Secondary battery manufacturing system

Abstract

According to exemplary embodiments, a secondary battery manufacturing system is provided. The system comprises: a data matrix reader configured to read a data matrix of a semi-finished electrode product, generate an unrecognized image including the data matrix which fails to be read, and match the unrecognized image with a virtual ID; a first server configured to store the unrecognized image transmitted from the data matrix reader; and a processor configured to determine a feature, which interferes with reading the data matrix, so as to generate classification data on the basis of the unrecognized image transmitted from the first server.

Description

Secondary battery manufacturing system

[0001] The present invention relates to a secondary battery manufacturing system. This application claims the benefit of Korean Application No. 10-2024-0011512, filed January 25, 2024, which is incorporated herein by reference in its entirety.

[0002] Unlike primary batteries, secondary batteries can be charged and discharged multiple times. They are widely used as a power source for various wireless devices, including handsets, laptops, and cordless vacuum cleaners. Recently, improved energy density and economies of scale have dramatically reduced the per-unit manufacturing cost of secondary batteries. Furthermore, as the range of battery electric vehicles (BEVs) has increased to match that of fuel-powered vehicles, the primary use of secondary batteries is shifting from mobile devices to mobility.

[0003] Secondary batteries are manufactured through electrode processes, assembly processes, and activation processes. To improve yield and reliability in the secondary battery manufacturing process, ensuring traceability is crucial. Accordingly, various studies are being conducted to ensure traceability in the secondary battery manufacturing process.

[0004] The technical idea of ​​the present invention aims to solve a problem by providing a secondary battery manufacturing system with improved traceability.

[0005] According to exemplary embodiments of the present invention for solving the above-described problem, a secondary battery manufacturing system is provided. The system includes a data matrix reader configured to read a data matrix of an electrode semi-finished product, generate an unrecognized image including the data matrix that has failed to be read, and match the unrecognized image with a virtual ID; a first server configured to store the unrecognized image transmitted from the data matrix reader; and a processor configured to determine a feature that impedes reading of the data matrix so as to generate classification data based on the unrecognized image transmitted from the first server.

[0006] The title of the above unrecognized image includes the above virtual ID.

[0007] The above first server is a network attached storage.

[0008] The above first server is configured to further store an image associated with the virtual ID, which is an image of the electrode semi-finished product matched with the virtual ID.

[0009] The title of the image associated with the above virtual ID includes the above virtual ID.

[0010] The processor is configured to retrieve an image associated with the virtual ID of the corresponding electrode semi-finished product based on the virtual ID matched to the unrecognized image.

[0011] The processor is configured to determine a feature based on an image associated with the virtual ID.

[0012] The above processor is configured to generate consistency verification data indicating the consistency of the classification data.

[0013] The above consistency verification data is generated by comparing the features of the unrecognized image and the features of the image associated with the virtual ID of the electrode semi-finished product corresponding to the unrecognized image.

[0014] The secondary battery manufacturing system further includes a second server configured to store the classification data.

[0015] The data matrix reader is configured to read out the cell ID of the electrode semi-finished product from the data matrix, and the second server is configured to store cell ID data including the cell ID and the virtual ID.

[0016] The processor is configured to transmit the consistency verification data to the second server.

[0017] A secondary battery manufacturing system according to exemplary embodiments of the present invention may be configured to generate classification data indicating features that cause failures in reading a data matrix, and to generate consistency verification data that verifies the classification data. Accordingly, cell traceability monitoring can be provided, and cell tracking with higher precision can be achieved.

[0018] The effects that can be obtained from the exemplary embodiments of the present invention are not limited to the effects mentioned above, and other effects not mentioned can be clearly derived and understood by those skilled in the art to which the exemplary embodiments of the present disclosure pertain from the following description. In other words, unintended effects resulting from practicing the exemplary embodiments of the present disclosure can also be derived by those skilled in the art from the exemplary embodiments of the present disclosure.

[0019] FIG. 1 is a block diagram illustrating a secondary battery manufacturing system according to exemplary embodiments.

[0020] Figures 2 to 5 illustrate examples of electrode semi-finished products according to exemplary embodiments.

