A digital twin model and digital twin system construction method for process manufacturing workshop

Abstract

The present invention discloses a digital twin model of a process manufacturing workshop and a method for constructing a digital twin system. The digital twin model construction method includes: modeling the geometric physical properties of each element of the process manufacturing physical workshop through industrial modeling software to construct a static physical model SPM; constructing a dynamic data relationship model DDRM based on the correlation between the dynamic data of the process manufacturing physical workshop; establishing a data communication interface, and performing model fusion between the SPM and the DDRM to complete the construction of the digital twin model. Furthermore, the multidimensional digital twin models of the workshop elements are graded according to the composition structure of the physical workshop to obtain a workshop-level multidimensional digital twin model; constructing a digital twin system composed of a physical production line system PS, a virtual production line system VS, a production line information service system IS, and a twin data system DS; and performing two-by-two interaction and iterative operation of PS, VS, and IS through DS to complete the construction of the digital twin system.

Description

Technical Field

[0001] The present invention relates to a digital twin model of a process manufacturing workshop and a method for constructing a digital twin system, and belongs to the technical field of digital twins in the process manufacturing industry. Background Art

[0002] The production process of the process industry is composed of different working steps arranged and combined in an orderly manner. The behavioral processes between each process are seriously coupled, and the process manufacturing industry involves numerous process regulations. The process equipment and process parameters used in different process regulations are closely related to quality indicators. How to form a virtual-to-real mapping and iterative operation mechanism for all elements of the production process in a manufacturing environment with human-machine-object collaboration and multi-process coupling in the process manufacturing workshop, and provide intelligent services for accurate prediction and control of the production process, is an urgent problem that needs to be solved. Summary of the Invention

[0003] The present invention provides a method and device for constructing a digital twin model of a process manufacturing workshop, which are used to construct a digital twin model of a workshop; and provides a method and device for constructing a digital twin system of a process manufacturing workshop, which are used to construct a digital twin system of a workshop.

[0004] The technical solution of the present invention is: a method for constructing a digital twin model of a process manufacturing workshop, comprising:

[0005] Use industrial modeling software to model the geometric and physical properties of each element of the process manufacturing physical workshop and build a static physical model SPM;

[0006] Based on the association between dynamic data in the physical workshop of process manufacturing, a dynamic data relationship model DDRM is constructed;

[0007] Establish a data communication interface DCI, fuse the static physical model SPM and the dynamic data relationship model DDRM, and complete the construction of a multi-dimensional digital twin model of workshop elements.

[0008] Optionally, the multidimensional digital twin model of workshop elements is formed by integrating a static physical model and a dynamic data relationship model. The expression of the multidimensional digital twin model DTM of workshop elements is:

[0009] DTM=SPM∪DDRM∪DCI

[0010] Among them: SPM is the static physical model; DDRM is the dynamic data relationship model; DCI is the data communication interface.

[0011] Optionally, the expression for model fusion of the static physical model SPM and the dynamic data relationship model DDRM is:

[0012] F=O∪U

[0013] DDRM={S,C}

[0014] O={o1,o2,…,o q}

[0015] C={c1,c2,…,c t}and

[0016]

[0017]

[0018] Among them: F represents reasonable evaluation rules; O represents reasonable constraint relationship, q represents the qth reasonable constraint relationship; U represents the reasonable operation threshold, u P represents the Pth reasonable operation threshold; S represents the equipment operation parameter set, S P represents the Pth operating parameter of the equipment; C represents the production process parameter data set, c t represents the tth process parameter; Indicates that S acts on C; WE represents workshop events; Z represents the event evaluation mechanism; It indicates that the process parameters constitute the workshop events WE, and the workshop events WE in the workshop are evaluated by the event evaluation mechanism Z; Indicates that the device operating parameters match the operating threshold characteristics; It indicates that reasonable evaluation rules and event evaluation mechanism are effectively integrated.

