Online reconstruction optimization method for virtual-real fusion interactive manufacturing system

Abstract

The invention provides an online reconstruction optimization method for a virtual-real fusion interactive manufacturing system. The online reconstruction optimization method comprises the following steps: S1, establishing a virtual mapping model based on parameters and rules of a physical entity; the physical entity is used for executing a production task; s2, establishing data connection between the physical entity and the virtual mapping model to form a virtual-real fusion interactive manufacturing system; s3, constructing a reconstruction optimization model based on the new order demand; s4, solving the reconstruction optimization model to obtain a reconstruction optimization scheme of the virtual-real fusion interactive manufacturing system; s5, adjusting the virtual mapping model according to the reconstruction optimization scheme; and S6, reconstructing the physical entity according to the adjusted virtual mapping model. According to the method, efficient adjustment of production tasks is achieved, and complex and changeable production requirements can be met.

Description

Technical Field

[0001] The present invention relates to the fields of industrial automation, intelligent manufacturing and operations optimization, and in particular to an online reconstruction optimization method for a virtual-reality fusion interactive manufacturing system. Background Art

[0002] The plug-and-play capability of the manufacturing system is to achieve flexible configuration and rapid iterative upgrades of the industrial manufacturing system without stopping the system through information modeling technology, industrial protocol unified communication technology, semantic modeling technology, etc.

[0003] Technological progress and the increase in demand for customized production have prompted manufacturing companies to put forward higher requirements for system flexibility. The flexibility of manufacturing systems is reflected in the system's expansion and reconstruction capabilities. The so-called reconstruction is to achieve the reorganization of the production system by adjusting the number, type and production steps of machines in the production line. In the actual manufacturing environment, unforeseen situations such as equipment failure and emergency order arrangements are often encountered. The impact of these situations on the system is difficult to estimate in advance. The reconstruction scheme based on the idealized mathematical model often ignores the dynamic characteristics of the real production environment, making the scheme inconsistent with reality. Current research focuses on the formulation of reconstruction strategies, but pays less attention to the actual deployment process. In addition, traditional reconstruction methods are usually offline operations, that is, they need to be shut down for adjustment and updating. This method relies on a lot of manpower and has obvious limitations. It is impossible to achieve dynamic reconstruction and real-time deployment of manufacturing systems, and it is difficult to meet the real-time and flexibility requirements of manufacturing systems. Summary of the invention

[0004] The purpose of the present invention is to provide an online reconstruction optimization method for a virtual-reality fusion interactive manufacturing system to achieve dynamic reconstruction and implementation deployment of the manufacturing system.

[0005] In order to solve the above technical problems, the present invention provides an online reconstruction optimization method for a virtual-reality fusion interactive manufacturing system, comprising the following steps: S1. Establish a virtual mapping model based on the parameters and rules of the physical entity; the physical entity is used to perform production tasks; S2. Establish data connection between physical entity and virtual mapping model to form a virtual-real fusion interactive manufacturing system; S3, build a reconstruction optimization model based on new order requirements; S4, solving the reconstruction optimization model to obtain a reconstruction optimization solution for the virtual-reality fusion interactive manufacturing system; S5. Adjust the virtual mapping model according to the reconstruction optimization scheme; S6. Reconstruct the physical entity according to the adjusted virtual mapping model. According to the above scheme, the virtual mapping model includes a geometric model, an information model, a capability model, and a rule model; The geometric model is used to provide the spatial posture data of the physical entity. The spatial posture data includes the appearance shape, size, spatial position, rotation angle of the physical entity compared to the world coordinate system, and the appearance shape of the product to be processed; The information model is used to provide the physical properties or parameters of the physical entity during static / dynamic operation. The physical properties or parameters include the physical properties and operating status of the industrial robot, the properties and characteristics of the product in the production process, the properties and characteristics of the manufacturing tool, and the environmental parameters of the environment in which the physical entity is located; The capability model is used to provide the manufacturing capability of the physical entity. The manufacturing capability includes the static characteristics, adjustment and configuration capabilities, and the completion of manufacturing tasks of the physical entity. The rule model includes rules or constraints for stabilizing the virtual-reality fusion interactive manufacturing system. The rules or constraints include product and equipment matching rules, reconstruction specifications, production target constraints, equipment capability constraints, process flow and tool matching rules, and hierarchical structure rules.

