Digital factory building method, device, equipment and medium

Abstract

The invention relates to the technical field of digital factories, and provides a digital factory building method and device, equipment and a medium, and the method comprises the steps: obtaining a digital factory building demand; converting the digital factory building demand into structured data, and determining a target module type and a target module parameter according to the structured data; generating a standard production module according to the target module type and the target module parameter; determining a functional area and a module position in the functional area according to a digital factory building requirement, and arranging standard production modules to the functional area and the module position to obtain a virtual factory building module network; on the basis of network nodes and edges of the virtual plant module network, a production line is built, time parameters are given to production nodes and paths of the production line, a production process simulation model is obtained, and the production process simulation model is used for guiding building of an actual plant. According to the scheme, efficient, flexible and self-adaptive digital factory construction is realized.

Description

Technical Field

[0001] The present application relates to the technical field of digital factories, and in particular to a method, device, equipment and medium for constructing a digital factory. Background Art

[0002] Digital factory is a modern production mode that simulates, evaluates and optimizes the entire production process through a computer virtual environment based on relevant data of the entire product life cycle. It covers all aspects from design, manufacturing, assembly to maintenance, and aims to improve production efficiency, reduce costs, shorten product launch time and improve product quality through digital means.

[0003] At present, the construction of digital factories mainly relies on the following technologies: 3D modeling and simulation, using 3D modeling tools to build virtual factory and equipment models, simulate the production process, and evaluate the layout and process flow of the production line; automation equipment integration: integrating various automation equipment (such as robots, conveyor belts, testing instruments, etc.) into the production line to realize automated production; data analysis and optimization: using big data analysis and artificial intelligence algorithms to analyze data in the production process, optimize production parameters, and improve production efficiency.

[0004] However, digital factories need to provide detailed warehouse models and equipment models, as well as simulations of the production process. This requires companies to provide a large amount of data support during the design phase, which increases the workload of preliminary preparation. Faced with numerous automated equipment, especially when full automation is required, the number of equipment models involved is huge, and the workload of remodeling and building motion models is huge. Especially when there are many types of equipment, the compatibility and interoperability between different equipment become a problem. During the construction process, any changes will cause some or all of the previous modeling work to become invalid labor, increasing the time and cost of the project. For example, if the location or function of a certain device changes, it may be necessary to readjust the layout and connection relationship of the entire production line. Existing technologies mainly focus on the optimization of a single device or a local area, and it is difficult to achieve the optimal configuration on a global scale. For example, the connection relationship between equipment is usually static and difficult to adjust dynamically according to actual needs. Existing production lines usually only consider the connection relationship of equipment, and lack refined management of time and logistics. This may lead to an unreasonable production rhythm and affect overall efficiency.

[0005] Therefore, how to achieve efficient, flexible and adaptable digital factory construction is an urgent problem that needs to be solved. Summary of the invention

[0006] In view of the above problems existing in the prior art, the purpose of this application is to propose a digital factory construction method, device, equipment and medium to at least solve the technical problem of how to achieve efficient, flexible and adaptable digital factory construction.

[0007] To achieve the above objectives and other related objectives, the present application provides a method for building a digital factory, the method comprising: Obtain the requirements for building a digital factory; Converting the digital factory construction requirements into structured data, and determining the target module type and target module parameters according to the structured data; Generate a standard production module according to the target module type and the target module parameters; According to the requirements for building the digital factory, functional areas and module positions in the functional areas are determined, and the standard production modules are arranged in the functional areas and the module positions to obtain a virtual plant module network, wherein the network nodes in the virtual plant module network are the standard production modules, and the edges in the virtual plant module network are the connection relationships between the standard production modules; Based on the network nodes and edges of the virtual factory module network, a production line is constructed, and time parameters are assigned to the production nodes and paths of the production line to obtain a production process simulation model, wherein the production process simulation model is used to guide the construction of an actual factory.

[0008] In some embodiments, the digital factory construction requirements include production line function requirements, equipment requirements, and space layout requirements, the structured data includes production process nodes, equipment model requirements, and space constraints, and the digital factory construction requirements are converted into structured data, including: Determine the production tasks, process nodes, and task dependencies according to the functional requirements of the production line, and obtain the production process nodes according to the production tasks, process nodes, and task dependencies; According to the device requirements, determine the device type, functional parameters, and interface requirements, and obtain the device model requirements according to the device type, functional parameters, and interface requirements; According to the spatial layout requirements, the equipment size, plant layout, and logistics path are determined, and according to the equipment size, plant layout, and logistics path, the spatial constraints are obtained.

[0009] In some embodiments, determining the target module type and target module parameters according to the structured data includes: Determine the demand parameters according to the structured data, and establish a module demand table according to the demand parameters, wherein the demand parameters include task parameters, equipment parameters and space parameters; Determine multiple candidate module types according to the task parameters, obtain the fitness corresponding to each of the candidate module types according to a preset weight coefficient, and use the candidate module type with the highest fitness as the target module type; Generate corresponding initial behavior parameters for the target module type according to the structured data, and optimize the initial behavior parameters to maximize the efficiency of the target module type, wherein the initial behavior parameters include execution speed and execution mode; According to the structured data, data interface parameters and physical interface parameters are configured, and the data interface parameters, the physical interface parameters and the optimized initial behavior parameters are used as the target module parameters.

[0010] In some embodiments, the standard production module includes a target device model, module behavior parameters, and a module interface, and generating the standard production module according to the target module type and the target module parameters includes: Determine a plurality of components according to the target module type and the target module parameters, the plurality of components including a device model component, an interface component, a behavior component and an environment adaptation component, and assign capability parameters to each of the components to obtain a component set; Based on the component set, determining module behavior parameters corresponding to the module behavior, the module behavior parameters including behavior characteristics and execution rules; Determining a module interface according to the component set and the module behavior parameters; Based on the module behavior parameters and the module interface, the components in the component set are combined to obtain the standard production module.

[0011] In some embodiments, determining the functional area and the module position in the functional area according to the digital factory construction requirements includes: According to the requirements of digital factory construction, extract the functional area type, the module type and quantity required for the functional area, the connection relationship between the functional areas, and generate a functional area requirement table; Based on the regional land requirements and factory space constraints, the functional areas in the functional area requirement table are divided to generate a regional layout diagram; In the functional area, the module position of the standard production module is determined according to the module function and behavior parameters of the standard production module.

[0012] In some embodiments, the production line includes a material line and a production sequence line, the time parameter includes a processing time parameter and a logistics time parameter, and the network nodes and edges of the virtual plant module network are used to construct the production line, and the production nodes and paths of the production line are assigned time parameters, including: Determine a task node sequence based on the network nodes and edges of the virtual plant module network, and construct the production sequence moving line based on the task node sequence; According to the connection relationship of the task nodes, the shortest path is selected in the virtual plant module network to obtain the material movement line; Acquire the processing time parameter from the behavior parameter of the standard production module, and assign the processing time parameter to the production node of the production line; The logistics time parameter is obtained from the logistics parameter of the edge, and the logistics time parameter is assigned to the path of the production line.

[0013] In some embodiments, after constructing a production line based on the network nodes and edges of the virtual plant module network, and assigning time parameters to the production nodes and paths of the production line, and obtaining a production process simulation model, the process further includes: In a pre-built virtual environment, running the production process simulation model to simulate the actual production process; Acquiring simulation data of the actual production process, wherein the simulation data includes equipment utilization, logistics efficiency, and bottleneck nodes; Optimization suggestions are generated based on the equipment utilization, logistics efficiency, and bottleneck nodes. The optimization suggestions include adjusting equipment operating parameters, optimizing material flow, and modifying equipment layout.

