KR20210146721A - Steel manufacturing process loss analysis method using transport planning method - Google Patents

Abstract

The present invention relates to a method for analyzing loss between processes using a transport planning method in a steel manufacturing process. According to the present invention, in production activities from material production to final product warehousing, improvement points for each unit process are suggested by analyzing profit-detrimental factors. An operation management system is constructed based on the concept of cost, such that the quality and profitability can be improved. Also, analysis items for each attribute of necessary operation performance information are coded in advance to create an analysis key, and necessary information is selectively extracted by using the analysis key to calculate a loss index between processes. In addition, the operation performance information can be managed and analyzed to establish countermeasures by recognizing and analyzing loss between processes using the loss index, and operation performance information between processes is managed and process loss is analyzed in a steel manufacturing process.

Description

Steel manufacturing process loss analysis method using transport planning method

The present invention relates to a process loss analysis method using a transportation planning method in a steel manufacturing process. In particular, operation performance information in each product manufacturing process is organized as an analysis key, and the entire process from molten steel to product production using this organized analysis key It relates to a method for analyzing loss in the steel manufacturing process that can easily and accurately analyze necessary cost reduction factors by improving profitability by comprehensively identifying factors for process loss.

In general, the characteristic of the steel manufacturing process is that it is an integrated process in which several processes are continuously flowed, and is divided into four main processes: iron making, steel making, hot rolling, and cold rolling. to produce molten iron Then, the molten iron becomes molten steel together with the cold wire and special elements in the converter of the steelmaking process, and this molten steel is cast in the continuous casting facility of the casting process and made into slabs with a thickness of 230 mm is shipped to In addition, in the hot rolling process, the width and thickness of the steel ingot are rolled using a roughing mill and a finishing mill to make a coil with a thickness of 1.2 to 25.4 mm. Finally, in the cold rolling process, the hot-rolled coil is pickled to remove surface iron oxide, and cold-rolled to a plate thickness of 0.15-3.2 mm at room temperature, followed by annealing, plating, and temper rolling process (Skin Pass Mill). Cold-rolled products include cold-rolled coils, galvanized coils, and electro-galvanized coils.

1 is a flowchart of a general iron making process. Referring to FIG. 1 , from the steel manufacturing process to producing a steel product from molten steel, it goes through several steps necessary for each product use. The materials that go through each of these processes are According to its shape, it is divided into molten steel produced in a converter, slab produced in a continuous casting machine, and coil produced in a winding process. , scale, and other process losses are occurring, and if these process losses are classified by type, quality conversion goods (grade-down), additional process occurrence goods, logistics cost additional goods, process inventory, error rate loss, etc.

In order to prevent such process losses and improve profitability, the overall process loss is comprehensively analyzed by analyzing the operation performance information generated in each process from molten steel to slab, slab to slab, slab to coil, and from coil to product. should be understood as

2 is a block diagram of a process loss analysis system. Referring to FIG. 2, the process loss analysis system collects operation and pumil performance information for each process and transmits it to a host computer. A steelmaking server 21 that collects information and operation performance information and performs quality statistical analysis and quality analysis, and a hot rolling server 22 that collects detailed quality information and operation performance information of the hot rolling process and performs quality statistical analysis and quality analysis; Cold rolling server 23 that collects detailed cold rolling process quality information and operation performance information and performs quality statistical analysis and quality analysis, and macros such as order information, customer information, specifications and usage information, material information, operation performance and quality information ) information management, the host computer 30 that edits and transmits the information necessary to the public server, and the macro information management and operation performance information management related to the quality of the steelmaking, hot rolling and cold rolling processes, that is, specific orders or specifications and uses, material units It consists of a common server 40 that comprehensively analyzes the order progress status, design content, manufacturing history, quality performance, production status, etc. by process from order to shipment.

3 is a flowchart showing a conventional process loss analysis method, and FIG. 4 is a conventional material code system diagram.