[0021] Figures 6 to 9 illustrate examples of unrecognized data matrix images according to exemplary embodiments.

[0022] Figure 10 is a flowchart illustrating a method for manufacturing a secondary battery according to exemplary embodiments.

[0023] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the attached drawings. Prior to this, it should be noted that the terms and words used in this specification and claims should not be construed as limited to their conventional or dictionary meanings. Based on the principle that the inventor can appropriately define the concepts of terms to best explain his or her invention, they should be interpreted in a way that aligns with the technical spirit of the present invention.

[0024] Accordingly, the embodiments described in this specification and the configurations illustrated in the drawings are merely the most preferred embodiments of the present invention and do not represent all of the technical ideas of the present invention. Therefore, it should be understood that there may be various equivalents and modified examples that can replace them at the time of filing this application.

[0025] In addition, when describing the present invention, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the present invention, the detailed description is omitted.

[0026] Since the embodiments of the present invention are provided to more fully explain the present invention to those skilled in the art, the shapes and sizes of components in the drawings may be exaggerated, omitted, or schematically illustrated for clearer explanation. Accordingly, the sizes and proportions of each component do not fully reflect the actual sizes or proportions.

[0027]

[0028] (Example 1)

[0029] FIG. 1 is a block diagram showing a secondary battery manufacturing system (10) according to exemplary embodiments.

[0030] Referring to FIG. 1, a secondary battery manufacturing system (10) may include a plurality of secondary battery manufacturing facilities (100), a server (210), a processor (220), and a server (230).

[0031] Secondary battery manufacturing facilities (100) may be configured to perform, for example, a secondary battery assembly process. Secondary battery manufacturing facilities (100) may include a plurality of data matrix readers (110), inspectors (120), processors (150), controllers (140), and processors (150).

[0032] According to exemplary embodiments, each of the secondary battery manufacturing facilities (100) may be configured to process an electrode semi-finished product. According to exemplary embodiments, a data matrix reader (110) may read a cell identification (CID) from the electrode semi-finished product, thereby matching the electrode semi-finished product with the process performed on the electrode semi-finished product, thereby enhancing traceability of the electrode semi-finished product.

[0033] Each of the secondary battery manufacturing facilities (100) may include a transport device for transporting electrode semi-finished products and a processing device for processing the electrode semi-finished products. According to exemplary embodiments, the transport device may be a Linear Motion System (LMS). The transport device may also include a conveyor device or a roll-to-roll transport device.

[0034] The processing apparatus may be configured to process electrode semi-finished products. The secondary battery manufacturing facilities (100) may be configured to perform different processes. For example, some of the secondary battery manufacturing facilities (100) may be configured to perform a notching process, other of the secondary battery manufacturing facilities (100) may be configured to perform a lamination process, other of the secondary battery manufacturing facilities (100) may be configured to perform a stacking process, other of the secondary battery manufacturing facilities (100) may be configured to perform a folding process, and other of the secondary battery manufacturing facilities (100) may be configured to perform a packaging process.

[0035] Figures 2 to 5 are drawings illustrating electrode semi-finished products according to exemplary embodiments. That is, the electrode semi-finished products may be an electrode sheet (ES) of Figure 2, a half cell (HC) of Figure 3, a mono cell (MC) of Figure 4, or an electrode assembly (EA) of Figure 5. The electrode semi-finished products may include electrodes as intermediate products for providing a completed battery cell.

[0036] Referring to FIG. 3, a notching process may be performed on an electrode sheet (ES) unwound from an electrode roll (ER) by a rewinder. In the notching process, an electrode tab (ETN) may be formed on a non-coated portion of the electrode sheet (ES). A V-groove may further be formed on the electrode sheet (ES) in the notching process. A data matrix (DM) may be formed on the electrode tab (ETN). The data matrix (DM) may be formed by a method such as inkjet printing or laser printing. According to exemplary embodiments, the electrode sheet (ES) on which the data matrix (DM) is formed may include, but is not limited to, a negative electrode. The electrode sheet (ES) may also include a positive electrode. After the electrode notching process, the electrode sheet (ES) may be individualized into unit electrodes including electrode tabs (ETN). The positive electrode may include a positive electrode collector and a positive electrode active material. The negative electrode may include a negative electrode collector and a negative electrode active material.