[0014] In one embodiment of the present application, a digital factory construction device is also provided, the device comprising: Demand acquisition unit, used to obtain digital factory construction requirements; A parameter determination unit, used to convert the digital factory construction requirements into structured data, and determine the target module type and target module parameters according to the structured data; A standard production module generating unit, used for generating a standard production module according to the target module type and the target module parameters; A network construction unit is used to determine the functional areas and the module positions in the functional areas according to the digital factory construction requirements, and arrange the standard production modules to the functional areas and the module positions to obtain a virtual plant module network, wherein the network nodes in the virtual plant module network are the standard production modules, and the edges in the virtual plant module network are the connection relationships between the standard production modules; The simulation model construction unit is used to construct a production line based on the network nodes and edges of the virtual factory module network, and assign time parameters to the production nodes and paths of the production line to obtain a production process simulation model, wherein the production process simulation model is used to guide the construction of an actual factory.

[0015] In one embodiment of the present application, a computer-readable storage medium is further provided, wherein the computer-readable storage medium includes a stored computer program, wherein the computer program executes the above-mentioned digital factory construction method when running.

[0016] In one embodiment of the present application, an electronic device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to execute the above-mentioned digital factory construction method through the computer program.

[0017] Beneficial effects of the present invention: First, the digital factory construction requirements are obtained; then, the digital factory construction requirements are converted into structured data, and the target module type and target module parameters are determined according to the structured data; then, according to the target module type and the target module parameters, a standard production module is generated; then, according to the digital factory construction requirements, the functional area and the module position in the functional area are determined, and the standard production module is arranged to the functional area and the module position to obtain a virtual factory module network, wherein the network nodes in the virtual factory module network are the standard production modules, and the edges in the virtual factory module network are the connection relationships between the standard production modules; finally, based on the network nodes and edges of the virtual factory module network, a production line is constructed, and time parameters are assigned to the production nodes and paths of the production line to obtain a production process simulation model, wherein the production process simulation model is used to guide the construction of an actual factory. In this application, obtaining the requirements for building a digital factory can better predict possible changes in the future (such as product line expansion, process improvement, etc.), so that flexibility can be taken into account at the beginning of the design to facilitate subsequent adjustments; the structured data format is easy to be parsed and operated by the computer system, supporting rapid iteration and updating. When the requirements change, they can be quickly reflected in the design by modifying the structured data without having to restart the entire design process; by selecting the optimal module type and configuration parameters, the best solution can be found in a short time, avoiding the trial and error exploration in traditional methods; modular design allows different modules to be combined according to different requirements to form a diversified production system, and each module can be independently developed, tested and optimized, reducing the complexity of the overall system; standard production modules simplify the manufacturing and installation process, reducing the additional cost and time consumption brought by customization; because standard production modules are highly customizable and extensible, the functions and interfaces of the modules can be flexibly adjusted according to actual conditions to meet the needs of different application scenarios, thereby realizing efficient, flexible and adaptable digital factory construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 is a schematic diagram of an application environment of a digital factory construction method shown in an exemplary embodiment of the present application; Figure 2 is a flow chart of a method for building a digital factory shown in an exemplary embodiment of the present application; Figure 3 is a schematic diagram of a digital factory construction device shown in an exemplary embodiment of the present application; Figure 4 It is a schematic diagram of the structure of an electronic device shown in an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0020] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0021] In one embodiment of the present application, a digital factory construction method, device, equipment and medium are provided. Optionally, as an optional implementation, the digital factory construction method can be but is not limited to being applied to Figure 1 in the environment shown. Figure 1 is a schematic diagram of an application environment of a digital factory construction method shown in an exemplary embodiment of the present application, see Figure 1, the implementation environment includes an actual factory 101, a data acquisition terminal 102, and a digital factory construction terminal 103. The actual factory 101, the data acquisition terminal 102, and the digital factory construction terminal 103 can communicate through a network, but are not limited to, and the digital factory construction terminal 103 can perform operations on the database, such as write data operations or read data operations. The above-mentioned digital factory construction terminal 103 can include, but is not limited to, a human-computer interaction screen, a processor, and a memory. The above-mentioned human-computer interaction screen can be used, but is not limited to, for displaying a production process simulation model. The above-mentioned processor can be used, but is not limited to, to respond to the above-mentioned human-computer interaction operation, perform corresponding operations, or generate corresponding instructions, and send the generated instructions to the actual factory 101. The above-mentioned memory is used to store relevant storage data, such as digital factory construction requirements and production process simulation models.

[0022] As an optional method, data can be collected through the data collection terminal 102, for example, the requirements for building a digital factory can be collected.

[0023] As an optional method, the production process simulation model generated by the digital factory construction terminal 103 can be used to guide the construction of the actual factory 101.

[0024] As an optional method, the following steps in the digital factory construction method may be performed on the digital factory construction terminal 103: Obtain the requirements for building a digital factory; Converting the digital factory construction requirements into structured data, and determining the target module type and target module parameters according to the structured data; Generate a standard production module according to the target module type and the target module parameters; According to the requirements for building the digital factory, functional areas and module positions in the functional areas are determined, and the standard production modules are arranged in the functional areas and the module positions to obtain a virtual plant module network, wherein the network nodes in the virtual plant module network are the standard production modules, and the edges in the virtual plant module network are the connection relationships between the standard production modules; Based on the network nodes and edges of the virtual factory module network, a production line is constructed, and time parameters are assigned to the production nodes and paths of the production line to obtain a production process simulation model, wherein the production process simulation model is used to guide the construction of an actual factory.

[0025] In the above method, obtaining the requirements for building a digital factory can better predict possible changes in the future (such as product line expansion, process improvement, etc.), so that flexibility can be taken into account at the beginning of the design to facilitate subsequent adjustments; the structured data format is easy to be parsed and operated by the computer system, supporting rapid iteration and updating. When the requirements change, they can be quickly reflected in the design by modifying the structured data without having to restart the entire design process; by selecting the optimal module type and configuration parameters, the best solution can be found in a short time, avoiding the trial-and-error exploration in traditional methods; modular design allows different modules to be combined according to different requirements to form a diversified production system, and each module can be independently developed, tested and optimized, reducing the complexity of the overall system; standard production modules simplify the manufacturing and installation process, reducing the additional cost and time consumption brought by customization; because standard production modules are highly customizable and extensible, the functions and interfaces of the modules can be flexibly adjusted according to actual conditions to meet the needs of different application scenarios, thereby realizing efficient, flexible and adaptive digital factory construction.

[0026] Optionally, in this embodiment, the above network may include but is not limited to: a wireless network, wherein the wireless network includes: Bluetooth, WIFI and other networks that implement wireless communication.

[0027] As an optional example, this embodiment does not limit the execution subject of the above-mentioned digital factory construction method, and some or all steps of the above-mentioned digital factory construction method can be executed on the digital factory construction terminal 103.

[0028] In one embodiment of the present application, a digital factory construction method is provided. Figure 2 is a flow chart of a method for building a digital factory shown in an exemplary embodiment of the present application, see Figure 2 The digital factory construction method includes the following steps S210 to S250: In step S210, the digital factory construction requirements are obtained.

