condition information and behavior information required to resolve the defective sealing thickness associated with the confirmed defect, and image guidance information 633 in image form including condition information and behavior information required to resolve the defective sealing thickness associated with the confirmed defect. Furthermore, the device action unit 130 can display or output the encapsulation and sealing model 620, which virtually realizes the encapsulation and sealing device actually used for the production of secondary batteries, on the display screen, and can display or output the position condition adjustment image guide 613 and the thickness condition adjustment image guide 633 in association with the encapsulation and sealing model 620.

[0123] According to one embodiment, the sealing position quality confirmation result can be output as good / bad based on whether it is defective for different reasons. When the sealing position quality confirmation result is bad, text guidance information 612 and image guidance information 613 for adjusting the position conditions can be output. Furthermore, the sealing thickness quality confirmation result can be output as good / bad based on whether it is defective for different reasons. When the sealing thickness quality confirmation result is bad, the cause of the sealing thickness defect and text guidance information 631 and image guidance information 633 for adjusting the thickness conditions to resolve the defect can be output.

[0124] Figure 7 This is a diagram illustrating the sealing position of a battery cell in a scenario where a sealing groove malfunction occurs, according to an embodiment of the present invention. Figure 8 This is a diagram illustrating an example of a sealing unit in a scenario where a sealing groove malfunctions according to an embodiment of the present invention.

[0125] Simulation device ( Figure 1The method (100) identifies one or more defective scenarios among multiple defective scenarios associated with malfunctions in 3D packaging, and modifies at least one of the 3D packaging actions and quality information associated with the material's quality based on the identified defective scenario. These multiple defective scenarios may include sealing groove defective scenarios. For example, a sealing groove defective scenario may refer to a scenario where the x-axis sealing position 710 of the material deviates from the outer or inner boundary of a preset specification. That is, a sealing groove defective scenario may refer to a scenario where the lower sealing unit of the sealing unit deviates from the preset groove boundary 810.

[0126] According to one embodiment, when one or more defective scenarios include a sealing groove defective scenario, the simulation device can change an image, video, or animation representing the sealing position of a substance generated by 3D encapsulation included in the device action unit 130, such as points, lines, or surfaces, to a predetermined area.

[0127] When a sealing groove defect occurs, the device actuation unit 130 generates an alarm and guides the user to confirm the quality and adjust the position of the lower sealing unit. The user can touch or drag a specific area of ​​the 3D package displayed on the device actuation unit 130 to address the sealing groove defect. In other words, the simulation device receives user behavior information about touching or dragging at least a portion of the area corresponding to the quality confirmation of the 3D package and understands the cause of the defect. It also receives user behavior information about touching or dragging at least a portion of the area corresponding to the lower sealing unit and changes the position of the lower sealing unit, thereby correcting the defective material back to normal.

[0128] Then, the simulation device can determine whether the sealing groove defect scenario has been resolved based on at least a portion of the calibrated material. For example, when user behavior information is generated based on touch input, drag input, etc., to a predetermined area in a predetermined sequence, the simulation device can determine that the sealing groove defect scenario has been resolved. Furthermore, when user condition information changes to a predetermined value, the simulation device can determine that the sealing groove defect scenario has been resolved. When the defect scenario is determined to be resolved, a predetermined area representing the sealing groove defect can be removed from the image, video, and / or animation of the 3D package or material, and the corresponding material quality parameters displayed on the device's actuation unit 130 can be corrected and changed to normal.

[0129] Figure 9 This is a diagram illustrating an example of a scenario where a sealing thickness defect occurs, with a deviation below a reference value, according to an embodiment of the present invention. Simulation device ( Figure 1The device (100) identifies one or more defective scenarios associated with malfunctions in 3D packaging and modifies at least one of the following based on the identified defective scenario: the operation of the 3D packaging and quality information associated with the quality of the material. The multiple defective scenarios may include sealing thickness defects where the deviation is below a reference value. For example, a sealing thickness defective scenario where the deviation is below a reference value may refer to a scenario where the sealing thickness of at least one of multiple thickness measurement points 910, 920, and 930 of the material deviates from the upper or lower limit of a preset specification, and the deviation of the sealing thickness between the measurement points is below a preset reference value. According to one embodiment, when one or more identified defective scenarios include sealing thickness defects where the deviation is below a reference value, the simulation device can change images, videos, or animations representing the sealing thickness of the material generated by the 3D packaging included in the device operation unit 130, such as points, lines, or surfaces, to a predetermined area.

[0130] When a sealing thickness defect occurs with a deviation below the reference value, the device operation unit 130 generates a sealing thickness defect alarm and guides the user to confirm the quality and change the adjustment parameters (e.g., sealing temperature, sealing pressure, contact time) associated with the sealing thickness adjustment of the device operation unit 120. The user can touch or drag a specific area of ​​the 3D package displayed on the device operation unit 130 and change the adjustment parameters of the setting operation unit 120 to address the sealing thickness defect scenario with a deviation below the reference value. In other words, the simulation device receives user behavior information about touching or dragging at least a portion of the area corresponding to the quality confirmation of the 3D package and understands the cause of the defect. It can also correct a defective material to normal by receiving user condition information about changing the adjustment parameters associated with the sealing thickness adjustment. For example, when the sealing thickness is less than the lower limit of the specification, the sealing thickness can be increased by decreasing the sealing temperature parameter setting, the sealing pressure parameter setting, or the contact time parameter setting. Furthermore, when the sealing thickness is greater than the upper limit of the specification, the sealing thickness can be decreased by increasing the sealing temperature parameter setting, the sealing pressure parameter setting, or the contact time parameter setting.

