Factory simulation model construction method and system based on digital twinning

Abstract

The invention relates to a factory simulation model construction method and system based on digital twinning, and belongs to the technical field of digital twinning construction models. The method comprises the following steps: acquiring equipment data and production data, and constructing an intelligent wood structure factory physical entity model according to the equipment data and the production data; mapping the intelligent wood structure factory physical entity model through Flex-sim three-dimensional modeling software to obtain an intelligent wood structure factory simulation model; and according to the intelligent wood structure factory physical entity model and the intelligent wood structure factory simulation model, performing information interaction through a Socket communication model to obtain the digital twin intelligent wood structure factory. The factory simulation model construction based on digital twinning is realized, and the model construction efficiency and expandability are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of digital twin construction models, and specifically relates to a method and system for constructing a factory simulation model based on digital twins. Background Art

[0002] As a traditional construction method, wooden structure factories are widely used in the construction field. However, traditional wooden structure factories often use manual operations, which makes it difficult to ensure production quality, low production efficiency, and great safety hazards. With the rapid development of robotics technology, wooden structure factories have become smart wooden structure factories that can quickly produce standardized wooden structures and customize personalized wooden structures with the help of the flexibility of robotic arms, promoting the green, safe and rapid development of the construction industry. However, the establishment and operation management of smart wooden structure factories is a complex system engineering, and the evaluation and optimization of their design, operation monitoring, and decision-making scheduling is a problem.

[0003] In view of the above problems, using simulation technology to build a simulation model of a wood structure factory to simulate the establishment and operation management of a smart wood structure factory is a good solution. However, traditional simulation technology is an "offline" simulation. The simulation model relies on data to run and lacks real-time information interaction with the actual physical system. It cannot meet the needs of operation monitoring and management decision-making of smart wood structure factories. Digital twin is a technology that uses digital means to build a virtual model corresponding to the physical entity in a virtual space. It is an important supporting technology for building a factory simulation model, but the definition varies in different application scenarios and needs to be adjusted according to specific needs. Summary of the invention

[0004] In order to solve the above problems existing in the prior art, the present invention provides a method and system for constructing a factory simulation model based on digital twins.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A method for constructing a factory simulation model based on digital twins, comprising:

[0007] Acquire equipment data and production data, and construct a physical entity model of the smart wooden structure factory according to the equipment data and the production data;

[0008] The physical entity model of the smart wooden structure factory is mapped by Flex-sim three-dimensional modeling software to obtain a simulation model of the smart wooden structure factory;

[0009] The digital twin smart wooden structure factory is obtained by exchanging information between the physical entity model of the smart wooden structure factory and the simulation model of the smart wooden structure factory through the Socket communication model.

[0010] Preferably, the equipment data includes equipment type, equipment operating status, equipment service life, equipment failure record, and equipment maintenance history; the production data includes production process, production process, equipment scheduling, and material flow.

[0011] Preferably, the physical entity model of the smart wooden structure factory includes a pre-processing area, a processing area and a post-processing area, and the operation process of the physical entity model of the smart wooden structure factory includes:

[0012] S101: obtaining preliminary processed raw materials according to the raw materials passing through the pre-processing zone processing model;

[0013] S102: obtaining a semi-finished component through a processing model in a processing area according to the preliminary processing of the raw materials;

[0014] S103: obtaining a finished wood component by processing the model in a post-processing area according to the semi-finished component;

[0015] S104: Obtaining the physical entity model of the smart wooden structure factory according to the steps S101 to S103.