[0019] The fusion step comprises:

[0020] By analyzing the hierarchical structure of the static physical model SPM, the reasonable constraint relationship and reasonable operation threshold in the static physical model SPM are established, and a reasonable evaluation rule including the reasonable constraint relationship and reasonable operation threshold is constructed;

[0021] Based on the dynamic changes of dynamic data in the dynamic data relationship model DDRM, a mapping relationship between production process dynamic data and production line events is established to generate an event evaluation mechanism;

[0022] The event evaluation mechanism compares and determines the current production line events with the workshop production process; the rationality of the reasonable constraint relationship and reasonable operation threshold in the static physical model is determined through reasonable evaluation rules; and feature matching is performed between the equipment operation parameter data of the production line and the reasonable operation threshold;

[0023] Through the data communication interface DCI, the real-time driving of static physical models by dynamic data and the real-time mapping of dynamic data are realized, and the effective integration of reasonable evaluation rules and event evaluation mechanisms is completed; the construction of a multi-dimensional digital twin model of workshop elements is completed.

[0024] According to another aspect of the present invention, a device for constructing a digital twin model of a process manufacturing workshop is provided, comprising:

[0025] The first building module is used to model the geometric and physical properties of various elements of the process manufacturing physical workshop through industrial modeling software to build a static physical model SPM;

[0026] The second building module is used to build a dynamic data relationship model DDRM based on the association relationship between the dynamic data of the process manufacturing physical workshop;

[0027] The third construction module is used to establish the data communication interface DCI, fuse the static physical model SPM and the dynamic data relationship model DDRM, and complete the construction of the multi-dimensional digital twin model of the workshop elements.

[0028] According to another aspect of the present invention, a method for constructing a digital twin system of a process manufacturing workshop is provided, comprising any one of the above-mentioned methods for constructing a digital twin model of a process manufacturing workshop, further comprising:

[0029] The multidimensional digital twin models of workshop elements are graded according to the composition structure of the physical workshop to obtain a multidimensional digital twin model at the workshop level;

[0030] Build a digital twin system consisting of a physical production line system, a virtual production line system, a production line information service system, and a twin data system; the virtual production line system includes a multi-dimensional digital twin model at the workshop level;

[0031] The physical production line system, virtual production line system and production line information service system are interacted and iteratively operated in pairs through the twin data system to complete the construction of the digital twin system of the process manufacturing workshop.

[0032] Optionally, the multi-dimensional digital twin model of workshop elements is divided into three physical levels according to the composition structure of the physical workshop: unit level, production line level, and workshop level. The model expression is as follows:

[0033] DTM ws =n×DTM pl +DTM ev

[0034] DTM pl =n1×DTM eq +n2×DTM pr +n3×DTM pe

[0035] Where: n, n1, n2, n3 represent the number of virtual representations of the corresponding twin model; DTM ws It is a workshop-level digital twin model; DTM pl It is a production line-level digital twin model; DTM ev Digital twin model of environmental elements; DTM eq DTM is the digital twin model of the device pr Digital twin model of materials / products; DTM pe A digital twin model for personnel.

[0036] Optionally, the physical production line system, the virtual production line system, and the production line information service system interact and iteratively operate in pairs through the twin data system to complete the construction of the digital twin system of the process manufacturing workshop, including:

[0037] The production line information service system communicates data with the physical production line system. Based on the production line information service system's acquisition of the physical production line system's production factor resources, the production line information service system allocates resources for production factors and formulates a production task plan. The physical production line system is used to obtain the production task plan formulated by the production line information service system for production operation and transmit the dynamic data generated by the production operation to the twin data system.

[0038] The physical production line system and the virtual production line system are mapped to each other. The virtual production line system monitors the production and operation status of the physical production line system in real time, establishes correlations between dynamic data based on the dynamic data of the physical production line system, and issues real-time warnings on the operation status of the physical production line system, thus achieving supervision of the physical production line system.

[0039] The production line information service system and the virtual production line system provide information feedback. The production line information service system obtains early warning information from the virtual production line system and optimizes the production task plan based on the early warning information.

[0040] The interactions between the systems continue to iterate until the production task is completed;

[0041] Among them, data interaction between the physical production line system, the virtual production line system and the production line information service system is realized through the twin data system.