[0037] The thickness of the positive electrode current collector may range from about 3 μm to about 500 μm. The positive electrode current collector may not cause chemical changes in the secondary battery to be ultimately manufactured and may have high conductivity. The positive electrode current collector may include, for example, stainless steel, aluminum, nickel, titanium, calcined carbon, and aluminum. The positive electrode current collector may also include stainless steel surface-treated with carbon, nickel, titanium, silver, or the like. The surface of the positive electrode current collector may include a micro-roughened structure to increase the adhesion of the active material. The positive electrode current collector may have a shape such as a film, a sheet, a foil, a net, a porous material, a foam, or a non-woven fabric.

[0038] The thickness of the negative electrode current collector may be in the range of about 3 μm to about 500 μm. The negative electrode current collector may not cause chemical changes in the secondary battery ultimately manufactured and may have high conductivity. The negative electrode current collector may include copper, stainless steel, aluminum, nickel, titanium, sintered carbon, and an aluminum-cadmium alloy. The negative electrode current collector may also include stainless steel surface-treated with carbon, nickel, titanium, silver, etc. The surface of the negative electrode current collector may include a micro-roughened structure to increase the adhesion of the active material. The negative electrode current collector may have a shape such as a film, a sheet, a foil, a net, a porous material, a foam, or a non-woven fabric.

[0039] A cathode active material is a material that can cause an electrochemical reaction. The cathode active material may be a lithium transition metal oxide. The cathode active material may be, for example, a layered compound such as lithium cobalt oxide (LiCoO2) and lithium nickel oxide (LiNiO2) substituted with one or more transition metals, lithium manganese oxide substituted with one or more transition metals, or a lithium manganese oxide having the chemical formula LiNi. 1-y M y Lithium nickel oxide, Li, expressed as O2 (wherein, M is any one of Co, Mn, Al, Cu, Fe, Mg, B, Cr, Zn, and Ga, and 0.01≤y≤0.7) 1+z Ni 1 / 3 Co 1 / 3 Mn 1 / 3 O2, Li 1+zN i 0.4 Mn 0.4 Co 0.2 Li like O2 1+z Ni b Mn c Co 1-(b+c+d) M d O (2-e) A e(wherein, -0.5≤z≤0.5, 0.1≤b≤0.8, 0.1≤c≤0.8, 0≤d≤0.2, 0≤e≤0.2, b+c+d<1, M is any one of Al, Mg, Cr, Ti, Si, and Y, and A is any one of F, P, and Cl) Lithium nickel cobalt manganese composite oxide, chemical formula Li 1+x M 1-y M' y PO 4-z X z (wherein, M is a transition metal, more specifically, one of Fe, Mn, Co, and Ni, M' is one of Al, Mg, and Ti, X is one of F, S, and N, -0.5≤x≤+0.5, 0≤y≤0.5, and 0≤z≤0.1) and may include an olivine-based lithium metal phosphate.

[0040] The negative active material may include carbon, such as non-graphitizable carbon, graphitic carbon, etc. The negative active material may include, for example, Li x Fe2O3(0≤x≤1), LixWO2(0≤x≤1), Sn x Me 1-x Me' y O z (Here, Me is any one of Mn, Fe, Pb, and Ge, and Me' is any one of Al, B, P, Si, elements of group 1, 2, and 3 of the periodic table, and halogens, and 0 <x≤1이고, 1≤y≤3 이며, 1≤z≤8) 등의 금속 복합 산화물을 포함할 수 있다. 음극 활물질은, 예컨대, 리튬 금속, 리튬 합금, 규소계 합금, 주석계 합금을 포함할 수 있다. 음극 활물질은, 예컨대, SnO, SnO2, PbO, PbO2, Pb2O3, Pb3O4, Sb2O3, Sb2O4, Sb2O5, GeO, GeO2, Bi2O3, Bi2O4, Bi2O5등의 금속 산화물을 포함할 수 있다. 음극 활물질은, 예컨대, 폴리아세틸렌 등의 도전성 고분자, Li-Co-Ni 계 재료 등을 포함할 수 있다.

