An intelligent control method and system for the production speed of motion cables based on automation

Abstract

The present invention relates to the technical field of production control, and discloses an intelligent control method and system for the production speed of moving cables based on automation. The method collects in real time the production order information of moving cables and the equipment status information required for producing moving cables. At the same time, based on the data collected in real time, it schedules the production order information of moving cables to generate an execution queue of moving cable production orders. Furthermore, it collects the time required for producing moving cables, constructs different production decision models based on the time required for producing moving cables, and at the same time, based on the constructed different production decision models and the generated execution queue of moving cable production orders, adjusts through a genetic algorithm to output an adjusted queue of moving cable production orders. Finally, it executes the output adjusted queue of moving cable production orders and monitors in real time. If an abnormal situation occurs, it recalculates the adjusted queue of moving cable production orders, improving the real-time performance of the intelligent control of the production speed of moving cables.

Description

Technical Field

[0001] The present invention relates to the technical field of production control, and specifically to an intelligent control method and system for the production speed of moving cables based on automation. Background Art

[0002] With the continuous development and progress of automated production technology, the automated production speed is getting faster and faster, and the load on production equipment also increases accordingly; and long-term load operation of the equipment is likely to cause damage to the equipment and unstable production. A production speed adjustment method is needed to reasonably adjust the production speed of the equipment.

[0003] The existing publicly applied patent CN117724417A obtains the production output completed within the current time node in real time through an equipment management module; and transmits the collected output data to a data processing module, which processes it to analyze whether the completed output reaches the corresponding predicted output. If not, the speed adjustment module will accelerate the production speed of the equipment; at the same time, the data processing module also monitors the equipment temperature and adjusts the production speed to keep the equipment temperature normal; however, since the output is not planned before production and no adjustments are made for special situations, only simple adjustments are made based on the output, which has certain limitations. Summary of the Invention

[0004] (I) Technical Problems to be Solved

[0005] In view of the deficiencies of the prior art, the present invention provides an intelligent control method and system for the production speed of moving cables based on automation, which have the advantages of accuracy, real-time, safety, etc., and solve the problems that long-term load operation of the equipment is likely to cause damage to the equipment and unstable production.

[0006] (II) Technical Solutions

[0007] To solve the above technical problems that long-term load operation of the equipment is likely to cause damage to the equipment and unstable production, the present invention provides the following technical solutions:

[0008] This embodiment discloses an intelligent control method for the production speed of moving cables based on automation, which specifically includes the following steps:

[0009] S1. Real-time collect the production order information of moving cables and the equipment status information required for producing moving cables;

[0010] S2. Based on the real-time collected production order information of moving cables and the equipment status information required for producing moving cables, perform production scheduling on the production order information of moving cables to generate a production order execution queue for moving cables;

[0011] S3. Collect the time required for producing moving cables, and construct different production decision models based on the time required for producing moving cables;

[0012] S4. Based on the constructed different production decision models and the generated execution queue of moving cable production orders, perform calculations and adjustments through the genetic algorithm, and output the adjusted queue of moving cable production orders;

[0013] S5. Execute the output adjusted queue of moving cable production orders, and monitor the status information of the equipment required for producing moving cables in real time. If an abnormal situation occurs, return to step S4 to recalculate the adjusted queue of moving cable production orders.

[0014] Through real-time collection of moving cable production order information and the status information of the equipment required for producing moving cables, and at the same time based on the real-time collected data, this invention performs production scheduling on the moving cable production order information to generate an execution queue of moving cable production orders; furthermore, by collecting the time required for producing moving cables and constructing different production decision models based on the time required for producing moving cables, and at the same time based on the constructed different production decision models and the generated execution queue of moving cable production orders, perform calculations and adjustments through the genetic algorithm, output the adjusted queue of moving cable production orders, and finally execute the output adjusted queue of moving cable production orders and monitor in real time. If an abnormal situation occurs, recalculate the adjusted queue of moving cable production orders, which improves the real-time performance of the intelligent control of the moving cable production speed.

[0015] Preferably, the real-time collection of moving cable production order information and the status information of the equipment required for producing moving cables includes the following steps:

[0016] The real-time collection of moving cable production order information includes: the receiving time of the moving cable production order, the deadline of the moving cable production order, the required quantity of moving cables, and the remarks information;

[0017] The status information of the equipment required for producing moving cables includes: the idle status information of the equipment, the quantity information of the equipment, and the required waiting time information.