[0006] According to the above scheme, step S2 includes: S201, connecting the physical entity to the corresponding PLC interface through a set protocol; S202, detecting physical entity state data by defining PLC variables; S203, mapping the PLC variables and the corresponding information models; S204: Input the data of the information model into the simulation platform.

[0007] According to the above scheme, step S3 includes: S301, using a virtual mapping model to analyze new order requirements and determine the cost required for the order requirements; S302, setting the constraint conditions of the reconstruction optimization model according to the cost required by the order demand; S303: Set the objective function of the reconstruction optimization model.

[0008] According to the above scheme, in step S4, the improved migratory bird algorithm is used, and after multiple iterations of optimization, the optimal reconstruction optimization scheme is output.

[0009] According to the above scheme, in the improved migratory bird algorithm, the encoding of the population includes the process layer, the machine selection layer, and the processing unit layer, and a mixture of uniform crossover and partial sequential crossover is adopted in the flying bird crossover operation.

[0010] According to the above scheme, step S5 includes: S501, evaluating whether the physical entity and the virtual mapping model meet the manufacturing requirements of the reconstruction optimization solution; if so, executing S503, if not, executing S502; S502, updating and optimizing the virtual mapping model until the virtual mapping model meets the manufacturing requirements; S503, testing the virtual mapping model that meets the manufacturing requirements, and if it meets the preset test results, proceed to the subsequent steps, otherwise proceed to the next update and optimization.

[0011] According to the above scheme, the virtual-reality fusion interactive manufacturing system includes a local discovery service, and step S6 reconstructs the physical entity based on the local discovery service; the local discovery service is established according to the physical entity parameters, and the local discovery service provides registration for the new physical entity, so that the registered physical entities can communicate with each other.

[0012] The present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the online reconstruction optimization method of the virtual-reality fusion interactive manufacturing system described in the claims above are implemented.

[0013] The present invention also provides a computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the online reconstruction optimization method of the virtual-reality fusion interactive manufacturing system described in the claims above are implemented.

[0014] Beneficial Effects The present invention establishes a corresponding virtual mapping model based on the physical entity, and establishes a data connection between the physical entity and the virtual mapping model, thereby realizing the control of the virtual mapping model over the physical entity during the manufacturing process, and the real-time feedback of the physical entity to the virtual mapping model, thereby enhancing the convenience and real-time performance of production task regulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of an online reconstruction optimization method of a virtual-reality fusion interactive manufacturing system according to a first embodiment of the present invention; Figure 2 This is a flow chart of an online reconstruction and dynamic deployment method of a plug-and-play virtual-reality fusion interactive manufacturing system according to a second embodiment of the present invention; Figure 3 Schematic diagram of the virtual-real data interaction mechanism of the virtual-real fusion interactive manufacturing system according to the second embodiment of the present invention; Figure 4 Schematic diagram of a reconstruction optimization model of a virtual-reality fusion interactive manufacturing system according to a second embodiment of the present invention; Figure 5 is a flow chart of a method for reconfiguring and optimizing a virtual-reality fusion interactive manufacturing system according to a second embodiment of the present invention; Figure 6 is a flow chart of an improved migratory bird algorithm according to the second embodiment of the present invention; Figure 7It is a schematic diagram of a virtual mapping model reconstruction strategy of a virtual-reality fusion interactive manufacturing system according to a second embodiment of the present invention; Figure 8 This is a flow chart of building a discovery service for a virtual-reality fusion interactive manufacturing system according to Embodiment 2 of the present invention; Fig. 9 It is a communication diagram of the discovery service of the virtual-reality fusion interactive manufacturing system according to the second embodiment of the present invention. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution of the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings of the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the described embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0017] Embodiment 1: See also Figure 1 This embodiment discloses an online reconstruction optimization method for a virtual-reality fusion interactive manufacturing system to achieve dynamic reconstruction and implementation deployment of the manufacturing system.

