Method and device for simulating production and manufacturing, computer equipment and readable storage medium

Abstract

The invention relates to a method and device for simulating production and manufacturing, computer equipment and a readable storage medium. The analog simulation production manufacturing method comprises the following steps: acquiring a plurality of sub-simulation tasks under a total simulation task registered for a to-be-simulated production line; acquiring a plurality of first timing processing times corresponding to the plurality of sub-simulation tasks, and respectively converting the plurality of first timing processing times to a simulation timeline corresponding to the to-be-simulated production line to obtain a plurality of second timing processing times; performing execution time sorting on the plurality of sub simulation tasks according to the plurality of second timing processing times to obtain a time sorting result; generating production line simulation data on the simulation timeline according to the time sorting result; and simulating the to-be-simulated production line on the simulation timeline according to the production line simulation data. By adopting the method, the simulation effect of production line simulation is improved.

Description

Technical Field

[0001] The present application relates to the field of simulation technology, and in particular to a method, device, computer equipment and readable storage medium for simulation production and manufacturing. Background Art

[0002] With the continuous development of science and technology, simulation technology is also constantly iterating. For example, in the field of vocational education, in order to efficiently demonstrate and promote production activities, it is necessary to simulate and simulate the actual production and manufacturing processes to ensure that students can learn and actually manage production under the simulated production line. This makes the control of the authenticity of the production line simulation a top priority.

[0003] At present, in the process of production line simulation, a scheduled task framework is usually used for simulation, that is, the production line simulation is realized based on the real physical timeline. However, due to the limitations of the time consumption of production line simulation and the relatively single production line simulation data under the scheduled task framework, the final simulated production line cannot match the user's actual production line simulation needs, which makes it easy to have insufficient interactivity and lack of reality. Therefore, the simulation effect of the current production line simulation needs to be improved. Summary of the invention

[0004] Based on this, it is necessary to provide a method, device, computer equipment and readable storage medium for simulation and manufacturing to improve the simulation effect of production line simulation in response to the above technical problems.

[0005] In a first aspect, the present application provides a scenario simulation method, the method comprising:

[0006] Obtain multiple sub-simulation tasks under the total simulation task registered for the production line to be simulated;

[0007] Acquire a plurality of first scheduled processing times corresponding to the plurality of sub-simulation tasks, and respectively convert the plurality of first scheduled processing times to the simulation timeline corresponding to the production line to be simulated, to obtain a plurality of second scheduled processing times;

[0008] According to the plurality of second scheduled processing times, the plurality of sub-simulation tasks are sorted by execution time to obtain a time sorting result;

[0009] Generating production line simulation data on the simulation timeline according to the time sorting result;

[0010] The production line to be simulated is simulated on the simulation timeline according to the production line simulation data.

[0011] In one embodiment, the step of obtaining a plurality of sub-simulation tasks under a total simulation task registered for the production line to be simulated includes:

[0012] Extracting data simulation parameters of the production line to be simulated from the overall simulation task;

[0013] The total simulation task is divided according to the data simulation parameters to obtain the multiple sub-simulation tasks.

[0014] In one embodiment, the data simulation parameter includes a total amount of data simulation; the total simulation task is divided according to the data simulation parameter to obtain the plurality of sub-simulation tasks, including:

[0015] According to the total amount of data simulation, generating the total amount of data simulation tasks for the production line to be simulated;

[0016] Performing simulation distribution on the total amount of data simulation to obtain data simulation amounts of multiple simulation tasks to be executed under the total amount of data simulation tasks;

[0017] Matching a corresponding simulation execution time point for each of the plurality of simulation tasks to be executed;

[0018] According to a plurality of data simulation quantities and a plurality of simulation execution time points, the plurality of simulation tasks to be executed are converted into the plurality of sub-simulation tasks.

[0019] In one embodiment, the converting the plurality of first scheduled processing times to the simulation timeline corresponding to the production line to be simulated to obtain a plurality of second scheduled processing times comprises:

[0020] Respectively obtain the first time speeds corresponding to the plurality of first scheduled processing times and the second time speed corresponding to the simulation timeline;

[0021] According to the time speed ratio between the plurality of first time speeds and the second time speed, the plurality of first regular processing times are respectively converted to the simulation time line corresponding to the production line to be simulated to obtain a plurality of second regular processing times.

[0022] In one embodiment, the step of performing execution time sorting on the plurality of sub-simulation tasks according to the plurality of second scheduled processing times to obtain a time sorting result includes:

[0023] Determine a first production line instance to which each of the plurality of sub-simulation tasks belongs;

[0024] generating a first execution timing between a plurality of first production line instances and a second execution timing between the plurality of sub-simulation tasks according to the plurality of second scheduled processing times;

[0025] The execution time of the plurality of sub-simulation tasks is sorted according to the first execution timing and the second execution timing to obtain the time sorting result.

[0026] In one embodiment, simulating the production line to be simulated on the simulation timeline according to the production line simulation data includes:

[0027] Determine a second production line instance to which the plurality of sub-simulation tasks commonly belong;

[0028] According to the identification information of the second production line instance, the plurality of sub-simulation tasks are matched with corresponding simulation service nodes respectively, wherein the simulation service nodes are used to simulate the production line simulation data;

[0029] The production line to be simulated is simulated on the simulation timeline according to a plurality of simulation service nodes and the production line simulation data.

[0030] In one embodiment, the method further comprises:

[0031] In the process of simulating the production line to be simulated, for any of the sub-simulation tasks, determining the third production line instance to which the sub-simulation task belongs;

[0032] In response to the adjustment operation triggered for the sub-simulation task, the default time speed of the sub-simulation task is adjusted, wherein the default time speed is used to characterize a preset time flow rate relationship between the simulation scene and the real scene.

[0033] In a second aspect, the present application also provides a production line simulation device, the device comprising:

[0034] An acquisition module, used for acquiring a plurality of sub-simulation tasks under a total simulation task registered for the production line to be simulated;

[0035] A conversion module, used for obtaining a plurality of first scheduled processing times corresponding to the plurality of sub-simulation tasks, and respectively converting the plurality of first scheduled processing times to the simulation timeline corresponding to the production line to be simulated, to obtain a plurality of second scheduled processing times;

[0036] A sorting module, used for sorting the execution time of the plurality of sub-simulation tasks according to the plurality of second scheduled processing times to obtain a time sorting result;

[0037] A generating module, used for generating production line simulation data on the simulation timeline according to the time sorting result;

[0038] The simulation module is used to simulate the production line to be simulated on the simulation timeline according to the production line simulation data.