[0131] Then, the simulation device can determine whether the sealing thickness defect scenario with a deviation below the reference value has been resolved based on at least a portion of the calibrated material. For example, when user behavior information is generated based on touch input, drag input, etc., to a predetermined area in a predetermined sequence, the simulation device can determine that the sealing thickness defect scenario with a deviation below the reference value has been resolved. Furthermore, when user condition information changes to a predetermined value, the simulation device can determine that the sealing thickness defect scenario with a deviation below the reference value has been resolved. When it is determined that the defect scenario has been resolved, a predetermined area representing the sealing thickness defect can be removed from the image, video, and / or animation of the 3D package or material, and the corresponding material quality parameters displayed on the device's actuation unit 130 can be corrected and changed to normal.

[0132] Figure 10 This is a diagram illustrating an example of a sealing thickness defect scenario where a deviation exceeds a reference value, according to an embodiment of the present invention. Simulation device ( Figure 1 The device (100) identifies one or more defective scenarios among multiple defective scenarios associated with malfunctions in 3D packaging, and modifies at least one of the 3D packaging operation and quality information associated with the material quality based on the identified defective scenario. The multiple defective scenarios may include a sealing thickness defective scenario where the deviation exceeds a reference value. For example, a sealing thickness defective scenario where the deviation exceeds a reference value may refer to a scenario where the sealing thickness of at least one of multiple thickness measurement points 1010, 1020, and 1030 of the material deviates from the upper and lower limits of a preset specification, and the deviation of the sealing thickness between the measurement points exceeds a preset reference value. According to one embodiment, when one or more defective scenarios include a sealing thickness defective scenario where the deviation exceeds a reference value, the simulation device can change images, videos, or animations such as points, lines, or surfaces representing the sealing thickness of the material generated by the 3D packaging included in the device operation unit 130 to a predetermined area.

[0133] When a sealing thickness defect occurs with a deviation exceeding a reference value, the device actuation unit 130 generates a sealing thickness defect alarm and guides the user to confirm the quality and clean the sealing tool. The user can touch or drag a specific area of ​​the 3D package displayed on the device actuation unit 130 to address the sealing thickness defect. In other words, the simulation device receives user behavior information about touching or dragging at least a portion of the area corresponding to the quality confirmation of the 3D package and understands the cause of the defect. It also receives user behavior information about touching or dragging at least a portion of the area corresponding to the sealing tool and removes contaminants attached to the sealing tool, thereby correcting the defective material to normal. Then, the simulation device can determine whether the sealing thickness defect with a deviation exceeding the reference value has been resolved based on at least a portion of the corrected material. For example, when user behavior information is generated based on touch input, drag input, etc., of a predetermined area in a predetermined order, the simulation device can determine that the sealing thickness defect has been resolved. Furthermore, when user condition information changes to a predetermined value, the simulation device can determine that the sealing thickness defect has been resolved. When it is determined that the defective scenario has been resolved, a predetermined area indicating poor sealing thickness can be removed from the 3D package or material image, video and / or animation, and the corresponding material quality parameters displayed on the device action unit 130 can be corrected and changed to normal.

[0134] However, if the material is not corrected to normal even after cleaning the sealing tool, the simulation device guides the user to confirm the quality and perform at least one of the following actions by the equipment operation unit 120: adjusting the height of the sealing tool stop and inserting / removing the feeler gauge. The simulation device receives user behavior information of touching or dragging at least a portion of the area corresponding to the quality confirmation of the 3D packaging and understands the cause of the defect. It can also receive user behavior information of touching or dragging at least a portion of the sealing tool stop and feeler gauge according to the cause of the defect and correct the defective material to normal by adjusting the height of the sealing tool stop or inserting or removing the feeler gauge into or from the sealing tool.

[0135] For example, when the sealing thickness on one side of the left and right measuring points is less than the lower limit of the specification, the sealing thickness on that side can be increased by adding a gasket to the sealing tool stop on that side or removing a feeler gauge from the sealing tool on that side. Conversely, when the sealing thickness on one side of the left and right measuring points is greater than the upper limit of the specification, the sealing thickness on that side can be decreased by removing a gasket from the sealing tool stop on that side or inserting a feeler gauge into the sealing tool on that side. Furthermore, when the sealing thickness at the center measuring point deviates significantly from the sealing thickness at the two side measuring points, adding or removing a gasket from the sealing tool stops on both sides, or removing or inserting a feeler gauge from them, corrects the sealing thickness while reducing the deviation between the center and side measuring points. The simulation device can then determine whether the poor sealing thickness scenario has been resolved based on at least a portion of the corrected material. For example, when user behavior information is generated based on touch input, drag input, etc., to a predetermined area in a predetermined sequence, the simulation device can determine that the poor sealing thickness scenario has been resolved. Additionally, when user condition information changes to a predetermined value, the simulation device can determine that the poor sealing thickness scenario has been resolved. When it is determined that the defective scenario has been resolved, a predetermined area indicating poor sealing thickness can be removed from the 3D package or material image, video and / or animation, and the corresponding material quality parameters displayed on the device action unit 130 can be corrected and changed to normal.

