Lithium extraction process batch management method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a lithium extraction process batch management method and device, electronic equipment and a storage medium, and relates to the technical field of lithium carbonate production. The method comprises the following steps: for each intermediate process, acquiring a first state parameter of a current liquid storage tank corresponding to the intermediate process based on a sensor group; and inputting the first state parameter into a preset flow compensation model to obtain the real-time corrected outflow volume of the current liquid storage tank. And if the real-time corrected outflow volume reaches a preset batch standard value, creating a batch for the liquid flowing out this time according to the first state parameter, the current process number, the batch serial number, the weight corresponding to the real-time corrected outflow volume and the current time. According to the invention, accurate batch division can be automatically carried out on the liquid in the lithium extraction process, and the batch management efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of lithium carbonate production technology, and more specifically, to a batch management method, apparatus, electronic equipment, and storage medium for lithium extraction processes. Background Technology

[0002] Lithium carbonate production mainly relies on two processes: lithium extraction from ore and lithium extraction from brine in salt lakes. With the expansion of production scale, ensuring product quality traceability, especially batch management of liquid semi-finished products and materials, has become a challenge that the industry needs to address.

[0003] Traditional methods often only allow for rough batch division based on the processing workshop and rely on manual experience and approximate time points to distinguish different batches. This batch division method is not precise enough and its efficiency needs to be improved. Summary of the Invention

[0004] The present invention aims to, for example, provide a batch management method, apparatus, electronic device, and storage medium for lithium extraction processes, which can at least partially solve the aforementioned technical problems.

[0005] The embodiments of the present invention can be implemented as follows: In a first aspect, embodiments of the present invention provide a batch management method for a lithium extraction process, used in a lithium carbonate production process, wherein the lithium carbonate production process includes multiple intermediate steps; the method includes: For each of the intermediate steps, the first state parameters of the current liquid storage tank corresponding to the intermediate step are obtained based on the sensor group; The first state parameter is input into a preset flow compensation model to obtain the real-time corrected outflow of the current liquid storage tank; If the real-time corrected outflow reaches the preset batching standard value, then a batch is created for the liquid outflowing this time based on the first status parameter, the current process number, the batch number, the weight corresponding to the real-time corrected outflow, and the current time.

[0006] Optionally, the first state parameters include the measured outflow rate, liquid temperature, and liquid viscosity. The step of inputting the first state parameters into a preset flow compensation model to obtain the real-time corrected outflow rate of the current liquid storage tank includes: Based on a preset flow compensation function, the real-time corrected flow rate is determined according to the measured outflow rate, the liquid temperature, and the liquid viscosity. The preset flow compensation function is: Q 修正 =Q 原始 ×[1+α(T T0)+β(η η0)]×γ(t) Among them, Q 修正 For the real-time corrected outflow, Q 原始 The measured outflow rate is denoted as α, the temperature compensation coefficient is denoted as T, the liquid temperature is denoted as T0, the preset reference temperature is denoted as β, the viscosity compensation coefficient is denoted as η, the liquid viscosity is denoted as η0, and the time decay factor is γ(t).

[0007] Optionally, the method further includes: The liquid level value of the subsequent liquid storage tank is obtained based on the liquid level sensor, wherein the subsequent liquid storage tank is an adjacent liquid storage tank connected to the current liquid storage tank through a pipeline, and is located after the process in which the current liquid storage tank is located; If the liquid level value is not zero, when a new batch of liquid flows into the subsequent liquid storage tank, a mixed batch is created for the liquid flowing out of the subsequent liquid storage tank, and the original batch of the mixed batch is recorded. The original batch includes the original batch of liquid in the subsequent liquid storage tank and the batch of newly flowing liquid.

[0008] Optionally, the method further includes: The corrected inflow rate of the newly flowing liquid into the subsequent liquid storage tank is determined based on the preset flow compensation model. The first weight of the original liquid is determined based on the liquid level value in the subsequent liquid storage tank; The second weight of the newly flowing liquid is determined based on the corrected inflow rate in the subsequent liquid storage tank; The first weight and the second weight are recorded in the corresponding original batches.