[0018] Preferably, the production scheduling of the moving cable production order information based on the real-time collection of moving cable production order information and the status information of the equipment required for producing moving cables to generate an execution queue of moving cable production orders includes the following steps:

[0019] When receiving r different moving cable production order information, sort the moving cable production order information according to the status information of the equipment required for producing moving cables collected in real time;

[0020] The methods for sorting r different moving cable production order information include:

[0021] Set the device status information matrix Ava[i,…,j], the maximum demand device matrix Max[i,…,j] for the production of motion cables, the allocated device matrix All[i,…,j], and the order demand device matrix Need[i,…,j];

[0022] Among them, the device status information matrix Ava[i,…,j]: Each element represents the number of a type of available device;

[0023] The maximum demand device matrix Max[i,…,j] for the production of motion cables: Represents the maximum demand for each type of device in the demand order;

[0024] The allocated device matrix All[i,…,j]: Represents the number of devices of each type that have been currently allocated to each order;

[0025] The order demand device matrix Need[i,…,j]: Represents the number of various types of devices still required for each order;

[0026] When Ava[i,…,j] < Need[i,…,j], it indicates that the remaining devices are insufficient to complete the order, and the order is waiting to be allocated;

[0027] When Ava[i,…,j] ≥ Need[i,…,j], calculate the order sequence to complete each demand order.

[0028] The present invention collects the motion cable production order information and the device status information required for the production of motion cables in real time, and performs matching calculations on the device status information required for the production of motion cables and the motion cable production order information; at the same time, based on the matching calculations, a set of motion cable production order execution queues is found to accurately complete all motion cable production orders, ensuring the safety of the execution of motion cable production orders.

[0029] Preferably, the time required for the production of motion cables is collected, and constructing different production decision models based on the time required for the production of motion cables includes the following steps:

[0030] S31. Set the start time of the production of motion cables, the processing time of motion cables, and decision variables;

[0031] S32. Construct different production decision models.

[0032] Preferably, setting the start time of the production of motion cables, the processing time of motion cables, and decision variables includes the following steps:

[0033] The decision variable formula is as follows:

[0034] ;

[0035] Among them, indicates whether the th process of the th moving cable is processed on the equipment . = 1 indicates that the th process of the th moving cable is processed on the equipment . = 0 indicates that the th process of the th moving cable is not processed on the equipment .

[0036] Calculate the completion time of producing the moving cable;

[0037] ;

[0038] Among them, indicates the processing time of the th process of the th moving cable on the equipment . indicates the start time of processing the th process of the th moving cable. indicates the completion time of processing the th process of the th moving cable.

[0039] Preferably, the constructing of different production decision models includes the following steps:

[0040] The decision model for minimizing the construction period is as follows:

[0041] ;

[0042] ;

[0043] Among them, indicates the decision model for minimizing the construction period, indicates the estimated completion time of all processes of all moving cables in the current order;

[0044] The decision model for minimizing the production cost is as follows:

[0045] ;

[0046] ;

[0047] Among them, indicates the decision model for minimizing the production cost, Represents the total number of production equipment, Represents the equipment working hours, Represents the equipment labor cost per hour, Represents the total amount of moving cables required, Represents the total amount of production processes for moving cables.

[0048] In the present invention, by setting the start time of moving cable production, the processing time of moving cables, and decision variables, and simultaneously constructing different decision models based on the set variable data, and providing a solution for moving cable production based on the constructed decision models, the stability of the execution of moving cable production orders is improved.

