A production equipment data management method and system

Abstract

This invention discloses a production equipment data management method and system, relating to the field of equipment management technology. The management system acquires multiple production process step parameters of the production equipment. After preprocessing these parameters, it comprehensively analyzes them based on a regression analysis model, outputting the production equipment amplitude. The acquired production equipment amplitude is compared with preset first and second defect thresholds to analyze whether the lead-acid battery has latent defects and the severity of any such defects. The first defect threshold is used to analyze the presence of latent defects, and the second defect threshold is used to analyze the severity of latent defects. Based on the analysis results, corresponding management strategies are generated and sent to the administrator. This management system can effectively analyze whether the produced lead-acid batteries have latent defects, resulting in more accurate quality analysis and further improving the quality of lead-acid batteries.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment management, and in particular to a production equipment data management method and system. Background Art

[0002] The management system is a system used to monitor and manage the production process of lead-acid batteries. Lead-acid batteries are a common type of lead-acid batteries, which are widely used in automobiles, UPS (uninterruptible power supply) systems, solar energy storage and other fields. After the lead-acid batteries are produced by production equipment, the voltage, capacity, internal resistance, etc. of the lead-acid batteries are usually tested. However, in the actual production process, if there are slight abnormalities in some processing parameters of the production equipment (that is, the parameters develop towards a bad trend, but do not exceed or fall below the threshold of the parameters), the lead-acid batteries will have invisible internal damage (such as tiny cracks or stratification) or hidden electrolyte (there may be tiny impurities in the electrolyte). The above problems are difficult to detect in the detection of lead-acid batteries, but as the lead-acid batteries are used for a long time, the performance of the lead-acid batteries will be reduced and the service life will be shortened;

[0003] Based on this, the present invention proposes a production equipment data management method and system, which can analyze whether the lead-acid battery has latent defects based on the production equipment data after the lead-acid battery is produced, so as to solve the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a production equipment data management method and system to solve the deficiencies in the background technology.

[0005] In order to achieve the above object, the present invention provides the following technical solution: a production equipment data management method, the management method comprising the following steps:

[0006] When a product is being produced, the management system determines the production process step that the product is in and obtains the parameters of the corresponding production process step. When the parameters of a production process step exceed or fall below the corresponding threshold value, the management system issues a warning signal and controls the production equipment to stop running.

[0007] After the product is produced, the management system will test the product for multiple indicators. If any indicator of the product fails to meet the quality standards, the management system will send a signal to the administrator that the product quality does not meet the standards.

[0008] If all indicators of the tested product are qualified, the management system obtains multiple production process step parameters of the production equipment, pre-processes the multiple production process step parameters, comprehensively analyzes the multiple production process step parameters based on the regression analysis model and outputs the amplitude of the production equipment;

[0009] Compare the acquired production equipment amplitude with the preset first defect threshold and second defect threshold to analyze whether the product has latent defects and the severity of the latent defective product;

[0010] When all production equipment is regularly maintained, multiple product potential defect analysis results of the production equipment are obtained, and a data set is established by combining the multiple analysis results with the number of times the production equipment is controlled to stop running. After analyzing the data set through a trend analysis model, management values ​​are generated for all production equipment, and all production equipment are sorted from large to small according to the management values ​​to generate an equipment list, and the production equipment is maintained in the positive order of the equipment list.

[0011] In a preferred embodiment, the management system obtains multiple production process step parameters of the production equipment, and preprocesses the multiple production process step parameters including the following steps:

[0012] The management system obtains the temperature and compression pressure of the lead-acid battery during the packaging process, obtains the electrolyte filling speed of the lead-acid battery during the filling process, and obtains the vibration amplitude in the entire production process;

[0013] The real-time temperature during the packaging process is obtained. If the real-time temperature is not within the stable temperature range, the time period when the real-time temperature is lower than the temperature range is recorded as the material shrinkage warning period, and the time period when the real-time temperature is higher than the temperature range is recorded as the material expansion period. The material shrinkage warning period and the material expansion period are integrated to obtain the temperature influence coefficient.

[0014] The real-time compression pressure during the packaging process is obtained, the difference between the real-time compression pressure and the pressure threshold is calculated, and the absolute value of the difference is taken as the compression pressure deviation value;

[0015] The electrolyte filling rate during the filling process is obtained, and the filling rate dispersion index within a period of time is calculated.

[0016] In a preferred embodiment, comprehensively analyzing multiple production process step parameters based on a regression analysis model and outputting a production equipment amplitude includes the following steps:

[0017] The management system comprehensively analyzes the material floating coefficient, compression pressure deviation value, filling speed discrete index and total vibration amplitude obtained after preprocessing based on the regression analysis model to obtain the amplitude of the production equipment. The function expression of the Logistic regression analysis model is: , where is the production equipment amplitude, is the error correction term, The value is 5.112. is the material floating coefficient, is the total vibration amplitude, is the compression pressure deviation value, is the speed dispersion index, , , , They are the regression coefficients of material floating coefficient, total vibration amplitude, compression pressure deviation value and velocity dispersion index, and all of them are greater than 0.

