Synchronous multi-domain digital twinning simulation method for flexible production line

Abstract

According to the synchronous multi-domain digital twinning simulation method for the flexible production line, a digital twinning shaft part production line is used as a synchronous multi-domain simulation model of a physical production line in a digital space, so that a system simulation effect of interactive three-dimensional dynamic scene and entity behavior of multi-source information fusion is realized; the method can be used for virtual debugging of a production line and real-time state monitoring, and then complete-cycle management of the machining process in a virtual space is achieved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent manufacturing, and in particular to a synchronous multi-domain digital twin simulation method for flexible production lines. Background Art

[0002] The flexible manufacturing system is a complex hierarchical control system, and production scheduling is the core key technology of the entire flexible manufacturing system. After manufacturing has evolved from traditional large-scale assembly lines to flexible job shops, the number of options for resource allocation has increased with the increase in production resources, and the number of processing tasks included in the scheduling plan has increased with the increase in the number of workpieces, resulting in an increase in the calculation dimension of scheduling and a geometric increase in difficulty. Secondly, in the scheduling of fully automated flexible production lines, it is necessary to consider relevant constraints such as order delivery time and order priority, and the requirements for shortening product production cycles in production have increased. Finally, due to frequent demand disturbances in production, the flexible production method has increased the processing path of dynamic scheduling. Combined with the characteristics of frequent switching and heavy production tasks of flexible production of certain products, the scheduling difficulty has been further increased.

[0003] The complexity of modern scheduling, especially because the operating environment of modern manufacturing systems is increasingly full of uncertainty and the manufacturing tasks of the system often change dynamically, these uncertainties, dynamics and complexities combined together make scheduling more difficult. Summary of the invention

[0004] In order to overcome the deficiencies of the prior art, the present invention provides a synchronous multi-domain digital twin simulation method for a flexible production line.

[0005] In order to solve the above problems, the present invention provides a synchronous multi-domain digital twin simulation method for a flexible production line, and the specific steps include:

[0006] Collect production data, establish a multi-domain mathematical model, use the multi-domain mathematical model to simulate and analyze the production process of the flexible production line, and obtain simulation data;

[0007] Post-process the production data and simulation data, and merge the post-processed data with the actual measurement data to form a new data set;

[0008] Use new data sets and the physical entities of the flexible production line to perform multi-domain digital twin modeling to form a multi-domain digital twin model;

[0009] Use a multi-domain digital twin model to predict production data of flexible production lines.

[0010] Preferably, the step of post-processing the production data and the simulation data comprises:

[0011] Data cleaning: filter data, remove duplicate values, process missing values, and correct errors;

[0012] Data transformation: Formatting, restructuring or converting data.

[0013] Preferably, the multi-domain mathematical model includes a simulation model, a digital model and a behavioral model.

[0014] Preferably, production data and simulation data are fused using a deep learning algorithm.

[0015] Preferably, when performing model simulation, the simulation tools include: one or more combinations of ANSYS Fluent, cfx, STAR-CCM, comsol, OpenFOAM, and Phoenics.

[0016] Beneficial effects:

[0017] The present invention adopts a digital twin shaft parts production line as a synchronous multi-domain simulation model of the physical production line in the digital space, which can realize the system simulation effect of interactive three-dimensional dynamic vision and entity behavior of multi-source information fusion, and can be used for virtual debugging and real-time status monitoring of the production line, thereby realizing the full-cycle management of the processing process in the virtual space.

[0018] Three-dimensional visual monitoring based on digital twins can accurately and realistically simulate the actual conditions on the production line. During the production process, data is collected in real time and mapped to the digital twin model, which can more intuitively and effectively reflect the operating status of the production line, and handle abnormal conditions in a timely manner through remote control to reduce the occurrence of failures. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flowchart of a synchronous multi-domain digital twin simulation method for a flexible production line provided by the present invention.

[0020] Figure 2 A synchronous multi-domain digital twin simulation method for a flexible production line is provided in the present invention, and a structure diagram of a flexible production line digital twin system is used. DETAILED DESCRIPTION

[0021] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0022] The present invention uses a shaft parts production line to construct a synchronous multi-domain simulation model, and uses the model to simulate to adjust production data. The details are as follows:

[0023] like Figure 1 As shown, the present invention provides a synchronous multi-domain digital twin simulation method for a flexible production line, the steps of which include:

[0024] Collect production data, establish a multi-domain mathematical model, use the multi-domain mathematical model to simulate and analyze the production process of the flexible production line, and obtain simulation data;

[0025] Post-process the production data and simulation data, and merge the post-processed data with the actual measurement data to form a new data set;

[0026] Use new data sets and the physical entities of the flexible production line to perform multi-domain digital twin modeling to form a multi-domain digital twin model;

[0027] Use a multi-domain digital twin model to predict production data of flexible production lines.

