Rolling line automation index display system

Abstract

The automation index presentation system, which displays an automation index that serves as an indicator of the automation rate of rolling line operations, includes a data processing device that processes actual data on manual interventions. The data processing device obtains predetermined intervention operation standard times for each product category, calculates a deviation coefficient representing the deviation rate of intervention operation time from the intervention operation standard time for each product category, accumulates the deviation coefficients for each product category and intervention operation pattern, and calculates the first automation index for each product category and intervention operation pattern by dividing the accumulated value of the deviation coefficients for each product category and intervention operation pattern by the number of interventions. The data processing device obtains predetermined weight coefficients for each intervention operation pattern, calculates the second automation index for each product category by accumulating the product value of the weight coefficients for each product category and intervention operation pattern and the first automation index, and displays the first and second automation indices on the display device.

Description

Technical Field

[0001] The present disclosure relates to an automation index presentation system that presents an automation index serving as an indicator of the operation automation rate of a rolling line.

Background Art

[0002] In the operation of a rolling line in a steel plant or a non-ferrous metal plant, manual intervention by an operator (also referred to as "manual operation") is performed to adjust and optimize each facility of the rolling line (see, for example, Patent Document 1). Such manual intervention has a great impact on the quality of rolled products. Therefore, a high level of proficiency is required for the operator who performs the manual intervention.

[0003] Since there is a shortage of such highly proficient operators, it is desirable to operate the rolling line with as few operators as possible. In order to reduce the number of operators, it is necessary to increase the operation automation rate of the rolling line by reducing the number of times of manual intervention or shortening the time required for manual intervention.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] By the way, when increasing the operation automation rate of a rolling line, it is necessary to grasp the current operation automation rate of the rolling line. However, there has been no index for quantifying the operation automation rate of a rolling line.

[0006] This disclosure was made to solve the problems described above. The purpose of this disclosure is to provide a rolling line automation index presentation system that can present an automation index that serves as an indicator of the automation rate of the rolling line's operation. [Means for solving the problem]

[0007] The first aspect of this disclosure relates to an automation index presentation system that presents an automation index as an indicator of the operational automation rate of a rolling line. The automation index presentation system comprises a data storage device that stores actual data on manual interventions by operators of the rolling line, and a data processing device that processes the actual data. The actual data includes product classification, which is the classification of the products manufactured on the rolling line, intervention operation patterns by manual intervention, and intervention operation time. The data processing device is configured to perform the following actions: obtain a predetermined intervention operation standard time for each product category; calculate a deviation coefficient representing the deviation rate of the intervention operation time from the intervention operation standard time for each product category; accumulate the deviation coefficients for each product category and intervention operation pattern; calculate the first automation index for each product category and intervention operation pattern by dividing the accumulated value of the deviation coefficients for each product category and intervention operation pattern by the number of interventions; obtain a predetermined weight coefficient for each intervention operation pattern; calculate the second automation index for each product category by accumulating the product of the weight coefficient and the first automation index for each product category and intervention operation pattern; and display the first automation index and the second automation index on a display device.

[0008] The second perspective, in addition to the first perspective, has the following further characteristics: Displaying the first and second automation indices includes displaying an automation index table that includes the number of interventions and the first automation index for each product category and intervention operation pattern, and the second automation index for each product category.

[0009] The third perspective, in addition to the first or second perspective, further has the following characteristics: The data processing device is configured to create a first heat map for each product classification, with the longitudinal position of the rolled product as the X-axis and the intervention operation pattern as the Y-axis, and to color-code the number of interventions for each intervention operation pattern; and to display the first heat map on a display device.

[0010] The fourth perspective, in addition to the first or second perspective, further has the following characteristics: The data processing device is configured to create a second heatmap for each product category, with the operating days of the rolling line on the X-axis and the equipment of the rolling line on the Y-axis, color-coding the number of interventions for each piece of equipment; and to display the second heatmap on a display device. [Effects of the Invention]

[0011] According to this disclosure, an automation index can be presented, which serves as an indicator of the operational automation rate of a rolling line. Therefore, it is possible to understand the current operational automation rate of a rolling line using the presented automation index. [Brief explanation of the drawing]

[0012] [Figure 1] This is a schematic diagram showing a rolling line in a steel plant to which the automated index presentation system according to the embodiment is applied. [Figure 2] This figure shows the actual data of manual interventions stored in the data storage device. [Figure 3] This figure shows an example of how the automated index table is displayed. [Figure 4] This figure shows an example of the first heat map display. [Figure 5] This figure shows an example of the second heatmap display. [Figure 6] This figure shows an example of the hardware configuration of the data processing unit for an automated index presentation system. [Modes for carrying out the invention]

[0013] Hereinafter, with reference to the drawings, the automated index presentation system for a rolling line according to the embodiment of this disclosure will be described, using the case of application to a steel plant as an example. In each figure, the same or corresponding parts are denoted by the same reference numerals, and redundant explanations will be simplified or omitted as appropriate.