[0042] According to another aspect of the present invention, a device for constructing a digital twin system of a process manufacturing workshop is provided, comprising the above-mentioned device for constructing a digital twin model of a process manufacturing workshop, and further comprising:

[0043] An acquisition module is used to classify the multidimensional digital twin models of workshop elements according to the composition structure of the physical workshop to obtain a multidimensional digital twin model at the workshop level;

[0044] The first building block is used to construct a digital twin system consisting of a physical production line system, a virtual production line system, a production line information service system, and a twin data system. The virtual production line system includes a multi-dimensional digital twin model at the workshop level.

[0045] The second construction module is used to enable the physical production line system, virtual production line system and production line information service system to interact and iteratively operate in pairs through the twin data system to complete the construction of the digital twin system of the process manufacturing workshop.

[0046] The beneficial effects of the present invention are:

[0047] In view of the serious coupling between processes in the process manufacturing process, the difficulty in process modeling, and the equipment operating parameters and process parameters in different process specifications are closely related to the performance index parameters, it is urgent to realize the intelligent prediction and timely feedback of the process manufacturing production process. The present invention provides a process manufacturing workshop digital twin model and digital twin system driven by data and model fusion, which realizes the fusion drive of data and model, and transforms the coupling relationship between processes in the process manufacturing production process into the coupling relationship between each twin model parameter. The proposed fusion method fundamentally guarantees the accuracy of the data source and avoids the disorder of the prediction results caused by data errors. In addition, the present invention can effectively realize the management of workshop equipment, visual management of process parameters, early warning of production process and optimization of production information feedback, enhance the high integration and optimization decision-making of process production workshops, and lay the foundation for intelligent control of workshops. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is the overall architecture diagram for building a digital twin model of a workshop;

[0049] Figure 2 This is a diagram of a digital twin model of a workshop according to an embodiment of the present invention;

[0050] Figure 3 It is a flow chart that integrates the static physical model and the dynamic data relationship model;

[0051] Figure 4 This is the overall architecture diagram of the digital twin system of the process manufacturing workshop;

[0052] Figure 5 It is the internal model hierarchy diagram of the workshop multi-dimensional digital twin model;

[0053] Figure 6 It is the iterative operation diagram of the digital twin system of the process manufacturing workshop;

[0054] Figure 7 This is a digital twin system diagram of a process manufacturing workshop in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] The invention will be further described below with reference to the accompanying drawings and embodiments, but the content of the present invention is not limited to the scope of the drawings.

[0056] like Figure 1-Figure 2 As shown, a method for constructing a digital twin model of a process manufacturing workshop includes:

[0057] The geometric and physical properties of each element of the process manufacturing physical workshop are modeled through industrial modeling software to construct a static physical model SPM; wherein, the geometric and physical properties include equipment size, equipment structure, constraint relationship, and physical properties; NX, Creo, 3Dmax and other industrial modeling software are used to perform proportional modeling of the geometric and physical properties of the physical workshop to achieve model accuracy; 3Dmax's surface reduction processing technology is used to achieve model lightweighting without affecting the accuracy of the model; the constructed model is further imported into Unity 3D to realize model interaction, fusion and visualization; thereby constructing a precise, lightweight, visual, interactive and fusionable static physical model.

[0058] Based on the association between dynamic data in the physical workshop of process manufacturing, a dynamic data relationship model DDRM is constructed;

[0059] Specifically, dynamic data includes the operating parameters, process parameters and performance index parameters of the elements in the production process; the collected multi-source heterogeneous dynamic data are standardized; and then a neural network model is used to fit the functional relationship, that is, the correlation relationship, between the operating parameters, process parameters and performance index parameters of each element, thereby constructing a standardized, optimizable, interactive and fusion-enabled dynamic data relationship model.

[0060] Establish a data communication interface DCI, fuse the static physical model SPM and the dynamic data relationship model DDRM, and complete the construction of a multi-dimensional digital twin model of workshop elements.

