Method for operating a production plant and operating system

Abstract

The production facility operation method according to the present application is a production facility operation method for operating a plurality of the same production facilities arranged in a plurality of production sites, including: a data information preparation step of collecting operation data of the production facilities for each production site; a data accumulation step of accumulating the operation data collected in the data information preparation step to a computer arranged at a data accumulation site; a data analysis step of analyzing the operation status of each production facility using the operation data accumulated in the data accumulation step; a data display step of displaying information on the operation status of each production facility analyzed in the data analysis step on a display unit arranged at each production site; and a facility operation step of operating the production facility arranged at a second production site from a first production site with reference to the information displayed by the data display step.

Description

Technical Field

[0001] This invention relates to a method and system for operating production equipment that enables multiple identical production devices configured at multiple production sites to operate. Background Technology

[0002] For manufacturing industries that require multiple large-scale production facilities to produce products, concentrating all production facilities in one location would necessitate a vast space or pose a risk of complete production halt in the event of a major disaster such as an earthquake. Therefore, some manufacturers disperse their production sites domestically and, in some cases, overseas. In such cases, production plans are completed at each production site, and the production equipment operates according to these plans.

[0003] Ironmaking plants are often located in multiple locations within the ironmaking industry. For so-called integrated ironmaking plants, which concentrate production equipment from upstream to downstream processes, it's common to find shared equipment across the various plants, such as blast furnaces for producing iron sources, converters for adjusting the composition of the molten iron produced in the blast furnace, continuous casting equipment for solidifying molten iron into plate-shaped billets, and hot rolling equipment for further extending the billets into thin plates. Currently, at each production site, anomalies in the operation of each piece of equipment are assessed, and corresponding responses are taken.

[0004] Typically, for production equipment, operators check various operational data while running the equipment. Furthermore, in cases where an operational anomaly is detected, operating conditions are changed in a way that prevents the anomaly from escalating, thus stabilizing the equipment's operation. For example, there is a technique described in Patent Document 1 for detecting anomalies in blast furnaces. Specifically, if the ventilation of the blast furnace is obstructed, the furnace body pressure fluctuates. Consequently, the value of the Q-statistic, obtained by performing principal component analysis on data from multiple pressure gauges installed in the furnace body, increases. Therefore, the technique described in Patent Document 1 sets a threshold for the pre-collected Q-statistic under normal conditions; when the Q-statistic exceeds the threshold, it is determined that an operational anomaly has occurred in the blast furnace.

[0005] Patent Document 1: Japanese Patent Application Publication No. 2017-128805

[0006] In recent years, due to personnel reductions resulting from business rationalization and a shrinking domestic labor force, the number of operators has also decreased. Ideally, when operational anomalies occur, necessary responses such as temporary shutdowns should be implemented quickly to eliminate the fault. However, with a small number of operators, a large amount of operational work is concentrated on a few. Furthermore, in such a small-scale operational response, the transmission of operational techniques during anomalies stagnates, and operations continue even when equipment malfunctions go unnoticed. This sometimes leads to larger failures, prolonged shutdowns, and costly recovery. Additionally, product manufacturing becomes more difficult, resulting in reduced sales. Against this backdrop, anomaly detection technologies, as described above, are being developed for various processes. However, it is crucial to reliably apply these anomaly detection technologies so that they reflect operational changes and prevent major equipment failures. Summary of the Invention

[0007] The present invention was made in view of the above-mentioned problems, and its purpose is to provide a method and system for operating production equipment that can detect operational abnormalities of production equipment with high precision without requiring a large amount of manpower and respond to operational abnormalities quickly.

[0008] The method for operating production equipment according to the present invention is a method for operating multiple identical production equipment configured at multiple production sites, comprising: a data information preparation step, which collects operating data of the production equipment for each production site; a data accumulation step, which accumulates the operating data collected in the above data information preparation step to a computer configured at the data accumulation site; a data analysis step, which uses the operating data accumulated in the above data accumulation step to analyze the operating status of each production equipment; a data display step, which displays information related to the operating status of each production equipment analyzed in the above data analysis step on a display unit configured at each production site; and an equipment operation step, which operates the production equipment configured at a second production site from a first production site with reference to the information displayed in the above data display step.

