Data integration system based on aluminum oxide factory

Abstract

The invention relates to the technical field of data factories, in particular to a data integration system based on an aluminum oxide factory. The operation monitoring module detects operation data of each production area; the regional analysis module determines the production type of each production region and determines a production management and control strategy; the analysis execution module calls the storage data to judge whether the actual production situation conforms to the production plan or not, or determines deviation index operation data conforming to the abnormal judgment condition; the tracking feedback module determines whether the reason which does not conform to the production plan is a dominant factor or an implicit factor, and performs tracking feedback on the production process of the production area; and the link optimization module determines whether the distribution and transportation links among the production areas need to be optimized or not, and sends out early warning information and corresponding reference strategies. According to the invention, accurate statistical analysis is carried out on each process of alumina production, production operation is tracked, and scheduling management is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of data factories, and in particular, to a data integration system based on an alumina factory. Background Art

[0002] The production process of an alumina factory is complex and involves multiple links, such as raw material grinding, digestion, sedimentation separation, roasting, etc. In the traditional mode, data interaction between each process mainly relies on manual scheduling or empirical judgment, resulting in lag and low efficiency in aspects such as production planning, quality control, and equipment management. In addition, market price fluctuations will also exacerbate the lag of production feedback and affect the accuracy of decision-making. Therefore, establishing a data integration system has become an important way to improve the intelligent and digital level of alumina factories.

[0003] Chinese Patent Application Publication No.: CN112180869A discloses a data integration system based on an alumina factory; the system includes the following modules: a data center, a logistics and energy flow system, a production auxiliary system, a video monitoring system, a digestion, evaporation, decomposition, sedimentation, roasting control system, a thermoelectric control system, a production visualization center, a digital assistant, and a one-way physical isolation system; among them, with the production visualization center as the core, the data center as the background guarantee, and the one-way physical isolation as the guarantee for production data security, modules including the logistics and energy flow system, the production auxiliary system, the video monitoring system, the digestion, evaporation, decomposition, sedimentation, roasting control system, the thermoelectric control system, and the digital assistant are integrated and fused. Thus, the following problems exist in the data integration system based on the alumina factory: The alumina production process is greatly affected by changes in working conditions. Existing data integration systems have insufficient analysis and prediction capabilities when dealing with periodic changes and abnormal working conditions, and it is difficult to optimize the production process in real time; Although the system has automation functions, it still needs to rely on manual experience to evaluate the actual production situation and analyze factors deviating from the plan, and it is unable to effectively organize scheduling for instruction optimization. Summary of the Invention

[0004] Therefore, the present invention provides a data integration system based on an alumina factory to overcome the problems of insufficient prediction ability and low analysis accuracy of evaluating production conditions in the existing data integration system during the alumina production process.

[0005] To achieve the above object, the present invention provides a data integration system based on an alumina factory, including: A factory function module, which is used to determine a complete factory operation environment, divide production areas and position each of the production areas; An operation monitoring module, which is connected to the factory function module, is used to detect the operation data of each production area and store the production data, quality data and equipment maintenance data of each production area; A regional analysis module, which is respectively connected to the factory function module and the operation monitoring module, is used to determine the production type of each production area according to the operation data, and determine the production control strategy according to the production type distribution; An analysis execution module, which is respectively connected to the regional analysis module and the operation monitoring module, is used to determine whether the actual production situation conforms to the production plan according to the production control strategy by retrieving the stored data, or to determine the deviation index operation data that meets the abnormal determination conditions according to the fluctuation degree of the deviation index operation data; A tracking feedback module, which is respectively connected to the analysis execution module and the operation monitoring module, is used to determine whether the reason for not conforming to the production plan is an obvious factor or a hidden factor according to the equipment maintenance data, and to track and feedback the production process of the production area; A link optimization module, which is respectively connected to the factory function module and the tracking feedback module, is used to determine whether the distribution and transportation link between production areas needs to be optimized according to the determined factors that do not conform to the production plan and the raw material out-of-production duration between processes, and issue a warning message and corresponding reference strategies.

[0006] Further, the regional analysis module confirms the production type of the production area according to the production area divided by the factory function module and the operation data of each production area detected by the operation monitoring module; If any operation data of a single production area is within the corresponding operation range, the regional analysis module determines that the production type of the corresponding production area is the first production type; If any operation data of a single production area is not within the corresponding operation range, the regional analysis module determines that the production type of the corresponding production area is the second production type.