[0136] exist Figures 7 to 10 The image, video, and / or animation representing a portion of the 3D package are shown on the device action unit 130, but are not limited thereto. The device action unit 130 may include images, videos, and / or animations with the same shape as the actual package. With the configuration described above, users can effectively train in advance on methods to deal with problems that may occur during the packaging process, and the simulation device can effectively determine whether the problem has been resolved based on the input or received user actions.

[0137] Figures 7 to 10 The document has already described scenarios such as poor sealing groove, poor sealing thickness with deviation below the reference value, and poor sealing thickness with deviation exceeding the reference value. However, multiple scenarios may also include other defects that may occur during packaging.

[0138] also, Figures 7 to 10 The document has already described the following scenarios: poor sealing groove, poor sealing thickness with deviation below the reference value, and poor sealing thickness with deviation exceeding the reference value. These scenarios are driven individually, but the document is not limited to these scenarios. Two or more poor scenarios may occur in combination.

[0139] Figure 11This is a diagram illustrating an embodiment of the generation of a defective scenario 1122 according to an embodiment of the present invention. As shown in the figure, the simulation device 100 can communicate with external devices (e.g., secondary battery production equipment, etc.) 1110, defective scenario DB 1120, etc., and can receive and receive data and / or information required to generate the defective scenario 1122.

[0140] According to one embodiment, in the event of a malfunction in external device 1110, simulation device 100 can receive or obtain error information 1112 associated with the malfunction in external device 1110. Error information 1112 may include operational information of external device 1110 at the time of the malfunction and the amount of quality change of the substance generated in external device 1110. In this case, simulation device 100 can determine the values ​​of condition values, setting values, and / or quality parameters of the 3D model device (e.g., 3D packaging) to correspond with the error information 1112, and can generate a defective scenario 1122 having the determined values ​​of the condition values, setting values, and / or quality parameters of the 3D model device. The defective scenario 1122 generated in this manner can be stored in defective scenario DB 1120 and managed. For example, the simulation device 100 can use any algorithm and / or a machine learning model learned for generating defective scene 1122 to determine the values ​​of the condition values, set values ​​and / or quality parameters of the 3D model device, so as to correspond to the error information 1112 and generate defective scene 1122.

[0141] According to one embodiment, the processor can convert the operation information of the external device 1110 into a first set of parameters associated with the operation of the 3D model device, and convert the quality change of the substance generated by the external device 1110 into a second set of parameters associated with quality information related to the quality of the substance generated by the 3D model device. The processor can then use the converted first and second sets of parameters to determine the category of the malfunction occurring in the external device 1110, and generate an adverse scenario based on the determined category, the first set of parameters, and the second set of parameters.

[0142] exist Figure 11 Although described as generating a defective scenario in the event of a malfunction in external device 1110, this is not limited to this. For example, the defective scenario can be determined in advance by any user. In other examples, defective scenarios can also be generated by randomly determining setpoints, condition values, quality information, etc., associated with the 3D model device within a pre-determined range of anomalies. With such a configuration, users can train their system using defective scenarios generated based on malfunctions occurring in actual working environments, thereby effectively improving their ability to respond to defects.

[0143] Figure 12This is a diagram illustrating an embodiment of the generation of operational capability information 1230 and test results 1240 according to an invention. As described above, in the event of an adverse scenario, the simulation device 100 can receive user condition information 1210, user behavior information 1220, etc. from the user, and determine whether the adverse scenario has been resolved based on the received user condition information 1210, user behavior information 1220, etc.

[0144] According to one embodiment, when a defective scenario is determined to be resolved, the simulation device 100 can calculate the duration and loss value of the defective scenario during its execution, and generate operational capability information 1230 for the 3D model device of the user account based on the calculated duration and loss value. In this case, test results 1240 can also be output along with the operational capability information 1230. For example, a user associated with this user account can perform tests for any defective scenario, and when all defective scenarios associated with a specific 3D model device are resolved according to a pre-specified benchmark, the simulation device 100 can determine that the user has passed the simulation test for the specific 3D model device.

[0145] Figure 13 This is a diagram illustrating an embodiment of a simulation method S1300 for producing secondary batteries according to an embodiment of the present invention. The simulation method S1300 for producing secondary batteries can be executed by a processor (e.g., at least one processor of a simulation device). As shown, the simulation method S1300 for producing secondary batteries can be started by the processor outputting a device operation unit, an equipment operation unit, and a quality verification unit. The device operation unit includes a 3D model device associated with the production of secondary batteries, the equipment operation unit includes multiple adjustment parameters for verifying the operation of the 3D model device, and the quality verification unit includes quality information (S1310) associated with the quality of the material generated by the 3D model device.

