CN117892949A - Intelligent steelmaking scheduling method - Google Patents
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- CN117892949A CN117892949A CN202410035695.0A CN202410035695A CN117892949A CN 117892949 A CN117892949 A CN 117892949A CN 202410035695 A CN202410035695 A CN 202410035695A CN 117892949 A CN117892949 A CN 117892949A
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- 238000000034 method Methods 0.000 title claims abstract description 118
- 238000009628 steelmaking Methods 0.000 title claims abstract description 33
- 238000004519 manufacturing process Methods 0.000 claims abstract description 93
- 238000005266 casting Methods 0.000 claims abstract description 55
- 229910000831 Steel Inorganic materials 0.000 claims abstract description 18
- 239000010959 steel Substances 0.000 claims abstract description 18
- 230000033764 rhythmic process Effects 0.000 claims abstract description 8
- 238000007599 discharging Methods 0.000 claims abstract description 4
- 238000012423 maintenance Methods 0.000 claims abstract description 4
- 238000012544 monitoring process Methods 0.000 claims description 12
- 238000007670 refining Methods 0.000 claims description 12
- 238000004590 computer program Methods 0.000 claims description 6
- 229910052751 metal Inorganic materials 0.000 claims description 6
- 239000002184 metal Substances 0.000 claims description 6
- 229910052720 vanadium Inorganic materials 0.000 claims description 4
- LEONUFNNVUYDNQ-UHFFFAOYSA-N vanadium atom Chemical compound [V] LEONUFNNVUYDNQ-UHFFFAOYSA-N 0.000 claims description 4
- 238000006477 desulfuration reaction Methods 0.000 claims description 3
- 230000023556 desulfurization Effects 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 3
- 238000003860 storage Methods 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 description 1
- 238000005094 computer simulation Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 239000002436 steel type Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
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Abstract
The invention provides an intelligent steelmaking scheduling method, which comprises the following steps: s1, establishing a corresponding whole-flow unit production model for the production of each casting machine; s2, obtaining production boundary constraint conditions; s3, arranging production, and following production boundary constraint conditions and a first procedure principle in the production process; s4, adopting a pulling mode, taking the casting machine as a center, and discharging expected starting time of each process according to standard operation time and standard logistics transportation time of different steel grades of each process in production boundary constraint conditions; s5, adopting a pushing mode, and pushing out planned starting time of each process according to actual production conditions, logistics transportation time, auxiliary operation time and fixed maintenance of each process; s6, obtaining a scheduling method of a full-flow unit production model; the invention provides an intelligent steelmaking scheduling method, which realizes the production rhythm and the overall logistics balance of each unit in each process, maximizes the productivity, performs intelligent scheduling in an up-down linkage manner and shortens the whole flow logistics time.
Description
Technical Field
The invention relates to the technical field of metallurgical steelmaking, in particular to an intelligent steelmaking scheduling method.
Background
Steelmaking scheduling, namely comprehensive production organization rules (such as a process path, standard operation time, necessary auxiliary operation time and the like corresponding to steel types) are used for organizing production based on information of production equipment, operation states, logistics tracking and the like and combining steelmaking production planning requirements.
The current steelmaking scheduling method adopts a manual steelmaking plan to process and units. However, the existing manual assignment method has the problems that the equipment state and the production process are not properly controlled and tracked under the condition of human intervention, and the production of each unit in each procedure is unbalanced and unstable.
Disclosure of Invention
Therefore, the invention aims to provide an intelligent steelmaking scheduling method, which aims to solve the problems of unbalanced and unstable production of each unit in each process, wherein the equipment state and the production process are not properly controlled and tracked in the conventional steelmaking scheduling method.