[0018] In a preferred embodiment, analyzing whether a lead-acid battery has a latent defect comprises the following steps:

[0019] After obtaining the production equipment amplitude, the production equipment amplitude is compared with a preset first defect threshold and a second defect threshold;

[0020] If the production equipment amplitude is ≤ the first defect threshold, it is analyzed that there is no latent defect in the lead-acid battery;

[0021] If the production equipment amplitude is greater than the first defect threshold, it is analyzed that the lead-acid battery has latent defects;

[0022] If the production equipment amplitude is greater than the first defect threshold, and the production equipment amplitude is less than or equal to the second defect threshold, it is analyzed that the lead-acid battery has a first-level latent defect;

[0023] If the production equipment amplitude is greater than the second defect threshold, it is analyzed that the lead-acid battery has a secondary latent defect.

[0024] In a preferred embodiment, the calculation logic of the material floating coefficient is:

[0025] The period when the real-time temperature is lower than the first temperature threshold is recorded as the material shrinkage warning period;

[0026] The period when the real-time temperature is higher than the second temperature threshold is recorded as the material expansion warning period;

[0027] The material floating coefficient is obtained by integrating the shrinkage warning period and the material expansion period.

[0028] In a preferred embodiment, after analyzing the data set through the trend analysis model, generating management assignments for all production equipment includes the following steps:

[0029] The data set includes the number of production equipment shutdowns, the number of lead-acid batteries with level 1 potential defects produced, and the number of lead-acid batteries with level 2 potential defects produced;

[0030] After analyzing the data set through the trend analysis model, management assignments are generated for all production equipment. The function expression is: , where Assign value to management, The number of times the production equipment stops running. To produce the number of secondary potential defective lead-acid batteries, To produce the number of first-level potential defective lead-acid batteries, , are the weight coefficients of the number of first-level potential defective lead-acid batteries produced and the number of second-level potential defective lead-acid batteries produced, respectively, and , .

[0031] In a preferred embodiment, the electrolyte filling speed during the filling process is obtained, and the filling speed dispersion index within a period of time is calculated. The calculation expression of the filling speed dispersion index is: , where , represents the number of sampling time periods, is a positive integer, represents the filling rate in the i-th sampling period, Indicates the average filling speed, Indicates the charging speed dispersion index.

[0032] The present invention also provides a production equipment data management system, including a process judgment module, a control module, an index detection module, an amplitude calculation module, a defect analysis module, an equipment analysis module, and a sorting management module;

[0033] Process judgment module: during product production, it determines the production process step of the product and obtains the parameters of the corresponding production process step;

[0034] Control module: When the parameters of a certain production process step exceed or fall below the corresponding threshold, the management system sends out a warning signal and controls the production equipment to stop running;

[0035] Index detection module: multiple indexes are tested on the product. If any index of the product fails to meet the standards, the management system will send a signal to the administrator that the product quality does not meet the standards.

[0036] Amplitude calculation module: If all indicators of the tested product are qualified, the management system obtains multiple production process step parameters of the production equipment, pre-processes the multiple production process step parameters, comprehensively analyzes the multiple production process step parameters based on the regression analysis model and outputs the amplitude of the production equipment;

[0037] Defect analysis module: compares the acquired production equipment amplitude with the preset first defect threshold and second defect threshold to analyze whether the product has latent defects and the severity of the product with latent defects. The first defect threshold is used to analyze whether the product has latent defects, and the second defect threshold is used to analyze the severity of the product's latent defects.

[0038] Equipment analysis module: When regularly maintaining all production equipment, obtain multiple product potential defect analysis results of production equipment, combine multiple analysis results with the number of times the production equipment stops running to establish a data set, and generate management values ​​for all production equipment after analyzing the data set through a trend analysis model;

[0039] Sorting management module: sort all production equipment from large to small according to the management assigned value, generate an equipment list, and maintain the production equipment in the positive order of the equipment list.

[0040] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0041] 1. When all indicators of the lead-acid battery are qualified, the management system of the present invention obtains multiple production process step parameters of the production equipment, pre-processes the multiple production process step parameters, and comprehensively analyzes the multiple production process step parameters based on the regression analysis model, and then outputs the production equipment amplitude, compares the obtained production equipment amplitude with the preset first defect threshold and the second defect threshold, analyzes whether there are latent defects in the lead-acid battery, and the severity of the latent defect lead-acid battery, the first defect threshold is used to analyze whether there are latent defects in the lead-acid battery, and the second defect threshold is used to analyze the severity of the latent defects in the lead-acid battery, and generates corresponding management strategies based on the analysis results and sends them to the administrator. The management system can effectively analyze whether there are latent defects in the lead-acid battery after production, and the quality analysis of the lead-acid battery is more accurate, further improving the quality of the lead-acid battery;

