Modeling method of manufacturing resource information model based on automation component

Abstract

The invention discloses a manufacturing resource information model modeling method based on an automation component in the field of model modeling, and the method comprises the following steps: building an asset model for asset equipment: carrying out the digital modeling of entity production equipment or modular control equipment, therefore, the working state and the working effect of the current entity equipment can be displayed in an asset model mode, and an input and output port is set for the asset model exported by the asset equipment according to the production demand and the production result of the entity production equipment. Therefore, an expected production result of the current entity production equipment can be obtained by performing data input on the asset model, and the automatic component is constructed by an automatic component model and comprises an asset model and a function model which respectively correspond to an asset entity and a function entity, so that modeling of manufacturing resource entities and functions is realized. The manufacturing resources involved in the production process can be conveniently modeled, and the integrity of information modeling in the production process is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of model modeling, and particularly to a method for modeling a manufacturing resource information model based on automated components. Background Art

[0002] Manufacturing resources in the production process include many elements such as people, machines, materials, and environment required in the production process, which are distributed in all links of the entire life cycle of intelligent factory production, support the execution of the production process, and are also an important part of the information modeling of the production process. By modeling the manufacturing resources in the production process and clarifying the various parameter attributes involved, it provides a model and data basis for the information modeling of the production process.

[0003] Traditional manufacturing resource modeling usually focuses on the modeling of manufacturing equipment itself. By analyzing the parameters and attributes of different manufacturing equipment, various categories such as static and dynamic are formed, and the relevant attributes of the manufacturing equipment are classified accordingly, thus completing the information modeling of the manufacturing equipment. On the one hand, the use of this modeling method is limited to the single classification of manufacturing equipment, and it fails to construct information models other than manufacturing equipment according to this modeling method, such as other production factors like people, materials, and environment, with relatively large limitations; on the other hand, the modeling mainly reflects information such as the parameters and indicators of the manufacturing equipment, and does not include the functions of the equipment, their interconnections and interactions during use. It is okay for the information modeling of the manufacturing equipment itself, but it cannot meet the requirements in more extensive applications such as the information modeling of the production process.

[0004] The existing manufacturing resource information modeling technology has a single application object and scope, has limitations, and cannot reflect the functions and mutual connections and interactions of manufacturing resources in actual applications. The present invention uses automated components as the modeling basis to perform information modeling on various manufacturing resources involved in the production process, and can describe the asset information and logical functions of the manufacturing resources, supporting the representation of the manufacturing resources and the information interaction between the manufacturing resources. Summary of the Invention

[0005] The purpose of this part is to outline some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this part, as well as in the abstract and title of the present invention, to avoid obscuring the purpose of this part, the abstract, and the title. However, such simplifications or omissions shall not be used to limit the scope of the present invention.

[0006] The object of the present invention is to address the technical problems existing in the background art. The present invention proposes a method for modeling a manufacturing resource information model based on automated components. This method divides manufacturing resources into multiple different sets of automated components, and describes the asset information and logical functions of manufacturing resources through the sets of automated components. Automated components are constructed by an automated component model, which includes an asset model and a function model, corresponding to an asset entity and a function entity respectively, thereby realizing the modeling of manufacturing resource entities and functions. It can conveniently model the manufacturing resources involved in the production process and improve the integrity of production process information modeling.

[0007] The present invention proposes a method for modeling a manufacturing resource information model based on automated components, including the following steps:

[0008] Step S1: Establish an asset model for asset equipment. In this step, digital modeling is performed on physical production equipment or modular control equipment, so that the working state and working effect of the current physical equipment can be displayed in the form of an asset model. Input and output ports are set for the asset model exported from the asset equipment according to the production requirements and production results of the physical production equipment, so that the expected production results of the current physical production equipment can be obtained by inputting data into the asset model.

[0009] Step S2: Establish a function model for function modules. In this step, the function steps of the function modules are recorded, so that a function model can be formed. By gradually recording the execution steps in the function modules and standardizing the input information and output information of the function modules, the function model has a unified input / output data interface, and at the same time, by directly calling the function model, operations on the internal steps of the function modules can be avoided, realizing the packaged operation and processing of the function modules.

