Maintenance support system for steel plant

Abstract

This maintenance support system includes a data storage device, an abnormality degree determination unit, a restoration time calculation unit, a maintenance evaluation unit, and a maintenance display unit. The data storage device stores, as records data acquired from measuring instruments installed in a steel plant, an abnormality occurrence time point, an abnormality occurrence location, a degree of abnormality, a maintenance method, a restoration time point at which an abnormal condition is restored to a normal condition due to execution of maintenance, a maintenance execution location, and a skill level of a person in charge who has executed the maintenance. The abnormality degree determination unit determines a degree of abnormality when an abnormality occurs in rolling equipment. The restoration time calculation unit calculates, for each of a plurality of past abnormalities having the same degree of abnormality as the degree of abnormality determined by the abnormality degree determination unit, a restoration time from the abnormality occurrence time point to the restoration time point due to execution of the maintenance. The maintenance evaluation unit uses a distance from the abnormality occurrence location to the maintenance execution location and the skill level to evaluate a predetermined number of maintenance methods with short restoration times calculated by the restoration time calculation unit. The maintenance display unit displays the maintenance method most highly evaluated by the maintenance evaluation unit on a display device.

Description

Steel plant maintenance support system

[0001] The present disclosure relates to a maintenance support system for a steel plant.

[0002] Japanese Patent Application Laid-Open No. 2006-124493 discloses a product quality analysis support system. This system includes a data storage device that stores performance data measured by sensors installed in a steel plant, and a data processing device that processes the stored performance data. The data processing device calculates statistical values ​​of sampling data obtained from the performance data, and if a quality defect occurs because the statistical values ​​do not meet a reference value, it proposes countermeasures for the quality defect.

[0003] Japanese Patent Publication No. 2021-192915

[0004] When an abnormality occurs in a steel plant, it is preferable to carry out maintenance to restore normal operation as quickly as possible in consideration of productivity. However, the measures proposed in Patent Document 1 do not necessarily result in a short recovery time.

[0005] The present disclosure has been made to solve the above-mentioned problems, and aims to provide a maintenance support system for a steel plant that can present a maintenance method for quickly restoring rolling equipment in the steel plant when an abnormality occurs.

[0006] The first aspect relates to a maintenance support system for a steel plant. The maintenance support system presents a maintenance method when an abnormality occurs in rolling equipment installed in the steel plant. The maintenance support system includes a data storage device, an abnormality degree determination unit, a recovery time calculation unit, a maintenance evaluation unit, and a maintenance display unit. The data storage device stores, as performance data acquired from measuring instruments installed in the steel plant, the time of abnormality occurrence, the location of the abnormality occurrence, the degree of abnormality, the maintenance method, the time of recovery from the abnormality to normal through maintenance, the maintenance implementation location, and the skill level of the person performing the maintenance. The abnormality degree determination unit determines the degree of abnormality when an abnormality occurs in the rolling equipment. The recovery time calculation unit calculates the recovery time by maintenance from the time of abnormality occurrence to the recovery time for each of multiple past abnormalities having the same abnormality degree as the abnormality degree determined by the abnormality degree determination unit. The maintenance evaluation unit evaluates a predetermined number of maintenance methods with the shortest recovery times calculated by the recovery time calculation unit using the distance from the location of the abnormality occurrence to the maintenance implementation location and the skill level. The maintenance display unit displays the maintenance technique that has been most highly evaluated by the maintenance evaluation unit on a display device.

[0007] The second aspect has the same features as the first aspect, but further includes the following: the maintenance display unit displays an actual waveform of the measurement value acquired from the measuring device when the abnormality occurs, and the maintenance support system further includes a predicted recovery curve display unit that displays, on the display device, a predicted recovery curve that is a predicted waveform of the measurement value predicted by performing the maintenance displayed by the maintenance display unit, following the actual waveform of the measurement value.

[0008] The third aspect has the following feature in addition to the first or second aspect: the maintenance evaluation unit is configured to evaluate a predetermined number of maintenance techniques based on a product of a first evaluation point according to a distance and a second evaluation point according to a skill level.