[0042] 2. When the present invention regularly maintains all production equipment, it obtains multiple analysis results of potential defects of lead-acid batteries in the production equipment, combines the multiple analysis results with the number of times the production equipment is stopped to establish a data set, and generates management values ​​for all production equipment after analyzing the data set through a trend analysis model. All production equipment are sorted from large to small according to the management values, and an equipment list is generated. The production equipment is maintained in the positive order of the equipment list, so that production equipment with a poor historical operating status is maintained first, thereby effectively improving the maintenance and management efficiency of the production equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0044] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Example 1: Please refer to Figure 1 As shown, a production equipment data management method described in this embodiment includes the following steps:

[0047] When the lead-acid battery is produced, the management system determines the production process step of the lead-acid battery and obtains the parameters of the corresponding production process step. The obtained parameters include:

[0048] Charging Current and Voltage: Monitors the current and voltage of charging equipment to ensure that design specifications are met when manufacturing lead-acid batteries.

[0049] Electrode material quality and size: Real-time monitoring of electrode material quality and size to ensure compliance with manufacturing requirements.

[0050] Lead Battery Case Temperature: Monitor the temperature of the lead battery case to prevent overheating or other temperature-related issues.

[0051] Electrolyte Composition: Real-time monitoring of electrolyte composition to ensure it meets specifications and remains consistent during production.

[0052] Packaging equipment parameters: including packaging temperature, pressure, packaging time and other parameters to ensure that the packaging process meets the design requirements.

[0053] Filling Rate: Monitors the rate at which the electrolyte is filled to ensure control and consistency of the filling process.

[0054] Lead-acid battery capacity and internal resistance: Real-time measurement of lead-acid battery capacity and internal resistance during the production process to ensure that lead-acid battery performance meets standards.

[0055] Equipment vibration and noise: Monitor equipment vibration and noise levels to ensure the stability and reliability of equipment operation.

[0056] Welding quality: Real-time monitoring of the quality of the welding process, including the connectivity and stability of the weld.

[0057] Electrolyte Charge and Discharge Process: Monitor the behavior of the electrolyte during charge and discharge to ensure lead battery performance and cycle life.

[0058] When the parameters of a certain production process step exceed or fall below the corresponding threshold, the management system sends out a warning signal and controls the production equipment to stop running. The administrator needs to manage the production equipment to restore it to normal before continuing the lead-acid battery production, including the following steps:

[0059] Real-time monitoring: Use sensors or monitoring equipment to monitor various parameters of production equipment in real time.

[0060] Parameter comparison: Compare the parameters monitored in real time with the set thresholds.

[0061] Trigger an alert: If a parameter exceeds or falls below a set threshold, the system triggers an alert signal.

[0062] Stop production equipment: The management system automatically controls production equipment to stop running to avoid further problems or damage.

[0063] Send warning information: Send warning information to administrators to inform them that the production equipment has stopped and provide relevant abnormal information.

[0064] Remote Monitoring: Provides administrators with the ability to remotely monitor and access systems so they can remotely view anomalies and perform preliminary diagnosis.

[0065] On-site inspection: The administrator goes to the production site to inspect and understand the causes of specific problems.

[0066] Fault diagnosis: Perform fault diagnosis on production equipment to determine the specific parameters and reasons that exceed or fall below the threshold.

[0067] Repair equipment: Administrators take necessary measures to repair production equipment and ensure it returns to normal working condition.

[0068] System unlock: The administrator uses the system unlock mechanism to allow production equipment to resume operation.

[0069] Recording and reporting: Record events, repair processes and related parameters for future quality traceability and analysis.

[0070] Continuous Monitoring: After normal operation is restored, the management system continues to monitor production equipment to ensure that parameters are within normal range.

[0071] After the lead-acid battery is produced, the management system performs multiple index tests on the lead-acid battery. If any index of the lead-acid battery fails to meet the quality standards, the management system sends a signal to the administrator that the lead-acid battery does not meet the quality standards, including the following steps:

[0072] Automatic testing: Use automatic testing equipment to test lead-acid batteries. The testing process may include physical parameter measurement, electrical performance testing, appearance inspection, etc.

[0073] Data collection: The detected data is transmitted to the management system for further analysis and processing.

[0074] Data analysis: Real-time analysis of test data is performed in the management system to determine whether the lead-acid battery meets the set qualification standards.

[0075] Abnormal detection: If any indicator is detected to be not up to standard, the system will mark the lead-acid battery as unqualified and trigger the subsequent processing flow.

[0076] Alarm signal: Send an alarm signal of substandard quality to the administrator or relevant staff to inform them that the lead-acid battery has failed the quality inspection.

[0077] Automatic sorting: The management system may automatically sort rejected lead-acid batteries for subsequent processing, such as repair, retesting or elimination.

[0078] Recording and traceability: The system records the test results of each lead-acid battery for quality traceability and analysis.