[0007] Further, the regional analysis module determines the production control strategy according to the production type distribution, If the production types of all production areas are the first production type, the regional analysis module determines that the production control strategy is to retrieve the production data, quality data and equipment maintenance data, and determine whether the actual production situation conforms to the production plan according to the retrieved data; If the production type of any production area is the second production type, the regional analysis module determines that the production control strategy is to determine the deviation index operation data that meets the abnormal determination conditions according to the fluctuation degree of the deviation index operation data.

[0008] Further, the area analysis module defines operation data below or exceeding the corresponding standard operation range as deviation index operation data, and the abnormal determination condition is that the data fluctuation of the deviation index operation data exceeds the normal range.

[0009] Further, the analysis execution module calculates the data variance based on the historical data of the deviation index operation data within the initial detection period; If the data variance is higher than the standard variance, the analysis execution module determines that the data fluctuation of the deviation index operation data exceeds the normal range, meets the abnormal determination condition, and reduces the calibration period of the sensor corresponding to the deviation index operation data and the sensors of the same functional type set in other production areas; If the data variance is lower than or equal to the standard variance, the analysis execution module determines that the data fluctuation of the deviation index operation data is within the normal range and does not meet the abnormal determination condition.

[0010] Further, the production plan includes the planned duration and the total demand, The analysis execution module predicts the total production volume of alumina within the planned duration based on the total amount of qualified alumina produced per unit time; If the predicted total production volume exceeds or is equal to the total demand of the production plan, the analysis execution module determines that the actual production situation meets the production plan; If the predicted total production volume is lower than the total demand of the production plan, the analysis execution module determines that the actual production situation does not meet the production plan.

[0011] Further, the tracking and feedback module determines whether the reason for the actual production situation not meeting the production plan is an obvious factor or a hidden factor based on the equipment maintenance data; If the maintenance frequency in the equipment maintenance data exceeds or is equal to the standard frequency, the tracking and feedback module determines that the reason for not meeting the production plan is an obvious factor and reduces the maintenance period in the equipment maintenance data; If the maintenance frequency in the equipment maintenance data is lower than the standard frequency, the tracking and feedback module determines that the reason for not meeting the production plan is a hidden factor.

[0012] Further, the tracking and feedback module conducts production operation tracking and feedback on the production processes of each production area, If the reason for not meeting the production plan is a hidden factor, the tracking and feedback module determines whether the theoretical maximum output can cover the demand output or verifies the refining and decomposition process based on whether there are production batches with unqualified alumina quality.

[0013] Further, the tracking and feedback module determines whether the theoretical maximum output can cover the demand output, If either the ore quality or the digestion process, or both, do not meet the standards, the tracking and feedback module determines that the theoretical maximum output fails to cover the required output in the production plan, marks the production area corresponding to the ore acceptance or the digestion process, and sends a marking signal. If both the ore quality and the digestion process meet the standards, the tracking and feedback module determines that the theoretical maximum output can cover the required output in the production plan, and the link optimization module determines whether the distribution and transportation link needs to be optimized.

[0014] Further, according to the positioning of the production area by the factory function module, the link optimization module detects the relative positions of each production area with respect to the production areas of subsequent processes. The link optimization module obtains the discharge times of raw materials in different processes and calculates the downtime of several raw materials between processes. If the average downtime is less than or equal to the average downtime mean under normal working conditions in the historical production data, the analysis and execution module determines that there is no abnormality in the production process and determines to send a planned warning message. If the average downtime is greater than the average downtime mean under normal working conditions in the historical production data, the analysis and execution module determines that there is an abnormality in the production process that needs to be optimized. Among them, if the downtime of any raw material is greater than or equal to the critical downtime, the analysis and execution module sends a downtime warning message and a reference strategy for the production area corresponding to the raw material downtime. The reference strategy is to increase the preparation speed of subsequent processes.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows. The production process of the alumina factory is complex and involves multiple links. The present invention first divides the multiple links corresponding to the production process into corresponding production areas, determines the production types of each production area by collecting on-site operation data and key equipment parameters, adopts corresponding production control strategies, evaluates the actual production situation accordingly, determines the reasons for not meeting the production plan, analyzes the factors deviating from the plan, tracks and feedbacks the production processes of the production areas, organizes and optimizes the distribution and transportation links according to the tracking results, ensures the completion of indicators and plans, realizes the dynamic adjustment and scheduling management of the production plan through a unified platform, reduces the deviation between the production plan and the actual execution, and improves the production efficiency.