[0009] The fourth aspect has the following characteristics in addition to the first or second aspect: the data storage device stores the number of evaluations of the maintenance technique that has received the highest evaluation as a count each time an evaluation is performed by the maintenance evaluation unit, and the maintenance evaluation unit is configured to evaluate a predetermined number of maintenance techniques based on the product of a first evaluation point according to the distance, a second evaluation point according to the skill level, and a third evaluation point according to the count.

[0010] According to the present disclosure, a configuration is adopted in which the recovery time from the time the abnormality occurred to the time of recovery by maintenance is calculated for each of multiple past abnormalities of the same abnormality level, a predetermined number of maintenance methods with the shortest calculated recovery times are evaluated, and the maintenance method with the highest evaluation is displayed. Here, by evaluating each of the predetermined number of maintenance methods using the distance from the abnormality location to the maintenance location and the skill level, the maintenance method that enables the fastest recovery is evaluated the highest. Therefore, a maintenance support device can be provided that can present the maintenance method that will enable the fastest recovery when an abnormality occurs in rolling equipment of a steel plant.

[0011] 1 is a schematic diagram showing an example of a steel plant to which a maintenance support system according to an embodiment is applied; FIG. 2 is a block diagram showing an example configuration of the maintenance support system; FIG. 3 is a diagram showing a processing flow by the maintenance support system when an abnormality occurs; FIG. 4 is a diagram showing a first table defining the relationship between the distance from the abnormality location to the maintenance location and a first evaluation point; FIG. 5 is a diagram showing a second table defining the relationship between the skill level of a maintenance technician and a second evaluation point; FIG. 6 is a diagram showing a predicted recovery curve; FIG. 7 is a diagram showing an example hardware configuration of the maintenance support system; and FIG. 8 is a diagram showing a third table defining the relationship between the count number and a third evaluation point.

[0012] Hereinafter, a maintenance support system for a steel plant according to an embodiment of the present disclosure will be described with reference to the drawings. Note that common elements in the drawings will be assigned the same reference numerals and redundant description will be omitted.

[0013] FIG. 1 is a schematic diagram showing an example of an iron and steel plant 2 to which a maintenance support system 1 according to an embodiment is applied. The iron and steel plant 2 will be described as a plant having a hot rolling line, but may also be a plant having a cold rolling line. The iron and steel plant 2 is equipped with a heating furnace 3, a roughing mill 4, a finishing mill 5, a cooling device 6, a winder 7, and a conveying table (not shown) for conveying steel sheets Pr as main rolling equipment constituting the hot rolling line. These rolling equipment are driven by an electrical system of motors and actuators.

[0014] The heating furnace 3 is configured to heat the steel plate (slab) Pr to a predetermined temperature (e.g., 1200°C) before rolling. The roughing mill 4 has one to three rolling stands (one in the example shown in Figure 1) and rolls the steel plate (slab) Pr heated in the heating furnace 3 in multiple passes in the forward direction (from upstream to downstream of the rolling line) and the reverse direction (from downstream to upstream of the rolling line). The finishing mill 5 is a tandem rolling mill equipped with multiple rolling stands Fi (seven in the example shown in Figure 1) arranged side by side in the rolling direction of the steel plate Pr. Each rolling stand Fi (i = 1 to 7) is equipped with two upper and lower work rolls 51, two upper and lower backup rolls 52, and a motor 53 for roll rotation. The backup roll 52 is provided with a screw down device 54, which is configured to adjust the gap between the upper and lower work rolls 51. The rolling load of each rolling stand F1 to F7 is measured by a rolling load sensor 55. The current Am of the motor 53 of each rolling stand F1 to F7 is measured by an ammeter 56. The cooling device 6 cools the steel sheet Pr by injecting water onto the steel sheet Pr using a cooling bank. The cooled steel sheet Pr is wound into a coil by a winder 7.