The invention adopts the following technical means:
an intelligent steelmaking scheduling method comprises the following steps:
s1, establishing a corresponding whole-flow unit production model for the production of each casting machine; the process flow of the full-flow unit production model sequentially comprises vanadium extraction, desulfurization, steelmaking, refining and casting; calculating the casting period of the casting machine and the current casting residual time in real time according to the current parameters of the casting machine;
s2, based on a full-flow unit production model, collecting and summarizing all elements and all information, and obtaining production boundary constraint conditions for information of each machine equipment, large tools, crown blocks, ground vehicles, production processes and steel grade planning regulations of each procedure;
s3, arranging production, and following production boundary constraint conditions and a first procedure principle in the production process;
s4, adopting a pulling mode, taking the casting machine as a center, and discharging expected starting time of each process according to standard operation time and standard logistics transportation time of different steel grades of each process in production boundary constraint conditions; the pulling mode is that the procedure flow of the step S1 is sequentially executed from the back to the front;
s5, adopting a pushing mode, and pushing out planned starting time of each process according to actual production conditions, logistics transportation time, auxiliary operation time and fixed maintenance of each process; the pushing mode is that the procedure flow of the step S1 is sequentially executed from front to back;
s6, calculating a difference value between the expected starting time and the planned starting time to obtain a time difference, and when the time difference is within a specified tolerance range, normally scheduling; when the time difference is larger than the specified tolerance range, the current working procedure needs to slow down the production and logistics rhythm during the positive tolerance event, so that the production can be temporarily not scheduled; when the time difference is smaller than the specified tolerance range, the time difference is a negative tolerance event, and the negative tolerance event indicates that the current procedure needs to accelerate the production and logistics rhythm; stopping the production and shutdown casting machine when the negative tolerance value is too large and the production requirement of the casting machine is not met; and when the negative tolerance value is controllable, timely scheduling and prompting hysteresis, so as to obtain the scheduling method of the full-flow unit production model.
Further, the casting machine current parameters include a working section, a real-time pull rate, a real-time flow rate, a molten steel density and a molten steel weight.
Further, the refining process includes LF refining and RH refining.
Further, the large-sized tool comprises a hot metal ladle, a tundish and a vacuum chamber.
Further, S2 specifically includes:
s21, monitoring equipment states of all working procedure machines in real time, and not scheduling production when the equipment states are in overhauling and fault states;
s22, monitoring loading quantity states and position information of the hot-metal ladle and the ladle tank in real time, monitoring casting periods of different loading quantities in real time, and monitoring expected time of different positions reaching a next working procedure in real time;
s23, tracking the operation states of the crown block and the ground vehicle in real time, and calculating the average operation time of the crown block and the ground vehicle by utilizing big data statistics to serve as standard logistics transportation time;
s24, calculating the standard operation time according to different steel production processes and regulation systems.
Further, the first process principle is as follows: the different working procedures comprise one machine and more than one machine, the different machines comprise one set of equipment and more than one set of equipment, and each machine of each working procedure is used for preferentially scheduling the idle equipment.
Further, when a plurality of casting machines are simultaneously arranged, the production process of the previous working procedure is driven according to the total expected completion time of the production queues of the casting machines, the sum of the expected completion time of each working procedure production queue of each casting machine is dynamically calculated, the casting machines with shorter time are preferentially arranged, and the casting machines with longer time are arranged and assigned to corresponding units according to the arrangement method of each working procedure.
The invention also provides a storage medium comprising a stored program, wherein the intelligent steelmaking scheduling method is executed when the program runs.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor runs and executes the intelligent steelmaking scheduling method through the computer program.
Compared with the prior art, the invention has the following advantages:
the invention provides an intelligent steelmaking scheduling method, which realizes the production rhythm and the overall logistics balance of each unit in each process, maximizes the productivity, performs intelligent scheduling in an up-down linkage manner and shortens the whole flow logistics time.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to the drawings without inventive effort to a person skilled in the art.
FIG. 1 is a schematic diagram of the method of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
As shown in FIG. 1, the invention provides an intelligent steelmaking scheduling method, which comprises the following steps:
s1, establishing a corresponding whole-flow unit production model for the production of each casting machine; the process flow of the full-flow unit production model sequentially comprises vanadium extraction, desulfurization, steelmaking, refining and casting; calculating the casting period of the casting machine and the current casting residual time in real time according to the current parameters of the casting machine; the current parameters of the casting machine comprise operation section, real-time drawing speed, real-time flow rate, molten steel density and molten steel weight. The refining process comprises LF refining and RH refining.
S2, based on a full-flow unit production model, collecting and summarizing all elements and all information, and obtaining production boundary constraint conditions for information of each machine equipment, large tools, crown blocks, ground vehicles, production processes and steel grade planning regulations of each procedure; the large-sized tool comprises a hot metal ladle, a tundish and a vacuum chamber.