[0009] The above data display steps may include the following steps: displaying information related to the current operating status of each production equipment on a display device located at a management location different from the above-mentioned multiple production locations; and the above-mentioned equipment operation steps may include the following steps: replacing the above-mentioned first production location, and operating the production equipment located at the above-mentioned second production location from the above-mentioned management location.

[0010] It can be configured to include an information prompting step instead of the above-mentioned equipment operation steps, in which the information prompting step provides operation guidance information of the production equipment configured at the second production site to the operator of the production equipment from the first production site or the management site.

[0011] It can be configured to include an operation status determination step, in which the analysis results of the above data analysis step are used to determine whether there is any operation abnormality in each production equipment. When there is a production equipment that is determined to be operating abnormally, the above equipment operation steps or the above information prompting steps are implemented.

[0012] The above-mentioned operation status determination steps may include the following steps: using at least one metadata from the same scaled operation indicators, operation data and operation conditions to determine whether there is an operation abnormality.

[0013] The production equipment operation system of the present invention is an operation system for multiple identical production equipment configured at multiple production sites, comprising: a data information preparation unit for collecting operation data of production equipment at each production site; a data accumulation unit for accumulating the operation data collected by the data information preparation unit; a data analysis unit for analyzing the operation status of each production equipment using the operation data accumulated by the data accumulation unit; a display unit configured at each production site for displaying information related to the operation status of each production equipment analyzed by the data analysis unit; and an equipment operation unit for operating the production equipment configured at a second production site from a first production site, referring to the information displayed on the display unit.

[0014] According to the operating method and operating system of the production equipment involved in this invention, it is possible to detect abnormalities in the operation of the production equipment with high precision without a large amount of manpower, and to respond quickly to the abnormalities. Attached Figure Description

[0015] Figure 1 This is a block diagram illustrating the structure of an embodiment of the present invention, namely, the operating system of a production equipment.

[0016] Figure 2 It means Figure 1 A block diagram of a modified example of the operating system of the production equipment shown.

[0017] Figure 3 This is a flowchart illustrating one embodiment of the present invention, namely, the process of device monitoring and processing. Detailed Implementation

[0018] An ironmaking plant mainly consists of upstream process equipment for manufacturing iron billets, the basis of the product; downstream process equipment for manufacturing the final product; and energy equipment for recycling electricity, fuel gas, and water. Upstream process equipment includes raw material storage yards for pig iron ore and other raw materials; coke ovens for producing coke from coal; sintering plants for sintering fine iron ore; blast furnaces for burning these raw materials at high temperatures to produce molten iron; torpedo cars for transporting molten iron; railway equipment for transporting torpedo cars; pretreatment equipment for adjusting the composition of molten iron; converters for adjusting the carbon content in molten iron to produce steel; furnaces for secondary refining; and continuous casting equipment for finally solidifying the molten steel into iron billets.

[0019] Downstream process equipment includes hot rolling equipment for heating iron billets to manufacture thin steel strips, cold rolling equipment for repeatedly heating and cooling steel strips while stretching them thinly to manufacture steel plates with specified strength, plating equipment for plating steel plates obtained in the cold rolling process, pipe making equipment for rolling up steel plates obtained in the hot rolling process and welding the plate ends together to manufacture pipes, and profile steel manufacturing equipment for manufacturing product groups called profile steel for construction, etc.

[0020] Energy equipment includes equipment for refining gases obtained from blast furnaces and coke, power generation equipment that uses refined gases to generate electricity, gas pipes for supplying gases to power generation equipment, and water supply pipes for transporting water to cool various furnaces and heated products, among other production equipment.

[0021] As such, multiple production facilities exist, each requiring a large area for setup. Therefore, combined iron and steel plants with upstream and downstream processes require vast areas. Consequently, the production capacity of a single iron and steel plant is insufficient to meet demand, necessitating the use of multiple plants. In such cases, there are also situations where iron and steel plants are located near users with high demand for iron and steel products to facilitate supply, or where multiple production sites are established to prevent operational shutdowns due to large-scale disasters.