[0061] Taking the silk production test line of a certain process manufacturing enterprise as an example, the key elements of the production test line include a parameter mixing machine, a silk cutting machine, a fragrance adding machine, a leaf moistening machine, a silk drying machine, a heating and humidifying machine, an industrial robot, materials, and an environment; a static physical model SPM is constructed for each element; taking the leaf moistening machine as an example, the dimensions of each component in the leaf moistening machine are obtained through industrial measurement tools, and each component is proportionally three-dimensionally modeled through industrial modeling software; the geometric model of the leaf moistening machine is formed through the constraint relationship between the components; physical properties such as material and appearance are added to the geometric model in the industrial modeling software to obtain a geometric physical model, and then the surface reduction processing is performed; the geometric physical modeling of other elements is carried out in the same way; after the geometric physical modeling of all elements is completed, the lightweight geometric physical model is then imported into Unity 3D to complete the construction of the static physical model SPM; it should be noted that in the present invention, all geometric physical properties are constructed through industrial modeling software, which can solve the problem of increased workload compared to constructing physical properties through Unity 3D.

[0062] Based on the correlation between dynamic data in the physical workshop of process manufacturing, a dynamic data relationship model (DDRM) was constructed. Taking the loosening and moistening process of the leaf moistening machine as an example, standardized dynamic data of the loosening and moistening process was obtained through the MES system. A neural network model was used to fit the functional relationship between the operating parameters of each element, process parameters, and performance index parameters to form the dynamic data relationship model (DDRM).

[0063] Furthermore, the multidimensional digital twin model of workshop elements is formed by integrating the static physical model and the dynamic data relationship model. The expression of the multidimensional digital twin model DTM of workshop elements is:

[0064] DTM=SPM∪DDRM∪DCI

[0065] Among them: SPM is the static physical model; DDRM is the dynamic data relationship model; DCI is the data communication interface.

[0066] Optionally, the expression for model fusion of the static physical model SPM and the dynamic data relationship model DDRM is:

[0067] F=O∪U

[0068] DDRM={S,C}

[0069] O={o1,o2,…,o q}

[0070] C={c1,c2,…,c t}and

[0071]

[0072]

[0073] Among them: F represents reasonable evaluation rules; O represents reasonable constraint relationship, q represents the qth reasonable constraint relationship; U represents the reasonable operation threshold, u P represents the Pth reasonable operation threshold; S represents the equipment operation parameter set, S P represents the Pth operating parameter of the equipment; C represents the production process parameter data set, c t represents the tth process parameter; Indicates that S acts on C; WE represents workshop events; Z represents the event evaluation mechanism; It indicates that the process parameters constitute the workshop events WE, and the workshop events WE in the workshop are evaluated by the event evaluation mechanism Z; Indicates that the device operating parameters match the operating threshold characteristics; It indicates that reasonable evaluation rules and event evaluation mechanism are effectively integrated.

[0074] Furthermore, if Figure 3 As shown, the fusion steps include:

[0075] By analyzing the hierarchical structure of the static physical model SPM, the reasonable constraint relationship and reasonable operation threshold in the static physical model SPM are established, and a reasonable evaluation rule including the reasonable constraint relationship and reasonable operation threshold is constructed;

[0076] Based on the dynamic changes of dynamic data in the dynamic data relationship model DDRM, a mapping relationship between production process dynamic data and production line events is established to generate an event evaluation mechanism;

[0077] The event evaluation mechanism compares and determines the current production line events with the workshop production process; the rationality of the reasonable constraint relationship and reasonable operation threshold in the static physical model is determined through reasonable evaluation rules; and feature matching is performed between the equipment operation parameter data of the production line and the reasonable operation threshold;

[0078] Through the data communication interface DCI, the real-time driving of static physical models by dynamic data and the real-time mapping of dynamic data are realized, and the effective integration of reasonable evaluation rules and event evaluation mechanisms is completed; the construction of a multi-dimensional digital twin model of workshop elements is completed.

