KR20240037291A - Operation support method, operation support device, and operation support program for rolling line - Google Patents

Abstract

A method of supporting operations in a rolling line includes steps for acquiring various data related to rolled products manufactured in the rolling line. The method includes, based on the various data, a step of calculating for each product specification the incidence of errors occurring in at least one of the quality of the rolled product, the operation status of the rolling line, and the operator's operation of the actuator of the rolling line. and a step of setting the manufacturing difficulty of the rolled product for each product specification according to the height of the production rate. The method is a step of outputting support data for supporting an operator involved in a manufacturing process of a manufacturing object manufactured on the rolling line from an operator terminal, wherein the support data is data on the manufacturing difficulty of the manufacturing object, and a step including data on the manufacturing difficulty of the rolled product having the same product specifications as the product specifications of the manufacturing target.

Description

Operation support method, operation support device, and operation support program for rolling line

The present disclosure relates to methods, devices, and programs that support operations in rolling lines.

Patent Document 1 discloses a device that generates a logistics schedule including charging of steel pieces into a heating furnace and rolling of materials performed in a hot rolling factory. In order to optimize the logistics schedule over a period of about 1 day to 1 week, this conventional device performs simulation in real time using information on the properties and delivery dates of the steel materials subject to the logistics schedule, and Predict logistics status. Then, according to this future logistics status, a lot organization schedule is created that combines the distribution schedule for the cold-sectioned steel lot and the hot-sectioned steel lot.

When creating a lot knitting schedule, the conventional apparatus performs lot knitting so that the amount of cold-knitted steel introduced is maximized. For this reason, Patent Document 1 states that the demand for the production of cold-piece steel tends to be higher than that of lobe-piece steel, and that rolling of cold-piece steel is more difficult than that of lobe-piece steel and misrolls are likely to occur. It is being described.

Japanese Patent Publication No. 2005-59020

It is an empirically or statistically known fact that the difficulty of rolling steel varies depending on the properties of the steel, in other words, depending on the specifications of the product manufactured on the rolling line. Therefore, when thinking about a manufacturing object to be manufactured in the future on a rolling line, when the difficulty of this manufacturing object is high, it is expected that the frequency of involvement in the manufacturing process by the operator in charge of the manufacturing process will increase. Although the frequency of involvement in the manufacturing process is low, it is expected that the timing of involvement in the manufacturing process and the degree of involvement in the manufacturing process will become important.

However, issues such as what information regarding involvement in the manufacturing process should be provided to the operator and by what means this information regarding involvement should be provided to the operator have been examined in the prior art, including Patent Document 1. is not made up. Therefore, technology development from this perspective is desired.

One purpose of the present disclosure is to provide a technique that can provide useful information to operators involved in the manufacturing process of a manufacturing object manufactured on a rolling line.

The first aspect of the present disclosure is a method for supporting operation in a rolling line, and has the following features.

The above method is,

A step of acquiring various data related to the rolled product manufactured in the rolling line, wherein the various data include data regarding product specifications of the rolled product, data regarding the quality of the rolled product, and manufacturing of the rolled product. A step including data regarding an operation status of the rolling line during production of the rolled product and data regarding an operator's operation of an actuator of the rolling line during production of the rolled product;

Based on the various data, a step of calculating for each product specification the occurrence rate of errors occurring in at least one of the quality of the rolled product, the operation status of the rolling line, and the operator operation;

A step of setting the manufacturing difficulty of the rolled product for each product specification according to the height of the incidence rate;

A step of outputting support data for supporting an operator involved in the manufacturing process of the manufacturing object manufactured on the rolling line from an operator terminal, wherein the support data is data of the manufacturing difficulty of the manufacturing object, and a step including data on the product specifications and the manufacturing difficulty of the rolled product having the same product specifications.

The second aspect of the present disclosure is a device that supports operation in a rolling line, and has the following features.

The device includes a storage device storing various data related to rolled products manufactured in the rolling line, and one or more processors.

The various data include data on the product specifications of the rolled product, data on the quality of the rolled product, data on the operation status of the rolling line during production of the rolled product, and manufacturing of the rolled product. It includes data regarding operator operation of the actuator of the rolling line.

The one or more processors,

Based on the various data, processing to calculate for each product specification the occurrence rate of errors occurring in at least one of the quality of the rolled product, the operation status of the rolling line, and the operator operation;

Processing of setting the manufacturing difficulty of the rolled product for each product specification according to the height of the incidence rate,

Processing of outputting support data for supporting an operator involved in the manufacturing process of a manufacturing object manufactured on the rolling line from an operator terminal, wherein the support data has the same product specifications as the product specifications of the manufacturing object. It is configured to perform processing including data on the manufacturing difficulty of the product.

The third aspect of the present disclosure is a program that supports operation in a rolling line, and has the following features.

The above program is,

Processing for acquiring various data related to the rolled product manufactured in the rolling line, wherein the various data include data regarding product specifications of the rolled product, data regarding the quality of the rolled product, and manufacturing of the rolled product. Processing including data on an operation status of the rolling line during production of the rolled product and data on operator operation of an actuator of the rolling line during production of the rolled product;

Based on the various data, processing to calculate for each product specification the occurrence rate of errors occurring in at least one of the quality of the rolled product, the operation status of the rolling line, and the operator operation;

Processing of setting the manufacturing difficulty of the rolled product according to the incidence rate for each product specification according to the height of the incidence rate;

Processing of outputting support data for supporting an operator involved in the manufacturing process of a manufacturing object manufactured on the rolling line from an operator terminal, wherein the support data has the same product specifications as the product specifications of the manufacturing object. Processing including data on the manufacturing difficulty of the product is executed on the computer.