[0022] The iron and steel plant is equipped with multiple sensors that measure the condition of the production equipment and the manufactured iron and steel products. During daily operation, operators set the necessary manufacturing conditions for the iron and steel products based on the data measured by these sensors. The following explanation uses the operation of the blast furnace in the upstream process as an example.

[0023] Generally, in a blast furnace, the opening of the top hopper is controlled to allow raw materials such as iron ore, sinter, and coke to be charged from the top at an appropriate charging speed. The inclination and rotation speed of the charging device are set and operated to achieve the intended distribution of the charge. For raw materials temporarily stored in the top hopper located at the furnace top, their weight is measured sequentially and the charging amount is managed. Furthermore, the surface shape of the charged raw materials is measured using a microwave profilometer to confirm the correct distribution. In the blast furnace, hot air is blown in from multiple tuyeres located circumferentially in the furnace belly. The blown hot air exchanges heat with the descending raw materials as it flows towards the top of the furnace. If the charged raw materials are distributed as intended, the data from multiple pressure gauges installed in the furnace body will show approximately the same movement. Furthermore, the temperature and composition of the gas reaching the top of the furnace are measured by probes located at the top to confirm that the gas flow within the furnace is as intended and that the raw materials are undergoing a normal chemical reaction to produce molten iron.

[0024] For the hot air blown in through the tuyeres, the airflow, temperature, moisture content, and oxygen enrichment are set, and the blowing pressure is measured. Powdered coal is blown in through lances installed inside the tuyeres, and the amount of coal blown in is set. Additionally, cameras are installed at the tuyeres to monitor the furnace interior, and images of the tuyeres are taken sequentially. The temperature of the tuyeres is also measured. Furthermore, numerous thermometers are installed to monitor the furnace body temperature, and the temperature is measured sequentially. The amount and temperature of the cooling water flowing to the cooling plates used to cool the furnace body, as well as the temperature of the cooling plates themselves, are also measured. The molten iron produced, along with the slag generated simultaneously inside the furnace, is discharged from the taphole at the bottom of the furnace. The start and end times of tapping are recorded. The molten iron and slag discharged from the taphole separate in the molten iron trough due to their difference in specific gravity, and the molten iron is then injected into the torpedo car.

[0025] In addition, slag flows into slag treatment equipment and is stored after being cooled by water or air. Immediately after the molten iron is discharged from the blast furnace, its temperature is measured, and the amount of silicon contained in the molten iron is also measured. Furthermore, the weight of the molten iron that has flowed into the torpedo car is measured using a weighing sensor. The basicity and discharge volume of the slag are also measured. In the final product manufacturing equipment, the operating speed of each production line, the furnace temperature, the product heating time, the set weight per unit area of ​​the coating, and other manufacturing conditions, as well as product defect, shape, and other product characteristic evaluation data obtained from sensors, can be considered as part of the operating data set. The products mentioned in the blast furnace can be replaced with molten iron and slag.

[0026] These operating conditions, sensor data, and product-related information are collected in a manner that allows the operator to monitor and are recorded by a control computer (called the process computer) along with a timestamp (time information). Inside the blast furnace's process computer, based on the recorded data, indices such as ventilation resistance and gas utilization rate, which accurately represent the blast furnace's condition, are calculated and recorded along with sensor data from various equipment, measurement data related to molten iron and slag, and operating conditions. The same operating data set is obtained by performing roughly the same operation at a blast furnace located remotely.

[0027] The following description, referring to the accompanying drawings, describes an embodiment of the present invention, namely, an operating system for production equipment, that applies the present invention to the process of operating multiple blast furnaces configured at multiple production sites. Furthermore, while this embodiment applies the present invention to the process of operating multiple blast furnaces configured at multiple production sites, the scope of the present invention is not limited to this embodiment and can be widely applied to all processes that operate multiple identical production equipment configured at multiple production sites.