[0028] In the present invention, production data is recorded in real time using a production line digital twin system. The multi-domain mathematical model includes simulation models, digital models, power system models, behavioral models, etc. The multi-domain mathematical model is a multi-domain model library that builds connected virtual copies for physical equipment in operation and establishes a mirror image for the life cycle operation experience of physical equipment.

[0029] The steps of post-processing the production data and the simulation data include:

[0030] Data cleaning: Screening, removing duplicate values, processing missing values, correcting errors, etc. to ensure data quality and integrity. Common techniques include deleting duplicate rows / columns, filling missing values, using interpolation methods to estimate missing values, and correcting erroneous data.

[0031] Data transformation: Formatting, restructuring, or converting data to make it suitable for specific analytical requirements or data models.

[0032] Based on the post-processed production data and simulation data, a deep learning algorithm is used for data fusion to form a new data set. At this time, the data set is split into a training set and a test set, and the training set and the physical entity of the flexible production line are used to build a multi-domain digital twin model; in the process of building the model, an artificial neural network is used for model training, and the final multi-domain digital twin model is obtained after repeated training. Based on the constructed multi-domain digital twin model, the test machine is input into it for test simulation. Among them, the simulation tool can use one or more combined simulations of ANSYS Fluent, cfx, STAR-CCM, comsol, OpenFOAM, Phoenics, etc.

[0033] According to the simulation results, the parameters are adjusted, the simulation data is iteratively optimized, and finally the production data with higher reliability is output.

[0034] The present invention performs simulation through a multi-domain digital twin model, thereby achieving a system simulation effect of interactive three-dimensional dynamic vision and entity behavior with multi-source information fusion, which can be used for virtual debugging of production lines and real-time status monitoring, thereby realizing full-cycle management of the processing process in a virtual space.

[0035] In addition, the constructed multi-domain digital twin model can be used to predict future changes in production data so that the production line can be quickly scheduled.

[0036] In the present invention, during the simulation process of the multi-domain digital twin model, the accuracy of the simulation data is further improved by synchronously running in the digital space.

[0037] The present invention is applied to the digital twin system of the flexible production line, and its structure is as follows: Figure 2 As shown. The digital twin system of the flexible production line includes: data management layer, logic processing layer, reference function layer, and human-computer interaction layer. For equipment management, its main functions include: (1) the system collects and counts equipment output, energy consumption, online time, utilization rate, and OEE; (2) provides real-time monitoring data and charts for each device; (3) provides basic daily and weekly reports for equipment; (4) accurately monitors the operation of all equipment. For production management, its full-process order management realizes the production of multi-process products, that is, a "full-process order" can be decomposed into multiple "process orders", and then the "process orders" are assigned to single / multiple devices to generate equipment "production tasks."

[0038] The present invention realizes three-dimensional visual monitoring based on digital twins by combining model simulation with the digital twin system of flexible production lines. It can accurately and realistically simulate the actual conditions of the production line. During the production process, data is collected in real time and mapped to the digital twin model, which more intuitively and effectively reflects the operating status of the production line, and handles abnormal conditions in time through remote control to reduce the occurrence rate of failures.

[0039] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

Claims

1. A synchronous multi-domain digital twin simulation method for flexible production lines, characterized in that: The specific steps include: Collect production data, establish a multi-domain mathematical model, use the multi-domain mathematical model to simulate and analyze the production process of the flexible production line, and obtain simulation data; Post-process the production data and simulation data, and merge the post-processed data with the actual measurement data to form a new data set; Use new data sets and the physical entities of the flexible production line to perform multi-domain digital twin modeling to form a multi-domain digital twin model; Use a multi-domain digital twin model to predict production data of flexible production lines.

2. The synchronous multi-domain digital twin simulation method for flexible production lines according to claim 1 is characterized in that: The step of post-processing the production data and simulation data comprises: Data cleaning: filter data, remove duplicate values, process missing values, and correct errors; Data transformation: Formatting, restructuring or converting data.

3. The synchronous multi-domain digital twin simulation method for flexible production lines according to claim 1 is characterized in that: The multi-domain mathematical model includes a simulation model, a digital model and a behavioral model.

4. The synchronous multi-domain digital twin simulation method for flexible production lines according to claim 1 is characterized in that: The production data and simulation data are fused using a deep learning algorithm.

5. The synchronous multi-domain digital twin simulation method for flexible production lines according to claim 1 is characterized in that: When simulating the model, the simulation tools include one or more combinations of ANSYS Fluent, cfx, STAR-CCM, comsol, OpenFOAM, and Phoenics.

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