[0029] The digital factory construction requirements refer to the specific requirements put forward by enterprises when building or renovating digital factories, including but not limited to the functional requirements of the production line, equipment requirements, space layout requirements, etc. These requirements reflect the production goals and operation modes that the enterprise expects to achieve, and serve as the basis of the entire design process to ensure that the final solution can meet the actual needs of the enterprise.

[0030] In step S220, the digital factory construction requirements are converted into structured data, and the target module type and target module parameters are determined according to the structured data.

[0031] Among them, structured data refers to the conversion of unstructured customer requirements into data with clear formats and levels, such as production process nodes, equipment model requirements, space constraints, etc. Structured data is easy for computer systems to process and analyze, providing clear input for subsequent automated processing and improving the speed and accuracy of data processing.

[0032] Among them, module type refers to the result of classifying production units according to their functions and uses, such as processing modules, assembly modules, inspection modules, etc. Each module type has specific functions and configurations. The modular design allows the factory to flexibly combine different modules to adapt to a variety of production tasks.

[0033] Among them, module parameters refer to specific parameters that describe the characteristics of the module, including task parameters (such as execution speed, execution mode), device parameters (such as model, performance indicators), physical interface parameters (such as size, connection method), etc., to accurately configure the performance and interface of the module to ensure that it can run efficiently in actual applications and cooperate well with other modules.

[0034] In step S230, a standard production module is generated according to the target module type and the target module parameters.

[0035] Among them, standard production modules refer to production units with complete functions generated according to preset standards, including target device models, module behavior parameters, module interfaces and other components. Standard production modules simplify the manufacturing and installation process, reduce the additional costs and time consumption caused by customization, and ensure interoperability between modules.

[0036] In step S240, according to the requirements of building the digital factory, the functional areas and the module positions in the functional areas are determined, and the standard production modules are arranged to the functional areas and the module positions to obtain a virtual factory module network, wherein the network nodes in the virtual factory module network are the standard production modules, and the edges in the virtual factory module network are the connection relationships between the standard production modules.

[0037] Among them, functional areas refer to specialized areas divided according to production processes and spatial layouts, such as processing areas, assembly areas, storage areas, etc. Each area concentrates modules related to a specific production stage.

[0038] Among them, module location refers to the specific placement of standard production modules in the virtual factory, which determines the relative relationship and connection method between modules. Reasonable module location arrangement helps shorten material transportation distance, reduce waiting time, and improve overall production efficiency.

[0039] The virtual factory module network refers to a virtual network composed of standard production modules, where the modules are network nodes and the connections between modules are network edges. This network simulates the production layout and process of an actual factory.

[0040] In step S250, a production line is constructed based on the network nodes and edges of the virtual factory module network, and time parameters are assigned to the production nodes and paths of the production line to obtain a production process simulation model, wherein the production process simulation model is used to guide the construction of an actual factory.

[0041] Among them, the production line refers to the path that describes the flow of materials and products in the production process, including material lines and production sequence lines.

[0042] Among them, production nodes refer to key points on the production line, which usually correspond to a specific production task or process, such as processing stations, assembly stations, etc.

[0043] Among them, the path refers to the route connecting different production nodes, indicating the movement trajectory of materials or products from one node to another, planning the most efficient logistics path, and reducing transportation time and cost.

[0044] Among them, time parameters refer to the time values ​​assigned to each node and path of the production line, such as processing time, transportation time, etc., which are used to finely manage the production rhythm, ensure that each process is completed on time, and avoid delays and waste.

[0045] Among them, the production process simulation model refers to a digital model built based on the virtual factory module network and time parameters, which is used to simulate the actual production process, predict possible problems and put forward improvement suggestions.

[0046] For example, an automobile manufacturer plans to build a new digital factory focusing on the production of electric vehicles. The company puts forward the following requirements: an annual output of 50,000 electric vehicles, supporting mixed-line production of multiple models, requiring a high degree of automation, and an area of ​​no more than 100,000 square meters. According to the requirements, the production process nodes (such as stamping, welding, painting, and assembly), equipment model requirements (such as robots, conveyor belts, and testing instruments), and space constraints (such as plant layout and logistics channels) are determined. The module types suitable for electric vehicle production are selected, such as battery assembly modules, motor test modules, and body welding modules, and the corresponding parameters are configured, such as hourly production capacity, equipment accuracy, and interface specifications. According to the selected module types and parameters, a series of standardized production modules are generated, each of which contains a complete equipment model, behavior parameters, and interfaces. The factory is divided into functional areas such as stamping area, welding area, painting area, and assembly area, and the location of the modules is reasonably arranged in each area to ensure that the logistics path is shortest and does not cross. A production line covering all functional areas was constructed, the entire process from raw material storage to finished product delivery was clarified, and specific time parameters were set for each production node and path, such as 2 minutes for welding and 1 minute for transportation. The simulation model was run in a virtual environment to simulate the actual production process, and some potential problems were found, such as the bottleneck of a certain process causing the subsequent processes to wait. According to the simulation results, the operating parameters of some equipment were adjusted, the material line was optimized, and finally an efficient production process was formed.

[0047] By adopting the above-mentioned embodiments provided by the present application, the requirements for building a digital factory can be obtained, and possible future changes (such as product line expansion, process improvement, etc.) can be better predicted, so that flexibility can be taken into account at the beginning of the design, which is convenient for subsequent adjustments; the structured data format is easy to be parsed and operated by the computer system, and supports rapid iteration and updating. When the requirements change, they can be quickly reflected in the design by modifying the structured data without having to restart the entire design process; by selecting the optimal module type and configuration parameters, the best solution can be found in a short time, avoiding the trial and error exploration in the traditional method; the modular design allows different modules to be combined according to different requirements to form a diversified production system, and each module can be independently developed, tested and optimized, reducing the complexity of the overall system; the standard production module simplifies the manufacturing and installation process, and reduces the additional cost and time consumption brought by customization; because the standard production module is highly customizable and extensible, the functions and interfaces of the module can be flexibly adjusted according to actual conditions to meet the needs of different application scenarios, thereby realizing efficient, flexible and adaptive digital factory construction.

[0048] In one embodiment of the present application, the digital factory construction requirements include production line function requirements, equipment requirements, and space layout requirements, the structured data includes production process nodes, equipment model requirements, and space constraints, and the digital factory construction requirements are converted into structured data, including: Determine the production tasks, process nodes, and task dependencies according to the functional requirements of the production line, and obtain the production process nodes according to the production tasks, process nodes, and task dependencies; According to the device requirements, determine the device type, functional parameters, and interface requirements, and obtain the device model requirements according to the device type, functional parameters, and interface requirements; According to the spatial layout requirements, the equipment size, plant layout, and logistics path are determined, and according to the equipment size, plant layout, and logistics path, the spatial constraints are obtained.

[0049] Among them, the functional requirements of the production line refer to the specific requirements of each process on the production line, including the production process, quality standards, production efficiency, etc. These requirements determine the functional configuration and process design of the production line.

[0050] Among them, equipment requirements refer to the various types of equipment and their performance requirements required to realize the functions of the production line, such as robots, conveyor belts, testing instruments, etc. Equipment requirements also include requirements for automation, accuracy, speed, etc.

[0051] Among them, spatial layout requirements refer to the spatial planning requirements within the factory, including building parameters such as factory area, floor height, column spacing, as well as the layout arrangements of production equipment, storage areas, logistics channels, etc.

