A production control system and method for optimizing steel bar cutting and arrangement based on the Internet of Things

Abstract

The invention discloses a steel bar optimized cutting and arranging production control system and method based on the Internet of Things, which relates to the technical field of steel bar production control, including storing the data of these tasks in a steel bar task table to be processed when new steel bar processing tasks are received, and sorting these tasks according to processing priorities; recording the status of each processing equipment, and allocating appropriate processing equipment to the steel bar task to be processed based on the maximum processing length, diameter and bending angle of the processing equipment; when a steel bar subtask is completed, checking whether there are other subtasks with the same raw materials as the subtask just completed, and deciding whether to adjust the processing sequence according to whether they belong to the same steel bar processing task and the estimated processing time; optimizing the steel bar production control method from two aspects of processing sequence and equipment allocation, thereby optimizing the production efficiency and processing time of the steel bar.

Description

Technical Field

[0001] The present invention relates to the technical field of steel bar production control, and in particular to a steel bar optimized blanking arrangement production control system and method based on the Internet of Things. Background Art

[0002] As the core material in modern construction, the production efficiency and processing quality of steel bars directly affect the progress and cost of the entire construction project. Steel bar production control optimization refers to the process of finely controlling the production process of steel bars through scientific management and technical means to improve production efficiency, reduce production costs, and ensure the quality of steel bar processing. This optimization process not only involves the scheduling of production equipment and the management of raw materials, but also includes the sorting of processing tasks, the matching of processing equipment and other links.

[0003] With the rapid development of IoT technology, its application in the manufacturing industry is becoming more and more extensive, providing a strong impetus for the transformation and upgrading of traditional industries. In the field of steel bar production, IoT technology can be deeply integrated with advanced technologies such as intelligent sensing, big data analysis, and cloud computing to achieve real-time monitoring of the production process, data collection and analysis, automatic control, and remote maintenance, thereby significantly improving production efficiency, reducing resource waste, and ensuring the stability of product quality.

[0004] However, in the existing rebar production control methods, the rebar production task sorting is often based only on a simple first-in-first-out principle, resulting in low processing efficiency and frequent situations where urgent tasks cannot be processed in a timely manner; in addition, the existing processing equipment matching method is often based on experience judgment or a simple idle equipment priority principle, lacking a scientific matching algorithm, resulting in low equipment utilization efficiency and unstable processing quality; finally, during the rebar processing process, switching between different tasks requires time and resource reconfiguration, while the existing rebar generation control methods often do not consider the correlation between tasks, resulting in low switching efficiency and increased unnecessary waiting time and processing costs. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In response to the technical problems in the background technology, the present invention proposes a steel bar optimized cutting arrangement production control system and method based on the Internet of Things, which calculates the processing priority of each steel bar processing task by combining the real-time monitoring technology of the Internet of Things and the RFID tag technology; allocates processing equipment to steel bar subtasks based on multiple parameters of each processing equipment; and adjusts the processing order of each steel bar subtask based on the raw materials of the last completed steel bar subtask, thereby solving the technical problems recorded in the background technology.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0009] A steel bar optimized cutting arrangement production control method based on the Internet of Things, comprising:

[0010] When a new steel bar processing task is received, the steel bar demand data in the new steel bar processing task is stored in the steel bar task table to be processed; whenever new data is added to the steel bar task table to be processed, the processing priority of all steel bar processing tasks is calculated according to the steel bar demand information in each steel bar processing task in the table. , according to the processing priority Sort the steel bar processing tasks from high to low;

[0011] Record the status of each rebar processing equipment. When there is a processing equipment with the status of "idle", assign the rebar processing task at the front of the waiting queue to be processed to the processing equipment group; according to the maximum processing length of each model of processing equipment , Maximum processing diameter And the maximum processing bending angle , calculate the length matching index of each steel bar subtask in the steel bar processing task for each processing equipment in turn , diameter matching index and bend angle matching index ; Combine the three matching indices to form an overall matching index , select the processing equipment for each steel bar subtask;

[0012] When the processing equipment completes a steel bar subtask, determine whether there are other steel bar subtasks with the same raw materials as the steel bar subtask just completed in the steel bar waiting queue of the equipment at this time; if so, determine whether the steel bar subtask belongs to the same steel bar processing task as the steel bar subtask just completed. If so, put the steel bar subtask in the first place in the corresponding steel bar waiting queue. If not, based on the estimated processing time of the steel bar subtask Determine whether to put the steel bar subtask at the first place in the corresponding steel bar waiting queue.

[0013] Specifically, a task table of steel bars to be processed is established to store the steel bar demand data of the steel bar processing tasks, the steel bar demand data includes the quantity data of the steel bars to be processed, the processing requirement data of each steel bar, the entry time data, and the expedited requirement data; each steel bar processing task contains multiple steel bar sub-tasks, and the steel bar sub-tasks contain specific requirement data for each steel bar, including the steel bar length, steel bar diameter, number of bends of the steel bar, and the bending angle of each bend, which are stored in the steel bar sub-task table of each steel bar processing task.

[0014] Further, the number of steel bars to be processed in each steel bar processing task in the steel bar processing task table is , the estimated usage of each raw material is , the storage timestamp is And the expedited index is ,in, Indicates the first steel bar processing tasks; the expedited index of each steel bar processing task is Obtained from the expedited request data; the corresponding raw material inventory in each steel bar processing task is , detect the corresponding raw material inventory through RFID tags.

[0015] Further, whenever new data is added to the steel bar task table, the number of steel bars to be processed for all steel bar processing tasks in the steel bar task table is , estimated usage of each raw material , the storage timestamp is And the expedited index is Combined, we can get the processing priority of each steel bar processing task. , the expression is:

[0016] ;

[0017] in, , , The number of steel bars to be processed is , the estimated raw material usage is , the storage timestamp is The preset weight coefficient of ; Indicates the total number of categories of raw materials required in each steel bar processing task; all steel bar processing tasks in the steel bar task table to be processed are sorted according to the corresponding processing priority Sort from large to small and put the sorted results into the waiting queue for processing.

