Aero-engine flexible production line simulation method and system

Abstract

The invention provides an aero-engine flexible production line simulation method and system, and relates to the technical field of production line simulation, and the method comprises the steps: collecting and storing various types of multi-source heterogeneous data from various systems; carrying out fusion processing on the multi-source heterogeneous data; constructing and storing an auxiliary decision-making model and a production line production unit model of the aero-engine; constructing a production line digital twinborn simulation project; according to the multi-source heterogeneous data and the auxiliary decision-making model, simulation parameters are configured on a production line digital twin simulation project, a model data flow is monitored, and simulation operation is achieved; and analyzing the simulation result based on the auxiliary decision model and obtaining an optimization scheme. The method has the advantage that production scenes based on different instantiated aero-engine production and manufacturing schemes are flexibly simulated and analyzed.

Description

Technical Field

[0001] The present invention relates to the technical field of production line simulation, and in particular to a simulation method and system for a flexible production line of an aero-engine. Background Art

[0002] In the era of intelligent manufacturing, the diversification and personalization of market demand are becoming increasingly prominent, and the pace of product updates is accelerating significantly.

[0003] Enterprise production models are rapidly transitioning from traditional large-scale, single-product production to flexible, multi-batch, small-batch production with diverse products. Given the actual demands of aircraft engine production, flexible production requires production lines with robust, rapid adjustment and adaptability. However, lack of effective planning for production line adjustments can easily lead to production disruptions and increased costs. By analyzing the production process of different aircraft engine models and batches on the same production line, we can clearly understand key information such as equipment load distribution and logistics efficiency, providing a precise basis for decision-making on actual production adjustments.

[0004] Therefore, there is an urgent need for a set of effective and practical production line flexible simulation methods and environments for the field of aviation engine manufacturing, which can simulate and analyze production scenarios based on different instantiated aviation engine production and manufacturing plans, such as production process changes on the production line for different product combinations, and predict the production line operation status in advance. Summary of the Invention

[0005] The purpose of the present invention is to provide a simulation method and system for a flexible production line of an aero-engine, which can flexibly simulate and analyze production scenarios based on different instantiated aero-engine production and manufacturing plans.

[0006] The present invention is achieved through the following technical solutions: A simulation method for an aero-engine flexible production line includes the following steps: Collect and store various types of multi-source heterogeneous data from various systems; Performing fusion processing on the multi-source heterogeneous data; Build and store decision-making support models and aircraft engine production line production unit models; Construct a production line digital twin simulation project, retrieve the production line production unit model and the auxiliary decision model, and configure the data flow parameters between the production line production unit models, the data flow parameters between the production line production unit model and the auxiliary decision model, and the multi-source heterogeneous data call interface parameters of the production line production unit model according to the aircraft engine production process nodes; According to the multi-source heterogeneous data and the auxiliary decision model, configuring simulation parameters and monitoring model data flow in the production line digital twin simulation project to implement simulation operations; The simulation results are analyzed based on the auxiliary decision-making model to obtain an optimization solution.

[0007] Preferably, the method for collecting and storing various types of multi-source heterogeneous data is performed at a fixed time and frequency through a data interaction interface between systems. The collection method includes: Define a classified storage resource directory for the multi-source heterogeneous data, including types such as production plan, process design, commissioning test, and production line status; Define and configure the data interaction interface according to the type of the data interaction interface for data interaction with the system when collecting the multi-source heterogeneous data, and configure the data resource directory corresponding to the data collection frequency and storage.

[0008] Preferably, the data interaction interface includes an FTP interface, an API interface, an SQL / ODBC / JDBC database interface and a Web Service interface.

[0009] Preferably, the multi-source heterogeneous data includes aircraft engine production plan data, process design data, test data, and aircraft engine production line status data. The method for fusing the multi-source heterogeneous data is: Assigning feature identifiers to parameters in the multi-source heterogeneous data according to parameter types; Obtaining characteristic identifiers of parameters in aircraft engine production plan data; Construct a data BOM structure tree based on the characteristic identifiers of the parameters in the aircraft engine production plan data; Based on the characteristic identifiers of the parameters in the aircraft engine production plan data, the corresponding parameters are identified from the process design data and the test data, and then mounted into the data BOM structure tree to form an instantiated production and manufacturing plan; The instantiated production and manufacturing plan and the aircraft engine production line status data are encapsulated.

[0010] Preferably, the method for constructing the auxiliary decision model and the aircraft engine production line production unit model is: Creating graphic elements of the auxiliary decision-making model for simulation of the flexible production line of an aircraft engine, editing the mathematical calculation expressions of the auxiliary decision-making model and binding them to the corresponding graphic elements, and defining the variable input interface and result output interface of the auxiliary decision-making model; Create the production line production unit model of the aircraft engine, define the internal production team or production equipment model respectively, define the variable input interface and result output interface of the production team or production equipment model, and define the variable input interface and result output interface of the production line production unit model.