According to the present disclosure, the difficulty of manufacturing a rolled product manufactured in a rolling line is determined by the quality of the rolled product, the operating status of the rolling line during the manufacturing of the rolled product, and the operator's operation of the actuator during the manufacturing of the rolled product. It is set for each product specification according to the level of occurrence of errors occurring in at least one of the following. According to the present disclosure, further, as support data for supporting an operator involved in the manufacturing process of a manufacturing object manufactured on a rolling line, data on the manufacturing difficulty of a rolled product having the same product specifications as the product specifications of this manufacturing object are provided. Output from the operator terminal.

Here, “rolled product manufactured on a rolling line” means a product for which manufacturing on a rolling line has been completed. Therefore, the manufacturing difficulty of “rolled products manufactured on a rolling line” has already been revealed. On the other hand, “manufacturing object manufactured on a rolling line” refers to a product before manufacturing on a rolling line is completed, that is, a product that will be manufactured on a rolling line in the future, and a product while manufacturing on a rolling line is being carried out. means a product of Therefore, the manufacturing difficulty of “manufacturing objects manufactured on a rolling line” has not yet been determined.

However, if the product specifications of the “manufactured object manufactured on the rolling line” are the same as those of the “rolled product manufactured on the rolling line,” it is predicted that the manufacturing difficulty of the former will be the same as that of the latter. This disclosure focuses on this point. Therefore, according to the present disclosure, the manufacturing difficulty of the “rolled product manufactured on the rolling line” having the same product specifications as the product specification of the “manufactured object manufactured on the rolling line” is output from the operator terminal as the support data, “ It is possible to provide the operator with useful information regarding the manufacturing difficulty of the “manufactured object manufactured on the rolling line.”

FIG. 1 is a diagram illustrating a configuration example of a rolling system to which the operation support device for a rolling line according to the first embodiment is applied.
Fig. 2 is a diagram showing a configuration example of data related to product specifications.
Fig. 3 is a diagram showing an example of the configuration of data regarding operating conditions.
Fig. 4 is a diagram explaining data related to operator operation.
Fig. 5 is a diagram showing a configuration example of quality-related data.
Fig. 6 is a diagram illustrating an example of data processing performed by the management server (processor) in the first embodiment.
Fig. 7 is a diagram illustrating an example of data processing performed by the management server (processor) in the first embodiment.
FIG. 8 is a diagram illustrating a configuration example of a rolling system to which the rolling line operation support device according to the second embodiment is applied.
Fig. 9 is a diagram illustrating an example of data processing performed by the management server (processor) in the second embodiment.
Fig. 10 is a diagram illustrating an example of data processing performed by a management server (processor) in the second embodiment.
Fig. 11 is a diagram illustrating an example of data processing performed by a management server (processor) in the second embodiment.

Hereinafter, the operation support method, operation support device, and operation support program of the rolling line according to the embodiment of the present disclosure will be described in detail with reference to the drawings. In addition, common elements in each drawing are assigned the same reference numerals and redundant descriptions are omitted.

1. First embodiment

1-1. Configuration example of rolling system

FIG. 1 is a diagram illustrating a configuration example of a rolling system to which the operation support device for a rolling line according to the first embodiment is applied. In the example shown in FIG. 1, the rolling system is provided with a management server 1, a PLC (Programmable Logic Controller) 2, and an operator terminal 3.

The management server 1 has a function as an operation support device according to the first embodiment. The management server 1 communicates with the PLC 2 and the operator terminal 3 through a communication network. The communication network is not particularly limited, and wired and wireless networks can be used. Examples of communication lines include Internet lines, WWW (World Wide Web), telephone lines, LAN (Local Area Network), SAN (Storage Area Network), and DTN (Delay Tolerant Network). Examples of wireless communication include Wi-Fi (Wireless Fidelity) and Bluetooth (registered trademark).

The management server 1 is equipped with a data processing device 11 and a database 12. The data processing device 11 includes at least one processor 13 and at least one memory 14. The processor 13 includes a CPU (Central Processing Unit). The memory 14 is a volatile memory such as DDR memory, and expands various programs used by the processor 13 and temporarily stores various data. The various programs used by the processor 13 include an operation support program related to the first embodiment. The various data used by the processor 13 include various data stored in the database 12.

Various data stored in the database 12 include data on product specifications (SPC) of a plurality of rolled products (RP) manufactured on a rolling line (RL). The various data also include data on the operation status (OPS) of the rolling line (RL) during the production of these rolled products (RP), and data on the rolling line during the production of these rolled products (RP) Data on the Operator Manipulation (OPM) of the actuators of the (RL) and the quality (QLT) of these rolled products (RP) are included.