Referring to FIG. 3 , the operation performance editing step 31 for collecting and organizing operation performance data such as throughput, production amount, working time, and process loss generation amount, and operation performance by process such as slab, hot rolled coil and cold rolled coil , a product code generation step (32) of giving a corresponding product code such as a code name and a code system as shown in FIG. 4, and editing the operation performance data by material unit according to the analysis target material selection standard, and the factors causing process loss A process loss analysis step 33 of performing a separate analysis and a process loss calculation step 34 of calculating a process loss for each process according to a process loss reference table; consists of

In such a conventional method, the database is built to manage the operation results of the product to be analyzed only in the unit process, and it is not possible to edit the necessary information by connecting each unit process. is a simple method of analyzing operation performance information for each unit process, so there is a problem in that it is not possible to continuously manage information from molten steel to product production and to analyze process loss factors between processes.

In this regard, the cost of loss between processes refers to the factors that impede profits in production activities from the production of slabs from molten steel to final products such as slabs, hot-rolled coils, cold-rolled coils, galvanized coils, and electro-galvanized coils, There is a need for a method to analyze process losses between processes by systematically storing operational performance information on these profit-impeding factors.

The present invention has been devised to solve the above problems. Therefore, an object of the present invention is to organize operation performance information in each product manufacturing process as an analysis key, and use this organized analysis key to process the entire process from molten steel to product production It aims to provide a method for analyzing loss in the steel manufacturing process that can easily and accurately analyze the cost reduction factors necessary to improve profitability by comprehensively understanding the factors for process loss.

As another technical means for achieving the object of the present invention, the method of the present invention provides a unique analysis key in the method for analyzing loss in the steel manufacturing process, collecting and organizing material work result data between each process, A first step of editing the job loss information and performing a job performance information organizing process to be stored for each material; A second step of performing an analysis target material selection process in which a product code is assigned to each product and emphasis in connection with an analysis key, and a product, steel type, and order specification are selected according to the selection criteria of the analysis target material; a third step of performing a process loss performance analysis process of selecting and integrating information on the selected analysis target material and analyzing the causes of each process loss; A fourth step of performing a process loss flowchart creation process of creating a flow chart for process loss between spaces by accumulating the amount of loss between each process based on the analyzed analysis code; It is characterized in that it consists of

According to the present invention as described above, when the inter-process loss analysis method of the present invention is applied, the following effects can be expected. First, when the operation performance information is stored in the database for each unit process, it is possible to track the operation performance information of the material unit in each process by managing the analysis key, which is a common item.

Second, by managing the analysis code, the cost of process loss incurred in each process for the analysis code to be analyzed can be identified by cause.

The above description is merely a description of one embodiment of the present invention, and various changes and modifications are possible within the scope of the present invention.

1 is a flowchart of a general iron making process.
2 is a block diagram of a process loss analysis system.
3 is a flowchart showing a conventional process loss analysis method.
4 is a system diagram of a conventional material code.
5 is a flowchart showing a method according to the present invention;
6A and 6B are detailed flowcharts of FIG. 5 .
7 is a system diagram of a material code and analysis key according to the present invention.
8 is an analysis code system diagram according to the present invention.
9 is a flow chart of a process loss according to the present invention.

Hereinafter, a configuration of an apparatus for performing a method for analyzing a loss in a steel manufacturing process according to the present invention will be described with reference to the accompanying drawings.

The steel manufacturing process loss analysis system for carrying out the present invention includes a processor computer 10 that collects and transmits operation and pumil performance information for each process to a host computer, collects detailed steel manufacturing process quality information and operation performance information, and collects quality statistics The steelmaking server 21 that performs analysis and quality analysis, the hot rolling server 22 that collects quality detailed information and operation performance information of the hot rolling process, and performs quality statistical analysis and quality analysis, and the cold rolling process quality detailed information and operation performance information The cold-rolled server 23 that collects and performs quality statistical analysis and quality analysis, and macro information management such as order information, customer information, specifications and usage information, material information, operation performance and quality information, and information necessary for a common server Host computer 30 that edits and transmits, macro information management and operation performance information management related to the quality of steelmaking, hot rolling and cold rolling processes, that is, order progress status by process from order to shipment in a specific order, specification, use, and material unit It consists of a public server 40 that comprehensively analyzes design contents, manufacturing history, quality performance, and production status.