[0146] The processor can obtain at least one of first user behavior information obtained through the device action unit and first user condition information obtained through the device operation unit (S1320). The first user condition information may include information associated with the value corresponding to at least one of the plurality of adjustment parameters.

[0147] The processor can determine the action of the 3D model device based on at least one of the obtained first user behavior information and first user condition information (S1330). Furthermore, the processor can execute the action of the 3D model device included in the device action unit based on the determined action (S1340). Upon receiving the first user behavior information, the processor can determine whether the received first user behavior information corresponds to a predetermined action condition of the 3D model device, and if it determines that the first user behavior information corresponds to the predetermined action condition of the 3D model device, allow the 3D model device to operate.

[0148] According to one embodiment, the processor can determine one or more quality parameters for determining the quality of a substance generated by a 3D modeling device, and during the execution of actions of the 3D modeling device, calculate values ​​corresponding to the determined one or more quality parameters based on the executed actions of the 3D modeling device. Furthermore, the processor can generate quality information associated with the quality of the substance generated by the 3D modeling device based on the calculated values ​​corresponding to the one or more quality parameters.

[0149] According to one embodiment, a processor can identify one or more defective scenarios associated with malfunctions of a 3D modeling device, and modify at least one of the following based on the identified defective scenario: the operation of the 3D modeling device and quality information associated with the quality of a substance. The processor can then receive at least one of second user behavior information and second user condition information for resolving the identified defective scenario, and correct the modified operation of the 3D modeling device based on the received second user behavior information and second user condition information. Furthermore, during the execution of the corrected operation of the 3D modeling device, the processor can calculate values ​​corresponding to multiple quality parameters associated with the quality of the substance generated by the 3D modeling device based on the executed operation of the 3D modeling device. In this case, the processor can correct the quality information associated with the quality of the substance generated by the corrected 3D modeling device based on the calculated values ​​corresponding to the multiple quality parameters, and use the corrected quality information to determine whether one or more defective scenarios have been resolved.

[0150] Figure 14This is a diagram illustrating an embodiment of a packaging simulation method (S1400) for producing secondary batteries according to an embodiment of the present invention. The packaging simulation method (S1400) for producing secondary batteries can be executed by a processor (e.g., at least one processor of a simulation device). As shown, the packaging simulation method (S1400) for producing secondary batteries can be started by the processor executing a device operation unit including 3D packaging associated with the production of secondary batteries and tools for verifying the quality of the material generated by the 3D packaging, and a device operation unit including multiple adjustment parameters for determining the operation of the 3D packaging (S1410).

[0151] The processor can obtain at least one of first user behavior information obtained through the device action unit and first user condition information obtained through the device operation unit (S1420). Furthermore, the processor can determine at least one action among material inspection, 3D packaging operation, autonomous inspection, and device stop based on at least one of the obtained first user behavior information and first user condition information (S1430). Furthermore, the processor can execute actions associated with 3D packaging based on the determined actions (S1440). The material inspection action can include actions such as inspecting packaging materials required for packaging, such as leads, aluminum pouches, and insulating tape. The 3D packaging operation action can include actions such as loading, tab welding, aluminum pouch forming, cell assembly, electrolyte filling, V-sealing, and unloading. In addition, the autonomous inspection can include actions such as welding tensile strength inspection, tab condition inspection, tab position inspection, lead film protrusion position inspection, lead center inspection, seal position inspection, seal thickness inspection, platform width inspection, and cup seal gap inspection.

[0152] According to one embodiment, the processor can change the adjustment parameters displayed on the device operating unit based on first user behavior information. Furthermore, when receiving the first user behavior information and first user condition information, if it is determined that the received first user behavior information and first user condition information correspond to previously determined user behavior and user condition inputs, the processor can allow the 3D packaging operation.

[0153] Furthermore, the processor can determine one or more quality parameters for determining the quality of the material generated by 3D packaging. During the execution of the 3D packaging operation, the processor can calculate values ​​corresponding to the determined quality parameters based on the executed 3D packaging operation. Then, the processor can generate quality information associated with the quality of the material generated by 3D packaging based on the calculated values ​​corresponding to the one or more quality parameters.

[0154] According to one embodiment, the processor can determine one or more defect scenarios associated with malfunctions in 3D packaging, and modify at least one of the following based on the determined defect scenario: the 3D packaging operation and quality information associated with the material's quality. For example, the multiple defect scenarios may include a sealing groove defect scenario, a sealing thickness defect scenario with a deviation below a reference value, a sealing thickness defect scenario with a deviation exceeding a reference value, etc. In this case, each defect scenario can be resolved using arbitrary user condition information and user behavior information input by the user.

[0155] Figure 15 This is a diagram illustrating an example of a test result calculation method S1500 according to an embodiment of the present invention. The test result calculation method S1500 can be executed by a processor (e.g., at least one processor of a simulation device). As shown, the test result calculation method S1500 can begin (S1510) by the processor receiving at least one of second user behavior information and second user condition information for resolving one or more determined adverse scenarios.

[0156] As described above, the processor can correct the modified operation of the 3D model device based on at least one of the received second user behavior information and second user condition information (S1520). Furthermore, during the execution of the corrected operation of the 3D model device, the processor can calculate values ​​corresponding to multiple quality parameters associated with the quality of the substance generated by the 3D model device based on the executed operation of the 3D model device (S1530). In this case, the processor can correct the quality information associated with the quality of the substance generated by the corrected 3D model device based on the calculated values ​​corresponding to the multiple quality parameters (S1540).