Data related to product specifications (SPC) is data included in manufacturing command information (rolling command information) held by PLC 2. Data regarding the operation status (OPS) is data that the PLC 2 acquires from the rolling line RL. These data are regularly updated through communication with PLC (2). Data related to operator operation (OPM) is regularly updated through communication with the operator terminal 3. Additionally, since data regarding operator operation (OPM) is input to the actuator of the rolling line RL, this data may be provided to the management server 1 via the rolling line RL (PLC 2). .

Data on quality (QLT) is data on each quality (eg, surface quality, and size quality evaluated by sheet thickness and sheet width) of a plurality of rolled products (RP). Data on quality (QLT) is updated by the management server 1 regularly acquiring inspection data performed after production of these rolled products (RP).

Fig. 2 is a diagram showing a configuration example of data related to product specifications (SPC). In the example shown in FIG. 2, data on product specifications (SP1 to SNx) of a plurality of rolled products (RP) are combined with data for lot numbers (LT1 to LT4). The lot number is set for every 100 to 200 rolled products (RP). The example shown in FIG. 2 is a data configuration example when paying attention to the rolling history of a certain day, and on this day, 4 lots are rolled. In addition, the period of attention of the rolling history is not particularly limited, and for example, attention may be paid to the rolling history of one week or the rolling history of one month may be paid attention to.

Product specifications are divided into x groups (x > i > 2). The product specifications of SP1 to SPx are specified, for example, by a combination of grade classification (AA to YY) and size classification (SZ1 to SZz). The grade classification of AA to YY is determined by referring to, for example, JIS standards or DIN standards. The size classification of SZ1 to SZz (z > j > 2) is determined, for example, based on the combination of the plate thickness and plate width of the rolled product (RP).

Furthermore, in the example shown in FIG. 2, the product specifications are specified by a combination of grade classification and size classification, but this combination may be additionally combined with classification of other elements such as temperature classification and rolling method classification.

Fig. 3 is a diagram showing a configuration example of data related to operation status (OPS). In the example shown in FIG. 3, data on the operation error items (OPS_ER1 to OPS_ERp) of a plurality of rolled products (RP) and the number of occurrences thereof are combined with data on the lot number and product specifications. The historical period of data on operation status (OPS) is the same period as that of data on product specifications (SPC) described in FIG. 2 (for example, 1 day). The operation error items of OPS_ER1 to OPS_ERp (p > 2) are set to correspond to events that lead to stopping the normal operation of the rolling line RL. Examples of such events include material fracture during rolling, engagement failure, and bottom end buckling.

Fig. 4 is a diagram explaining data related to operator operation (OPM). The operator OP, who is in charge of the manufacturing process on the rolling line RL, monitors various information output to the HMI (e.g., display groups (DPG1 and DPG2) shown in FIG. 1) of the operator terminal 3. do. Then, when it is determined that it is necessary to participate in this manufacturing process, the operator OP operates the input device of the operator terminal 3 and transmits various operation commands to the actuator. Examples of the actuator here include a hydraulic cylinder that controls the roll gap, a drive motor that controls the roll speed, and a water pump that controls coolant.

FIG. 4 shows an example of the transition of time series data (ACT) of the operation command transmitted from the operator terminal 3 to the actuator. Data related to operator manipulation (OPM) is generated based on the results of analysis processing for this time series data. Additionally, this analysis processing and data generation processing related to operator operation (OPM) are performed by the management server 1 (e.g., processor 13).

When there is involvement in the manufacturing process by the operator (OP), the data (ACT) changes. If the data (ACT) acquired during the manufacture of a rolled product (RP) changes frequently, the operator (OP) is aware of any risks affecting the manufacturing process of this rolled product (RP), or , it is assumed that some kind of trouble has already occurred in the manufacturing process. In addition, the recognition of such risks and the occurrence of troubles can be expected even when the speed of change in data (ACT) (dACT/dt) is large.

In the analysis processing of the data (ACT), for example, when the number of times the data (ACT) changes is greater than the upper limit, data indicating that an error has occurred (hereinafter also referred to as “error data”) is provided. In another example, error data is given when the change rate (dACT/dt) exceeds the upper limit rate. Error data is assigned to a combination of the lot number of the rolled product (RP) and product specification data. The error data may be data that specifies the type of actuator. When there are multiple actuators of the same type, the error data may be data that identifies the actuator.

Fig. 5 is a diagram showing a configuration example of data related to quality (QLT). In the example shown in Fig. 5, data on quality error items (QLT_ER1 to QLT_ERq) of a plurality of rolled products (RP) and whether or not they occur (presence: 0, absence: 1) are combined with data of the lot number and product specifications. It is done. The historical period of data on quality (QLT) is the same period as that of data on product specifications (SPC) described in Figure 2 (eg, 1 day). The quality error items of QLT_ER1 to QLT_ERq (q > 2) are set in accordance with preset quality standards. Examples of quality standards include standards for surface quality and standards for size quality evaluated by plate thickness and plate width.

Various data stored in the database 12 are processed by the processor 13. This processing includes (i) calculation processing of the error occurrence rate (α) in the rolled product (RP), (ii) setting processing of the manufacturing difficulty level (DLv) of the rolled product (RP), and (iii) manufacturing difficulty level. Transmission processing of (DLv) is included.