[0028] 〔structure〕

[0029] First, refer to Figure 1 as well as Figure 2 The structure of an embodiment of the present invention, namely the operating system of a production equipment, will be described. Figure 1 This is a block diagram illustrating the structure of an embodiment of the present invention, namely, the operating system of a production equipment. Figure 2 It means Figure 1 A block diagram of a modified example of the operating system of the production equipment shown.

[0030] like Figure 1 As shown, one embodiment of the present invention, namely the production equipment operation system 1, is a system that operates multiple blast furnaces (blast furnace A to blast furnace X) configured at multiple production sites, comprising: blast furnace sensors 2 (blast furnace A sensor to blast furnace X sensor), installed in each blast furnace, measuring data representing the condition of the blast furnace and the molten iron produced by the blast furnace; a process computer 3 at each production site, electrically connected to the blast furnace sensor 2; an edge server computer 4 at each production site, electrically connected to the process computer 3; and a global data server computer 5, connected to each edge server computer 4 via a telecommunications line.

[0031] Here, the process computer 3, the edge server computer 4, and the global data server computer 5 are composed of known information processing devices. The global data server computer 5 is configured at any production site or at a location other than a production site. The location (data accumulation point) of the global data server computer 5 is not physically limited to one place and can be located in multiple locations. Furthermore, as... Figure 2 As shown, a dedicated computer 6a for sensor data processing, a PLC (Programmable Logic Controller) 6b, a DCS (Distributed Control System) 6c, and other devices can also be connected to the blast furnace sensor 2, and the blast furnace sensor 2 and the edge server computer 4 can be electrically connected through these devices.

[0032] The operating system 1 of the production equipment with this structure, by performing the equipment monitoring process shown below, is able to detect blast furnace operational anomalies with high precision without requiring a large amount of manpower, and to respond quickly to these anomalies. The following refers to... Figure 3 The flowchart shown illustrates the operation of the production equipment's operating system 1 when performing the equipment monitoring process.

[0033] [Equipment Monitoring and Processing]

[0034] Figure 3 This is a flowchart illustrating one embodiment of the present invention, namely, the process of device monitoring and processing. Figure 3 The equipment monitoring process shown begins at the start of blast furnace operation and proceeds to step S1.

[0035] In step S1, the process computer 3 collects the operation data set and sends it to the edge server computer 4. The edge server computer 4 saves the operation data set sent from the process computer 3 to a data storage unit such as a hard disk, optical disk, or USB flash drive. Here, the operation data set refers to the blast furnace operation data and metadata obtained at the same time. The operation data refers to the data measured by the blast furnace sensor 2 and / or various indices calculated based on the data measured by the blast furnace sensor 2. In addition, the metadata refers to the blast furnace's operating condition data, setpoints, operating status, and operation data other than the operation data of interest at the time the operation data is obtained. Furthermore, it is preferable that the number of items, item names, and units of the operation data and metadata are all the same across multiple production sites to achieve commonality.

[0036] The process computer 3 operates under heavy load due to performing model calculations, controlling various instruments, and collecting and processing data. Furthermore, if the operational data sets are sent to the global data server computer 5 via telecommunication lines, potential standby times due to busy telecommunication lines could impact blast furnace operation. Therefore, in this embodiment, an edge server computer 4 is positioned close to the process computer 3 via the telecommunication lines, connecting the process computer 3 and the edge server computer 4. Moreover, the operational data sets are temporarily stored on the edge server computer 4, and as described later, the global data server computer 5 accumulates the operational data sets stored on the edge server computer 4 via the telecommunication lines. Additionally, in the production equipment's operating system 1... Figure 2 In the structure shown, the edge server computer 4 also stores data sent from devices such as the dedicated sensor data processing computer 6a, PLC 6b, and DCS 6c. Thus, the processing in step S1 is completed, and the equipment monitoring process proceeds to step S2.

[0037] In step S2, the global data server computer 5 reads and records electronic files of the operating data sets stored in each edge server computer 4 at predetermined intervals (e.g., every minute if tracking changes in the various sensors of the blast furnace). Furthermore, the edge server computer 4 can also send the electronic files containing the recorded operating data sets to the global data server computer 5 at predetermined intervals. Thus, step S2 is completed, and the equipment monitoring process proceeds to step S3.