[0009] Optionally, the method further includes: Real-time monitoring of whether any abnormalities occur in each of the intermediate processes; If so, the intermediate process in which the aforementioned abnormal situation occurs is identified as the target intermediate process; The system controls the target liquid storage tank corresponding to the target intermediate process to stop the inflow of liquid, and creates an abnormal batch based on the liquid that has already flowed into the target liquid storage tank.

[0010] Optionally, the method further includes: In response to terminal operation, a manual batching instruction is obtained, wherein the manual batching instruction includes specifying intermediate processes; Based on the manual batching instruction, a manual batch is created for the liquid flowing out of the specified liquid storage tank corresponding to the specified intermediate process.

[0011] Optionally, the method further includes: Receive a batch backtracking instruction, wherein the batch backtracking instruction includes the target finished product batch; Determine the original batch recorded in the target finished product batch; Batch backtracking is performed on the target finished product based on each of the original batches.

[0012] Secondly, embodiments of the present invention provide a batch management device for a lithium extraction process, used in a lithium carbonate production process, wherein the lithium carbonate production process includes multiple intermediate steps; the batch management device for the lithium extraction process includes: The first state parameter acquisition unit is used to acquire the first state parameter of the current liquid storage tank corresponding to each intermediate process based on the sensor group. The real-time corrected outflow determination unit is used to input the first state parameter into a preset flow compensation model to obtain the real-time corrected outflow of the current liquid storage tank. The batch creation unit is used to create a batch of liquid for this outflow based on the first status parameter, the current process number, the batch number, the weight corresponding to the real-time corrected outflow, and the current time when the real-time corrected outflow reaches the preset batching standard value.

[0013] Thirdly, embodiments of the present invention provide an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of any of the methods described above.

[0014] Fourthly, embodiments of the present invention provide a computer-readable storage medium, the computer-readable storage medium including a computer program, wherein the computer program, when executed, controls a server where the computer-readable storage medium is located to implement the steps of any of the methods described above.

[0015] The beneficial effects of the embodiments of the present invention include, for example: By employing sensor arrays to acquire the initial state parameters of the corresponding liquid storage tank at each intermediate process, and inputting these parameters into a preset flow compensation model to determine the real-time corrected outflow rate for each tank, the accuracy of subsequent batch division is ensured. When the real-time corrected outflow rate reaches the preset batching standard value, the initial state parameters, current process number, batch number, weight corresponding to the real-time corrected outflow rate, and current time are automatically recorded into the batch created for this outflow, ensuring data traceability and improving batch management efficiency. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A block diagram illustrating an electronic device according to an embodiment of the present invention; Figure 2 A flowchart illustrating the steps of a batch management method for lithium extraction process provided in this embodiment of the invention; Figure 3 A flow chart of a lithium carbonate production process provided in an embodiment of the present invention; Figure 4 A schematic diagram of a sensor array provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of a batch management device for lithium extraction process provided in an embodiment of the present invention.

[0018] Icons: 100 - Electronic device; 110 - Memory; 120 - Processor; 130 - Communication module; 300 - Lithium extraction process batch management device; 301 - First state parameter acquisition unit; 302 - Real-time correction outflow determination unit; 303 - Batch creation unit. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0020] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0021] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0022] Furthermore, the terms "first" and "second" are used only to distinguish descriptions and should not be interpreted as indicating or implying relative importance.

[0023] It should be noted that, where there is no conflict, the features in the embodiments of the present invention can be combined with each other.

[0024] Lithium carbonate production mainly relies on two processes: lithium extraction from ore and lithium extraction from brine in salt lakes. With the expansion of production scale, ensuring product quality traceability, especially batch management of liquid semi-finished products and materials, has become a pressing problem for the industry.

[0025] Currently, industries involved in the production of liquid semi-finished products generally lack an effective and accurate batch management method. The existing batch management approach primarily relies on calculating the time required for each individual processing step, working backwards from the time allotted for raw material movement between different production stages. However, this method cannot accurately trace quality when dealing with the complex production processes of liquid semi-finished products.

[0026] The flow paths of liquid semi-finished products in the production process are diverse and complex. They do not simply flow in pipelines, but also frequently pass through various equipment such as mixing tanks, reaction vessels, evaporators, mixers, and thickeners. Furthermore, the environmental conditions of the liquid vary significantly in different processes; its key properties, such as temperature and viscosity, change significantly as the process progresses. These changes further affect the flow rate and mixing degree of the liquid between equipment, making the entire flow process even more difficult to control.