[0010] Step S3: Generate an automated component model. In this step, the asset model and the function model that are mutually related are combined under the same automated component model. By reserving a call interface in the automated component model, the asset model inside the automated component model can be accessed according to actual usage requirements, and the function model inside the automated component model can be run. By setting different levels of access permissions for the call interface, the protection of the asset model data inside the automated component model can be realized, and only the results calculated by the corresponding function model are output during the use of the function model, hiding the specific calculation steps inside it, and avoiding external influence on the inside of the automated component model.

[0011] S4 Establish the internal connection steps of the automated component model. This step connects through the input and output interfaces reserved in the asset model to the input and output interfaces of the operation steps in the function model under the same automated component model, enabling the function model to use the asset model for data calculation and then obtaining the expected production result data under the operation of the function model on the asset model. By standardizing the input and output interfaces of multiple asset models and the function model under the same automated component model, when actually associating data, the input interface of the function model is docked with the total input interface of the automated component model, the output interface of the function model is docked with the input interface of the asset model, and the output interface of the asset model is docked with the total output interface of the automated component model, thus realizing the internal model calculation method of the automated component model. By selecting different asset models and function models for combination when calling the automated component model, different data model calculation effects can be achieved;

[0012] S5 Establish the connection steps between multiple automated component models. This step standardizes and unifies the input and output ports of multiple automated component models. After an automated component model performs input and output model calculations, the result obtained from this automated component model can be input into other automated component models again for further calculation, thus obtaining multiple multiple calculation results, and thus obtaining the comprehensive working effect of multiple automated component models from one data result.

[0013] By adopting the above technical solution, in this solution, the asset equipment and function steps are respectively exported as asset models and function models. Thus, during the model usage process, by the cooperative usage methods of different function models and asset models, the working conditions of actual production equipment can be simulated. Furthermore, the actual equipment production can be arranged according to the data generated by the models, thereby achieving the optimization effect of production equipment.

[0014] Preferably, in the step of establishing the asset model for the asset equipment, the information recorded for the asset equipment includes hard assets and soft assets. Hard assets include equipment, controllers, modules, hardware components, or other hardware products. Soft assets include firmware, software, licenses, etc.

[0015] By adopting the above technical solution, in this solution, by classifying and storing the asset models, different devices can be accurately specified during the calling process. At the same time, through the soft assets, the calling instructions can be detected, thus simulating the effect that specific licenses are required for actual use.

[0016] Preferably, the equipment among the hard assets also consists of different components. In the asset model, different components under the hard assets are registered and the physical attributes of the components are recorded.

[0017] By adopting the above technical solution, this solution can, during the simulation of the actual production process by recording its physical properties, calculate through algorithms the risk of overheating of the equipment and the speed of overheating, and then deduce the true working efficiency.

[0018] Preferably, in the step of establishing a function model for the function module, this step has a self-diagnosis function when executed. When the asset model is running the function model, the function model diagnoses its own running state at this time, and calculates the true working efficiency of the equipment corresponding to the asset model in the actual production environment according to the physical properties of the hard assets in the above asset model, and diagnoses whether there are unexpected situations such as overheating.

[0019] By adopting the above technical solution, this solution can effectively improve the running efficiency of this device through the calling method of the function model, and by packing and integrating the instruction sets of certain functions, the operation difficulty during model simulation is reduced.

[0020] Preferably, in the step of establishing the internal connection of the automation component model, there is a one-to-one or one-to-many association situation during actual association. When a one-to-many association situation occurs, the priority order of the function model needs to be set when the resource model loads the function model. When the resource model reads the function model to run, it sorts according to the different function model priorities, and then runs the function models in different priority orders.

[0021] By adopting the above technical solution, this solution can enable the resource model to execute high-priority instructions in a timely manner through the method of reading in priority order, avoiding the loss of timeliness of the function model.