[0039] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0040] Acquire multiple sub-simulation tasks under the total simulation task registered for the production line to be simulated; acquire multiple first scheduled processing times corresponding to the multiple sub-simulation tasks, and respectively convert the multiple first scheduled processing times to the simulation timeline corresponding to the production line to be simulated to obtain multiple second scheduled processing times; sort the execution time of the multiple sub-simulation tasks according to the multiple second scheduled processing times to obtain a time sorting result; generate production line simulation data on the simulation timeline according to the time sorting result; simulate the production line to be simulated on the simulation timeline according to the production line simulation data.

[0041] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0042] Acquire multiple sub-simulation tasks under the total simulation task registered for the production line to be simulated; acquire multiple first scheduled processing times corresponding to the multiple sub-simulation tasks, and respectively convert the multiple first scheduled processing times to the simulation timeline corresponding to the production line to be simulated to obtain multiple second scheduled processing times; sort the execution time of the multiple sub-simulation tasks according to the multiple second scheduled processing times to obtain a time sorting result; generate production line simulation data on the simulation timeline according to the time sorting result; simulate the production line to be simulated on the simulation timeline according to the production line simulation data.

[0043] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0044] Acquire multiple sub-simulation tasks under the total simulation task registered for the production line to be simulated; acquire multiple first scheduled processing times corresponding to the multiple sub-simulation tasks, and respectively convert the multiple first scheduled processing times to the simulation timeline corresponding to the production line to be simulated to obtain multiple second scheduled processing times; sort the execution time of the multiple sub-simulation tasks according to the multiple second scheduled processing times to obtain a time sorting result; generate production line simulation data on the simulation timeline according to the time sorting result; simulate the production line to be simulated on the simulation timeline according to the production line simulation data.

[0045] The above-mentioned method, device, computer equipment and readable storage medium for simulating and emulating production manufacturing first obtain multiple sub-simulation tasks under the total simulation task registered for the production line to be simulated, and then obtain multiple first scheduled processing times corresponding to the multiple sub-simulation tasks, and respectively convert the multiple first scheduled processing times to the simulation timeline corresponding to the production line to be simulated, and obtain multiple second scheduled processing times, thereby achieving the purpose of unifying the multiple sub-simulation tasks to the simulation timeline corresponding to the production line to be simulated, and obtaining the second scheduled processing times corresponding to different sub-simulation tasks on the simulation timeline, and then sorting the execution time of the multiple sub-simulation tasks according to the multiple second scheduled processing times to obtain the time sorting result, that is, with the help of timeline engine technology, time sorting is performed on the multiple sub-simulation tasks corresponding to the production line to be simulated, thereby realizing the simulation and simulation of the production line to be simulated, and obtaining the time sorting results of the multiple sub-simulation tasks on the production line to be simulated, and then generating the production line simulation data on the simulation timeline according to the time sorting results. That is, on the basis of the timeline engine, a data engine is added to generate production line simulation data corresponding to each sub-simulation task, and finally the production line to be simulated is simulated on the simulation timeline based on the production line simulation data. Since the simulation execution timeline is a timeline simulated relative to the real physical timeline, the user can flexibly control the timing processing time of multiple sub-simulation tasks on the simulation timeline, so that the production line to be simulated meets the simulation time requirements of the production line, and can generate corresponding production line simulation data based on multiple sub-simulation tasks, so as to meet the diversified needs of production line simulation data under the production line to be simulated, thereby achieving the purpose of providing a flexible and realistic simulation production line. Therefore, the limitations of the simulation time of the production line are overcome, and the production line simulation data under the timing task framework is relatively single, resulting in the final simulated production line cannot match the user's actual production line simulation needs, which makes it easy to have technical defects such as insufficient interactivity and lack of reality. Therefore, the simulation effect of the production line simulation is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0047] Figure 1 A schematic diagram of a process flow of a production line simulation method in one embodiment;

[0048] Figure 2 A schematic diagram of a flow chart of a production line simulation method in another embodiment;

[0049] Figure 3 It is an implementation architecture diagram of a production line simulation of a production line simulation method in another embodiment;

[0050] Figure 4 is a structural block diagram of a production line simulation device in one embodiment;

[0051] Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0053] First of all, it should be understood that with the development of simulation technology, all walks of life have achieved personalized application needs by simulating business scenarios, such as traffic safety education, industrial production training, fire escape drills, and medical emergency response. Taking industrial production training as an example, in the field of higher vocational school education, schools will offer practical training courses, which can demonstrate and promote production activities. Generally, students are required to play various roles in production to achieve the integration of practice and theory. In this process, it is necessary to conduct an overall evaluation of the students' understanding of production, so as to understand the students' mastery of knowledge points. In the existing industrial production training, there are at least three defects in the simulation of actual production lines: 1) Lack of interactivity: At this stage, online courses cannot simulate real production lines due to the lack of sufficient interactivity. Teamwork and communication in a production environment; 2) Lack of sense of reality: At this stage, it is impossible to simulate the concept of the flow rate of time in real production, and the corresponding production can only be completed by the teacher's operation of the nodes, so the students' immersion experience cannot be enhanced; 3) Lack of integration of industry and education: At this stage, schools are unable to simulate the real production scenarios of enterprises, which is not conducive to students mapping theoretical knowledge to real scenarios. From the above, it can be seen that in the current production line simulation process, simulation based on a timed task framework will be due to its limitations in simulation time and the singleness of the simulated production line simulation data, resulting in the final simulated production line unable to match the user's actual production line simulation needs, which makes it easy to appear as shown in the above example. Problems such as lack of interactivity and lack of sense of reality, so there is an urgent need for a production line simulation method to improve the simulation effect of production line simulation.