[0018] Furthermore, a processing equipment group is provided in the steel bar processing workshop, including processing equipment of multiple models, and different models of processing equipment have different maximum processing lengths, maximum processing diameters and maximum processing bending angles for steel bars; RFID tags are used to mark all processing equipment, and the status of each processing equipment is monitored in real time, and the status of the processing equipment includes "operating", "busy" and "idle"; when it is detected that there is a processing equipment with an "idle" status in the processing equipment group, and there are steel bar processing tasks to be processed in the waiting queue for processing, the steel bar processing task at the front of the waiting queue for processing is taken out, and all steel bar subtasks in the steel bar processing task are obtained; each steel bar subtask is matched with the processing equipment according to the length of the steel bar to be processed in each steel bar subtask from small to large.

[0019] Furthermore, the length of each steel bar to be processed is , the diameter of each steel bar to be processed is , the maximum bending angle of each steel bar to be processed is ; The maximum processing length of the processing equipment to be matched , Maximum processing diameter And the maximum processing bending angle The length of each steel bar to be processed ,diameter , Maximum bending angle Combined with calculating the length matching index of each steel bar subtask for the current processing equipment to be matched , diameter matching index and bend angle matching index , the expression is: .

[0020] Furthermore, starting from the processing equipment with the smallest maximum processing length of steel bars, the length matching index of each model of the processing equipment to be matched and each steel bar subtask is calculated one by one. , diameter matching index and bend angle matching index ; Combine the length matching index, diameter matching index and bending angle matching index to obtain the overall matching index of each steel bar subtask to be matched with the processing equipment , the expression is: ; If the overall matching index of the steel bar subtask to be matched with the processing equipment , then use the same equipment as the processing equipment to be matched to execute the steel bar subtask; if the overall matching index of the steel bar subtask for the processing equipment to be matched is , then continue to calculate the overall matching index between the steel bar subtask and the next model of processing equipment to be matched;

[0021] Each processing equipment has a corresponding steel bar waiting queue. If multiple steel bar sub-tasks match the same model of processing equipment, the steel bar sub-task will be placed in the steel bar waiting queue of the matching model processing equipment, and will be placed first in the steel bar waiting queue of the processing equipment with an empty steel bar waiting queue or the least steel bar sub-tasks in the steel bar waiting queue. If there are multiple empty steel bar waiting queues of the matching model processing equipment, the steel bar sub-task will be randomly placed in any one of the processing equipment; the data in the steel bar waiting queue will be preliminarily sorted according to the order of matching.

[0022] Furthermore, after completing the processing equipment allocation operation for each steel bar processing task, the steel bar processing task to which each steel bar subtask in the steel bar waiting queue of each processing equipment belongs is detected. When it is detected that all the steel bar subtasks in the steel bar waiting queue of the processing equipment belong to two different steel bar processing tasks, the processing equipment allocation operation for the steel bar subtasks in the steel bar processing task is stopped, and the status of the processing equipment with an "idle" status is adjusted to "busy"; when it is detected that all the steel bar subtasks in the steel bar waiting queues of all processing equipment belong to the same steel bar processing task, the processing equipment that meets the requirements of non-maintenance, non-maintenance and "busy" status at the same time is adjusted to "idle" status.

[0023] Furthermore, when each processing device completes a steel bar subtask, it sequentially detects whether there are other steel bar subtasks with the same raw materials as those required by the just-completed steel bar subtask in the steel bar waiting queue of the processing device; if so, it is determined whether the detected steel bar subtask belongs to the same steel bar processing task as the just-completed steel bar subtask; if they belong to the same steel bar processing task, the detected steel bar subtask is directly placed at the first position in the corresponding steel bar waiting queue, and the next steel bar subtask is executed according to the original order in the steel bar waiting queue;

[0024] If they are not the same steel bar processing task, obtain the estimated processing time data of the detected steel bar subtask , and the estimated processing time data of each rebar subtask in the rebar waiting queue that belongs to the same rebar processing task as the rebar subtask that has just been completed , Indicates the number of the task in the current rebar waiting queue that belongs to the same rebar processing task as the rebar subtask that has just been completed. When a steel bar processing task completes the allocation operation of the processing equipment, the estimated processing time data of each steel bar subtask belonging to the steel bar processing task in each processing equipment is obtained. , Indicates the first steel bar subtasks; set a maximum processing time index for each steel bar processing task ;like , then the detected steel bar subtask cannot be placed in the first place in the corresponding steel bar waiting queue; if , the detected steel bar subtask is placed at the first position in the corresponding steel bar waiting queue; Indicates the total number of steel bar subtasks in the steel bar waiting queue that belong to the same steel bar processing task as the steel bar subtask that has just been completed, including steel bar subtasks that have been processed and those that have not been processed; Indicates the total number of unprocessed rebar subtasks in the rebar waiting queue that belong to the same rebar processing task as the rebar subtask that has just been completed; It indicates the actual total processing time of all the rebar subtasks that belong to the same rebar processing task as the rebar subtask that has just been completed and have been processed.

