Simulation Scheduling Method, System, Terminal Device and Storage Medium for Production Line

Abstract

The present invention discloses a simulation scheduling method, system, terminal device and storage medium for a production line. The method includes: obtaining product materials and process routes of products to be processed; based on the product materials of the products to be processed, the process routes, a pre-created simulation scheduling model, and a preset matching algorithm, obtaining processing stations to process the products to be processed according to the equipment of the processing stations; wherein, the simulation scheduling model is trained based on the preset production capacity of processing equipment and workstations. The purpose of the present invention is to improve the quality of products, reduce production costs and improve the efficiency of the production line.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent manufacturing, and particularly to a simulation scheduling method, system, terminal device and storage medium for a production line. Background Art

[0002] In the traditional packaging and printing industry, the processing equipment for products to be processed is usually selected based on the historical experience of the staff. With the continuous increase of production demand and the continuous update of processing equipment, when the staff has insufficient control over production demand and processing equipment, the product quality will be reduced, the production cost will be increased, and the working efficiency of the production line will be reduced. Summary of the Invention

[0003] The main purpose of the embodiments of the present invention is to provide a simulation scheduling method, system, terminal device and storage medium for a production line, aiming to improve the product quality, reduce the production cost and improve the efficiency of the production line.

[0004] To achieve the above object, an embodiment of the present invention provides a simulation scheduling method for a production line, and the simulation scheduling method for the production line includes:

[0005] Obtain the product materials and process routes of the product to be processed;

[0006] Based on the product materials of the product to be processed, the process route, a pre-created simulation scheduling model, and a preset matching algorithm, obtain a processing station to process the product to be processed according to the equipment of the processing station; wherein, the simulation scheduling model is trained based on the preset production capacity and stations of the processing equipment.

[0007] Optionally, the step of obtaining a processing station based on the product materials of the product to be processed, the process route, a pre-created simulation scheduling model, and a preset matching algorithm includes:

[0008] Based on the product materials of the product to be processed, the process route, the simulation scheduling model, and the preset matching algorithm, determine the key stations of the product to be processed;

[0009] Based on the key stations, calculate the fitness value and the current iteration number;

[0010] If the current iteration number does not meet the preset condition, determine the adjustment stations based on the product materials of the product to be processed, the process route, the simulation scheduling model, the preset matching algorithm, the fitness value, and the key stations;

[0011] Update the key stations according to the adjustment stations, and return to execute the step: based on the key stations, calculate the fitness value and the current iteration number;

[0012] If the current iteration count meets the preset condition, then use the critical work station as the processing work station.

[0013] Optionally, the step of determining the adjustment work station based on the product material of the product to be processed, the process route, the simulation production scheduling model, the preset matching algorithm, the fitness value, and the critical work station includes:

[0014] Calculate the recombination probability based on the critical work station and the fitness value;

[0015] Obtain a selection sample based on the product material of the product to be processed, the process route, the simulation production scheduling model, the preset matching algorithm, and the recombination probability;

[0016] Perform MS crossover and OS crossover on the sample to obtain a crossover result;

[0017] Calculate the mutation probability based on the crossover result;

[0018] Search the selection sample based on the mutation probability to obtain the adjustment work station.

[0019] Optionally, before the step of obtaining the processing work station based on the product material of the product to be processed, the process route, the pre-created simulation production scheduling model, and the preset matching algorithm:

[0020] Establish the simulation production scheduling model;

[0021] Wherein, the step of establishing the simulation production scheduling model includes:

[0022] Obtain the preset production capacity and work stations of the processing equipment;

[0023] Construct the simulation production scheduling model according to the preset production capacity and work stations of the processing equipment.

[0024] Optionally, after the step of obtaining the processing work station based on the product material of the product to be processed, the process route, the pre-created simulation production scheduling model, and the preset matching algorithm:

[0025] Calculate the number of processing equipment on the production line corresponding to the product to be processed based on the efficiency of the equipment at the processing work station, the task volume corresponding to the product to be processed, and the latest delivery date of the product to be processed; and / or the number of operating workers required for the production line corresponding to the product to be processed;

[0026] If the number of processing devices on the production line corresponding to the product to be processed; and / or the number of operating workers required for the production line corresponding to the product to be processed does not meet the preset number, then adjust the number of production lines corresponding to the product to be processed; and / or adjust the number of devices at the processing stations.

[0027] Optionally, the step of calculating the number of processing devices on the production line corresponding to the product to be processed; and / or the number of operating workers required for the production line corresponding to the product to be processed based on the efficiency of the devices at the processing stations, the task volume corresponding to the product to be processed, and the latest delivery date of the product to be processed includes:

[0028] If the processing method of the product to be processed is discrete processing, then calculate the number of processing devices on the production line corresponding to the product to be processed; and / or the number of operating workers required for the production line corresponding to the product to be processed based on the efficiency of the devices at the processing stations, the task volume corresponding to the product to be processed, the latest delivery date of the product to be processed, and a preset discrete processing formula;

[0029] If the processing method of the product to be processed is continuous processing, then calculate the number of processing devices on the production line corresponding to the product to be processed; and / or the number of operating workers required for the production line corresponding to the product to be processed based on the efficiency of the devices at the processing stations, the task volume corresponding to the product to be processed, the latest delivery date of the product to be processed, and a preset continuous processing formula.

[0030] Optionally, after the step of obtaining the processing stations based on the product materials of the product to be processed, the process route, a pre-created simulation scheduling model, and a preset matching algorithm, includes:

[0031] Obtain the actual production capacity of the processing devices;

[0032] Transmit the actual production capacity back to the simulation scheduling model to update the preset production capacity; and return to execute the step: construct the simulation scheduling model according to the preset production capacity of the processing devices and the workstations.

[0033] In addition, to achieve the above object, the present invention also provides a simulation scheduling system for a production line, the system includes:

[0034] A data acquisition module for acquiring the product materials and process route of the product to be processed;

[0035] A workstation analysis module for obtaining processing workstations based on the product materials of the product to be processed, the process route, a pre-created simulation scheduling model, and a preset matching algorithm, so as to process the product to be processed according to the devices at the processing workstations; wherein, the simulation scheduling model is trained based on the preset production capacity of the processing devices and the workstations.

[0036] In addition, to achieve the above object, the present invention further provides a terminal device, which includes: a memory, a processor, and a simulation scheduling method for a production line stored on the memory and executable on the processor. When the program of the simulation scheduling of the production line is executed by the processor, the steps of the simulation scheduling method for the production line as described above are implemented.