[0079] If all indicators of the lead-acid battery are qualified, the management system obtains multiple production process step parameters of the production equipment, pre-processes the multiple production process step parameters, comprehensively analyzes the multiple production process step parameters based on the regression analysis model and outputs the production equipment amplitude, compares the obtained production equipment amplitude with the preset first defect threshold and the second defect threshold, analyzes whether the lead-acid battery has latent defects, and the severity of the lead-acid battery with latent defects, the first defect threshold is used to analyze whether the lead-acid battery has latent defects, and the second defect threshold is used to analyze the severity of the latent defects of the lead-acid battery, and generates corresponding management strategies based on the analysis results and sends them to the administrator.

[0080] When all production equipment is regularly maintained, multiple lead-acid battery latent defect analysis results of the production equipment are obtained, and a data set is established by combining the multiple analysis results with the number of times the production equipment is stopped. After analyzing the data set through a trend analysis model, management values ​​are generated for all production equipment. All production equipment are sorted from large to small according to the management values, and an equipment list is generated. The production equipment is maintained in the positive order of the equipment list, so that production equipment with a poor historical operating status is maintained first, effectively improving the maintenance and management efficiency of the production equipment.

[0081] When all the indicators of the lead-acid battery are qualified, the management system obtains multiple production process step parameters of the production equipment, pre-processes the multiple production process step parameters, and outputs the production equipment amplitude after comprehensive analysis of the multiple production process step parameters based on the regression analysis model, and compares the obtained production equipment amplitude with the preset first defect threshold and the second defect threshold, analyzes whether the lead-acid battery has latent defects, and the severity of the lead-acid battery with latent defects, the first defect threshold is used to analyze whether the lead-acid battery has latent defects, and the second defect threshold is used to analyze the severity of the latent defects of the lead-acid battery, and generates corresponding management strategies based on the analysis results and sends them to the administrator. The management system can effectively analyze whether the lead-acid battery produced has latent defects, and the quality analysis of the lead-acid battery is more accurate, further improving the quality of the lead-acid battery.

[0082] When the present application regularly maintains all production equipment, it obtains the results of multiple potential defect analyses of lead-acid batteries in the production equipment, combines the multiple analysis results with the number of times the production equipment is stopped to establish a data set, and generates management values ​​for all production equipment after analyzing the data set through a trend analysis model. It also sorts all production equipment from large to small according to the management values, generates an equipment list, and maintains the production equipment in the positive order of the equipment list, so that production equipment with a poor historical operating status is maintained first, thereby effectively improving the maintenance and management efficiency of the production equipment.

[0083] Embodiment 2: If all indicators of the lead-acid battery are qualified, the management system obtains multiple production process step parameters of the production equipment, pre-processes the multiple production process step parameters, comprehensively analyzes the multiple production process step parameters based on the regression analysis model and outputs the production equipment amplitude, compares the obtained production equipment amplitude with the preset first defect threshold and the second defect threshold, analyzes whether the lead-acid battery has latent defects, and the severity of the lead-acid battery with latent defects, the first defect threshold is used to analyze whether the lead-acid battery has latent defects, the second defect threshold is used to analyze the severity of the latent defects of the lead-acid battery, and generates corresponding management strategies based on the analysis results and sends them to the administrator;

[0084] The management system obtains multiple production process step parameters of the production equipment, and preprocesses the multiple production process step parameters, including the following steps:

[0085] The management system obtains the temperature and compression pressure of the lead-acid battery during the packaging process, obtains the electrolyte filling speed of the lead-acid battery during the filling process, and obtains the total vibration amplitude in the entire production process;

[0086] The calculation expression for the total vibration amplitude in the entire production process is: , where is the total vibration amplitude, , Indicates the number of process steps in the production equipment, It indicates the vibration amplitude collected by the vibration sensor during the processing of the lead-acid battery in the ath process step. The larger the total vibration amplitude in the entire production process, the more likely the lead-acid battery is to have potential defects, specifically:

[0087] Loose materials: Strong vibrations may cause the materials inside the lead-acid battery to loosen, especially the components and connections of the lead-acid battery. Loose materials may cause instability in the internal structure of the lead-acid battery, thus affecting performance and safety.

[0088] Welding problems: Vibration may cause the breakage or poor connection of welding points, affecting the electrical performance of the lead-acid battery. This is critical for the connection and conductive performance of the lead-acid battery.

[0089] Electrode peeling: Strong vibration may cause the electrode material (such as the plate) to peel off, affecting the performance and life of the lead-acid battery. This may cause the capacity of the lead-acid battery to decrease or the internal resistance to increase.

[0090] Diaphragm damage: Vibration may cause additional stress on the diaphragm material within the lead-acid battery, causing damage to the diaphragm, which may lead to short circuits or other problems.

[0091] Uneven distribution of electrolyte: Strong vibration may cause uneven distribution of electrolyte inside the lead-acid battery, which may cause electrolyte leakage or other hidden problems.

[0092] Shell deformation: Vibration may cause deformation of the lead-acid battery shell, which may cause structural instability of the lead-acid battery and affect the performance and safety of the lead-acid battery.

[0093] Aging of solder joints: Long-term vibration may cause aging of solder joints, resulting in solder joint failure or poor connection.