[0049] Preferably, based on the constructed different production decision models and the generated execution queue of moving cable production orders, the following steps are included for calculation and adjustment through a genetic algorithm to output an adjusted queue of moving cable production orders:

[0050] S41. Perform chromosome encoding on the generated execution queue of moving cable production orders;

[0051] Collect the current idle equipment numbers, and sequentially number the generated execution queues of moving cable production orders;

[0052] Set 0 as the start equipment for production and s as the end equipment for production. When the chromosome encoding string is {0, 1, 5, 7, s; 0, 3, 6, 9, s; 0, 4, 2, 8, s}, it means that 9 idle equipment in the chromosome encoding string sequentially execute 3 groups of moving cable production orders;

[0053] S42. Perform population initialization;

[0054] Set the initial execution queue of moving cable production orders as , represents the th group of moving cable production orders. Each group of chromosome encoding represents a set of execution data for moving cable production orders. Set the population set scale and the maximum number of iterations ;

[0055] S43. Establish a fitness function;

[0056] S44. Select genetic operators based on the established fitness function;

[0057] S45. Perform chromosome crossover on the selected genetic operators;

[0058] Randomly select crossover points among the selected genetic operators, and perform pairwise crossover in the way of order crossover to generate a pair of new chromosome encodings;

[0059] Also use the newly generated chromosome encoding as a path to participate in the iteration;

[0060] S46. Iteratively execute steps S42 - S45 until the maximum number of iterations is reached and output the adjustment queue of the production orders for the moving cables.

[0061] Preferably, the establishment of the fitness function includes the following steps:

[0062] Set the fitness function as follows:

[0063] ;

[0064] where represents the fitness of the execution data of the y - th production order for the moving cable in the initial population;

[0065] Set that when the latest estimated completion time of the production order for the moving cable is less than the end time of the production order for the moving cable, execute the production cost minimization decision model, otherwise execute the project duration minimization decision model.

[0066] Preferably, the selection of genetic operators based on the established fitness function includes the following steps:

[0067] Randomly select genetic operators by using the roulette wheel method. In a random form, the probability of each group of execution data of the production order for the moving cable being selected is proportional to the fitness, and select a group of execution data of the production order for the moving cable with high fitness;

[0068] The probability formula for the selection of genetic operators is as follows:

[0069] ,

[0070] where represents the population size, represents the probability of the y - th group of execution data of the production order for the moving cable in the initial population being selected.

[0071] The present invention constructs different production decision models and the generated execution queue of the production orders for the moving cables, uses the genetic algorithm, encodes the generated execution queue of the production orders for the moving cables in sequence, constructs a fitness function to perform fitness analysis on the encoded execution queue of the production orders for the moving cables, and finally determines the adjustment queue of the production orders for the moving cables through selection, crossover, and mutation operations, improving the reliability of the adjustment of the production orders for the moving cables.

[0072] Further, execute the adjusted queue of the production order for the moving cable output, and monitor the status information of the equipment required for producing the moving cable in real time. If an abnormal situation occurs, return to step S4 to recalculate the adjusted queue of the production order for the moving cable, including the following steps:

[0073] When receiving a user's adjustment of the production order for the moving cable during the execution of the adjusted queue of the production order for the moving cable;

[0074] When the user cancels the production order for the moving cable, directly move the subsequent orders forward;

[0075] When the user adjusts the end time of the production order for the moving cable, return to step S4 to recalculate the adjusted queue of the production order for the moving cable.

[0076] The present invention also discloses an intelligent control system for the production speed of moving cables based on automation, which is used to implement the intelligent control method for the production speed of moving cables based on automation. The system includes: a data acquisition module, an order queue generation module, a production decision model construction module, and a production order adjustment module;

[0077] The data acquisition module is used to collect the production order information of the moving cable and the status information of the equipment required for producing the moving cable in real time, and transmit the collected data to the order queue generation module;

[0078] The order queue generation module is used to generate an execution queue of the production order for the moving cable according to the received data;

[0079] The production decision model construction module is used to collect the time required for producing the moving cable, and construct different production decision models based on the time required for producing the moving cable;

[0080] The production order adjustment module is used to adjust the execution queue of the production order for the moving cable that has been generated according to the different production decision models constructed.

[0081] (III) Beneficial effects

[0082] Compared with the prior art, the present invention provides an intelligent control method and system for the production speed of moving cables based on automation, having the following beneficial effects:

[0083] 1. The invention collects real-time production order information of sports cables and equipment status information required for producing sports cables. At the same time, based on the real-time collected data, it schedules the production order information of sports cables to generate an execution queue for sports cable production orders. Furthermore, it collects the time required for producing sports cables and constructs different production decision models based on the collected time. Then, based on the constructed different production decision models and the generated execution queue for sports cable production orders, it calculates and adjusts through a genetic algorithm, outputs an adjusted queue for sports cable production orders, and finally executes the output adjusted queue for sports cable production orders and monitors it in real time. If an abnormal situation occurs, it recalculates the adjusted queue for sports cable production orders, improving the real-time performance of intelligent control of sports cable production speed.