[0014] Figure 1 is a schematic diagram showing a rolling line 2 in a steel plant to which the automated index presentation system 1 according to the embodiment is applied. The steel plant comprises a rolling line 2 for rolling rolled material 20, which is a rolled product, a control system 3 for controlling the rolling line 2, and a display device 4.

[0015] The rolling line 2 is equipped with multiple pieces of equipment. Examples of the main equipment include a heating furnace FCE, a roughing mill RM, an edge heater FME, a finishing mill FM, a cooling system, and a winding machine. As the rolled material 20 passes through these pieces of equipment, it undergoes heating, processing, cooling, and winding in sequence, ultimately producing a finished product. Each piece of equipment in the rolling line 2 is controlled by command data d1 transmitted from the control system 3.

[0016] Multiple sensors are installed on the rolling line 2. The actual data measured by these multiple sensors can be broadly divided into two types. One is actual data d2 used by the control system 3. Actual data d2 represents changes in the physical quantities of the equipment and the rolled material 1 and is collected at regular time intervals. The control system 3 generates command data d1 based on the actual data d2. The other is actual data d4, which is not used by the control system 3 but is used for the analysis and evaluation of product quality and the evaluation of the operation of the rolling line 2. Actual data d4 includes actual data of manual interventions that are analyzed by the automation index presentation system 1. Actual data of manual interventions is registered in the data storage device 11, described later, at the start and completion of manual interventions when the operator 5 performs a manual intervention using the input / output interface (not shown). Note that manual interventions themselves are publicly known, so a detailed explanation is omitted here.

[0017] The automation index presentation system 1 includes a data storage device 11, a data processing device 12, and an information display device 13. These devices 11, 12, and 13 may each be devices having independent hardware, or may be computer functions realized by executing corresponding programs on a processor.

[0018] The data storage device 11 is a device that stores performance data related to changes in physical quantities related to quality measured by sensors arranged on the rolling line 2 over a fixed time period or a fixed length period, as well as performance data of manual interventions. FIG. 2 is a diagram showing the performance data of manual interventions stored in the data storage device 11. The performance data of manual interventions can be stored, for example, as an intervention operation history table (not shown) having the following items. The items of the performance data of manual interventions include, for example, product classification, tracking position of the rolled material 20, equipment for manual intervention (hereinafter also referred to as "intervention equipment"), intervention operation pattern by manual intervention, start time of the intervention operation, end time of the intervention operation, intervention operation time, as well as the intervention operation reference time and weight coefficient described later. The product classification is the classification of products manufactured on the rolling line 2. The product classification is classified by steel type, plate width, plate thickness, etc. The intervention operation pattern is specified by, for example, an operation button manually operated by an operator and its function. The intervention operation pattern is classified into, for example, confirmation operations, normal operations, adjustment operations, error response operations, etc. The intervention operation pattern can be specified by referring to an intervention operation pattern definition table (not shown) in which the name of the operation button, the function of the operation button, and the intervention operation reference time are defined for each classification. Note that the intervention operation time may be calculated by the data processing device 12 from the start time and end time of the intervention operation.

[0019] The data storage device 11 includes, for example, a magnetic disk such as an HDD, an optical disk such as a DVD, a flash memory storage device such as an SSD, and the like. The data set d3 and the performance data d4 are sent to and stored in the data storage device 11. The data set d3 is a set of data obtained by combining the performance data d2 used in the control system 3, the intermediate calculation data in the control system 3, and the calculation result data. The data storage device 11 sends the data d5 obtained by combining the data set d3 and the performance data d4 to the data processing device 12.

[0020] The data processing device 12 analyzes the performance data of manual intervention included in the data d5 received from the data storage device 11, and performs calculations for displaying an automation index, which is an index of the automation rate of the rolling line 2, on the monitor 4, which is a display device. Hereinafter, the process of the data processing device 12 calculating the automation index will be described.