[0041] Referring to FIGS. 3 and 4, in the lamination process, individualized unit electrodes may be bonded to a separator. In the lamination process, the separator and the unit electrode may be heat-treated to enhance the bonding strength between the separator and the unit electrode. The lamination process may provide a half-cell (HC) or a mono-cell (MC). A bi-cell, etc. may also be provided by the lamination process. The half-cell (HC) may include a separator and an anode, or a separator and a cathode. The half-cell (HC) may include an electrode tab (ETN) including a data matrix (DM). The mono-cell (MC) may include an anode, a first separator, a cathode, and a second separator, which are sequentially stacked. The mono-cell (MC) may include an electrode tab (ETN) including a data matrix (DM) and an electrode tab (ETP) having an opposite polarity to the electrode tab (ETN). Unlike in FIG. 4, the data matrix (DM) may be formed on each of the electrode tabs (ETP, ETN) or may be formed only on the electrode tab (ETP).

[0042] Referring to FIGS. 3 to 5, in a stacking process, at least one of a half cell (HC), a mono cell (MC), and a bi-cell may be repeatedly stacked. An electrode assembly (EA) may be provided by the stacking process. The electrode assembly (EA) may include a tape for fixing positive and negative electrodes. The electrode assembly (EA) may include an electrode tab (ETN) including a data matrix (DM) and an electrode tab (ETP) of opposite polarity to the electrode tab (ETN). Unlike FIG. 5, the data matrix (DM) may be formed on each of the electrode tabs (ETP, ETN) or may be formed only on the electrode tab (ETP).

[0043] In the folding process, half-cells, mono-cells, and bi-cells may be wrapped around a separator. The packaging process may include inserting the electrode assembly into a case, injecting the electrolyte, and sealing the case.

[0044] Referring back to FIG. 1, the data matrix reader (110) may be configured to capture an image of an electrode semi-finished product including a data matrix, and detect the data matrix of the image of the electrode semi-finished product to read out a cell identification (CID). As a non-limiting example, the data matrix may be a two-dimensional barcode. The data matrix may include information regarding a cell identification (CID) for identifying the electrode semi-finished product. That is, the cell identification (CID) may include a plurality of symbols for distinguishing and / or identifying the electrode semi-finished product. Here, the symbols may collectively refer to signs, letters, and marks that represent a certain meaning.

[0045] At this time, some of the images of the electrode semi-finished products may include features that interfere with the reading of the data matrix, and thus, the data matrix reader (110) may fail to read the data matrix.

[0046] Figures 6 to 9 illustrate unrecognized images (UIMa, UIMb, UIMc, UIMd) containing features that impede the reading of the data matrix.

[0047] Referring to FIG. 6, the features of the unrecognized image (UIMa) may include distortion (CRP) of the electrode tab (ET).

[0048] Referring to FIG. 7, a feature of an unrecognized image (UIMb) may be an NG tag (NGT) attached to an electrode tab (ET). If the inspection result of the electrode semi-finished product indicates that the electrode semi-finished product contains a defect, an NG tag (NGT) may be attached to the electrode tab (ET).

[0049] Referring to FIG. 8, the features of the unrecognized image (UIMc) may include contamination (STN) of the electrode tab (ET).

[0050] Referring to FIG. 9, the features of the unrecognized image (UIMd) may include contamination (WRK) of the electrode tab (ET).

[0051] Referring back to FIG. 1, the data matrix reader (110) may be configured to generate a virtual ID (VID) if the data matrix reading fails. The data matrix reader (110) may be configured to transmit a signal indicating a cell ID (CID) and a virtual ID (VID) to the controller (140). The virtual ID (VID) may have a different generation rule (or format) from the cell ID (CID), and the virtual ID (VID) may be easily distinguished from the cell ID (CID). For example, the length of the virtual ID (VID) may be different from the cell ID (CID).

[0052] As previously described, the Cell ID (CID) provides traceability for the secondary battery assembly process, while the Virtual ID (VID), as described below, can provide traceability for data matrix readout failures. By matching the Virtual ID (VID) to the electrode semi-finished product corresponding to the failed readout data matrix and the data derived from the electrode semi-finished product, additional insight into the traceability of the secondary battery assembly process can be provided.