[0084] 2. The invention collects real-time production order information of sports cables and equipment status information required for producing sports cables, and performs matching calculations on the equipment status information required for producing sports cables and the production order information of sports cables. At the same time, based on the matching calculations, it finds a set of execution queues for sports cable production orders, accurately completes all sports cable production orders, and ensures the safety of the execution of sports cable production orders.

[0085] 3. The invention sets the start time for producing sports cables, the processing time of sports cables, and decision variables. At the same time, it constructs different decision models based on the set variable data and provides solutions for producing sports cables based on the constructed decision models, improving the stability of the execution of sports cable production orders.

[0086] 4. The invention constructs different production decision models and the generated execution queue for sports cable production orders, uses a genetic algorithm, encodes the generated execution queue for sports cable production orders in sequence, constructs a fitness function to analyze the fitness of the encoded execution queue for sports cable production orders, and finally determines the adjusted queue for sports cable production orders through selection, crossover, and mutation operations, improving the reliability of the adjustment of sports cable production orders. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 It is a schematic structural diagram of intelligent control of sports cable production speed according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0088] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0089] Embodiment 1

[0090] Please refer to Figure 1 , this embodiment discloses an intelligent control method for the production speed of motion cables based on automation, which specifically includes the following steps:

[0091] S1. Real-time collect the production order information of motion cables and the equipment status information required for producing motion cables;

[0092] S2. Based on the real-time collected production order information of motion cables and the equipment status information required for producing motion cables, perform production scheduling on the production order information of motion cables to generate an execution queue of production orders for motion cables;

[0093] S3. Collect the time required for producing motion cables, and build different production decision models based on the collected time required for producing motion cables;

[0094] S4. Based on the built different production decision models and the generated execution queue of production orders for motion cables, perform calculations and adjustments through the genetic algorithm, and output an adjusted queue of production orders for motion cables;

[0095] S5. Execute the output adjusted queue of production orders for motion cables, and real-time monitor the equipment status information required for producing motion cables. If an abnormal situation occurs, return to step S4 to recalculate the adjusted queue of production orders for motion cables;

[0096] Further, please refer to Figure 1 , the real-time collection of the production order information of motion cables and the equipment status information required for producing motion cables includes the following steps:

[0097] The real-time collection of the production order information of motion cables includes: the receiving time of the production order of motion cables, the deadline of the production order of motion cables, the required quantity of motion cables, and the remarks information;

[0098] The equipment status information required for producing motion cables includes: equipment idle status information, equipment quantity information, and required waiting time information;

[0099] Further, please refer to Figure 1 , based on the real-time collected production order information of motion cables and the equipment status information required for producing motion cables, performing production scheduling on the production order information of motion cables to generate an execution queue of production orders for motion cables includes the following steps:

[0100] When receiving r different production order information of motion cables, the production order information of motion cables will be sorted according to the real-time collected equipment status information required for producing motion cables;

[0101] The methods for sorting the information of r different production orders of moving cables include:

[0102] Set the device status information matrix Ava[i,…,j], the maximum demand device matrix Max[i,…,j] for moving cable production, the allocated device matrix All[i,…,j], and the order demand device matrix Need[i,…,j];

[0103] Among them, the device status information matrix Ava[i,…,j]: Each element represents the number of available devices of a certain type;

[0104] The maximum demand device matrix Max[i,…,j] for moving cable production: Represents the maximum demand of each type of device in the demand order;

[0105] The allocated device matrix All[i,…,j]: Represents the number of devices of each type currently allocated to each order;

[0106] The order demand device matrix Need[i,…,j]: Represents the number of devices of each type still required for each order;

[0107] When Ava[i,…,j]<Need[i,…,j], it means that the remaining devices are insufficient to complete the order, and the order waits to be allocated;

[0108] When Ava[i,…,j]≥Need[i,…,j], calculate the order sequence to complete each demand order;