[0011] Preferably, the method for constructing a production line digital twin simulation project is: Based on the simulation requirements of the aircraft engine flexible production line, a digital twin simulation engineering project for the aircraft engine production line was created; According to the simulation requirements of the aircraft engine flexible production line, enter the model name or number, retrieve the required production line production unit model and auxiliary decision model, and add them to the aircraft engine production line digital twin simulation project; According to the simulation requirements of the flexible production line of aircraft engines and the nodes of the aircraft engine production process, the data flow parameters between the production unit models of the production line and between different production stages are configured, as well as the data flow parameters between the auxiliary decision-making model and the production unit model of the production line; According to the simulation requirements of the flexible production line of aircraft engines and the API data interface of the defined production line production unit model, the API data interface is configured and defined to meet the requirements of calling the multi-source heterogeneous data during the simulation process.

[0012] Preferably, the method for implementing the simulation operation is: Configuring simulation parameters for the digital twin simulation project of the aircraft engine production line, including simulation parameters such as the number of simulation project executions and the simulation cycle; Select the required components from the simulation operation data visualization components and define the model objects to be observed, including model interfaces and data flows; Start the simulation.

[0013] Preferably, when analyzing the simulation results based on the auxiliary decision model and obtaining the optimization solution, the optimization content includes logistics flow time and adjusting the production unit capacity. The optimization method of the auxiliary decision model is: Establish the target optimization function: ; ; in, is the optimization object, T is the total production time of the aircraft engine, 、 and They are the actual production time in the parts manufacturing stage, the actual production time in the assembly stage, and the actual production time in the assembly stage. The cost of an additional shift when producing device b for production unit u, The true value representing whether the production team or equipment b in production unit u increases the working shift, if yes, it is 1, otherwise it is 0, represents the set of production units within the production stage S, is the production team or equipment set in production unit u; Establish part production task allocation constraints: ; in, Representative production parts The true value of whether to use the production team or equipment b in the production unit u, if yes, then it is 1, otherwise it is 0, The stage represented is the parts production stage; Establish component assembly task allocation constraints: ; in, Representative production parts The true value of whether to use the production team or equipment b in the production unit u, if yes, then it is 1, otherwise it is 0, The stage represented is the assembly stage; Establish the task allocation constraints for machine assembly and test run inspection: ; in, Represents the production of complete machines The true value of whether to use the production team or equipment b in the production unit u, if yes, then it is 1, otherwise it is 0, Represents the production team or equipment collection in the whole machine test production unit; Establish capacity constraints: ; ; ; Among them, P represents the set of all parts, B represents the set of all components, and O represents the set of all production machines. The capacity improvement coefficient after the production team or equipment b in the production unit u increases the number of shifts and its value is not less than 1, is the unit time capacity of the production team or equipment b in production unit u, is the total duration of the production planning period, The estimated remaining completion time for the production task currently being executed by the production team or equipment b in production unit u, is the downtime maintenance time of the production team or equipment b in production unit u; Establish an overall time constraint: T≤D; Where D is the set threshold.

[0014] Preferably, the actual production time consumed in the parts manufacturing stage, the actual production time consumed in the assembly stage, and the actual production time consumed in the assembly stage are obtained by: ; ; ; ; ; ; in, For parts The time spent on production by production team or equipment b in production unit u, For components The time spent on assembly by the production team or equipment b in production unit u, For the whole machine The time spent on assembly or test run by the production team or equipment b in production unit u, For parts The number of For components The number of For the whole machine The number of Producing parts for production unit u The time, Producing parts for production unit u The time, Produce complete machines for production unit u The time, To produce units within the same production phase To the production unit The logistics flow time between Indicates production units within the same production stage To the production unit The waiting time for logistics flow between Indicates the production stage To the production stage The logistics flow time between Indicates the production stage To the production stage The logistics flow waiting time between them, i=1,2,3,4,j=1,2.

[0015] The present invention further provides an aircraft engine flexible production line simulation system, which is applied to the above-mentioned aircraft engine flexible production line simulation method, comprising: Multi-source heterogeneity belongs to the acquisition module, which is used to collect and store various types of multi-source heterogeneous data from various systems; A multi-source heterogeneous data fusion processing module is used to perform fusion processing on the multi-source heterogeneous data; The decision-making support model library and production unit model library are used to build and store decision-making support models and aircraft engine production line production unit models; The aircraft engine production line digital twin module is used to build a production line digital twin simulation project, retrieve the production line production unit model and the auxiliary decision model, and configure the data flow parameters between the production line production unit models, the data flow parameters between the production line production unit model and the auxiliary decision model, and the multi-source heterogeneous data call interface parameters of the production line production unit model according to the aircraft engine production process nodes; and further configure simulation parameters and monitor model data flow in the production line digital twin simulation project based on the multi-source heterogeneous data and the auxiliary decision model to achieve simulation operations; The intelligent auxiliary decision-making module is used to analyze the simulation results based on the auxiliary decision-making model and obtain an optimization solution.