(i) The calculation process of the incidence rate (α) is at least the following: errors that occurred in the operating conditions of the rolled product (RP), errors that occurred in the operator's operation of the actuator, and errors that occurred in the quality of the rolled product (RP). It is carried out for one person.

The occurrence rate of errors in the operation situation (α_OPS) is the ratio of the number of occurrences of operation error items (N_Eops) included in the data on the operation situation (OPS) to the number of manufactured rolls (RP) (N_RP). It can be expressed by The occurrence rate of errors in operator operations (α_OPM) is expressed by the ratio of the number of error data provided (N_Eopm) to data related to operator operations (OPM) to the number of manufactured rolls (RP) (N_RP). You can. The incidence rate of quality errors (α_QLT) is the ratio of the number of occurrences of quality error items included in the data on quality (QLT) (N_Eqlt) to the number of manufactured rolled products (RP) (N_RP). It can be expressed by Additionally, the production number (N_RP) can be determined from production command information.

The incidence rates (α_OPS, α_OPM and α_QLT) are calculated for each product specification (SPC) of the rolled product (RP), respectively. Hereinafter, the occurrence rate (α_OPS) calculated for each product specification (SPC) of the rolled product (RP) is referred to as “occurrence rate (α_OPS(SP)).” In addition, the incidence rate (α_OPM) calculated for each product specification (SPC) of the rolled product (RP) is called “generation rate (α_OPM(SP))”, and the incidence rate (α_QLT) calculated for each product specification (SPC) of the rolled product (RP) ) is called “incidence rate (α_QLT(SP))”. If the incidence rates (α_OPS(SP), α_OPM(SP), and α_QLT(SP)) are not specified, they are collectively referred to as “incidence rates (α(SP)).”

(ii) The setting process of the manufacturing difficulty (DLv) is based on at least one of the incidence rates (α_OPS(SP), α_OPM(SP), and α_QLT(SP)) calculated in (i) the calculation process of the incidence rate (α). It is carried out. Like the incidence rate (α(SP)), the manufacturing difficulty (DLv) is calculated per product specification (SPC) of the rolled product (RP). Hereinafter, the manufacturing difficulty level (DLv) calculated for each product specification (SPC) of the rolled product (RP) is referred to as “manufacturing difficulty level (DLv(SP)).”

Manufacturing difficulty (DLv(SP)), for example, divides the incidence rate (α(SP)) into two or more levels at one or more preset boundary values, such as "DLv: LV1", "DLv: LV2", Manufacturing difficulty (DLv(SP)) can be set according to the numerical range to which the incidence rate (α(SP)) falls, such as “DLv: LV3”. The value of the incidence rate (α(SP)) may be set as the manufacturing difficulty level (DLv(SP)).

In calculating the incidence rate (α), if two or more incidence rates (α(SP)) are calculated, use the following equation (1), which includes a weighting coefficient (β) for each incidence rate (α(SP)). Thus, the “comprehensive” manufacturing difficulty (hereinafter also referred to as “comprehensive difficulty”) (CDLv(SP)) may be calculated.

Additionally, the weighting coefficient (β) represents the relative weighting of two or more occurrence rates (α(SP)) used in the calculation of the comprehensive difficulty level (CDLv), and is a calculation factor (in short, the error) of these occurrence rates (α(SP)). element) is set in advance. However, regarding the weighting coefficient (ops) of an error in an operation situation, when a delay occurs in the manufacturing process due to the occurrence of this error, this delay time may be measured. Also, depending on the length of this delay time, the relative values of the weighting coefficient (βopm) for errors in operator (OP) operation (βopm) and the weighting coefficients for errors in quality (βqlt) may be adjusted. do. Alternatively, when production decreases due to an error occurring in the operating situation, this decrease may be measured and the relative value of the weighting coefficient (βopm) may be adjusted.

(iii) The transmission process of the manufacturing difficulty level (DLv) (or comprehensive difficulty level (CDLv)) transmits the data of the manufacturing difficulty level (DLv) set in the (ii) manufacturing difficulty level (DLv) setting process to the operator terminal 3. It is a process that is done.

Returning to Fig. 1, the description of the configuration example of the rolling system continues. PLC 2 is a calculator that calculates various settings in the rolling line RL. The PLC 2 communicates with control devices for various actuators provided in the rolling line RL and various sensors provided in the rolling line RL. For example, a control command calculated based on a setting calculation and an operation command received from the operator terminal 3 are transmitted from the PLC 2 to the control device. Data regarding the state of the actuator is transmitted from the control device to the PLC 2. Various sensors include a thermometer that measures the temperature of the intermediate product (hereinafter also referred to as “rolled material (MR)”), a plate thickness gauge that measures the plate thickness of the rolled material (MR), and a load gauge that measures the load on the rolling mill. , a speedometer that measures roll speed, etc. are examples. Measurements by these sensors are transmitted to PLC (2).

The operator terminal 3 is a terminal for the operator OP to monitor the manufacturing process in the rolling line RL or to participate in the manufacturing process. The operator terminal 3 is connected to the display groups (DPG1 and DPG2). For example, images from a surveillance camera formed on the rolling line RL are output to the display group DPG1. To the display group DPG2, data measured by various sensors of the rolling line RL, data regarding the operation of the actuator in charge of the operator OP, etc. are output. Although not shown, an input device is provided in the operator terminal 3. If it is determined that there is a need to intervene in the manufacturing process, the operator (OP) manipulates this input device.