The public server 40 is a device for analyzing the loss of the steel manufacturing process according to the present invention, which provides a unique analysis key to collect and organize the material work result data between each process, and edit the job loss information for each The first step (61, 62) of carrying out the process of organizing operation performance information stored by material, and assigning product codes for each product and each emphasis in connection with the analysis key, and according to the selection criteria of the material to be analyzed, The second step 63 of performing the analysis target material selection process of selecting specifications, and performing the process loss performance analysis process of selecting and integrating information on the selected analysis target material and analyzing the cause of each process loss It consists of a third step (64) and a fourth step (65) of performing a process loss flowchart creation process of creating a flow chart for inter-space process losses by accumulating the amount of loss between each process based on the analyzed analysis code, It is composed to comprehensively analyze the loss of the steel manufacturing process.

The operation according to the present invention configured as described above will be described in detail below based on the accompanying drawings.

The present invention manages the analysis key as a common item separately from the material codes set and managed separately for each process, such as slab code, hot rolled coil code, and cold rolled coil code, that is, in addition to the material code managed by each process unit, analysis By additionally setting and managing the key, it is possible to track the operation performance in each process through which the material has passed through the analysis key, and accordingly, operation performance information can be collected and analyzed.

When the present invention is described with reference to FIGS. 5 to 9, first, in the first step 61 and 62, a unique analysis key is given to collect and organize material work result data between each process, and edit job loss information. The process of organizing the operation performance information stored for each material is performed, that is, when collecting and organizing the data of the work results of the materials in each process, a unique analysis key is given to each material, and operation performance information for each process is edited and stored in the corresponding database.

In detail with respect to the first steps 61 and 62, first, in the first process, the materials for which operation results are generated are arranged in the order in which they were worked. Next, in the second process, a unique analysis key as shown in Fig. 7 is assigned to each material. When the slab operation performance occurs, the analysis key is given the same as the slab code, and the hot-rolled coil operation performance occurs. In this case, the hot-rolled coil split code is added to the next digit of the slab code already assigned to the analysis key. Add split code.

And in the third process, operation performance information is organized. Finally, in the fourth process, the organized operation performance information is stored in databases for slabs, hot-rolled coils, and cold-rolled coils for each material.

The present invention is useful for analyzing inter-process process loss and identifying information for establishing improvement plans and making an optimal decision. It is organized by key and stored in the database, and operation performance information must be managed so that the factors of process loss of the entire process from molten steel to product production can be comprehensively identified using this analysis key. At this time, the operation performance information management standard that can comprehensively understand the loss factors of the entire process is set, and the operation performance is managed separately for each process, such as slab operation performance database, hot-rolled coil operation database, cold-rolled coil operation performance database, etc. , the slab operation performance database manages the operation performance information that occurs when a slab is made from molten steel and a slab is made by finishing the slab.

The slab is used as a basic material for producing steel products in an integrated steel process, and when viewed by use, the slab is delivered to a customer in a semi-finished state or used as a material for a hot rolling mill, which is a post-process. The slab processed at the hot rolling mill is called a hot rolled coil, and the hot rolled coil is delivered to the customer as a hot rolled product or supplied as a material for the cold rolling mill, which is a post process. The hot rolled coil processed at the cold rolling mill is called a cold rolled coil, and the cold rolled coil is delivered to the customer as a cold rolled product or supplied as a material for the hot-dip plating plant or annealing plant, which is a post-process. The cold-rolled coil processed in the hot-dip plating plant is called a hot-dip galvanized coil, and the hot-dip plated coil is delivered to the customer as a hot-dip plated product. And the cold rolled coil processed at the annealing plant is called an annealing coil, and the annealed coil is delivered to the customer as an annealing product or supplied as a material for the electroplating plant, which is a post-process. The cold rolled coil processed in the electroplating factory is called the electroplating coil, and the electroplating coil is delivered to the customer as an electroplating product.