[0054] In one embodiment, Figure 1As shown, a production line simulation method is provided. This embodiment takes the method applied to a terminal as an example. The terminal includes but is not limited to a personal computer, a laptop computer, a smart phone, and a tablet computer. The terminal includes an acquisition module, a conversion module, a sorting module, a generation module, and a simulation module. The acquisition module is used to acquire multiple sub-simulation tasks under the total simulation task registered for the production line to be simulated. The conversion module is used to acquire multiple first timed processing times corresponding to the multiple sub-simulation tasks, and respectively convert the multiple first timed processing times to the simulation timeline corresponding to the production line to be simulated to obtain multiple second timed processing times. The sorting module is used to sort the execution time of the multiple sub-simulation tasks according to the multiple second timed processing times to obtain a time sorting result. The generation module is used to generate production line simulation data on the simulation timeline according to the time sorting result. The simulation module is used to simulate the production line to be simulated on the simulation timeline according to the production line simulation data. This embodiment uses the acquisition module, the conversion module, the sorting module, the generation module, the generation module, and the simulation module. The information interaction between the module, the sorting module, the generation module and the simulation module, in the process of simulating the production line, first obtains a plurality of sub-simulation tasks set for the production line to be simulated, and then uniformly converts the plurality of first timing processing times corresponding to the plurality of sub-simulation tasks to the plurality of second timing processing times on the simulation timeline corresponding to the production line to be simulated, and then sorts the execution time of the plurality of sub-simulation tasks through the plurality of second timing processing times to obtain the time sorting result, and generates the production line simulation data on the simulation timeline based on the time sorting result, and finally simulates the production line to be simulated on the simulation timeline according to the production line simulation data, so as to achieve the purpose of providing a flexible and realistic simulation production line, rather than relying on the timing task framework for production line simulation, so as to improve the simulation effect of the production line simulation, it can be understood that the method can also be applied to the server, and can also be applied to the system including the terminal and the server, and is realized through the interaction between the terminal and the server. In this embodiment, the method includes the following steps 202 to 210. Among them:

[0055] Step 202, obtaining a plurality of sub-simulation tasks under the total simulation task registered for the production line to be simulated.

[0056] It should be noted that the production line to be simulated refers to the production line waiting to be simulated or emulated, the total simulation task refers to the overall simulation task deployed for the production line to be simulated, and the sub-simulation task refers to the local simulation task divided by the total simulation task. For example, a practical training course can be understood as a total simulation task deployed for the production line that needs to be simulated or emulated. A practical training course includes sub-simulation tasks such as order submission, order analysis, procurement, production preparation, work order scheduling, dispatching, warehousing, production, quality inspection, reporting, product warehousing, delivery, logistics and receipt. It can be understood that there is a sequence of execution time between the multiple sub-simulation tasks under the total simulation task, and the timelines that different sub-simulation tasks depend on can be the same or different. Different sub-simulation tasks can be deployed on the same terminal or on different terminals for execution.

[0057] It should be noted that the production line simulation method can be executed in a production line simulation system, and the production line simulation system can specifically be a training system. For example, in one feasible method, a total simulation task is registered in the training system, and the total simulation task is associated with multiple sub-simulation tasks through a task identifier. Therefore, in the process of simulating the production line to be simulated, multiple sub-simulation tasks under the total simulation task registered for the production line to be simulated can be obtained through the task identifier.

[0058] As an example, step 202 includes: obtaining a total simulation task registered for the production line to be simulated, and querying and obtaining a plurality of sub-simulation tasks under the total simulation task according to a task identifier of the total simulation task.

[0059] Step 204, obtaining a plurality of first scheduled processing times corresponding to a plurality of sub-simulation tasks, and converting the plurality of first scheduled processing times to the simulation timeline corresponding to the production line to be simulated, to obtain a plurality of second scheduled processing times.

[0060] It should be noted that different sub-simulation tasks have different simulation execution times, that is, each sub-simulation task has a corresponding first timing processing time. It can be understood that the existing timing task technology framework is scheduled based on the real physical world time, that is, the first timing processing time is the timing processing time set based on the physical timeline. If multiple sub-simulation tasks all rely on the corresponding first timing processing time for processing, it is easy to be difficult to adapt to the same task and the same trigger cycle, resulting in different real trigger times under different time flow rate configurations. Therefore, in the process of simulating the production line, it is necessary to uniformly convert multiple first timing processing times to the simulation timeline corresponding to the production line to be simulated, so as to obtain multiple second timing processing times, wherein the second timing processing time is the timing processing time set based on the simulation timeline. After the first timing processing times corresponding to different sub-simulation tasks are converted to the corresponding second timing processing times, the simulation timeline corresponding to the production line to be simulated can be used as a benchmark to realize the execution of the total simulation task of the production line to be simulated. For example, in a cocoa-implementable method, assuming that the first timing processing time is 9:00-11:00, the second timing processing time can be 1min30s-3min30s.

[0061] As an example, step 204 includes: extracting the scheduled processing times pre-set for each of the multiple sub-simulation tasks to obtain multiple first scheduled processing times, and converting the multiple first scheduled processing times to the simulation timeline according to the correspondence between the simulation timeline and the actual timeline corresponding to the production line to be simulated to obtain multiple second scheduled processing times.

[0062] Step 206, sorting the execution time of the plurality of sub-simulation tasks according to the plurality of second scheduled processing times to obtain a time sorting result.

[0063] It should be noted that in the process of simulating the production line to be simulated, after obtaining the second scheduled processing time corresponding to different sub-simulation tasks, it is necessary to sort the execution time of multiple sub-simulation tasks according to the order of time execution, so as to facilitate the time management of the production line simulation system. It can be understood that the execution time sorting of multiple sub-simulation tasks can be implemented based on the timeline engine technology, and different sub-simulation tasks can realize the start, pause and fast forward functions based on the obtained simulation execution timeline.

[0064] As an example, step 206 includes: extracting the processing start time points of multiple second scheduled processing times, sorting the multiple processing start time points in chronological order, sorting the execution time of multiple sub-simulation tasks, and obtaining a time sorting result. For example, assuming that the multiple sub-simulation tasks are sub-simulation task A, sub-simulation task B and sub-simulation task C, the time sorting result may be executing sub-simulation task B at the first second processing time, executing sub-simulation task C at the second second processing time, and executing sub-simulation task A at the third second processing time.