[0018] In order to solve the above technical problems, the present invention provides an online reconstruction optimization method for a virtual-reality fusion interactive manufacturing system, comprising the following steps: S1. Establish a virtual mapping model based on the parameters and rules of the physical entity; the physical entity is used to perform production tasks; S2. Establish data connection between physical entity and virtual mapping model to form a virtual-real fusion interactive manufacturing system; S3, build a reconstruction optimization model based on new order requirements; S4, solving the reconstruction optimization model to obtain a reconstruction optimization solution for the virtual-reality fusion interactive manufacturing system; S5. Adjust the virtual mapping model according to the reconstruction optimization scheme; S6. Reconstruct the physical entity according to the adjusted virtual mapping model. Further, the virtual mapping model includes a geometric model, an information model, a capability model, and a rule model; The geometric model is used to provide the spatial posture data of the physical entity. The spatial posture data includes the appearance shape, size, spatial position, rotation angle of the physical entity compared to the world coordinate system, and the appearance shape of the product to be processed; In this embodiment, the geometric model is expressed as:

[0019] In the above formula, Shape represents the appearance shape of the physical entity (in this embodiment, the physical entity includes the industrial robot, manufacturing tool, conveying device, sensor) and the appearance shape of the product to be processed; Size represents the size of the physical entity; Location represents the spatial position of the physical entity in the world coordinate system, including the three parameters of X, Y, and Z; Posture represents the rotation angle of the physical entity relative to the world coordinate system, including the three parameters of A, B, and C; The information model is used to provide the physical properties or parameters of the physical entity during static / dynamic operation. The physical properties or parameters include the physical properties and operating status of the industrial robot, the properties and characteristics of the product in the production process, the properties and characteristics of the manufacturing tool, and the environmental parameters of the environment in which the physical entity is located; In this embodiment, the information model is expressed as:

[0020] In the above formula, RobotInfo represents the physical properties and operating status of the industrial robot; ProductInfo represents the product properties and characteristics in the production process, including product ID, processing route and process parameters; ToolInfo represents the properties and characteristics of the manufacturing tool, including tool ID, type, status and specifications; EnvironmentInfo represents the environmental parameters of the environment in which the physical entity is located, including temperature and humidity; The capability model is used to provide the manufacturing capability of the physical entity. The manufacturing capability includes the static characteristics, adjustment and configuration capabilities, and the completion of manufacturing tasks of the physical entity. In this embodiment, the capability model is expressed as:

[0021] In the above formula, TP is the technical parameter, which indicates the static capability of the physical entity (such as manufacturing equipment), including production accuracy, maximum load, and maximum speed; MB is the manufacturing behavior, which includes the adjustment and configuration capability of the physical entity, such as the processing capability for specific products / specific processes; MP is the manufacturing process, which indicates the completion of the manufacturing task of the physical entity, including the execution time of the manufacturing equipment and the task progress; The rule model includes rules or constraints for stabilizing the virtual-real fusion interactive manufacturing system. The rules or constraints include product and equipment matching rules, reconstruction specifications, production target constraints, equipment capacity constraints, process flow and tool matching rules, and hierarchical structure rules. In this embodiment, the rule model is expressed as:

[0022] In the above formula, PEMR is the product and equipment matching rules (Production and Equipment Matching Rules), which is used to accurately match various products in production requirements to equipment with corresponding processing capabilities to achieve effective docking of production factors; RR is the reconstruction specification (Reconfiguration Rules), which is used to standardize the content of equipment-level reconstruction and system-level reconstruction; POC is the production objective constraint (Production Objective Constraints), which is used to determine whether the virtual-reality fusion interactive manufacturing system meets the production requirements. If not, the reconstruction service is triggered; ECC is the equipment capability constraint (Equipment Capability Constraints), which stipulates the processing capability of each equipment and the working time required to complete the corresponding production; PFTMR is the process flow and tool matching rules (Process Flow and Tool Matching Rules), which stipulates the tool selection corresponding to the process flow; SR is the hierarchical structure rules (Subordination Rules), which defines the affiliation between different levels in the virtual-reality fusion interactive manufacturing system.