[0025] A steel bar optimized cutting and arrangement production control system based on the Internet of Things, comprising:

[0026] The data acquisition and marking module, when receiving a new steel bar processing task, stores the steel bar demand data in the new steel bar processing task in the steel bar task table to be processed; uses RFID tags to mark all steel bar raw materials, all processing equipment and all processed steel bars respectively;

[0027] Priority determination module, whenever new data is added to the steel bar task table, the processing priority of all steel bar processing tasks is calculated according to the steel bar demand information in each steel bar processing task in the table , according to the processing priority Sort the steel bar processing tasks from high to low;

[0028] The equipment allocation optimization module records the status of each rebar processing equipment. When there is a processing equipment with the status of "idle", the rebar processing task at the front of the waiting queue is allocated to the processing equipment group; according to the maximum processing length of each model of processing equipment , Maximum processing diameter And the maximum processing bending angle Calculate the length matching index of each steel bar subtask in the steel bar processing task for each processing equipment in turn , diameter matching index and bend angle matching index ; Combine the three matching indices to form an overall matching index , select the processing equipment for each steel bar subtask;

[0029] The processing sequence optimization module determines whether there are other steel bar subtasks with the same raw materials as the just completed steel bar subtask in the steel bar waiting queue of the equipment when the processing equipment completes a steel bar subtask; if so, it determines whether the steel bar subtask belongs to the same steel bar processing task as the just completed steel bar subtask. If so, it puts the steel bar subtask in the first place in the corresponding steel bar waiting queue; if not, it is based on the estimated processing time of the steel bar subtask. Determine whether to put the steel bar subtask at the first place in the corresponding steel bar waiting queue.

[0030] (III) Beneficial effects

[0031] The present invention provides a steel bar optimized cutting arrangement production control system and method based on the Internet of Things, which has the following beneficial effects:

[0032] 1. By establishing a task table of steel bars to be processed and monitoring the inventory of raw materials in real time, combined with the steel bar demand data of the steel bar processing tasks, the processing priority of each steel bar processing task is calculated, and the tasks are sorted from high to low according to the priority; effective management and optimized scheduling of steel bar processing tasks are achieved, which not only reduces the amount of data in the task table of steel bars to be processed and reduces the calculation complexity, but also gives priority to steel bar processing tasks with less task volume, sufficient raw materials, longer storage time or urgent processing, thereby improving the overall production efficiency and response speed, and meeting the actual needs and production requirements of different steel bar processing tasks;

[0033] 2. By calculating the matching index between each steel bar subtask and the length, diameter and bending angle of the processing equipment, this method can ensure that each steel bar is assigned to the most suitable and smallest possible processing equipment, which not only meets the processing requirements of the steel bars, but also effectively reduces the manufacturing cost and the complexity of operation and maintenance; in addition, by setting a steel bar waiting queue for each processing equipment and assigning tasks according to the principle of giving priority to idle equipment queues and the principle of minimum number, this method further optimizes the scheduling and execution order of steel bar processing tasks, and improves production efficiency and equipment utilization;

[0034] 3. By real-time monitoring of the status of the processing equipment, and when the equipment completes a steel bar subtask, it is intelligently determined whether there are other steel bar subtasks in the steel bar waiting queue that require the same raw materials as the steel bar subtask that has just been completed. When the detected steel bar subtask and the steel bar subtask that has just been completed belong to the same steel bar processing task, it is placed at the first place in the corresponding steel bar waiting queue. This method effectively optimizes the execution order of the steel bar processing tasks, further reduces the switching time between tasks, and improves production efficiency. By setting the maximum processing time index, this method also avoids the long waiting time of any steel bar processing task due to the insertion of other steel bar processing tasks, thereby ensuring the controllability of the production schedule. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A flowchart of the steps of the steel bar optimization cutting and arrangement production control method based on the Internet of Things provided by the present invention;

[0036] Figure 2 This is a schematic diagram of the structure of the Internet of Things-based steel bar optimization cutting and arrangement production control system provided by the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] refer to Figure 1 The present invention provides a steel bar optimized cutting arrangement production control method based on the Internet of Things, comprising:

[0039] Step 1: When a new steel bar processing task is received, the steel bar demand data in the new steel bar processing task is stored in the steel bar task table to be processed; whenever new data is added to the steel bar task table to be processed, the processing priority of all steel bar processing tasks is calculated according to the steel bar demand information in each steel bar processing task in the table. , according to the processing priority Sort the steel bar processing tasks from high to low;

[0040] The step one includes the following steps:

[0041] Step 101, establish a steel bar task table to be processed, which is used to store steel bar demand data of steel bar processing tasks. The steel bar demand data specifically represents all steel bar processing tasks that have not yet started and related data of these steel bar processing tasks, such as the number of steel bars to be processed, the processing requirement data of each steel bar, the entry time data, the expedited requirement data, etc.; when the steel bar task table to be processed receives a new steel bar processing task, the steel bar demand data in the new steel bar processing task is stored in the steel bar task table to be processed; each steel bar processing task contains multiple steel bar subtasks, that is, corresponding to the processing task of each steel bar, and the steel bar subtask carries the specific requirement data of each steel bar, including the length of the steel bar, the diameter of the steel bar, the number of bends of the steel bar, and the bending angle of each bend, etc. These data are stored in the steel bar subtask table of each steel bar processing task; in addition, all steel bar raw materials are marked with RFID tags, and the inventory data of each raw material is monitored in real time;

[0042] Among them, the processed steel bar quantity data indicates the number of steel bars required to be processed in each steel bar processing task. The fewer the number of steel bars required to be processed in the steel bar processing task, the higher the processing priority of the steel bar processing task. The steel bar processing tasks with fewer tasks are carried out first, which can reduce the amount of data in the steel bar task table to be processed, thereby reducing the complexity of calculation; the processing requirement data of each steel bar includes the raw materials required for each steel bar subtask and the estimated usage, size and shape requirements of each raw material, and when calculating the processing priority, the inventory of raw materials required for all steel bars to be processed in each steel bar processing task must be considered. If the inventory of the required raw materials is not enough to complete the processing operation of the corresponding steel bar, the processing priority of the corresponding steel bar processing task will become lower; the storage time data indicates the time when the steel bar processing task enters the steel bar task table to be processed, and is stored in the steel bar task table to be processed in the form of a timestamp. The longer the time to enter the steel bar task table to be processed, the higher the priority of the steel bar processing task; the expedited requirement data indicates whether the steel bar processing task needs to be processed urgently, and the expedited steel bar processing task needs to be processed first;