[0037] In addition, to achieve the above object, the present invention further provides a computer-readable storage medium, on which a program of the simulation scheduling of the production line is stored. When the program of the simulation scheduling of the production line is executed by a processor, the steps of the simulation scheduling method for the production line as described above are implemented.

[0038] The simulation scheduling method, system, terminal device, and storage medium for a production line proposed in the embodiments of the present invention improve the efficiency of the production line by obtaining the product materials and process routes of the products to be processed, and selecting corresponding processing equipment according to the product materials and process routes of the products to be processed; based on the product materials of the products to be processed, the process routes, a pre-created simulation scheduling model, and a preset matching algorithm, a processing station is obtained, and the products to be processed are processed according to the equipment of the processing station; wherein, the simulation scheduling model is trained based on the preset production capacity and stations of the processing equipment, so that the working path of the obtained production line is optimal and the efficiency is the highest. Through the above method, the present invention improves the quality of the products, reduces the production cost, and improves the efficiency of the production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the functional modules of the terminal device to which the simulation scheduling device for the production line of the present invention belongs;

[0040] Figure 2 It is a schematic flowchart of the first embodiment of the simulation scheduling method for the production line of the present invention;

[0041] Figure 3 It is a schematic diagram of the critical path involved in the second embodiment of the simulation scheduling method for the production line of the present invention;

[0042] Figure 4 It is a schematic diagram of the preset matching algorithm involved in the second embodiment of the simulation scheduling method for the production line of the present invention;

[0043] Figure 5 It is a schematic flowchart of the third embodiment of the simulation scheduling method for the production line of the present invention;

[0044] Figure 6 It is a schematic flowchart of the fourth embodiment of the simulation scheduling method for the production line of the present invention;

[0045] Figure 7It is a schematic diagram of the functional modules of the simulation scheduling system for the production line of the present invention.

[0046] The realization, functional characteristics and advantages of the object of the present invention will be further described with reference to the embodiments and the accompanying drawings. Specific embodiments

[0047] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0048] The main solution of the embodiment of the present invention is: obtaining the product materials and process routes of the product to be processed; based on the product materials of the product to be processed, the process routes, a pre-created simulation scheduling model, and a preset matching algorithm, obtaining processing stations to process the product to be processed according to the equipment of the processing stations; wherein, the simulation scheduling model is trained based on the preset production capacity and stations of the processing equipment.

[0049] Technical terms related to the embodiments of the present invention:

[0050] Genetic Algorithm: (Genetic Algorithm, GA), this algorithm is designed and proposed according to the evolution law of organisms in nature. It is a computational model that simulates the natural selection and genetic mechanism of Darwin's theory of biological evolution in the biological evolution process, and is a method for searching for the optimal solution by simulating the natural evolution process. This algorithm uses mathematical methods and computer simulation operations to convert the problem-solving process into processes similar to the crossover and mutation of chromosome genes in biological evolution. When solving relatively complex combinatorial optimization problems, compared with some conventional optimization algorithms, it can usually obtain better optimization results more quickly. Genetic algorithms have been widely applied in the fields of combinatorial optimization, machine learning, signal processing, adaptive control, and artificial life.

[0051] BOM: (Bill of Material, material list), when using computer-aided enterprise production management, first, the computer must be able to read the product composition and all the materials involved in the products manufactured by the enterprise. In order to facilitate computer recognition, the product structure expressed in diagrams must be converted into a certain data format. The file that describes the product structure in this data format is the material list, that is, Bom. It is a technical document that defines the product structure. Therefore, it is also called the product structure table or product structure tree. In some industrial fields, it may be called "formula", "element table" or other names.

[0052] MS crossover: The crossover of the machine selection part includes two-point crossover and single-point mutation operators, that is: updating the value at the specified position of MS to the code of the machine with the shortest processing time in the set of optional machines corresponding to a certain workpiece process.

[0053] OS Crossover: The crossover in the process selection part includes sequential crossover and inverse mutation operator, that is, swapping values at different positions in the OS.

[0054] Scheduling Algorithm: Production scheduling refers to the process of allocating production tasks to production resources. On the premise of considering capacity and equipment, with a certain amount of materials, arrange the production sequence of each production task, optimize the production sequence, and optimize the selection of production equipment to reduce waiting time and balance the production load of each machine and worker. Scheduling algorithms include: scheduling according to the shortest construction period, scheduling according to the delivery date in sequence, scheduling according to the distance between the construction period and the delivery date, and scheduling according to the CR value. Among them, CR is the abbreviation of the English critical ratio, which can be translated as the important ratio. Its calculation method is: the difference between the delivery date and the current date, and then divided by the construction period. The smaller the value, the higher the degree of urgency and the higher the scheduling priority.

[0055] VNS: Deep analysis of vagus nerve stimulation. The vagus nerve is the 10th pair of the 12 pairs of cranial nerves in the human body and belongs to a part of the autonomic nervous system. Its function is to control the information input and output of glands and internal organs.

[0056] In the traditional packaging and printing industry, insufficient production forecasting and demand control will lead to an increase in production costs, while simulation scheduling software can simulate the production line. However, simulation scheduling software, although highly functional, has a high learning cost and cannot be customized, and there is even less simulation scheduling software specifically for the packaging and printing industry.

[0057] The present invention provides a solution, aiming to improve the quality of products, reduce production costs, and improve the working efficiency of the production line.

[0058] Specifically, refer to Figure 1 , Figure 1 is a schematic diagram of the functional modules of the terminal device to which the simulation scheduling device of the production line of the present invention belongs. The simulation scheduling device of this production line can be a device independent of the terminal device, capable of image processing and network model training, and can be carried on the terminal device in the form of hardware or software. The terminal device can be an intelligent mobile terminal with data processing functions such as a mobile phone or a tablet computer, or a fixed terminal device or a server with data processing functions, etc.

[0059] In this embodiment, the terminal device to which the simulation scheduling device of this production line belongs at least includes an output module 110, a processor 120, a memory 130, and a communication module 140.

[0060] The operation method and the simulation scheduling program of the production line are stored in the memory 130; the output module 110 can be a display screen, etc. The communication module 140 can include a WIFI module, a mobile communication module, a Bluetooth module, etc., and communicates with external devices or servers through the communication module 140.