[0053] The data matrix reader (110) may be configured to transmit a corresponding image, an unrecognized image (UIM), to the processor if the data matrix reading fails. The UIM may be matched with a virtual identifier (VID). Accordingly, the VID may be used to store and retrieve the UIM. For example, the title of the UIM may include the VID.

[0054] The tester (120) may be configured to test the electrode semi-finished product. The tester (120) may include, for example, a Time Delay and Integration (TDI) camera, a Complementary Metal Oxide Semiconductor (CMOS) image sensor, etc. The tester (120) may also include a Time of Flight (TOF) sensor, etc. The tester (120) may also include an emitter and a receiver configured to perform measurements using non-destructive signals, such as ultrasound, microwaves, terahertz waves, and infrared waves. The tester (120) may also include analog and / or digital sensors, such as biosensors, chemical sensors, composition sensors, current and / or power meters, air quality sensors, gas sensors, Hall effect sensors, brightness level sensors, and light sensors. The tester (120) may also include pressure sensors, temperature sensors, ultrasonic sensors, proximity sensors, door status sensors, motion tracking sensors, humidity sensors, visible and infrared sensors, and cameras, etc. An image (IMG) of the electrode semi-finished product can be generated by the inspector (120), and the inspector (120) can be configured to transmit the image (IMG) of the electrode semi-finished product to the processor (220).

[0055] The processor (130) may configure a vision machine together with the inspector (120), and the processor (130) may include an algorithm for processing an image (IMG) of an electrode semi-finished product. The algorithm of the processor (130) may include various algorithms for determining the quality (i.e., whether it is a defective product or a normal product) of the electrode semi-finished product based on the image (IMG) of the electrode semi-finished product, including an artificial neural network that is pre-trained or trained in real time. For example, the processor (130) may be configured to determine a defect in any one of the following: matching, sealing, dimension, short, NG marking, gap, tab appearance, separator appearance, alignment between elements, and welding quality.

[0056] The processor (130) can match the image (IMG) of the electrode semi-finished product to the cell ID (CID) and the virtual ID (VID). Accordingly, the cell ID-related image (CIMG) and the virtual ID-related image (VIMG) of the electrode semi-finished product can be provided. The processor (130) can be configured to transmit the cell ID-related image (CIMG) and the virtual ID-related image (VIMG) of the electrode semi-finished product to the server (210).

[0057] More specifically, if the data matrix of the electrode semi-finished product is successfully read, the image (IMG) can be matched with the cell ID (CID), and accordingly, a cell ID-associated image (CIMG) can be provided. The cell ID (CID) can be used to search and store the cell ID-associated image (CIMG). For example, the title of the cell ID-associated image (CIMG) can include the cell ID (CID).

[0058] Similarly, if the data matrix of the electrode semi-finished product fails to be read, the image (IMG) can be matched with a virtual ID (VID), and accordingly, a virtual ID-associated image (VIMG) can be provided. The virtual ID (VID) can be used to retrieve and store the virtual ID-associated image (VIMG). For example, the title of the virtual ID-associated image (VIMG) can include the virtual ID (VID).

[0059] The controller (140) may be configured to control elements of the secondary battery manufacturing facility (100). For example, the controller (140) may be configured to control the reading of cell ID by the data matrix reader (110), the inspection of electrode semi-finished products by the inspector (120), and the operation and stop of the processing mechanism of the secondary battery manufacturing facility.

[0060] The controller (140) may be configured to receive signals indicating a cell ID (CID) and a virtual ID (VID) from the data matrix reader (110). The controller (140) may be configured to transmit the signals to elements requiring matching using the cell ID (CID) and the virtual ID (VID), such as processors (130, 150).

[0061] The controller (140) may be a Programmable Logic Controller (PLC). A PLC is a specialized type of microprocessor-based controller that uses programmable memory to store commands and implement functions such as logic, sequencing, timing, counting, and arithmetic to control machines and processes. PLCs are easy to operate and program.