[0016] Furthermore, in the production process of an alumina factory, the production situation of the current single area is affected by the corresponding production process in the previous production area. If there are fluctuations in the production status of the previous functional area, the production status of the current and subsequent functional areas will also be affected, resulting in a reduction in the final production quality or total production volume of alumina. In the present invention, the corresponding production processes are demarcated and separated by production areas, and by analyzing the operation data within the areas, the production status of the corresponding production processes can be judged accordingly. This avoids the confusion or unclear mutual influence of the corresponding data for determining the production status due to the same types of data that need to be detected in the production process, such as temperature and pressure, thereby improving the accuracy and convenience of determining the production status of a single process in an alumina factory.

[0017] Furthermore, for an alumina factory, the data interaction between processes mainly relies on manual scheduling or empirical judgment, resulting in problems such as lag and low efficiency in production planning, quality control, equipment management, etc. The present invention adopts different production control strategies according to the production types of production areas. On the one hand, it ensures that the efficiency of production planning and quality control can meet the target requirements, and on the other hand, it extracts and analyzes the operation data that deviates from the indicators. At the same time, due to reasons such as differences in sensor accuracy, unstable data collection, and large fluctuations in the parameters of operation data in processes such as digestion during the production process, it is difficult to guarantee the data quality, which directly affects the accuracy of data analysis and decision-making. By detecting the fluctuations of the operation data that deviates from the indicators and determining that the detection result of the sensor is inaccurate for calibration, the purpose is to eliminate the influence of the fluctuations of the operation data on the analysis and decision-making, further improve the accuracy of the analysis and judgment, and increase the adaptability of production decision-making, integrating production planning and equipment monitoring to achieve the intelligentization and high efficiency of the production process.

[0018] Furthermore, the output and quality of alumina production fluctuate greatly. When there are no problems in the production process, the present invention predicts in advance the total production volume of alumina within the planned duration based on the total amount of qualified alumina produced per unit time, judges whether the actual production situation conforms to the production plan, conducts quality control and plan supervision on the production process of the factory, significantly improving the production management efficiency of the production process. At the same time, when the determined actual production situation does not conform to the production plan, it determines the corresponding reasons as production equipment factors or production process factors based on the equipment maintenance data, providing information support for equipment control and production control, saving the time for analyzing and making decisions on the problem source, and further improving production efficiency and product quality.

[0019] Further, in the production process, the process before sedimentation separation determines the extraction efficiency of alumina, and the process after that determines the extraction quality of alumina. Among them, the quality of the ore in ore processing is uneven. The digestion process determines the extraction rate of alumina transferred from solid to solution. The ore quality and the extraction rate together determine the upper limit of the production volume of alumina that can be extracted. The refining and decomposition process determines the proportion of sodium aluminate in the solution decomposed into aluminum hydroxide precipitate. The impurities present in the precipitate affect the extraction quality of alumina. The present invention determines the standards for ore quality, digestion process, and refining and decomposition process through the aluminum-silicon ratio of the ore, the digestion rate, and the concentration of sodium aluminate in the mother liquor, and marks the production areas corresponding to the processes that do not meet the standards, providing information support for management decision-makers, realizing the refinement and visualization of the production process, and providing strong support for production optimization and equipment management.

[0020] Further, the present invention monitors and optimizes the storage, distribution, and transportation of raw materials between processes by positioning the production area, issues corresponding early warning information and reference strategies, strengthens the information support for production and operation management, improves the process operation rate, enables the production organization to be stable and efficient, thereby greatly increasing the output, realizes the real-time update of material balance and inventory data, and reduces the waste in the logistics link. Brief Description of the Drawings

[0021] Figure 1 It is the unit connection diagram of the data integration system based on the alumina factory in the embodiment of the present invention; Figure 2 It is the flow chart for determining the production type of the production area in the embodiment of the present invention; Figure 3 It is the flow chart for determining the production control strategy in the embodiment of the present invention; Figure 4 It is the flow chart for determining the cause factors that do not meet the production plan in the embodiment of the present invention. Detailed Embodiment

[0022] In order to make the purpose and advantages of the present invention clearer, the present invention will be further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0023] The preferred embodiments of the present invention will be described below with reference to the drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention and do not limit the protection scope of the present invention.