S21, monitoring equipment states of all working procedure machines in real time, and not scheduling production when the equipment states are in overhauling and fault states;
s22, monitoring loading quantity states and position information of the hot-metal ladle and the ladle tank in real time, monitoring casting periods of different loading quantities in real time, and monitoring expected time of different positions reaching a next working procedure in real time;
s23, tracking the operation states of the crown block and the ground vehicle in real time, and calculating the average operation time of the crown block and the ground vehicle by utilizing big data statistics to serve as standard logistics transportation time;
s24, calculating the standard operation time according to different steel production processes and regulation systems.
S3, arranging production, and following production boundary constraint conditions and a first procedure principle in the production process; the first working procedure principle is as follows: the different working procedures comprise one machine and more than one machine, the different machines comprise one set of equipment and more than one set of equipment, and each machine of each working procedure is used for preferentially scheduling the idle equipment.
S4, adopting a pulling mode, taking the casting machine as a center, and discharging expected starting time of each process according to standard operation time and standard logistics transportation time of different steel grades of each process in production boundary constraint conditions; the pulling mode is that the procedure flow of the step S1 is sequentially executed from the back to the front;
s5, adopting a pushing mode, and pushing out planned starting time of each process according to actual production conditions, logistics transportation time, auxiliary operation time and fixed maintenance of each process; the pushing mode is that the procedure flow of the step S1 is sequentially executed from front to back;
s6, calculating a difference value between the expected starting time and the planned starting time to obtain a time difference, and when the time difference is within a specified tolerance range, normally scheduling; when the time difference is larger than the specified tolerance range, the current working procedure needs to slow down the production and logistics rhythm during the positive tolerance event, so that the production can be temporarily not scheduled; when the time difference is smaller than the specified tolerance range, the time difference is a negative tolerance event, and the negative tolerance event indicates that the current procedure needs to accelerate the production and logistics rhythm; stopping the production and shutdown casting machine when the negative tolerance value is too large and the production requirement of the casting machine is not met; and when the negative tolerance value is controllable, timely scheduling and prompting hysteresis, so as to obtain the scheduling method of the full-flow unit production model.
When a plurality of casting machines are used for simultaneous production scheduling, the production process of the previous working procedure is driven by the total expected completion time of the production queues of the casting machines, the sum of the expected completion time of each working procedure production queue of each casting machine is dynamically calculated, the casting machines with shorter time are used for priority production scheduling, and the casting machines with longer time are used for scheduling and are assigned to corresponding units according to the scheduling method of each working procedure.
According to the invention, a production scheduling plan is automatically compiled and assigned to a specific unit, logistics time of each unit is automatically calculated and issued, and intelligent steelmaking scheduling is realized.
The invention provides the following technical scheme:
1. and (3) establishing a casting machine pulling speed control model according to the parameters of the current operation section, the real-time pulling speed, the real-time flow speed, the density and the like of the casting machine and combining the whole-flow unit production rules of the vanadium extraction-casting machine taking the casting machine as the center.
2. And dynamically calculating the casting time (expected time) of all the heats to be cast in the same package. And combining the standard operation time length, the standard preparation time length and the logistics time length of the steel clock process path and the steel grade process, and carrying out inverse dynamic simulation calculation on expected starting time of each process along the process path.
3. And dynamically calculating the planned time for reaching the next working procedure unit by taking the actual real-time logistics tracking time for reaching the current unit as a reference and combining the steelmaking plan, the standard operation time length and the logistics time length.
4. The production scheduling mode combining push type and pull type is generally adopted, an interval scheduling-tolerance event-whole flow overall production scheduling model is established through the system, and the production is assigned to a specific unit. The push type aims at conveying the logistics from the front working procedure to the back working procedure with the maximum productivity, and the pull type aims at conveying the real-time demand information flow from the back working procedure to the front working procedure in the opposite direction of the logistics.
5. And collecting all elements and all information, and establishing a period matching production mode by summarizing all information in all aspects of machines, materials, rings, methods and the like and combining time flows in the scheme.