In the first embodiment, data for supporting the operator OP (hereinafter also referred to as “Assist Data (ASS)”) is output from any one of the display group DPG2. The support data (ASS) includes data of the manufacturing difficulty level (DLv) (or comprehensive difficulty level (CDLv)) received from the management server 1. The data on the manufacturing difficulty level (DLv) is for the manufacturing object (TP) manufactured on the rolling line (RL). Output control of the assistance data (ASS) is performed by a processor (not shown) of the operator terminal 3.

Here, the manufacturing target (TP) refers to a product before manufacturing on the rolling line (RL) has been completed, that is, a product for which manufacturing on the rolling line (RL) will be performed in the future, and manufacturing on the rolling line (RL). It refers to products that are being implemented between Korea and China. On the other hand, the manufacturing difficulty level (DLv) is set for the rolled product (RP), that is, the product for which manufacturing on the rolling line (RL) has been completed. Therefore, the manufacturing difficulty level (DLv) of the manufacturing target (TP) is not actually set.

However, if the product specification (SPC) of the manufacturing object (TP) is the same as that of the rolled product (RP), it is predicted that the manufacturing difficulty level (DLv) of the former will be the same as that of the latter. So, in the embodiment, the data on the manufacturing difficulty level (DLv) of the rolled product (RP) having the same product specifications (SPC) as the product specification (SPC) of the manufacturing object (TP) is used as that of the manufacturing object (TP). and output from the display group (DPG2).

1-2. Data processing example

Next, a data processing example particularly related to the first embodiment will be described. 6 and 7 are diagrams illustrating examples of data processing performed by the management server 1 (processor 13). The processing flows shown in FIGS. 6 and 7 are each repeatedly executed at regular intervals.

In the routine shown in FIG. 6, various data are first acquired (step S11). The various data are data stored in the database 12. Various data include data on the product specifications (SPC) of a plurality of rolled products (RP), data on the operating status (OPS) of the rolling line (RL) during the production of these rolled products (RP), and data on the rolling products (RP) Data on operator operation (OPM) on the actuator of the rolling line RL during production of the product RP, and data on the quality (QLT) of these rolled products RP are exemplified.

Following the processing of step S11, the error occurrence rate (α(SP)) is calculated (step S12). Calculation of the incidence rate (α(SP)) is performed on the data acquired in step S11. Specifically, when data on the operating situation (OPS) is obtained, the occurrence rate (α_OPS(SP)) is calculated. When data on operator manipulation (OPM) is acquired, the occurrence rate (α_OPM(SP)) is calculated. If data on quality (QLT) are obtained, the incidence rate (α_QLT(SP)) is calculated.

Following the processing of step S12, the manufacturing difficulty (DLv(SP)) is calculated (step S13). The calculation of the manufacturing difficulty (DLv(SP)) is, for example, based on the incidence rate (α(SP)) calculated in step S12, for each calculation element (in short, the error element) of this incidence rate (α(SP)). It is carried out. When calculating the overall difficulty level (CDLv(SP)), the incidence rate (α(SP)) calculated in step S12 is applied to the above equation (1). Additionally, data on the manufacturing difficulty level (DLv(SP)) or the overall level of difficulty (CDLv(SP)) obtained by the process in step S13 are stored in the database 12.

In the routine shown in Fig. 7, first, it is determined whether or not the manufacturing object TP is scheduled (step S21). The processing of step S21 is performed, for example, with reference to schedule data included in production command information held by PLC 2. The reference range of the schedule data is, for example, that of the day of operation of the rolling line (RL). In another example, schedule data for a lot to be manufactured next to the lot currently being manufactured is referenced.

Following the processing of step S21, data of the product specification (SPC) of the manufacturing target (TP) is specified (step S22). The processing of step S22 is performed, for example, with reference to production command information held by PLC 2.

Following the processing of step S22, the manufacturing difficulty level (DLv(SP)) of the manufacturing target TP is specified (step S23). In the processing of step S23, for example, the database 12 is referenced using the product specification (SPC) of the manufacturing target (TP) specified in the processing of step S22. Thereby, the manufacturing difficulty (DLv(SP)) and/or the overall difficulty (CDLv(SP)) of the rolled product (RP) having the same product specifications (SPC) as the product specifications (SPC) of the manufacturing object (TP) are specified. .

Following the processing in step S23, data on the manufacturing difficulty level (DLv(SP)) is transmitted to the operator terminal 3 (step S24). In the process of step S24, specifically, data of the manufacturing difficulty level (DLv(SP)) and/or the comprehensive level of difficulty (CDLv(SP)) specified in the process of step S23 are transmitted to the operator terminal 3. When transmitting data, the data of the calculation element (in short, the error element) of the occurrence rate (α(SP)) used in calculating the manufacturing difficulty (DLv(SP)) and/or the overall difficulty (CDLv(SP)) is this. It may be transmitted together with .

The data of the manufacturing difficulty level (DLv(SP)) and/or the overall level of difficulty (CDLv(SP)) transmitted to the operator terminal 3 through the above processing are output from the display group DPG2 as support data ASS.