[0052] Among them, the production process node refers to each specific operation step or process point in the production process, such as stamping, welding, painting, assembly, etc. Each process node has clear tasks and operation specifications.

[0053] Among them, equipment model requirements refer to the detailed information of the equipment required to achieve specific production process nodes, including equipment type (such as robots, machine tools), functional parameters (such as power, speed), interface requirements (such as data interface, physical connection), etc.

[0054] Among them, spatial constraints refer to the restrictions that must be followed when carrying out spatial layout, such as equipment size, factory structure, safety distance, logistics channel width, etc.

[0055] Among them, when determining the production tasks, process nodes, and task dependencies based on the functional requirements of the production line, the functional requirements of the production line are analyzed, the task content, execution order, and dependencies between tasks in each production stage are clarified, and then the specific production process nodes are determined.

[0056] Among them, when determining the equipment type, functional parameters, and interface requirements according to the equipment requirements, select the appropriate equipment type based on the equipment requirements, and determine its key performance parameters and interface requirements to meet the requirements of the production process node. Ensure that the selected equipment can complete the specified tasks efficiently and accurately, and has good interoperability to facilitate integration into the entire production system.

[0057] Among them, when obtaining the device model requirements based on the device type, functional parameters, and interface requirements, the device type, functional parameters, and interface requirements are comprehensively considered to form a detailed device model requirement document as a basis for equipment selection and procurement.

[0058] Among them, according to the space layout requirements, the size specifications of each equipment, the overall layout plan of the factory and the route planning of material transportation are clarified to ensure that all equipment can be correctly installed at the predetermined location, the logistics path is unobstructed, and the production and logistics efficiency is improved.

[0059] Among them, when the space constraints are obtained based on the equipment size, plant layout, and logistics path, the equipment size, plant layout, and logistics path can be comprehensively considered to formulate specific space constraints, such as minimum safety distance, maximum carrying capacity, etc.

[0060] For example, an electronics manufacturing company plans to build a new SMT (surface mount technology) production line, focusing on the production of smartphone motherboards. The company's requirements include: annual production of 1 million motherboards, support for mixed-line production of multiple models, high degree of automation, product quality in line with international standards, and production cycle of no more than 48 hours. In order to meet the above functional requirements, the company lists the following equipment requirements: SMT placement machine: high precision, high speed, support for the placement of multiple components. Reflow oven: precise temperature control, support for multiple welding processes. Automatic optical inspection (AOI) equipment: high resolution, fast detection, support for multiple defect identification. Automated material handling system: flexible scheduling, support for 24-hour uninterrupted operation.

[0061] The factory area provided by the enterprise is 5,000 square meters, with a floor height of 8 meters and a column distance of 10 meters. The production line layout is required to be compact, the logistics path is smooth, and sufficient maintenance and expansion space is reserved. According to the functional requirements of the production line, the following process nodes are determined: PCB (Printed Circuit Board) boarding, solder paste printing, component mounting, reflow soldering, AOI inspection, and board packaging. Each process node clarifies the specific tasks (such as thickness control of solder paste printing), process nodes (such as the connection from solder paste printing to component mounting) and task dependencies (such as AOI inspection must be performed after reflow soldering).

[0062] According to the equipment requirements, the following equipment was selected: SMT placement machine: Model XYZ-123, placement speed 10,000 CPH (number of placements per hour), supports 0201 to 2020 components, and the interface supports MES (manufacturing execution system). Reflow oven: Model ABC-456, temperature range 150°C to 260°C, 10 heating sections, 2 cooling sections, and the interface supports PLC (programmable logic controller). AOI inspection equipment: Model DEF-789, resolution 2μm, inspection speed 1 second / board, and the interface supports industrial Ethernet. Automated material handling system: Model GHI-012, load capacity 500kg, travel speed 1.5m / s, and the interface supports WMS (warehouse management system).

[0063] According to the space layout requirements, the following space constraints were determined: The SMT placement machine covers an area of ​​10m², a height of 2.5m, and a safety distance of 1m is left in front and behind. The reflow oven covers an area of ​​15m², a height of 3m, and a maintenance passage of 1.5m is left on both sides. The track length of the material handling system is 50m, the width is 1m, and the turning radius is 5m. The internal logistics channel of the factory is 3m wide to ensure unobstructed passage of forklifts and other transportation tools.

[0064] In this embodiment, through a detailed analysis of the functional requirements, equipment requirements and spatial layout requirements of the production line, it is ensured that the selected equipment and layout scheme can fully meet the production goals of the enterprise, reducing unnecessary adjustments and rework. Structured data processing makes it faster to convert requirements into specific design schemes, shortening the pre-project preparation time. Through reasonable spatial layout and logistics path planning, the space utilization and logistics efficiency of the plant are maximized, and the construction and operation costs are reduced. Each process node and equipment has an independent functional module, which can be flexibly combined and adjusted according to actual needs to adapt to the changing market environment. During the production process, the equipment parameters and logistics paths can be quickly adjusted according to actual conditions (such as order changes, equipment failures) to maintain the continuity and stability of production. Standardized equipment interfaces and modular design make it easier to add new production lines or upgrade existing equipment in the future. Through continuous simulation testing and feedback mechanisms, the production process is continuously optimized to adapt to changes in technology and market demand. Modular and standardized design enhances the robustness of the system, and even if a certain device fails, the normal operation of other parts can be quickly restored. Based on the analysis of simulation data and actual production data, production strategies can be continuously improved to improve product quality and customer satisfaction.

[0065] In one embodiment of the present application, determining the target module type and target module parameters according to the structured data includes: Determine the demand parameters according to the structured data, and establish a module demand table according to the demand parameters, wherein the demand parameters include task parameters, equipment parameters and space parameters; Determine multiple candidate module types according to the task parameters, obtain the fitness corresponding to each of the candidate module types according to a preset weight coefficient, and use the candidate module type with the highest fitness as the target module type; Generate corresponding initial behavior parameters for the target module type according to the structured data, and optimize the initial behavior parameters to maximize the efficiency of the target module type, wherein the initial behavior parameters include execution speed and execution mode; According to the structured data, data interface parameters and physical interface parameters are configured, and the data interface parameters, the physical interface parameters and the optimized initial behavior parameters are used as the target module parameters.

[0066] Among them, task parameters refer to the specific requirements that describe the production task, such as processing time, accuracy, operation mode, etc. These parameters determine the behavior of the module when performing a specific task. Equipment parameters refer to the performance indicators that describe the equipment, such as power, speed, accuracy, load capacity, etc. These parameters affect the selection and configuration of the module. Space parameters refer to the layout requirements that describe the module in the physical space, such as floor space, height, safety distance, logistics channel, etc. These parameters ensure that the module can be reasonably installed and operated within the predetermined space.

[0067] Among them, according to the pre-set weight coefficient, the parameters of different candidate module types are weighted and scored to calculate the suitability of each candidate module. The weight coefficient reflects the importance of each parameter when selecting a module. Through quantitative evaluation, the module type that best suits the current needs can be selected to ensure that the selected module achieves the best balance in terms of performance, cost, space utilization, etc.

[0068] Among them, based on the structured data, a set of initial behavior parameters are generated for the selected target module type, such as execution speed, execution mode, etc. These parameters define the basic working mode of the module in actual operation.