[0016] The technical solution of the present invention has at least the following advantages and beneficial effects: This invention solves the problem that existing technologies are difficult to systematically and accurately simulate and analyze production line flexibility planning, resource demand bottlenecks, etc. according to the production needs of different models / batches / units of aircraft engines, and provide auxiliary decision-making suggestions. This invention provides a flexible aero-engine production line simulation system based on digital twin technologies such as virtual-reality fusion, data fusion, and decision support. This system can be used to build flexible production line simulation analysis based on the digital twin of the aero-engine production line before production begins, in response to the needs of multi-batch and small-batch production of aero-engines. The decision-making support model of the present invention can promptly identify bottlenecks in production lines and assist in optimizing and adjusting aircraft engine production lines. For example, it can optimize production line layout to shorten logistics flow time / logistics flow waiting time and adjust production unit capacity, thereby improving the production efficiency of aircraft engine production lines. The present invention has reasonable design, high cost performance, can be easily applied to various production lines through simple module changes, and has high scalability. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of the flow of the aero-engine flexible production line simulation method provided in Example 1 of the present invention; Figure 2 A schematic diagram of the structure of the data BOM structure tree for the case provided in Example 1 of the present invention; Figure 3 A schematic diagram of the structure of the data BOM structure tree after mounting in the case provided in Example 1 of the present invention; Figure 4 A schematic diagram of the structure of the production line production unit model framework provided in Example 2 of the present invention; Figure 5 A schematic diagram of the structure of the production line digital twin simulation project design provided in Example 2 of the present invention; Figure 6This is a schematic diagram of the principles of the aviation engine flexible production line simulation system provided in Example 3 of the present invention. DETAILED DESCRIPTION

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0019] Example 1 This embodiment provides a simulation method for an aircraft engine flexible production line, comprising the following steps: Collect and store various types of multi-source heterogeneous data from various systems; Performing fusion processing on the multi-source heterogeneous data; Build and store decision-making support models and aircraft engine production line production unit models; Construct a production line digital twin simulation project, retrieve the production line production unit model and the auxiliary decision model, and configure the data flow parameters between the production line production unit models, the data flow parameters between the production line production unit model and the auxiliary decision model, and the multi-source heterogeneous data call interface parameters of the production line production unit model according to the aircraft engine production process nodes; According to the multi-source heterogeneous data and the auxiliary decision model, configuring simulation parameters and monitoring model data flow in the production line digital twin simulation project to implement simulation operations; The simulation results are analyzed based on the auxiliary decision-making model to obtain an optimization solution.

[0020] In this embodiment, refer to Figure 1First, through the system data interaction interface, multi-source heterogeneous data are collected from relevant business systems such as the production plan management system, aircraft engine process design system, aircraft engine test management system, and aircraft engine production line status monitoring system. Specifically, it can include production plan, parts processing technology, assembly process, test inspection and production line status, and the collected multi-source heterogeneous data are managed; then the multi-source heterogeneous data are fused and processed. This step mainly takes the aircraft engine production plan data as the object, performs data feature recognition, and extracts and calls corresponding data from the process design data and test data to form an instantiated aircraft engine production and manufacturing plan, and performs standardized data fusion packaging. At the same time, the production line status data will also be packaged; then, the auxiliary decision model and the aircraft engine production line production unit model are constructed and stored in the modeling environment, and the constructed auxiliary decision model and production line production unit model are stored in the auxiliary decision model respectively. The decision model library and the production unit model library are used for modeling the digital twin of the aircraft engine production line; then, the digital twin simulation project of the aircraft engine production line is constructed and simulation calculations are performed to obtain the results of the simulation calculation object with the production and manufacturing plan of the specific model / batch / unit aircraft engine as the simulation calculation object. The specific implementation is to first create a new production line digital twin project, then perform model retrieval and call and twin construction, then perform multi-source heterogeneous data call, and then execute the production line simulation calculation; finally, according to the called auxiliary decision model, the production simulation results of the specific model / batch / unit aircraft engine are analyzed, and then according to the delivery time in the production and manufacturing plan of the specific model / batch / unit aircraft engine, production line optimization adjustment suggestions are given. Specifically, the auxiliary decision model and production line production unit model constructed earlier have been stored in the corresponding model library. Based on this, intelligent auxiliary decision-making can be realized, that is, simulation result analysis can be realized to obtain auxiliary decision recommendations.

[0021] In this embodiment, the method for collecting and storing various types of multi-source heterogeneous data is performed at a fixed time and frequency through a data interaction interface between systems. The collection method includes: Define a classified storage resource directory for the multi-source heterogeneous data, including types such as production plan, process design, commissioning test, and production line status; Define and configure the data interaction interface according to the type of the data interaction interface for data interaction with the system when collecting the multi-source heterogeneous data, and configure the data resource directory corresponding to the data collection frequency and storage.

[0022] Furthermore, the data interaction interface includes an FTP interface, an API interface, an SQL / ODBC / JDBC database interface and a Web Service interface.

[0023] Next, the multi-source heterogeneous data includes aircraft engine production plan data, process design data, test data, and aircraft engine production line status data. The method for fusing the multi-source heterogeneous data is as follows: Assigning feature identifiers to parameters in the multi-source heterogeneous data according to parameter types; Obtaining characteristic identifiers of parameters in aircraft engine production plan data; Construct a data BOM structure tree based on the characteristic identifiers of the parameters in the aircraft engine production plan data; Based on the characteristic identifiers of the parameters in the aircraft engine production plan data, the corresponding parameters are identified from the process design data and the test data, and then mounted into the data BOM structure tree to form an instantiated production and manufacturing plan; The instantiated manufacturing plan and the aircraft engine production line status data are encapsulated, with data API interface encapsulation being prioritized. This encapsulation method may include configuring the interface URL, determining the data request method (using the GET request method), defining request parameters, and defining the response data format to form an instantiated data model. This ensures that the aircraft engine production line digital twin module can recognize and access the required instantiated manufacturing plan data and production line status data during simulation operations.