1-3. effect

According to the first embodiment described above, useful information such as data on the manufacturing difficulty level (DLv(SP)) and/or the comprehensive level of difficulty level (CDLv(SP)) can be provided to the operator OP. If additional data are provided on the calculation factors (in short, error factors) of the incidence rate (α(SP)) used in the calculation of the manufacturing difficulty level (DLv(SP)) and/or the overall difficulty level (CDLv(SP)), It is possible to provide the operator (OP) with useful information, such as information on error factors to be aware of in the manufacturing process of the object (TP).

2. Second embodiment

2-1. Configuration example of rolling system

FIG. 8 is a diagram illustrating a configuration example of a rolling system to which the rolling line operation support device according to the second embodiment is applied. The configuration example shown in FIG. 8 is basically the same as the configuration example shown in FIG. 1. The difference between the former and the latter is that the management server 1 has a database 15 separately from the database 12.

The database 15 contains the State of Material to be Rolled (SMR) of the rolled product (RP) (more precisely, the rolled material (MR)) acquired on the rolling line (RL) during the production of the rolled product (RP). Data regarding (SMR) is stored. Data on the state (SMR) are obtained directly from various sensors provided in the rolling line (RL), such as the temperature and plate thickness of the rolled material (MR), the load applied to the rolled material (MR), and the rolling speed. Data, or data calculated based on this acquired data, are illustrated.

The database 15 also stores data (EX_SMR) extracted from data regarding the state (SMR). The data (EX_SMR) is data about the state (SMR) when the occurrence of an error is not confirmed in the quality of the rolled product (RP), the operation status (OPS) of the rolling line (RL), and the operator operation (OPM). . The errors referred to here are exemplified by operation error items (OPS_ER1 to OPS_ERp) illustrated in FIG. 3, operator operations (OPM) to which error data is provided illustrated in FIG. 4, and quality error items (QLT_ER1 to QLT_ERq) illustrated in FIG. 5. .

The database 15 also stores data (EX_OPM) extracted from data related to operator operations (OPM). The data (EX_OPM) is data regarding the quality of the rolled product (RP) and the operator operation (OPM) when the occurrence of an error is not confirmed in the operation status (OPS) of the rolling line (RL). Additionally, extraction processing of data (EX_OPM) and data (EX_SMR) is performed by management server 1 (e.g., processor 13).

Various data stored in the database 15 are processed by the processor 13. This processing includes (i) generation processing of data of the exemplary state of the rolled material (MR), (ii) generation processing of data of the operator's exemplary operation, and (iii) generation processing of passing (指南) data for the operator. and (iv) transmission processing of Advice Data (ADV).

(i) The generation process of model state data is performed for each product specification (SPC) of the rolled product (RP) based on the data (EX_SMR). (ii) The data generation process of the exemplary operation is performed for each combination of the product specification (SPC) of the rolled product (RP) and the actuator, based on the data (EX_OPM). The generation processing of (i) and (ii) is performed, for example, each time data (EX_SMR and EX_OPM) is generated.

(iii) The generation process of passing data (ADV) is performed during manufacturing of the manufacturing object (TP). The generation process of (iii) includes, for example, data on exemplary status regarding a rolled product (RP) having the same product specifications (SPC) as the manufacturing object (TP) and data on the performance status of the manufacturing object (TP). It is implemented based on The data on the performance status of the manufacturing object (TP) refers to data regarding the state of the manufacturing object (TP) acquired on the rolling line RL during production of the manufacturing object (TP). In this example, the passed data (ADV) is the data in the exemplary state and the difference between the data in the exemplary state and the data in the performance state.

In another example, passing data (ADV) is generated using data from a non-exemplary state of a rolled product (RP) to the same product specification (SPC) as the object to be manufactured (TP). Data in a non-standard state include the operating status (OPS) of the rolling line (RL) during the production of the rolled product (RP), the operator operation (OPM) during the production of the rolled product (RP), and the rolling product (RP). This refers to data regarding the status (SMR) when an error in the quality (QLT) of the product (RP) is confirmed. Generation of data in non-standard states is performed for each product specification (SPC) of rolled products (RP). The passing data (ADV) in this example is data in a good state and a non-standard state.

In another example of the generation process of (iii), data of the operator's exemplary operation during the production of a rolled product (RP) having the same product specifications (SPC) as the manufacturing object (TP), and manufacturing of the manufacturing object (TP) Passage data (ADV) is generated based on the data of the operator's performance manipulation during the operation. The data of the operator's performance operation refers to data regarding the operator operation (OPM) performed on the same actuator as the actuator that generated the data of the exemplary operation during the manufacture of the manufacturing object (TP). In this example, the passing data (ADV) is the data of the model operation and the difference between the data of the model operation and the data of the performance operation.

In another example, passing data (ADV) is generated using data of an operator's non-standard operation during the manufacture of a rolled product (RP) having the same product specifications (SPC) as the manufacturing object (TP). Data on non-standard operation refers to the operating status (OPS) of the rolling line (RL) during the production of rolled products (RP) and the occurrence of errors confirmed in the quality (QLT) of these rolled products (RP). Indicates data of operator operation (OPM). The generation of data for non-conforming operations is carried out for each product specification (SPC) of rolled products (RP). The passing data (ADV) in this example is data for exemplary operations and non-model operations.