[0024] It should be noted that in the description of the present invention, the terms indicating the direction or positional relationship such as "upper", "lower", "left", "right", "inner", "outer", etc. are based on the direction or positional relationship shown in the drawings. This is only for convenience of description, rather than indicating or implying that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention.

[0025] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and defined, the terms "installation", "connection", and "coupling" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0026] Please refer to Figures 1-4 as shown Figure 1 which is the unit connection diagram of the data integration system based on the alumina factory in the embodiment of the present invention; Figure 2 which is the flow chart for determining the production type of the production area in the embodiment of the present invention; Figure 3 which is the flow chart for determining the production control strategy in the embodiment of the present invention; Figure 4 which is the flow chart for determining the cause factors of non - compliance with the production plan in the embodiment of the present invention.

[0027] The present invention provides a data integration system based on an alumina factory, including: A factory function module, which is used to determine the factory operation environment, divide the production area and locate each of the production areas; An operation monitoring module, which is connected to the factory function module and is used to detect the operation data of each production area and store the production data, quality data and equipment maintenance data of each production area; A region analysis module, which is respectively connected to the factory function module and the operation monitoring module, and is used to determine the production type of each production area according to the operation data and determine the production control strategy according to the production type distribution; An analysis execution module, which is respectively connected to the region analysis module and the operation monitoring module, and is used to determine whether the actual production situation conforms to the production plan according to the production control strategy by retrieving the stored data, or to determine the deviation index operation data that meets the abnormal determination conditions according to the fluctuation degree of the deviation index operation data; A tracking and feedback module, which is respectively connected to the analysis and execution module and the job monitoring module, is used to determine whether the reason for not meeting the production plan in the equipment maintenance data is an obvious factor or a hidden factor, and track and feedback the production processes in the production areas; A link optimization module, which is respectively connected to the factory function module and the tracking and feedback module, is used to determine whether the distribution and transportation links between production areas need to be optimized according to the determined factors not meeting the production plan and the several raw material out-of-production durations between processes, and issue warning information and corresponding reference strategies.

[0028] In this embodiment, the production process flow of the alumina factory includes ore treatment, pulp preparation, digestion process, sedimentation separation, refining and decomposition, roasting process, and mother liquor circulation; (1) Ore treatment: The bauxite goes through processes such as crushing and screening to ensure that the particle size meets the requirements of subsequent processes. At the same time, auxiliary materials such as limestone and sodium carbonate are added to adjust the mineral phase structure of the ore and improve the subsequent treatment efficiency; (2) Pulp preparation: The treated bauxite is mixed with dilute alkali solution and stirred to form a uniform pulp; (3) Digestion process: Through the pressurized high-temperature digestion method, the alumina in the bauxite is converted into sodium aluminate and dissolved in the solution; (4) Sedimentation separation: The digested pulp enters the sedimentation tank for solid-liquid separation, and the sodium aluminate solution in the solution and the undissolved residue (red mud) are naturally stratified; (5) Refining and decomposition: Remove the impurities in the sodium aluminate solution, cool and stir to decompose the sodium aluminate in the sodium aluminate solution into aluminum hydroxide precipitate and mother liquor; (6) Roasting process: Calcinate the aluminum hydroxide at a high temperature of 950 - 1200 °C to obtain alumina products; (7) Mother liquor circulation: Treat the mother liquor and return the treated mother liquor as a solvent to the pulp preparation process.

[0029] In this embodiment, the temperature range of the pressurized high-temperature digestion method in the digestion process is 240 - 260 °C, the pressure range is 3.5 - 4.5 MPa, and the refining and decomposition can adopt the seed method or the carbonation method.

[0030] In implementation, the factory function module divides the factory operation environment into several production areas corresponding to the production processes according to the various production processes of the alumina factory.

[0031] Specifically, the production process of the alumina factory is complex and involves multiple links. First, the present invention divides the multiple links corresponding to the production process into corresponding production areas. By collecting on-site operation data and key equipment parameters, it determines the production types of the respective production areas, correspondingly adopts production control strategies, evaluates the actual production situation accordingly, determines the reasons for non-compliance with the production plan, analyzes the factors deviating from the plan, tracks and feedbacks the production processes of the production areas, optimizes the organization of the distribution and transportation links according to the tracking results, ensures the completion of indicators and plans, realizes the dynamic adjustment and scheduling management of the production plan through a unified platform, reduces the deviation between the production plan and the actual execution, and improves production efficiency.