[0024] The characteristic identifier of this embodiment can be set as the name, model, batch and number of aircraft engines, such as: XX aircraft engine, XX-XX model, 202501 batch, 01-10 units and other production plan data characteristic identifiers. Then, a data BOM structure tree of the aircraft engine production and manufacturing plan can be constructed with the aircraft engine name, model, batch and number as the characteristic identifiers. The data BOM structure tree of this case can be referred to. Figure 2 According to the identified aircraft engine name, model, batch, and number of units, the corresponding data is identified and extracted from the collected process design data (including process data for parts manufacturing, component assembly, and complete machine assembly) and test data, and mounted to the data BOM structure tree of the constructed aircraft engine production and manufacturing plan, forming an instantiated production and manufacturing plan for the specific aircraft engine model, batch, and number of units. For details on the mounted data BOM structure tree, please refer to Figure 3 , the mounted data BOM structure tree can be displayed visually. As a preferred solution, the method for constructing the auxiliary decision model and the aircraft engine production line production unit model is: Creating graphic elements of the auxiliary decision-making model for simulation of the flexible production line of an aircraft engine, editing the mathematical calculation expressions of the auxiliary decision-making model and binding them to the corresponding graphic elements, and defining the variable input interface and result output interface of the auxiliary decision-making model; Create the production line production unit model of the aircraft engine, define the internal production team or production equipment model respectively, define the variable input interface and result output interface of the production team or production equipment model, and define the variable input interface and result output interface of the production line production unit model.

[0025] Next, the method for constructing the production line digital twin simulation project is as follows: Based on the simulation requirements of the aircraft engine flexible production line, a digital twin simulation engineering project for the aircraft engine production line was created; According to the simulation requirements of the aircraft engine flexible production line, enter the model name or number, retrieve the required production line production unit model and auxiliary decision model, and add them to the aircraft engine production line digital twin simulation project; According to the simulation requirements of the flexible production line of aircraft engines and the nodes of the aircraft engine production process, the data flow parameters between the production unit models of the production line and between different production stages are configured, as well as the data flow parameters between the auxiliary decision-making model and the production unit model of the production line; According to the simulation requirements of the flexible production line of aircraft engines and the API data interface of the defined production line production unit model, the API data interface is configured and defined to meet the requirements of calling the multi-source heterogeneous data during the simulation process.

[0026] Then, the method for realizing simulation operation is: Configuring simulation parameters for the digital twin simulation project of the aircraft engine production line, including simulation parameters such as the number of simulation project executions and the simulation cycle; Select the required components from the simulation operation data visualization components and define the model objects to be observed, including model interfaces and data flows; Start the simulation.

[0027] After the production line production unit model of this embodiment is completed, it can be stored in the production unit model library. Specifically, an actual case of establishing and running a production line digital twin simulation project is as follows: Creation of production line digital twin simulation engineering project: Based on the current simulation requirements for the aero-engine flexible production line, create an aero-engine production line digital twin simulation engineering project and name the created simulation engineering project.

[0028] Selection of production unit model and decision support model: According to the simulation requirements of the flexible production line of aircraft engines, enter the model name or number in the search box of the production unit model library and the auxiliary decision model library, retrieve the required production line production unit model and auxiliary decision model from the production unit model library and the auxiliary decision model library, and drag and drop them into the production line digital twin simulation engineering project modeling work area.

[0029] Data interaction configuration of production unit model and auxiliary decision model: According to the simulation requirements of the flexible production line of aircraft engines, after dragging and dropping the production unit model of the production line, configure the data flow parameters between each production unit model and between different production stages (such as production line material flow direction, logistics flow time, and logistics flow waiting time) according to the aircraft engine production process nodes. At the same time, configure the data flow parameters between the auxiliary decision model and each production unit model or production stage. The production line digital twin simulation project design is as follows Figure 5 shown.

[0030] During the simulation process, based on the acquired multi-source heterogeneous data and decision-making support model, simulation parameters (such as the number of simulation executions and simulation cycles) are configured on the basis of the constructed digital twin of the aircraft engine production line, and the model data flow (model interface, data flow) is monitored. Simulation results are obtained based on the production and manufacturing plan of a specific aircraft engine model, batch, or unit. The simulation of the production line digital twin includes the following steps: Simulation parameter configuration: Configure the simulation parameters of the digital twin simulation project for the aero-engine production line, including the number of simulation executions (e.g., 20 simulation executions) and the simulation cycle (e.g., a single simulation cycle of 100 seconds).

[0031] Simulation visualization configuration: From the simulation data visualization component, select the desired component and go to the simulation control panel. Define and configure the model object to be monitored (specifically, the production unit model, production team / equipment model), including the model interface and data flow. This allows you to view the input and output results of specific model objects in real time during the simulation.

[0032] Simulation calculation: Start the simulation operation, view the data monitoring visualization results of each model in real time during the simulation process, and finally obtain the simulation operation results, including the simulation results of the total production time T of the aircraft engine and the simulation results of the cost optimization objective function C.