The invention also provides a storage medium comprising a stored program, wherein the intelligent steelmaking scheduling method is executed when the program runs.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor runs and executes the intelligent steelmaking scheduling method through the computer program.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (9)
1. The intelligent steelmaking scheduling method is characterized by comprising the following steps of:
s1, establishing a corresponding whole-flow unit production model for the production of each casting machine; the process flow of the full-flow unit production model sequentially comprises vanadium extraction, desulfurization, steelmaking, refining and casting; calculating the casting period of the casting machine and the current casting residual time in real time according to the current parameters of the casting machine;
s2, based on a full-flow unit production model, collecting and summarizing all elements and all information, and obtaining production boundary constraint conditions for information of each machine equipment, large tools, crown blocks, ground vehicles, production processes and steel grade planning regulations of each procedure;
s3, arranging production, and following production boundary constraint conditions and a first procedure principle in the production process;
s4, adopting a pulling mode, taking the casting machine as a center, and discharging expected starting time of each process according to standard operation time and standard logistics transportation time of different steel grades of each process in production boundary constraint conditions; the pulling mode is that the procedure flow of the step S1 is sequentially executed from the back to the front;
s5, adopting a pushing mode, and pushing out planned starting time of each process according to actual production conditions, logistics transportation time, auxiliary operation time and fixed maintenance of each process; the pushing mode is that the procedure flow of the step S1 is sequentially executed from front to back;
s6, calculating a difference value between the expected starting time and the planned starting time to obtain a time difference, and when the time difference is within a specified tolerance range, normally scheduling; when the time difference is larger than the specified tolerance range, the current working procedure needs to slow down the production and logistics rhythm during the positive tolerance event, so that the production can be temporarily not scheduled; when the time difference is smaller than the specified tolerance range, the time difference is a negative tolerance event, and the negative tolerance event indicates that the current procedure needs to accelerate the production and logistics rhythm; stopping the production and shutdown casting machine when the negative tolerance value is too large and the production requirement of the casting machine is not met; and when the negative tolerance value is controllable, timely scheduling and prompting hysteresis, so as to obtain the scheduling method of the full-flow unit production model.
2. The intelligent steelmaking scheduling method as claimed in claim 1, wherein the casting machine current parameters include working section, real-time pull rate, real-time flow rate, molten steel density and molten steel weight.
3. The intelligent steelmaking scheduling method of claim 1, wherein the refining process comprises LF refining and RH refining.
4. The intelligent steelmaking scheduling method according to claim 1, wherein the large-scale tool comprises a hot metal ladle, a tundish and a vacuum chamber.
5. The intelligent steelmaking scheduling method as claimed in claim 1, wherein S2 specifically comprises:
s21, monitoring equipment states of all working procedure machines in real time, and not scheduling production when the equipment states are in overhauling and fault states;
s22, monitoring loading quantity states and position information of the hot-metal ladle and the ladle tank in real time, monitoring casting periods of different loading quantities in real time, and monitoring expected time of different positions reaching a next working procedure in real time;
s23, tracking the operation states of the crown block and the ground vehicle in real time, and calculating the average operation time of the crown block and the ground vehicle by utilizing big data statistics to serve as standard logistics transportation time;
s24, calculating the standard operation time according to different steel production processes and regulation systems.
6. The intelligent steelmaking scheduling method as claimed in claim 1, wherein the first process principle is as follows: the different working procedures comprise one machine and more than one machine, the different machines comprise one set of equipment and more than one set of equipment, and each machine of each working procedure is used for preferentially scheduling the idle equipment.
7. The intelligent steelmaking scheduling method according to claim 1, further comprising, when a plurality of casting machines are simultaneously scheduled, driving the production process of the previous process by the total predicted completion time of the production queues of the casting machines, dynamically calculating the sum of the predicted completion times of the production queues of each process of each casting machine, and giving priority to the scheduling of the shorter casting machines, and giving priority to the corresponding units according to the scheduling method of each process after the longer casting machines.
8. A storage medium comprising a stored program, wherein the program, when run, performs the intelligent steelmaking scheduling method of any one of claims 1 to 7.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor is operative to perform the intelligent steelmaking scheduling method of any one of claims 1 to 7 by the computer program.
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| CN202410035695.0A CN117892949A (en) | 2024-01-09 | 2024-01-09 | Intelligent steelmaking scheduling method |
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