Therefore, when a product is produced, in order to consistently track and manage the operation performance information in each process that the product has gone through, a common item that can connect the operation performance information generated in each process is required, and the common item is analyzed as an analysis key. It is said As for the analysis key, the code system is configured as shown in FIG. 7 so that the division code is managed simultaneously in the hot rolling mill and the cold rolling mill in the slab code. That is, if the slab is divided into n pieces when it is made into hot-rolled coils in a hot-rolling mill, the division performance is managed from 1 to n in the hot-rolled division to determine which hot-rolled coil the slab was processed into, and how many cold-rolled coils the hot-rolled coil was processed into. It is configured to be tracked.

As described above, the operation performance information from the slab to each product is stored in various databases. This slab is stored in the slab operation performance database with the slab code as the key, the hot-rolled coil in the hot-rolled coil operation database with the hot-rolled coil code as the key, and cold-rolled. Each coil is stored in the cold-rolled coil operation record database with the cold-rolled coil code as the key. Information such as pickling, annealing, hot-dip plating, and electroplating coils is also stored in each database with the corresponding coil code as the key. And in each database, the analysis key is managed as a common item, and in each database, the analysis key, the slab code, and each coil code have a 1:n correspondence.

The analysis key is uniquely assigned to each material unit. After arranging the operation performance information from the slab to the final product in the working order, when the slab operation performance occurs for each material, the analysis key is given the same as the slab code. , the criteria for assigning a value to the post-process division code among the analysis keys are as follows.

First, if the result of slab delivered to the customer in a semi-finished state is generated, a blank is given to the hot-rolled division of the analysis key. The number of hot-rolled divisions is given as '1' when the slab is processed into one hot-rolled coil, '2' when processed into two hot-rolled coils, and 'n' when processed into n pieces. The cold rolling and pickling division code is blank in the cold rolling and pickling division of the analysis key when the hot-rolled coil is delivered to the customer as a hot-rolled product. It is assigned in the same way as the hot-rolled split number assignment method. As described above, the number of divisions is given to the cold-rolled, hot-dip galvanized, and electroplated divided codes in the same way.

Next, in the second step 63, a product code is assigned to each product and emphasis in connection with the analysis key, and the analysis target material selection process of selecting the product, steel type, and order specification according to the selection criteria of the analysis target material is performed. , it codes the target material to be analyzed by attribute, and this code is called the analysis code, and product codes such as all products, hot rolled products, and cold rolled products are given to each product. Again, products are coded for each steel type. First, a representative steel type code is assigned by grouping similar steel types into a representative steel type, and each steel type constituting the representative steel type uses the corresponding order specification. Codes for other order specifications are assigned in the same way as representative steel grade codes. The codes given in this way connect the analysis key managed in each database to select the order specifications or other order specifications and operation performance information of the target materials to be analyzed.

If the second step 63 is described for each process, in the first process, a product to be analyzed is selected from the analysis target selection criterion table. Next, if you want to subdivide and analyze the steel type within the product selected in the second process, select the representative steel grade or steel grade. When analyzing only the product, select the entire representative steel grade. And in the third process, if you want to analyze by other order specifications within the steel type, select the desired order specification.

That is, the operation performance information stored in each database is given an analysis code for each attribute, and the purpose of this analysis code is to allow the user to easily select and edit the information to be analyzed. It is configured so that the user can selectively select various analysis targets by classifying steel types and product specifications into codes, and assigning detailed codes again. For example, products are subdivided into all products produced in the steel process, and representative steel types are also classified as representative steel types. In the same way as above, process classification and other order specifications also constitute an analysis code system as shown in FIG. 8 . The analysis code plays a role in reducing the target range that the user wants to analyze and selecting so that the information managed in each database can be easily collected and analyzed. Such analysis code classification criteria are registered and used in the analysis target material selection criteria database as shown in FIG. 6 .