[0022] Preferably, in the step of establishing connections between multiple automated component models, when this step is being carried out, there may be a situation where the same automated component model is called recursively, or when other automated component models call the current automated component model, the current automated component model is running internally. At this time, when multiple automated component models are combined through connections, a relay buffer is provided. Multiple interrelated automated component models are associated through the relay buffer. The relay buffer does not have a control function for the automated component models. When the relay buffer receives a call instruction from an automated component model to another automated component model, the relay buffer will first query and access the target automated component model to determine whether the current target automated component model is in an idle state. If the target automated component model is in an idle state, a call instruction will be sent to the target automated component model and the current target automated component model will be marked as being in a working state. If the current target automated component model is busy, the relay buffer will store the current call instruction and wait to send the call instruction after receiving a feedback from the target automated component model regarding the query access information. When the relay buffer stores multiple call instructions, they are arranged in the order of generation, and the target automated component models are queried and accessed one by one to complete the transfer of the call instructions.

[0023] By adopting the above technical solution, this solution can effectively improve the stability of the coordinated use of multiple automated component models of this device through the structure of the relay buffer, and avoid problems such as command loss caused by instruction congestion.

[0024] In summary, the present invention includes at least one of the following beneficial effects:

[0025] Manufacturing resources in the production process include many elements such as people, machines, materials, and the environment required in the production process, which are distributed in all links of the entire life cycle of intelligent factory production, supporting the execution of the production process. Manufacturing resources in the production process are composed of an automated component set. Through the automated component set, the asset information and logical functions of manufacturing resources can be described, supporting the representation of manufacturing resources and information interaction between manufacturing resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0027] Figure 1 It is a schematic diagram showing the representation of the production process asset model in a method for modeling a manufacturing resource information model based on automated components according to the present invention;

[0028] Figure 2 Schematic diagram of the automation component model in the embodiment of the present invention;

[0029] Figure 3 Schematic diagram of the asset model representation in the embodiment of the present invention;

[0030] Figure 4 Schematic diagram of the function model representation in the embodiment of the present invention;

[0031] Figure 5 Schematic diagram of the relationship between the asset model and the function model in the embodiment of the present invention;

[0032] Figure 6 Schematic diagram of the interaction between function models in the embodiment of the present invention. Detailed implementation manners

[0033] The following further describes the present invention in detail with reference to the attached Figure 1-6 drawings.

[0034] Embodiment 1

[0035] As Figure 1 - Figure 6 shown, in this embodiment, in order to solve the existing problems, the present invention discloses a method for modeling a manufacturing resource information model based on automation components, including the following steps:

[0036] Step S1 of establishing an asset model for asset equipment, which digitally models the entity production equipment or modular control equipment, so as to be able to display the working state and working effect of the current entity equipment in the form of an asset model, and sets input and output ports for the asset model exported by the asset equipment according to the production requirements and production results of the entity production equipment, so that the expected production results of the current entity production equipment can be obtained by inputting data into the asset model;

[0037] Step S2 of establishing a function model for function modules, which records the function steps of the function modules, so as to form a function model. By gradually recording the execution steps in the function modules and standardizing the input information and output information of the function modules, the function model has a unified input and output data interface, and at the same time, by directly calling the function model, the operation of the steps inside the function modules can be avoided, realizing the packaged operation and processing of the function modules;

[0038] Step S3 for generating an automated component model, which aggregates the asset models and function models that are mutually related under the same automated component model. By reserving call interfaces in the automated component model, the asset models inside the automated component model can be accessed according to actual usage requirements, and the function models inside the automated component model can be run. By setting different levels of access permissions for the call interfaces, it is possible to protect the asset model data inside the automated component model, and only the results calculated by the function model are output during the process of using the function model, hiding the specific calculation steps inside it to avoid external influence on the inside of the automated component model;

[0039] Step S4 for establishing internal connections within the automated component model. This step connects the input and output interfaces reserved in the asset model with the input and output interfaces of the operation steps in the function model under the same automated component model, achieving the effect that the function model uses the asset model for data operations and then obtains the expected production result data under the operation of the function model on the asset model. By standardizing the input and output interfaces of multiple asset models and function models under the same automated component model, when actually associating data, the input interface of the function model is docked with the total input interface of the automated component model, the output interface of the function model is docked with the input interface of the asset model, and the output interface of the asset model is docked with the total output interface of the automated component model, thus realizing the internal model calculation method of the automated component model. By selecting different asset models and function models for combination when calling the automated component model, different data model calculation effects can be achieved;

[0040] Step S5 for establishing connections between multiple automated component models. This step standardizes and unifies the input and output ports of multiple automated component models. After an automated component model performs input-output model calculations, the results obtained by this automated component model can be input into other automated component models for further calculations, thereby obtaining multiple multiple calculation results, and thus obtaining the comprehensive working effects of multiple automated component models from one data result.