[0069] Among them, the initial behavior parameters are adjusted and optimized through algorithms or simulation tools to improve the working efficiency of the module. The optimization process may include adjusting the execution speed, changing the execution mode, etc. Ensure that the module can complete the task with the highest efficiency in actual operation, reducing resource waste and time consumption.

[0070] The execution speed refers to the time required for the module to complete a task, such as the number of parts processed per minute, the speed of the conveyor belt, etc. The execution mode refers to the operation mode of the module when executing a task, such as continuous operation, intermittent operation, automatic / manual switching, etc.

[0071] Among them, data interface parameters are used to describe the data communication requirements between the module and external systems (such as MES, SCADA), such as communication protocol, data format, transmission rate, etc. Physical interface parameters are used to describe the physical connection requirements between the module and other equipment or facilities, such as power interface, signal line interface, mechanical connectors, etc.

[0072] In this embodiment, through quantitative evaluation and fitness calculation, it is ensured that the selected module achieves the best balance in terms of performance, cost, space utilization, etc., reducing unnecessary adjustments and rework. Structured data processing and intelligent algorithms greatly shorten the time for module selection and configuration, and improve the speed of project advancement. By optimizing the initial behavioral parameters, the working efficiency of the module is maximized, and resource waste and time consumption are reduced. Each module has an independent functional module, which can be flexibly combined and adjusted according to actual needs to adapt to the changing market environment. During the production process, the behavioral parameters of the module can be quickly adjusted according to actual conditions (such as order changes, equipment failures), maintaining the continuity and stability of production. Standardized data interface and physical interface design make it easier to add new modules or upgrade existing modules in the future.

[0073] In one embodiment of the present application, the standard production module includes a target device model, module behavior parameters, and a module interface. The generating of the standard production module according to the target module type and the target module parameters includes: Determine a plurality of components according to the target module type and the target module parameters, the plurality of components including a device model component, an interface component, a behavior component and an environment adaptation component, and assign capability parameters to each of the components to obtain a component set; Based on the component set, determining module behavior parameters corresponding to the module behavior, the module behavior parameters including behavior characteristics and execution rules; Determining a module interface according to the component set and the module behavior parameters; Based on the module behavior parameters and the module interface, the components in the component set are combined to obtain the standard production module.

[0074] Among them, the target device model refers to the specific model and specifications of the selected production equipment, including its physical structure, functional characteristics, technical parameters, etc. It is the core component of the standard production module. Module behavior parameters refer to the behavioral characteristics and operating rules that describe the module when performing tasks, such as execution speed, execution mode, working cycle, etc. These parameters determine the working mode and efficiency of the module. The module interface refers to the connection method between the module and other systems or devices, including data interface (such as communication protocol) and physical interface (such as power supply, signal line, mechanical connector). The module interface ensures that the module can be seamlessly integrated with the external system. By clarifying the target device model, module behavior parameters and module interface, it can be ensured that each standard production module has complete and independent functions, can operate efficiently in the entire production system and cooperate well with other modules.

[0075] Among them, according to the selected target module type and configuration parameters, multiple sub-components constituting the module are determined. These components are the basic building blocks of the module and together constitute a complete standard production module. Decomposing complex modules into multiple sub-components that are easy to manage and optimize facilitates flexible combination and adjustment to meet different production needs.

[0076] Among them, the device model component refers to the specific model, specifications and technical parameters of the target device, such as robots, machine tools, testing instruments, etc. The interface component refers to the data communication and physical connection between the module and other systems or devices, such as communication protocols, power interfaces, signal line interfaces, etc. The behavioral component refers to the behavioral logic and operating rules that define the module when performing tasks, such as control algorithms, execution modes, fault handling mechanisms, etc. The environmental adaptation component refers to the adaptive design that ensures that the module can operate normally in a specific production environment, such as environmental factors such as temperature, humidity, and vibration. By subdividing into different types of components, each part can be configured and optimized more accurately to ensure that the module can work stably and efficiently under various conditions.

[0077] Among them, capability parameters refer to the capability parameters assigned to each component, which describe the performance indicators and functional characteristics of the component under specific conditions. For example, the capability parameters of a device model component may include power, speed, accuracy, etc.; the capability parameters of an interface component may include communication rate, transmission distance, etc. By clarifying the capability parameters of each component, the performance of each component can be quantitatively evaluated to ensure that it meets the expected requirements and provide a basis for subsequent optimization.

[0078] Among them, the capability parameters of each component are comprehensively considered to determine the behavior parameters of the module when executing tasks, such as execution speed, execution mode, working cycle, etc. These parameters reflect the overall behavior characteristics and operation rules of the module. It ensures that the module can work efficiently in the predetermined way in actual operation, and can be dynamically adjusted as needed to adapt to different production tasks.

[0079] Among them, behavioral characteristics refer to the main features that describe the module when performing tasks, such as work efficiency, accuracy, reliability, etc. Execution rules refer to the operation logic and decision-making mechanism that define the module in a specific situation, such as startup sequence, fault handling, automatic / manual switching, etc.

[0080] Among them, based on the component set and module behavior parameters, determine the interface type and connection method between the module and other systems or devices, such as communication protocols, physical connectors, etc. Ensure that the module can be seamlessly integrated with the external system, realize the smooth transmission of information flow and material flow, and improve the overall coordination and interoperability of the system.

[0081] Among them, each component is combined according to the requirements of module behavior parameters and module interface to form a complete standard production module. This process involves hardware assembly, software configuration and system integration. By reasonably combining various components, it is ensured that the standard production module has complete and independent functions, can run efficiently in the entire production system and cooperate well with other modules.

[0082] In this embodiment, by subdividing into multiple components and assigning capability parameters to them, it is ensured that each component has the best performance, thereby improving the overall efficiency of the module. The standardized component design makes the assembly and configuration of the module easier, reducing the time and cost of customized development. By finely configuring the module behavior parameters, it is ensured that the module can complete the task efficiently and accurately in actual operation, reducing resource waste and time consumption.

[0083] In one embodiment of the present application, determining the functional area and the module position in the functional area according to the digital factory construction requirements includes: According to the requirements of digital factory construction, extract the functional area type, the module type and quantity required for the functional area, the connection relationship between the functional areas, and generate a functional area requirement table; Based on the regional land requirements and factory space constraints, the functional areas in the functional area requirement table are divided to generate a regional layout diagram; In the functional area, the module position of the standard production module is determined according to the module function and behavior parameters of the standard production module.

[0084] Among them, the functional area type refers to the different work areas divided according to the production process and tasks, such as processing area, assembly area, testing area, storage area, etc. Each functional area has specific responsibilities and operation content. The type and number of modules required for the functional area refer to the type and number of standard production modules that need to be installed in each functional area. These modules are the core units for realizing specific production tasks. The connection relationship between functional areas refers to the physical connection and information flow transmission method between different functional areas, such as material transmission path, data communication interface, etc. The connection relationship ensures the coordinated operation between the functional areas. By extracting and analyzing the needs of the functional areas in detail, we can fully understand the overall layout and production process of the factory, and provide a basis for subsequent space planning and module configuration.

[0085] Among them, the regional floor space requirement refers to the floor space required for each functional area in the actual factory building, including equipment, logistics channels, maintenance space, etc. The floor space requirement determines the size and shape of the functional area. Factory space constraints refer to the architectural parameters and space restrictions of the factory building, such as total area, floor height, column spacing, safety distance, etc. These constraints affect the layout of the functional area and the installation location of the module. Comprehensive consideration of the regional floor space requirements and factory space constraints can ensure that the division of functional areas and the layout of modules meet production requirements, make full use of existing space resources, and avoid problems caused by insufficient or unreasonable space.