[0033] Finally, based on the simulation of the digital twin of the aircraft engine production line, the production simulation results for a specific aircraft engine model, batch, or unit are analyzed using the invoked decision-making support model. The simulation and analysis results are presented, including the simulation results for the total aircraft engine production time T and the cost optimization objective function C after multiple simulation runs. Furthermore, based on the delivery times of each production stage in the manufacturing plan for a specific aircraft engine model, batch, or unit, production line optimization recommendations are provided. These recommendations include shortening logistics flow and waiting times between production units and between different production stages, and adjusting production unit capacity (such as increasing work shifts and improving the capacity factor).

[0034] Example 2 This embodiment is based on the technical solution of Example 1 and further explains the auxiliary decision model and the production line production unit model.

[0035] The following is a specific implementation case of building the auxiliary decision model: Create a decision-making support model in the modeling environment and name it the aircraft engine flexible production line simulation decision-making support model. To support simulation-based decision-making for flexible aircraft engine production lines, a production line optimization decision-making algorithm was designed. This algorithm aims to design a mathematical model-based production line optimization calculation method and formula by considering the production and manufacturing sequence between production units, logistics flow time and frequency, and other relevant factors. For specific design methods, please refer to the objective function and constraints designed for this model later in this article. The algorithm aims to calculate a comprehensive indicator that minimizes logistics costs and production time, thereby assisting in production decision analysis.

[0036] When building a production line production unit model, the specific case is as follows: In the modeling environment, create an aircraft engine production line production unit model and define its internal production team or production equipment model. At the same time, define the variable input interface and result output interface of the production team or production equipment model, as well as the variable input interface and result output interface of the aircraft engine production line production unit model. The construction of the production line production unit model includes the following steps: (1) Creation of production line production unit model elements: Based on the aircraft engine production process, production line characteristics and internal organizational structure, create aircraft engine production line production unit model elements in the modeling environment and name them as machining production unit model, special processing production unit model, welding production unit model, surface treatment production unit model, component assembly production unit model, complete machine assembly production unit model, and complete machine test and inspection production unit model respectively; (2) Modeling of production line production unit model: Each production unit of an aircraft engine production line is composed of multiple production teams or production equipment. In the modeling environment, the internal production team or production equipment models of the created production line production unit model are designed and defined, and the production capacity parameters of these production team or production equipment models are designed.

[0037] Specific modeling includes: 1) Data model building ①Model data design and interface design A data model is defined within the production line production unit model. This data model is used to obtain instantiated manufacturing plan data and production line status data, which are encapsulated as data API interfaces. It also encapsulates the production characteristic data of the production team or production equipment contained within the current production unit (i.e., the product types that the production team or production equipment can produce and the unit time capacity of a single type of product). The data model also defines input and output interfaces. The input interface is used to obtain instantiated manufacturing plan data, production line status data, and the output results of external production unit model simulation operations. The output interface is used to distribute data incentives to the production team or production equipment model.

[0038] ②Logical design of data distribution mechanism Define the data distribution mechanism logic of the design data model, that is, during the simulation operation of the production line data twin, the data model distributes the instantiated production and manufacturing plan data and production line status data to the designated production team or production equipment model based on the obtained instantiated production and manufacturing plan data and production line status data, combined with the production characteristic data of all production teams or production equipment of the production unit, as an incentive for the simulation operation.

[0039] For the data model of the production unit in the parts manufacturing stage, its data distribution mechanism uses the parts production task allocation constraints as the design logic.

[0040] For the data model of the component assembly production unit in the assembly phase, its data distribution mechanism uses the component assembly task allocation constraints as the design logic.

[0041] For the data models of the whole machine final assembly production unit in the assembly phase and the whole machine test and inspection production unit in the test and inspection phase, the data distribution mechanism uses the whole machine final assembly and test and inspection task allocation constraints as the design logic.

[0042] 2) Modeling of production teams or production equipment Define multiple production teams or production equipment models within the production unit model, and define their (capacity per unit time), (estimated remaining completion time of the currently executing production task), (downtime for maintenance), (whether to use the production team or production equipment), (whether to increase work shifts), (Capacity improvement coefficient after increasing the number of working shifts) and other parameter items; as well as the production characteristic data that define the production team or production equipment contained in the current production unit (that is, the product types that the production team or production equipment can produce, and the unit time capacity of a single type of product). These parameter items and production characteristic data are used to represent the capabilities of the production team or production equipment.

[0043] For the production team or production equipment model of all production units in the part manufacturing stage, the production time of a single type of part is calculated. Mathematical formula for calculation Build a single production team or production equipment model; when producing multiple types of parts, the total production time of the production team or production equipment for . And use the parts manufacturing capacity constraint to constrain the production capacity of the production team or production equipment.

[0044] For the production team or production equipment model of the component assembly production unit in the assembly stage, the production time of a single type of component is calculated. Computational mathematical formulas Build a single production team or production equipment model, Representative production parts The true value of whether to use the production team or equipment b in the production unit u, if yes, it is 1, otherwise it is 0; when producing multiple types of parts, the total production time of the production team or production equipment is . And use the parts manufacturing capacity constraint to constrain the production capacity of the production team or production equipment.