[0062] The controller (140) may include a power supply, a central processing unit (CPU), an input interface, an output interface, a communication interface, and memory devices. The power supply may be configured to supply power to other elements of the controller (140), such as the CPU, the input interface, the output interface, the communication interface, and the memory devices, for the operation of the controller (140). The memory devices may include a read-only memory (ROM) configured to store a system program, such as an operating system, and a random access memory (RAM) configured to store data, such as user programs and status information of input and output devices, timers, counters, and other internal device values. The CPU may be configured to control communication between modules that implement logic and convert input signals into output operation signals. The CPU may operate based on the system program and the user program stored in the memory devices. The CPU may be configured to write or read inspection data and measurement data to the data area of ​​the memory devices based on the system program and the user program. Conditions or data of industrial devices and production processes may be transmitted to the CPU through the input module. The results processed by the CPU can be transmitted to the actuator via the output module. The communication interface can be configured to relay the transmission and reception of data between the controller (140) and the processors (130, 150).

[0063] However, the controller (140) is not limited thereto, and may include any one of a simple controller, a complex processor such as a microprocessor, a CPU, a GPU, a processor configured by software, dedicated hardware, and firmware. The controller (140) may be implemented by, for example, a general-purpose computer or application-specific hardware such as a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), and an ASIC (Application Specific Integrated Circuit).

[0064] Each processor (150) of the secondary battery manufacturing facilities (100) can receive an unrecognized image (UIM). Unlike the illustration in FIG. 1, the number of data matrix readers (110) included in each of the secondary battery manufacturing facilities (100) may be two or more, and each processor (150) of the secondary battery manufacturing facilities (100) may be a type of data hub that collects unrecognized images (UIM) at the facility network level.

[0065] Each processor (150) of the secondary battery manufacturing facilities (100) may be configured to collect cell ID data including a cell ID (CID) and a virtual ID (VID). The processor (150) may be configured to transmit the cell ID data to a server (230).

[0066] Each processor (150) of the secondary battery manufacturing facilities (100) may be configured to transmit an unidentified image (UIM) to a server (210). The server (210) may be configured to store original data (i.e., images). The server (210) may be, but is not limited to, a network attached storage (NAS) that stores images such as an unidentified image (UIM), a cell ID associated image (CIMG), and a virtual ID associated image (VIMG).

[0067] The server (210) may be configured to transmit an unrecognized image (UIM) to the processor (220). The processor (220) may be configured to receive the unrecognized image (UIM) from the server (210). The processor (220) may be configured to analyze the unrecognized image (UIM) from the server (210). The processor (220) may be configured to generate classification data (CD) based on the unrecognized image (UIM). The processor (220) may be configured to determine a feature that impedes the reading of a data matrix of the unrecognized image (UIM). The classification data (CD) may represent a feature that impedes the reading of the unrecognized image (UIM). The classification data (CD) may include a feature that impedes the reading of the unrecognized image (UIM) and a virtual identifier (VID) matched to the feature. The processor (220) may be configured to transmit classification data (CD) to the server (230).

[0068] The processor (220) may be configured to determine a virtual ID (VID) matching the unrecognized image (UIM) from the unrecognized image (UIM), and retrieve an image (VIMG) associated with the virtual ID based on the virtual ID (VID) of the unrecognized image (UIM) from the database of the server (210). The processor (220) may further be configured to receive an image (VIMG) associated with the virtual ID corresponding to the unrecognized image (UIM) from the server (230).

[0069] The processor (220) may be configured to analyze an image (IMG) of an electrode semi-finished product corresponding to an unrecognized image (UIM). The processor (220) may be configured to determine a feature that interferes with the reading of the image (IMG) of the electrode semi-finished product.

[0070] The processor (220) may be configured to generate integrity verification data (IVD). The integrity verification data (IVD) may indicate the integrity of the classification data (CD). That is, the integrity verification data (IVD) may indicate the accuracy of the classification of the unidentified image (UIM) by the processor. The integrity verification data (IVD) may be determined based on a feature that interferes with reading determined based on the unidentified image (UIM) and a feature that interferes with reading determined based on the image (IMG) of the electrode semi-finished product. More specifically, the integrity verification data (IVD) may indicate a match or mismatch between a feature that interferes with reading determined based on the unidentified image (UIM) and a feature that interferes with reading determined based on the image (IMG) of the electrode semi-finished product. The processor (220) may be configured to transmit the integrity verification data (IVD) to the server (230).

