Intelligent steel ladle maintenance management method and system

Abstract

The invention discloses an intelligent steel ladle overhaul management method and system. The steel ladle maintenance management method comprises the steps that an in-service steel ladle database is set, and the in-service steel ladle database is used for recording and storing in-service data information of in-service steel ladles; a statistical analysis module is arranged, and the statistical analysis module is used for obtaining in-service data information of the in-service steel ladle from the in-service steel ladle database and then analyzing the in-service data information of the in-service steel ladle to obtain the next maintenance time point of the in-service steel ladle; and an automatic operation and maintenance system is arranged, and the automatic operation and maintenance system is used for automatically formulating a steel ladle maintenance resource allocation strategy according to the steel ladle maintenance evaluation standard and the in-service data information of the in-service steel ladle. According to the steel ladle overhaul management method and system, manual intervention is not needed, the turnover efficiency of in-service steel ladles is improved, and the labor cost is greatly reduced.

Description

Technical Field

[0001] This invention relates to a ladle management method, and more particularly to an intelligent ladle maintenance management method and system. Background Technology

[0002] As the core equipment for holding and transferring molten steel in steel production, the steel ladle is constantly in use under normal production conditions in a steel plant. The use of the steel ladle has a limited lifespan. When the lifespan expires, the steel ladle needs to be repaired to extend its lifespan before it can be put back into production.

[0003] Currently, the turnover life of steel ladles is determined manually. Experienced staff determine the next maintenance time based on the performance data of the steel ladle, and then arrange personnel and materials to repair the steel ladle.

[0004] The current problem is:

[0005] Currently, determining the next maintenance time for steel ladles and arranging personnel and materials for ladle repair are all done manually. This requires high labor costs, and the allocation effect of manual methods is not good. For example, occasional ladles may be damaged, which affects the operating efficiency of steel ladles in the steel plant.

[0006] It should be noted that the determination of the next maintenance time for the ladle refers to the maintenance time for a ladle that is in normal use without any abnormalities, determined by the number of times the ladle is used / number of furnaces as specified by the steel plant. Abnormalities refer to damage to the ladle edge, cracks in the body, severe wear of the trunnion, etc. Depreciation requires daily inspection and monitoring by the inspection personnel, and they must keep records. In addition, for individual ladles with major safety hazards, the inspection personnel will judge whether maintenance is necessary based on their experience. This invention does not involve steel leakage caused by damage to the internal refractory material of the ladle. Summary of the Invention

[0007] The purpose of this invention is to provide an intelligent ladle maintenance management method and system, which can monitor in-service ladles in real time and automatically formulate ladle maintenance resource allocation strategies for in-service ladles.

[0008] To achieve the above-mentioned technical objectives, the present invention adopts the following technical solution:

[0009] An intelligent ladle maintenance management method includes: S1, setting up an in-service ladle database to record in-service data information of the in-service ladles; S2, setting up a statistical analysis module to obtain in-service data information of the in-service ladles from the in-service ladle database, analyze the in-service data information of the in-service ladles, and determine the next maintenance time of the in-service ladles; S3, setting up an automatic operation and maintenance system to automatically formulate a ladle maintenance resource allocation strategy based on ladle maintenance evaluation standards and in-service data information of the in-service ladles.

[0010] Furthermore, the method for analyzing the in-service data of the steel ladles to determine the next maintenance time is specifically implemented by: inputting the ladle temperature field, ladle stress distribution area, ladle deformation data during turnover, ladle trunnion wear data, ladle usage time, and ladle furnace usage times into SolidWorks software, performing simulation calculations using SolidWorks software, and finally calculating the next maintenance time of the in-service steel ladles.

[0011] Furthermore, the method of automatically formulating a ladle maintenance resource allocation strategy based on the ladle maintenance evaluation standards and in-service data of in-service ladles includes: automatically generating maintenance plans for in-service ladles in advance based on the prediction of the next maintenance time and workload of in-service ladles; determining the quantity of materials, equipment and personnel required for ladle maintenance; procuring and processing materials in advance; allocating equipment to the maintenance site in advance; and rationally arranging riveters, welders and inspectors to meet the workload, thereby avoiding resource waste.

[0012] Furthermore, the automated operation and maintenance system is also used to provide early warnings for in-service ladles that require maintenance based on the next maintenance schedule of the in-service ladles.