[0045] For the production team or production equipment model of the whole machine final assembly production unit in the assembly stage and the whole machine test and inspection production unit in the test and inspection stage, the time consumption of the whole machine final assembly / test and inspection is used. Mathematical formula for calculation Build a single production team or production equipment model, To produce complete machines Whether to use the true value of the production team or equipment b in the production unit u; when producing multiple types of complete machines, the total production time of the production team or production equipment is . And use the parts manufacturing capacity constraint to constrain the production capacity of the production team or production equipment.

[0046] At the same time, the input interface and output interface of the production team or production equipment model are defined. The input interface is used to obtain the distributed simulation operation incentive data from the data model, and the output interface is used to output the results of the simulation operation process.

[0047] 3) Production unit model building The production unit model is composed of multiple production team or production equipment models and data models. Based on the data model, production team or production equipment model model, the data interaction relationship between the data model and multiple production team or production equipment models is defined; at the same time, the input and output interfaces of the production unit model are defined. The input interface is used to obtain the output results of the external production unit model simulation operation, and the output interface is used to output the simulation operation results of the production unit model. The production line production unit model framework is as follows: Figure 4 shown.

[0048] Production unit models for different production stages to calculate mathematical formulas Build models of all production units, Indicates the total production time of all production teams or production equipment in the production unit. Indicates the logistics flow time between the production unit and the external production unit, Indicates the waiting time for logistics flow between the production unit and external production units.

[0049] Based on the modeling results, when analyzing the simulation results based on the auxiliary decision model and obtaining an optimization solution, the optimization content includes logistics flow time and adjusting the production unit capacity. The optimization method of the auxiliary decision model is: Instantiate the aircraft engine manufacturing plan to minimize the total production time. By continuously adjusting the values ​​of each variable in the decision variable, the total production time T of the aircraft engine is minimized, that is, T=min T. When considering the cost of adjusting the production unit u capacity, the cost of increasing the shift is defined as , on this basis, the target optimization function is established: ; ; in, is the optimization object, T is the total production time of the aircraft engine, 、 and They are the actual production time in the parts manufacturing stage, the actual production time in the assembly stage, and the actual production time in the assembly stage. The cost of an additional shift when producing device b for production unit u, The true value representing whether the production team or equipment b in production unit u increases the working shift, if yes, it is 1, otherwise it is 0, represents the set of production units within the production stage S, is the production team or equipment set in production unit u; For each part During the production phase, a part can only be assigned to a certain team or equipment in a certain production unit of that phase for production. The constraints on part production task allocation are established: ; in, Representative production parts The true value of whether to use the production team or equipment b in the production unit u, if yes, then it is 1, otherwise it is 0, The stage represented is the parts production stage; For each component During the assembly phase, a component can only be assigned to a certain team or equipment in a certain production unit of that phase for assembly. The component assembly task allocation constraints are established: ; in, Representative production parts The true value of whether to use the production team or equipment b in the production unit u, if yes, then it is 1, otherwise it is 0, The stage represented is the assembly stage; For each machine During the final assembly or test run phase, a task can only be assigned to a certain team or equipment in a certain production unit in that phase for assembly or test run. This establishes task allocation constraints for final assembly and test run: ; in, Represents the production of complete machines The true value of whether to use the production team or equipment b in the production unit u, if yes, then it is 1, otherwise it is 0, Represents the production team or equipment collection in the whole machine test production unit; Establish capacity constraints: Parts manufacturing capacity constraints: ; Component assembly capacity constraints: ; Capacity constraints for machine assembly / testing and inspection: ; Among them, P represents the set of all parts, B represents the set of all components, and O represents the set of all production machines. The capacity improvement coefficient after the production team or equipment b in the production unit u increases the number of shifts and its value is not less than 1, is the unit time capacity of the production team or equipment b in production unit u, is the total duration of the production planning period, The estimated remaining completion time for the production task currently being executed by the production team or equipment b in production unit u, is the downtime maintenance time of the production team or equipment b in production unit u; Establish an overall time constraint: T≤D; Where D is the set threshold.

[0050] Preferably, the actual production time consumed in the parts manufacturing stage, the actual production time consumed in the assembly stage, and the actual production time consumed in the assembly stage are obtained by: ; ; ; ; ; ; in, For parts The time spent on production by production team or equipment b in production unit u, For components The time spent on assembly by the production team or equipment b in production unit u, For the whole machine The time spent on assembly or test run by the production team or equipment b in production unit u, For parts The number of For components The number of For the whole machine The number of Producing parts for production unit u The time, Producing parts for production unit u The time, Produce complete machines for production unit u The time, To produce units within the same production phase To the production unit The logistics flow time between Indicates production units within the same production stage To the production unit The waiting time for logistics flow between Indicates the production stage To the production stage The logistics flow time between Indicates the production stage To the production stage The logistics flow waiting time between them, i=1,2,3,4,j=1,2.

[0051] Optimization can be achieved by solving the established objective function and constraints. Heuristic algorithms (such as genetic algorithms, particle swarm optimization algorithms, etc.) can be used for approximate solutions. During the simulation process, the constructed production line digital twin simulation project (including the production unit model of each production line) is combined with continuous adjustment. 、 、 、 、 、 and The value of is used to achieve the optimal solution of the optimization objective function under the premise of satisfying the constraints.