[0061] Among them, when the simulation scheduling program of the production line in the memory 130 is executed by the processor, the following steps are implemented:

[0062] Obtain the product materials and process routes of the product to be processed;

[0063] Based on the product materials of the product to be processed, the process route, the pre-created simulation scheduling model, and the preset matching algorithm, obtain the processing stations to process the product to be processed according to the equipment of the processing stations; among them, the simulation scheduling model is trained based on the preset production capacity and stations of the processing equipment.

[0064] Furthermore, when the simulation scheduling program of the production line in the memory 130 is executed by the processor, the following steps are also implemented:

[0065] Based on the product materials of the product to be processed, the process route, the simulation scheduling model, and the preset matching algorithm, determine the key stations of the product to be processed;

[0066] Based on the key stations, calculate the fitness value and the current iteration number;

[0067] If the current iteration number does not meet the preset conditions, then based on the product materials of the product to be processed, the process route, the simulation scheduling model, the preset matching algorithm, the fitness value, and the key stations, determine the adjustment stations;

[0068] Update the key stations according to the adjustment stations, and return to execute the steps: based on the key stations, calculate the fitness value and the current iteration number;

[0069] If the current iteration number meets the preset conditions, then use the key stations as the processing stations.

[0070] Furthermore, when the simulation scheduling program of the production line in the memory 130 is executed by the processor, the following steps are also implemented:

[0071] Based on the key stations and the fitness value, calculate the recombination probability;

[0072] Based on the product materials of the product to be processed, the process route, the simulation scheduling model, the preset matching algorithm, and the recombination probability, obtain the selection samples;

[0073] Perform MS crossover and OS crossover on the sample to obtain a crossover result;

[0074] Based on the crossover result, calculate the mutation probability;

[0075] Based on the mutation probability, search for the selected sample to obtain the adjusted workstations.

[0076] Further, when the simulation scheduling program of the production line in the memory 130 is executed by the processor, the following steps are also implemented:

[0077] Establish the simulation scheduling model;

[0078] Among them, the step of establishing the simulation scheduling model includes:

[0079] Obtain the preset production capacity and workstations of the processing equipment;

[0080] Construct the simulation scheduling model according to the preset production capacity and workstations of the processing equipment.

[0081] Further, when the simulation scheduling program of the production line in the memory 130 is executed by the processor, the following steps are also implemented:

[0082] Based on the efficiency of the equipment at the processing workstation, the task volume corresponding to the product to be processed, and the latest delivery date of the product to be processed, calculate the number of processing equipment on the production line corresponding to the product to be processed; and / or the number of operators required for the production line corresponding to the product to be processed;

[0083] If the number of processing equipment on the production line corresponding to the product to be processed; and / or the number of operators required for the production line corresponding to the product to be processed does not meet the preset quantity, adjust the number of production lines corresponding to the product to be processed; and / or adjust the number of equipment at the processing workstation.

[0084] Further, when the simulation scheduling program of the production line in the memory 130 is executed by the processor, the following steps are also implemented:

[0085] If the processing method of the product to be processed is discrete processing, based on the efficiency of the equipment at the processing workstation, the task volume corresponding to the product to be processed, the latest delivery date of the product to be processed, and the preset discrete processing formula, calculate the number of processing equipment on the production line corresponding to the product to be processed; and / or the number of operators required for the production line corresponding to the product to be processed;

[0086] If the processing method of the product to be processed is continuous processing, calculate the number of processing devices on the production line corresponding to the product to be processed based on the efficiency of the equipment at the processing station, the task volume corresponding to the product to be processed, the latest delivery date of the product to be processed, and a preset continuous processing formula; and / or the number of operators required for the production line corresponding to the product to be processed.

[0087] Further, when the simulation scheduling program of the production line in the memory 130 is executed by the processor, the following steps are also implemented:

[0088] Obtain the actual production capacity of the processing equipment;

[0089] Transmit the actual production capacity back to the simulation scheduling model to update the preset production capacity; and return to execute the step: construct the simulation scheduling model according to the preset production capacity of the processing equipment and the workstations.

[0090] In this embodiment, through the above solution, specifically, obtain the product materials and process routes of the product to be processed; based on the product materials of the product to be processed, the process routes, a pre-created simulation scheduling model, and a preset matching algorithm, obtain the processing stations to process the product to be processed according to the equipment at the processing stations; wherein, the simulation scheduling model is trained based on the preset production capacity of the processing equipment and the workstations. The purpose of the present invention is to improve the quality of products, reduce production costs, and improve the efficiency of the production line.

[0091] Based on the above terminal device architecture but not limited to the above architecture, an embodiment of the method of the present invention is proposed.

[0092] Refer to Figure 2 , Figure 2 is a schematic flowchart of the first embodiment of the simulation scheduling method for the production line of the present invention. The simulation scheduling method for the production line includes:

[0093] Step S101, obtain the product materials and process routes of the product to be processed.

[0094] Step S102, based on the product materials of the product to be processed, the process routes, a pre-created simulation scheduling model, and a preset matching algorithm, obtain the processing stations to process the product to be processed according to the equipment at the processing stations; wherein, the simulation scheduling model is trained based on the preset production capacity of the processing equipment and the workstations.

[0095] The execution subject of the method in this embodiment can be a simulation scheduling device for a production line, or a simulation scheduling terminal device or server for a production line. In this embodiment, a simulation scheduling device for a production line is taken as an example, and this simulation scheduling device for a production line can be integrated on terminal devices such as smart phones and tablet computers with data processing functions.

[0096] To improve the quality of products, reduce production costs, and improve the efficiency of the production line, first, obtain the product materials and process routes of the products to be processed.

[0097] For easy computer recognition and to enable the computer to read the product composition and all related materials manufactured by the enterprise, it is necessary to convert the product structure expressed in diagrams into a certain data format. The file that describes the product structure in this data format is the Bill of Materials, i.e., Bom.

[0098] Specifically, obtain the material Bom and process route of the products to be processed. Among them, the user can set the material Bom and process route of the products to be processed according to actual needs. The process route includes all processes involved in processing the products to be processed, and there is a one-to-many relationship between the process and the equipment.

[0099] Furthermore, input the product materials and process routes of the products to be processed into a pre-created simulation production scheduling model for analysis. Based on a preset matching algorithm, obtain the processing stations to process the products to be processed according to the equipment at the processing stations; among them, the preset matching algorithm is a hybrid algorithm of tabu search + genetic algorithm.