[0013] Furthermore, the in-service data information of the steel ladle includes basic information, operational data, annual maintenance data, and accident and hazard records. The basic information of the steel ladle includes: ladle specifications, serial number, manufacturer, manufacturing date, material, and volume. The operational data of the steel ladle includes: usage time, amount of molten steel filled each time, operating conditions, temperature, cumulative number of furnace uses, and condition inspection records. The annual maintenance data of the steel ladle includes: deformation of the ladle shell, records of repairing cracks in the body, and non-destructive testing data. The accident and hazard records of the steel ladle include: detailed records of the time, process, cause analysis, and handling measures of the accidents and hazards.

[0014] An intelligent ladle maintenance management system includes an in-service ladle database, a statistical analysis module, and an automated operation and maintenance system. The in-service ladle database records in-service data information stored in the in-service ladle database. The statistical analysis module retrieves the in-service data information from the in-service ladle database, analyzes the data, and determines the next maintenance time for each in-service ladle. The automated operation and maintenance system automatically formulates a ladle maintenance resource allocation strategy based on ladle maintenance evaluation standards and the in-service data information of the in-service ladles.

[0015] Furthermore, the ladle maintenance management system can implement the ladle maintenance management method described above.

[0016] The main advantages of the intelligent ladle maintenance management method and system of the present invention compared with the prior art are as follows:

[0017] The ladle maintenance management method and system of the present invention can monitor in-service ladles in real time, automatically optimize resource allocation for in-service ladle maintenance without manual intervention, which not only improves the turnover efficiency of in-service ladles, but also greatly reduces labor costs. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the computer program implementation of the intelligent ladle maintenance management method and system of the present invention. Detailed Implementation

[0019] First, to facilitate a clear and accurate description of the technical solution later in the text, the following definitions are made in advance:

[0020] Definition 1: The term "in-service steel ladle" as used in this article refers to steel ladles that are in circulation or that are being taken offline for maintenance.

[0021] The following provides further details on specific embodiments of the present invention:

[0022] This embodiment provides an intelligent ladle maintenance management method. The implementation background of this ladle maintenance management method is a steel plant. Its function is to determine the next maintenance time of the in-service ladles that are in the turnover state in the steel plant, and to automatically optimize resource allocation for the maintenance of in-service ladles.

[0023] See Figure 1 The ladle maintenance management method of this embodiment includes the following steps S1 to S3.

[0024] S1. Set up a database and define the database name as "In-Service Steel Ladle Database". This In-Service Steel Ladle Database is used to record and store the in-service data information of all in-service steel ladles.

[0025] The in-service data includes basic information, operational data, annual maintenance data, and records of accidents and potential hazards. In other words, a basic file is created for each in-service ladle in the in-service ladle database to facilitate monitoring of its basic condition and to statistically analyze the number of furnaces put into production.

[0026] The basic information of in-service steel ladles mainly refers to: ladle specifications, serial number, manufacturer, date of manufacture, material, and volume, etc.

[0027] The operating data of in-service steel ladles mainly refers to: usage time, amount of molten steel filled each time, operating conditions, temperature, cumulative number of furnace uses, condition inspection records, and other data.

[0028] The annual maintenance data of in-service steel ladles mainly refers to: the deformation of the ladle shell, records of repairing cracks in the body, non-destructive testing data, and other data.

[0029] The accident and hazard records of in-service steel ladles mainly refer to: if there are any safety accidents (such as steel leakage) or safety hazards related to steel ladles, record in detail the time, process, cause analysis, and handling measures of the accident or hazard.

[0030] It should be noted that when entering the in-service data information of steel ladles into the in-service steel ladle database, the existing DSMP data management platform can be used;

[0031] It should be noted that DSMP mentioned in this embodiment refers to the Data Standard Management Platform: DSMP is the core standard component of 3DSky Information's integrated platform solution for standardized management. The Data Standard Management Platform provides comprehensive management of enterprise data execution standards, considering data templates and data structures from a modular and functional perspective, and defining and managing data encoding and data constraints. Its functions include data model definition, data model template definition, data template standard definition, data template meta-attribute definition, data template constraint rule definition, data encoding rule definition, data model publishing, and data model maintenance, providing pre-built, professional master data models.

[0032] It should be noted that the in-service ladle database is connected to the on-site production process control system, and the in-service ladle database can automatically obtain relevant data of in-service ladles from the on-site production process control system.

[0033] This includes: the time the in-service ladle is put into use after each maintenance and the time it is taken off the line for maintenance, how many heats of molten steel were produced by the ladle during that time period, the weight of each heat of molten steel, ladle surface temperature monitoring records, thermal deformation monitoring records, and thermal stress monitoring data, etc.

[0034] S2 sets up a statistical analysis module, which is essentially a software module, or application program, that runs on a computer terminal.