[0043] Step 102: Record the number of steel bars to be processed in each steel bar processing task in the steel bar processing task table as , the estimated usage of each raw material is , the storage timestamp is And the expedited index is ,in, Indicates the first steel bar processing tasks; the expedited index of each steel bar processing task is From the expedited requirement data, if the expedited requirement data of the steel bar processing task is "expedited", then the expedited index of the steel bar processing task is ; If the expedited requirement data of the steel bar processing task is "non-expedited", the expedited index of the steel bar processing task is In addition, the corresponding raw material inventory in each steel bar processing task is , specifically monitoring the inventory changes of each raw material through RFID tags;

[0044] Step 103: Whenever new data is added to the steel bar task table, the number of steel bars to be processed for all steel bar processing tasks in the steel bar task table is , estimated usage of each raw material , the storage timestamp is And the expedited index is Combined, we can get the processing priority of each steel bar processing task. , the expression is:

[0045] ;

[0046] in, , , The number of steel bars to be processed is , the estimated raw material usage is , the storage timestamp is The preset weight coefficient is obtained by combining the processing priority and actual processing order of each steel bar processing task in history with the entropy weight method. The entropy weight method is a commonly used objective weighting method. It is based on the concept of information entropy and determines the weight of the indicator by calculating the entropy value of each indicator to determine the degree of variation of the indicator. ; Indicates the total number of categories of raw materials required in each steel bar processing task. Indicates when hour, The overall value of ;when hour, The overall value of ; All steel bar processing tasks in the steel bar task list to be processed are sorted according to the corresponding processing priority Sort from large to small and put the sorted results into the waiting queue for processing.

[0047] When using, combine the contents in steps 101 to 103:

[0048] By establishing a task list of steel bars to be processed and monitoring the inventory of raw materials in real time, combined with the steel bar demand data of the steel bar processing tasks, the processing priority of each steel bar processing task is calculated, and sorted from high to low according to priority; effective management and optimized scheduling of steel bar processing tasks are achieved, which not only reduces the amount of data in the task list of steel bars to be processed and reduces the complexity of calculations, but also gives priority to steel bar processing tasks with smaller task volumes, sufficient raw materials, longer warehousing time or that require expedited processing, thereby improving overall production efficiency and response speed, and meeting the actual needs and production requirements of different steel bar processing tasks.

[0049] Step 2: Record the status of each steel bar processing equipment. When there is a processing equipment with the status of "idle", assign the steel bar processing task at the front of the waiting queue to be processed to the processing equipment group; according to the maximum processing length of each model of processing equipment , Maximum processing diameter And the maximum processing bending angle , calculate the length matching index of each steel bar subtask in the steel bar processing task for each processing equipment in turn , diameter matching index and bend angle matching index ; Combine the three matching indices to form an overall matching index , select the processing equipment for each steel bar subtask;

[0050] The step 2 includes the following steps:

[0051] Step 201: A processing equipment group is provided in a steel bar processing workshop, including multiple types of processing equipment, specifically multiple types of steel bar cutting and bending integrated equipment; different types of processing equipment have different maximum processing lengths, maximum processing diameters, and maximum processing bending angles for steel bars. For each steel bar, a suitable and as small a type of processing equipment as possible needs to be selected, because the larger the type of processing equipment, the more manufacturing costs and corresponding operation and maintenance complexity required; there are multiple processing equipment of the same type;

[0052] Use RFID tags to mark all processing equipment and monitor the status of each processing equipment in real time. The status of processing equipment includes "operating", "busy" and "idle". The "operating" status means that the processing equipment is currently processing steel bars; the "busy" status means that the current processing equipment is under repair or maintenance, or is waiting for processing operations of other processing equipment, and cannot process steel bars, nor match the processing equipment with steel bar subtasks; the "idle" status means that the current processing equipment is in an idle state and can process steel bars;

[0053] Step 202: when it is detected that there is a processing device in the processing device group with a status of "idle", and there is a steel bar processing task to be processed in the waiting queue, the steel bar processing task at the front of the waiting queue is taken out, and all steel bar subtasks in the steel bar processing task are obtained; each steel bar subtask is matched with the processing device according to the length of the steel bar to be processed in each steel bar subtask from small to large, the length of the steel bar to be processed represents the length data in the specific requirement data of each steel bar, the diameter of the subsequent steel bar to be processed represents the diameter data in the specific requirement data of each steel bar, and the bending angle of the steel bar to be processed represents all the bending angle data in the specific requirement data of each steel bar;

[0054] The length of each steel bar to be processed is , the diameter of each steel bar to be processed is , the maximum bending angle of each steel bar to be processed is ; The maximum processing length of the processing equipment to be matched , Maximum processing diameter And the maximum processing bending angle The length of each steel bar to be processed ,diameter , Maximum bending angle Combined with calculating the length matching index of each steel bar subtask for the current processing equipment to be matched , diameter matching index and bend angle matching index , the expression is:

[0055]

[0056] when =1, indicating that the processing equipment of this model can meet the requirements of The length requirement of each steel bar subtask is =0, indicating that the processing equipment of this type cannot meet the requirements of The length requirement of each steel bar subtask; =1, indicating that the processing equipment of this model can meet the requirements of The diameter requirement of each steel bar subtask is =0, indicating that the processing equipment of this type cannot meet the requirements of The diameter requirement of each steel bar subtask; =1, indicating that the processing equipment of this model can meet the requirements of The bending angle requirement of each steel bar subtask is =0, indicating that the processing equipment of this type cannot meet the requirements of Bending angle requirements for each steel bar subtask;

[0057] Step 203: Starting from the processing equipment with the smallest maximum processing length for steel bars, calculate the length matching index of each type of processing equipment to be matched and each steel bar subtask one by one. , diameter matching index and bend angle matching index Each type of processing equipment only needs to be matched once; the length matching index, diameter matching index and bending angle matching index are combined to obtain the overall matching index of the matching processing equipment for each steel bar subtask. , the expression is:

[0058] ;