[0071] The server (230) may be configured to receive and store cell ID data transmitted from each processor (150) of the secondary battery manufacturing facilities (100). The server (230) may be configured to receive and store classification data (CD) and integrity verification data (IVD) from the processor (220).

[0072] Event data representing events occurring in secondary battery manufacturing facilities (100) can be matched to cell IDs. Accordingly, events occurring in the secondary battery manufacturing process can be matched to electrode semi-finished products, and traceability of the process of problematic electrode semi-finished products after shipment can be provided.

[0073] The servers (210, 230) may include physical servers or cloud servers. The servers (210, 230) may be implemented as virtual servers, but are not limited thereto. The servers (210, 230) may provide data and analysis results to workers through various frameworks. The frameworks may include protocols that support data transmission, allowing client devices to visualize data through a user interface and provide updated visualizations as computed by the servers (210, 230). The protocols that support the data transmission may use HTML, JavaScript, and / or JSON.

[0074] The servers (210, 230) may include various Application Programming Interfaces (APIs) for storing data in databases and other data management tools. The APIs may also be used to retrieve data from databases in various data management systems. The data management systems may provide access to the databases, pull data from the databases, retrieve data, and generate metrics. Metrics are tools for visualizing data. Metrics include time-series measurements and can be used for monitoring applications and generating status alerts.

[0075] The server (230) may be configured to transmit a Uniform Resource Locator (URL) (or schema) including source code for displaying classification data (CD) and integrity verification data (IVD) stored in a database to a client device in response to an API request from a client or another server. The stored classification data (CD) and integrity verification data (IVD) may be visualized using tables and graphs. The client device may access the source code for visualizing and displaying the stored classification data (CD) and integrity verification data (IVD) through the URL (or schema).

[0076] The processors (130, 150, 220) and servers (210, 230) may be implemented using hardware, firmware, software, or a combination thereof. For example, the processors (130, 150, 220) and servers (210, 230) may include computing devices such as workstation computers, desktop computers, laptop computers, tablet computers, etc. The processors (130, 150, 220) and servers (210, 230) may also include any one of simple controllers, complex processors such as microprocessors, CPUs, GPUs, processors configured by software, dedicated hardware, and firmware. The processors (130, 150, 220) and servers (210, 230) may be implemented by, for example, a general-purpose computer or application-specific hardware such as a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), and an ASIC (Application Specific Integrated Circuit).

[0077] The operations of the processors (130, 150, 220) and the servers (210, 230) may be implemented as instructions stored on a machine-readable medium that can be read and executed by one or more processors. Here, the machine-readable medium may include any mechanism for storing and / or transmitting information in a form readable by a machine (e.g., a computing device). For example, the machine-readable medium may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium, an optical storage medium, a flash memory, an electrical, optical, acoustical or other form of radio signal (e.g., a carrier wave, an infrared signal, a digital signal, etc.), and any other signal.

[0078] The processors (130, 150, 220) and servers (210, 230) may be configured with firmware, software, routines, and instructions for performing the operations described above or any of the processes described below. For example, the processors (130, 150, 220) and servers (210, 230) may be instantiated within memory.

[0079] The client device may be any device capable of communicating with the server (300), such as a workstation computer, a laptop, a desktop computer, a tablet, a mobile device such as a smartphone, or a wearable device. The client device may include input tools for entering API requests and a display device for displaying the status of cell ID (CID) reading.

[0080] The secondary battery manufacturing system (10) can implement a plug-in architecture with an API for data acquisition to provide plug-and-play connectivity for sensors, measuring instruments, and testers. This allows resources from a specific process step and site to be easily transferred to other processes and sites, or new resources to be easily introduced to each process step and site.

[0081] In some embodiments, the secondary battery manufacturing system (10) may further include a manual input system that allows a worker to input manufacturing data. The secondary battery manufacturing system (10) may allow a worker to input data using an input tool and computer-based input of manufacturing data, such as scraping an Excel file. The manual input system may be, for example, a Human-Machine Interface (HMI) of a Supervisory Control And Data Acquisition (SCADA) system. SCADA may typically include a combination of software and hardware, such as a PLC and a Remote Terminal Unit (RTU). The HMI is a screen that supports communication between the operator and the SCADA system and is a key element of the SCADA system. For example, manual input by the HMI may include selecting a defect type and reflecting performance upon completion.