[0100] Since there are multiple processing methods for the product materials of the products to be processed and multiple processes are included in the process route, therefore, inputting the product materials and process routes of the products to be processed into a pre-created simulation production scheduling model for analysis can screen and obtain the processing stations for processing the product materials of the products to be processed according to the process route. And the processing equipment at the processing stations obtained through the analysis of the pre-created simulation production scheduling model and the preset matching algorithm is the most suitable processing equipment for the process route of the products to be processed, thereby optimizing production capacity, equipment utilization rate, bottlenecks, production efficiency, logistics efficiency, and worker efficiency.

[0101] Furthermore, based on the equipment at the processing stations, obtain the production line corresponding to the products to be processed and calculate the production efficiency of this production line.

[0102] Specifically, according to the equipment at the processing stations, obtain the production line corresponding to the process route of the products to be processed and calculate the production efficiency of this production line; among them, the production efficiency includes the production capacity of this production line, the setup time of the equipment on the production line, the number of processes, the buffer time of the processes, etc.

[0103] Furthermore, output the production efficiency so that the user can judge whether it is necessary to retrain the simulation production scheduling model according to the work efficiency, improve the accuracy of the simulation production scheduling model, improve the efficiency of the production line, and reduce production costs.

[0104] In this embodiment, through the above solution, specifically, the product materials and process routes of the product to be processed are obtained; based on the product materials of the product to be processed, the process routes, a pre-created simulation scheduling model, and a preset matching algorithm, processing stations are obtained to process the product to be processed according to the equipment at the processing stations; wherein, the simulation scheduling model is trained based on the preset production capacity of the processing equipment and the stations. The present invention inputs the product materials and process routes of the product to be processed into a pre-created simulation scheduling model, analyzes based on a preset matching algorithm, and filters out processing stations that can process the product materials of the product to be processed according to the process routes. Moreover, the processing equipment at the processing stations obtained through analysis by the pre-created simulation scheduling model is the processing equipment most suitable for the process route of the product to be processed, thereby optimizing production capacity, equipment utilization rate, bottlenecks, production efficiency, logistics efficiency, and worker efficiency.

[0105] Based on the above Figure 2 shown embodiment, the second embodiment of the simulation scheduling method for the production line of the present invention is proposed. In this embodiment, step S102: Based on the product materials of the product to be processed, the process routes, a pre-created simulation scheduling model, and a preset matching algorithm, processing stations are obtained to process the product to be processed according to the equipment at the processing stations; wherein, the simulation scheduling model trained based on the preset production capacity of the processing equipment and the stations includes:

[0106] Step S1021, based on the product materials of the product to be processed, the process routes, the simulation scheduling model, and the preset matching algorithm, determine the key stations of the product to be processed.

[0107] Based on the product materials of the product to be processed, the process routes, the simulation scheduling model, and the preset matching algorithm, determine the key stations of the product to be processed; wherein, the key stations are the stations that must be included and are indispensable in the process route corresponding to the product to be processed.

[0108] For example: As Figure 3 shown, the product to be processed includes A1 - A11 processing stations. Among them, A1, A5, A2, A3, A6, A10, and A11 are the key stations of the product to be processed, and the remaining stations are non-essential stations of the product to be processed. The gray path is the process flow path that includes all the key stations of the product to be processed. The gray path is the optimal path of the product to be processed. All the key stations of the product to be processed are included on this path, and there are no non-essential stations. Thus, the processing route obtained has the highest efficiency.

[0109] It should be noted that the preset matching algorithm is a hybrid algorithm of tabu search + genetic algorithm, and the specific description is as follows:

[0110] The description of the production scheduling problem in the production workshop is as follows: A production and processing factory has m machines and needs to process n parts. Each part contains one or more processes, and the process sequence of the parts is predetermined. Each process can be processed on multiple different machines, and the processing time of the process varies with the performance of the machine. The goal of production scheduling is to select the most suitable machine for each process, determine the best processing sequence and start time of each part's process on each machine, so as to minimize the production lead time or make the delivery date the earliest.

[0111] Suppose the unit-time production capacity of the selected equipment (M) is A, the machine setup time is B, the single task is C, the process is D, the process buffer time is E, and the task volume is F. There is an association relationship between process D and equipment M. Calculate the production duration of the task: The production duration of task C = F / A + B + E.

[0112] Start time = MAX (the earliest available production time of this task, the earliest available time of the equipment)

[0113] End time = Start time + Task production duration.

[0114] In addition, the following conditions need to be met during the production process:

[0115] a. Only one part can be processed on the same machine at the same time;

[0116] b. The same process of the same part can only be processed by one machine at the same time;

[0117] c. Once the processing of each process of each part starts, it cannot be interrupted;

[0118] d. Different parts have the same priority;

[0119] e. There is no precedence constraint between the processes of different parts, but there is a precedence constraint between the processes of the same part;

[0120] f. All parts can be processed at time zero.

[0121] For the above optimal scheduling solution problem, the algorithm adopted is a hybrid algorithm of tabu search + genetic algorithm, that is, the above preset matching algorithm. Compared with a single algorithm, the hybrid algorithm has significantly improved in terms of solution efficiency and quality. The specific algorithm process is as Figure 4 shown:

[0122] 1. Parameter setting ( N pop - Population size, N gen - Maximum number of generations, P c - Recombination probability, P m - Mutation probability).

[0123] 2. Obtain chromosomes; among them, the chromosomes are randomly arranged to generate the initial population.

[0124] Specifically, first, a population of 100 individuals is randomly generated, and each individual is represented by a chromosome. For each chromosome, an OS sequence is randomly generated while ensuring that the number of all processes of all workpieces is satisfied, and an MS sequence is randomly generated while ensuring the existence of the machine corresponding to the process of a certain workpiece.

[0125] 3. Decode and calculate the fitness value of the chromosomes in the current initial population; where the fitness value is the maximum completion time for each workpiece to complete all processing operations.

[0126] 4. Calculate the termination condition: If the condition is satisfied and the optimal solution or approximate optimal solution is obtained, the algorithm terminates; otherwise, execute step 5; where the termination condition is the number of termination loop times, which can be set according to actual requirements.

[0127] 5. Calculate the recombination probability p of the initial population. If the recombination probability p is less than the set probability value P c , execute step 6; otherwise, execute step 7; P c which can be set according to actual requirements.

[0128] 6. Select one individual from the external memory bank and the tournament respectively, and execute step 8.

[0129] 7. Select one individual from the tournament and execute step 8.

[0130] 8. Perform MS crossover and OS crossover on the selected chromosomes, and calculate the mutation probability.