In the third step 64, information on the selected analysis target material is selected and integrated, and a process loss performance analysis process of analyzing the cause of each process loss is performed, which determines the period to be analyzed and collects the information from each database. In the second step (63), information on the selected analysis target materials is selected and integrated.

The third step 64 will be described in detail. First, the analysis period is determined in the first process. Next, in the second process, analysis key information of materials corresponding to the analysis code selected in the second step 63 is selected from the Slav database. In the third process, operation performance information by analysis key is collected from the Slav database. In the fourth process, the same analysis key is selected from the hot-rolled coil database as the analysis key selected from the slab database. In the fifth process, operation performance information by analysis key is collected from the hot-rolled coil database. In the sixth process, the same analysis key is selected from the cold rolled coil database as the analysis key selected from the slab database. In the seventh process, operation performance information by analysis key is collected from the cold-rolled coil database. Finally, in the eighth process, the information collected in the third, fifth and seventh processes is integrated for each analysis key.

If the user decides on the subject and period for analysis, the slab code having the corresponding analysis code is selected from the slab database, and items related to the analysis key and operation performance are collected in units of the slab code. After collecting the necessary information from the slab database, the necessary hot-rolling operation information is collected from the hot-rolling database. At this time, the analysis target information is collected by comparing the analysis key in the hot-rolling database with the analysis key in the slab database, and selecting the hot-rolling code having the same slab code of the analysis key. In other databases, operation performance information necessary for analysis is collected in the same way as above.

In the fourth step (65), a process loss flow chart creation process of creating a flow chart for the inter-space process loss by accumulating the amount of loss between each process based on the analyzed analysis code is performed, which in the third step (64) Based on the analysis code based on the integrated operation performance information, the amount of loss generated between processes by each process unit and by cause is aggregated to create a flow chart of process loss between processes.

The fourth step (65) will be described in detail. First, in the first process, the performance information collected in the third step (64) is analyzed for the material throughput and production volume for each process by analysis key, and the process loss occurred in each process. Count by cause. And, in the second process, the error rate for each process and the process loss rate for each cause are calculated using the values calculated in the first process.

Next, in the third process, the process loss by cause is calculated as follows using the calculated value of the first process and the process loss reference table. And, the cost of process loss was calculated using the transportation planning method, which distributes the quantity given during the decision-making regarding facility location and facility arrangement to each facility so that the total transportation cost is minimized while satisfying the needs of each facility. used in case Here, information on the process loss factors that need to be improved in order to minimize the process loss cost is provided. The process loss cost is calculated by Equation 1 below.

Here, k is the type of process loss, I is the material, j is the analysis key, C is the cost, W is the amount of process loss, g, k, i, j are integers, c, w > 0. In the real rate (k = 1), Ckij means k process loss cost of i material j analysis key in the g process, that is, the unit selling price of the product - the unit cost of scrap (or scale). In addition, Wkij is the scrap or scale generation amount of the i material j analysis key in the g process, that is, the material throughput-production amount in the g process. In the quality conversion material (k = 2), Ckij is the k process loss cost of the i material j analysis key in the g process (product selling price before quality conversion - product selling unit price after quality conversion), and Wkij is i material in the g process j This is the amount of quality conversion material generated by the analysis key. For the additional process material (k = 3), Ckij is the cost of k process loss of the i material j analysis key in the g process, and Wkij is the additional process material generation amount of the i material j analysis key in the g process. For the additional logistics cost (k=4), Ckij is the cost of k process loss of the i material j analysis key in the g process, and Wkij is the logistic additional generation of the i material j analysis key in the g process. In the inventory (k = 5), Cij is the cost of k process loss of the i material j analysis key in the g process, and Wij is the process inventory amount of the i material j analysis key in the g process.