[0094] The real-time temperature during the packaging process is obtained. If the real-time temperature is not within the stable temperature range, the time period when the real-time temperature is lower than the temperature range is recorded as the material shrinkage warning period, and the time period when the real-time temperature is higher than the temperature range is recorded as the material expansion period. The material shrinkage warning period and the material expansion period are integrated to obtain the material floating coefficient.

[0095] The calculation logic of the material floating coefficient is: the period when the real-time temperature is lower than the first temperature threshold is recorded as the material shrinkage warning period, at which time the material of the lead-acid battery will shrink, resulting in invisible internal damage to the modest lead-acid battery; the period when the real-time temperature is higher than the second temperature threshold is recorded as the material expansion warning period, at which time the material of the lead-acid battery will expand, resulting in invisible internal damage to the modest lead-acid battery;

[0096] The material floating coefficient is obtained by integrating the shrinkage warning period and the material expansion period. The expression is: ; is the material floating coefficient, is the real-time volume change of the lead-acid battery, This is the period of material expansion warning. The period of material shrinkage warning is larger. The larger the material floating coefficient is, the longer the material expands or shrinks due to temperature deviation during the packaging process, which will cause invisible internal damage to the lead-acid battery. Specifically:

[0097] Diaphragm damage: Temperature deviation may cause the diaphragm material in the lead-acid battery to expand or contract. If this change is too drastic or uneven, it may cause damage to the diaphragm and affect the performance and safety of the lead-acid battery.

[0098] Electrode material deformation: The electrode material (such as the plate) in the lead-acid battery may expand or contract under temperature changes. Long-term material deformation may cause structural problems inside the lead-acid battery and affect the stability of the electrode.

[0099] Sealing problem: Temperature deviation may cause the lead-acid battery packaging material to expand or contract, which in turn affects the sealing performance of the lead-acid battery. The reduction in sealing performance may lead to the intervention of the external environment, causing corrosion or other problems inside the lead-acid battery.

[0100] Changes in electrolyte volume: Temperature changes may cause changes in the electrolyte volume. If this change is not controlled, it may cause uneven distribution of electrolyte inside the lead-acid battery, leading to corrosion or other invisible damage.

[0101] Material aging: Long-term temperature deviation may cause aging of lead-acid battery materials, affecting the performance and life of the lead-acid battery.

[0102] Solder point problems: Temperature deviation may affect the solder points inside the lead-acid battery, causing the solder points to break or have poor connections, which in turn affects the electrical performance of the lead-acid battery.

[0103] The real-time compression pressure during the packaging process is obtained, the difference between the real-time compression pressure and the pressure threshold is calculated, and the absolute value of the difference is taken as the compression pressure deviation value. The calculation expression is: , where is the real-time compression pressure, is the pressure threshold, The larger the compression pressure deviation value during the packaging process of the lead-acid battery, the greater the real-time compression pressure is, which indicates that the real-time compression pressure is too large or too small, which will cause invisible internal damage to the lead-acid battery, specifically:

[0104] Damage to diaphragm: High pressure may cause additional stress to the diaphragm material in the lead-acid battery, causing tearing or damage to the diaphragm, thereby affecting the performance and safety of the lead-acid battery.

[0105] Electrode deformation: Excessive compression pressure may cause electrode materials (such as plates) to deform or be compressed. Long-term deformation may cause structural problems of the electrode and affect the performance of the lead-acid battery.

[0106] Sealing issues: High or low compression pressure may cause different degrees of expansion or contraction of the lead-acid battery packaging material, affecting the sealing performance of the lead-acid battery, which may lead to external environmental intervention and cause corrosion or other problems inside the lead-acid battery.

[0107] Lead-acid battery casing deformation: High pressure may cause deformation of the lead-acid battery casing, which may lead to structural instability of the lead-acid battery and further affect the performance and life of the lead-acid battery.

[0108] Solder point problems: High pressure may affect the solder points inside the lead-acid battery, causing the solder points to break or have poor connections, affecting the electrical performance of the lead-acid battery.

[0109] Electrolyte leakage: Excessive compression pressure may cause rupture of the lead-acid battery packaging material, thereby causing electrolyte leakage, which may cause damage to the internal structure of the lead-acid battery.

[0110] Aging of internal materials of lead-acid batteries: Long-term pressure deviation may cause aging of internal materials of lead-acid batteries, affecting the performance and life of lead-acid batteries.

[0111] Obtain the electrolyte filling rate during the filling process and calculate the filling rate dispersion index within a period of time;

[0112] The calculation expression of the filling speed dispersion index is: , where , represents the number of sampling time periods, is a positive integer, represents the filling rate in the i-th sampling period, Indicates the average filling speed, It indicates the dispersion index of filling speed. The larger the dispersion index of filling speed, the greater the fluctuation of filling speed of production equipment during electrolyte filling, which will lead to uneven distribution of electrolyte inside lead-acid battery, thus causing hidden problems, specifically:

[0113] Uneven capacity of lead-acid batteries: Uneven electrolyte distribution may lead to different electrolyte concentrations in different areas inside the lead-acid battery, which in turn affects the capacity distribution of the lead-acid battery. Some areas may be overcharged while other areas may be undercharged, resulting in a decrease in the overall capacity of the lead-acid battery.