[0131] 9. If the mutation probability is less than the set parameter P m , then perform chromosome MS mutation and OS mutation, and execute step 10. If the mutation probability is greater than the set parameter, execute step 10.

[0132] 10. Perform VNS search on each individual of the initial population to generate a new generation of population, and then execute step 3.

[0133] Step S1022: Calculate the fitness value and the current iteration number based on the key workstations.

[0134] Step S1023: If the current iteration number does not meet the preset condition, determine the adjustment workstation based on the product materials of the product to be processed, the process route, the simulation scheduling model, the preset matching algorithm, the fitness value, and the key workstations.

[0135] Step S1024: Update the key workstations according to the adjustment workstation, and return to execute step S1022: Calculate the fitness value and the current iteration number based on the key workstations.

[0136] Step S1025: If the current iteration number meets the preset condition, then use the key station as the processing station.

[0137] In this embodiment, based on the key stations, calculate the fitness value and the current iteration number; if the current iteration number does not meet the preset condition, then based on the product material, process route, simulation scheduling model, preset matching algorithm, fitness value, and key stations of the product to be processed, determine the adjustment stations; where the preset condition is the preset iteration number, which is set according to the actual situation; update the key stations according to the adjustment stations, and return to execute step S1022: based on the key stations, calculate the fitness value and the current iteration number; if the current iteration number meets the preset condition, then use the key stations as the processing stations.

[0138] For example: The calculated key stations of the product A to be processed are A1 and A2, calculate the fitness values and the current iteration number of A1 and A2; if the current iteration number does not meet the preset condition B, then based on the product material, process route, simulation scheduling model, preset matching algorithm, fitness value, and key stations of the product A to be processed, determine the adjustment stations, and recalculate the fitness value and iteration number according to the adjustment stations until the current loop number meets the preset condition B, and terminate the loop.

[0139] Among them, step S1023 includes:

[0140] Step A1: Calculate the recombination probability based on the key stations and the fitness value.

[0141] Step A2: Obtain the selection samples based on the product material, process route, simulation scheduling model, preset matching algorithm, and recombination probability of the product to be processed.

[0142] Step A3: Perform MS crossover and OS crossover on the samples to obtain the crossover result.

[0143] Step A4: Calculate the mutation probability based on the crossover result.

[0144] Step A5: Search the selection samples based on the mutation probability to obtain the adjustment stations.

[0145] Specifically, based on the key workstations and fitness values, calculate the recombination probability of the key workstations; if the recombination probability is less than the preset recombination probability, select an individual from the external memory bank and tournament selection as the selection sample; if the recombination probability is not less than the preset recombination probability, select an individual from the tournament selection as the selection sample; perform MS crossover and OS crossover on the selection sample to obtain the crossover result, and calculate the mutation probability of the crossover result. If the calculated mutation probability is less than the preset mutation probability, perform MS mutation and OS mutation, and perform VNS search on each individual to obtain the adjusted workstations; if the calculated mutation probability is not less than the preset mutation probability, perform VNS search on each individual to obtain the adjusted workstations; where the chromosome consists of two parts, the machine selection part (MS) and the operation selection part (OS), with lengths of N respectively, and N represents the sum of the number of all operations of all workpieces. Both MS and OS are implemented using indirect coding. For MS, two-point crossover and single-point mutation operators are used respectively, and for OS, order crossover and inversion mutation operators are used.

[0146] In this embodiment, through the above scheme, specifically, obtain the product materials and process routes of the product to be processed; based on the product materials of the product to be processed, the process route, the pre-created simulation scheduling model, and the preset matching algorithm, obtain the processing workstations to process the product to be processed according to the equipment of the processing workstations; where the simulation scheduling model is trained based on the preset production capacity and workstations of the processing equipment. The algorithm adopted by the present invention is a hybrid algorithm of tabu search + genetic algorithm. Compared with a single algorithm, the hybrid algorithm has significantly improved in both solution efficiency and quality. The processing equipment on the processing workstations obtained through the analysis of the tabu search + genetic algorithm hybrid algorithm is the most suitable processing equipment for the process route of the product to be processed, thereby optimizing production capacity, equipment utilization rate, bottlenecks, production efficiency, logistics efficiency, and worker efficiency.

[0147] Refer to Figure 5 , Figure 5 is a schematic flowchart of the third embodiment of the simulation scheduling method for the production line of the present invention. Based on the above Figure 2 shown embodiment, in this embodiment, step S102: Based on the product materials of the product to be processed, the process route, the pre-created simulation scheduling model, and the preset matching algorithm, obtain the processing workstations to process the product to be processed according to the equipment of the processing workstations; where, before the simulation scheduling model is trained based on the preset production capacity and workstations of the processing equipment, it includes:

[0148] Step S103, obtain the preset production capacity and workstations of the processing equipment.

[0149] Step S104, construct the simulation scheduling model according to the preset production capacity and workstations of the processing equipment.

[0150] As an implementation, for a physical factory, the layout of a workshop or production line can be modeled to obtain a simulation production scheduling model to restore factory equipment, production lines, process routes, and workstations. By collecting the current production capacity and production capacity per unit time of the equipment and inputting the current production capacity and production capacity per unit time of the equipment into the simulation production scheduling model, an optimal production plan based on infinite production capacity and finite production capacity can be obtained.

[0151] To obtain the simulation production scheduling model, first, obtain the preset production capacity and workstations of the processing equipment; wherein, the processing equipment includes all the equipment included in the physical factory and the layout relationship between the equipment, and the workstations of the processing equipment include the physical relationship corresponding between the workstations of the processing equipment in the factory and the processing equipment. The user can set the preset production capacity according to the actual situation, and this embodiment does not make specific limitations on this.

[0152] Further, construct a simulation production scheduling model according to the preset production capacity and workstations of the processing equipment.

[0153] As another implementation, obtain the product materials and process routes of the training products, perform a running simulation on the product materials, process routes of the training products, the preset production capacity and workstations of the processing equipment through a clock simulator, and record in detail the production scheduling process data. After statistical calculation, important data regarding time, utilization rate, quantity of products, efficiency, etc. are obtained. By analyzing these data, quantitatively evaluate the performance of the factory, and according to the needs of the customers, improve the layout. The program can be run again for iterative optimization; wherein, the clock simulator can quickly complete the running simulation of a relatively long physical time in a short time.

[0154] Thus, by obtaining the preset production capacity and workstations of the processing equipment, modeling the factory to obtain a simulation production scheduling model, the physical factory simulation modeling is realized. Furthermore, through the simulation production scheduling model, predict and optimize the production scheduling, and improve the efficiency and flexibility of the production scheduling.