[0065] Step 208: Generate production line simulation data on the simulation timeline according to the time sorting result.

[0066] It should be noted that in order to improve the flexibility of production line simulation, the production line simulation system can generate production line simulation data for different sub-simulation tasks based on the time sorting results obtained by sorting, that is, on the basis of the simulation execution timeline, a new data engine is added to allow support for random generation of production line simulation data based on the timeline engine. It can be understood that the production line simulation data corresponding to different sub-simulation tasks may be the same or different. For example, in one feasible method, assuming that the production line simulation system is a training system, the generated production line simulation data may specifically include abnormal data (orders, purchase orders, and equipment, etc.) generated by the training system according to the scheduled task rules, business data generated by the training system when processing various business scenarios (such as creating orders, order review, and equipment exception handling, etc.), various business data randomly generated by the data engine, and various emergencies in simulation of real-life processes, as well as data randomly triggered by scheduled task rules or a random number of data, wherein the production line simulation data is used to simulate the production line to be simulated.

[0067] As an example, step 208 includes: randomly generating production line simulation data corresponding to each of the plurality of sub-simulation tasks according to the simulation execution timeline.

[0068] Step 210, simulating the production line to be simulated according to the production line simulation data.

[0069] As an example, step 210 includes: simulating the production line to be simulated by using production line simulation data.

[0070] In the above production line simulation method, firstly, a plurality of sub-simulation tasks under the total simulation task registered for the production line to be simulated are obtained, and then a plurality of first scheduled processing times corresponding to the plurality of sub-simulation tasks are obtained, and the plurality of first scheduled processing times are respectively converted to the simulation timeline corresponding to the production line to be simulated, and a plurality of second scheduled processing times are obtained, so as to unify the plurality of sub-simulation tasks to the simulation timeline corresponding to the production line to be simulated, and obtain the second scheduled processing times corresponding to different sub-simulation tasks on the simulation timeline, and then, according to the plurality of second scheduled processing times, the execution time of the plurality of sub-simulation tasks is sorted to obtain the time sorting result, that is, with the help of the timeline engine technology, the plurality of sub-simulation tasks corresponding to the production line to be simulated are sorted in time, so as to realize the simulation and simulation of the production line to be simulated, and obtain the time sorting result of the plurality of sub-simulation tasks on the production line to be simulated, and then, according to the time sorting result, the production line simulation data on the simulation timeline is generated, that is, in the timeline engine. On this basis, a data engine is added to generate production line simulation data corresponding to each sub-simulation task, and finally the production line to be simulated is simulated on the simulation timeline based on the production line simulation data. Since the simulation execution timeline is a timeline simulated relative to the real physical timeline, the user can flexibly control the timing processing time of multiple sub-simulation tasks on the simulation timeline, so that the production line to be simulated meets the simulation time requirements of the production line, and can generate corresponding production line simulation data based on multiple sub-simulation tasks, so as to meet the diversified needs of production line simulation data under the production line to be simulated, thereby achieving the purpose of providing a flexible and realistic simulation production line. Therefore, the limitations of the simulation time of the production line and the relatively single production line simulation data under the timing task framework are overcome, resulting in the final simulated production line being unable to match the user's actual production line simulation needs, which in turn makes it easy to have technical defects such as insufficient interactivity and insufficient sense of reality. Therefore, the simulation effect of the production line simulation is improved.

[0071] In one embodiment, Figure 2 As shown, multiple sub-simulation tasks under the total simulation task registered for the production line to be simulated are obtained, including:

[0072] Step 302: extracting data simulation parameters of the production line to be simulated from the overall simulation task.

[0073] It should be noted that in the process of real-time simulation of the simulated production line, multiple sub-simulation tasks under the overall simulation task can be obtained based on demand, wherein the overall simulation task carries data simulation parameters, and the data simulation parameters are used to characterize the demand for simulation data of the production line generated. For example, in one feasible method, assuming that the overall simulation task is based on the scheduled task rule generation task under the data engine, specifically "randomly generate 10 orders every hour, and the number of triggers and the number of orders generated each time are random", the key fields can be extracted from the overall simulation task to obtain the data simulation parameters of the production line to be simulated.

[0074] As an example, step 302 includes: extracting key fields from the overall simulation task to obtain data simulation parameters of the production line to be simulated.

[0075] Step 304, dividing the total simulation task according to the data simulation parameters to obtain a plurality of sub-simulation tasks.

[0076] It should be noted that after obtaining the data simulation parameters, the total task can be divided based on the data simulation parameters. For example, in an implementable method, assuming that the data simulation parameters are "generate a total of 10 orders", "trigger 3 times" and "generate a random number of orders each time", the obtained sub-simulation tasks can be sub-simulation task a "trigger the generation of 1 data at simulation execution time point 1", sub-simulation task b "trigger the generation of 4 data at simulation execution time point 2" and sub-simulation task c "trigger the generation of 5 data at simulation execution time point 3", among which the order of simulation execution time point 1, simulation execution time point 2 and simulation execution time point 3 is not specifically limited.

[0077] As an example, step 304 includes: generating a task division rule according to the data simulation parameters, and dividing the total simulation task according to the task division rule to obtain a plurality of sub-simulation tasks.

[0078] In this embodiment, by extracting the data simulation parameters of the production line to be simulated in the total simulation task, and then dividing the total simulation task into multiple sub-simulation tasks based on the data simulation parameters, a reference basis can be provided for the division of the total simulation task registered for the production line to be simulated, that is, to ensure that the production line to be simulated can meet the actual simulation needs of the user when it is realized by executing multiple sub-simulation tasks, thus laying a foundation for improving the simulation effect of the production line simulation.

[0079] In one embodiment, the data simulation parameters include the total amount of data simulation; according to the data simulation parameters, the total simulation task is divided to obtain a plurality of sub-simulation tasks, including:

[0080] According to the total amount of data simulation, the total amount of data simulation tasks for the production line to be simulated is generated; the total amount of data simulation is simulated and distributed to obtain the data simulation amount of multiple simulation tasks to be executed under the total amount of data simulation tasks; the corresponding simulation execution time points are matched for each of the multiple simulation tasks to be executed; according to the multiple data simulation amounts and the multiple simulation execution time points, the multiple simulation tasks to be executed are converted into multiple sub-simulation tasks.