[0114] Unstable internal resistance of lead-acid batteries: Uneven electrolyte distribution may cause uneven internal resistance of lead-acid batteries. The internal resistance in some areas may be higher, affecting the discharge performance and stability of the lead-acid battery.

[0115] Plate corrosion: Uneven distribution of electrolyte in lead-acid batteries may cause different degrees of corrosion on the plates in certain areas, affecting the life and performance of the lead-acid batteries.

[0116] Lead-acid battery temperature rise: Due to uneven electrolyte distribution, some areas may generate excessive heat due to overcharging, resulting in local temperature rise, which may cause thermal problems inside the lead-acid battery.

[0117] Electrolyte concentration changes: Uneven distribution may lead to uneven solute concentration in the electrolyte, which may trigger chemical reactions and produce adverse chemical effects.

[0118] Uneven pressure inside the lead-acid battery: Uneven distribution may cause uneven gas production inside the lead-acid battery, affecting the pressure balance of the lead-acid battery, which may cause leakage or other problems.

[0119] Comprehensively analyzing multiple production process step parameters based on the regression analysis model and outputting the production equipment amplitude includes the following steps:

[0120] The management system comprehensively analyzes the material floating coefficient, compression pressure deviation value, filling speed discrete index and total vibration amplitude obtained after preprocessing based on the regression analysis model to obtain the amplitude of the production equipment. The function expression of the Logistic regression analysis model is: , where is the production equipment amplitude, is the error correction term, The value is 1.112. is the material floating coefficient, is the total vibration amplitude, is the compression pressure deviation value, is the speed dispersion index, , , , are the regression coefficients of material floating coefficient, total vibration amplitude, compression pressure deviation value and velocity dispersion index, respectively, and , , , All are greater than 0;

[0121] in, It means that when the material floating coefficient, compression pressure deviation value, filling speed discrete index and total vibration amplitude influencing parameters do not exist, there are other factors that affect the quality of lead-acid batteries, such as environmental pollution degree, ambient temperature and other parameters, which will have a slight impact on the quality of lead-acid batteries;

[0122] Compare the acquired production equipment amplitude with the preset first defect threshold and second defect threshold to analyze whether there are latent defects in the lead-acid battery and the severity of the latent defects in the lead-acid battery. The first defect threshold is used to analyze whether there are latent defects in the lead-acid battery, and the second defect threshold is used to analyze the severity of the latent defects in the lead-acid battery. Generate a corresponding management strategy based on the analysis results and send it to the administrator;

[0123] After obtaining the production equipment amplitude, the production equipment amplitude is compared with a preset first defect threshold and a second defect threshold;

[0124] If the production equipment amplitude is ≤ the first defect threshold, it is analyzed that there is no latent defect in the lead-acid battery;

[0125] If the production equipment amplitude is greater than the first defect threshold, it is analyzed that the lead-acid battery has latent defects;

[0126] If the production equipment amplitude is greater than the first defect threshold, and the production equipment amplitude is less than or equal to the second defect threshold, it is analyzed that the lead-acid battery has a first-level latent defect;

[0127] If the production equipment amplitude is greater than the second defect threshold, it is analyzed that the lead-acid battery has a secondary latent defect;

[0128] Among them, the severity of the second-level latent defect is greater than the severity of the first-level latent defect;

[0129] Generating corresponding management policies based on the analysis results and sending them to the administrator includes the following steps:

[0130] If the lead-acid battery is analyzed to have a first-level latent defect, the generated management strategy is: make a judgment based on the use field of the lead-acid battery currently produced. If the use field supports the use of lead-acid batteries with a first-level latent defect, the batch of lead-acid batteries will be prompted to reduce the price; the service life of the lead-acid battery with a first-level latent defect will be slightly shortened, but it will not affect the normal use of the lead-acid battery. If the customer has an urgent need for the lead-acid battery produced that day, the lead-acid battery with a first-level latent defect can be appropriately reduced in price;

[0131] If the lead-acid battery is analyzed to have a secondary latent defect, the generated management strategy is: send a warning signal to the administrator, reminding the lead-acid battery that the lead-acid battery cannot be used. The lead-acid battery with a secondary latent defect will have low stability and shortened service life in the future and cannot be put into use. When the first lead-acid battery produced has a secondary latent defect, the production equipment needs to be managed.