[0109] For example,

[0110]

[0111] Within the same time period, arranged in the order of arrival of demand orders as ;

[0112] First, the order of arrival and the order of demand satisfaction, Meet the condition of Ava[i,…,j]≥Need[i,…,j], so execute , when After the execution ends, All the occupied devices are released. At this time, the value of Ava becomes [4, 3, 2]. At this time , , All meet the condition of Ava[i,…,j]≥Need[i,…,j], and execute according to the order of arrival of demand orders , and calculate iteratively in turn according to the above steps to obtain the execution queue of moving cable production orders ;

[0113] Further, please refer to Figure 1 , collect the time required to produce the moving cable, and build different production decision models based on the time required to produce the moving cable, including the following steps:

[0114] S31. Set the start time of producing the moving cable, the processing time of the moving cable, and the decision variables;

[0115] The formula for the decision variable is as follows:

[0116] ;

[0117] Among them, represents whether the th process of the th moving cable is processed on the device . = 1 means that the th process of the th moving cable is processed on the device . = 0 means that the th process of the th moving cable is not processed on the device ;

[0118] Calculate the completion time of producing the moving cable;

[0119] ;

[0120] Among them, represents the processing time of the th process of the th moving cable on the device , represents the start time of the th process of the th moving cable, represents the completion time of the th process of the th moving cable;

[0121] S32. Build different production decision models;

[0122] The decision model for minimizing the project duration is as follows:

[0123] ;

[0124] ;

[0125] Among them, represents the decision model for minimizing the project duration, Indicates the estimated processing completion time of all processes for all motion cables in the current order;

[0126] The decision-making model for minimizing production costs is as follows:

[0127] ;

[0128] ;

[0129] Among them, Indicates the decision-making model for minimizing production costs, Indicates the total number of production equipment, Indicates the equipment 's working hours, Indicates the equipment 's labor cost per hour, Indicates the total amount of motion cables required, Indicates the total number of production processes for motion cables;

[0130] Furthermore, please refer to Figure 1 , based on the constructed different production decision models and the generated execution queue of motion cable production orders, calculate and adjust through the genetic algorithm. The steps for outputting the adjusted queue of motion cable production orders are as follows:

[0131] S41. Perform chromosome encoding on the generated execution queue of motion cable production orders;

[0132] Collect the current idle equipment numbers and sequentially number the generated execution queues of motion cable production orders;

[0133] Set 0 as the production start equipment and s as the production end equipment. When the chromosome encoding string is {0, 1, 5, 7, s; 0, 3, 6, 9, s; 0, 4, 2, 8, s}, it means that the 9 idle equipment in this chromosome encoding string sequentially execute 3 groups of motion cable production orders;

[0134] S42. Initialize the population;

[0135] Set the initial execution queue of motion cable production orders as , Indicates the th group of motion cable production orders. Each chromosome encoding represents a set of execution data for motion cable production orders. Set the population set size and the maximum number of iterations ;

[0136] S43. Establish a fitness function;

[0137] Set the fitness function as follows:

[0138] ;

[0139] Among them, represents the fitness of the execution data of the y-th production order of the moving cable in the initial population;

[0140] It is set that when the latest estimated completion time of the production order of the moving cable is less than the end time of the production order of the moving cable, the production cost minimization decision model is executed, otherwise the construction period minimization decision model is executed;

[0141] S44. Select genetic operators based on the established fitness function;

[0142] The genetic operators are randomly selected by using the roulette wheel method. In a random form, the probability of each group of execution data of the production order of the moving cable being selected is proportional to the fitness, and a group of execution data of the production order of the moving cable with high fitness is selected;

[0143] The probability formula for the selection of genetic operators is as follows:

[0144] ,

[0145] Among them, represents the population size, represents the probability of the execution data of the y-th production order of the moving cable in the initial population being selected;

[0146] S45. Perform chromosome crossover on the selected genetic operators;

[0147] Randomly select crossover points among the selected genetic operators, and perform pairwise crossover by the order crossover method to generate a pair of new chromosome codes;

[0148] The generated new chromosome codes are also used as paths to participate in the iteration;

[0149] S46. Iteratively execute steps S42 - S45 until the maximum number of iterations is reached, and output the adjustment queue of the production order of the moving cable;