[0027] A prominent issue during the processing of liquids in various stages of equipment is that liquids are often mixed in multiple batches. This means that the current batch of products may contain a mixture of different materials from multiple preceding processes. For example, in a mixing process, different liquid semi-finished products from the previous three processes may be simultaneously fed into the same equipment for mixing, resulting in a final batch of products that includes material components from all three preceding processes.

[0028] If the industry-standard batch processing logic is used at this point, it becomes impossible to clearly distinguish the precise correspondence between the current process and the materials processed in the previous process. This ambiguity creates significant difficulties in actual production management and quality traceability. Specifically, it is difficult to accurately trace the batch information of auxiliary materials added during processing from the final batch information of the product. This is because auxiliary materials may be added in batches across multiple different processes, and due to the mixing of batches, it is impossible to determine which final product batch a particular batch of auxiliary materials entered. Furthermore, it is difficult to confirm the accurate correspondence between the current process and the batches of the previous process, and it is unclear how the product of the current process was transformed from which batch of materials from the previous process.

[0029] Due to the limitations of the batch-based logic described above, it is difficult to effectively trace various quality-influencing factors that arise during processing. For example, when product quality issues arise, it could be due to equipment malfunctions, such as unstable stirring speed in the mixing tank leading to uneven liquid mixing; it could also be due to abnormalities in the auxiliary materials, such as substandard purity in a particular batch, resulting in impurities; or it could be due to abnormalities in the process itself, such as improper temperature control in the reactor, affecting the progress and outcome of the chemical reaction. However, the existing simple batch-based logic cannot link these possible causes to specific product batches, making it difficult to accurately identify the root cause of the quality problems.

[0030] In the complex process of lithium carbonate production, batch identification, tracking, and data management of liquid raw materials (such as sulfuric acid and hydrochloric acid, which are highly corrosive and chemically active substances) and semi-finished products (including intermediate products of different forms and purities such as clear liquid, purified solution, and wet lithium carbonate) face numerous challenges. These challenges restrict production efficiency and product quality, specifically as follows: 1. Lack of Systematic Batch Management: In traditional batch production models, there is a lack of scientific, precise, and systematic methods for batch classification of liquid materials. Due to the high fluidity and difficulty in precise segmentation and measurement of liquid materials, traditional methods often only allow for rough batch classification based on the processing workshop and rely on manual experience and approximate time points to distinguish different batches. This imprecise batch classification makes it difficult to accurately determine the specific raw materials, production process parameters, and other information of a particular batch of products during subsequent quality traceability. For example, when a batch of lithium carbonate products has quality problems, because it is impossible to accurately trace back to the corresponding liquid raw material batch, it is impossible to deeply analyze whether the problem lies in the quality of the raw materials themselves or in other factors affecting the production process. This leads to difficulties in quality traceability, making it hard to find the root cause of the problem and take effective improvement measures.

[0031] 2. Incomplete Data Recording: The production of lithium carbonate involves numerous key parameters, such as the concentration of liquid raw materials, the temperature during production, and the impurity content in the reaction system. These parameters have a crucial impact on product quality. However, current technologies have significant shortcomings in data recording, failing to accurately and in real-time correlate these key parameters with specific batches. While some parameters may be monitored and recorded periodically or irregularly during production, this data often exists in isolation, without establishing an effective correlation with specific batches. This makes it impossible to comprehensively and accurately understand the various conditions and environments experienced by each batch during production, hindering in-depth and detailed analysis and evaluation of product quality. For example, when analyzing the purity of a particular batch of lithium carbonate, the lack of complete records of key parameters such as temperature and impurity content during the batch's production process makes it impossible to accurately determine the extent of these factors' impact on product purity, thus affecting the accuracy and reliability of the quality analysis.