[0132] During regular maintenance of all production equipment, obtain multiple lead-acid battery latent defect analysis results of the production equipment, combine the multiple analysis results with the number of production equipment shutdowns to establish a data set, and generate management values ​​for all production equipment after analyzing the data set through a trend analysis model, including the following steps:

[0133] The data set includes the number of production equipment shutdowns, the number of lead-acid batteries with level 1 potential defects produced, and the number of lead-acid batteries with level 2 potential defects produced;

[0134] After analyzing the data set through the trend analysis model, management assignments are generated for all production equipment. The function expression is: , where Assign value to management, The number of times the production equipment stops running. To produce the number of secondary potential defective lead-acid batteries, To produce the number of first-level potential defective lead-acid batteries, , are the weight coefficients of the number of first-level potential defective lead-acid batteries produced and the number of second-level potential defective lead-acid batteries produced, respectively, and , ;

[0135] From the function expression of management assignment, it can be seen that the number of times the production equipment stops running is the main influencing parameter of management assignment, that is, the more times the production equipment stops running, the more it needs to be prioritized for maintenance management.

[0136] All production equipment are sorted from large to small according to the management assignment, and an equipment list is generated. The production equipment is maintained in the positive order of the equipment list, so that the production equipment with poor historical operating status is maintained first, effectively improving the maintenance management efficiency of the production equipment, including the following steps:

[0137] After obtaining the management values ​​of all production equipment in the factory, all production equipment are sorted from large to small according to the management values, and an equipment list is generated. The production equipment is maintained in the positive order of the equipment list.

[0138] Embodiment 3: A production equipment data management system described in this embodiment includes a process judgment module, a control module, an index detection module, an amplitude calculation module, a defect analysis module, an equipment analysis module, and a sorting management module;

[0139] Process judgment module: during the production of lead-acid batteries, it judges the production process step of the lead-acid batteries, obtains the parameters of the corresponding production process step, and sends the parameters of the process step to the control module;

[0140] Control module: When the parameters of a certain production process step exceed or fall below the corresponding threshold, the management system sends out a warning signal and controls the production equipment to stop running. The administrator needs to manage the production equipment to restore it to normal before continuing the lead-acid battery production. After the lead-acid battery production is completed, the indicator detection module is awakened and the control result is sent to the equipment analysis module;

[0141] Index detection module: multiple index detection is performed on the lead-acid battery. If any index of the lead-acid battery is found to be unqualified, the management system sends a signal to the administrator that the lead-acid battery quality does not meet the standard, and the index detection result is sent to the amplitude calculation module;

[0142] Amplitude calculation module: If all indicators of the lead-acid battery are qualified, the management system obtains multiple production process step parameters of the production equipment, pre-processes the multiple production process step parameters, and comprehensively analyzes the multiple production process step parameters based on the regression analysis model, and then outputs the production equipment amplitude, which is sent to the defect analysis module;

[0143] Defect analysis module: compares the acquired production equipment amplitude with the preset first defect threshold and second defect threshold, analyzes whether the lead-acid battery has latent defects and the severity of the lead-acid battery with latent defects. The first defect threshold is used to analyze whether the lead-acid battery has latent defects, and the second defect threshold is used to analyze the severity of the latent defects of the lead-acid battery. According to the analysis results, a corresponding management strategy is generated and sent to the administrator, and the analysis results are sent to the equipment analysis module;

[0144] Equipment analysis module: When regularly maintaining all production equipment, obtain multiple lead-acid battery latent defect analysis results of the production equipment, combine the multiple analysis results with the number of times the production equipment stops running to establish a data set, analyze the data set through the trend analysis model, and generate management assignments for all production equipment. The management assignments are sent to the sorting management module;

[0145] Sorting management module: sort all production equipment from large to small according to the management assignment, generate an equipment list, and maintain the production equipment in the positive order of the equipment list, so as to effectively improve the maintenance management efficiency of the production equipment with poor historical operating status.

[0146] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0147] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0148] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A production equipment data management method, characterized in that: The management method comprises the following steps: When a product is being produced, the management system determines the production process step that the product is in and obtains the parameters of the corresponding production process step. When the parameters of a production process step exceed or fall below the corresponding threshold value, the management system issues a warning signal and controls the production equipment to stop running. After the product is produced, the management system will test the product for multiple indicators. If any indicator of the product fails to meet the quality standards, the management system will send a signal to the administrator that the product quality does not meet the standards. If all indicators of the tested product are qualified, the management system obtains multiple production process step parameters of the production equipment, pre-processes the multiple production process step parameters, comprehensively analyzes the multiple production process step parameters based on the regression analysis model and outputs the amplitude of the production equipment; Compare the acquired production equipment amplitude with the preset first defect threshold and second defect threshold to analyze whether the product has latent defects and the severity of the latent defective product; When all production equipment is regularly maintained, multiple product potential defect analysis results of the production equipment are obtained, and multiple analysis results are combined with the number of production equipment shutdowns to establish a data set. After analyzing the data set through a trend analysis model, management values ​​are generated for all production equipment. All production equipment are sorted from large to small according to the management values ​​to generate an equipment list, and the production equipment is maintained in the positive order of the equipment list; The management system obtains multiple production process step parameters of the production equipment, and preprocesses the multiple production process step parameters, including the following steps: The management system obtains the temperature and compression pressure of the lead-acid battery during the packaging process, obtains the electrolyte filling speed of the lead-acid battery during the filling process, and obtains the vibration amplitude in the entire production process; The real-time temperature during the packaging process is obtained. If the real-time temperature is not within the stable temperature range, the time period when the real-time temperature is lower than the temperature range is recorded as the material shrinkage warning period, and the time period when the real-time temperature is higher than the temperature range is recorded as the material expansion period. The material shrinkage warning period and the material expansion period are integrated to obtain the temperature influence coefficient. The real-time compression pressure during the packaging process is obtained, the difference between the real-time compression pressure and the pressure threshold is calculated, and the absolute value of the difference is taken as the compression pressure deviation value; Obtain the electrolyte filling rate during the filling process and calculate the filling rate dispersion index within a period of time; Comprehensively analyzing multiple production process step parameters based on the regression analysis model and outputting the production equipment amplitude includes the following steps: The management system comprehensively analyzes the material floating coefficient, compression pressure deviation value, filling speed discrete index and total vibration amplitude obtained after preprocessing based on the regression analysis model to obtain the amplitude of the production equipment. The function expression of the Logistic regression analysis model is: , where is the production equipment amplitude, is the error correction term, The value is 5.