[0032] During the production process of the alumina factory, the area analysis module is used to confirm the production type of the production area according to the production areas divided by the factory function module and the operation data of each production area detected by the operation monitoring module; If any operation data of a single production area is within the corresponding operation interval, the area analysis module determines that the production type of the corresponding production area is the first production type; If any operation data of a single production area is not within the corresponding operation interval, the area analysis module determines that the production type of the corresponding production area is the second production type.

[0033] The determination condition for any operation data of a single production area to be within the corresponding operation interval is that the pulp concentration, pulp temperature, pulp pH value, digestion temperature, stirring temperature, stirring speed, sedimentation duration, and calcination temperature are all within the corresponding standard operation intervals; The determination condition for any operation data of a single production area not to be within the corresponding operation interval is that one or several of the pulp concentration, pulp temperature, pulp pH value, digestion temperature, stirring temperature, stirring speed, sedimentation duration, and calcination temperature are lower than or exceed the corresponding standard operation intervals.

[0034] In implementation, the standard operation intervals of each area are preset values determined according to the historical operation data corresponding to the functional types of the production areas.

[0035] Specifically, in the production process of an alumina factory, the production situation in the current single area is affected by the corresponding production process in the previous production area. If there are fluctuations in the production status of the previous functional area, the production status of the current and subsequent functional areas will also be affected, resulting in a reduction in the production quality or total production volume of the final alumina. The present invention demarcates and separates the corresponding production processes through production areas, and analyzes the operation data within the areas to correspondingly judge the production status of the corresponding production processes, avoiding confusion or unclear mutual influence of the corresponding data for determining the production status due to the same types of data that need to be detected in the production process, such as temperature and pressure. Thus, the accuracy and convenience of determining the production status of a single process in an alumina factory are improved.

[0036] If the production type of all production areas is the first production type, the area analysis module determines the production control strategy as follows: retrieve production data, quality data, and equipment maintenance data, and judge whether the actual production situation conforms to the production plan based on the retrieved data. If the production type of any production area is the second production type, the area analysis module determines the production control strategy as follows: determine the off - target operation data that meets the abnormal determination conditions according to the fluctuation degree of the off - target operation data. Specifically, the area analysis module defines the operation data below or beyond the corresponding standard operation range as off - target operation data, and the abnormal determination condition is that the data fluctuation of the off - target operation data exceeds the normal range.

[0037] In implementation, the analysis execution module calculates the data variance based on the historical data of the off - target operation data within the initial detection period. If the data variance is higher than the standard variance, the analysis execution module determines that the data fluctuation of the off - target operation data exceeds the normal range and meets the abnormal determination conditions, and reduces the calibration period of the sensor corresponding to the off - target operation data and the sensors of the same functional type set in other production areas. If the data variance is lower than or equal to the standard variance, the analysis execution module determines that the data fluctuation of the off - target operation data is within the normal range and does not meet the abnormal determination conditions. Among them, the standard variance is a preset value set according to the average variance of the historical data of the operation data within the corresponding standard operation range.

[0038] It can be understood that in processes such as digestion, if the data fluctuation of the detected off - target operation data exceeds the normal range, it can be determined that the detection result of the sensor is inaccurate, and calibration can be carried out. Specifically, the analysis execution module reduces the calibration period of the sensor corresponding to the off - target operation data and the sensors of the same functional type set in other production areas according to the ratio of the standard variance to the data variance.

[0039] Specifically, for alumina factories, the data interaction between processes mainly relies on manual scheduling or empirical judgment, resulting in lag and low efficiency in production planning, quality control, equipment management, etc. The present invention adopts different production control strategies according to the production types in the production areas. On the one hand, it ensures that the efficiency of production planning and quality control can meet the target requirements. On the other hand, it extracts and analyzes the operation data deviating from the indicators. At the same time, due to reasons such as differences in sensor accuracy, unstable data collection, and large parameter fluctuations in the operation data during processes such as digestion in the production process, it is difficult to guarantee the data quality, which directly affects the accuracy of data analysis and decision-making. By detecting the fluctuations of the operation data deviating from the indicators and determining that the detection results of the sensor are inaccurate for calibration, the purpose is to eliminate the influence of the fluctuations of the operation data on the analysis and decision-making, further improve the accuracy of the analysis and judgment, and increase the adaptability of production decisions. Integrate production planning and equipment monitoring to achieve the intelligentization and high efficiency of the production process.