[0052] The program editor in the modeling environment can be used to edit the objective function, constraints, etc. of the above calculations into script programs and associate them with the auxiliary decision model elements. The interfaces defined by the auxiliary decision model are divided into variable input interfaces and result output interfaces. Among them, the defined variable input interface includes 、 、 、 、 、 and The variable input interface and the data interface for interacting with each production unit model; the result output interface includes the output interface for the calculation results of the total production time T of the aircraft engine and the cost optimization objective function C. After the above auxiliary decision-making models are built, they are stored in the auxiliary decision-making model library.

[0053] The aircraft engine manufacturing production line has the characteristics of multiple stages, multiple processes, and multiple equipment collaboration, so the production line optimization is relatively difficult. This embodiment proposes an auxiliary decision-making optimization method that integrates production process characteristics and resource constraints in view of the characteristics of multiple varieties of parts, complex production lines, and highly collaborative operations in the aircraft engine production process. In the above scheme, the parts manufacturing stage, component assembly stage, whole machine assembly and test run inspection stage are taken into consideration in the process of establishing the optimization. The process of each stage in the complex system production line, logistics time, logistics waiting time, and equipment remaining working hours and downtime maintenance are comprehensively modeled, and the exclusive resource allocation method for each type of production task is optimized, thereby achieving more adaptable and more accurate optimization for the field of aircraft engine manufacturing production lines.

[0054] Example 3 This embodiment provides an aircraft engine flexible production line simulation system, which is applied to an aircraft engine flexible production line simulation method of the above embodiment. Figure 6 ,include: Multi-source heterogeneity belongs to the acquisition module, which is used to collect and store various types of multi-source heterogeneous data from various systems; A multi-source heterogeneous data fusion processing module is used to perform fusion processing on the multi-source heterogeneous data; The decision-making support model library and production unit model library are used to build and store decision-making support models and aircraft engine production line production unit models; The aircraft engine production line digital twin module is used to build a production line digital twin simulation project, retrieve the production line production unit model and the auxiliary decision model, and configure the data flow parameters between the production line production unit models, the data flow parameters between the production line production unit model and the auxiliary decision model, and the multi-source heterogeneous data call interface parameters of the production line production unit model according to the aircraft engine production process nodes; and further configure simulation parameters and monitor model data flow in the production line digital twin simulation project based on the multi-source heterogeneous data and the auxiliary decision model to achieve simulation operations; The intelligent auxiliary decision-making module is used to analyze the simulation results based on the auxiliary decision-making model and obtain an optimization solution.

[0055] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A simulation method for an aero-engine flexible production line, characterized in that: The following steps are involved: Collect and store various types of multi-source heterogeneous data from various systems; Performing fusion processing on the multi-source heterogeneous data; Build and store decision-making support models and aircraft engine production line production unit models; Construct a production line digital twin simulation project, retrieve the production line production unit model and the auxiliary decision model, and configure the data flow parameters between the production line production unit models, the data flow parameters between the production line production unit model and the auxiliary decision model, and the multi-source heterogeneous data call interface parameters of the production line production unit model according to the aircraft engine production process nodes; According to the multi-source heterogeneous data and the auxiliary decision model, configuring simulation parameters and monitoring model data flow in the production line digital twin simulation project to implement simulation operations; The simulation results are analyzed based on the auxiliary decision-making model to obtain an optimization solution.

2. The method for simulating an aerospace engine flexible production line according to claim 1, characterized in that: The method for collecting and storing various types of multi-source heterogeneous data is to collect data at a fixed time and frequency through the data interaction interface between the systems. The collection method includes: Define a classified storage resource directory for the multi-source heterogeneous data, including types such as production plan, process design, commissioning test, and production line status; Define and configure the data interaction interface according to the type of the data interaction interface for data interaction with the system when collecting the multi-source heterogeneous data, and configure the data resource directory corresponding to the data collection frequency and storage.

3. The simulation method for flexible production line of an aero-engine according to claim 2, characterized in that: The data interaction interface includes FTP interface, API interface, SQL / ODBC / JDBC database interface and Web Service interface.

4. The method for simulating an aero-engine flexible production line according to claim 1, characterized in that: The multi-source heterogeneous data includes aircraft engine production plan data, process design data, test data, and aircraft engine production line status data. The method for fusing the multi-source heterogeneous data is as follows: Assigning feature identifiers to parameters in the multi-source heterogeneous data according to parameter types; Obtaining characteristic identifiers of parameters in aircraft engine production plan data; Construct a data BOM structure tree based on the characteristic identifiers of the parameters in the aircraft engine production plan data; Based on the characteristic identifiers of the parameters in the aircraft engine production plan data, the corresponding parameters are identified from the process design data and the test data, and then mounted into the data BOM structure tree to form an instantiated production and manufacturing plan; The instantiated production and manufacturing plan and the aircraft engine production line status data are encapsulated.

5. The method for simulating an aero-engine flexible production line according to claim 1, characterized in that: The method for constructing the auxiliary decision model and the aircraft engine production line production unit model is as follows: Creating graphic elements of the auxiliary decision-making model for simulation of the flexible production line of an aircraft engine, editing the mathematical calculation expressions of the auxiliary decision-making model and binding them to the corresponding graphic elements, and defining the variable input interface and result output interface of the auxiliary decision-making model; Create the production line production unit model of the aircraft engine, define the internal production team or production equipment model respectively, define the variable input interface and result output interface of the production team or production equipment model, and define the variable input interface and result output interface of the production line production unit model.