112. is the material floating coefficient, is the total vibration amplitude, is the compression pressure deviation value, is the speed dispersion index, , , , They are the regression coefficients of material floating coefficient, total vibration amplitude, compression pressure deviation value and velocity dispersion index, and they are all greater than 0; Analyzing whether a lead-acid battery has latent defects includes the following steps: After obtaining the production equipment amplitude, the production equipment amplitude is compared with a preset first defect threshold and a second defect threshold; If the production equipment amplitude is ≤ the first defect threshold, it is analyzed that there is no latent defect in the lead-acid battery; If the production equipment amplitude is greater than the first defect threshold, it is analyzed that the lead-acid battery has latent defects; If the production equipment amplitude is greater than the first defect threshold, and the production equipment amplitude is less than or equal to the second defect threshold, it is analyzed that the lead-acid battery has a first-level latent defect; If the production equipment amplitude is greater than the second defect threshold, it is analyzed that the lead-acid battery has a secondary latent defect; The calculation logic of the material floating coefficient is: The period when the real-time temperature is lower than the first temperature threshold is recorded as the material shrinkage warning period; The period when the real-time temperature is higher than the second temperature threshold is recorded as the material expansion warning period; The material floating coefficient is obtained by integrating the shrinkage warning period and the material expansion period; After analyzing the data set through the trend analysis model, management assignments are generated for all production equipment, including the following steps: The data set includes the number of production equipment shutdowns, the number of lead-acid batteries with level 1 potential defects produced, and the number of lead-acid batteries with level 2 potential defects produced; After analyzing the data set through the trend analysis model, management assignments are generated for all production equipment. The function expression is: , where Assign value to management, The number of times the production equipment stops running. To produce the number of secondary potential defective lead-acid batteries, To produce the number of first-level potential defective lead-acid batteries, , are the weight coefficients of the number of first-level potential defective lead-acid batteries produced and the number of second-level potential defective lead-acid batteries produced, respectively, and , .

2. A production equipment data management method according to claim 1, characterized in that: The electrolyte filling speed during the filling process is obtained, and the filling speed dispersion index within a period of time is calculated. The calculation expression of the filling speed dispersion index is: , where , represents the number of sampling time periods, is a positive integer, represents the filling rate in the i-th sampling period, Indicates the average filling speed, Indicates the charging speed dispersion index.

3. A production equipment data management system, used to implement the management method according to any one of claims 1-2, characterized in that: It includes process judgment module, control module, index detection module, amplitude calculation module, defect analysis module, equipment analysis module and sorting management module; Process judgment module: during product production, it determines the production process step of the product and obtains the parameters of the corresponding production process step; Control module: When the parameters of a certain production process step exceed or fall below the corresponding threshold, the management system sends out a warning signal and controls the production equipment to stop running; Index detection module: multiple indexes are tested on the product. If any index of the product fails to meet the standards, the management system will send a signal to the administrator that the product quality does not meet the standards. Amplitude calculation module: If all indicators of the tested product are qualified, the management system obtains multiple production process step parameters of the production equipment, pre-processes the multiple production process step parameters, comprehensively analyzes the multiple production process step parameters based on the regression analysis model and outputs the amplitude of the production equipment; Defect analysis module: compares the acquired production equipment amplitude with the preset first defect threshold and second defect threshold to analyze whether the product has latent defects and the severity of the product with latent defects. The first defect threshold is used to analyze whether the product has latent defects, and the second defect threshold is used to analyze the severity of the product's latent defects. Equipment analysis module: When regularly maintaining all production equipment, obtain multiple product potential defect analysis results of production equipment, combine multiple analysis results with the number of times the production equipment stops running to establish a data set, and generate management values ​​for all production equipment after analyzing the data set through a trend analysis model; Sorting management module: sort all production equipment from large to small according to the management assigned value, generate an equipment list, and maintain the production equipment in the positive order of the equipment list.

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