[0081] It should be noted that the total amount of data simulation refers to the total amount of data of the production line simulation data obtained by simulation, which can be 10, 20 or 30 items, etc. The total amount of data simulation tasks is used to characterize the number of sub-simulation tasks divided by the total simulation task, which can be 2, 3 or 4 items, etc. Simulation allocation refers to the allocation of corresponding data simulation quantities to different sub-simulation tasks, which can be specifically allocated in a random simulation manner or in accordance with preset allocation rules, wherein the data simulation quantities correspond one-to-one to the simulation tasks to be executed, which can be 5, 10 or 15 items, etc. It can be understood that any data simulation quantity is less than the total amount of data simulation, and the sum of the data simulation quantities of different simulation tasks to be executed is the total amount of data simulation.

[0082] It should be noted that the simulation tasks to be executed are used for sub-simulation tasks that have not set the simulation data volume and have not been executed. The simulation execution time point can be 08:15, 08:22, 08:45 or 08.55, etc. For example, in one feasible method, assuming that the total number of data simulation tasks is 4, there are 4 simulation tasks to be executed, among which, none of the 4 simulation tasks to be executed are allocated with data simulation volume, and the corresponding data simulation volume needs to be obtained through simulation allocation, wherein the data simulation volume and the simulation execution time point correspond one to one. After the simulation task to be executed has the simulation execution time point and the data simulation volume, the simulation task to be executed can be converted into a sub-simulation task. For example, the task to be simulated is expressed as "triggering the generation of order data", and the sub-simulation task is "triggering the generation of 5 order data at 08:22".

[0083] As an example, the total amount of data simulation tasks for the production line to be simulated is randomly generated within a random interval of the total amount constructed by the data simulation total amount; multiple simulation tasks to be executed are simulated based on the total amount of data simulation tasks, and the corresponding data simulation amounts are simulated for the multiple simulation tasks to be executed under the total amount of data simulation; the benchmark time point for simulating the production line to be simulated is obtained, and corresponding simulation execution time points are randomly generated for the multiple simulation tasks to be executed according to the benchmark time point; corresponding data simulation amounts and simulation execution time points are respectively set for the multiple simulation tasks to be executed to obtain multiple sub-simulation tasks.

[0084] In an implementable manner, assuming that the scheduled task rule is: 10 orders are randomly generated every hour, and the number of triggers and the number of orders generated each time are random, then the above-mentioned process of dividing the total simulation task based on the rule algorithm to obtain multiple sub-simulation tasks is as follows: 1) Calculate the random triggering number (the total number of data simulation tasks), and randomly generate a number between 1 and 10 as the random triggering number according to the total number of data simulation (10); 2) Calculate the amount of data for each trigger according to the total number of data simulation (10), that is, determine the data simulation amount of each simulation task to be executed; 3) Generate an array of length 3, and initialize each element in the array to 1, that is, initialize and set multiple simulation tasks to be executed; 4) Take the number of remaining elements 7 (the difference between the total number of data simulation and the total number of data simulation tasks), and determine whether the number of remaining elements is greater than 0; 5) Randomly take the array index (0~3), and randomly generate the number of elements (0~ 7) and add it to the corresponding array element; 6) loop step 4) and step 5); 7) finally generate an array with a triggering number of 3 and a total of 10 elements, for example [1,7,2], where the number of elements in the array represents the total amount of data simulation tasks, that is, randomly trigger three simulation tasks to be executed, and the numbers in the array represent the amount of trigger data (data simulation amount) corresponding to each simulation task to be executed, which is 1,7,2; 8) take the current time as the benchmark, for example: 08:00, every hour with an interval of 60 minutes, traverse the array, generate random numbers between 0 and 60, add them to the benchmark time point respectively, and get the random trigger time, for example "08:15, 08:22, 08:55"; 9) generate a unique batch ID, combined with the amount of triggered data, then generate 3 sub-simulation tasks under this batch, namely "08:15 triggers 1 data, 08:22 triggers 7 data, 08:55 triggers 2 data".

[0085] In this embodiment, in the process of dividing the total simulation task into multiple sub-simulation tasks based on data simulation parameters, the total data simulation task amount of the production line to be simulated is first generated through the total data simulation amount, and then the total data simulation amount is simulated and allocated to obtain the data simulation amount of multiple simulation tasks to be executed under the total data simulation task amount, and the corresponding simulation execution time points are matched for each of the multiple simulation tasks to be executed, and finally, the multiple simulation tasks to be executed are converted into multiple sub-simulation tasks through multiple data simulation amounts and multiple simulation execution time points, that is, with the help of the total data simulation amount, in the process of dividing the sub-simulation tasks, the data simulation amount and simulation execution time points of the sub-simulation tasks are flexibly set, thereby laying a foundation for the subsequent setting of the simulation execution timeline of the production line to be simulated and generating production line simulation data that meets the actual simulation needs of the user, and therefore, laying a foundation for improving the simulation effect of the production line simulation.

[0086] It is understandable that, through the above embodiments, the limitation of tasks in the time dimension can be broken, and thus all sub-simulation tasks do not need to be executed with reference to the same time system, for example, they do not need to be executed according to the standard of once an hour.

[0087] In one embodiment, the plurality of first scheduled processing times are converted to the simulation timeline corresponding to the production line to be simulated to obtain the plurality of second scheduled processing times, including:

[0088] Respectively obtain the first time speeds corresponding to multiple first scheduled processing times and the second time speeds corresponding to the simulation timeline; according to the time speed ratio between the multiple first time speeds and the second time speeds, respectively convert the multiple first scheduled processing times to the simulation timeline corresponding to the production line to be simulated to obtain multiple second scheduled processing times.

