System for presenting automation index for rolling line
The automation index presentation system addresses the lack of quantification for rolling line automation by calculating and displaying indices based on manual intervention data, enhancing operational efficiency and reducing operator dependency.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- TMEIC CORP
- Filing Date
- 2025-01-15
- Publication Date
- 2026-07-23
Smart Images
Figure JP2025000943_23072026_PF_FP_ABST
Abstract
Description
Automation Index Presentation System for Rolling Line
[0007] ,
[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.
[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 piece of equipment on the rolling line (see, for example, Patent Document 1). Such manual intervention has a significant 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 operators with such a high level of proficiency, it is desired 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.
[0004] Japanese Patent Application Laid-Open No. 2012-170963
[0005] By the way, when increasing the operation automation rate of the 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 the rolling line.
[0006] The present disclosure has been made to solve the above-described problems. An object of the present disclosure is to provide an automation index presentation system for a rolling line that can present an automation index serving as an indicator of the operation automation rate of the rolling line.
[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 a first automation index for each product category and intervention operation pattern by dividing the accumulated values 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 a 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 aspect, in addition to the first or second aspect, 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 aspect, in addition to the first or second aspect, further has the following characteristics: The data processing device is configured to create a second heat map 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, and to color-code the number of interventions for each piece of equipment; and to display the second heat map on a display device.
[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.
[0012] 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. This is a diagram showing the actual data of manual interventions stored in the data storage device. This is a diagram showing an example of the display of the automated index table. This is a diagram showing an example of the display of the first heat map. This is a diagram showing an example of the display of the second heat map. This is a diagram showing an example of the hardware configuration of the data processing device of the automated index presentation system.
[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 device, and a winding machine. As the rolled material 20 passes through these pieces of equipment, heating, processing, cooling, and winding are performed sequentially, ultimately producing the final 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 the actual data d2 used by the control system 3. The 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 the 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. The actual data d4 includes the actual data of manual interventions that are analyzed by the automation index presentation system 1. The actual data of manual interventions is registered in the data storage device 11, described later, at the start and completion of the manual intervention when the operator 5 performs the manual intervention using the input / output interface (not shown). Note that manual intervention itself is publicly known, so a detailed explanation is omitted here.
[0017] The automated index presentation system 1 comprises 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 with independent hardware, or they may be computer functions realized by the execution of corresponding programs on a processor.
[0018] The data storage device 11 stores not only actual data representing changes in physical quantities related to quality measured by sensors placed on the rolling line 2 over a fixed time period or a fixed long period, but also actual data of manual interventions. Figure 2 shows the actual data of manual interventions stored in the data storage device 11. The actual 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 actual data of manual interventions include, for example, product classification, tracking position of the rolled material 20, equipment used for manual intervention (hereinafter also referred to as "intervention equipment"), intervention operation pattern by manual intervention, start time of intervention operation, end time of intervention operation, intervention operation duration, and the intervention operation reference time and weighting coefficient described later. Product classification is the classification of products manufactured on the rolling line 2. Product classification is divided by steel type, plate width and plate thickness, etc. Intervention operation patterns are identified, for example, by operation buttons and their functions that are manually operated by the operator. Intervention operation patterns are classified, for example, into confirmation operations, normal operations, adjustment operations and error response operations. The intervention operation pattern can be identified by referring to an intervention operation pattern definition table (not shown) which defines the names of the operation buttons, the functions of the operation buttons, and the standard intervention operation times for each classification. The intervention operation time may also be calculated by the data processing device 12 from the start and end times 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, or a flash memory storage device such as an SSD. The data storage device 11 receives and stores data set d3 and actual data d4. Data set d3 is a collection of data that combines the actual data d2 used by the control system 3 with intermediate calculation data and calculation result data within the control system 3. The data storage device 11 sends data d5, which is a combination of data set d3 and actual data d4, to the data processing device 12.
[0020] The data processing device 12 analyzes the actual manual intervention data contained in the data d5 received from the data storage device 11 and performs calculations to display the automation index, which is an indicator of the operational automation rate of the rolling line 2, on the monitor 4, which is a display device. The following describes the process by which the data processing device 12 calculates the automation index.
[0021] First, the data processing device 12 counts the number of intervention operations for each product category and each intervention operation pattern. Here, the intervention operation pattern can be obtained by referring to the intervention operation pattern definition table above. For manual interventions of the obtained intervention operation patterns, the data processing device 12 calculates the duration of each intervention operation using the following formula (1): Intervention operation duration = Intervention operation end time - Intervention operation start time ... (1)
[0022] Next, the data processing device 12 refers to the intervention operation pattern definition table and obtains the predetermined standard intervention operation time for each product category. The standard intervention operation time is the standard intervention operation time predetermined for each intervention operation pattern.
[0023] Next, the data processing device 12 calculates a deviation coefficient for each product category, which represents the deviation rate of the intervention operation time from the standard intervention operation time, using the following formula (2): Deviation coefficient = (Intervention operation time - Standard intervention operation time) / Standard intervention operation 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 deviation coefficient is accumulated for each product category and intervention operation pattern, and the accumulated value of the deviation coefficient is divided by the number of interventions to calculate the first automation index for each product category and intervention operation pattern. 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 above. Second automation index = Σ (First automation index × Weight 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 a function to create 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 may 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 in which the number of interventions for each piece of equipment is color-coded, with the operating days of rolling line 2 on the X axis and the equipment of rolling line 2 on the Y axis, for each product category. In the example shown in Figure 5, the equipment shown is 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. The operator 5 who is looking at the monitor 4 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 in conjunction 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 the memory 123. The processor 122 realizes each function of the data processing device 12 by reading and executing the programs stored in the memory 123. The processor 122 is also called a CPU (Central Processing Unit), processing unit, arithmetic unit, microprocessor, microcomputer, or DSP. The memory 123 includes, 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.
[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 that serves as an indicator of the operational automation rate of a rolling line, comprising: a data storage device that stores actual data of manual interventions by operators of the rolling line; and a data processing device that processes the actual data, wherein the actual data includes a product classification which is the classification of products manufactured on the rolling line, an intervention operation pattern by manual intervention, and an intervention operation time, and the data processing device performs the following: obtaining a predetermined intervention operation standard time for each product classification; calculating a deviation coefficient for each product classification which represents the deviation rate of the intervention operation time from the intervention operation standard time; accumulating the deviation coefficients for each product classification and each intervention operation pattern, and dividing the accumulated value of the deviation coefficients by the number of interventions to calculate a first automation index for each product classification and each intervention operation pattern, respectively; obtaining a predetermined weighting coefficient for each intervention operation pattern; and calculating a second automation index for each product classification by accumulating the product value of the weighting coefficient and the first automation index for each product classification and each intervention operation pattern. An automation index presentation system for a rolling line, configured to display the first automation index and the second automation index on a display device.
2. An automation index presentation system for a rolling line according to claim 1, wherein the display of the first automation index and the second automation index includes displaying an automation index table that includes the number of interventions and the first automation index for each product classification and intervention operation pattern, and the second automation index for each product classification.
3. An automated rolling line index presentation system according to claim 1 or claim 2, wherein the data processing device is configured to further perform the following: 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 color-code the number of interventions for each intervention operation pattern; and display the first heat map on the display device.
4. A rolling line automation index presentation system according to claim 1 or claim 2, wherein the data processing device is configured to further perform the following: create a second heat map for each product classification, with the operating days of the rolling line on the X axis and the equipment of the rolling line on the Y axis, and color-code the number of interventions for each piece of equipment; and display the second heat map on the display device.