[0150] Furthermore, please refer to Figure 1 , execute the output adjustment queue of the production order of the moving cable, and monitor the status information of the equipment required for the production of the moving cable in real time. If an abnormal situation occurs, return to step S4 to recalculate the adjustment queue of the production order of the moving cable, including the following steps:

[0151] When receiving a user's adjustment of the production order of the moving cable during the execution of the adjustment queue of the production order of the moving cable;

[0152] When the user cancels the production order of the motion cable, directly move the subsequent orders forward;

[0153] When the user adjusts the end time of the production order of the motion cable, return to step S4 to recalculate the adjustment queue of the production order of the motion cable;

[0154] Embodiment 2

[0155] Please refer to Figure 1 , this embodiment also discloses an intelligent control system for the production speed of motion cables based on automation, which is used to implement the intelligent control method for the production speed of motion cables based on automation. The system includes: a data acquisition module, an order queue generation module, a production decision model construction module, and a production order adjustment module;

[0156] The data acquisition module is used to collect the production order information of the motion cable and the equipment status information required for producing the motion cable in real time, and transmit the collected data to the order queue generation module;

[0157] The order queue generation module is used to generate an execution queue of the production order of the motion cable according to the received data;

[0158] The production decision model construction module is used to collect the time required for producing the motion cable, and construct different production decision models based on the time required for producing the motion cable;

[0159] The production order adjustment module is used to adjust the execution queue of the production order of the motion cable that has been generated according to the constructed different production decision models.

[0160] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent control method for production speed of motion cables based on automation, characterized in that: The following steps are involved: S1. Real-time collection of motion cable production order information and equipment status information required for the production of motion cables; S2. Based on the real-time collection of motion cable production order information and the equipment status information required for producing the motion cable, production scheduling is performed on the motion cable production order information to generate a motion cable production order execution queue; S3, collecting the time required for producing the motion cable, and building different production decision models based on the collected time required for producing the motion cable; The S3 comprises the following steps: S31, setting the start time of producing the motion cable, the motion cable processing time and the decision variables; S32. Construct different production decision models; The S31 comprises the following steps: The decision variable formula is as follows: in, Indicates whether the βth process of the αth moving cable is processed on equipment k, It means that the βth process of the αth moving cable is processed on the equipment k, It means that the βth process of the αth moving cable is not processed on the equipment k; Calculate the completion time for producing motion cables; in, represents the processing time of the βth process of the αth moving cable on the equipment k, ST αβ Indicates the processing start time of the βth process of the αth moving cable, ET αβ represents the processing completion time of the βth process of the αth moving cable; The S32 comprises the following steps: The construction period minimization decision model is as follows: f1=min(ET all ); AND all =max(ET αβ ); Among them, f1 represents the construction period minimization decision model, ET all Indicates the estimated processing completion time of all processes of all motion cables in the current order; The production cost minimization decision model is as follows: Among them, f2 represents the production cost minimization decision model, m represents the total number of production equipment, MET k represents the working time of device k, C k represents the man-hour cost of equipment k, n represents the total amount of cables to be moved, and p represents the total amount of production processes for moving cables; S4, based on constructing different production decision models and generating motion cable production order execution queues, calculating and adjusting through genetic algorithms, and outputting motion cable production order adjustment queues; S5. Execute the output motion cable production order adjustment queue, and monitor the equipment status information required for producing the motion cable in real time. If an abnormal situation occurs, return to step S4 to recalculate the motion cable production order adjustment queue.

2. According to claim 1, a method for intelligently controlling the production speed of a moving cable based on automation is characterized in that: The real-time collection of the motion cable production order information and the equipment status information required for producing the motion cable comprises the following steps: The real-time collection of the motion cable production order information includes: the motion cable production order receiving time, the motion cable production order deadline, the required motion cable quantity and remarks information; The device status information required for producing the moving cable includes: device idle status information, device quantity information and required waiting time information.