[0155] Further, after step S104 includes:

[0156] Step B1, obtain the actual production capacity of the processing equipment;

[0157] Step B2, transmit the actual production capacity back to the simulation production scheduling model to update the preset production capacity; and return to execute step S104: construct the simulation production scheduling model according to the preset production capacity and workstations of the processing equipment.

[0158] During the actual production process, obtain the actual production capacity of the processing equipment; and transmit the actual production capacity back to the factory model to update the preset production capacity; and return to execute step S104: construct the simulation production scheduling model according to the preset production capacity and workstations of the processing equipment.

[0159] Specifically, in the actual production process, obtain the actual production capacity of the processing equipment, calculate the setup time and running time of the equipment; transmit the actual production capacity back to the simulation scheduling model to update the preset production capacity, and transmit the setup time and running time of the equipment to the simulation scheduling model; and return to execute step S104: construct the simulation scheduling model according to the preset production capacity of the processing equipment and the workstations.

[0160] Thus, during the actual production process, the preset production capacity is corrected, enabling the simulation scheduling model to more accurately reproduce the actual working conditions of the factory and obtaining a scheduling efficiency that better conforms to actual production. Directly connect the software with the simulation scheduling model to the production system, directly obtain the basic elements of the factory through the production system, and perform simulation scheduling at any time, which has significant advantages in terms of ease of use and openness.

[0161] In this embodiment, through the above solution, specifically, obtain the product materials and process routes of the product to be processed; based on the product materials of the product to be processed, the process routes, the pre-created simulation scheduling model, and the preset matching algorithm, obtain the processing workstations to process the product to be processed according to the equipment at the processing workstations; wherein, the simulation scheduling model is trained based on the preset production capacity and workstations of the processing equipment. The present invention models the factory by obtaining the preset production capacity and workstations of the processing equipment to obtain a simulation scheduling model, realizing the simulation modeling of the physical factory, and then predicting and optimizing the production scheduling through the simulation scheduling model, improving the efficiency and flexibility of the scheduling.

[0162] Refer to Figure 6 , Figure 6 is a schematic flowchart of the fourth embodiment of the simulation scheduling method for the production line of the present invention. Based on the above Figure 2 shown embodiment, in this embodiment, after step S102: based on the product materials of the product to be processed, the process routes, the pre-created simulation scheduling model, and the preset matching algorithm, obtain the processing workstations, it includes:

[0163] Step S105, calculate the number of processing equipment on the production line corresponding to the product to be processed based on the efficiency of the equipment at the processing workstations, the task volume corresponding to the product to be processed, and the latest delivery date of the product to be processed; and / or the number of operators required for the production line corresponding to the product to be processed.

[0164] Step S106, if the number of processing equipment on the production line corresponding to the product to be processed; and / or the number of operators required for the production line corresponding to the product to be processed does not meet the preset quantity, then adjust the number of production lines corresponding to the product to be processed; and / or adjust the number of equipment at the processing workstations.

[0165] As an implementation manner, in this embodiment, based on the efficiency of the equipment at the processing station, the task volume corresponding to the product to be processed, and the latest delivery date of the product to be processed, the number of processing equipment on the production line corresponding to the product to be processed is calculated; and / or the number of operators required for the production line corresponding to the product to be processed.

[0166] Specifically, based on the unit-time production capacity of the standard equipment in the factory, the setup time of the equipment, the number of processes, the buffer time of the process, the number of production tasks, the production line, the process sequence, the correspondence between the equipment and the process, the latest delivery date, and the working system (24-hour / shift system / standard working hours), the number of processing equipment on the production line corresponding to the product to be processed is calculated.

[0167] As another implementation manner, based on the unit-time production capacity of the standard equipment in the factory, the setup time of the equipment, the number of processes, the buffer time of the process, the number of production tasks, the production line, the process sequence, the correspondence between the equipment and the process, the latest delivery date, and the working system (24-hour / shift system / standard working hours), the number of operators required for the production line corresponding to the product to be processed is calculated.

[0168] As yet another implementation manner, based on the unit-time production capacity of the standard equipment in the factory, the setup time of the equipment, the number of processes, the buffer time of the process, the number of production tasks, the production line, the process sequence, the correspondence between the equipment and the process, the latest delivery date, and the working system (24-hour / shift system / standard working hours), the number of processing equipment on the production line corresponding to the product to be processed; the number of operators required for the production line corresponding to the product to be processed is calculated.

[0169] More specifically, first, the processing method of the product to be processed is determined.

[0170] If the processing method of the product to be processed is discrete processing, the number of processing equipment on the production line corresponding to the product to be processed is obtained based on a preset discrete processing formula.

[0171] For example: The unit-time production capacity of the standard equipment for the process is A, the setup duration is B, a single task is C, the process is D, the process buffer time is E, the task volume is F, and let the number of equipment required for a single task be n.

[0172] n = (latest delivery date - current time, excluding non-working hours) / total production duration, total production duration = F / nA + nB + nE, and this formula is used as the discrete processing formula.

[0173] According to the total task volume of the production order, the number of all equipment required is calculated.

[0174] If the processing method of the product to be processed is continuous processing, the number of processing equipment on the production line corresponding to the product to be processed is obtained based on a preset continuous processing formula.

[0175] For example: The unit time production capacity of the standard equipment for the process is A, the machine setup time is B, a single task is C, the process is D, the process buffer time is E, the task volume is F. Let the number of production lines be n, and the number of process equipment on a single production line be xi.

[0176] n = (latest delivery date - current time, excluding non - working hours) / total production time, total production time = F / (xiA + xiB + xiE). This formula is used as the continuous processing formula.

[0177] Based on the total task volume of the production order, calculate the total number of all required equipment: xi * n.

[0178] Thus, by collecting the current production capacity and unit - time production capacity of equipment and workers, and inputting the current production capacity and unit - time production capacity of equipment and workers into the simulation production scheduling model, an optimal production plan based on infinite capacity and finite capacity can be obtained, and the number of processing equipment for the production line corresponding to the product to be processed can be calculated; and / or the number of operating workers required for the production line corresponding to the product to be processed.

[0179] Furthermore, if the number of processing equipment for the production line corresponding to the product to be processed does not meet the preset quantity, then adjust the number of production lines corresponding to the product to be processed; and / or adjust the number of equipment at the processing stations, where the preset quantity includes the preset number of equipment and the preset number of workers.