[0032] 3. Difficulty in Guaranteeing Material Uniqueness: During the lithium carbonate production process, batch mixing is prone to occur due to the numerous production stages, complex equipment, and personnel operations involved. Under traditional production management models, batch identification and management of semi-finished products are not strict or standardized enough, lacking effective anti-mixing measures. For example, during the storage, transportation, and transfer of semi-finished products, unclear labeling or poor management can lead to mixing of different batches, thus compromising material uniqueness. Once batch mixing occurs, it severely impacts the consistency of the final product's quality. Because different batches of semi-finished products may differ in quality characteristics, mixing can cause significant fluctuations in the quality of the final product, failing to meet market demands for stable product quality. For instance, in the production of high-purity lithium carbonate, if batches of semi-finished products of different purities are mixed, the purity of the final product will fail to meet standards, affecting product performance and application areas.

[0033] 4. Low Traceability Efficiency: When quality problems occur during lithium carbonate production, quickly and accurately locating the problematic batch is crucial for resolution. However, current traceability technology is extremely inefficient. Due to the lack of systematic batch management and complete data records, investigating problems requires significant manpower and time to collect, organize, and analyze various relevant information. Staff may need to review numerous production records, test reports, and interview relevant operators to gradually narrow down the problematic batches. This process is not only time-consuming but also susceptible to human factors, leading to inaccurate results. For example, if a product quality issue arises, it may require personnel from multiple departments to spend several days or even weeks investigating, which not only increases production costs but also delays product delivery, impacting the company's product competitiveness.

[0034] In addition, conventional batching methods typically lack dynamic compensation mechanisms. In actual production, due to various factors such as fluctuations in raw material quality, changes in equipment performance, and alterations in environmental conditions, the production process is often not entirely stable. Conventional batching methods cannot adjust batch segmentation strategies in a timely manner according to these actual changes, leading to discrepancies between batch segmentation results and actual production conditions, thus affecting the accuracy and effectiveness of batch management.

[0035] Based on the above, embodiments of the present invention provide a batch management method, apparatus, electronic device, and storage medium for lithium extraction processes, which can effectively alleviate the aforementioned technical problems.

[0036] Please refer to Figure 1 This is a block diagram of an electronic device 100 provided in this application. The electronic device 100 can be a data processing device, and this embodiment does not limit this. The electronic device 100 includes a memory 110, a processor 120, and a communication module 130. The memory 110, processor 120, and communication module 130 are electrically connected directly or indirectly to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines.

[0037] The memory 110 is used to store programs or data. The memory 110 may be, but is not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.

[0038] The processor 120 is used to read / write data or programs stored in memory and to perform corresponding functions.

[0039] The communication module 130 is used to establish a communication connection between the server and other communication terminals through the network, and to send and receive data through the network.

[0040] It should be understood that, Figure 1 The structure shown is only a schematic diagram of the electronic device 100. The electronic device 100 may also include components that are larger than... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown. Figure 1 The components shown can be implemented using hardware, software, or a combination thereof. This electronic device 100 can be integrated into other devices or configured as a standalone device.

[0041] Corresponding to electronic device 100, this embodiment of the invention provides a batch management method for lithium extraction processes, which can be applied to electronic device 100 for controlling access to an authentication server, wherein the authentication server is connected to the terminal via a router. The method includes, for example... Figure 2 The following steps are shown: Step S110: For each intermediate process, obtain the first state parameter of the current liquid storage tank corresponding to the intermediate process based on the sensor group.

[0042] Step S120: Input the first state parameter into the preset flow compensation model to obtain the real-time corrected outflow of the current liquid storage tank.

[0043] Step S130: If the real-time corrected outflow reaches the preset batching standard value, then create a batch for the liquid outflowing this time based on the first status parameter, the current process number, the batch number, the weight corresponding to the real-time corrected outflow, and the current time.

[0044] In step S110, for each intermediate process, the first state parameter of the current liquid storage tank corresponding to the intermediate process is obtained based on the sensor group.

[0045] like Figure 3 The diagram shows the process flow for lithium carbonate extraction. The steps requiring pipeline transportation are primarily liquid-to-liquid conversions, each of which can be considered an intermediate step. For each intermediate step's corresponding liquid storage tank, a configuration such as... Figure 4 The sensor array shown includes an inlet flow meter, an outlet flow meter, a viscometer, and a thermometer, used to obtain the state of the liquid in each liquid storage tank, as well as the outflow and outflow status between the two process liquid storage tanks.