[0021] First, the data processing device 12 counts the number of intervention operations for each product classification and for each intervention operation pattern. Here, the intervention operation pattern can be obtained by referring to the above intervention operation pattern definition table. For the manual intervention of the obtained intervention operation pattern, the data processing device 12 calculates the intervention operation time for each time by the following formula (1). Intervention operation time = Intervention operation end time - Intervention operation start time ··· (1)

[0022] Next, the data processing device 12 refers to the above intervention operation pattern definition table and obtains the predetermined intervention operation reference time for each product classification. The intervention operation reference time is the standard intervention operation time determined in advance for each intervention operation pattern.

[0023] Next, the data processing device 12 calculates a deviation coefficient representing the deviation rate of the intervention operation time with respect to the intervention operation reference time for each product classification by the following formula (2). Deviation coefficient = (Intervention operation time - Intervention operation reference time) / Intervention operation reference time ··· (2)

[0024] Next, the data processing device 12 calculates the first automation index for each product category and intervention operation pattern using the following formula (3). Specifically, the first automation index for each product category and intervention operation pattern is calculated by accumulating the deviation coefficients for each product category and intervention operation pattern, and then dividing the accumulated value of the deviation coefficients by the number of interventions. First automation index = Σ(1 + deviation coefficient) / number of interventions ... (3)

[0025] Next, the data processing device 12 calculates the second automation index for each product category using the following formula (4). That is, the second automation index for each product category is calculated by multiplying the weight coefficient for each product category and intervention operation pattern by the first automation index. Here, the weight coefficient is a constant defined for each intervention operation pattern. The weight coefficient for each intervention operation pattern can be obtained by referring to the intervention operation pattern definition table described above. Second automation index = Σ(first automation index × weighting coefficient) ... (4)

[0026] The calculation results from the data processing device 12 are sent to the information display device 13. The information display device 13 edits the calculation results from the data processing device 12 and displays them on the monitor 4, which serves as the display screen for the information display device 13. Figure 3 shows an example of the display of the automation index table. The automation index table includes the number of interventions and the first automation index for each product category and intervention operation pattern, as well as the second automation index for each product category. By looking at the first automation index and the second automation index displayed on the monitor 4, the operator 5 can grasp the current operational automation rate of the rolling line 2.

[0027] Incidentally, when determining the automation rate of the rolling line 2, it is sometimes preferable to understand the actual amount of manual intervention. Therefore, the data processing device 12 further has the function of creating two types of heatmaps. Figure 4 shows an example of the display of the first heatmap. Figure 5 shows an example of the display of the second heatmap.

[0028] The first heatmap shown in Figure 4 is a heatmap in which the number of interventions for each intervention pattern is color-coded, with the longitudinal position of the rolled material 20 (a rolled product) on the X axis and the intervention operation pattern on the Y axis, for each product classification. Each cell is displayed without color when there is no manual intervention at the corresponding position of the rolled material 20, and is colored according to the number of interventions. In the example shown in Figure 4, different patterns are used for coloring, but coloring can also be done using shades of gray. The longitudinal position of the rolled material 20 can be obtained by referring to the "Tracking Position" item in the intervention operation pattern definition table above. Since tracking is publicly known, a detailed explanation is omitted here.

[0029] The second heatmap shown in Figure 5 is a heatmap that displays the number of interventions for each piece of equipment, with the operating days of Rolling Line 2 on the X axis and the equipment of Rolling Line 2 on the Y axis, color-coded for each product category. In the example shown in Figure 5, the equipment includes the heating furnace FCE, roughing mill RM, edge heater FME, and finishing mill FM. Each cell is displayed without color if there was no manual intervention for that piece of equipment on the corresponding operating day of Rolling Line 2, and is colored according to the number of interventions. In the example shown in Figure 5, different patterns are used for coloring, but coloring could also be done using shades of gray.

[0030] As described above, according to this embodiment, the first automation index and the second automation index, which are indicators of the operational automation rate of the rolling line 2, are displayed on the monitor 4 in the form of an automation index table, thereby presenting these automation indices to the operator 5 who is looking at the monitor 4. By looking at the monitor 4, the operator 5 can grasp the current operational automation rate of the rolling line 2 from the presented automation indices. Furthermore, displaying the first heat map and the second heat map on the monitor 4 along with the automation index table makes it easier for the operator 5 to grasp the actual amount of manual intervention, which is advantageous.