[0023] Further, step S2 includes: S201, connecting the physical entity to the corresponding PLC interface by setting a protocol (PROFINET protocol is used in this embodiment); S202, detecting physical entity state data by defining PLC variables; S203, mapping the PLC variables and the corresponding information model (OPC UA information model in this embodiment) to each other; S204 , inputting the data of the information model into a simulation platform (in this embodiment, the Demo3D simulation platform).

[0024] Further, step S3 includes: S301, using the virtual mapping model to analyze new order requirements and determine the cost required for the order requirements (the cost includes the equipment set required for the order requirements and the execution time of the corresponding process); S302, setting the constraint conditions of the reconstruction optimization model according to the cost required by the order demand; S303: Set the objective function of the reconstruction optimization model.

[0025] In this embodiment, the objective function is expressed as:

[0026] In the above formula

[0027]

[0028]

[0029] f1, f2, and f3 represent minimizing the number of cross-unit times, minimizing the maximum processing time, and minimizing the processing reconstruction cost, respectively; is the cross-unit frequency indicator; The jth process of product i on the machine The starting processing time on The jth process of product i on the machine Processing time on Refactoring costs for the system; The jth process of product i on the machine The reconstruction cost of the upper processing.

[0030] The constraints include: 1) the principle of continuity in process execution (once a process starts, it cannot be interrupted until it is completed); 2) the preceding and following constraints in the manufacturing process (each product must be completely completed before the subsequent processes can be processed); 3) the upper limit of the capacity of the machine resources in each manufacturing unit; 4) the principle of process occupancy (a process can only be processed by one machine in the same time period); Constraints 1) to 4) are expressed as:

[0031]

[0032]

[0033]

[0034] In the above formula, The jth process of product i on the machine The completion time on the above; A is the processing unit set; A value of 1 indicates that the j-th process of product i is processed on the k-th machine, and a value of 0 indicates that it is not processed on this machine.

[0035] Furthermore, in step S4, an improved migratory bird algorithm is used to output an optimal reconstruction optimization solution after multiple iterations of optimization.

[0036] Furthermore, in the improved migratory bird algorithm, the encoding of the population includes the process layer, the machine selection layer, and the processing unit layer, and a mixture of uniform crossover and partial order crossover (POX) is used in the flying bird crossover operation.

[0037] Further, step S5 includes: S501, evaluating whether the physical entity and the virtual mapping model meet the manufacturing requirements of the reconstruction optimization solution; if so, executing S503, if not, executing S502; S502, updating and optimizing the virtual mapping model until the virtual mapping model meets the manufacturing requirements; S503, testing the virtual mapping model that meets the manufacturing requirements, and if it meets the preset test results, proceed to the subsequent steps, otherwise proceed to the next update and optimization.

[0038] Furthermore, the virtual-real fusion interactive manufacturing system includes a local discovery service (OPC UA local discovery service, i.e., Local Discovery Server, LDS) in this embodiment, and step S6 reconstructs the physical entity based on the local discovery service; the local discovery service is established according to the physical entity parameters, and the local discovery service provides registration to the new physical entity, so that the registered physical entities can communicate with each other; In this embodiment, the virtual-reality fusion interactive manufacturing system configures and initializes the LDS when it is started. After initialization, it will be ready to receive registration requests from various physical devices and centrally manage and process these requests. When a new device is connected to the network, the system will dynamically assign a randomly generated service port number to its built-in OPC UA server for service use. After its built-in OPC UA server completes its own initialization, it will actively send a registration message containing key information (such as DiscoveryUrl, etc.) to the LDS. Devices registered with the LDS can be easily discovered by other devices in the network. When a device needs to find and connect to another device, it only needs to query the server registration list maintained by the LDS to obtain the OPC UA server information of the target device, and then establish a secure and reliable communication connection.