[0079] Specifically:

[0080] (1) By analyzing the hierarchical structure of the static physical model (SPM), the constraint relationships between the physical models of each level and each element are explored, and reasonable constraint relationships and reasonable operation thresholds in the static physical model (SPM) are established. A reasonable evaluation rule including reasonable constraint relationships and reasonable operation thresholds is constructed. For example, the static physical model of an industrial robot arm should have the same reasonable constraint relationships as the physical entity, such as size constraints and angle constraints, to ensure the rationality of the static physical model. At the same time, the operation thresholds of each physical model are established, and the reasonable operation thresholds of each model are established based on the actual operation range of the physical entity. For example, the operation angles of each joint of the static physical model of an industrial robot arm should be consistent with the entity.

[0081] Table 1 Reasonable operating thresholds for industrial robotic arms

[0082]

[0083] (2) Conduct in-depth analysis of the dynamic data in the dynamic data relationship model (DDRM), analyze the dynamic changes of production process data based on the real-time changes of equipment operation data, and establish a mapping relationship between production process dynamic data and production line events, analyze the rationality of the production line event logic, and generate an event evaluation mechanism.

[0084] (3) First, the event evaluation mechanism is used to compare and judge the current production line events with the workshop production process, analyze the rationality of the production line data and events, and provide a basis for the twin model to accurately map the production line events. Secondly, the rationality of the constraint relationship and operation threshold in the static physical model is judged by using reasonable evaluation rules, so that the operation rules of the twin model are consistent with the physical entity. After that, the equipment operation data of the production line is matched with the reasonable operation threshold to ensure the correctness of the real-time operation data. Finally, the real-time driving of the static physical model by dynamic data and the real-time mapping of dynamic data are realized through the data communication interface DCI, completing the effective integration of reasonable evaluation rules and event evaluation mechanism. For example, taking the operation of an industrial robot arm in a production process at a certain moment, an event evaluation mechanism should first be used to compare the currently mapped production line event (robot arm movement) with the production process. If the physical robot arm does not move, but the currently mapped production line event is to make the robot arm move, it is determined that the event does not match the production process and dynamic data needs to be re-collected. If the event matches the production process, the constraint relationship and operation threshold in the static physical model of the robot arm are set and judged to ensure the rationality of the static physical model. Then, the real-time operation parameter data of the robot arm is compared with the reasonable operation threshold. If the real-time operation parameter data meets the reasonable operation threshold of the robot arm, the real-time data is used to drive the static physical model and the data is mapped in real time (specifically: the element operation parameters drive the static physical model, and the process parameters and performance indicator parameters are displayed in real time through the display board to achieve real-time mapping; the performance indicator parameters include predicted performance indicator parameters and real-time performance indicator parameters. Among them, the dynamic data relationship model DDRM can be used to predict performance indicator parameters, and the predicted performance indicator parameters are displayed through the display board of the static physical model).

[0085] According to another aspect of the present invention, a device for constructing a digital twin model of a process manufacturing workshop is provided, comprising:

[0086] The first building module is used to model the geometric and physical properties of various elements of the process manufacturing physical workshop through industrial modeling software to build a static physical model SPM;

[0087] The second building module is used to build a dynamic data relationship model DDRM based on the association relationship between the dynamic data of the process manufacturing physical workshop;

[0088] The third construction module is used to establish the data communication interface DCI, fuse the static physical model SPM and the dynamic data relationship model DDRM, and complete the construction of the multi-dimensional digital twin model of the workshop elements.

[0089] According to another aspect of the present invention, a method for constructing a digital twin system of a process manufacturing workshop is provided, comprising any one of the above-mentioned methods for constructing a digital twin model of a process manufacturing workshop, further comprising:

[0090] The multidimensional digital twin models of workshop elements are graded according to the composition structure of the physical workshop to obtain a multidimensional digital twin model at the workshop level;

[0091] Construct a digital twin system consisting of a physical production line system, a virtual production line system, a production line information service system, and a twin data system, such as Figure 4 As shown in the figure, the virtual production line system includes a multi-dimensional digital twin model at the workshop level. The specific expression is DTS = {PS, VS, IS, DS}, where PS is the physical production line system, VS is the virtual production line system, IS is the production line information service system, and DS is the twin data system.