[0086] Among them, based on the regional land demand and factory space constraints, the functional areas in the functional area demand table are divided and the regional layout diagram is generated, which means that according to the information in the functional area demand table, combined with the regional land demand and factory space constraints, the functional areas are reasonably divided using intelligent algorithms (such as genetic algorithms, simulated annealing, etc.), and a detailed regional layout diagram is generated. The layout diagram shows the specific location, size and relationship of each functional area. Through scientific and reasonable regional division, space utilization can be optimized, the length of logistics paths can be reduced, production and logistics efficiency can be improved, and smooth connection between functional areas can be ensured.

[0087] Among them, in the functional area, the module position of the standard production module is determined according to the module function and behavior parameters of the standard production module, which means that in the divided functional area, the specific installation position of each module is determined according to the functional characteristics and behavior parameters (such as execution speed, working range, interface type, etc.) of the standard production module. The location selection should take into account factors such as the collaborative work between modules, logistics path optimization, and maintenance convenience.

[0088] For example, an electronics manufacturing company plans to build a new SMT production line, focusing on the production of smartphone motherboards. According to the production process, the following functional areas are determined: PCB board area, solder paste printing area, component mounting area, reflow soldering area, AOI inspection area, and board packaging area. The types and quantities of modules required for the functional areas: PCB board area: 1 automatic board loading machine. Solder paste printing area: 1 solder paste printer. Component mounting area: 2 SMT placement machines. Reflow soldering area: 1 reflow oven. AOI inspection area: 1 automatic optical inspection equipment. Board packaging area: 1 automatic board unloading machine and 1 packaging machine. Connection relationship between functional areas: The functional areas are connected by automated material handling systems (such as conveyor belts and AGV carts) to ensure the smooth flow of materials and products between each process.

[0089] Based on the above information, a functional area requirement table as shown in Table 1 was generated, which clarified the type of each functional area, the required module type and quantity, and the connection relationship.

[0090] Table 1 Functional area requirements Functional Area Module Type quantity Connection relationship PCB board area Automatic loading machine 1 Connect to solder paste printing area Solder paste printing area Solder paste printer 1 Connect to component mounting area Component mounting area SMT placement machine 2 Connect to reflow soldering area Reflow soldering area Reflow Oven 1 Connect to AOI inspection area AOI inspection area Automatic optical inspection equipment 1 Connect to lower board packaging area Lower plate packaging area Automatic unloading machine, packaging machine 2 Finished product packaging Generate regional layout diagram based on regional land requirements and factory space constraints.

[0091] The area requirements can be, for example: PCB board area: 5m², height 2m, 1m safety distance left in front and back. Solder paste printing area: 8m², height 2.5m, 0.5m maintenance channel left on both sides. Component mounting area: 20m², height 3m, 1m maintenance channel left on both sides. Reflow soldering area: 15m², height 3m, 1.5m maintenance channel left on both sides. AOI inspection area: 10m², height 2.5m, 0.5m maintenance channel left on both sides. Lower board packaging area: 12m², height 2m, 1m safety distance left in front and back. The plant area is 5,000 square meters, with a floor height of 6 meters and a column distance of 8 meters. The production line layout is required to be compact, the logistics path is smooth, and sufficient maintenance and expansion space is reserved. The functional areas are divided using intelligent algorithms, and a detailed regional layout map is generated to ensure smooth connections between the functional areas and the shortest logistics path.

[0092] In the functional areas that have been divided, the specific installation location of each module is determined according to the functional characteristics and behavioral parameters of the standard production modules. For example: PCB loading machine: installed at the entrance of the PCB loading area, close to the starting point of the conveyor belt, to ensure that the materials can quickly enter the next process. Solder paste printer: installed in the center of the solder paste printing area, with sufficient maintenance space on both sides to facilitate the replacement of solder paste templates. SMT placement machine: two placement machines are installed side by side in the component placement area, with a conveyor belt in the middle to ensure that materials can flow in and out continuously. Reflow oven: installed in the center of the reflow soldering area, with 1.5m maintenance channels on both sides to ensure good heat dissipation of the equipment and easy maintenance. Automatic optical inspection equipment: installed at the end of the AOI inspection area, close to the lower board packaging area, to ensure that the finished products after inspection can directly enter the packaging link. Automatic unloading machine and packaging machine: installed at the exit of the lower board packaging area to ensure that the finished products can be quickly packaged and shipped out.

[0093] In this embodiment, by extracting the requirements of functional areas in detail, it is ensured that the division of functional areas and the layout of modules meet production requirements, fully utilize existing space resources, and reduce unnecessary adjustments and rework. Reasonable regional layout and module location arrangement shorten the logistics path, reduce material transportation time and cost, and improve overall production efficiency. The application of intelligent algorithms makes regional division and module location determination faster, shortens the project preparation time, and speeds up the progress of factory construction.

[0094] In one embodiment of the present application, the production line includes a material line and a production sequence line, the time parameter includes a processing time parameter and a logistics time parameter, and the network nodes and edges of the virtual plant module network are used to construct the production line, and the production nodes and paths of the production line are assigned time parameters, including: Determine a task node sequence based on the network nodes and edges of the virtual plant module network, and construct the production sequence moving line based on the task node sequence; According to the connection relationship of the task nodes, the shortest path is selected in the virtual plant module network to obtain the material movement line; Acquire the processing time parameter from the behavior parameter of the standard production module, and assign the processing time parameter to the production node of the production line; The logistics time parameter is obtained from the logistics parameter of the edge, and the logistics time parameter is assigned to the path of the production line.

[0095] Among them, the material flow line refers to the flow path of materials in the factory, including the entry of raw materials, transmission during the processing process, and the output of finished products. The design of the material flow line needs to consider factors such as logistics efficiency, transportation costs and time. The production sequence flow line refers to the flow order of products between various processes, that is, the entire production process from raw materials to semi-finished products to finished products. The production sequence flow line ensures that each process can be carried out according to the predetermined time and order, avoiding production bottlenecks and waste of resources.

[0096] Among them, the processing time parameter refers to the time required for each standard production module to complete a specific task, such as machine processing time, manual operation time, etc. The processing time parameter directly affects the production rhythm and capacity. The logistics time parameter refers to the time required for materials to be transferred between different processes, including loading and unloading time, transportation time, waiting time, etc. The logistics time parameter affects the overall production cycle and inventory level.

[0097] Among them, the virtual factory module network refers to the abstraction of all production modules (such as equipment and workstations) in the factory as nodes in the network, and the connection relationship between modules (such as material transmission and data communication) is represented as the edge in the network. The task node sequence refers to the determination of the execution order of each task node (i.e., production module) according to the requirements of the production process. By constructing a virtual factory module network and determining the task node sequence, the logical relationship of the production process can be clearly demonstrated, providing a basis for the subsequent production line design.

[0098] Among them, according to the task node sequence, each production module is connected in a predetermined order to form a complete production sequence line. This line clarifies the sequence and connection method of each process, ensuring the continuity and smoothness of production. The construction of the production sequence line makes the production process more orderly, reduces conflicts and waiting time between processes, and improves production efficiency.