[0040] The area analysis module determines the production control strategy as follows: retrieve the production data, quality data, and equipment maintenance data, and judge whether the actual production situation conforms to the production plan according to the stored data; The production plan includes the planned duration and the total demand.

[0041] The analysis and execution module predicts the total amount of alumina produced within the planned duration based on the total amount of qualified alumina produced per unit time. If the predicted total production amount exceeds or is equal to the total demand of the production plan, the analysis and execution module judges that the actual production situation conforms to the production plan; If the predicted total production amount is lower than the total demand of the production plan, the analysis and execution module judges that the actual production situation does not conform to the production plan.

[0042] Specifically, the analysis and execution module determines the production quality of the current production batch according to the quality data of the produced alumina. If the average sample purity of the produced alumina is greater than or equal to the purity standard, the analysis and execution module judges that the quality of the alumina in the current production batch meets the standard; If the average sample purity of the produced alumina is less than the purity standard, the analysis and execution module judges that the quality of the alumina in the current production batch does not meet the standard.

[0043] Among them, the purity standard is 98.5%, and the unit time can be daily, weekly, monthly, etc.

[0044] In implementation, the tracking and feedback module determines whether the reason for the actual production situation not conforming to the production plan determined according to the equipment maintenance data is an obvious factor or a hidden factor; If the maintenance frequency in the equipment maintenance data is greater than or equal to the standard frequency, the tracking and feedback module determines that the reason for not meeting the production plan is an obvious factor, and reduces the maintenance cycle in the equipment maintenance data; If the maintenance frequency in the equipment maintenance data is lower than the standard frequency, the tracking and feedback module determines that the reason for not meeting the production plan is a hidden factor; Among them, the standard frequency is 4 times per month.

[0045] Specifically, the output and quality of alumina production fluctuate greatly. When there are no problems in the production process of the present invention, the total amount of qualified alumina produced within a unit time is used to predict in advance the total amount of alumina production within the planned time, and it is judged whether the actual production situation meets the production plan, and quality control and plan supervision are carried out on the production process of the factory, which significantly improves the production management efficiency of the production process. At the same time, when it is determined that the actual production situation does not meet the production plan, the corresponding reason is determined according to the equipment maintenance data as a production equipment factor or a production process factor, providing information support for equipment control and production control, saving the time for analyzing and making decisions on the problem source, and further improving production efficiency and product quality.

[0046] The tracking and feedback module conducts production operation tracking and feedback on the production processes of each production area; If the reason for not meeting the production plan is a hidden factor and there are no production batches with unqualified alumina quality, the tracking and feedback module determines whether the theoretical maximum output can cover the required output according to the ore quality in ore processing and the digestion process; If the reason for not meeting the production plan is a hidden factor, but there are production batches with unqualified alumina quality, the tracking and feedback module verifies the refining and decomposition process; Specifically, the tracking and feedback module extracts the aluminum-silicon ratio in the ore quality and digestion process inspection data; If one or both of the ore quality and the digestion process do not meet the standards, the tracking and feedback module determines that the theoretical maximum output fails to cover the required output in the production plan, marks the production area corresponding to the ore acceptance or the digestion process to send a marking signal, and conducts production operation tracking and feedback; If both the ore quality and the digestion process meet the standards, the tracking and feedback module determines that the theoretical maximum output can cover the required output in the production plan, and the link optimization module determines whether the distribution and transportation link needs to be optimized; In the implementation, the tracking and feedback module determines that the ore quality meets the standard if the aluminum-silicon ratio is greater than or equal to 5, and determines that the digestion process meets the standard if the digestion rate is greater than or equal to 90%.

[0047] Digestion rate = [1 - (A / S) 溶出液 ÷(A / S) 原矿浆 ×100%, where (A / S) 溶出液 represents the weight ratio of silicon oxide to aluminum oxide in the solid phase of the leaching solution, and (A / S) 原矿浆 represents the weight ratio of silicon oxide to aluminum oxide in the solid phase of the original ore pulp.