[0015] Various sensors are installed as measuring instruments at key points in the steel plant 2. Key points in the steel plant 2 include, for example, the outlet side of the heating furnace 3, the outlet side of the roughing mill 4, the outlet side of the finishing mill 5, and the inlet side of the winder 7. Various sensors may also be installed between rolling stands F1 to F7 of the finishing mill 5. The various sensors include a shape detector 81 capable of measuring the shape of the steel sheet Pr at the outlet side of the roughing mill 3, a thermometer 82 that measures the surface temperature of the steel sheet Pr at the inlet side of the finishing mill 5, a speed detector 83 that measures the speed Va of the steel sheet Pr at the outlet side of the finishing mill 5, a thickness / width meter 84 that measures the thickness and width of the steel sheet Pr at the outlet side of the finishing mill 5, a thermometer 85 that measures the surface temperature of the steel sheet Pr at the inlet side of the winder 7, the rolling load sensor 55, and the current meter 56. As the various sensors can be well known, detailed description thereof will be omitted. The various sensors sequentially measure the state of the steel sheet Pr and each rolling equipment. The performance data measured by the various sensors is time-series data that is transmitted to the control computer 101 from time to time. The time-series data includes waveform data of actually measured values, such as the actual measurement value waveform (see FIG. 6 ) described below. A threshold value is set for each performance data. When the performance data exceeds the threshold value, the abnormality detection unit 121 described below detects that an abnormality has occurred in the corresponding or related rolling equipment.

[0016] The steel plant 2 is operated by a control system using computers with a hierarchical structure. The computers include a control computer 101 and a host computer 102, which are connected to each other via a network. The control computer 101 is connected to the maintenance support system 1 via the network. The control computer 101 has a control controller such as a PLC (programmable logic controller). An HMI (human machine interface) device 103 is connected to the control computer 101 via the network. Data of the monitored object (rolling equipment) is presented to the HMI 103, allowing an operator (not shown) to monitor or operate (control) the monitored rolling equipment. When a rolling plan is input to the host computer 102, rolling information is sent from the host computer 102 to the control computer 101. The rolling information includes a target plate thickness, a target plate width, a target temperature, etc. The control computer 101 receives rolling information input from the host computer 102, calculates setting data including setting values ​​for each rolling equipment to be controlled, and transmits the calculated design data to the steel plant 2, thereby controlling each rolling equipment that constitutes the steel plant 2.

[0017] The maintenance support system 1 collects rolling data including design data and performance data exchanged between each rolling facility of the steel plant 2 and the control computer 101. As will be described later, the maintenance support system 1 uses the collected rolling data to display a maintenance technique on the HMI 103, thereby presenting the maintenance technique to a maintenance technician Mp who is different from an operator. The HMI 103 corresponds to the "display device" in the claims.

[0018] The maintenance support system 1 includes a data storage device 11 and a data processing device 12. The data storage device 11 has a function of collecting rolling data and storing it in a database DB. The rolling data includes the above-mentioned rolling information, setting data, and performance data. The performance data includes the time when the abnormality occurred, the location where the abnormality occurred, the degree of the abnormality, the maintenance method, the time when the abnormality was restored to normal by performing maintenance, the location where the maintenance was performed, and the skill level of the person who performed the maintenance.

[0019] The data processing device 12 uses the rolling data stored in the data storage device 11 to display on the HMI 103 a maintenance method for restoring the rolling equipment of the steel plant 2 to normal when an abnormality occurs, thereby presenting this to the maintenance person Mp.

[0020] FIG. 2 is a block diagram showing an example of the configuration of the maintenance support system 1. FIG. 3 is a diagram showing the flow of processing by the maintenance support system 1 when an abnormality occurs. FIG. 4 is a diagram showing a first table Tb1 that defines the relationship between the distance from the abnormality location to the maintenance location and the first evaluation score. FIG. 5 is a diagram showing a second table Tb2 that defines the relationship between the skill level of a maintenance technician and the second evaluation score. FIG. 6 is a diagram showing a predicted recovery curve.

[0021] 2, the data processing device 12 includes an abnormality detection unit 121, an abnormality degree determination unit 122, a recovery time calculation unit 123, a maintenance evaluation unit 124, a maintenance display unit 125, and a predicted recovery curve display unit 126. The functions of the units 121 to 126 of the data processing device 12 and the functions of the data storage device 11 can be realized, for example, by a processor 10b shown in FIG. 7, which will be described later, reading and executing a program stored in a memory 10c.