[0089] It should be noted that the timeline management can set the time speed for executing the sub-simulation task, wherein the time speed may specifically include 1, 2, 4, 6, 8, 16 and 60, etc. The time speed is used to characterize the time flow rate relationship between the simulation scene and the real scene. For example, 1:1 means that the training time is synchronized with the real time; 1:2 means that 1 second of real time corresponds to 2 seconds of training time. It can be understood that when the timeline corresponding to the sub-simulation task is different from the simulation timeline set for the production line to be simulated, the correlation relationship between the time speeds of different timelines can be determined first in the process of converting the timing processing time, that is, the time speed ratio of the first time speed corresponding to multiple first timing processing times and the second time speed corresponding to the simulation timeline is determined, so as to further map the timing processing time. For example, in an implementable manner, assuming that the first time speed is 1:2, the second time speed is 1:16, and the third time speed is 1:4, the obtained time speed ratios are 2:1 and 4:1 respectively, and then when performing different first timing processing time conversions, they are performed based on different time multiple ratios.

[0090] As an example: obtain the first time speeds corresponding to multiple first scheduled processing times, and obtain the second time speeds corresponding to the simulation timeline; divide the multiple first time speeds by the second time speeds to obtain multiple speed ratios, and based on the multiple speed ratios, convert the multiple first scheduled processing times to the simulation timeline corresponding to the production line to be simulated to obtain multiple second scheduled processing times.

[0091] In the process of converting the first scheduled processing time corresponding to the sub-simulation task into the second scheduled processing time, this embodiment first obtains the first time speed corresponding to the first scheduled processing time and the second time speed corresponding to the simulation timeline respectively, and then determines the time speed relationship between different sub-simulation tasks and the production line to be simulated based on the first time speed and the second time speed, that is, determines the time speed ratio between multiple first time speeds and second time speeds, and finally converts multiple first scheduled processing times into the second scheduled processing time on the simulation timeline through different time speed ratios, thereby avoiding the defect that the scheduled processing time simulated for the sub-simulation task cannot be applied to the overall total simulation task due to the difference in the time speed settings, and thus lays a foundation for improving the simulation effect of simulating the production line.

[0092] In one embodiment, the execution time of the plurality of sub-simulation tasks is sorted according to the plurality of second timing processing times to obtain a time sorting result, including:

[0093] Determine the first production line instance to which each of the multiple sub-simulation tasks belongs; generate a first execution sequence between the multiple first production line instances and a second execution sequence between the multiple sub-simulation tasks based on the multiple second scheduled processing times; sort the execution time of the multiple sub-simulation tasks based on the first execution sequence and the second execution sequence to obtain a time sorting result.

[0094] It should be noted that in the production line simulation system, a large number of production line instances can be created. Among them, for the creation of production line instances (environments), a production line instance with a unique identifier can be automatically generated through preset parameters or configuration information entered by the user. Each production line instance includes information such as instance name, description and type, and is automatically associated with the corresponding timeline setting software to automatically set a default timeline for each newly created production line instance. The setting ensures that all business scenario examples have a consistent time reference point, providing a benchmark for subsequent timeline management. Different production line instances have their own timelines, and sub-simulation tasks can be registered under any production line instance. When multiple sub-simulation tasks under the total simulation task of the production line to be simulated belong to different production line instances, the actual execution frequencies of different sub-simulation tasks are completely different. Therefore, when simulating the simulation execution timeline of the production line to be simulated, it is necessary to first classify the sub-simulation tasks according to the environment, and then sort the multiple sub-simulation tasks according to the execution time.

[0095] It should be noted that, for different sub-simulation tasks, they may belong to the same production line instance or may be in different production line instances. When the production line instances to which different sub-simulation tasks belong are the same, the first execution timing between different sub-simulation tasks between production line instances can be determined through the second timing processing time. When the production line instances to which different sub-simulation tasks belong are the same, the second execution timing between different sub-simulation tasks within the production line instance can be determined through the second timing processing time. This allows the execution time of multiple sub-simulation tasks to be sorted based on the execution timing relationship within the production line instance and between production line instances.

[0096] As an example, based on the task identifiers of multiple sub-simulation tasks, the first production line instances to which the multiple sub-simulation tasks respectively belong are queried; based on the multiple second scheduled processing times, the first execution sequence between the multiple first production line instances and the second execution sequence between the multiple sub-simulation tasks are generated; the execution time of the multiple sub-simulation tasks is sorted by the first execution sequence and the second execution sequence to obtain a time sorting result, wherein the first execution sequence is used to characterize the execution sequence between the first production line instances, and the second execution sequence is used to characterize the execution sequence between different production line instances.

[0097] In the process of simulating the production line to be simulated, if multiple sub-simulation tasks involve multiple production line instances, the first execution sequence in the same production line instance and the second execution sequence between different production line instances in different sub-simulation tasks can be determined respectively, and then the execution time of multiple sub-simulation tasks can be sorted by combining the first execution sequence and the second execution sequence as a benchmark to obtain the time sorting result, thereby laying a foundation for improving the simulation effect of business simulation.

[0098] In one embodiment, simulating a production line to be simulated on a simulation timeline according to production line simulation data includes:

[0099] Determine the second production line instance to which multiple sub-simulation tasks belong together; match corresponding simulation service nodes for multiple sub-simulation tasks respectively according to the identification information of the second production line instance, wherein the simulation service node is used to simulate the production line simulation data; simulate the production line to be simulated on the simulation timeline according to the multiple simulation service nodes and the production line simulation data.

[0100] It should be noted that the data engine can trigger the generation of data according to dynamic time. At the same time, in order to support a large amount of business data, the data diversification engine has added distributed support, which can disperse different data diversification to different service nodes. That is, since the scanning and execution of a large number of scheduled tasks have high performance requirements for the data diversification engine, distributed support has been added. For the production line simulation scheme completed by multiple sub-simulation tasks under the same production line instance, since the time flow rate under the same production line instance is consistent, the simulation service nodes corresponding to different sub-simulation tasks can be determined through the identification information of the production line instance. Among them, the simulation service node refers to the specific terminal that executes the sub-simulation task. It can be understood that after applying distributed support, the amount of tasks to be scanned and executed by a single service node can be reduced, thereby improving performance.