[0092] The physical production line system, virtual production line system and production line information service system are interacted and iteratively operated in pairs through the twin data system to complete the construction of the digital twin system of the process manufacturing workshop.

[0093] Furthermore, if Figure 5 As shown in the figure, the multi-dimensional digital twin model of workshop elements is divided into three physical levels according to the composition structure of the physical workshop: unit level, production line level, and workshop level. The model expression is as follows:

[0094] DTM ws =n×DTM pl +DTM ev

[0095] DTM pl =n1×DTM eq +n2×DTM pr +n3×DTM pe

[0096] Where: n, n1, n2, n3 represent the number of virtual representations of the corresponding twin model; DTM ws It is a workshop-level digital twin model; DTM pl It is a production line-level digital twin model; DTM ev Digital twin model of environmental elements; DTM eq DTM is the digital twin model of the device pr Digital twin model of materials / products; DTM pe A digital twin model for personnel.

[0097] Furthermore, if Figure 6As shown, the physical production line system, virtual production line system, and production line information service system interact and iteratively operate in pairs through the twin data system to complete the construction of the digital twin system of the process manufacturing workshop, including:

[0098] Data communication is carried out between the production line information service system (IS) and the physical production line system (PS). Based on the acquisition of production factor resources of the physical production line system by the production line information service system, the production line information service system allocates resources for production factors and formulates production task plans. The physical production line system is used to obtain the production task plans formulated by the production line information service system for production operation and transmit the dynamic data generated by the production operation to the twin data system.

[0099] The physical production line system (PS) and the virtual production line system (VS) are mapped to each other. The virtual production line system monitors the production and operation status of the physical production line system in real time, establishes correlations between dynamic data based on the dynamic data of the physical production line system (PS), and issues real-time warnings on the operation status of the physical production line system, thus achieving supervision of the physical production line system (PS).

[0100] Information feedback is provided between the production line information service system (IS) and the virtual production line system (VS). The production line information service system obtains early warning information from the virtual production line system and optimizes the production task plan based on the early warning information (for example, the early warning information can be the predicted value of the performance parameter);

[0101] The interactions between the systems continue to iterate until the production task is completed;

[0102] Among them, data interaction between the physical production line system, the virtual production line system and the production line information service system is realized through the twin data system.

[0103] According to another aspect of the present invention, a device for constructing a digital twin system of a process manufacturing workshop (including a first construction module, a second construction module, and a third construction module) is provided, including the above-mentioned device for constructing a digital twin model of a process manufacturing workshop, and further including:

[0104] An acquisition module is used to classify the multidimensional digital twin models of workshop elements according to the composition structure of the physical workshop to obtain a multidimensional digital twin model at the workshop level;

[0105] The first building block is used to construct a digital twin system consisting of a physical production line system, a virtual production line system, a production line information service system, and a twin data system. The virtual production line system includes a multi-dimensional digital twin model at the workshop level.

[0106] The second construction module is used to enable the physical production line system, virtual production line system and production line information service system to interact and iteratively operate in pairs through the twin data system to complete the construction of the digital twin system of the process manufacturing workshop.

[0107] The construction of a digital twin system for a process manufacturing workshop begins with the construction of a digital twin model for workshop elements. The twin model is then divided into three levels based on the physical structure of the workshop: unit level, production line level, and workshop level. A digital twin system is then established, consisting of a physical production line system, a virtual production line system, a production line information service system, and a twin data system. Finally, through the closed-loop operation of the digital twin system, visual monitoring, intelligent prediction, and iterative optimization of the process manufacturing workshop are achieved. Therefore, digital twin technology is used to construct a digital twin system for a process manufacturing workshop. By adopting digital twin system operating mechanisms such as real-time interaction and iterative operation between the twin model and the physical entity, three-dimensional visual monitoring, intelligent prediction, and production control functions are achieved for the production process in the process manufacturing workshop, significantly improving production efficiency and quality.