[0039] Embodiment 2: This embodiment provides an online reconstruction and dynamic deployment method for a plug-and-play virtual-real fusion interactive manufacturing system. Figure 2 As shown, the following steps are included: Step 1: Construct a multi-dimensional virtual mapping model of the virtual-reality fusion interactive manufacturing system to cover the basic functions of the virtual-reality fusion interactive manufacturing system and support the reconstruction of the system at different granularities; Step 2: Build a virtual-real data interaction mechanism for the virtual-real fusion interactive manufacturing system. This is used to build a virtual mapping model in the manufacturing process to control the operating status of the physical manufacturing system; Step 3: Construct a mathematical model for the reconstruction optimization of the virtual-real fusion interactive manufacturing system. This model is used to construct the reconstruction problem model of the virtual-real fusion interactive manufacturing system. Its goals include reasonably adjusting and optimizing the configuration of processing resources between units. It reduces the number of production tasks transferred between different units, designs production scheduling strategies, and minimizes completion time and reconstruction costs. Step 4: Combine the virtual-reality fusion interactive manufacturing system reconstruction optimization method with the improved migratory bird algorithm. It is used to solve the reconstruction problem model of the virtual-reality fusion interactive manufacturing system and obtain a reconstruction solution that can achieve a balance between multiple optimization objectives; Step 5: Reconstruction strategy of virtual mapping model of virtual-real fusion interactive manufacturing system. It is used to simulate the reconstruction of the physical manufacturing system in the reconstruction design of virtual-real fusion interactive manufacturing system, and guide the virtual mapping model to match the physical manufacturing system again; Step 6: Online reconstruction and deployment of the virtual-real fusion interactive manufacturing system combined with the OPC UA discovery mechanism. Used to achieve online real-time discovery, registration, and integration of equipment based on the reconstruction solution.

[0040] The use of the virtual mapping model of the virtual-reality fusion interactive manufacturing system described in step 1 of the present invention includes building a visualization model by importing an internal model library and an external model, and using two different methods, ontology modeling and Asset Administration Shell modeling, to unify the abstract modeling of the virtual mapping model of the virtual-reality fusion interactive manufacturing system, including four dimensions: geometric model, information model, capability model, and rule model; the definitions are as follows.

[0041] (1) (2) (3) (4) (5) The geometric model provides the spatial posture data of the virtual mapping model to the upper-level decision-making system of the virtual-reality fusion interactive manufacturing system: Shape mainly describes the appearance shape of physical entities such as industrial robots, manufacturing tools, conveying devices, sensors, and the actual appearance of the products to be processed. Size is used to indicate the size of the physical entity, such as the length of the joint axis of an industrial robot, the model size of an assembly tool, etc. Location defines the spatial position of the physical entity in the world coordinate system, including the three parameters X, Y, and Z. Posture describes the rotation angle of the physical entity relative to the world coordinate system, including the three parameters A, B, and C.

[0042] The information model mainly considers the various physical properties and parameters of the entity during static and dynamic operation: RobotInfo contains the core properties of the robot and is used to describe the physical properties and operating status of the robot. ProductInfo is used to describe the product properties and characteristics in the production process, including product ID, processing route and process parameters. ToolInfo refers to the properties and characteristics of the tools used in the manufacturing process, including tool ID, type, status, specifications, etc. EnvironmentInfo refers to the environmental conditions of the virtual-reality interactive manufacturing system, including temperature, humidity, etc.

[0043] The capability model is used to accurately describe the manufacturing capability of a physical entity: Technical Parameters (TP) cover the static characteristics of manufacturing equipment, such as production accuracy, maximum load, maximum speed, etc.; Manufacturing Behavior (MB) includes the ability of manufacturing units to be flexibly adjusted and configured, such as the processing capability for specific processes of specific products; Manufacturing Process (MP) refers to the completion status of manufacturing tasks, including the execution time of manufacturing equipment, task progress, etc.