In another example, data on optimal operation of the actuator to avoid the occurrence of errors is generated by applying data on exemplary and non-exemplary operations to known data analysis techniques such as AI and machine learning. The passing data (ADV) in this example is data of optimal operation.

The (iv) passing data (ADV) transmission process is a process for transmitting to the operator terminal 3 the passing data (ADV) set in (iii) the passing data (ADV) generation process.

In the first embodiment, data on the manufacturing difficulty level (DLv) as support data (ASS) was output from any one of the display groups (DPG2). In the second embodiment, the passage data (ADV) is output from any one of the display groups (DPG2) in the form of addition to the data of the manufacturing difficulty level (DLv). In short, in the second embodiment, manufacturing difficulty level (DLv) and progress data (ADV) are output as support data (ASS).

2-2. Data processing example

Next, a data processing example particularly related to the second embodiment will be described. 9 to 11 are diagrams illustrating examples of data processing performed in the management server 1 (processor 13). The processing flows shown in FIGS. 9 to 11 are each repeatedly executed at regular intervals.

In the routine shown in Fig. 9, various data are first acquired (step S31). The various data are data stored in the databases 12 and 15. Examples of various types of data include data described in the description of the process in step S11 in FIG. 6 . The various data also include data regarding the state (SMR) of the rolled product (RP) acquired in the rolling line (RL) during production of the rolled product (RP).

Following the processing in step S31, extraction data is generated (step S32). The extracted data referred to here is at least one of the data (EX_SMR and EX_OPM). The generation of data (EX_SMR) is based on the data on the state (SMR) acquired in the processing of step S31, the quality of the rolled product (RP), the operation status (OPS) of the rolling line (RL), and the operator operation (OPM). This is carried out by extracting data for which the occurrence of an error has not been confirmed. The generation of data (EX_OPM) is based on the data on the operator operation (OPM) acquired in the processing of step S31, the quality of the rolled product (RP), and errors in the operation status (OPS) of the rolling line (RL). This is done by extracting data whose occurrence has not been confirmed.

Following the processing in step S32, model data is generated (step S33). The processing of step S33 is performed based on the extracted data generated in step S32. If data (EX_SMR) is generated in the processing of step S32, data in an exemplary state is generated based on this data (EX_SMR). On the other hand, when data (EX_OPM) is generated in the processing of step S32, data of the model operation is generated based on this data (EX_OPM). Additionally, the model data obtained through the processing in step S33 is stored in the database 15.

In the routine shown in Fig. 10, first, it is determined whether or not the manufacturing object TP is scheduled (step S41). The content of the processing of step S41 is the same as that of step S21 in FIG. 7 . Additionally, following the processing of step S41, data of the product specification (SPC) of the manufacturing target (TP) is specified (step S42). The content of the processing of step S42 is the same as that of step S22 in FIG. 7 .

Following the processing of step S42, exemplary data of the manufacturing object (TP) is specified (step S43). In the processing of step S43, for example, the database 15 is referred to using the product specification (SPC) of the manufacturing target (TP) specified in the processing of step S42. Thereby, exemplary data (i.e., data of exemplary state and exemplary operation) for the rolled product (RP) having the same product specifications (SPC) as the product specifications (SPC) of the manufacturing object (TP) are specified.

Following the processing of step S43, model data is transmitted to the operator terminal 3 (step S44). In the processing of step S44, the model data specified in the processing of step S43 is transmitted to the operator terminal 3. When transmitting exemplary data, non-conventional data (i.e., data with non-conventional states and non-conventional operations) may be transmitted together with this.

The model data transmitted to the operator terminal 3 through the above processing is output from the display group DPG2 as support data (ASS). When non-standard data is transmitted to the operator terminal 3, the non-standard data is output from the display group DPG2 together with the model data.

In the routine shown in Fig. 11, first, model data (i.e., data of model status and model operation) is acquired (step S51). The model data acquired in step S51 is that of the rolled product (RP) having the same product specification (SPC) as the product specification (SPC) of the manufacturing object (TP) being manufactured on the rolling line (RL), and is stored in the database (15) ) is read and output from.

Following the processing of step S51, performance data (that is, data of performance status and performance operation) is acquired (step S52). The performance data acquired in step S52 is data corresponding to the model data acquired in the processing of step S51.

Following the processing of step S52, passing data (ADV) is generated (step S53). The passing data (ADV) is, for example, the difference between exemplary data acquired in step S52 and performance data correspondingly acquired in step S53. Other examples of passing data (ADV) include exemplary data acquired in step S52 and non-exemplary data corresponding to this exemplary data. Another example of advanced data (ADV) is data on the optimal operation of an actuator to avoid the occurrence of errors.

Following the processing of step S53, passing data (ADV) is transmitted (step S54). In the process of step S54, passage data (ADV) generated in the process of step S53 is transmitted to the operator terminal 3.

The passage data (ADV) transmitted to the operator terminal 3 through the above processing is output from the display group DPG2 as assistance data ASS.

2-3. effect

According to the second mode described above, useful information called exemplary data can be provided to the operator (OP). In addition, useful information called passing data (ADV), which includes exemplary data, can also be provided to the operator (OP). Therefore, it is expected to avoid the occurrence of errors in the production of the production object TP on the rolling line RL.