[0016] Preferably, the step of obtaining the preliminary processed raw materials according to the raw materials passing through the pre-processing zone processing model comprises:

[0017] Obtain the raw materials from the raw material storage area, and collect the moisture content of the raw materials through a humidity sensor;

[0018] A moisture content threshold is preset, and raw materials with moisture content meeting the standard are obtained by judging the moisture content state according to the moisture content threshold and the moisture content of the raw materials;

[0019] The processing status judgment includes judging whether the moisture content of the raw material exceeds the moisture content threshold, if yes, then the raw material is not processed; if no, then the raw material with moisture content meeting the standard is obtained;

[0020] The bending degree of the raw material with qualified moisture content is collected by a laser sensor, a bending degree threshold is preset, and the bending state and the raw material with qualified moisture content are obtained by bending state judgment according to the bending degree threshold and the bending degree of the raw material with qualified moisture content;

[0021] The bending state judgment includes judging whether the bending degree of the raw material with qualified moisture content exceeds the bending degree threshold value. If yes, the raw material with qualified moisture content is not processed; if no, the bending state and the raw material with qualified moisture content are obtained;

[0022] The bending state and cracking degree of the raw materials with qualified moisture content are collected by a laser sensor, a cracking degree threshold is preset, and the raw materials meeting the processing requirements are obtained by cracking state judgment according to the bending state and cracking degree of the raw materials with qualified moisture content and the cracking degree threshold;

[0023] The cracking state judgment includes judging whether the cracking degree of the raw material with bending state and moisture content meeting the standard exceeds the cracking degree threshold. If yes, the raw material with bending state and moisture content meeting the standard is not processed; if no, the raw material meeting the processing requirements is obtained;

[0024] Obtaining the thickness standard of the raw material, and obtaining the preliminary processed raw material through the gluing and grinding area according to the raw material meeting the processing requirements and the thickness standard of the raw material;

[0025] The gluing and polishing area processing includes a gluing robot arm performing a gluing process on the raw material that meets the processing requirements according to the raw material thickness standard to obtain a glued raw material; and a polishing robot arm obtains the preliminarily processed raw material by performing a leveling process on the glued raw material.

[0026] Preferably, obtaining a semi-finished component by processing the raw material through a processing area processing model according to the preliminary processing comprises:

[0027] According to the preliminary processing of raw materials, classified materials for processing are obtained by classification, and the classified materials for processing include plate components and beam-column components;

[0028] Processing the plate component through a plate component processing line to obtain a semi-finished plate component;

[0029] Processing the beam-column components through a beam-column component processing assembly line to obtain a semi-finished beam-column assembly;

[0030] The semi-finished product assembly is formed according to the semi-finished product plate assembly and the semi-finished product beam-column assembly.

[0031] Preferably, the step of obtaining a finished wood component by processing the model in a post-processing zone according to the semi-finished component comprises:

[0032] Correcting the semi-finished product component through a correction process to obtain a corrected semi-finished product component;

[0033] Obtaining a storage-resistant semi-finished component by spraying the modified semi-finished component;

[0034] The finished wood component is obtained by assembling the storage-resistant semi-finished product components.

[0035] Preferably, mapping the physical entity model of the smart wooden structure factory by using Flex-sim three-dimensional modeling software to obtain a simulation model of the smart wooden structure factory includes:

[0036] The physical entity model of the smart wood structure factory includes entities and operation processes; a virtual entity is obtained by manual modeling based on the entity;

[0037] The Flex-sim three-dimensional modeling software establishes a connection relationship between the virtual entities according to the operation process to obtain the simulation model of the smart wooden structure factory.

[0038] A digital twin-based factory simulation model construction system and a digital twin-based factory simulation model construction method include a model construction module, a model mapping module, and a model communication module, including:

[0039] The model building module is used to obtain equipment data and production data, and build a physical entity model of the smart wooden structure factory according to the equipment data and the production data;

[0040] The model mapping module is used to map the physical entity model of the smart wooden structure factory through the Flex-sim three-dimensional modeling software to obtain a simulation model of the smart wooden structure factory;

[0041] The model communication module is used to obtain a digital twin smart wooden structure factory by exchanging information between the physical entity model of the smart wooden structure factory and the simulation model of the smart wooden structure factory through a Socket communication model.