[0035] The function of this statistical analysis module is:

[0036] The statistical analysis module is connected to the in-service ladle database set in step S1, enabling data communication between them. The statistical analysis module can automatically obtain relevant data of in-service ladles from the in-service ladle database, and then compare and analyze these data with the ladle maintenance evaluation standards to determine the next maintenance time point for each in-service ladle. Based on this time point, an early warning can be issued for in-service ladles that need maintenance.

[0037] In this embodiment, "the statistical analysis module analyzes the relevant data of in-service steel ladles to determine the next maintenance time for each in-service steel ladle" specifically includes:

[0038] Various data, such as ladle temperature field, ladle stress distribution area, ladle deformation data during turnover, ladle trunnion wear data, ladle service time, and number of times the ladle has been used in the furnace, are input into SolidWorks software. SolidWorks software is then used for simulation calculations to finally determine the next maintenance time for the in-service ladle.

[0039] It should be noted that the "deformation data during the turnover process of steel ladles" mentioned earlier specifically refers to the data on the different pressures and temperatures that different parts of the steel ladle are subjected to under high temperature when it is filled with molten steel, and the data on the most easily deformed locations and amounts of deformation when the steel ladle is poured out of the molten steel.

[0040] In summary, the function of the statistical analysis module is to analyze and predict the next maintenance time of in-service steel ladles based on various data related to them (data stored in the in-service steel ladle database), so as to provide early warning for in-service steel ladles that need maintenance.

[0041] S3 sets up an automated operation and maintenance system, which is essentially a software system, or rather, an application program, running on a computer terminal.

[0042] The function of this automated operation and maintenance system is:

[0043] The ladle maintenance evaluation criteria are input into the automated operation and maintenance system. Furthermore, this automated operation and maintenance system is communicatively connected to the statistical analysis module set in step S2, enabling data connectivity. The statistical analysis module can push the derived "next maintenance time point for in-service ladles" to the automated operation and maintenance system. In other words, the automated operation and maintenance system can automatically obtain the "next maintenance time point for in-service ladles" from the statistical analysis module. Then, based on the "next maintenance time point for in-service ladles" and the "ladle maintenance evaluation criteria," the automated operation and maintenance system can "provide early warnings for in-service ladles requiring maintenance" and "automatically optimize resource allocation."

[0044] Specifically

[0045] The system inputs the evaluation criteria for ladle maintenance, automatically compares the monitoring and testing data of in-service ladles with the standard data, and generates the maintenance requirements for each in-service ladle. At the same time, it uses historical data to predict faults and provide reminders. During the maintenance process, it automatically optimizes resource allocation, further reduces manual intervention, improves maintenance efficiency, and achieves the goal of reducing costs and increasing efficiency.

[0046] It should be noted that the "automatic optimization of resource allocation" specifically refers to the automatic generation of maintenance plans for in-service steel ladles in advance, based on the prediction of the next maintenance time and workload by the automated operation and maintenance system. This plan determines the required materials, equipment, and personnel for the maintenance. Materials can be procured and processed in advance (cutting, rolling, forming, beveling, etc.), equipment can be pre-allocated to the maintenance site, and sufficient riveters, welders, and testing personnel can be rationally assigned to meet the workload, thereby reducing waiting time and labor waste during the maintenance process. Essentially, this forms a resource allocation strategy for steel ladle maintenance.

[0047] It should be noted that the in-service ladle database, statistical analysis module, and automated operation and maintenance system are interconnected, and any two of them can exchange data. The combination of these three components essentially constitutes a ladle maintenance management system to implement the aforementioned ladle maintenance management method.

[0048] The following is a summary of the functional implementation and interrelationships of the in-service steel ladle database, statistical analysis module, and automated operation and maintenance system:

[0049] The in-service steel ladle database is used to automatically acquire relevant data information of in-service steel ladles from the production process control system at the work site, and to store this data information;

[0050] The statistical analysis module is used to analyze and process the "relevant data information of in-service steel ladles" stored in the in-service steel ladle database in order to obtain the next maintenance time of the in-service steel ladles.

[0051] The automated operation and maintenance system is used for,

[0052] 1) Based on the next maintenance time of the in-service steel ladles obtained from the statistical analysis module, provide early warning for the in-service steel ladles that need maintenance;

[0053] 2) Input the ladle maintenance evaluation criteria into the automated operation and maintenance system. The automated operation and maintenance system will automatically formulate a ladle maintenance resource allocation strategy based on the ladle maintenance evaluation criteria and the relevant data information of in-service ladles stored in the in-service ladle database (to make a comprehensive evaluation).