[0048] The tracking and feedback module verifies the sodium aluminate concentration in the mother liquor during the refining and decomposition process. If the sodium aluminate concentration in the mother liquor exceeds the standard range after the refining and decomposition process, the tracking and feedback module marks the production area corresponding to the refining and decomposition process to send a marking signal for production operation tracking and feedback; wherein, the standard range is 180 - 250 g / L.

[0049] Specifically, during the production process, the processes before sedimentation and separation determine the extraction efficiency of alumina, and the processes after that determine the extraction quality of alumina. The quality of the ore in ore processing is uneven. The leaching process determines the extraction rate of alumina from the solid to the solution. The ore quality and the extraction rate together determine the upper limit of the production volume of alumina that can be extracted. The refining and decomposition process determines the proportion of sodium aluminate in the solution decomposed into aluminum hydroxide precipitate. The impurities present in the precipitate affect the extraction quality of alumina. The present invention determines the standards for ore quality, leaching process, and refining and decomposition process through the ore aluminum-silicon ratio, leaching rate, and sodium aluminate concentration in the mother liquor, and marks the production areas corresponding to the processes that do not meet the standards accordingly, providing information support for the implementers of management decisions, realizing the refinement and visualization of the production process, and providing strong support for production optimization and equipment management.

[0050] Specifically, when the link optimization module determines that the theoretical maximum production volume can cover the required production volume in the production plan, according to the positioning of the production area by the factory function module, it detects the relative positions of each production area with respect to the production area of the subsequent process; Obtain the discharging times of the raw materials in different processes, calculate the downtime of several raw materials between processes, and the downtime of raw materials is equal to the sum of the static waiting time and the transportation time. If the average downtime is less than or equal to the average downtime mean value under normal working conditions in the historical production data, the analysis and execution module determines that there is no abnormality in the production process and determines to send a planned warning message; If the average downtime is greater than the average downtime mean value under normal working conditions in the historical production data, the analysis and execution module determines that there is an abnormality in the production process that needs to be optimized. If the downtime of any raw material is greater than or equal to the critical time, the analysis and execution module sends a downtime warning message and a reference strategy for the production area corresponding to the downtime of the raw material, and the reference strategy is to increase the preparation speed of the subsequent process; The critical duration is the maximum value of the off-the-job duration under normal working conditions in historical production data.

[0051] Specifically, the present invention locates the production area, monitors and optimizes the storage, distribution, and transportation of raw materials between processes, issues corresponding warning messages and reference strategies, strengthens the information support for production and operation management, improves the process operation rate, enables the production organization to be stable and efficient, thereby significantly increasing the output, realizes the real-time update of material balance and inventory data, and reduces the waste in the logistics link.

[0052] So far, the technical solution of the present invention has been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of the present invention.

[0053] The above are only the preferred embodiments of the present invention and are not used to limit the present invention; for those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A data integration system based on an alumina plant, characterized in that: include: A factory function module, which is used to determine the factory operating environment, divide the production areas and locate each of the production areas; An operation monitoring module, which is connected to the factory function module and is used to detect the operation data of each production area and store the production data, quality data and equipment maintenance data of each production area; A regional analysis module, which is connected to the factory function module and the operation monitoring module respectively, and is used to determine the production type of each production area according to the operation data, and determine the production control strategy according to the distribution of the production type; An analysis execution module, which is connected to the regional analysis module and the operation monitoring module respectively, and is used to retrieve the stored data to determine whether the actual production situation conforms to the production plan according to the production control strategy, or to determine the deviation index operation data that meets the abnormal determination conditions according to the fluctuation degree of the deviation index operation data; A tracking and feedback module, which is connected to the analysis execution module and the operation monitoring module respectively, and is used to determine whether the reason for not meeting the production plan is an explicit factor or an implicit factor based on the equipment maintenance data, and to track and feedback the production process in the production area; The link optimization module is connected to the factory function module and the tracking feedback module respectively, and is used to determine whether the distribution and transportation links between production areas need to be optimized based on the factors that are determined to be inconsistent with the production plan and the length of time that several raw materials are off-line between processes, and to issue early warning information and corresponding reference strategies.

2. The data integration system based on an alumina plant according to claim 1, characterized in that: The regional analysis module confirms the production type of the production area according to the production area divided by the factory function module and the operation data of each production area detected by the operation monitoring module; If any operation data of a single production area is within the corresponding operation interval, the regional analysis module determines that the production type of the corresponding production area is the first production type; If any operation data of a single production area is not within the corresponding operation interval, the regional analysis module determines that the production type of the corresponding production area is the second production type.