[0042] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for constructing a factory simulation model based on digital twins is implemented.

[0043] A storage medium containing computer executable instructions, which are used to execute the above-mentioned digital twin-based factory simulation model construction method when executed by a computer processor.

[0044] The beneficial effects of the present invention are:

[0045] (1) The construction of the physical entity model of the smart timber structure factory can accurately reflect the workflow of the smart timber structure factory, providing a physical foundation for the subsequent construction of the smart timber structure factory simulation model based on digital twins, and increasing the authenticity and reliability of the construction of the smart timber structure factory simulation model.

[0046] (2) The physical model of the smart timber factory is mapped to a simulation model through the FlexSim 3D modeling software, which allows the model to be constructed without specific data. This not only greatly improves the efficiency of model construction, but also enhances the scalability of the virtual model, providing greater flexibility and convenience for subsequent optimization operations based on the simulation model.

[0047] (3) The information interaction between the physical model and the virtual model is realized through the Socket communication model. The physical model monitors the virtual model and can send control instructions to the virtual model. The parameter configuration and strategy in the physical model can be verified and optimized through simulation testing of the simulation model, and then optimized on the physical model, which can reduce costs while improving optimization efficiency and quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0049] Figure 1 A schematic flow chart of a method for constructing a factory simulation model based on digital twins according to the present invention. DETAILED DESCRIPTION

[0050] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0051] See also Figure 1 , a method for constructing a factory simulation model based on digital twins, comprising:

[0052] S1: Acquire equipment data and production data, and construct a physical entity model of the smart wooden structure factory according to the equipment data and the production data;

[0053] S2: Mapping the physical entity model of the smart wooden structure factory through Flex-sim three-dimensional modeling software to obtain a simulation model of the smart wooden structure factory;

[0054] S3: A digital twin smart wooden structure factory is obtained by exchanging information between the physical entity model of the smart wooden structure factory and the simulation model of the smart wooden structure factory through a Socket communication model.

[0055] In this embodiment, the overall layout of the physical entity model of the smart wood structure factory is divided into three parts: pre-processing area, processing area and post-processing area. The pre-processing area is an area where raw materials are stored and pre-processed; the pre-processing includes raw material storage, raw material testing and raw material polishing. The processing area is an area where raw materials are milled and cut according to customized requirements and the processed components are stored. The post-processing area is an area where components are assembled, secondary processed and painted.

[0056] Specifically, the equipment data includes equipment type, equipment operating status, equipment service life, equipment failure record, and equipment maintenance history.

[0057] Specifically, the production data includes production process, production process, equipment scheduling, and material flow.

[0058] In step S1, the physical entity model of the smart wooden structure factory includes a pre-processing area, a processing area and a post-processing area. The operation process of the physical entity model of the smart wooden structure factory includes:

[0059] S101: obtaining preliminary processed raw materials according to the raw materials passing through the pre-processing zone processing model;

[0060] S102: obtaining a semi-finished component through a processing model in a processing area according to the preliminary processing of the raw materials;

[0061] S103: obtaining a finished wood component by processing the model in a post-processing area according to the semi-finished component;

[0062] S104: Obtaining the physical entity model of the smart wooden structure factory according to the steps S101 to S103.

[0063] In step S101, the pre-processing area processing model includes:

[0064] S101-1: Obtain the raw materials from the raw material storage area, and collect the moisture content of the raw materials through a humidity sensor;

[0065] S101-2: Preset a moisture content threshold, and determine the moisture content of the raw material by moisture content status according to the moisture content threshold and the moisture content of the raw material to obtain the raw material with moisture content that meets the standard;

[0066] The processing status judgment includes judging whether the moisture content of the raw material exceeds the moisture content threshold, if yes, then the raw material is not processed; if no, then the raw material with moisture content meeting the standard is obtained;