[0101] As an example, a second production line instance commonly identified by multiple sub-simulation tasks is obtained, and the identification information of the second production line instance is used as an index to query corresponding simulation service nodes for multiple sub-simulation tasks respectively, wherein the simulation service node is used to simulate the production line simulation data; the production line to be simulated is simulated through multiple simulation service nodes and production line simulation data.

[0102] This embodiment first determines the second production line instance to which multiple sub-simulation tasks belong, and then matches corresponding simulation service nodes for multiple sub-simulation tasks according to the identification information of the second production line instance. Finally, the production line to be simulated is simulated through multiple simulation service nodes and production line simulation data. That is, in the process of distributed simulation of the production line to be simulated, the simulation of all production line simulation data is completed through multiple simulation service nodes, thereby improving the simulation effect of the production line simulation.

[0103] In one embodiment, the method further comprises:

[0104] In the process of simulating the production line to be simulated, for any sub-simulation task, the third production line instance to which the sub-simulation task belongs is determined; in response to the adjustment operation triggered for the sub-simulation task, the default time speed of the sub-simulation task is adjusted, wherein the default time speed is used to characterize a pre-set time flow rate relationship between the simulation scene and the real scene.

[0105] It should be noted that the timeline management can set the default time speed, which includes 1, 2, 4, 6, 8, 16 and 60. The default time speed is used to characterize the preset time flow rate relationship between the simulation scene and the real scene. For example, 1:1 means that the training time is synchronized with the real time; 1:2 means that 1 second of real time corresponds to 2 seconds of training time; and so on. By adjusting the time ratio, the software can simulate production processes or production tasks at different speeds, effectively utilize the simulation time, and improve the simulation authenticity of the production line simulation.

[0106] As an example, in the process of simulating the production line to be simulated, for any sub-simulation task, the third production line instance to which the sub-simulation task belongs is determined; in response to the execution time adjustment operation triggered for the sub-simulation task, the default time speed of the sub-simulation task is adjusted, wherein the default time speed is used to characterize a pre-set time flow rate relationship between the simulation scene and the real scene.

[0107] In one feasible method, assuming that the production line simulation system is a training system, during the training process, the training system can also automatically detect the occurrence of events and control the pause and resume of the timeline. For example, when an order generation event is triggered, the software automatically pauses the timeline and sends a processing prompt to the corresponding system module. The software simulates processes such as order push, procurement actions, and supplier delivery; it can also handle other events that occur during the procurement cycle and automatically adjust the fast forward of the timeline until the event is processed.

[0108] In one practicable manner, referring to Figure 3 , Figure 3 This is the implementation architecture diagram of the production line simulation. First, the business system (production line simulation system) registers the total simulation task for the production line to be simulated, and then generates batch tasks to be executed according to the task rules, that is, multiple sub-simulation tasks under the total simulation task are obtained. Then, the batch tasks to be executed are scanned by the data diversification engine, and the simulation execution timeline of the production line to be simulated given by the time engine is combined to determine whether to trigger. After the trigger task is executed, a signal is sent to the business system. The business system receives the signal and determines the data type of the production line simulation data based on the signal, which can be purchasing materials, creating orders, equipment alarms, order review and other business operations. Finally, the production line to be simulated is simulated through the production line simulation data.

[0109] Since the simulation execution timeline of the above-mentioned production line simulation method is a timeline simulated relative to the real physical timeline, the user can flexibly control the timing processing time of multiple sub-simulation tasks on the simulation timeline, so that the production line to be simulated meets the simulation time requirements of the production line, and can generate corresponding production line simulation data based on multiple sub-simulation tasks, thereby meeting the diversified needs for production line simulation data under the production line to be simulated, thereby achieving the purpose of providing a flexible and realistic simulation production line. Therefore, it overcomes the limitations of the simulation time of the production line and the relatively single production line simulation data under the timing task framework, resulting in the final simulated production line being unable to match the user's actual production line simulation needs, which in turn makes it easy to have technical defects such as insufficient interactivity and lack of reality. Therefore, the simulation effect of the production line simulation is improved.

[0110] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0111] Based on the same inventive concept, the embodiment of the present application also provides a production line simulation device for implementing the production line simulation method involved above. The implementation solution provided by the device to solve the problem is similar to the implementation solution recorded in the above method, so the specific limitations in one or more production line simulation device embodiments provided below can refer to the limitations of the production line simulation method above, and will not be repeated here.

[0112] In an exemplary embodiment, Figure 4 As shown, it is applied to a production line simulation device, the device includes: an acquisition module 401, a conversion module 402, a sorting module 403, a generation module 404 and a simulation module 405, wherein:

[0113] An acquisition module 401 is used to acquire a plurality of sub-simulation tasks under a total simulation task registered for a production line to be simulated;

[0114] The conversion module 402 is used to obtain a plurality of first scheduled processing times corresponding to the plurality of sub-simulation tasks, and respectively convert the plurality of first scheduled processing times to the simulation timeline corresponding to the production line to be simulated, to obtain a plurality of second scheduled processing times;

[0115] A sorting module 403 is used to sort the execution time of the plurality of sub-simulation tasks according to the plurality of second scheduled processing times to obtain a time sorting result;

[0116] A generating module 404, configured to generate production line simulation data on the simulation timeline according to the time sorting result;

[0117] The simulation module 405 is used to simulate the production line to be simulated on the simulation timeline according to the production line simulation data.

[0118] In one embodiment, the acquisition module 401 is further used for:

[0119] The data simulation parameters of the production line to be simulated are extracted from the overall simulation task; and the overall simulation task is divided according to the data simulation parameters to obtain the multiple sub-simulation tasks.

[0120] In one embodiment, the acquisition module 401 is further used for:

[0121] According to the total amount of data simulation, generate the total amount of data simulation tasks for the production line to be simulated; perform simulation allocation on the total amount of data simulation to obtain the data simulation amount of multiple simulation tasks to be executed under the total amount of data simulation tasks; match the corresponding simulation execution time point for each of the multiple simulation tasks to be executed; and according to the multiple data simulation amounts and the multiple simulation execution time points, convert the multiple simulation tasks to be executed into the multiple sub-simulation tasks.