Then, in the fourth process, a flow chart of process loss from slab-hot rolling-cold rolling to warehousing is prepared, and in the fifth process, the values calculated in the first, second and third processes are automatically input to the corresponding process location.

To elaborate on the fourth step (65), the collected performance information is aggregated for each analysis code, such as material throughput, product production, and process loss by cause, and with this aggregated value, error rate and process loss for each process Calculate the incidence rate. The real rate is the percentage of product production to material throughput, and the process loss rate is the percentage of process loss to material throughput. Process loss cost is the amount of process loss converted into cost according to the process loss cost standard table. The amount of process loss between each process analyzed above is automatically displayed at the corresponding position in the process loss flow chart between processes.

When storing the operation performance information in the present invention, the slab database manages the analysis code and the analysis key required when collecting information from other databases. And the analysis key is managed as a common item in each process unit database. When the analysis target is determined, desired information is collected from each database through the analysis key. Therefore, when a product is produced, it is meaningful to establish a system that can analyze the amount of process loss between processes by collecting the operation information generated in the processes that the product went through until it was made.

On the other hand, the process loss flow chart between processes prepared in the fourth step (65) can be used as process management improvement directions and decision-making data.

10 processor computer 21 steelmaking server
22: hot rolled server 23: cold rolled server
30: host computer 40: public server

Claims (4)

In the steel manufacturing process loss analysis method,
a first step (61, 62) of collecting and organizing material work result data between each process by giving a unique analysis key, and performing an operation performance information organization process that edits operation loss information and stores it for each material;
a second step (63) of performing an analysis target material selection process in which a product code is assigned to each product and each emphasis in connection with the analysis key, and a product, steel type, and order specification are selected according to the selection criteria of the analysis target material;
a third step (64) of selecting and integrating information on the selected analysis target material and performing a process loss performance analysis process to analyze the cause of each process loss;
a fourth step (65) of performing a process loss flowchart creation process of creating a flow chart for inter-space process loss by accumulating the amount of loss between each process based on the analyzed analysis code; Steel manufacturing process loss analysis method, characterized in that consisting of. According to claim 1, wherein the first step (61, 62)
Sorting the materials for which the operation performance is generated according to the work order;
A unique analysis key is given to each material, but when the slab operation performance occurs, the analysis key is given in the same way as the slab code. adding a coil split code, and adding a cold rolled coil split code to the next digit of the slab code and hot rolled coil split code already assigned to the analysis key when the cold rolled coil operation performance occurs;
organizing business performance information; and
storing operation performance information in a database; Steel manufacturing process loss analysis method comprising a. According to claim 1, wherein the third step (64)
determining an analysis period;
collecting analysis key information of materials corresponding to the selected analysis code from the Slav database;
collecting operation performance information for each analysis key from the Slav database;
selecting the same analysis key from the hot-rolled coil database as the analysis key selected from the slab database;
collecting operation performance information for each analysis key from the hot-rolled coil database;
selecting the same analysis key from the cold-rolled coil database as the analysis key selected from the slab database;
collecting operation performance information for each analysis key from the cold-rolled coil database;
integrating the collected operation performance information for each analysis key; Steel manufacturing process loss analysis method comprising a. According to claim 1, wherein the fourth step (65)
aggregating the amount of material processing, production, and process loss by cause of the performance information collected in the third step for each analysis key;
calculating the error rate for each process and the rate of occurrence of process loss by cause using the aggregated information;
Calculating process loss cost by cause according to the following equation using the aggregated information and process loss cost reference table;
[Equation 1]

Slab - hot rolling - cold rolling - preparing a process loss flow chart until warehousing;
automatically inserting the value calculated in the above process into the corresponding fixed position in the process loss flowchart;
Steel manufacturing process loss analysis method comprising a.

Images