[0157] Then, the processor can use the corrected quality information and / or the settings and condition values ​​of the 3D model device to determine whether one or more defective scenarios have been resolved (S1550). If it is determined that the defective scenario has not been resolved, the processor can use the information input by the user to regenerate or obtain second user behavior information, second user condition information, etc.

[0158] If one or more defective scenarios are determined to be resolved, the processor can calculate the execution time and loss value of one or more defective scenarios during the period of handling the defective scenarios (S1560). Furthermore, the processor can generate operational capability information for the 3D model device specific to the user account based on the calculated execution time and loss value (S1570). While the operational capability information may include, but is not limited to, parameters such as execution speed and accuracy calculated using execution time and loss value, it may also include the user's test score and test pass / fail status. In this case, each user performing secondary battery production can be assigned a user account, and the operational capability information generated based on the user's defective scenario execution time and loss value can be stored or managed in association with that user account.

[0159] Figure 16 This is a diagram illustrating an example of a defective scene generation method S1600 according to an embodiment of the present invention. The defective scene generation method S1600 can be executed by a processor (e.g., at least one processor of a simulation device). As shown, the defective scene generation method S1600 can begin (S1610) by the processor obtaining error information associated with a malfunction in an external device associated with a 3D model device.

[0160] The processor can generate a malfunction scenario associated with the malfunction of the 3D model device based on the obtained error information (S1620). The error information may include the values ​​and setpoints of various adjustment parameters of the actual secondary battery production equipment associated with the 3D model device when a malfunction occurs. For example, if the quality of the material produced by the secondary battery production equipment exceeds a predetermined normal range, a malfunction can be determined. In the case of a determined malfunction, the processor can obtain error information associated with the malfunction and generate a malfunction scenario associated with the malfunction of the 3D model device based on the obtained error information.

[0161] Figure 17 An exemplary computing device 1700 is shown for performing the methods and / or embodiments described above. According to one embodiment, the computing device 1700 may use hardware and / or software configured to interact with a user. The computing device 1700 may include the analog device 100 described above. Figure 1For example, computing device 1700 can be configured to support virtual reality (VR), augmented reality (AR), or mixed reality (MR) environments, but is not limited thereto. Computing device 1700 may include laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, etc., but is not limited thereto. The constituent elements of computing device 1700, their interconnections, and their functions described above are merely illustrative and are not intended to limit the embodiments of the invention described herein and / or claimed.

[0162] The computing device 1700 includes a processor 1710, a memory 1720, a storage device 1730, a communication device 1740, a high-speed interface 1750 connected to a high-speed expansion port, and a low-speed interface 1760 connected to a low-speed bus and storage device. These components (1710, 1720, 1730, 1740, 1750, and 1760) can be interconnected using various buses and can be mounted on a main board or otherwise appropriately mounted and connected. The processor 1710 can perform basic arithmetic, logic, and input / output operations to process computer program instructions. For example, the processor 1710 can process instructions stored in the memory 1720, storage device 1730, etc., and / or instructions executed within the computing device 1700, and display graphical information on an external input / output device 1770, such as a display device, coupled to the high-speed interface 1750.

[0163] The communication device 1740 can provide configurations or functions for enabling the input / output device 1770 and the computing device 1700 to communicate with each other via a network, and can also provide configurations or functions for supporting communication between the input / output device 1770 and / or the computing device 1700 and other external devices. For example, requests or data generated by the processor of an external device according to arbitrary program code can be transmitted to the computing device 1700 via the network under the control of the communication device 1740. Conversely, control signals or instructions provided under the control of the processor 1710 of the computing device 1700 can be transmitted to other external devices via the communication device 1740 and the network.

[0164] exist Figure 17Although the computing device 1700 is shown as including a processor 1710, a memory 1720, etc., it is not limited to this; the computing device 1700 can be implemented using multiple memories, multiple processors, and / or multiple buses, etc. Furthermore, in Figure 17 Although it is described as having a single computing device 1700, it is not limited to this; multiple computing devices can interact and perform actions for executing the methods described above.

[0165] The memory 1720 may store information within the computing device 1700. According to one embodiment, the memory 1720 may include volatile memory cells or multiple memory cells. Alternatively or additionally, the memory 1720 may include non-volatile memory cells or multiple memory cells. Furthermore, the memory 1720 may include other forms of computer-readable media, such as a magnetic disk or optical disk. Additionally, an operating system and at least one program code and / or instructions may be stored in the memory 1720.

[0166] Storage device 1730 can be one or more high-capacity storage devices for storing data for computing device 1700. For example, storage device 1730 can be a computer-readable medium including, or can be configured to include, semiconductor storage devices such as hard disks, magnetic discs, optical discs, EPROMs (Erasable Programmable Read-Only Memory), EEPROMs (Electrically Erasable PROMs), flash memory devices, CD-ROMs, and DVD-ROMs. Furthermore, computer programs can be embodied in such computer-readable media.