[0067] S101-3: collecting the bending degree of the raw material with qualified moisture content through a laser sensor, presetting a bending degree threshold, and obtaining the bending state and the raw material with qualified moisture content through bending state judgment according to the bending degree threshold and the bending degree of the raw material with qualified moisture content;

[0068] The bending state judgment includes judging whether the bending degree of the raw material with qualified moisture content exceeds the bending degree threshold value. If yes, the raw material with qualified moisture content is not processed; if no, the bending state and the raw material with qualified moisture content are obtained;

[0069] S101-4: Collect the bending state and cracking degree of the raw material with qualified moisture content through a laser sensor, preset a cracking degree threshold, and obtain raw materials that meet the processing requirements through cracking state judgment based on the bending state and cracking degree of the raw material with qualified moisture content and the cracking degree threshold;

[0070] The cracking state judgment includes judging whether the cracking degree of the raw material with bending state and moisture content meeting the standard exceeds the cracking degree threshold. If yes, the raw material with bending state and moisture content meeting the standard is not processed; if no, the raw material meeting the processing requirements is obtained;

[0071] S101-5: Obtaining a raw material thickness standard, and obtaining the preliminarily processed raw material through the gluing and polishing area according to the raw material meeting the processing requirements and the raw material thickness standard;

[0072] The gluing and polishing area processing includes a gluing robot arm performing a gluing process on the raw material that meets the processing requirements according to the raw material thickness standard to obtain a glued raw material; and a polishing robot arm obtains the preliminarily processed raw material by performing a leveling process on the glued raw material.

[0073] In step S102, the processing area processing model includes:

[0074] S102-1: Classifying the initially processed raw materials to obtain classified processing materials, wherein the classified processing materials include plate components and beam-column components;

[0075] S102-2: Processing the plate component through a plate component processing line to obtain a semi-finished plate component;

[0076] S102-3: Processing the beam-column components through a beam-column component processing line to obtain semi-finished beam-column assemblies;

[0077] S102-4: Construct the semi-finished assembly according to the semi-finished plate assembly and the semi-finished beam-column assembly.

[0078] Specifically, the sheet material component processing line includes cutting, punching, nailing and storage of semi-finished sheet material components.

[0079] Specifically, the beam-column component processing line includes cutting, drilling, milling and storage of semi-finished beam-column components.

[0080] In this embodiment, the processing area includes a plate component processing line and a beam-column component processing line, and the two lines are arranged side by side. The plate component processing line includes a cutting process area, a hole-punching process area, a nailing process area, and a finished product storage area; the beam-column component processing line includes a cutting process area, a hole-punching process area, a milling process area, and a finished product storage area; the milling process area of ​​the beam-column component processing line and the hole-punching process area of ​​the plate component processing line are connected by a conveyor belt. The processing area is equipped with four robotic arms, robotic arm slide rails, a processing platform, and a component temporary retention platform.

[0081] In step S103, the post-processing area processing model includes:

[0082] S103-1: Correcting the semi-finished component through a correction process to obtain a corrected semi-finished component;

[0083] S103-2: obtaining a storable semi-finished component by spraying the modified semi-finished component;

[0084] S103-3: The finished wooden component is obtained by assembling the storable semi-finished components.

[0085] Specifically, the spraying operation includes polishing and anti-corrosion of the modified semi-finished component.

[0086] In this embodiment, the components are transported to the post-processing area for processing by the AGV trolley and the mechanical arms in the finished product storage area. The post-processing area includes a comprehensive processing area, a spraying area, and an assembly area; the semi-finished components are subjected to secondary processing and correction processes in the comprehensive processing area to obtain the corrected semi-finished components; the corrected semi-finished components are subjected to component polishing and anti-corrosion treatment in the spraying area to obtain the storable semi-finished components; according to the storable semi-finished components, the structure is assembled in the assembly area by the gripper mechanical arm and the suction cup mechanical arm to obtain the finished wood components.