[0122] In one embodiment, the conversion module 402 is further configured to:

[0123] Respectively obtain the first time speeds corresponding to the multiple first scheduled processing times and the second time speeds corresponding to the simulation timeline; according to the time speed ratio between the multiple first time speeds and the second time speeds, respectively convert the multiple first scheduled processing times to the simulation timeline corresponding to the production line to be simulated to obtain multiple second scheduled processing times.

[0124] In one embodiment, the sorting module 403 is further used to:

[0125] Determine the first production line instance to which each of the multiple sub-simulation tasks belongs; generate a first execution sequence between the multiple first production line instances and a second execution sequence between the multiple sub-simulation tasks based on the multiple second scheduled processing times; sort the execution time of the multiple sub-simulation tasks based on the first execution sequence and the second execution sequence to obtain the time sorting result.

[0126] In one embodiment, the simulation module 405 is further configured to:

[0127] Determine a second production line instance to which the multiple sub-simulation tasks belong together; match corresponding simulation service nodes for the multiple sub-simulation tasks respectively according to the identification information of the second production line instance, wherein the simulation service node is used to simulate the production line simulation data; simulate the production line to be simulated on the simulation timeline according to the multiple simulation service nodes and the production line simulation data.

[0128] In one embodiment, the device is further used for:

[0129] In the process of simulating the production line to be simulated, for any of the sub-simulation tasks, the third production line instance to which the sub-simulation task belongs is determined; in response to an adjustment operation triggered for the sub-simulation task, the default time speed of the sub-simulation task is adjusted, wherein the default time speed is used to characterize a pre-set time flow rate relationship between the simulation scene and the real scene.

[0130] Each module in the above production line simulation device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0131] In an exemplary embodiment, the computer device may be a terminal, and its internal structure diagram may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface, the display unit and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a production line simulation method is implemented. Those skilled in the art can understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0132] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0133] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0134] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0135] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0136] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for simulating production, characterized in that: The method comprises: Obtain multiple sub-simulation tasks under the total simulation task registered for the production line to be simulated; Acquire a plurality of first scheduled processing times corresponding to the plurality of sub-simulation tasks, and respectively convert the plurality of first scheduled processing times to the simulation timeline corresponding to the production line to be simulated, to obtain a plurality of second scheduled processing times; According to the plurality of second scheduled processing times, the plurality of sub-simulation tasks are sorted by execution time to obtain a time sorting result; Generating production line simulation data on the simulation timeline according to the time sorting result; The production line to be simulated is simulated on the simulation timeline according to the production line simulation data.

2. The method according to claim 1, characterized in that The step of obtaining multiple sub-simulation tasks under the total simulation task registered for the production line to be simulated includes: Extracting data simulation parameters of the production line to be simulated from the overall simulation task; The total simulation task is divided according to the data simulation parameters to obtain the multiple sub-simulation tasks.

3. The method according to claim 2, characterized in that The data simulation parameters include the total amount of data simulation; the total simulation task is divided according to the data simulation parameters to obtain the multiple sub-simulation tasks, including: According to the total amount of data simulation, generating the total amount of data simulation tasks for the production line to be simulated; Performing simulation distribution on the total amount of data simulation to obtain data simulation amounts of multiple simulation tasks to be executed under the total amount of data simulation tasks; Matching a corresponding simulation execution time point for each of the plurality of simulation tasks to be executed; According to a plurality of data simulation quantities and a plurality of simulation execution time points, the plurality of simulation tasks to be executed are converted into the plurality of sub-simulation tasks.

4. The method according to claim 1, characterized in that The step of converting the plurality of first scheduled processing times to the simulation timeline corresponding to the production line to be simulated to obtain a plurality of second scheduled processing times comprises: Respectively obtain the first time speeds corresponding to the plurality of first scheduled processing times and the second time speed corresponding to the simulation timeline; According to the time speed ratio between the plurality of first time speeds and the second time speed, the plurality of first regular processing times are respectively converted to the simulation time line corresponding to the production line to be simulated to obtain a plurality of second regular processing times.

5. The method according to claim 1, characterized in that The step of performing execution time sorting on the plurality of sub-simulation tasks according to the plurality of second scheduled processing times to obtain a time sorting result includes: Determine a first production line instance to which each of the plurality of sub-simulation tasks belongs; generating a first execution timing between a plurality of first production line instances and a second execution timing between the plurality of sub-simulation tasks according to the plurality of second scheduled processing times; The execution time of the plurality of sub-simulation tasks is sorted according to the first execution timing and the second execution timing to obtain the time sorting result.

6. The method according to claim 1, characterized in that The simulating the production line to be simulated on the simulation timeline according to the production line simulation data comprises: Determine a second production line instance to which the plurality of sub-simulation tasks commonly belong; According to the identification information of the second production line instance, the plurality of sub-simulation tasks are matched with corresponding simulation service nodes respectively, wherein the simulation service nodes are used to simulate the production line simulation data; The production line to be simulated is simulated on the simulation timeline according to a plurality of simulation service nodes and the production line simulation data.

7. The method according to claim 1, characterized in that The method further comprises: In the process of simulating the production line to be simulated, for any of the sub-simulation tasks, determining the third production line instance to which the sub-simulation task belongs; In response to the adjustment operation triggered for the sub-simulation task, the default time speed of the sub-simulation task is adjusted, wherein the default time speed is used to characterize a preset time flow rate relationship between the simulation scene and the real scene.

8. A device for simulating production and manufacturing, characterized in that: The device comprises: An acquisition module, used for acquiring a plurality of sub-simulation tasks under a total simulation task registered for the production line to be simulated; A conversion module, used for obtaining a plurality of first scheduled processing times corresponding to the plurality of sub-simulation tasks, and respectively converting the plurality of first scheduled processing times to the simulation timeline corresponding to the production line to be simulated, to obtain a plurality of second scheduled processing times; A sorting module, used for sorting the execution time of the plurality of sub-simulation tasks according to the plurality of second scheduled processing times to obtain a time sorting result; A generating module, used for generating production line simulation data on the simulation timeline according to the time sorting result; The simulation module is used to simulate the production line to be simulated on the simulation timeline according to the production line simulation data.

9. A computer device comprising a memory and a processor, characterized in that: The memory stores a computer program, and when the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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