[0044] The rule model ensures the stable operation of the system by creating a series of rules and constraints: The Product and Equipment Matching Rules (PEMR) focus on accurately matching various products in demand to equipment with corresponding processing capabilities to achieve effective docking of production factors. Reconfiguration Rules (RR) are used to standardize the content of equipment-level reconfiguration and system-level reconfiguration. Production Objective Constraints (POC) are used to determine whether the virtual-real fusion interactive manufacturing system meets production requirements. If not, the reconfiguration service is triggered. Equipment Capability Constraints (ECC) stipulate the processing capability of each equipment and the working time required to complete the corresponding production. Process Flow and Tool Matching Rules (PFTMR) stipulate the tool selection corresponding to the process flow. Subordination Rules (SR) define the affiliation between different levels of the system.

[0045] The virtual-real data interaction mechanism of the virtual-real fusion interactive manufacturing system described in step 2 of the present invention is as follows: Figure 3 As shown, the following steps are included: Step 2-1: Connect manufacturing components such as industrial robots and sensors to the corresponding PLC interface through protocols such as PROFINET; Step 2-2: Implement physical status data detection with manufacturing components by defining PLC variables; Step 2-3: Map the PLC variables to the corresponding OPC UA information model; Step 2-4: In the Demo3D simulation platform, receive data from the OPC UA information model.

[0046] The reconstruction optimization model of the virtual-reality fusion interactive manufacturing system described in step 3 of the present invention is as follows: Figure 4 As shown, the following steps are included: Step 3-1: When receiving a new order requirement, use the digital twin system to analyze and determine the equipment set required to implement the order and the execution time and cost of its corresponding processes; Step 3-2: Define the constraints of the reconstruction problem model of the virtual-real fusion interactive manufacturing system, including the continuity principle in the process execution, the before and after constraints in the manufacturing process, and the capacity limit of the machine resources in each manufacturing unit; Step 3-3: Define the objective function of the reconstruction problem model of the virtual-reality fusion interactive manufacturing system, including the minimum number of cross-unit times, the minimum reconstruction cost and the minimum processing time.

[0047] The reconstruction scheme of the virtual-reality fusion interactive manufacturing system needs to minimize the number of cross-unit times, as shown in the formula: (6) The reconstruction scheme of the virtual-reality fusion interactive manufacturing system requires the minimum maximum processing time, as shown in the formula: (7) The reconstruction scheme of the virtual-reality fusion interactive manufacturing system needs to minimize the processing reconstruction cost, as shown in the formula: (8) The objective function is shown in formula (9): (9) The constraints are shown in equations (10) to (13): (10) (11) (12) (13) Formula (9) is used to define the objective function of the entire reconstruction optimization problem. Formula (10) shows the constraints in the manufacturing process, that is, each product must be completely completed before the subsequent process can be processed. Formula (11) shows the continuity principle in the process of process execution, that is, once the process starts, it cannot be interrupted until the processing is completed; Formula (12) stipulates that a process can only be processed by one machine in the same time period. Formula (13) clarifies the capacity upper limit of the machine resources in each manufacturing unit.

[0048] The virtual-reality fusion interactive manufacturing system reconstruction optimization method combined with the improved migratory bird algorithm described in step 4 of the present invention is as follows Figure 5 As shown, the specific steps include: Step 4-1: Supplement and adjust machine resources based on the real-time order task information and existing processing resource status data in the manufacturing system; Step 4-2: Under the premise of meeting production continuity and efficiency, flexibly reorganize and optimize the structure of each processing unit; Step 4-3: According to the adjusted machine allocation of each processing unit, formulate an orderly production task scheduling strategy; through the improved migratory bird algorithm, multiple iterations of optimization are performed to achieve the output of the optimal reconstruction solution. The algorithm flow chart is as follows: Figure 6As shown in the figure. When solving the reconstruction problem of the virtual-real fusion interactive manufacturing system, the population encoding method adopts a three-layer encoding rule, which is divided into three parts: process layer, machine selection layer and processing unit layer. When crossing with the flying bird, the uniform crossover and partial order crossover (POX) strategies are mixed.