[0099] In the virtual plant module network, the shortest path algorithm is used to select the optimal material transmission path based on the connection relationship between the task nodes to form a material flow line. The selection of the shortest path not only considers the physical distance, but also factors such as logistics time and transportation cost. By selecting the shortest path, the material transmission time can be shortened to the maximum extent, the transportation cost can be reduced, the logistics efficiency can be optimized, and the overall production efficiency can be improved.

[0100] In this embodiment, by selecting the shortest path, the material transmission time is shortened to the maximum extent, the transportation cost is reduced, and the logistics efficiency is improved. By assigning processing time parameters and logistics time parameters, the refined management of the production process is realized, the seamless connection between each process is ensured, and the production rhythm is optimized. The reasonable production sequence dynamic line design reduces the waiting time between processes, improves production efficiency, and shortens the overall production cycle.

[0101] In one embodiment of the present application, after constructing a production line based on the network nodes and edges of the virtual plant module network, assigning time parameters to the production nodes and paths of the production line, and obtaining a production process simulation model, the method further includes: In a pre-built virtual environment, running the production process simulation model to simulate the actual production process; Acquiring simulation data of the actual production process, wherein the simulation data includes equipment utilization, logistics efficiency, and bottleneck nodes; Optimization suggestions are generated based on the equipment utilization, logistics efficiency, and bottleneck nodes. The optimization suggestions include adjusting equipment operating parameters, optimizing material flow, and modifying equipment layout.

[0102] The pre-built virtual environment refers to a digital virtual factory environment built using simulation software based on the digital factory construction requirements and virtual factory module network. This environment can simulate various aspects of the actual production process, such as equipment operation, material flow, and personnel operation. By conducting simulation tests in a virtual environment, potential problems can be discovered before actual construction, the production process can be optimized, and the time and cost of actual construction and debugging can be reduced.

[0103] Among them, simulating the actual production process means running a production process simulation model in a virtual environment to simulate the execution of each process in the actual production process, including equipment operation, material transmission, personnel activities, etc. The simulation process can be simulated multiple times according to different production scenarios to evaluate the effects of various solutions. By simulating the actual production process, potential problems such as equipment failure, logistics bottlenecks, and insufficient personnel can be discovered and solved in advance to ensure that actual production can proceed smoothly.

[0104] The simulation data of the actual production process refers to various production index data obtained from the simulation process, which is used to evaluate the performance of the production system. These data include but are not limited to equipment utilization, logistics efficiency, bottleneck nodes, etc. By analyzing the simulation data, we can fully understand the operation status of the production system, identify areas that need improvement, and provide a basis for optimizing the production process.

[0105] Among them, equipment utilization refers to the proportion of the actual working time of the equipment in a certain period of time to the total available time. Equipment utilization reflects the working intensity and efficiency of the equipment. High equipment utilization means that the equipment is fully utilized and the production efficiency is high; low equipment utilization may indicate that the equipment is idle or faulty and needs to be adjusted and optimized.

[0106] Among them, logistics efficiency refers to the speed and accuracy of material transmission within the factory, including loading and unloading time, transportation time, waiting time, etc. Logistics efficiency directly affects the entire production cycle and inventory level. An efficient logistics system can shorten the production cycle, reduce inventory backlogs, reduce transportation costs, and improve overall production efficiency.

[0107] The bottleneck node refers to the key link in the production process that causes the entire process to stagnate or slow down, usually due to the inefficiency of a certain equipment, a certain workstation or a certain logistics path. Identifying and eliminating bottleneck nodes is the key to improving production efficiency. Bottleneck problems can be solved by optimizing equipment configuration, adjusting logistics paths, etc.

[0108] Among them, adjusting equipment operating parameters means adjusting the equipment operating parameters (such as speed, temperature, pressure, etc.) according to the simulation results to improve the equipment's working efficiency and stability. Optimizing material flow means replanning the material transmission path to reduce unnecessary transportation distance and waiting time and improve logistics efficiency. Modifying equipment layout means adjusting the equipment's installation location according to the simulation results, optimizing the division of functional areas, and improving space utilization and production efficiency.

[0109] In this embodiment, by performing simulation tests in a virtual environment, potential problems can be discovered before actual construction, avoiding rework and delays caused by design defects or equipment failures. By analyzing the simulation data, bottleneck nodes in the production process can be identified, and targeted optimization suggestions can be put forward to improve production efficiency and product quality. Simulation testing allows enterprises to verify the feasibility of the production system before actual construction, reducing the time and cost of actual debugging.

[0110] It can be seen from the above embodiments that obtaining the requirements for building a digital factory can better predict possible changes in the future (such as product line expansion, process improvement, etc.), so that flexibility can be taken into account at the beginning of the design, which is convenient for subsequent adjustments; the structured data format is easy to be parsed and operated by the computer system, supporting rapid iteration and updating. When the requirements change, they can be quickly reflected in the design by modifying the structured data without having to restart the entire design process; by selecting the optimal module type and configuration parameters, the best solution can be found in a short time, avoiding the trial-and-error exploration in the traditional method; the modular design allows different modules to be combined according to different requirements to form a diversified production system, and each module can be independently developed, tested and optimized, reducing the complexity of the overall system; the standard production module simplifies the manufacturing and installation process, reducing the additional cost and time consumption caused by customization; because the standard production module is highly customizable and extensible, the function and interface of the module can be flexibly adjusted according to the actual situation to meet the needs of different application scenarios, thereby realizing efficient, flexible and adaptive digital factory construction.

[0111] In one embodiment of the present application, a digital factory construction device is also provided. Figure 3 is a schematic diagram of a digital factory construction device shown in an exemplary embodiment of the present application, see Figure 3 , the device comprises: The demand acquisition unit 301 is used to acquire the digital factory construction demand; A parameter determination unit 302 is used to convert the digital factory construction requirements into structured data, and determine the target module type and target module parameters according to the structured data; A standard production module generating unit 303, configured to generate a standard production module according to the target module type and the target module parameters; The network construction unit 304 is used to determine the functional areas and the module positions in the functional areas according to the digital factory construction requirements, and arrange the standard production modules to the functional areas and the module positions to obtain a virtual factory module network, wherein the network nodes in the virtual factory module network are the standard production modules, and the edges in the virtual factory module network are the connection relationships between the standard production modules; The simulation model construction unit 305 is used to construct a production line based on the network nodes and edges of the virtual factory module network, and assign time parameters to the production nodes and paths of the production line to obtain a production process simulation model, wherein the production process simulation model is used to guide the construction of an actual factory.

[0112] The digital factory construction device in the embodiment of the present application can better predict possible future changes (such as product line expansion, process improvement, etc.) by obtaining the digital factory construction requirements, so as to take flexibility into consideration at the beginning of the design, which is convenient for subsequent adjustments; the structured data format is easy to be parsed and operated by the computer system, supports rapid iteration and update, and when the requirements change, it can be quickly reflected in the design by modifying the structured data without having to restart the entire design process; by selecting the optimal module type and configuration parameters, the best solution can be found in a short time, avoiding the trial and error exploration in the traditional method; the modular design allows different modules to be combined according to different requirements to form a diversified production system, and each module can be independently developed, tested and optimized, reducing the complexity of the overall system; the standard production module simplifies the manufacturing and installation process, reducing the additional cost and time consumption caused by customization; because the standard production module is highly customizable and extensible, the function and interface of the module can be flexibly adjusted according to the actual situation to meet the needs of different application scenarios, thereby realizing efficient, flexible and adaptive digital factory construction.