[0022] The abnormality detection unit 121 detects the occurrence of an abnormality in the rolling equipment by using performance data of the rolling equipment. Hereinafter, an example will be described in which the abnormality detection unit 121 detects a current abnormality when the current Am of the motor 53 measured by the current meter 56 exceeds a predetermined threshold Ath.

[0023] When an abnormality occurs in the rolling equipment, the abnormality degree determination unit 122 determines the degree of the abnormality in at least two stages. When the degree of the abnormality of the current abnormality is determined in two stages, it is determined to be either severe or mild.

[0024] The restoration time calculation unit 123 calculates the restoration time required for maintenance from the time of occurrence of the abnormality to the time of restoration for each of a plurality of past abnormalities having the same degree of abnormality as the degree of abnormality determined by the abnormality degree determination unit 122 .

[0025] The maintenance evaluation unit 124 evaluates a predetermined number (for example, five) of maintenance methods that have the shortest recovery times calculated by the recovery time calculation unit 123, using the distance from the location where the abnormality occurred to the location where maintenance was performed and the skill level of the person who performed the maintenance. As will be described in detail later, the maintenance evaluation unit 124 multiplies a first evaluation point corresponding to the distance by a second evaluation point corresponding to the skill level, and evaluates the predetermined number of maintenance methods based on the product obtained by the multiplication.

[0026] The maintenance display unit 125 displays the maintenance method that has been most highly evaluated by the maintenance evaluation unit 124 on the HMI device (display device) 103. That is, the maintenance method that has the highest product of the first evaluation point and the second evaluation point is displayed on the HMI device 103. The person in charge of performing maintenance Mp performs maintenance on the rolling equipment in accordance with the maintenance method displayed (presented) on the HMI device 103, thereby restoring the rolling equipment to normal operation.

[0027] The predicted recovery curve display unit 126 displays on the HMI device 103, following the actual measurement waveform of the measurement value (current Am), a predicted recovery curve, which is a predicted waveform of the measurement value predicted by carrying out the maintenance method displayed on the HMI device 103 by the maintenance display unit 125 (see Figure 6).

[0028] At an abnormality occurrence time t0 (see FIG. 6 ) when the current Am measured by the current meter 56 exceeds the threshold Ath, the abnormality detection unit 121 detects the occurrence of a current abnormality. Thereafter, at a current time t1, the abnormality degree determination unit 122 determines the degree of the abnormality in at least two stages depending on the type of abnormality detected (step S1). If the type of abnormality is a current abnormality, the abnormality can be determined to be severe when the deviation from the threshold Ath (i.e., the amplitude) is large or when the time from time t0 (swing time) is long. On the other hand, the abnormality can be determined to be mild when the amplitude is small or the swing time is short.

[0029] Here, multiple anomalies with the same degree of anomaly include not only anomalies with the same amplitude, but also anomalies with different amplitudes. Separating by the degree of anomaly is advantageous because it can also handle cases where a new anomaly occurs with an amplitude different from that of an anomaly that occurred in the past. A preset reference value can be used to determine the degree of anomaly. Furthermore, a medium level can be set between severe and mild, and the degree of anomaly can be determined in three levels.

[0030] Next, the recovery time calculation unit 123 calculates the time from the occurrence of the abnormality to recovery (hereinafter referred to as "recovery time") for each of multiple past abnormalities of the same abnormality level (step S2). The recovery time can be calculated using the abnormality occurrence time and recovery time stored in the database DB. The data storage device 11 records (saves) in the database DB a predetermined number (e.g., five) of maintenance techniques with the shortest recovery times calculated in step S2 (step S3). Examples of maintenance techniques for recovering from a current abnormality include repairing broken parts of cords and repairing poorly connected parts of connectors.