[0049] The virtual mapping model reconstruction strategy of the virtual-reality fusion interactive manufacturing system described in step 5 of the present invention is as follows: Figure 7 As shown, the specific steps include: Step 5-1: Evaluate whether the current system meets the new manufacturing capability requirements.

[0050] Step 5-2: If the system's manufacturing capabilities are sufficient to meet the requirements, proceed to the virtual platform verification phase.

[0051] Step 5-3: If the manufacturing capacity of the system is not enough to meet the demand, perform equipment-level reconstruction and system-level reconstruction. The manufacturing capacity is updated by reorganizing, adjusting the configuration of equipment components, updating the equipment control code, replacing, deleting and adding the corresponding virtual mapping model.

[0052] Step 5-4: Test the digital twin system that meets manufacturing needs in the virtual visualization platform.

[0053] The online reconstruction deployment of the virtual-reality fusion interactive manufacturing system combined with OPC UA described in step 6 of the present invention is as follows Figure 8 and Fig. 9 As shown, the specific steps include: Step 6-1: Use the OPC UA Local Discovery Server (LDS) as the core component to build a virtual-reality fusion interactive manufacturing system discovery service. When the system starts, configure and initialize the LDS. After initialization, it will be ready to receive registration requests from various physical devices and centrally manage and process these requests; Step 6-2: Analyze the physical entity device abstraction to extract its key attributes and functions, and establish an OPC UA information model for the device; Step 6-3: When a new device is connected to the network, the system will dynamically assign a randomly generated service port number to its built-in OPC UA server for service use. After the built-in server completes its own initialization, it will actively send a registration message containing key information (such as DiscoveryUrl, etc.) to LDS; Step 6-4: Devices registered with LDS can be easily discovered by other devices in the network. When a device needs to find and connect to another device, it only needs to query the server registration list maintained by LDS to obtain the OPC UA server information of the target device, and then establish a secure and reliable communication connection.

[0054] Compared with the prior art, the present invention has the following advantages: (1) Based on the reconstruction requirements of the virtual-reality interactive manufacturing system, a multi-dimensional virtual mapping model was established, including geometric model, information model, capability model and rule model. These dimensions comprehensively describe the basic functions of the manufacturing system and provide support for the reconstruction of the system at different granularities.

[0055] (2) A virtual-real data interaction mechanism for the virtual-real interactive manufacturing system was constructed, which enabled the control of the virtual mapping model over the physical manufacturing system during the manufacturing process and enhanced the digital simulation and real-time feedback functions of the manufacturing process.

[0056] (3) A reconstruction optimization model for the virtual-reality interactive manufacturing system was constructed, with the minimum number of cross-unit times, minimum reconstruction cost, and minimum processing time as the goals, providing a more accurate scheduling basis for the reconstruction process.

[0057] (4) A virtual mapping model reconstruction strategy suitable for manufacturing systems is proposed, which realizes the dynamic matching between the virtual mapping model and the physical manufacturing system during the reconstruction process and provides a guiding basis for the online reconstruction of the system.

[0058] (5) By adopting the OPC UA discovery service mechanism, the system can realize online integration and deployment of equipment during operation, effectively supporting the real-time reconstruction and dynamic adjustment of the virtual-reality interactive manufacturing system.

[0059] It should be pointed out that, according to the needs of implementation, the various steps / components described in this application can be split into more steps / components, and two or more steps / components or partial operations of steps / components can be combined into new steps / components to achieve the purpose of the present invention.