[0167] High-speed interface 1750 and low-speed interface 1760 can be tools for interacting with input / output device 1770. For example, input devices may include devices such as cameras, keyboards, microphones, and mice containing audio and / or image sensors, while output devices may include devices such as displays, speakers, and haptic feedback devices. In other examples, high-speed interface 1750 and low-speed interface 1760 can be tools for interfacing with devices such as touchscreens that integrate input and output configuration or functions.

[0168] According to one embodiment, high-speed interface 1750 manages bandwidth-intensive operations of computing device 1700, while low-speed interface 1760 manages bandwidth-intensive operations less than those of high-speed interface 1750. This functional allocation is merely illustrative. According to one embodiment, high-speed interface 1750 can be combined with a high-speed expansion port, which can accommodate memory 1720, input / output device 1770, and various expansion cards (not shown). Furthermore, low-speed interface 1760 can be combined with storage device 1730 and low-speed expansion port. In addition, low-speed expansion ports, which may include various communication ports (e.g., USB, Bluetooth, Ethernet, wireless Ethernet), can be combined with network devices such as routers and switches via one or more input / output devices 1770, such as keyboards, pointing devices, scanners, or network adapters.

[0169] The computing device 1700 can be implemented in different forms. For example, the computing device 1700 can be implemented as a standard server, or as a group of such standard servers. Alternatively or additionally, the computing device 1700 can be implemented as part of a rack server system, or as a personal computer such as a laptop computer. In this case, the components of the computing device 1700 can be combined with other components within any mobile device (not shown). Such a computing device 1700 can include or communicate with more than one other computing device.

[0170] exist Figure 17 Although shown as an input / output device 1770 not included in the computing device 1700, it is not limited thereto and can be configured as a device with the computing device 1700. Furthermore, in Figure 17 Although the high-speed interface 1750 and / or low-speed interface 1760 are shown as separate components of the processor 1710, this is not a limitation, and the high-speed interface 1750 and / or low-speed interface 1760 may be included in the processor.

[0171] The methods and / or various embodiments described above can be implemented using digital electronic circuits, computer hardware, firmware, software, and / or combinations thereof. Various embodiments of the present invention can be executed by a data processing apparatus, such as 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 computer program described above can be written in any form of programming language, including compiled or interpreted languages, and can be distributed as independent executable programs, modules, subroutines, etc. The computer program can be distributed via a single computing device, multiple computing devices connected to the same network, and / or multiple computing devices distributed via multiple different network connections.

[0172] The methods and / or various embodiments described above can be executed by one or more processors configured to perform actions based on input data or generate output data, thereby executing one or more computer programs to process, store, and / or manage arbitrary functions, etc. For example, the methods and / or various embodiments of the present invention can be executed by dedicated logic circuits such as FPGAs (Field Programmable Gate Arrays) or ASICs (Application Specific Integrated Circuits), and the apparatus and / or system for executing the methods and / or embodiments of the present invention can be implemented as dedicated logic circuits such as FPGAs or ASICs.

[0173] One or more processors executing a computer program may include one or more processors of a general-purpose or special-purpose microprocessor and / or any type of digital computing device. The processor may receive instructions and / or data from read-only memory and random access memory, respectively, or from both read-only memory and random access memory. In this invention, the components of the computing device executing the method and / or embodiment may include one or more processors for executing instructions and one or more memories for storing instructions and / or data.

[0174] According to one embodiment, a computing device can send and receive data with one or more mass storage devices for storing data. For example, the computing device can receive and / or transfer data from a magnetic disc or optical disc, and transfer data to a magnetic disc or optical disc. Computer-readable media suitable for storing instructions and / or data associated with computer programs may include, but are not limited to, non-volatile memories of any form including semiconductor storage devices, such as EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable PROM), and flash memory devices. For example, computer-readable media may include magnetic discs such as internal hard disks or external hard disks, photomagnetic discs, CD-ROMs, and DVD-ROMs.

[0175] To provide interaction with the user, a computing device may include, but is not limited to, display devices for providing or displaying information to the user (e.g., CRT (Cathode Ray Tube), LCD (Liquid Crystal Display), etc.) and indicating devices for the user to input and / or provide instructions to the computing device (e.g., keyboard, mouse, trackball, etc.). That is, the computing device may also include any other type of device for providing interaction with the user. For example, the computing device may provide the user with any form of sensory feedback, including visual feedback, auditory feedback, and / or tactile feedback, to interact with the user. In this regard, the user can provide input to the computing device through various gestures such as vision, speech, and movement.

[0176] In this invention, multiple embodiments can be implemented in a computing device that includes back-end components (e.g., a data server), middleware components (e.g., an application server), and / or front-end components. In this case, the components can be interconnected via any form or medium of digital data communication, such as a communication network. According to one embodiment, the communication network may include wired networks such as Ethernet, power line communication, telephone line communication devices, and RS-serial communication; wireless networks such as mobile communication networks, WLAN (Wireless LAN), Wi-Fi, Bluetooth, and ZigBee; or combinations thereof. For example, the communication network may include a LAN (Local Area Network), a WAN (Wide Area Network), etc.