[0038] In step S3, the global data server computer 5 saves the operating data sets of each blast furnace read in step S2 to a data recording device such as a hard disk, optical disk, or USB flash drive. At this time, the global data server computer 5 synchronizes the operating data sets of each blast furnace so that the operating data sets of each blast furnace at the same time can be compared with each other. Furthermore, if the names and units of data items in the operating data sets are different, the global data server computer 5 unifies the names and units by changing them to predetermined names and units. Thus, step S3 is completed, and the equipment monitoring process proceeds to step S4.

[0039] In step S4, the global data server computer 5 analyzes the operating status of each blast furnace by analyzing the operating data sets of each blast furnace stored in the cumulative data recording device. Specifically, the operating status of the blast furnace can be determined from the ventilation resistance index calculated based on pressure data, the Q statistic calculated based on pressure data, the gas utilization rate calculated based on gas analysis values, and the deviation of the Q statistic in the furnace periphery direction calculated based on the brightness of multiple image data of the tuyeres at the blast furnace. Additionally, the operating status of the blast furnace can also be detected by the ventilation resistance obtained by dividing the difference between the furnace body pressure and the furnace top pressure by the furnace volume. Furthermore, the gas utilization rate, which represents the CO to CO2 composition ratio obtained by analyzing the gas composition obtained from the furnace top, is also an indicator of the blast furnace's operating status. Focusing on the lower part of the blast furnace, a furnace heat index reflecting the thermal state inside the blast furnace can be calculated based on the heat balance calculation of the lower part of the blast furnace, allowing for the assessment of the reaction status inside the blast furnace earlier than the molten iron temperature. In addition, the operating data set contains a large amount of data that can reveal the operating status of the blast furnace. The operating status of the blast furnace can also be determined by the moving average, standard deviation shift from the pre-calculated average, addition and subtraction of multiple data points when they are treated as time series data.

[0040] The global data server computer 5 calculates an index representing the operating status of each blast furnace by performing the above-described analysis on the operating data sets of each blast furnace. Furthermore, it is preferable that the global data server computer 5 saves the index representing the operating status of each blast furnace along with the operating data sets to the cumulative data recording device after the analysis is completed. Alternatively, the edge server computer 4 can also perform the processing in step S4, incorporating the index representing the operating status of the blast furnace into the operating data sets. Thus, the processing in step S4 is completed, and the equipment monitoring process proceeds to step S5.

[0041] In step S5, the global data server computer 5 displays the indices and operating data sets representing the operating status of each blast furnace in a manner that clearly shows their time changes on data display units such as LCD displays configured on each blast furnace. Furthermore, it is preferable that the global data server computer 5 simultaneously displays the indices and operating data sets representing the operating status of each blast furnace on the data display units and can compare the indices and operating data sets representing the operating status of each blast furnace. Additionally, it is preferable that the period for displaying the data can be arbitrarily set, so that the progression of the operating status of each blast furnace can be easily understood by referring to long-term trends to short-term trends. Through this process, it is easy to determine whether the operating status of the blast furnace is good and easy to predict how the operating status of the blast furnace will change in the future. Thus, step S5 is completed, and the equipment monitoring process proceeds to step S6.

[0042] In step S6, the global data server computer 5 determines the operational status of each blast furnace based on indices representing its operating condition. At this time, the global data server computer 5 can also determine where and what type of anomaly has occurred within the blast furnace. Specifically, good ventilation within the blast furnace is crucial for continuous and stable operation. However, if the gas flow within the furnace becomes turbulent for some reason, anomalies such as material suspension, slippage, and leakage may occur. "Material suspension" refers to the phenomenon where the raw material stops descending normally. Slippage occurs when "material suspension" is eliminated, or high-temperature gas blown in from the tuyeres at the bottom of the furnace may be abruptly ejected upwards for some reason. Multiple furnace body pressure gauges are installed in the blast furnace body. The Q statistic, obtained by performing principal component analysis on the data from these pressure gauges, is an indicator of the degree of deviation from the distribution of pressure data obtainable under normal operating conditions. Therefore, by setting a threshold for the Q statistic, operational anomalies can be determined. Furthermore, when an operational anomaly is determined, referring to all furnace pressure data allows us to determine the direction of the pressure disturbance. Here, in the principal component analysis, which is a prerequisite for calculating the Q statistic, each data point is modeled based on data standardized using the mean and standard deviation of each data point. Therefore, the judgment of the Q statistic is not inherent to the equipment, but can be used to determine anomalies under a common benchmark for the equipment.