[0031] Figure 6 shows an example of the hardware configuration of the data processing device 12 of the automated index presentation system 1. Each of the functions of the data processing device 12 described above can be realized by the processing circuit 120 shown in Figure 6. This processing circuit 120 may be dedicated hardware 121. This processing circuit 120 may include a processor 122 and a memory 123. This processing circuit 120 may be partially formed as dedicated hardware 121 and further include a processor 122 and a memory 123. In the example shown in Figure 6, part of the processing circuit 120 is formed as dedicated hardware 121, and the processing circuit 120 also includes a processor 122 and a memory 123. The processing circuit 120 may include at least one dedicated hardware 121. In this case, the processing circuit 120 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 120 may include at least one processor 122 and at least one memory 123. In this case, each function of the data processing device 12 is realized by software, firmware, or a combination of software and firmware. The software and firmware are written as programs and stored in memory 123. The processor 122 realizes each function of the data processing device 12 by reading and executing the programs stored in memory 123. The processor 122 is also called a CPU (Central Processing Unit), processing unit, arithmetic unit, microprocessor, microcomputer, or DSP. Memory 123 can be, for example, non-volatile or volatile semiconductor memory such as RAM, ROM, flash memory, EPROM, or EEPROM. In this way, the processing circuit 120 can realize each function of the data processing device 12 by hardware, software, firmware, or a combination thereof.

[0032] While embodiments of this disclosure have been described above, this disclosure is not limited to the embodiments described above and can be implemented in various modified forms without departing from the spirit of this disclosure. When the number of elements, quantities, amounts, ranges, etc., are mentioned in the embodiments described above, this invention is not limited to the number mentioned unless it is specifically stated or clearly defined in principle. Furthermore, the structures, etc., described in the embodiments described above are not necessarily essential to this invention unless they are specifically stated or clearly defined in principle.

[0033] Furthermore, although the above embodiment was described using the application of the automated index presentation system 1 of this disclosure to a steel plant as an example, the automated index presentation system 1 can also be applied to non-steel plants. [Explanation of Symbols]

[0034] 1…Automated index display system, 10…Processing circuit, 11…Data storage device, 12…Data processing device, 120…Processing circuit, 121…Dedicated hardware, 122…Processor, 123…Memory, 13…Information display device, 2…Rolling line, 20…Rolled material (rolled product), 3…Control system, 4…Monitor (display device), 5…Operator, FCE…Heating furnace (equipment), RM…Roughing mill (equipment), FME…Edge heater (equipment), FM…Finishing mill (equipment)

Claims

1. An automation index presentation system that presents an automation index, which serves as an indicator of the automation rate of a rolling line, The system includes a data storage device that stores actual data on manual interventions by operators of the rolling line, and a data processing device that processes the actual data. The aforementioned performance data includes the product classification, which is the classification of the products manufactured on the rolling line, the intervention operation pattern by manual intervention, and the intervention operation time. The aforementioned data processing device is Obtain a predetermined intervention operation standard time for each of the aforementioned product classifications, To calculate a deviation coefficient representing the deviation rate of the intervention operation time from the standard intervention operation time for each of the aforementioned product classifications, The first automation index is calculated for each product category and each intervention operation pattern by accumulating the deviation coefficients for each product category and each intervention operation pattern, and dividing the accumulated value of the deviation coefficients by the number of interventions. Obtain predetermined weight coefficients for each of the aforementioned intervention operation patterns, The second automation index is calculated for each product category by accumulating the product of the weight coefficient for each product category and each intervention operation pattern with the first automation index, Displaying the first automation index and the second automation index on the display device, An automated index presentation system for a rolling line configured to perform the following actions.

2. An automated index presentation system for a rolling line according to claim 1, An automation index presentation system for a rolling line, which includes displaying the first automation index and the second automation index, and an automation index table that includes the number of interventions and the first automation index for each product category and each intervention operation pattern, and the second automation index for each product category.

3. An automated index presentation system for a rolling line according to claim 1 or claim 2, The aforementioned data processing device is For each product classification, a first heat map is created in which the longitudinal position of the rolled product is the X-axis and the intervention operation pattern is the Y-axis, and the number of interventions for each intervention operation pattern is displayed in different colors. Displaying the first heatmap on the display device, An automated index presentation system for a rolling line, configured to further perform the following.

4. An automated index presentation system for a rolling line according to claim 1 or claim 2, The aforementioned data processing device is For each of the aforementioned product classifications, a second heat map is created in which the operating days of the rolling line are on the X axis and the equipment of the rolling line is on the Y axis, and the number of interventions for each piece of equipment is displayed in different colors. Displaying the second heatmap on the display device, An automated index presentation system for a rolling line, configured to further perform the following.

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