[0046] For each intermediate process, a sensor array can be used to acquire the first state parameters of the liquid storage tank. The liquid storage tank whose first state parameters are currently acquired is the current liquid storage tank. The first state parameters can be parameters acquired by each sensor in the sensor array, such as liquid viscosity, liquid temperature, etc.

[0047] In step S120, the first state parameter is input into a preset flow compensation model to obtain the real-time corrected outflow of the current liquid storage tank.

[0048] Because changes in liquid temperature affect its viscosity, the measured flow rate of viscous liquids flowing through the flowmeter may be lower than expected. Different batches of raw materials may have slight differences in their inherent properties (such as density). Furthermore, sensors themselves develop errors over time, causing the measured values ​​to gradually deviate from the true values. Therefore, a pre-trained flow compensation model can be set up. After the sensor array acquires the initial state parameters of the current liquid storage tank, these parameters are input into the pre-trained flow compensation model to overcome the above problems and obtain a more accurate flow rate value, i.e., real-time correction of the outflow rate. It can be understood that the pre-trained flow compensation model can obtain the real-time corrected inflow rate based on a similar principle; it only requires replacing the data measured by the outlet flowmeter in the initial state parameters with the data measured by the inlet flowmeter.

[0049] Optionally, the first state parameters include the measured outflow rate, liquid temperature, and liquid viscosity. The step of inputting the first state parameters into a preset flow compensation model to obtain the real-time corrected outflow rate of the current liquid storage tank includes: Based on a preset flow compensation function, the real-time corrected flow rate is determined according to the measured outflow rate, the liquid temperature, and the liquid viscosity.

[0050] The preset flow compensation function is: Q 修正 =Q 原始 ×[1+α(T T0)+β(η η0)]×γ(t) Among them, Q 修正 For the real-time corrected outflow, Q 原始 The measured outflow rate is denoted as α, the temperature compensation coefficient is denoted as T, the liquid temperature is denoted as T0, the preset reference temperature is denoted as β, the viscosity compensation coefficient is denoted as η, the liquid viscosity is denoted as η0, and the time decay factor is γ(t).

[0051] As an optional implementation, the preset flow compensation function of the preset flow compensation model can be as described above. The first state parameters can be the measured outflow rate of the liquid storage tank as measured by the outlet flow meter, the liquid temperature as measured by the thermometer, and the liquid viscosity as measured by the viscometer. By inputting these parameters into the preset flow compensation model, the real-time corrected outflow rate can be obtained through the calculation of the preset flow compensation function.

[0052] For example, the flow meter's initial readings are: measured outflow of 1050.0 kg (converted weight), liquid temperature of 40℃, liquid viscosity of 1.8 mPa·s, sensor array having run continuously for 1000 hours, preset reference temperature of 25℃, preset reference viscosity of 1.2 mPa·s, temperature compensation coefficient of -0.005 (indicating that as temperature increases, the measured value tends to be larger), and viscosity compensation coefficient of -0.003 (indicating that as viscosity increases, the measured value tends to be larger). Substituting these data into the preset flow compensation function, the real-time corrected outflow is 922.0 kg.

[0053] In step S130, if the real-time corrected outflow reaches the preset batching standard value, a batch is created for the liquid outflowing this time based on the first status parameter, the current process number, the batch number, the weight corresponding to the real-time corrected outflow, and the current time.

[0054] After obtaining the real-time corrected outflow volume, it can be compared and judged with a pre-set batching standard value. If the real-time corrected outflow volume reaches the pre-set batching standard value, a batch creation operation is triggered. When creating a batch, the system can combine the currently obtained first status parameter, the current process number identifying the process location, the batch sequence number used to distinguish different batches within the same process, the corresponding weight converted from the real-time corrected outflow volume, and the current timestamp to generate a batch record with complete production information, thereby completing precise batch management of the outflowing liquid. For example, if the naming rule is: Batch_Date_Process Number_Batch Sequence Number, then the system creates the batch as Batch_20250611_Process1_003, and then marks the first status parameter, the corresponding weight converted from the real-time corrected outflow volume, etc., on this batch.

[0055] Optionally, the method further includes: The liquid level value of the subsequent liquid storage tank is obtained based on the liquid level sensor, wherein the subsequent liquid storage tank is an adjacent liquid storage tank connected to the current liquid storage tank through a pipeline, and is located after the process in which the current liquid storage tank is located.