[0060] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An online reconstruction optimization method for a virtual-reality fusion interactive manufacturing system, characterized in that: The following steps are involved: S1. Establish a virtual mapping model based on the parameters and rules of the physical entity; the physical entity is used to perform production tasks; S2. Establish data connection between physical entity and virtual mapping model to form a virtual-real fusion interactive manufacturing system; S3, build a reconstruction optimization model based on new order requirements; S4, solving the reconstruction optimization model to obtain a reconstruction optimization solution for the virtual-reality fusion interactive manufacturing system; S5. Adjust the virtual mapping model according to the reconstruction optimization scheme; S6. Reconstruct the physical entity according to the adjusted virtual mapping model.

2. The online reconstruction optimization method of the virtual-reality fusion interactive manufacturing system according to claim 1 is characterized in that: The virtual mapping model includes geometric model, information model, capability model and rule model; The geometric model is used to provide the spatial posture data of the physical entity. The spatial posture data includes the appearance shape, size, spatial position, rotation angle of the physical entity compared to the world coordinate system, and the appearance shape of the product to be processed; The information model is used to provide the physical properties or parameters of the physical entity during static / dynamic operation. The physical properties or parameters include the physical properties and operating status of the industrial robot, the properties and characteristics of the product in the production process, the properties and characteristics of the manufacturing tool, and the environmental parameters of the environment in which the physical entity is located; The capability model is used to provide the manufacturing capability of the physical entity. The manufacturing capability includes the static characteristics, adjustment and configuration capabilities, and the completion of manufacturing tasks of the physical entity. The rule model includes rules or constraints for stabilizing the virtual-reality fusion interactive manufacturing system. The rules or constraints include product and equipment matching rules, reconstruction specifications, production target constraints, equipment capability constraints, process flow and tool matching rules, and hierarchical structure rules.

3. The online reconstruction optimization method of the virtual-reality fusion interactive manufacturing system according to claim 1 is characterized in that: Step S2 includes: S201, connecting the physical entity to the corresponding PLC interface through a set protocol; S202, detecting physical entity state data by defining PLC variables; S203, mapping the PLC variables and the corresponding information models; S204: Input the data of the information model into the simulation platform.

4. The online reconstruction optimization method of the virtual-reality fusion interactive manufacturing system according to claim 1 is characterized in that: Step S3 includes: S301, using a virtual mapping model to analyze new order requirements and determine the cost required for the order requirements; S302, setting the constraint conditions of the reconstruction optimization model according to the cost required by the order demand; S303: Set the objective function of the reconstruction optimization model.

5. The online reconstruction optimization method of the virtual-reality fusion interactive manufacturing system according to claim 1 is characterized in that: In step S4, the improved migratory bird algorithm is used to output the best reconstruction optimization solution after multiple iterations of optimization.

6. The online reconstruction optimization method of the virtual-reality fusion interactive manufacturing system according to claim 5 is characterized in that: In the improved migratory bird algorithm, the encoding of the population includes the process layer, the machine selection layer, and the processing unit layer, and a mixture of uniform crossover and partial sequential crossover is used in the flying bird crossover operation.

7. The online reconstruction optimization method of the virtual-reality fusion interactive manufacturing system according to claim 1 is characterized in that: Step S5 includes: S501, evaluating whether the physical entity and the virtual mapping model meet the manufacturing requirements of the reconstruction optimization solution; if so, executing S503, if not, executing S502; S502, updating and optimizing the virtual mapping model until the virtual mapping model meets the manufacturing requirements; S503, testing the virtual mapping model that meets the manufacturing requirements, and if it meets the preset test results, proceed to the subsequent steps, otherwise proceed to the next update and optimization.

8. The online reconstruction optimization method of the virtual-reality fusion interactive manufacturing system according to claim 1 is characterized in that: The virtual-reality fusion interactive manufacturing system includes a local discovery service. Step S6 reconstructs the physical entity based on the local discovery service. The local discovery service is established according to the physical entity parameters. The local discovery service provides registration for new physical entities so that registered physical entities can communicate with each other.

9. A computer 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 computer program, the steps of the online reconstruction optimization method of the virtual-reality fusion interactive manufacturing system according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the online reconstruction optimization method of the virtual-reality fusion interactive manufacturing system according to any one of claims 1 to 8 are implemented.

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