[0180] Specifically, if the number of processing equipment for the production line corresponding to the product to be processed does not meet the preset number of equipment, then adjust the number of production lines corresponding to the product to be processed.

[0181] If the number of processing equipment for the production line corresponding to the product to be processed does not meet the preset number of equipment, then adjust the number of equipment at the processing stations.

[0182] If the number of processing equipment for the production line corresponding to the product to be processed does not meet the preset number of equipment, then adjust the number of production lines corresponding to the product to be processed; adjust the number of equipment at the processing stations.

[0183] As another implementation method, if the number of operating workers required for the production line corresponding to the product to be processed does not meet the preset quantity, then adjust the number of production lines corresponding to the product to be processed; and / or adjust the number of equipment at the processing stations, where the preset quantity includes the preset number of equipment and the preset number of workers.

[0184] Specifically, if the number of operating workers required for the production line corresponding to the product to be processed does not meet the preset number of workers, then adjust the number of production lines corresponding to the product to be processed.

[0185] If the number of operating workers required for the production line corresponding to the product to be processed does not meet the preset number of workers, the number of devices at the processing stations is adjusted.

[0186] If the number of operating workers required for the production line corresponding to the product to be processed does not meet the preset number of workers, the number of production lines corresponding to the product to be processed is adjusted; the number of devices at the processing stations is adjusted.

[0187] As another implementation, if the number of processing devices on the production line corresponding to the product to be processed and the number of operating workers required for the production line corresponding to the product to be processed do not meet the preset quantity, the number of production lines corresponding to the product to be processed is adjusted; and / or the number of devices at the processing stations is adjusted, where the preset quantity includes a preset number of devices and a preset number of workers.

[0188] Specifically, if the number of processing devices on the production line corresponding to the product to be processed does not meet the preset number of devices and the number of operating workers required for the production line corresponding to the product to be processed does not meet the preset number of workers, the number of production lines corresponding to the product to be processed is adjusted.

[0189] If the number of processing devices on the production line corresponding to the product to be processed does not meet the preset number of devices and the number of operating workers required for the production line corresponding to the product to be processed does not meet the preset number of workers, the number of devices at the processing stations is adjusted.

[0190] If the number of processing devices on the production line corresponding to the product to be processed does not meet the preset number of devices and the number of operating workers required for the production line corresponding to the product to be processed does not meet the preset number of workers, the number of production lines corresponding to the product to be processed is adjusted; the number of devices at the processing stations is adjusted.

[0191] Thus, by adjusting the number of production lines and / or the number of processing devices, the simulation scheduling model is made to meet the user's requirements and the user experience is improved.

[0192] It should be noted that the preset quantity is set according to the actual situation, and this embodiment does not make specific limitations on this.

[0193] In this embodiment, through the above solution, specifically, the product materials and process routes of the product to be processed are obtained; based on the product materials of the product to be processed, the process routes, a pre-created simulation production scheduling model, and a preset matching algorithm, processing stations are obtained to process the product to be processed according to the equipment of the processing stations; wherein, the simulation production scheduling model is trained based on the preset production capacity of the processing equipment and the stations. The present invention collects the current production capacity and unit-time production capacity of the equipment and workers, inputs the current production capacity and unit-time production capacity of the equipment and workers into the simulation production scheduling model, obtains the optimal production plan based on infinite production capacity and finite production capacity, and can calculate the number of processing equipment for the production line corresponding to the product to be processed; and / or the number of operating workers required for the production line corresponding to the product to be processed.

[0194] Referring to Figure 7 , Figure 7 is a schematic diagram of the functional modules of the simulation production scheduling system of the production line of the present invention. The simulation production scheduling system of the production line includes:

[0195] A data acquisition module 10, configured to acquire the product materials and process routes of the product to be processed;

[0196] A station analysis module 20, configured to obtain processing stations based on the product materials of the product to be processed, the process routes, a pre-created simulation production scheduling model, and a preset matching algorithm, so as to process the product to be processed according to the equipment of the processing stations; wherein, the simulation production scheduling model is trained based on the preset production capacity of the processing equipment and the stations.

[0197] For the principle and implementation process of realizing the simulation production scheduling of the production line in this embodiment, please refer to the above embodiments, and details will not be described herein again.

[0198] In addition, an embodiment of the present invention further provides a terminal device, where the terminal device includes a memory, a processor, and a simulation production scheduling program of the production line stored on the memory and executable on the processor. When the simulation production scheduling program of the production line is executed by the processor, the steps of the simulation production scheduling method of the production line as described above are implemented.

[0199] Since all the technical solutions of all the foregoing embodiments are adopted when the simulation production scheduling program of the production line is executed by the processor, it has at least all the beneficial effects brought by all the technical solutions of all the foregoing embodiments, and details will not be described herein one by one.

[0200] In addition, an embodiment of the present invention further provides a computer-readable storage medium, where a simulation production scheduling program of the production line is stored on the computer-readable storage medium. When the simulation production scheduling program of the production line is executed by the processor, the steps of the simulation production scheduling method of the production line as described above are implemented.

[0201] Since all the technical solutions of the foregoing embodiments are adopted when the simulation scheduling program of this production line is executed by a processor, it has at least all the beneficial effects brought by all the technical solutions of the foregoing embodiments, and details are not described herein one by one.

[0202] Compared with the prior art, a simulation scheduling method, system, terminal device and storage medium for a production line provided by the present invention obtain the product materials and process routes of products to be processed; and based on the product materials of the products to be processed, the process routes, a pre-created simulation scheduling model and a preset matching algorithm, obtain processing stations to process the products to be processed according to the devices at the processing stations; wherein the simulation scheduling model is trained based on the preset production capacity of processing devices and stations. The present invention aims to improve the quality of products, reduce production costs and improve the efficiency of the production line.

[0203] It should be noted that, in this article, the terms "include", "comprise" or any other variation thereof are intended to cover non-exclusive inclusion, so that a process, method, article or method including a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or method. Without further limitation, an element defined by the phrase "including a..." does not exclude the existence of additional identical elements in the process, method, article or method including the element.

[0204] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0205] Through the description of the above embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. The computer software product is stored in a storage medium as described above (such as ROM / RAM, magnetic disk, optical disc) and includes several instructions to enable a terminal device (which may be a mobile phone, computer, server, controlled terminal, or network device, etc.) to execute the methods of each embodiment of the present invention.