[0054] The main advantages of the ladle maintenance management method of this embodiment are:

[0055] 1) The ladle maintenance management method of this embodiment can monitor the in-service ladles in real time, dynamically determine the next maintenance time of the in-service ladles, and automatically optimize resource allocation for the maintenance of in-service ladles without manual intervention. This not only improves the turnover efficiency of in-service ladles, but also greatly reduces labor costs.

[0056] The ladle maintenance management method of this embodiment also has other advantages, as follows:

[0057] 2) The ladle maintenance management method of this implementation can improve maintenance safety, reduce accident risks, improve maintenance efficiency, reduce production downtime, accurately control costs, reduce losses throughout the ladle's life cycle, drive decision-making with data, improve the level of management refinement, adapt to the trend of intelligent manufacturing, and support the digital transformation of steel enterprises.

[0058] 3) Intelligent management of ladle maintenance, through “automated safety early warning, digitalized process control, and data-driven decision support”, can not only solve the pain points of “over-reliance on experience, information lag, and difficulty in risk control” in traditional maintenance, but also provide core support for steel companies to reduce costs and increase efficiency and ensure production continuity. It is an important practice for the steel industry to transform towards high quality and intelligence.

[0059] The above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An intelligent ladle maintenance management method, characterized in that: The ladle maintenance and management method includes: S1 is set in the in-service steel ladle database, which is used to record in-service data information stored in the in-service steel ladles; S2, set up a statistical analysis module. This statistical analysis module is used to obtain the in-service data information of in-service steel ladles from the in-service steel ladle database, and then analyze the in-service data information of in-service steel ladles to determine the next maintenance time of in-service steel ladles. S3. Set up an automatic operation and maintenance system. This automatic operation and maintenance system is used to automatically formulate a ladle maintenance resource allocation strategy based on the ladle maintenance evaluation standards and the in-service data information of the ladles in service.

2. The intelligent ladle maintenance management method according to claim 1, characterized in that: The method for analyzing the in-service data of steel ladles to determine the next maintenance time for in-service steel ladles includes: The ladle temperature field, ladle stress distribution area, ladle turnover deformation data, ladle trunnion wear data, ladle service time, and ladle furnace usage data are input into SolidWorks software. SolidWorks software is used for simulation calculation to finally calculate the next maintenance time of the in-service ladle.

3. The intelligent ladle maintenance management method according to claim 1, characterized in that: The method for automatically formulating a ladle maintenance resource allocation strategy based on ladle maintenance evaluation standards and in-service ladle data includes: Based on the predicted time of the next overhaul of in-service steel ladles and the workload of the overhaul, the system automatically generates an overhaul plan for in-service steel ladles in advance, determines the required materials, equipment and personnel for the overhaul, procures and processes materials in advance, allocates equipment to the overhaul site in advance, and rationally arranges riveters, welders and inspectors to meet the workload, so as to avoid waste of resources.

4. The intelligent ladle maintenance management method according to claim 1, characterized in that: The automated operation and maintenance system is also used to provide early warnings for in-service ladles that need maintenance based on the next maintenance time of the in-service ladles.

5. The intelligent ladle maintenance management method according to claim 1, characterized in that: The in-service data information of the steel ladle includes basic information, operating data, maintenance data over the years, and records of accidents and potential hazards; Basic information about in-service steel ladles includes: ladle specifications, serial number, manufacturer, manufacturing date, material, and volume; Operating data for in-service steel ladles includes: usage time, amount of molten steel filled each time, operating conditions, temperature, cumulative number of furnace uses, and condition inspection records; The annual maintenance data of in-service steel ladles include: the deformation of the ladle shell, records of body crack repairs, and non-destructive testing data; Accident and hazard records for in-service steel ladles include: detailed records of the time, process, cause analysis, and handling measures of the accident or hazard.

6. An intelligent ladle maintenance management system, characterized in that: The ladle maintenance management system includes an in-service ladle database, a statistical analysis module, and an automated operation and maintenance system. The in-service steel ladle database is used to record in-service data information stored in the in-service steel ladles; The statistical analysis module is used to obtain in-service data information of in-service steel ladles from the in-service steel ladle database, and then analyze the in-service data information of in-service steel ladles to determine the next maintenance time of in-service steel ladles. The automated operation and maintenance system is used to automatically formulate a ladle maintenance resource allocation strategy based on the ladle maintenance evaluation standards and in-service data information of the ladles in service.

7. The intelligent ladle maintenance management system according to claim 6, characterized in that: The ladle maintenance management system can implement the ladle maintenance management method as described in any one of claims 2 to 5.

Images