[0059] If the overall matching index of the steel bar subtask to match the processing equipment , it means that the steel bar subtask matches the processing equipment to be matched, and the steel bar subtask is executed using the same equipment as the processing equipment to be matched; if the overall matching index of the steel bar subtask to the processing equipment to be matched is , it means that the steel bar subtask does not match the processing equipment to be matched, and the calculation of the overall matching index between the steel bar subtask and the next model of processing equipment to be matched continues;

[0060] Step 204, each processing equipment has a corresponding steel bar waiting queue. If multiple steel bar subtasks match the same model of processing equipment, the steel bar subtask will be placed in the steel bar waiting queue of the matching model of processing equipment, and will be placed in the steel bar waiting queue of the processing equipment with an empty steel bar waiting queue first. If there are multiple matching models of processing equipment with empty steel bar waiting queues, the steel bar subtask will be randomly placed in any one of the processing equipment. If the steel bar waiting queues of all processing equipment of the matching model are not empty, the minimum principle is followed. When a new steel bar subtask matches the processing equipment of this model, the steel bar subtask will be placed in the steel bar waiting queue of the processing equipment with the least steel bar subtask in the steel bar waiting queue. The data in the steel bar waiting queue is preliminarily sorted in the order of matching, that is, the first matched one will be processed first.

[0061] When using, combine the contents in steps 201 to 204:

[0062] By calculating the matching index between each steel bar subtask and the length, diameter and bending angle of the processing equipment, this method can ensure that each steel bar is assigned to the most suitable and smallest possible processing equipment, which not only meets the processing requirements of the steel bars, but also effectively reduces the manufacturing cost and the complexity of operation and maintenance; in addition, by setting a steel bar waiting queue for each processing equipment and following the principle of giving priority to idle equipment queues and the least principle for task allocation, this method further optimizes the scheduling and execution order of steel bar processing tasks, and improves production efficiency and equipment utilization.

[0063] Step 3: When the processing equipment completes a steel bar subtask, determine whether there are other steel bar subtasks with the same raw material type as the steel bar subtask just completed in the steel bar waiting queue of the equipment; if so, determine whether the steel bar subtask belongs to the same steel bar processing task as the steel bar subtask just completed. If so, put the steel bar subtask in the first place in the corresponding steel bar waiting queue; if not, based on the estimated processing time of the steel bar subtask Determine whether to put the steel bar subtask in the first place in the corresponding steel bar waiting queue;

[0064] The step three includes the following steps:

[0065] Step 301, when it is detected that there is a processing equipment with a status of "idle" in the processing equipment group, and there is a pending steel bar processing task in the waiting queue to be processed, the steel bar processing task at the front in the waiting queue to be processed is taken out, and the processing equipment allocation operation of the steel bar subtask in step 2 is performed, then the steel bar waiting queue of each processing equipment can simultaneously contain steel bar subtasks in multiple steel bar processing tasks; it is required that there are at most two steel bar subtasks in the steel bar waiting queue of all processing equipment, that is, after the processing equipment allocation operation of each steel bar processing task is allocated, the steel bar processing task to which each steel bar subtask in the steel bar waiting queue of each processing equipment belongs is detected, when it is detected that all the steel bar subtasks in the steel bar waiting queue of a certain processing equipment belong to two different steel bar processing tasks, the processing equipment allocation operation of the steel bar subtask in the steel bar processing task is stopped, and if there is a processing equipment with a status of "idle" at this time, the status of these equipments is adjusted to "busy", and when it is detected that all the steel bar subtasks in the steel bar waiting queues of all processing equipment belong to the same steel bar processing task, the processing equipment that meets the non-maintenance, non-maintenance and "busy" status at the same time is adjusted to "idle" state;

[0066] Step 302: when each processing device completes a steel bar subtask, it is sequentially detected whether there are other steel bar subtasks with the same raw materials as the steel bar subtask just completed in the steel bar waiting queue of the processing device; if there are, it is determined whether the detected steel bar subtask belongs to the same steel bar processing task as the steel bar subtask just completed, and the next steel bar subtask to be executed is further selected based on the determination result; if there are no other steel bar subtasks, the next steel bar subtask is executed according to the original order in the steel bar waiting queue;

[0067] Step 303, determine whether the steel bar subtask detected in step 302 belongs to the same steel bar processing task as the steel bar subtask just completed. If they belong to the same steel bar processing task, directly put the detected steel bar subtask into the first place in the corresponding steel bar waiting queue, and execute the next steel bar subtask according to the original order in the steel bar waiting queue; if they belong to different steel bar processing tasks, further determine whether it is necessary to adjust the order in the corresponding steel bar waiting queue, specifically: obtain the estimated processing time data of the detected steel bar subtask , and the estimated processing time data of each rebar subtask in the rebar waiting queue that belongs to the same rebar processing task as the rebar subtask that has just been completed , Indicates the number of the task in the current rebar waiting queue that belongs to the same rebar processing task as the rebar subtask that has just been completed. The estimated processing time data is based on the historical normal processing time data of each steel bar subtask, and includes the material preparation time; every time a steel bar processing task completes the allocation operation of the processing equipment, the estimated processing time data of each steel bar subtask belonging to the steel bar processing task in each processing equipment is obtained according to the above analysis , Indicates the first steel bar subtasks; set a maximum processing time index for each steel bar processing task , which is used to avoid each rebar processing task from waiting too long due to the insertion of other rebar processing tasks, and The general value is 1.2; if , it means that if the detected steel bar subtask is placed at the first position in the corresponding steel bar waiting queue, the completion time of the steel bar processing task to which the just completed steel bar subtask belongs will exceed the set maximum processing time. Therefore, the detected steel bar subtask cannot be placed in the first place in the corresponding steel bar waiting queue; if , it means that if the detected steel bar subtask is placed at the first position in the corresponding steel bar waiting queue, the completion time of the steel bar processing task to which the just completed steel bar subtask belongs will not exceed the set maximum processing time, and the detected steel bar subtask will be placed at the first position in the corresponding steel bar waiting queue; where, Indicates the total number of steel bar subtasks in the steel bar waiting queue that belong to the same steel bar processing task as the steel bar subtask that has just been completed, including steel bar subtasks that have been processed and those that have not been processed; Indicates the total number of unprocessed rebar subtasks in the rebar waiting queue that belong to the same rebar processing task as the rebar subtask that has just been completed; It indicates the actual total processing time of all the rebar subtasks that belong to the same rebar processing task as the rebar subtask that has just been completed and have been processed;

[0068] Step 304: RFID mark each processed steel bar and perform subsequent arrangement operations.