1: Management Server
2:PLC
3: Operator terminal
12, 15: Database
13: processor
14: memory
OP: operator
RL: rolling line
RP: Rolled product
DLv: Manufacturing Difficulty
OPM: Operator operation
OPS: Fishing situation
QLT: Quality
SMR: Status of rolled material
SPC: Product Specification

Claims (7)

As a method of supporting operation in a rolling line,
A step of acquiring various data related to the rolled product manufactured in the rolling line, wherein the various data include data regarding product specifications of the rolled product, data regarding the quality of the rolled product, and manufacturing of the rolled product. A step including data regarding an operation status of the rolling line during production of the rolled product and data regarding an operator's operation of an actuator of the rolling line during production of the rolled product;
Based on the various data, a step of calculating for each product specification the occurrence rate of errors occurring in at least one of the quality of the rolled product, the operation status of the rolling line, and the operator operation;
A step of setting the manufacturing difficulty of the rolled product for each product specification according to the height of the incidence rate;
A step of outputting support data for supporting an operator involved in the manufacturing process of the manufacturing object manufactured on the rolling line from an operator terminal, wherein the support data is data of the manufacturing difficulty of the manufacturing object, A method of supporting operation of a rolling line, comprising a step including data on the manufacturing difficulty of the rolled product having the same product specifications as the product specifications. According to claim 1,
Based on the various data, a step of extracting data for each product specification regarding the quality of the rolled product, the operation status of the rolling line, and the operator operation when the occurrence of an error in the operator operation is not confirmed;
Based on the extracted data of the data related to the operator operation, it further includes a step of generating data of the operator's exemplary operation during operation of the rolling line for each combination of product specifications and actuators,
In the step of outputting the support data from the operator terminal, the support data further includes data of the model operation generated based on the various data for product specifications identical to the product specifications of the product to be manufactured. A method of supporting operation of a rolling line characterized by: According to claim 2,
It further includes a step of acquiring data on performance of the operator's operation during manufacturing of the manufacturing object,
In the step of outputting the support data from the operator terminal, the support data further includes passage data for the operator,
The operation of the rolling line, wherein the passing data is generated based on the data of the performance operation and the data of the exemplary operation generated based on the various data for product specifications identical to the product specifications of the product to be manufactured. How to apply. The method of claim 1 or 2,
The various data further include data regarding the state of an intermediate product of the rolled product obtained on the rolling line during production of the rolled product,
Based on the various data, a step of extracting data for each product specification regarding the quality of the rolled product, the operation status of the rolling line, and the state of the intermediate product when the occurrence of an error is not confirmed in the operator operation. class,
Based on the extracted data of the data regarding the state of the intermediate product, it further includes a step of generating data on the exemplary state of the intermediate product during operation of the rolling line for each product specification,
In the step of outputting the support data from the operator terminal, the support data further includes data of the exemplary state generated based on the various data for product specifications identical to the product specifications of the product to be manufactured. A method of supporting operation of a rolling line characterized by: According to claim 4,
It further includes a step of acquiring data on the performance state of the manufacturing object obtained from the rolling line during manufacturing of the manufacturing object,
In the step of outputting the support data from the operator terminal, the support data further includes passage data for the operator,
The operation of a rolling line, wherein the passing data is generated based on the data on the performance state and the data on the exemplary state generated based on the various data on product specifications identical to the product specifications of the product to be manufactured. How to apply. As a device to support operation in a rolling line,
a storage device storing various data related to rolled products manufactured in the rolling line;
Equipped with one or more processors,
The various data include data on the product specifications of the rolled product, data on the quality of the rolled product, data on the operation status of the rolling line during production of the rolled product, and manufacturing of the rolled product. Contains data regarding operator operation of the actuator of the rolling line in the
The one or more processors,
Based on the various data, processing to calculate for each product specification the occurrence rate of errors occurring in at least one of the quality of the rolled product, the operation status of the rolling line, and the operator operation;
Processing of setting the manufacturing difficulty of the rolled product for each product specification according to the height of the incidence rate,
Processing of outputting support data for supporting an operator involved in the manufacturing process of a manufacturing object manufactured on the rolling line from an operator terminal, wherein the support data has the same product specifications as the product specifications of the manufacturing object. An operation support device for a rolling line, characterized in that it is configured to perform processing including data on the manufacturing difficulty of the product. As a program to support operations on a rolling line,
Processing for acquiring various data related to the rolled product manufactured in the rolling line, wherein the various data include data regarding product specifications of the rolled product, data regarding the quality of the rolled product, and manufacturing of the rolled product. Processing including data on an operation status of the rolling line during production of the rolled product and data on operator operation of an actuator of the rolling line during production of the rolled product;
Based on the various data, processing to calculate for each product specification the occurrence rate of errors occurring in at least one of the quality of the rolled product, the operation status of the rolling line, and the operator operation;
Processing of setting the manufacturing difficulty of the rolled product according to the incidence rate for each product specification according to the height of the incidence rate;
Processing of outputting support data for supporting an operator involved in the manufacturing process of a manufacturing object manufactured on the rolling line from an operator terminal, wherein the support data has the same product specifications as the product specifications of the manufacturing object. A rolling line operation support program characterized by causing a computer to execute processing including data on the manufacturing difficulty of the product.

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