[0087] In this embodiment, a visual positioning system and an end tool holder are arranged in the pre-processing area, the processing area and the post-processing area.

[0088] In step S2, mapping the physical entity model of the smart wooden structure factory by using Flex-sim three-dimensional modeling software to obtain a simulation model of the smart wooden structure factory includes:

[0089] S201: The physical entity model of the smart wooden structure factory includes an entity and an operation process; a virtual entity is obtained by manual modeling according to the entity;

[0090] S202: Flex-sim three-dimensional modeling software establishes a connection relationship between the virtual entities according to the operation process to obtain the intelligent wooden factory simulation model.

[0091] Specifically, the entities include a processing robot arm, a processing platform, a conveyor belt, a visual positioning device, an end tool rack, a raw material storage rack, an AGV mobile platform, a slide rail, and a fence.

[0092] A digital twin-based factory simulation model construction system and a digital twin-based factory simulation model construction method include a model construction module, a model mapping module, and a model communication module, including:

[0093] The model building module is used to obtain equipment data and production data, and build a physical entity model of the smart wooden structure factory according to the equipment data and the production data;

[0094] The model mapping module is used to map the physical entity model of the smart wooden structure factory through the Flex-sim three-dimensional modeling software to obtain a simulation model of the smart wooden structure factory;

[0095] The model communication module is used to obtain a digital twin smart wooden structure factory by exchanging information between the physical entity model of the smart wooden structure factory and the simulation model of the smart wooden structure factory through a Socket communication model.

[0096] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: 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 or 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 this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device.

[0097] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media 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.

[0098] The program code included on the computer readable medium can be transmitted with any appropriate medium, including but not limited to wireless, electric wire, optical cable, RF, etc., or any suitable combination of the above. The computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or their combinations, and the programming language includes object-oriented programming languages-such as Java, Smalltalk, C++, and also includes conventional procedural programming languages-such as "C" language or similar programming languages. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0099] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A method for constructing a factory simulation model based on digital twins, characterized in that: The following steps are involved: Acquire equipment data and production data, and construct a physical entity model of the smart wooden structure factory according to the equipment data and the production data; The physical entity model of the smart wooden structure factory is mapped by Flex-sim three-dimensional modeling software to obtain a simulation model of the smart wooden structure factory; The digital twin smart wooden structure factory is obtained by exchanging information between the physical entity model of the smart wooden structure factory and the simulation model of the smart wooden structure factory through the Socket communication model.

2. The method for constructing a factory simulation model based on digital twins according to claim 1, characterized in that: The equipment data includes equipment type, equipment operating status, equipment service life, equipment failure record, and equipment maintenance history; the production data includes production process, production process, equipment scheduling, and material flow.

3. The method for constructing a factory simulation model based on digital twins according to claim 1, characterized in that: The physical entity model of the smart wooden structure factory includes a pre-processing area, a processing area and a post-processing area. The operation process of the physical entity model of the smart wooden structure factory includes: S101: obtaining preliminary processed raw materials according to the raw materials passing through the pre-processing zone processing model; S102: obtaining a semi-finished component through a processing model in a processing area according to the preliminary processing of the raw materials; S103: obtaining a finished wood component by processing the model in a post-processing area according to the semi-finished component; S104: Obtaining the physical entity model of the smart wooden structure factory according to the steps S101 to S103.