[0069] When used, combine the contents in steps 301 to 304:

[0070] By monitoring the status of the processing equipment in real time, and when the equipment completes a steel bar subtask, it is intelligently determined whether there are other steel bar subtasks in the steel bar waiting queue that require the same raw materials as the steel bar subtask that has just been completed. When the detected steel bar subtask and the steel bar subtask that has just been completed belong to the same steel bar processing task, it is placed at the first place in the corresponding steel bar waiting queue. This method effectively optimizes the execution order of the steel bar processing tasks, further reduces the switching time between tasks, and improves production efficiency. By setting the maximum processing time index, this method also avoids the long waiting time of any steel bar processing task due to the insertion of other steel bar processing tasks, thereby ensuring the controllability of the production schedule.

[0071] refer to Figure 2 The present invention also provides a steel bar optimized cutting and arrangement production control system based on the Internet of Things, comprising:

[0072] The data acquisition and marking module, when receiving a new steel bar processing task, stores the steel bar demand data in the new steel bar processing task in the steel bar task table to be processed; uses RFID tags to mark all steel bar raw materials, all processing equipment and all processed steel bars respectively;

[0073] Priority determination module, whenever new data is added to the steel bar task table, the processing priority of all steel bar processing tasks is calculated according to the steel bar demand information in each steel bar processing task in the table , according to the processing priority Sort the steel bar processing tasks from high to low;

[0074] The equipment allocation optimization module records the status of each rebar processing equipment. When there is a processing equipment with the status of "idle", the rebar processing task at the front of the waiting queue is allocated to the processing equipment group; according to the maximum processing length of each model of processing equipment , Maximum processing diameter And the maximum processing bending angle Calculate the length matching index of each steel bar subtask in the steel bar processing task for each processing equipment in turn , diameter matching index and bend angle matching index ; Combine the three matching indices to form an overall matching index , select the processing equipment for each steel bar subtask;

[0075] The processing sequence optimization module determines whether there are other steel bar subtasks with the same raw materials as the just completed steel bar subtask in the steel bar waiting queue of the equipment when the processing equipment completes a steel bar subtask; if so, it determines whether the steel bar subtask belongs to the same steel bar processing task as the just completed steel bar subtask. If so, it puts the steel bar subtask in the first place in the corresponding steel bar waiting queue; if not, it is based on the estimated processing time of the steel bar subtask. Determine whether to put the steel bar subtask at the first place in the corresponding steel bar waiting queue.

[0076] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer storage medium or transmitted via a computer storage medium.

[0077] Computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. Computer storage media can be any available media that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media. Available media can be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid state drives (SSDs)).