[0056] If the liquid level value is not zero, when a new batch of liquid flows into the subsequent liquid storage tank, a mixed batch is created for the liquid flowing out of the subsequent liquid storage tank, and the original batch of the mixed batch is recorded. The original batch includes the original batch of liquid in the subsequent liquid storage tank and the batch of newly flowing liquid.

[0057] In some cases, there may be liquid in a liquid storage tank (subsequent liquid storage tank) that has not completely flowed into the next intermediate process, while new liquid flows in from the previous liquid storage tank (current liquid storage tank) that is connected to it by a pipeline, resulting in multiple batches of liquid being mixed together in the subsequent liquid storage tank.

[0058] In this scenario, a level sensor can be installed on the liquid storage tank to obtain the real-time level value of subsequent liquid storage tanks. When the level value of the subsequent liquid storage tank is detected to be non-zero, and a new batch of liquid begins to flow into that tank, batch mixing is determined to have occurred. For this mixing situation, a new mixed batch can be created for the liquid subsequently flowing out of that subsequent liquid storage tank.

[0059] At the same time, the system records the original batch information that constitutes this mixed liquid batch, that is, it clearly records the batch to which the original liquid in the subsequent liquid storage tank belonged before mixing, and the batch to which the newly flowing liquid belonged. For example, if there is already liquid residue from the previous batch (Batch_20250611_process1_002) in the liquid storage tank of process 2 (the subsequent liquid storage tank), when a new batch (Batch_20250611_process1_003) of liquid flows into the liquid storage tank of process 1 (the current liquid storage tank), the system will create a new mixed liquid batch for the mixed liquid flowing out of process 2, and record that its original batch comes from the above two batches.

[0060] Optionally, the method further includes: The corrected inflow rate of the newly flowing liquid into the subsequent liquid storage tank is determined based on the preset flow compensation model. The first weight of the original liquid is determined based on the liquid level in the subsequent liquid storage tank.

[0061] The second weight of the newly flowing liquid is determined based on the corrected inflow rate in the subsequent liquid storage tank. The first weight and the second weight are then recorded in their respective original batches.

[0062] To facilitate batch-by-batch traceability in case of finished product issues, the weight of each batch before and after mixing can be accurately measured and recorded in a mixed-liquid scenario. First, based on a pre-defined flow compensation model, the "corrected inflow rate" after adjustments for factors such as temperature and viscosity is calculated for the new liquid flowing into the subsequent liquid storage tank. Second, based on the real-time monitored liquid level in the subsequent liquid storage tank and information such as liquid density, the first weight of the original liquid in the tank before mixing is calculated. Simultaneously, based on the aforementioned corrected inflow rate, the second weight of the newly flowing liquid is determined. Finally, the calculated first and second weights are assigned to and recorded in their respective original batch records, thereby determining the ratio of new to old liquid in the mixed batch and achieving precise traceability of the weight of each component in the mixed batch.

[0063] Optionally, the method further includes: Real-time monitoring is performed to check for any abnormalities in each of the intermediate processes. If any abnormality occurs, the intermediate process in which the abnormality occurs is identified as the target intermediate process.

[0064] The system controls the target liquid storage tank corresponding to the target intermediate process to stop the inflow of liquid, and creates an abnormal batch based on the liquid that has already flowed into the target liquid storage tank.

[0065] In addition to the batch classification mentioned above, various abnormal situations are inevitable during the production process, such as a liquid data value exceeding the standard, blockage in the liquid delivery pipeline, equipment malfunction and shutdown, etc. These situations may result in the production of a batch of defective products. To address this, the operating status of each intermediate process can be monitored in real time to determine if any abnormalities have occurred. Once an abnormality is detected in an intermediate process, that process is designated as the target intermediate process. A control command is issued to stop the inflow of new liquid into the target liquid storage tank corresponding to the target intermediate process, thus isolating the impact of the abnormality. Simultaneously, based on the liquid that had already flowed into the target liquid storage tank before the abnormality occurred, a special abnormal batch is created, and the status and relevant parameters at the time of the abnormality are recorded to facilitate subsequent problem analysis and quality traceability.