[0043] In addition, the ventilation resistance index is used as an indicator to judge the ventilation status inside the blast furnace. The ventilation resistance index is calculated by dividing the difference between the hot air inlet pressure at the tuyeres and the pressure at the furnace top by the furnace volume. If a threshold is set in the ventilation resistance index, operational abnormalities can be identified. Furthermore, by using the measurements from pressure sensors in the upper, middle, and lower parts of the furnace instead of the tuyeres' inlet pressure, the area can be divided into upper, middle, and lower sections for evaluation, thus revealing where the ventilation abnormality occurs. However, the specifications of production equipment at other production sites often vary. In such cases, even using the same index to evaluate the operating status may not instantly determine whether an abnormality has occurred. Therefore, evaluating indices obtained from the same type of production equipment with different specifications using the same scale can reduce the possibility of misjudgment. Considering the blast furnace itself, it's clear that due to differences in blast furnace volume and shape, as well as variations in the location and number of pressure sensors and thermometers, the obtained indices and their fluctuation ranges differ across various production equipment.

[0044] Therefore, an index for judging the operating status of equipment obtained from operational data is used as the first index, and the average value of the first index obtained during periods when the equipment was considered to be normal in past production conditions is calculated. The second index is calculated by dividing the first index obtained sequentially by this average value, thereby facilitating comparison of the equipment status of different types of production equipment and enabling instant identification of anomalies. Furthermore, the period for calculating the average value varies depending on the type of production equipment, ranging from one month to several months. Additionally, considering factors such as ambient temperature, seasonal variations can also be taken into account to calculate the average value of the first index over a period of approximately one year. Moreover, this transformation to the same scale can also be a statistical standardization, i.e., dividing the value obtained by subtracting the average value from the operational data by the standard deviation. In this specification, this processing is referred to as the standardization of various indicators and operational data. The aforementioned ventilation resistance index, various sensor observations other than pressure sensors, etc., can also be utilized through standardization.

[0045] Furthermore, it is preferable that the temperature of the molten iron exiting the blast furnace is approximately constant. However, in the event of an abnormality during operation, the temperature of the molten iron may drop excessively, preventing the molten iron and slag from being discharged from the tap hole. Such a failure is called a furnace cooling accident, which takes a long time to recover from, halts product manufacturing, and results in significant production reduction. To prevent such accidents, an operational abnormality can be determined using an index such as the furnace heat index TQ. The furnace heat index TQ can be calculated using the following formula (1). Moreover, similar to the case of the ventilation resistance index, a threshold is set for the furnace heat index TQ, and an operational abnormality is determined when the furnace heat index TQ is below the threshold.

[0046] TQ=(Q1+Q2)-(Q3+Q4+Q5+Q6)+(Q7-Q8-Q9)…(1)

[0047] Here, Q1 represents the sensible heat of the blast air, Q2 represents the heat of carbon combustion at the tuyere tip, Q3 represents the heat of moisture decomposition in the blast air, Q4 represents the heat of reaction due to dissolution loss, Q5 represents heat loss, Q6 represents the heat of decomposition of PC (pulverized coal), Q7 represents the sensible heat carried in by coke and molten material, Q8 represents the sensible heat carried out by generated gases, and Q9 represents the sensible heat carried out by coke. Regarding the furnace thermal index, structural differences in the blast furnace body also have an impact; therefore, a standardized furnace thermal index can be used to allow for comparable analysis across different equipment, similar to the ventilation resistance index.