[0082]

[0083] (Example 2: Method)

[0084] FIG. 10 is a flowchart illustrating a method for manufacturing a secondary battery according to exemplary embodiments.

[0085] Referring to FIGS. 1 and 10, an unidentified image (UIM) can be received at P110. The unidentified image (UIM) can be received by the processor (220).

[0086] Next, classification data (CD) can be generated at P120. The processor (220) can generate classification data (CD) based on the unrecognized image (UIM). The generation of the classification data (CD) can include determining features that impede the reading of the data matrix included in the unrecognized image (UIM). The classification data (CD) can be transmitted to the server (230) by the processor (220).

[0087] Next, at P150, an image (IMG) of an electrode semi-finished product corresponding to an unrecognized image (UIM) may be received. The image (IMG) of the electrode semi-finished product may be received by a processor (220). The processor (220) may search for an image (VIMG) associated with a virtual ID of the electrode semi-finished product based on a virtual ID (VID) matched to the unrecognized image (UIMG), and may receive an image (VIMG) associated with a virtual ID corresponding to the unrecognized image (UIMG).

[0088] Next, in P140, integrity verification data (IVD) can be generated. The integrity verification data (IVD) can be generated by the processor (220). The generation of the integrity verification data (IVD) can include comparing features included in an unrecognized image (UIM) (i.e., features that interfere with the reading of a data matrix) with features included in an image (IMG) of an electrode semi-finished product corresponding to the unrecognized image (UIM) (i.e., features that interfere with the reading of a data matrix).

[0089] The present invention has been described in more detail through drawings and examples. However, the configurations described in the drawings or examples described in this specification are merely embodiments of the present invention and do not represent all of the technical ideas of the present invention. Therefore, it should be understood that various equivalents and modified examples may exist as of the time of this application.

Claims

1. A data matrix reader configured to read a data matrix of an electrode semi-finished product, configured to generate an unrecognized image including the data matrix that has failed to be read, and configured to match the unrecognized image with a virtual ID; A first server configured to store unrecognized images transmitted from the data matrix reader; and A secondary battery manufacturing system comprising a processor configured to determine a feature that interferes with the reading of the data matrix to generate classification data based on the unrecognized image transmitted from the first server.

2. In paragraph 1, A secondary battery manufacturing system, characterized in that the title of the above unrecognized image includes the above virtual ID.

3. In paragraph 1, A secondary battery manufacturing system, characterized in that the first server is a network attached storage.

4. In paragraph 1, A secondary battery manufacturing system, characterized in that the first server is configured to further store an image associated with the virtual ID, which is an image of the electrode semi-finished product matched with the virtual ID.

5. In paragraph 4, A secondary battery manufacturing system, characterized in that the title of the image associated with the virtual ID includes the virtual ID.

6. In paragraph 4, A secondary battery manufacturing system, characterized in that the processor is configured to search for an image associated with the virtual ID of the corresponding electrode semi-finished product based on the virtual ID matched to the unrecognized image.

7. In paragraph 4, A secondary battery manufacturing system, wherein the processor is configured to determine a feature based on an image associated with the virtual ID.

8. In paragraph 7, A secondary battery manufacturing system, characterized in that the processor is configured to generate consistency verification data indicating the consistency of the classification data.

9. In paragraph 8, A secondary battery manufacturing system, characterized in that the above consistency verification data is generated by comparing the features of the unrecognized image and the features of the image associated with the virtual ID of the electrode semi-finished product corresponding to the unrecognized image.

10. In paragraph 9, A secondary battery manufacturing system further comprising a second server configured to store the above classification data.

11. In paragraph 10, The above data matrix reader is configured to read the cell ID of the electrode semi-finished product from the data matrix, and A secondary battery manufacturing system, characterized in that the second server is configured to store cell ID data including the cell ID and the virtual ID.

12. In paragraph 10, A secondary battery manufacturing system, characterized in that the processor is configured to transmit the consistency verification data to the second server.

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