[0066] Optionally, the method further includes: in response to a terminal operation, obtaining a manual batching instruction, the manual batching instruction including a specified intermediate process.

[0067] Based on the manual batching instruction, a manual batch is created for the liquid flowing out of the specified liquid storage tank corresponding to the specified intermediate process.

[0068] During product manufacturing, some special or non-standard situations require manual batching, such as temporary adjustments to the production plan, transitional production after equipment malfunctions, trial production stages, transitional periods between multiple product types, or situations where automatic batching logic cannot accurately identify boundaries. Therefore, the system can respond to user operations on the terminal by receiving manual batching instructions containing information about specified intermediate processes. Upon receiving this instruction, the system performs a batch creation operation on the specified liquid storage tank corresponding to the intermediate process specified in the instruction, generating a manual batch. This is useful for special production scenarios that automatic batching logic cannot cover or that require human intervention.

[0069] Optionally, the method further includes: receiving a batch backtracking instruction, the batch backtracking instruction including a target finished product batch.

[0070] Identify the original batches recorded in the target finished product batch. Perform batch backtracking on the target finished product based on each of the original batches.

[0071] When customer complaints, quality inspection anomalies, production process alarms, or market feedback occur, it is necessary to locate and trace the production batch corresponding to a specific product or material. At this time, the system receives a batch tracing command from the user containing information about the target finished product batch that needs to be traced. Upon receiving this command, the system identifies all the original batches associated with the target finished product batch record in the batch database. These original batches may originate from different preceding processes. Based on the flow and mixing relationships between these original batches, tracing is performed upstream level by level, thereby clearly reconstructing the complete production path and composition of the target finished product from raw materials to semi-finished products and then to finished products.

[0072] Based on the same inventive concept, such as Figure 5 As shown in the figure, an embodiment of the present invention provides a batch management device 300 for a lithium extraction process, used in a lithium carbonate production process, which includes multiple intermediate steps. The lithium extraction batch management device 300 includes: The first state parameter acquisition unit 301 is used to acquire the first state parameter of the current liquid storage tank corresponding to each intermediate process based on the sensor group.

[0073] The real-time corrected outflow determination unit 302 is used to input the first state parameter into a preset flow compensation model to obtain the real-time corrected outflow of the current liquid storage tank.

[0074] The batch creation unit 303 is used to create a batch of liquid for this outflow based on the first status parameter, the current process number, the batch number, the weight corresponding to the real-time corrected outflow, and the current time when the real-time corrected outflow reaches the preset batching standard value.

[0075] Regarding the lithium extraction process batch management device 300 mentioned above, the specific functions of each unit have been described in detail in the embodiments of the lithium extraction process batch management method provided in this specification, and will not be elaborated here.

[0076] Based on the same inventive concept, embodiments of this invention provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods in the aforementioned lithium extraction process batch management method.

[0077] The present invention has at least the following beneficial effects: 1. By using sensor arrays to acquire the first state parameters of the corresponding liquid storage tank for each intermediate process, and inputting these first state parameters into a preset flow compensation model to determine the real-time corrected outflow rate of each liquid storage tank, the accuracy of subsequent batch division is ensured. When the real-time corrected outflow rate reaches the preset batching standard value, the first state parameters, current process number, batch number, weight corresponding to the real-time corrected outflow rate, and current time are automatically recorded into the batch created for this outflow, ensuring the traceability of batch data and improving batch management efficiency.

[0078] 2. By establishing mixed liquid batches and determining the weight ratio, the batches of the original liquid in the liquid storage tank before and after mixing, as well as the batches of the newly flowing liquid, were clearly identified, which facilitated data backtracking.

[0079] 3. By setting batching strategies for abnormal batches and manual batches, it is easier to find abnormal situations in the production process, and it meets some special production scenarios that cannot be covered by automatic batching logic or require human intervention.

[0080] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of the invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0081] In addition, the functional modules in the various embodiments of the present invention can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0082] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0083] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A batch management method for lithium extraction processes, characterized in that, For use in a lithium carbonate production process, the lithium carbonate production process including multiple intermediate steps; the method includes: For each of the intermediate steps, the first state parameters of the current liquid storage tank corresponding to the intermediate step are obtained based on the sensor group; The first state parameter is input into a preset flow compensation model to obtain the real-time corrected outflow of the current liquid storage tank; If the real-time corrected outflow reaches the preset batching standard value, then a batch is created for the liquid outflowing this time based on the first status parameter, the current process number, the batch number, the weight corresponding to the real-time corrected outflow, and the current time.