[0078] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A steel bar optimized cutting arrangement production control method based on the Internet of Things, characterized by: include: When a new steel bar processing task is received, the steel bar demand data in the new steel bar processing task is stored in the steel bar task table to be processed; Whenever new data is added to the steel bar task table, the processing priority Mp of all steel bar processing tasks is calculated based on the steel bar demand information in each steel bar processing task in the table. i , according to the processing priority Mp i The steel bar processing tasks are sorted from high to low, specifically: Whenever new data is added to the waiting steel bar task table, the number of waiting steel bars for all steel bar processing tasks in the waiting steel bar task table is Nrp. i , Estimated usage of each raw material Emu ik , the storage time stamp is T i And the expedited index is Ur i Combined, we get the processing priority Mp of each steel bar processing task. i , the expression is: Among them, α1, α2, and α3 are the number of steel bars to be processed Nrp i , the estimated raw material usage is Emu i , the storage time stamp is T i The preset weight coefficient, and α1+α2+α3=1; n i Indicates the total number of categories of raw materials required in each steel bar processing task; all steel bar processing tasks in the steel bar task list to be processed are sorted according to the corresponding processing priority Mp i Sort from large to small and put the sorted results into the waiting queue for processing; Record the status of each rebar processing equipment. When there is a processing equipment with the status of "idle", assign the rebar processing task at the front of the waiting queue to be processed to the processing equipment group; calculate the length matching index Ml of each rebar subtask in the rebar processing task for each processing equipment in turn according to the maximum processing length Mle, maximum processing diameter Mdia and maximum processing bending angle Mmba of each type of processing equipment j , diameter matching index Md j And the bending angle matching index Mb j ; Combine the three matching indices to form the overall matching index Mc j , select the processing equipment for each steel bar subtask, specifically: Starting from the processing equipment with the smallest maximum processing length of steel bars, calculate the length matching index Ml of each model of processing equipment to be matched and each steel bar subtask one by one j , diameter matching index Md j And the bending angle matching index Mb j ; Combine the length matching index, diameter matching index and bending angle matching index to obtain the overall matching index Mc of each steel bar subtask to be matched with the processing equipment j , the expression is: Mc j =Ml j *Md j *Mb j ; If the overall matching index Mc of the steel bar subtask to be matched with the processing equipment j =1, the same equipment as the to-be-matched processing equipment is used to execute the steel bar subtask; if the overall matching index Mc of the steel bar subtask to the to-be-matched processing equipment is j =0, then continue to calculate the overall matching index between the steel bar subtask and the next model of processing equipment to be matched; Each processing equipment has a corresponding steel bar waiting queue. If multiple steel bar subtasks match the same type of processing equipment, the steel bar subtask will be placed in the steel bar waiting queue of the matching type of processing equipment, and will be placed first in the steel bar waiting queue of the processing equipment with an empty steel bar waiting queue or the least steel bar subtasks in the steel bar waiting queue. If there are multiple steel bar waiting queues of matching types of processing equipment that are empty, the steel bar subtask will be randomly placed in any of the processing equipment. The data in the steel bar waiting queue will be preliminarily sorted according to the order of matching. When the processing equipment completes a steel bar subtask, it is determined whether there are other steel bar subtasks with the same raw material type as the steel bar subtask just completed in the steel bar waiting queue of the equipment at this time; if so, it is determined whether the steel bar subtask belongs to the same steel bar processing task as the steel bar subtask just completed. If so, the steel bar subtask is placed at the first position in the corresponding steel bar waiting queue; if not, it is determined whether the steel bar subtask is placed at the first position in the corresponding steel bar waiting queue based on the estimated processing time t of the steel bar subtask, specifically: When each processing equipment completes a steel bar subtask, it sequentially detects whether there are other steel bar subtasks with the same raw materials as the steel bar subtask just completed in the steel bar waiting queue of the processing equipment; if so, it determines whether the detected steel bar subtask belongs to the same steel bar processing task as the steel bar subtask just completed; if they belong to the same steel bar processing task, the detected steel bar subtask is directly placed at the first position in the corresponding steel bar waiting queue, and the next steel bar subtask is executed according to the original order in the steel bar waiting queue; If they are not the same steel bar processing task, the estimated processing time data t of the detected steel bar subtask is obtained, as well as the estimated processing time data t of each steel bar subtask in the steel bar waiting queue that belongs to the same steel bar processing task as the just completed steel bar subtask. l , l represents the lth steel bar subtask in the current steel bar waiting queue that belongs to the same steel bar processing task as the steel bar subtask that has just been completed; whenever a steel bar processing task completes the allocation operation of the processing equipment, the estimated processing time data of each steel bar subtask belonging to the steel bar processing task in each processing equipment is obtained p represents the pth steel bar subtask belonging to the steel bar processing task in each processing equipment; a maximum processing time index γ is set for each steel bar processing task; if Then the detected steel bar subtask cannot be placed in the first place in the corresponding steel bar waiting queue; if The detected steel bar subtask is placed in the first place of the corresponding steel bar waiting queue; M represents the total number of steel bar subtasks in the steel bar waiting queue that belong to the same steel bar processing task as the steel bar subtask just completed, including steel bar subtasks that have been processed and those that have not been processed; m represents the total number of steel bar subtasks in the steel bar waiting queue that belong to the same steel bar processing task as the steel bar subtask just completed and have not been processed; t fin It indicates the actual total processing time of all the rebar subtasks that belong to the same rebar processing task as the rebar subtask that has just been completed and have been processed.

2. The method for optimizing steel bar blanking and arrangement production control based on the Internet of Things according to claim 1, characterized in that: Establish a task table of steel bars to be processed to store the steel bar demand data of the steel bar processing tasks. The steel bar demand data includes the quantity data of the steel bars to be processed, the processing requirement data of each steel bar, the entry time data, and the expedited requirement data; each steel bar processing task contains multiple steel bar subtasks. The steel bar subtasks contain specific requirement data for each steel bar, including the length of the steel bar, the diameter of the steel bar, the number of bends of the steel bar, and the bending angle of each bend, which are stored in the steel bar subtask table of each steel bar processing task.

3. The method for controlling the optimal cutting and arrangement of steel bars based on the Internet of Things according to claim 2, characterized in that: The number of steel bars to be processed in each steel bar processing task in the steel bar processing task table is Nrp. i , the estimated usage of each raw material is Emu ik , the storage time stamp is T i And the expedited index is Ur i , where i represents the i-th steel bar processing task in the steel bar processing task list; the expedited index of each steel bar processing task is Ur i Obtained from the expedited request data; the corresponding raw material inventory in each steel bar processing task is recorded as Rms ik , detect the corresponding raw material inventory through RFID tags.

4. The method for controlling the optimal cutting and arrangement of steel bars based on the Internet of Things according to claim 3, characterized in that: A processing equipment group is set up in the steel bar processing workshop, including multiple types of processing equipment. Different types of processing equipment have different maximum processing lengths, maximum processing diameters and maximum processing bending angles for steel bars. All processing equipment are marked with RFID tags, and the status of each processing equipment is monitored in real time. The status of the processing equipment includes "operating", "busy" and "idle". When it is detected that there is a processing equipment with a status of "idle" in the processing equipment group, and there are steel bar processing tasks to be processed in the waiting queue, the steel bar processing task at the front of the waiting queue is taken out, and all steel bar subtasks in the steel bar processing task are obtained; each steel bar subtask is matched with the processing equipment according to the length of the steel bar to be processed in each steel bar subtask from small to large.

5. The method for controlling the optimal cutting and arrangement of steel bars based on the Internet of Things according to claim 4, characterized in that: The length of each steel bar to be processed is Le j , the diameter of each steel bar to be processed is Dia j , the maximum bending angle of each steel bar to be processed is Mba j ; The maximum processing length Mle, the maximum processing diameter Mdia and the maximum processing bending angle Mmba of the processing equipment to be matched with the length Le of each steel bar to be processed j 、Diameter j , Maximum bending angle Mba j Combined, calculate the length matching index Ml of each steel bar subtask to the current processing equipment to be matched j , diameter matching index Md j And the bending angle matching index Mb j , the expression is:

6. The method for controlling the optimal cutting and arrangement of steel bars based on the Internet of Things according to claim 5, characterized in that: After completing the processing equipment allocation operation for each rebar processing task, detect the rebar processing task to which each rebar subtask in the rebar waiting queue of each processing equipment belongs. When it is detected that all the rebar subtasks in the rebar waiting queue of the processing equipment belong to two different rebar processing tasks, stop the processing equipment allocation operation for the rebar subtasks in the rebar processing task, and adjust the status of the processing equipment with the "idle" status to "busy"; when it is detected that all the rebar subtasks in the rebar waiting queue of all processing equipment belong to the same rebar processing task, adjust the processing equipment that meets the non-inspection, non-maintenance and "busy" status to "idle" status.