[0031] Next, the maintenance evaluation unit 124 evaluates the five maintenance methods recorded in step S3 (step S4). The evaluation of the maintenance methods is performed using evaluation scores for two items. The first item is the distance from the abnormality location to the maintenance location. By referring to FIG. 4, a first evaluation score corresponding to the distance can be obtained. According to this, the shorter the distance, the higher the first evaluation score. If the type of abnormality is, for example, a current abnormality, the abnormality location is a location in the motor, and the maintenance location is a broken location in the cord or a location with a poor connection. The second item is the skill level of the maintenance technician Mp based on the skill map. By referring to FIG. 5, a second evaluation score corresponding to the skill level of the technician Mp can be obtained. According to this, the higher the skill level, such as for a senior technician, the higher the second evaluation score can be. The five maintenance methods are evaluated based on the product of the first evaluation score and the second evaluation score. The maintenance display unit 125 displays the maintenance method with the highest evaluation on the HMI 103 (step S5). The maintenance person Mp can restore the system as quickly as possible by performing the displayed maintenance with the highest evaluation, thereby shortening the restoration time.

[0032] As shown in FIG. 6 , a predicted recovery curve is displayed by applying a past measured value waveform 1 corresponding to the maintenance technique performed by the maintenance technician Mp following the actual measured value waveform of the current Am up to the current time t1 (step S6). The actual measured value waveform 1 corresponds to the maintenance technique with the highest evaluation, while the past measured value waveforms 2 and 3 correspond to maintenance methods with lower evaluations. This allows even an inexperienced maintenance technician Mp to easily grasp the recovery time t2 at which the current Am falls below the threshold value Ath, as well as the time from the current time t1 to the recovery time t2. Note that the actual measured value waveforms 2 and 3 may be omitted from the illustration.

[0033] As described above, according to this embodiment, for multiple past anomalies of the same type and degree of anomaly, the recovery time from the time the anomaly occurred to the time the maintenance was performed to restore the system is calculated, a predetermined number of maintenance methods with the shortest calculated recovery times are evaluated, and the most highly rated maintenance method is displayed on the HMI device 103. Here, by evaluating each of the predetermined number of maintenance methods using the distance from the location where the anomaly occurred to the location where maintenance was performed and the skill level of the maintenance technician Mp, the maintenance method that enables the fastest recovery is evaluated most highly. Therefore, it is possible to provide a maintenance support system 1 that can present a maintenance method that will achieve the fastest recovery when an anomaly occurs in the rolling equipment of the steel plant 2.

[0034] FIG. 7 is a diagram illustrating an example of the hardware configuration of the maintenance support system 1. The above-described functions of the maintenance support system 1 can be realized by the processing circuit 10 shown in FIG. 7. The processing circuit 10 may be dedicated hardware 10a. The processing circuit 10 may include a processor 10b and a memory 10c. The processing circuit 10 may be partially formed as dedicated hardware 10a and further include a processor 10b and a memory 10c. In the example shown in FIG. 7, a portion of the processing circuit 10 is formed as dedicated hardware 10a, and the processing circuit 10 also includes a processor 10b and a memory 10c. The processing circuit 10 may be at least one dedicated hardware 10a. In this case, the processing circuit 10 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC, an FPGA, or a combination thereof. The processing circuit 10 may include at least one processor 10b and at least one memory 10c. In this case, the functions of the maintenance support system 1 are realized by software, firmware, or a combination of software and firmware. The software and firmware are written as programs and stored in memory 10c. The processor 10b realizes each function of the maintenance support system 1 by reading and executing the programs stored in memory 10c. The processor 10b is also called a CPU (Central Processing Unit), central processing unit, processing device, arithmetic unit, microprocessor, microcomputer, or DSP. The memory 10c corresponds to a storage device such as a non-volatile or volatile semiconductor memory, such as RAM, ROM, flash memory, EPROM, or EEPROM. The memory 10c can also serve as a database (DB). In this way, the processing circuit 10 can realize each function of the maintenance support system 1 by hardware, software, firmware, or a combination of these.

[0035] While the embodiments of the present disclosure have been described above, the present disclosure is not limited to the above embodiments and can be implemented in various modifications without departing from the spirit of the present disclosure. In the above embodiments, an example has been described in which the HMI device 103, which is a display device, is provided outside the maintenance support system 1. However, the display device may also be provided inside the maintenance support system 1.