2. The batch management method for lithium extraction process as described in claim 1, characterized in that, The first state parameters include the measured outflow rate, liquid temperature, and liquid viscosity. The step of inputting the first state parameters into a preset flow compensation model to obtain the real-time corrected outflow rate of the current liquid storage tank includes: Based on a preset flow compensation function, the real-time corrected flow rate is determined according to the measured outflow rate, the liquid temperature, and the liquid viscosity. The preset flow compensation function is: Q 修正 =Q 原始 ×[1+α(T T0)+β(η η0)]×γ(t) Among them, Q 修正 For the real-time corrected outflow, Q 原始 The measured outflow rate is denoted as α, the temperature compensation coefficient is denoted as T, the liquid temperature is denoted as T0, the preset reference temperature is denoted as β, the viscosity compensation coefficient is denoted as η, the liquid viscosity is denoted as η0, and the preset reference viscosity is denoted as γ(t).

3. The batch management method for lithium extraction process as described in claim 1, characterized in that, The method further includes: The liquid level value of the subsequent liquid storage tank is obtained based on the liquid level sensor, wherein the subsequent liquid storage tank is an adjacent liquid storage tank connected to the current liquid storage tank through a pipeline, and is located after the process in which the current liquid storage tank is located; If the liquid level value is not zero, when a new batch of liquid flows into the subsequent liquid storage tank, a mixed batch is created for the liquid flowing out of the subsequent liquid storage tank, and the original batch of the mixed batch is recorded. The original batch includes the original batch of liquid in the subsequent liquid storage tank and the batch of newly flowing liquid.

4. The batch management method for lithium extraction process as described in claim 3, characterized in that, The method further includes: The corrected inflow rate of the newly flowing liquid into the subsequent liquid storage tank is determined based on the preset flow compensation model. The first weight of the original liquid is determined based on the liquid level value in the subsequent liquid storage tank; The second weight of the newly flowing liquid is determined based on the corrected inflow rate in the subsequent liquid storage tank; The first weight and the second weight are recorded in the corresponding original batches.

5. The batch management method for lithium extraction process as described in claim 3, characterized in that, The method further includes: Real-time monitoring of whether any abnormalities occur in each of the intermediate processes; If so, the intermediate process in which the aforementioned abnormal situation occurs is identified as the target intermediate process; The system controls the target liquid storage tank corresponding to the target intermediate process to stop the inflow of liquid, and creates an abnormal batch based on the liquid that has already flowed into the target liquid storage tank.

6. The batch management method for lithium extraction process as described in claim 1, characterized in that, The method further includes: In response to terminal operation, a manual batching instruction is obtained, wherein the manual batching instruction includes specifying intermediate processes; Based on the manual batching instruction, a manual batch is created for the liquid flowing out of the specified liquid storage tank corresponding to the specified intermediate process.

7. The batch management method for lithium extraction process as described in claim 4, characterized in that, The method further includes: Receive a batch backtracking instruction, wherein the batch backtracking instruction includes the target finished product batch; Determine the original batch recorded in the target finished product batch; Batch backtracking is performed on the target finished product based on each of the original batches.

8. A batch management device for lithium extraction process, characterized in that, For use in lithium carbonate production processes, the lithium carbonate production process includes multiple intermediate steps; the lithium extraction process batch management device includes: The first state parameter acquisition unit is used to acquire the first state parameter of the current liquid storage tank corresponding to each intermediate process based on the sensor group. The real-time corrected outflow determination unit is used to input the first state parameter into a preset flow compensation model to obtain the real-time corrected outflow of the current liquid storage tank. The batch creation unit is used to create a batch of liquid for this outflow based on the first status parameter, the current process number, the batch number, the weight corresponding to the real-time corrected outflow, and the current time when the real-time corrected outflow reaches the preset batching standard value.

9. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a computer program, which, when executed, controls the server where the computer-readable storage medium is located to implement the steps of the method according to any one of claims 1 to 7.

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