3. The data integration system based on an alumina plant according to claim 1, characterized in that: The regional analysis module determines the production control strategy according to the distribution of production types. If the production type of all production areas is the first production type, the regional analysis module determines the production control strategy as retrieving production data, quality data and equipment maintenance data, and judging whether the actual production situation meets the production plan based on the retrieved data; If the production type of any production area is the second production type, the regional analysis module determines the production control strategy as determining the deviation index operation data that meets the abnormality determination condition according to the fluctuation degree of the deviation index operation data.

4. The data integration system based on an alumina plant according to claim 3, characterized in that: The regional analysis module defines operation data that is lower than or exceeds the corresponding standard operation range as deviation index operation data, and the abnormality determination condition is that the data fluctuation of the deviation index operation data exceeds the normal range.

5. The data integration system based on an alumina plant according to claim 4, characterized in that: The analysis execution module calculates data variance based on historical data of the deviation index operation data within the initial detection period; If the data variance is higher than the standard variance, the analysis execution module determines that the data fluctuation of the deviation index operation data exceeds the normal range and meets the abnormality determination condition, and reduces the calibration period of the sensor corresponding to the deviation index operation data and the sensors of the same functional type set in other production areas; If the data variance is lower than or equal to the standard variance, the analysis execution module determines that the data fluctuation of the deviating index operation data is within the normal range and does not meet the abnormal determination condition.

6. The data integration system based on an alumina plant according to claim 3, characterized in that: The production plan includes the planned duration and the total demand. The analysis execution module predicts the total amount of aluminum oxide produced within the planned time period according to the total amount of aluminum oxide produced to meet the standard within the unit time period; If the predicted total production volume exceeds or is equal to the total production plan demand volume, the analysis execution module determines that the actual production situation is consistent with the production plan; If the predicted total production volume is lower than the total production plan requirement, the analysis execution module determines that the actual production situation does not conform to the production plan.

7. The data integration system based on an alumina plant according to claim 1, characterized in that: The tracking and feedback module determines the explicit or implicit factors that cause the actual production situation to fail to meet the production plan based on the equipment maintenance data, wherein: If the maintenance frequency in the equipment maintenance data exceeds or is equal to the standard frequency, the tracking feedback module determines that the reason for not meeting the production plan is a dominant factor, and reduces the maintenance cycle in the equipment maintenance data; If the maintenance frequency in the equipment maintenance data is lower than the standard frequency, the tracking feedback module determines that the reason for not meeting the production plan is a hidden factor.

8. The data integration system based on an alumina plant according to claim 7, characterized in that: The tracking and feedback module performs production operation tracking and feedback on the production process of each production area. If the reason for non-compliance with the production plan is an implicit factor, the tracking and feedback module determines whether the theoretical maximum output can cover the required output or verifies the refining and decomposition process based on whether there are production batches of alumina that do not meet the quality standards.

9. The data integration system based on an alumina plant according to claim 8, characterized in that: The tracking feedback module determines whether the theoretical maximum output can cover the required output. If one or both of the ore quality and the dissolution process do not meet the corresponding standards, the tracking feedback module determines that the theoretical maximum output fails to cover the required output in the production plan, marks the production area that does not meet the standards, and sends a marking signal; If the ore quality and the dissolution process meet the corresponding standards, the tracking feedback module determines that the theoretical maximum output can cover the required output in the production plan, and the link optimization module determines whether the allocation and transportation link needs to be optimized.

10. The data integration system based on an alumina plant according to claim 9, characterized in that: The link optimization module detects the relative position of each production area to the production area of ​​the subsequent process according to the positioning of the production area by the factory function module; The link optimization module obtains the discharge time of raw materials in different processes and calculates the off-line time of several raw materials between processes. If the average off-production time is less than or equal to the average off-production time under normal working conditions in the historical production data, the analysis and execution module determines that there is no abnormality in the production process and determines to issue a planned warning information; If the average off-production time is greater than the mean off-production time under normal working conditions in the historical production data, the analysis and execution module will determine that there is an abnormality in the production process and needs to be optimized. If the off-production time of any raw material is greater than or equal to the critical time, the analysis and execution module will issue an off-production warning information and a reference strategy for the production area corresponding to the off-production time of the raw material. The reference strategy is to increase the preparation speed of subsequent processes.

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