[0048] The global data server computer 5 pre-prepares multiple such anomaly detection algorithms to sequentially evaluate operating data sets obtained from the same blast furnace. Furthermore, the global data server computer 5 can compare metadata obtained from the current operation with past metadata also included in metadata obtained from other production sites, thereby extracting periods of change in past operating conditions similar to the changes in current operating conditions over a specified time period. Based on the operating status of the production equipment during the extracted period, it can determine whether the production equipment has any operational anomalies. Here, in addition to operating conditions including charge distribution, air flow rate, oxygen enrichment, pulverized coal flow rate, coke ratio, air moisture, air temperature, and air pressure, the metadata can also include operational conditions. Within this metadata, metadata at different scales for each equipment also includes data scaled to the same level and is stored, so it can be used for anomaly diagnosis even if the equipment is different.

[0049] Alternatively, human intervention can be used to determine the operating status. In this case, an input device is prepared in advance to indicate an operating abnormality. This allows the label representing the abnormality to be synchronized with the time-series data and recorded along with a timestamp. In this case, various abnormal states can be recorded using different labels. Furthermore, when the abnormality determination processing load on the global data server computer 5 is high, an abnormality determination computer connected directly below the global data server computer 5 can be prepared to perform the abnormality determination processing. Additionally, the global data server computer 5 can learn from the operating data set when the blast furnace's operating status is determined to be normal during the processing in step S6, thereby constructing a learning model that uses the operating data set as input and the blast furnace's operating status determination value as output. Based on the blast furnace's operating status determination value output by inputting the current operating data set into the learning model, the operating status of the blast furnace is determined.

[0050] Furthermore, the aforementioned human-input anomaly labels and data obtained by standardizing at least one metadata from each device's operating indicators (excluding ventilation resistance index and furnace heat index), operating data, and operating conditions, can be used to construct a machine learning model for anomaly diagnosis and determine the blast furnace's operating status. By standardizing the operating data specific to each device to represent operating indices, and further standardizing, a model based on a large amount of data utilizing all devices can be achieved. Therefore, even if anomalies occur infrequently in individual devices, a machine learning model for anomaly determination based on all data can be constructed. Thus, step S6 is completed, and the equipment monitoring process proceeds to step S7.

[0051] In step S7, the global data server computer 5 notifies the operators of each blast furnace of information related to the blast furnace experiencing an operational anomaly, the type of anomaly, and the location of the anomaly. For example, in anomaly detection based on Q statistics and ventilation resistance, the possibility of anomalies caused by raw material properties is suspected; in anomaly detection based on furnace heat index, an anomaly related to slag discharge is suspected. Examples of anomaly transmission units to operators include: preparing a screen displaying anomaly information on a dedicated personal computer or tablet connected to the same telecommunications line and displaying the anomaly information on that screen; or notifying the operator via email to their mobile phone or smartphone. Furthermore, the global data server computer 5 may also notify the operators of each blast furnace of a continued good operating condition or a determination that the condition is deteriorating. Thus, step S7 is completed, and the equipment monitoring process proceeds to step S8.

[0052] In step S8, the operators of the blast furnaces without operational abnormalities communicate with the operators of the blast furnaces identified as having operational abnormalities. The operators of the blast furnaces identified as having operational abnormalities relinquish control of their blast furnaces to the operators of the blast furnaces without operational abnormalities. When multiple blast furnaces are operating at multiple production sites, the likelihood of including highly skilled operators increases. The highly skilled operators assess the situation based on various information and communicate with the operators of the blast furnaces identified as having operational abnormalities. In cases of low urgency, the operators of the blast furnaces identified as having operational abnormalities operate the blast furnaces according to the recommendations of the highly skilled operators. On the other hand, in cases of high urgency, control of the blast furnaces at the sites where the abnormalities occurred is relinquished to the highly skilled operators, who then operate the blast furnaces to address the abnormalities.