[0177] The computing device based on the exemplary embodiments described herein can be implemented using hardware and / or software configured to interact with a user, including a user device, a user interface (UI) device, a user terminal, or a client device. For example, the computing device may include a portable computing device such as a laptop computer. Additionally or alternatively, the computing device may include, but is not limited to, PDAs (Personal Digital Assistants), tablet PCs, game consoles, wearable devices, IoT (Internet of Things) devices, VR (virtual reality) devices, AR (augmented reality) devices, etc. The computing device may also include other types of devices configured to interact with a user. Furthermore, the computing device may include portable communication devices (e.g., mobile phones, smartphones, wireless cellular phones, etc.) suitable for wireless communication via networks such as mobile communication networks. The computing device is capable of communicating wirelessly with a web server using wireless communication technologies and / or protocols such as radio frequency (RF), microwave frequency (MWF), and / or infrared ray frequency (IRF).

[0178] In this invention, various embodiments, including specific structural and functional details, are illustrative. Therefore, the embodiments of this invention are not limited to the above description and can be implemented in many different forms. Furthermore, the terminology used in this invention is used to describe some embodiments and should not be construed as limiting the embodiments. For example, unless explicitly stated in the context, singular words and the above content can be interpreted to include plural forms.

[0179] In this invention, unless defined differently, all terms used in this specification, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Furthermore, terms as commonly used as those defined in dictionaries should be interpreted as having a meaning consistent with their meaning in the relevant technical context.

[0180] While the invention has been described in connection with a subset of embodiments in this specification, various modifications and variations can be made without departing from the scope of the invention as understood by one of ordinary skill in the art. Furthermore, such modifications and variations should be considered to fall within the scope of the appended claims.

Claims

1. A packaging simulation device for producing secondary batteries, comprising: The memory is configured to store at least one instruction; as well as At least one processor is configured to execute the at least one instruction stored in the memory. The at least one instruction includes instructions for the following: The device includes an actuation unit that performs 3D packaging associated with the production of secondary batteries and tools for verifying the quality of the material generated by the 3D packaging, as well as an equipment operation unit that includes multiple adjustment parameters for determining the operation of the 3D packaging. Obtain at least one of first user behavior information obtained through the device action unit and first user condition information obtained through the device operation unit; At least one action among raw material inspection, 3D packaging operation, and autonomous inspection is determined based on at least one of the obtained first user behavior information and first user condition information. Perform the determined actions; A defective scenario is executed that modifies at least one of the 3D packaging action and the quality information of the material to a defective area, the defective scenario including at least one of a sealing groove defective scenario, a first sealing thickness defective scenario, and a second sealing thickness defective scenario; Obtain at least one of the following: second user behavior information (touching or dragging at least a portion of the 3D package) and second user condition information (changing one of the plurality of adjustment parameters of the device operating unit); Based on at least one of the obtained second user behavior information and second user condition information, at least one of the 3D packaging action that was changed to the defective area and the quality information of the material will be corrected to normal. Calculate the values ​​corresponding to one or more quality parameters associated with and from the quality of the material generated by the corrected 3D encapsulation; and The quality information associated with the quality of the material generated by the corrected 3D encapsulation is corrected based on the calculated values ​​corresponding to the one or more quality parameters.

2. The packaging simulation apparatus for producing secondary batteries according to claim 1, wherein, The at least one instruction further includes instructions for the following: Inspect at least one of the leads, aluminum bag, and insulating tape.

3. The packaging simulation apparatus for producing secondary batteries according to claim 1, wherein, The at least one instruction further includes instructions for the following: The electrode tab welding, aluminum bag forming, battery cell assembly, electrolyte filling, and V-type sealing are performed.

4. The packaging simulation apparatus for producing secondary batteries according to claim 1, wherein, The at least one instruction further includes instructions for the following: Check at least one of the following: weld tensile strength, tab condition, tab position, lead film protrusion position, lead center, sealing position, sealing thickness, platform width, and cup seal gap.

5. The packaging simulation apparatus for producing secondary batteries according to claim 1, wherein, The at least one instruction further includes instructions for the following: Determine one or more quality parameters for determining the quality of the material generated by the 3D encapsulation; During the execution of the 3D packaging operation, values ​​corresponding to the determined one or more quality parameters are calculated based on the executed 3D packaging operation. Based on the calculated values ​​corresponding to the one or more quality parameters, quality information associated with the quality of the material generated by the 3D encapsulation is output.

6. The packaging simulation apparatus for producing secondary batteries according to claim 1, wherein, The at least one instruction further includes instructions for the following: More than one defective scenario is identified among a plurality of defective scenarios associated with the quality of the material generated by the 3D encapsulation; Based on the identified one or more adverse scenarios, at least one of the following is used to modify the 3D packaging action and quality information associated with the quality of the material.

7. The packaging simulation apparatus for producing secondary batteries according to claim 1, wherein, In the scenario of poor sealing groove, the x-axis groove position of the material deviates from the boundary of the preset specification. In the scenario of poor sealing thickness, the sealing thickness of at least one of the multiple measurement points of the material deviates from the upper or lower limit of the preset specification, and the deviation of the sealing thickness between the multiple measurement points is below the preset reference value. In the scenario of poor sealing thickness, the sealing thickness of at least one of the multiple measurement points of the material deviates from the upper or lower limit of the preset specification, and the deviation of the sealing thickness between the multiple measurement points exceeds the preset reference value.