[0108] Taking the silk production test line of a process manufacturing enterprise as an example, a digital twin system construction device for a process manufacturing workshop is used to build its digital twin system. Figure 7 As shown in the figure: the production line operation equipment and data acquisition devices of the silk production test line are divided into a physical production line system, which not only ensures the production activities of the physical production line system, but also ensures its data acquisition capabilities; constructs a virtual production line system that combines static mapping and dynamic mapping of the physical production line system; builds a production line information service system that provides specific support and services for the production activities of the silk production test line; builds an integrated and shared digital twin system for the silk production test line digital twin system, eliminates information barriers, and opens up data channels.

[0109] The specific embodiments of the present invention are described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Various changes can be made within the knowledge of ordinary technicians in this field without departing from the scope of the present invention.

Claims

1. A method for constructing a digital twin model of a process manufacturing workshop, characterized by: include: Use industrial modeling software to model the geometric and physical properties of each element of the process manufacturing physical workshop and build a static physical model SPM; Based on the association between dynamic data in the physical workshop of process manufacturing, a dynamic data relationship model DDRM is constructed; Establish a data communication interface (DCI), integrate the static physical model (SPM) with the dynamic data relationship model (DDRM), and complete the construction of a multi-dimensional digital twin model of workshop elements. The expression for model fusion of the static physical model SPM and the dynamic data relationship model DDRM is: F=O∪U DDRM={S,C} O={o1,o2,…,o q } C={c1,c2,…,c t }and Among them: F represents reasonable evaluation rules; O represents reasonable constraint relationship, q represents the qth reasonable constraint relationship; U represents the reasonable operation threshold, u P represents the Pth reasonable operation threshold; S represents the equipment operation parameter set, S P represents the Pth operating parameter of the equipment; C represents the production process parameter data set, c t represents the tth process parameter; Indicates that S acts on C; WE represents workshop events; Z represents the event evaluation mechanism; It indicates that the process parameters constitute the workshop events WE, and the workshop events WE in the workshop are evaluated by the event evaluation mechanism Z; Indicates that the device operating parameters match the operating threshold characteristics; It indicates that reasonable evaluation rules and event evaluation mechanism are effectively integrated.

2. The method for constructing a digital twin model of a process manufacturing workshop according to claim 1, characterized in that: The multidimensional digital twin model of workshop elements is formed by integrating the static physical model and the dynamic data relationship model. The expression of the multidimensional digital twin model DTM of workshop elements is: DTM=SPM∪DDRM∪DCI Among them: SPM is the static physical model; DDRM is the dynamic data relationship model; DCI is the data communication interface.

3. The method for constructing a digital twin model of a process manufacturing workshop according to claim 1, characterized in that: The fusion step comprises: By analyzing the hierarchical structure of the static physical model SPM, the reasonable constraint relationship and reasonable operation threshold in the static physical model SPM are established, and a reasonable evaluation rule including the reasonable constraint relationship and reasonable operation threshold is constructed; Based on the dynamic changes of dynamic data in the dynamic data relationship model DDRM, a mapping relationship between production process dynamic data and production line events is established to generate an event evaluation mechanism; The event evaluation mechanism compares and determines the current production line events with the workshop production process; the rationality of the reasonable constraint relationship and reasonable operation threshold in the static physical model is determined through reasonable evaluation rules; and feature matching is performed between the equipment operation parameter data of the production line and the reasonable operation threshold; Through the data communication interface DCI, the real-time driving of static physical models by dynamic data and the real-time mapping of dynamic data are realized, and the effective integration of reasonable evaluation rules and event evaluation mechanisms is completed; the construction of a multi-dimensional digital twin model of workshop elements is completed.