[0053] Furthermore, while the above description assumes the presence of highly skilled operators at other production sites, a monitoring center (e.g., the head office of a steel plant) could also be located separately from the production site where the blast furnace is located, allowing various blast furnace-related information to be displayed at the monitoring center. Moreover, highly skilled operators could be stationed at the monitoring center to perform the same anomaly responses as described above. Additionally, if a highly skilled operator, after reviewing the displayed information, determines that a certain action is needed, the monitoring center could be contacted without waiting for a determination of an operational anomaly in the blast furnace to take various actions, including anomaly prevention measures. Thus, step S8 is completed, and the series of equipment monitoring processes concludes.

[0054] The embodiments of the invention made by the inventors have been described above, but the present invention is not limited to the description and drawings that form part of the disclosure of the present invention as described in these embodiments. That is, all other embodiments, examples, and techniques applied based on these embodiments by those skilled in the art are included within the scope of the present invention.

[0055] Industrial availability

[0056] According to the present invention, a method and system for operating production equipment can be provided that can detect operational abnormalities of production equipment with high precision without requiring a large amount of manpower and respond to operational abnormalities quickly.

[0057] Explanation of reference numerals in the attached figures

[0058] 1…Operating system of production equipment; 2…Blast furnace sensor; 3…Process computer; 4…Edge server computer; 5…Global data server computer.

Claims

1. A method for operating production equipment, characterized in that, multiple identical production devices configured at multiple production sites are operated, and the method enables the operation of such equipment. include: The data preparation step involves collecting operational data of production equipment for each production site. The data accumulation step accumulates the operational data collected in the data information preparation step to a computer configured at the data accumulation location; The data analysis step uses the operational data accumulated in the data accumulation step to analyze the operating status of each production device; The operation status determination step determines whether there are any operational abnormalities in each production equipment based on the analysis results of the data analysis step. The data display step displays information related to the operating status of each production device analyzed in the data analysis step on the display units configured at each production site. as well as The equipment operation steps, referring to the information displayed through the data display steps, involve operating the production equipment located at the second production site from the first production site. The operation status determination step includes the following steps: taking at least one metadata, operation indicator, and operation data in the operation conditions as a first index for determining the operation status of the production equipment; calculating the average value of the first index obtained during the period when the equipment was considered to be normal in the past production conditions; and dividing the first index obtained in sequence by the average value to calculate a second index, so that at least one metadata, operation indicator, and operation data in the operation conditions are scaled to the same standard, thereby comparing the equipment status of different types of production equipment and determining whether there is an operation abnormality.

2. The method for operating the production equipment according to claim 1, characterized in that, The data display step includes the following steps: displaying information related to the current operating status of each production device on a display device configured at a management location different from the plurality of production locations. The equipment operation steps include the following steps: replacing the first production site and operating the production equipment configured at the second production site from the management site.

3. The method for operating the production equipment according to claim 2, characterized in that, Instead of the equipment operation steps, an information prompting step is included, in which operating instructions for the production equipment configured at the second production site are prompted from the first production site or the management site.

4. The method for operating the production equipment according to claim 3, characterized in that, When there is production equipment that is determined to be operating abnormally, the equipment operation steps or the information prompt steps shall be implemented.

5. A production equipment operation system, which enables multiple identical production equipment configured at multiple production sites to operate, characterized in that... have: The data information preparation unit collects the operating data of production equipment for each production site. The data accumulation unit accumulates the operational data collected by the data information preparation unit; The data analysis unit uses the operating data accumulated by the data accumulation unit to analyze the operating status of each production device; The operation status determination unit determines whether there are any operational abnormalities in each production equipment based on the analysis results of the data analysis unit. Display units are configured at each production site to display information related to the operating status of each production equipment as analyzed by the data analysis unit. as well as The equipment operation unit operates the production equipment located at the second production site from the first production site, referring to the information displayed on the display unit. The operation status determination unit uses at least one metadata, operation indicator, and operation data in the operation conditions as a first index to determine the operation status of the production equipment. It calculates the average value of the first index obtained during the period when the equipment was considered to be normal in the past production conditions, and divides the first index obtained in turn by the average value to calculate a second index, so that at least one metadata, operation indicator, and operation data in the operation conditions are scaled to the same standard, thereby comparing the equipment status of different types of production equipment and determining whether there is an operation abnormality.

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