4. The method for constructing a factory simulation model based on digital twins according to claim 3 is characterized in that: The raw materials are initially processed by the pre-processing zone processing model according to the raw materials, including: Obtain the raw materials from the raw material storage area, and collect the moisture content of the raw materials through a humidity sensor; A moisture content threshold is preset, and raw materials with moisture content meeting the standard are obtained by judging the moisture content state according to the moisture content threshold and the moisture content of the raw materials; The processing status judgment includes judging whether the moisture content of the raw material exceeds the moisture content threshold, if yes, then the raw material is not processed; if no, then the raw material with moisture content meeting the standard is obtained; The bending degree of the raw material with qualified moisture content is collected by a laser sensor, a bending degree threshold is preset, and the bending state and the raw material with qualified moisture content are obtained by bending state judgment according to the bending degree threshold and the bending degree of the raw material with qualified moisture content; The bending state judgment includes judging whether the bending degree of the raw material with qualified moisture content exceeds the bending degree threshold value. If yes, the raw material with qualified moisture content is not processed; if no, the bending state and the raw material with qualified moisture content are obtained; The bending state and cracking degree of the raw materials with qualified moisture content are collected by a laser sensor, a cracking degree threshold is preset, and the raw materials meeting the processing requirements are obtained by cracking state judgment according to the bending state and cracking degree of the raw materials with qualified moisture content and the cracking degree threshold; The cracking state judgment includes judging whether the cracking degree of the raw material with bending state and moisture content meeting the standard exceeds the cracking degree threshold. If yes, the raw material with bending state and moisture content meeting the standard is not processed; if no, the raw material meeting the processing requirements is obtained; Obtaining the thickness standard of the raw material, and obtaining the preliminary processed raw material through the gluing and grinding area according to the raw material meeting the processing requirements and the thickness standard of the raw material; The gluing and polishing area processing includes a gluing robot arm performing a gluing process on the raw material that meets the processing requirements according to the raw material thickness standard to obtain a glued raw material; and a polishing robot arm obtains the preliminarily processed raw material by performing a leveling process on the glued raw material.

5. The method for constructing a factory simulation model based on digital twins according to claim 3, characterized in that: The obtaining of semi-finished components by processing the raw materials in the processing area through the processing model according to the preliminary processing comprises: According to the preliminary processing of raw materials, classified materials for processing are obtained by classification, and the classified materials for processing include plate components and beam-column components; Processing the plate component through a plate component processing line to obtain a semi-finished plate component; Processing the beam-column components through a beam-column component processing assembly line to obtain a semi-finished beam-column assembly; The semi-finished product assembly is formed according to the semi-finished product plate assembly and the semi-finished product beam-column assembly.

6. The method for constructing a factory simulation model based on digital twins according to claim 3, characterized in that: The method of obtaining a finished wood component by processing the model in a post-processing area according to the semi-finished component comprises: Correcting the semi-finished product component through a correction process to obtain a corrected semi-finished product component; Obtaining a storage-resistant semi-finished component by spraying the modified semi-finished component; The finished wood component is obtained by assembling the storable semi-finished product components.

7. The method for constructing a factory simulation model based on digital twins according to claim 1, characterized in that: The mapping of the physical entity model of the smart wooden structure factory by the Flex-sim three-dimensional modeling software to obtain the smart wooden structure factory simulation model includes: The physical entity model of the smart wood structure factory includes entities and operation processes; a virtual entity is obtained by manual modeling based on the entity; The Flex-sim three-dimensional modeling software establishes a connection relationship between the virtual entities according to the operation process to obtain the simulation model of the smart wooden structure factory.

8. A digital twin-based factory simulation model construction system using the digital twin-based factory simulation model construction method according to claims 1-7, comprising a model construction module, a model mapping module, and a model communication module, characterized in that: include: The model building module is used to obtain equipment data and production data, and build a physical entity model of the smart wooden structure factory according to the equipment data and the production data; The model mapping module is used to map the physical entity model of the smart wooden structure factory through the Flex-sim three-dimensional modeling software to obtain a simulation model of the smart wooden structure factory; The model communication module is used to obtain a digital twin smart wooden structure factory by exchanging information between the physical entity model of the smart wooden structure factory and the simulation model of the smart wooden structure factory through a Socket communication model.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method for constructing a factory simulation model based on digital twins as described in any one of claims 1 to 7 is implemented.

10. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions, when executed by a computer processor, are used to execute the digital twin-based factory simulation model construction method as described in any one of claims 1 to 7.

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