3. The method for intelligently controlling the production speed of a moving cable based on automation according to claim 1 is characterized in that: The method of performing production scheduling on the motion cable production order information based on real-time collection of motion cable production order information and equipment status information required for producing the motion cable, and generating a motion cable production order execution queue comprises the following steps: When receiving r different motion cable production order information, the motion cable production order information is sorted according to the real-time collected equipment status information required for producing the motion cable; Methods for sorting r different motion cable production order information include: Set the equipment status information matrix Ava[i,…,j], the maximum demand equipment matrix Max[i,…,j] for motion cable production, the allocated equipment matrix All[i,…,j], and the order demand equipment matrix Need[i,…,j]; Among them, the device status information matrix Ava[i,…,j]: each element represents the number of available devices of a type; The maximum demand equipment matrix Max[i,…,j] for sports cable production: represents the maximum demand for each type of equipment in the demand order; Allocated equipment matrix All[i,…,j]: indicates the number of equipment of each type currently allocated to each order; Demand order demand equipment matrix Need[i,…,j]: represents the number of various types of equipment required for each order; When Ava[i,…,j] < Need[i,…,j], it indicates that the remaining devices are insufficient to complete the order, and the order is waiting to be allocated. When Ava[i,…,j] ≥ Need[i,…,j], calculate the order sequence to complete each demand order.

4. The method for intelligently controlling the production speed of a moving cable based on automation according to claim 1 is characterized in that: The steps of calculating and adjusting the execution queue of the production orders of the moving cables through the genetic algorithm based on the constructed different production decision models and the generated execution queue of the production orders of the moving cables are as follows: S41. Perform chromosome encoding on the generated execution queue of the production orders of the moving cables. Collect the current idle device numbers, and sequentially number the h generated execution queues of the production orders of the moving cables. Set 0 as the starting device for production and s as the ending device for production. When the chromosome encoding string is {0, 1, 5, 7, s; 0, 3, 6, 9, s; 0, 4, 2, 8, s}, it means that the 9 idle devices in this chromosome encoding string sequentially execute 3 groups of production orders of the moving cables. S42. Initialize the population. Set the initial motion cable production order queue to {1,2,...,h}, where h represents the hth group of motion cable production orders, and each group of chromosome codes represents a group of motion cable production order execution data. Set the population set size and the maximum number of iterations d max ; S43. Establish a fitness function. S44. Select genetic operators based on the established fitness function. S45. Perform chromosome crossover on the selected genetic operators. Randomly select a crossover point among the selected genetic operators, and perform pairwise crossover in the way of order crossover to generate a pair of new chromosome encodings. The generated new chromosome encodings are also used as paths to participate in the iteration. S46, iteratively execute steps S42-S45 until the maximum number of iterations d is reached max , output motion cable production order adjustment queue.

5. The method for intelligently controlling the production speed of a moving cable based on automation according to claim 4 is characterized in that: The steps of establishing the fitness function are as follows: Set the fitness function as shown below: Among them, Fit(y) represents the fitness of the y-th group of execution data of the production orders of the moving cables in the initialized population. Set that when the latest estimated completion time of the production order of the moving cable is less than the end time of the production order of the moving cable, execute the production cost minimization decision model; otherwise, execute the construction period minimization decision model.

6. The method for intelligently controlling the production speed of a moving cable based on automation according to claim 4 is characterized in that: The steps of selecting genetic operators based on the established fitness function are as follows: Randomly select genetic operators by using the roulette wheel method. In a random form, the probability of each group of execution data of the production orders of the moving cables being selected is proportional to the fitness, and select a group of execution data of the production orders of the moving cables with high fitness. The probability formula for the genetic operator to be selected is as follows: Among them, Y represents the population size, and X(y) represents the probability of the y-th group of execution data of the production orders of the moving cables in the initialized population being selected.

7. A system for implementing the method for intelligently controlling the production speed of a moving cable based on automation as described in any one of claims 1 to 6, characterized in that: Include: Data acquisition module, order queue generation module, production decision model construction module, and production order adjustment module; The data acquisition module is used to collect the production order information of the moving cables and the device status information required for producing the moving cables in real time, and transmit the collected data to the order queue generation module. The order queue generation module is used to generate an execution queue of the production orders of the moving cables according to the received data. The production decision model construction module is used to collect the time required for producing the moving cables, and construct different production decision models based on the time required for producing the moving cables. The production order adjustment module is used to adjust the generated execution queue of the production orders of the moving cables according to the constructed different production decision models.

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