[0036] In the above embodiment, five maintenance techniques are evaluated based on the product of a first evaluation point corresponding to the distance from the abnormality location to the maintenance location and a second evaluation point corresponding to the skill level. However, this is not limited to this, and the following modifications are possible. That is, each time the maintenance evaluation unit 124 performs an evaluation, the data storage device 11 stores the highest evaluation count of the maintenance technique that received the highest evaluation (the maintenance technique displayed on the HMI device 103) as a count. FIG. 8 is a diagram showing a third table Tb3 that defines the relationship between the count and the third evaluation point. According to this, the larger the count, the higher the third evaluation point obtained. The maintenance evaluation unit 124 is configured to multiply the first evaluation point corresponding to the distance, the second evaluation point corresponding to the skill level, and the third evaluation point corresponding to the count, and evaluate a predetermined number of maintenance techniques based on the product obtained by the multiplication. According to this, maintenance techniques that are performed frequently are highly evaluated, thereby enabling accurate evaluation of the maintenance techniques.

[0037] In the above embodiment, an example has been described in which a current abnormality occurs in the motor 53, but the type of abnormality is not limited to this, and the present disclosure can also be applied to cases in which an abnormality other than a current abnormality occurs. Examples of other types of abnormality include a rolling load abnormality measured by the rolling load sensor 55.

[0038] Furthermore, when the number, quantity, amount, range, etc. of each element is mentioned in the above-mentioned embodiments, the present invention is not limited to the mentioned numbers unless otherwise specified or clearly specified in principle. Furthermore, the structures, etc. described in the above-mentioned embodiments are not necessarily essential to the present invention unless otherwise specified or clearly specified in principle.

[0039] 1...Maintenance support system, 11...Data storage device, DB...Database, 12...Data processing device, 121...Abnormality detection unit, 122...Abnormality degree determination unit, 123...Recovery time calculation unit, 124...Maintenance evaluation unit, 125...Maintenance display unit, 126...Predicted recovery curve display unit, 2...Steel plant, 5...Finishing rolling mill (rolling equipment), 53...Motor (rolling equipment), 103...HMI device (display unit), Mp...Maintenance person

Claims

1. A maintenance support system for a steel plant that suggests maintenance methods when an abnormality occurs in rolling equipment installed in the steel plant, comprising: a data storage device that stores, as performance data obtained from measuring instruments installed in the steel plant, the time the abnormality occurred, the location where the abnormality occurred, the degree of the abnormality, the maintenance method, the time when the abnormality was restored to normal by performing maintenance, the location where the maintenance was performed, and the skill level of a person who performed the maintenance; an abnormality degree determination unit that determines the degree of the abnormality when an abnormality occurs in the rolling equipment; a recovery time calculation unit that calculates the recovery time by maintenance from the time of the abnormality occurrence to the recovery time for each of multiple past abnormalities that have the same abnormality degree as the abnormality degree determined by the abnormality degree determination unit; a maintenance evaluation unit that evaluates a predetermined number of maintenance methods that have the shortest recovery time calculated by the recovery time calculation unit using the distance from the location where the abnormality occurred to the location where maintenance was performed and the skill level; and a maintenance display unit that displays on a display device the maintenance method that was most highly evaluated by the maintenance evaluation unit.

2. A steel plant maintenance support system as described in claim 1, wherein the maintenance display unit displays the actual waveform of the measurement value acquired from the measuring instrument when an abnormality occurs, and further comprising a predicted recovery curve display unit that displays on the display device, following the actual waveform of the measurement value, a predicted recovery curve which is the predicted waveform of the measurement value predicted by carrying out the maintenance displayed by the maintenance display unit.

3. A steel plant maintenance support system as described in claim 1 or claim 2, wherein the maintenance evaluation unit is configured to evaluate a predetermined number of the maintenance techniques based on the product of a first evaluation point according to the distance and a second evaluation point according to the skill level.

4. A maintenance support system for a steel plant as described in claim 1 or claim 2, wherein the data storage device stores the highest number of evaluations of the most highly rated maintenance technique as a count each time an evaluation is performed by the maintenance evaluation unit, and the maintenance evaluation unit is configured to evaluate a predetermined number of the maintenance techniques based on the product of a first evaluation point according to the distance, a second evaluation point according to the skill level, and a third evaluation point according to the count.

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