6. The method for simulating an aero-engine flexible production line according to claim 1, characterized in that: The method for constructing a production line digital twin simulation project is as follows: Based on the simulation requirements of the aircraft engine flexible production line, a digital twin simulation engineering project for the aircraft engine production line was created; According to the simulation requirements of the aircraft engine flexible production line, enter the model name or number, retrieve the required production line production unit model and auxiliary decision model, and add them to the aircraft engine production line digital twin simulation project; According to the simulation requirements of the flexible production line of aircraft engines and the nodes of the aircraft engine production process, the data flow parameters between the production unit models of the production line and between different production stages are configured, as well as the data flow parameters between the auxiliary decision-making model and the production unit model of the production line; According to the simulation requirements of the flexible production line of aircraft engines and the API data interface of the defined production line production unit model, the API data interface is configured and defined to meet the requirements of calling the multi-source heterogeneous data during the simulation process.

7. The method for simulating an aero-engine flexible production line according to claim 6, characterized in that: The method for realizing simulation operation is: Configuring simulation parameters for the digital twin simulation project of the aircraft engine production line, including simulation parameters such as the number of simulation project executions and the simulation cycle; Select the required components from the simulation operation data visualization components and define the model objects to be observed, including model interfaces and data flows; Start the simulation.

8. The method for simulating an aero-engine flexible production line according to claim 1, characterized in that: When analyzing the simulation results based on the auxiliary decision model and obtaining the optimization plan, the optimization content includes logistics flow time and adjusting the production unit capacity. The optimization method of the auxiliary decision model is: Establish the target optimization function: ； ； in, is the optimization object, T is the total production time of the aircraft engine, 、 and They are the actual production time in the parts manufacturing stage, the actual production time in the assembly stage, and the actual production time in the assembly stage. The cost of an additional shift when producing device b for production unit u, The true value representing whether the production team or equipment b in production unit u increases the working shift, if yes, it is 1, otherwise it is 0, represents the set of production units within the production stage S, is the production team or equipment set in production unit u; Establish part production task allocation constraints: ； in, Representative production parts The true value of whether to use the production team or equipment b in the production unit u, if yes, then it is 1, otherwise it is 0, The stage represented is the parts production stage; Establish component assembly task allocation constraints: ； in, Representative production parts The true value of whether to use the production team or equipment b in the production unit u, if yes, then it is 1, otherwise it is 0, The stage represented is the assembly stage; Establish the task allocation constraints for machine assembly and test run inspection: ； in, Represents the production of complete machines The true value of whether to use the production team or equipment b in the production unit u, if yes, then it is 1, otherwise it is 0, Represents the production team or equipment collection in the whole machine test production unit; Establish capacity constraints: ； ； ； Among them, P represents the set of all parts, B represents the set of all components, and O represents the set of all production machines. The capacity improvement coefficient after the production team or equipment b in the production unit u increases the number of shifts and its value is not less than 1, is the unit time capacity of the production team or equipment b in production unit u, is the total duration of the production planning period, The estimated remaining completion time for the production task currently being executed by the production team or equipment b in production unit u, is the downtime maintenance time of the production team or equipment b in production unit u; Establish an overall time constraint: T≤D; Where D is the set threshold.

9. The method for simulating an aero-engine flexible production line according to claim 8, characterized in that: The actual production time consumed in the parts manufacturing stage, the actual production time consumed in the assembly stage, and the actual production time consumed in the assembly stage are obtained by: ； ； ； ； ； in, For parts The time spent on production by production team or equipment b in production unit u, For components The time spent on assembly by the production team or equipment b in production unit u, For the whole machine The time spent on assembly or test run by the production team or equipment b in production unit u, For parts The number of For components The number of For the whole machine The number of Producing parts for production unit u The time, Producing parts for production unit u The time, Produce complete machines for production unit u The time, To produce units within the same production phase To the production unit The logistics flow time between Indicates production units within the same production stage To the production unit The waiting time for logistics flow between Indicates the production stage To the production stage The logistics flow time between Indicates the production stage To the production stage The logistics flow waiting time between them, i=1,2,3,4,j=1,2.

10. An aircraft engine flexible production line simulation system, applied to an aircraft engine flexible production line simulation method according to any one of claims 1 to 9, characterized in that: include: Multi-source heterogeneity belongs to the acquisition module, which is used to collect and store various types of multi-source heterogeneous data from various systems; A multi-source heterogeneous data fusion processing module is used to perform fusion processing on the multi-source heterogeneous data; The decision-making support model library and production unit model library are used to build and store decision-making support models and aircraft engine production line production unit models; The aircraft engine production line digital twin module is used to build a production line digital twin simulation project, retrieve the production line production unit model and the auxiliary decision model, and configure the data flow parameters between the production line production unit models, the data flow parameters between the production line production unit model and the auxiliary decision model, and the multi-source heterogeneous data call interface parameters of the production line production unit model according to the aircraft engine production process nodes; and further configure simulation parameters and monitor model data flow in the production line digital twin simulation project based on the multi-source heterogeneous data and the auxiliary decision model to achieve simulation operations; The intelligent auxiliary decision-making module is used to analyze the simulation results based on the auxiliary decision-making model and obtain an optimization solution.

Images