[0113] The specific embodiments of the digital factory construction device in the present application can refer to the examples shown in the above-mentioned digital factory construction method, which will not be repeated here.

[0114] In one embodiment of the present application, an electronic device for implementing the above-mentioned digital factory construction method is also provided. The electronic device includes a memory and a processor, the memory stores a computer program, and the processor is configured to execute the above-mentioned digital factory construction method through the computer program.

[0115] See also Figure 4 , Figure 4 404 is a schematic diagram of the structure of an electronic device shown in an exemplary embodiment of the present application. The computer system 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage part 408 to the random access memory (RAM) 403, such as executing the method described in the above embodiment. Various programs and data required for system operation are also stored in RAM 403. CPU 401, ROM 402 and RAM 403 are connected to each other via bus 404. Input / output (I / O) interface 405 is also connected to bus 404.

[0116] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed so that a computer program read therefrom is installed into the storage section 408 as needed.

[0117] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 409, and / or installed from a removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, various functions defined in the system of the present application are executed.

[0118] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier, in which a computer-readable computer program is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. A computer program contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0119] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0120] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0121] Another aspect of the present application further provides a computer-readable storage medium, the computer-readable storage medium including a stored computer program, wherein the computer program executes the above-mentioned digital factory construction method when it is run. The computer-readable storage medium may be included in the electronic device described in the above embodiment, or may exist independently without being assembled into the electronic device.

[0122] Another aspect of the present application also provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the digital factory construction method provided in each of the above embodiments.

[0123] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present invention. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A method for building a digital factory, characterized in that: The method comprises: Obtain the requirements for building a digital factory; Converting the digital factory construction requirements into structured data, and determining the target module type and target module parameters according to the structured data; Generate a standard production module according to the target module type and the target module parameters; According to the requirements for building the digital factory, functional areas and module positions in the functional areas are determined, and the standard production modules are arranged in the functional areas and the module positions to obtain a virtual plant module network, wherein the network nodes in the virtual plant module network are the standard production modules, and the edges in the virtual plant module network are the connection relationships between the standard production modules; Based on the network nodes and edges of the virtual factory module network, a production line is constructed, and time parameters are assigned to the production nodes and paths of the production line to obtain a production process simulation model, wherein the production process simulation model is used to guide the construction of an actual factory.

2. The digital factory construction method according to claim 1, characterized in that: The digital factory construction requirements include production line function requirements, equipment requirements, and space layout requirements. The structured data includes production process nodes, equipment model requirements, and space constraints. The digital factory construction requirements are converted into structured data, including: Determine the production tasks, process nodes, and task dependencies according to the functional requirements of the production line, and obtain the production process nodes according to the production tasks, process nodes, and task dependencies; According to the device requirements, determine the device type, functional parameters, and interface requirements, and obtain the device model requirements according to the device type, functional parameters, and interface requirements; According to the spatial layout requirements, the equipment size, plant layout, and logistics path are determined, and according to the equipment size, plant layout, and logistics path, the spatial constraints are obtained.

3. The digital factory construction method according to claim 2, characterized in that: The determining the target module type and target module parameters according to the structured data includes: Determine the demand parameters according to the structured data, and establish a module demand table according to the demand parameters, wherein the demand parameters include task parameters, equipment parameters and space parameters; Determine multiple candidate module types according to the task parameters, obtain the fitness corresponding to each of the candidate module types according to a preset weight coefficient, and use the candidate module type with the highest fitness as the target module type; Generate corresponding initial behavior parameters for the target module type according to the structured data, and optimize the initial behavior parameters to maximize the efficiency of the target module type, wherein the initial behavior parameters include execution speed and execution mode; According to the structured data, data interface parameters and physical interface parameters are configured, and the data interface parameters, the physical interface parameters and the optimized initial behavior parameters are used as the target module parameters.

4. The digital factory construction method according to claim 1, characterized in that: The standard production module includes a target device model, module behavior parameters, and a module interface. The generating of the standard production module according to the target module type and the target module parameters includes: Determine a plurality of components according to the target module type and the target module parameters, the plurality of components including a device model component, an interface component, a behavior component and an environment adaptation component, and assign capability parameters to each of the components to obtain a component set; Based on the component set, determining module behavior parameters corresponding to the module behavior, the module behavior parameters including behavior characteristics and execution rules; Determining a module interface according to the component set and the module behavior parameters; Based on the module behavior parameters and the module interface, the components in the component set are combined to obtain the standard production module.

5. The method for constructing a digital factory according to claim 1, characterized in that: Determining the functional area and the module position in the functional area according to the digital factory construction requirements includes: According to the requirements of digital factory construction, extract the functional area type, the module type and quantity required for the functional area, the connection relationship between the functional areas, and generate a functional area requirement table; Based on the regional land requirements and factory space constraints, the functional areas in the functional area requirement table are divided to generate a regional layout diagram; In the functional area, the module position of the standard production module is determined according to the module function and behavior parameters of the standard production module.

6. The method for constructing a digital factory according to claim 1, characterized in that: The production line includes a material line and a production sequence line, the time parameters include a processing time parameter and a logistics time parameter, and the network nodes and edges of the virtual plant module network are used to construct the production line, and the production nodes and paths of the production line are assigned time parameters, including: Determine a task node sequence based on the network nodes and edges of the virtual plant module network, and construct the production sequence moving line based on the task node sequence; According to the connection relationship of the task nodes, the shortest path is selected in the virtual plant module network to obtain the material movement line; Acquire the processing time parameter from the behavior parameter of the standard production module, and assign the processing time parameter to the production node of the production line; The logistics time parameter is obtained from the logistics parameter of the edge, and the logistics time parameter is assigned to the path of the production line.

7. The method for constructing a digital factory according to claim 1, characterized in that: After constructing a production line based on the network nodes and edges of the virtual plant module network and assigning time parameters to the production nodes and paths of the production line to obtain a production process simulation model, the method further includes: In a pre-built virtual environment, running the production process simulation model to simulate the actual production process; Acquiring simulation data of the actual production process, wherein the simulation data includes equipment utilization, logistics efficiency, and bottleneck nodes; Optimization suggestions are generated based on the equipment utilization, logistics efficiency, and bottleneck nodes. The optimization suggestions include adjusting equipment operating parameters, optimizing material flow, and modifying equipment layout.

8. A digital factory construction device, characterized in that: The device comprises: Demand acquisition unit, used to obtain digital factory construction requirements; A parameter determination unit, used to convert the digital factory construction requirements into structured data, and determine the target module type and target module parameters according to the structured data; A standard production module generating unit, used for generating a standard production module according to the target module type and the target module parameters; A network construction unit is used to determine the functional areas and the module positions in the functional areas according to the digital factory construction requirements, and arrange the standard production modules to the functional areas and the module positions to obtain a virtual plant module network, wherein the network nodes in the virtual plant module network are the standard production modules, and the edges in the virtual plant module network are the connection relationships between the standard production modules; The simulation model construction unit is used to construct a production line based on the network nodes and edges of the virtual factory module network, and assign time parameters to the production nodes and paths of the production line to obtain a production process simulation model, wherein the production process simulation model is used to guide the construction of an actual factory.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein the computer program executes the digital factory construction method according to any one of claims 1 to 7 when running.

10. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the digital factory construction method according to any one of claims 1 to 7 through the computer program.

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