8. The packaging simulation apparatus for producing secondary batteries according to claim 1, wherein, The at least one instruction further includes instructions for the following: Obtain third user behavior information for at least a portion of the area corresponding to the quality confirmation of the material produced by the 3D encapsulation; The cause of the substance's adverse effects is output based on the third user behavior information.

9. The packaging simulation apparatus for producing secondary batteries according to claim 1, wherein, The at least one instruction further includes instructions for the following: The output includes guidance information on the conditions and behaviors required to resolve one or more adverse scenarios.

10. A packaging simulation method for producing secondary batteries, the method being executed by at least one processor, wherein, The method includes: The steps include an apparatus operating unit that performs 3D packaging associated with the production of secondary batteries and tools for verifying the quality of the material generated by the 3D packaging, and an equipment operating unit that includes multiple adjustment parameters for determining the operation of the 3D packaging. The step of obtaining at least one of first user behavior information obtained through the device action unit and first user condition information obtained through the device operation unit; The steps for determining at least one action in raw material inspection, 3D packaging operation, and autonomous inspection are based on at least one of the obtained first user behavior information and first user condition information. The steps to perform the determined action; A defective scenario is executed that modifies at least one of the 3D packaging action and the quality information of the material to a defective area, the defective scenario including at least one of a sealing groove defective scenario, a first sealing thickness defective scenario, and a second sealing thickness defective scenario; Obtain at least one of the following: second user behavior information (touching or dragging at least a portion of the 3D package) and second user condition information (changing one of the plurality of adjustment parameters of the device operating unit); Based on at least one of the obtained second user behavior information and second user condition information, at least one of the 3D packaging action that was changed to the defective area and the quality information of the material will be corrected to normal. Calculate the values ​​corresponding to one or more quality parameters associated with and from the quality of the material generated by the corrected 3D encapsulation; and The quality information associated with the quality of the material generated by the corrected 3D encapsulation is corrected based on the calculated values ​​corresponding to the one or more quality parameters.

11. The packaging simulation method for producing secondary batteries according to claim 10, wherein, When the determined action is raw material inspection, the steps for performing the determined action include: The steps for inspecting at least one of the leads, aluminum bag, and insulating tape.

12. The packaging simulation method for producing secondary batteries according to claim 10, wherein, When the determined action is a 3D encapsulation operation, the steps for performing the determined action include: The steps of performing at least one of the following: tab welding, aluminum bag forming, battery cell assembly, electrolyte filling, and V-sealing.

13. The packaging simulation method for producing secondary batteries according to claim 10, wherein, When the determined action is a self-check, the steps for performing the determined action include: The procedure involves checking at least one of the following: weld tensile strength, tab condition, tab position, lead film protrusion position, lead center, sealing position, sealing thickness, platform width, and cup seal gap.

14. The packaging simulation method for producing secondary batteries according to claim 10, wherein, Also includes: The step of determining one or more quality parameters for determining the quality of the material generated by the 3D encapsulation; During the execution of the 3D packaging operation, the step of calculating the value corresponding to each of the determined one or more quality parameters based on the executed 3D packaging operation; as well as The step of outputting quality information associated with the quality of the substance generated by the 3D encapsulation, based on the calculated values ​​corresponding to the one or more quality parameters.

15. The packaging simulation method for producing secondary batteries according to claim 10, wherein, Also includes: The step of identifying more than one defective scenario among multiple defective scenarios associated with the quality of the material generated by the 3D encapsulation; as well as The steps of modifying the 3D packaging action and at least one of the quality information associated with the quality of the material based on the identified one or more adverse scenarios.

16. The packaging simulation method for producing secondary batteries according to claim 10, wherein, In the scenario of poor sealing groove, the x-axis groove position of the material deviates from the boundary of the preset specification. In the scenario of poor sealing thickness, the sealing thickness of at least one of the multiple measurement points of the material deviates from the upper or lower limit of the preset specification, and the deviation of the sealing thickness between the multiple measurement points is below the preset reference value. In the scenario of poor sealing thickness, the sealing thickness of at least one of the multiple measurement points of the material deviates from the upper or lower limit of the preset specification, and the deviation of the sealing thickness between the multiple measurement points exceeds the preset reference value.

17. The packaging simulation method for producing secondary batteries according to claim 10, wherein, After performing the steps of at least one of the following defect scenarios: the sealing groove defect scenario, the first sealing thickness defect scenario, and the second sealing thickness defect scenario, the method further includes: The step of obtaining third user behavior information corresponding to at least a portion of the area touched or dragged in relation to quality confirmation of the material produced by the 3D encapsulation; and The step of outputting the cause of the substance's adverse effects based on the third user behavior information.

18. The packaging simulation method for producing secondary batteries according to claim 10, wherein, Also includes: The output includes steps for providing guidance on the conditions and behaviors required to resolve one or more adverse scenarios.

19. A computer program product stored on a computer-readable medium, wherein, The computer program product is used to execute the method according to any one of claims 10 to 18 in a computer.

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