4. A device for constructing a digital twin model of a process manufacturing workshop, characterized by: include: The first building module is used to model the geometric and physical properties of various elements of the process manufacturing physical workshop through industrial modeling software to build a static physical model SPM; The second building module is used to build a dynamic data relationship model DDRM based on the association relationship between the dynamic data of the process manufacturing physical workshop; The third construction module is used to establish the data communication interface DCI, integrate the static physical model SPM and the dynamic data relationship model DDRM, and complete the construction of the multi-dimensional digital twin model of the workshop elements; The expression for model fusion of the static physical model SPM and the dynamic data relationship model DDRM is: F=O∪U DDRM={S,C} O={o1,o2,…,o q } C={c1,c2,…,c t }and Among them: F represents reasonable evaluation rules; O represents reasonable constraint relationship, q represents the qth reasonable constraint relationship; U represents the reasonable operation threshold, u P represents the Pth reasonable operation threshold; S represents the equipment operation parameter set, S P represents the Pth operating parameter of the equipment; C represents the production process parameter data set, c t represents the tth process parameter; Indicates that S acts on C; WE represents workshop events; Z represents the event evaluation mechanism; It indicates that the process parameters constitute the workshop events WE, and the workshop events WE in the workshop are evaluated by the event evaluation mechanism Z; Indicates that the device operating parameters match the operating threshold characteristics; It indicates that reasonable evaluation rules and event evaluation mechanism are effectively integrated.

5. A method for constructing a digital twin system for a process manufacturing workshop, characterized by: The method for constructing a digital twin model of a process manufacturing workshop according to any one of claims 1 to 3 further includes: The multidimensional digital twin models of workshop elements are graded according to the composition structure of the physical workshop to obtain a multidimensional digital twin model at the workshop level; Build a digital twin system consisting of a physical production line system, a virtual production line system, a production line information service system, and a twin data system; the virtual production line system includes a multi-dimensional digital twin model at the workshop level; The physical production line system, virtual production line system and production line information service system are interacted and iteratively operated in pairs through the twin data system to complete the construction of the digital twin system of the process manufacturing workshop.

6. The method for constructing a digital twin system for a process manufacturing workshop according to claim 5, characterized in that: The multi-dimensional digital twin model of workshop elements is divided into three physical levels according to the composition structure of the physical workshop: unit level, production line level, and workshop level. The model expression is as follows: DTM ws =n×DTM pl +DTM ev DTM pl =n1×DTM eq +n2×DTM pr +n3×DTM pe Where: n, n1, n2, n3 represent the number of virtual representations of the corresponding twin model; DTM ws It is a workshop-level digital twin model; DTM pl It is a production line-level digital twin model; DTM ev Digital twin model of environmental elements; DTM eq DTM is the digital twin model of the device pr Digital twin model of materials / products; DTM pe A digital twin model for personnel.

7. The method for constructing a digital twin system for a process manufacturing workshop according to claim 5, characterized in that: The physical production line system, virtual production line system, and production line information service system interact and iteratively operate in pairs through the twin data system to complete the construction of the digital twin system of the process manufacturing workshop, including: The production line information service system communicates data with the physical production line system. Based on the production line information service system's acquisition of the physical production line system's production factor resources, the production line information service system allocates resources for production factors and formulates a production task plan. The physical production line system is used to obtain the production task plan formulated by the production line information service system for production operation and transmit the dynamic data generated by the production operation to the twin data system. The physical production line system and the virtual production line system are mapped to each other. The virtual production line system monitors the production and operation status of the physical production line system in real time, establishes correlations between dynamic data based on the dynamic data of the physical production line system, and issues real-time warnings on the operation status of the physical production line system, thus achieving supervision of the physical production line system. The production line information service system and the virtual production line system provide information feedback. The production line information service system obtains early warning information from the virtual production line system and optimizes the production task plan based on the early warning information. The interactions between the systems continue to iterate until the production task is completed; Among them, data interaction between the physical production line system, the virtual production line system and the production line information service system is realized through the twin data system.

8. A device for constructing a digital twin system for a process manufacturing workshop, characterized by: The device for constructing a digital twin model of a process manufacturing workshop according to claim 4 further comprises: An acquisition module is used to classify the multidimensional digital twin models of workshop elements according to the composition structure of the physical workshop to obtain a multidimensional digital twin model at the workshop level; The first building block is used to construct a digital twin system consisting of a physical production line system, a virtual production line system, a production line information service system, and a twin data system. The virtual production line system includes a multi-dimensional digital twin model at the workshop level. The second construction module is used to enable the physical production line system, virtual production line system and production line information service system to interact and iteratively operate in pairs through the twin data system to complete the construction of the digital twin system of the process manufacturing workshop.

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