[0206] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structure or equivalent process transformation made by using the specification and drawings of the present invention, or directly or indirectly applied to other related technical fields, shall be included in the patent protection scope of the present invention in the same way.

Claims

1. A simulation scheduling method for a production line, characterized in that, The method includes the following steps: Obtain the product materials and process route of the product to be processed; Based on the product materials of the product to be processed, the process route, a pre-created simulation scheduling model, and a preset matching algorithm, obtain the processing stations to process the product to be processed according to the equipment at the processing stations; wherein, the simulation scheduling model is trained based on the preset production capacity and stations of the processing equipment; Among them, the step of obtaining the processing stations based on the product materials of the product to be processed, the process route, a pre-created simulation scheduling model, and a preset matching algorithm includes: Based on the product materials of the product to be processed, the process route, the simulation scheduling model, and the preset matching algorithm, determine the key stations of the product to be processed; Based on the key stations, calculate the fitness value and the current iteration number; If the current iteration number does not meet the preset conditions, then based on the product materials of the product to be processed, the process route, the simulation scheduling model, the preset matching algorithm, the fitness value, and the key stations, determine the adjustment stations; Update the key stations according to the adjustment stations, and return to execute the steps: based on the key stations, calculate the fitness value and the current iteration number; If the current iteration number meets the preset conditions, then use the key stations as the processing stations; Among them, the step of determining the adjustment stations based on the product materials of the product to be processed, the process route, the simulation scheduling model, the preset matching algorithm, the fitness value, and the key stations includes: Based on the key stations and the fitness value, calculate the recombination probability; Based on the product materials of the product to be processed, the process route, the simulation scheduling model, the preset matching algorithm, and the recombination probability, obtain the selection samples; Perform MS crossover and OS crossover on the samples to obtain the crossover results; Based on the crossover results, calculate the mutation probability; Based on the mutation probability, search the selection samples to obtain the adjustment stations.

2. The simulation scheduling method for the production line according to claim 1, wherein Before the step of obtaining the processing stations based on the product materials of the product to be processed, the process route, a pre-created simulation scheduling model, and a preset matching algorithm includes: Establish the simulation scheduling model; Among them, the step of establishing the simulation scheduling model includes: Obtain the preset production capacity and stations of the processing equipment; Construct the simulation scheduling model according to the preset production capacity and stations of the processing equipment.

3. The simulation scheduling method for the production line according to claim 1, characterized in that, After the step of obtaining the processing stations based on the product materials of the product to be processed, the process route, a pre-created simulation scheduling model, and a preset matching algorithm includes: Based on the efficiency of the equipment at the processing stations, the task volume corresponding to the product to be processed, and the latest delivery date of the product to be processed, calculate the number of processing equipment on the production line corresponding to the product to be processed; and / or the number of operators required for the production line corresponding to the product to be processed; If the number of processing devices on the production line corresponding to the product to be processed; and / or the number of operating workers required for the production line corresponding to the product to be processed does not meet the preset quantity, then adjust the number of production lines corresponding to the product to be processed; and / or adjust the number of devices at the processing stations.

4. The simulation scheduling method for the production line according to claim 3, wherein Calculating the number of processing devices on the production line corresponding to the product to be processed based on the efficiency of the devices at the processing stations, the task volume corresponding to the product to be processed, and the latest delivery date of the product to be processed; And / or the step of calculating the number of operating workers required for the production line corresponding to the product to be processed includes: If the processing method of the product to be processed is discrete processing, calculate the number of processing devices on the production line corresponding to the product to be processed and / or the number of operating workers required for the production line corresponding to the product to be processed based on the efficiency of the devices at the processing stations, the task volume corresponding to the product to be processed, the latest delivery date of the product to be processed, and a preset discrete processing formula; If the processing method of the product to be processed is continuous processing, calculate the number of processing devices on the production line corresponding to the product to be processed and / or the number of operating workers required for the production line corresponding to the product to be processed based on the efficiency of the devices at the processing stations, the task volume corresponding to the product to be processed, the latest delivery date of the product to be processed, and a preset continuous processing formula.

5. The simulation scheduling method for the production line according to claim 2, wherein After the step of obtaining the processing stations based on the product materials of the product to be processed, the process route, a pre-created simulation scheduling model, and a preset matching algorithm, it includes: Obtaining the actual production capacity of the processing devices; Transmitting the actual production capacity back to the simulation scheduling model to update the preset production capacity; and then return to execute the step: constructing the simulation scheduling model according to the preset production capacity of the processing devices and the workstations.

6. A simulation scheduling system for a production line, characterized in that, It includes: A data acquisition module for acquiring the product materials and process route of the product to be processed; A workstation analysis module for obtaining processing stations based on the product materials of the product to be processed, the process route, a pre-created simulation scheduling model, and a preset matching algorithm, so as to process the product to be processed according to the devices at the processing stations; wherein, the simulation scheduling model is trained based on the preset production capacity of the processing devices and the workstations; The workstation analysis module is further configured to determine the key workstations of the product to be processed based on the product materials of the product to be processed, the process route, the simulation scheduling model, and the preset matching algorithm; calculate the fitness value and the current iteration number based on the key workstations; if the current iteration number does not meet the preset conditions, then determine the adjustment workstations based on the product materials of the product to be processed, the process route, the simulation scheduling model, the preset matching algorithm, the fitness value, and the key workstations; update the key workstations according to the adjustment workstations, and then return to execute the step: calculate the fitness value and the current iteration number based on the key workstations; if the current iteration number meets the preset conditions, then use the key workstations as the processing stations; The station analysis module is further configured to calculate a recombination probability based on the key stations and the fitness value; obtain a selection sample based on the product materials of the product to be processed, the process route, the simulation scheduling model, the preset matching algorithm, and the recombination probability; perform MS crossover and OS crossover on the sample to obtain a crossover result; calculate a mutation probability based on the crossover result; and search the selection sample based on the mutation probability to obtain the adjusted stations.

7. A terminal device, characterized in that, The terminal device includes a memory, a processor, and a simulation scheduling method for a production line stored on the memory and executable on the processor. When the program for the simulation scheduling of the production line is executed by the processor, the steps of the simulation scheduling method for the production line according to any one of claims 1-5 are implemented.

8. A computer-readable storage medium, characterized in that, A program for the simulation scheduling of a production line is stored on the computer-readable storage medium. When the program for the simulation scheduling of the production line is executed by the processor, the steps of the simulation scheduling method for the production line according to any one of claims 1-5 are implemented.

Images