7. A steel bar optimized cutting and arrangement production control system based on the Internet of Things, characterized in that: include: The data acquisition and marking module, when receiving a new steel bar processing task, stores the steel bar demand data in the new steel bar processing task in the steel bar task table to be processed; uses RFID tags to mark all steel bar raw materials, all processing equipment and all processed steel bars respectively; Priority determination module, whenever new data is added to the steel bar task table, the processing priority Mp of all steel bar processing tasks is calculated according to the steel bar demand information in each steel bar processing task in the table. i , according to the processing priority Mp i The steel bar processing tasks are sorted from high to low, specifically: Whenever new data is added to the waiting steel bar task table, the number of waiting steel bars for all steel bar processing tasks in the waiting steel bar task table is Nrp. i , Estimated usage of each raw material Emu ik , the storage time stamp is T i And the expedited index is Ur i Combined, we get the processing priority Mp of each steel bar processing task. i , the expression is: Among them, α1, α2, and α3 are the number of steel bars to be processed Nrp i , the estimated raw material usage is Emu i , the storage time stamp is T i The preset weight coefficient, and α1+α2+α3=1; n i Indicates the total number of categories of raw materials required in each steel bar processing task; all steel bar processing tasks in the steel bar task list to be processed are sorted according to the corresponding processing priority Mp i Sort from large to small and put the sorted results into the waiting queue for processing; The equipment allocation optimization module records the status of each rebar processing equipment. When there is a processing equipment with the status of "idle", the rebar processing task at the front of the waiting queue is allocated to the processing equipment group; the length matching index Ml of each rebar subtask in the rebar processing task for each processing equipment is calculated in turn according to the maximum processing length Mle, maximum processing diameter Mdia and maximum processing bending angle Mmba of each model of processing equipment. j , diameter matching index Md j And the bending angle matching index Mb j ; Combine the three matching indices to form the overall matching index Mc j , select the processing equipment for each steel bar subtask, specifically: Starting from the processing equipment with the smallest maximum processing length of steel bars, calculate the length matching index Ml of each model of processing equipment to be matched and each steel bar subtask one by one j , diameter matching index Md j And the bending angle matching index Mb j ; Combine the length matching index, diameter matching index and bending angle matching index to obtain the overall matching index Mc of each steel bar subtask to be matched with the processing equipment j , the expression is: Mc j =Ml j *Md j *Mb j ; If the overall matching index Mc of the steel bar subtask to be matched with the processing equipment j =1, the same equipment as the to-be-matched processing equipment is used to execute the steel bar subtask; if the overall matching index Mc of the steel bar subtask to the to-be-matched processing equipment is j =0, then continue to calculate the overall matching index between the steel bar subtask and the next model of processing equipment to be matched; Each processing equipment has a corresponding steel bar waiting queue. If multiple steel bar subtasks match the same type of processing equipment, the steel bar subtask will be placed in the steel bar waiting queue of the matching type of processing equipment, and will be placed first in the steel bar waiting queue of the processing equipment with an empty steel bar waiting queue or the least steel bar subtasks in the steel bar waiting queue. If there are multiple steel bar waiting queues of matching types of processing equipment that are empty, the steel bar subtask will be randomly placed in any of the processing equipment. The data in the steel bar waiting queue will be preliminarily sorted according to the order of matching. The processing sequence optimization module, when the processing equipment completes a steel bar subtask, determines whether there are other steel bar subtasks with the same raw material type as the steel bar subtask just completed in the steel bar waiting queue of the equipment at this time; if so, determines whether the steel bar subtask belongs to the same steel bar processing task as the steel bar subtask just completed. If so, put the steel bar subtask in the first place in the corresponding steel bar waiting queue; if not, determine whether to put the steel bar subtask in the first place in the corresponding steel bar waiting queue based on the estimated processing time t of the steel bar subtask, specifically: When each processing equipment completes a steel bar subtask, it sequentially detects whether there are other steel bar subtasks with the same raw materials as the steel bar subtask just completed in the steel bar waiting queue of the processing equipment; if so, it determines whether the detected steel bar subtask belongs to the same steel bar processing task as the steel bar subtask just completed; if they belong to the same steel bar processing task, the detected steel bar subtask is directly placed at the first position in the corresponding steel bar waiting queue, and the next steel bar subtask is executed according to the original order in the steel bar waiting queue; If they are not the same steel bar processing task, the estimated processing time data t of the detected steel bar subtask is obtained, as well as the estimated processing time data t of each steel bar subtask in the steel bar waiting queue that belongs to the same steel bar processing task as the just completed steel bar subtask. l , l represents the lth steel bar subtask in the current steel bar waiting queue that belongs to the same steel bar processing task as the steel bar subtask that has just been completed; whenever a steel bar processing task completes the allocation operation of the processing equipment, the estimated processing time data of each steel bar subtask belonging to the steel bar processing task in each processing equipment is obtained p represents the pth steel bar subtask belonging to the steel bar processing task in each processing equipment; a maximum processing time index γ is set for each steel bar processing task; if Then the detected steel bar subtask cannot be placed in the first place in the corresponding steel bar waiting queue; if The detected steel bar subtask is placed in the first place of the corresponding steel bar waiting queue; M represents the total number of steel bar subtasks in the steel bar waiting queue that belong to the same steel bar processing task as the steel bar subtask just completed, including steel bar subtasks that have been processed and those that have not been processed; m represents the total number of steel bar subtasks in the steel bar waiting queue that belong to the same steel bar processing task as the steel bar subtask just completed and have not been processed; t fin It indicates the actual total processing time of all the rebar subtasks that belong to the same rebar processing task as the rebar subtask that has just been completed and have been processed.

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