[0041] Embodiment 2

[0042] As Figure 1 - Figure 6 shown, in this embodiment, in order to solve the existing problems, based on the same concept as in Embodiment 1 above, this modeling method for a manufacturing resource information model based on automated components further includes: the step of establishing an asset model for the asset equipment, and the information recorded by this step for the asset equipment includes hard assets and soft assets. Hard assets include equipment, controllers, modules, hardware components, or other hardware products, and soft assets include firmware, software, licenses, etc.

[0043] Among the hard assets, the equipment also consists of different components. In the asset model, different components under the hard assets are registered and the physical attributes of the components are recorded.

[0044] For the step of establishing a function model for the function module, this step has a self-diagnosis function when executed. When the asset model is running the function model, the function model diagnoses its own running state at this time, and calculates the actual working efficiency of the equipment corresponding to the asset model in the actual production environment according to the physical attributes of the hard assets in the above asset model, and diagnoses whether there are unexpected situations such as overheating.

[0045] For the step of establishing the internal connection of the automation component model, there are one-to-one or one-to-many association situations in actual association. When there is a one-to-many association situation, it is necessary to set the priority order of the function model when the resource model loads the function model. When the resource model reads the function model and runs, it is sorted according to different function model priorities, and then the function models with different priorities are run in order.

[0046] For the step of establishing the connection between multiple automation component models, when this step is carried out, there will be a situation where the same automation component model is cyclically called or the current automation component model is running internally when other automation component models call the current automation component model. At this time, when multiple automation component models are connected and combined, a relay buffer is set. Multiple interrelated automation component models are associated through the relay buffer. The relay buffer does not have the control function for the automation component model. When the relay buffer receives a call instruction from an automation component model to another automation component model, the relay buffer will first query and access the target automation component model at this time, so as to judge whether the current target automation component model is in an idle state. If the target automation component model is in an idle state, a call instruction will be sent to the target automation component model and the current target automation component model will be marked as being in a working state. If the current target automation component model is busy, the relay buffer will store the current call instruction and wait for the target automation component model to feedback the query access information before sending the call instruction. When the relay buffer stores multiple call instructions, they are arranged in the order of generation, and the target automation component models are queried and accessed one by one to complete the transfer of the call instruction.

[0047] The specific working principle is that the structure of the relay buffer can temporarily store the call commands between multiple groups of automation component models, thus avoiding problems such as instruction forgetting. At the same time, the transfer of the mutual call instructions between multiple automation component models through the time sorting method of the relay buffer can avoid the situation where the target automation component model cannot execute the call instruction currently.

[0048] The above are all preferred embodiments of the present invention, and the protection scope of the present invention is not limited thereby. Therefore, all equivalent changes made according to the structure, shape and principle of the present invention shall be covered within the protection scope of the present invention.

Claims

1. A manufacturing resource information modeling method based on automation components, comprising the following steps: S1 is a step of establishing an asset model for asset equipment. This step digitally models the physical production equipment or modular control equipment, so that the working status and working effect of the current physical equipment can be displayed through the asset model. According to the production requirements and production results of the physical production equipment, the input and output ports of the asset model derived from the asset equipment are set, so that the expected production results of the current physical production equipment can be obtained by inputting data into the asset model; S2 is a step of establishing a functional model for the functional module. This step records the functional steps of the functional module to form a functional model. By gradually recording the execution steps in the functional module and normalizing and restricting the input information and output information of the functional module, the functional model has an agreed input and output data interface. By directly calling the functional model, it is possible to avoid operating the steps inside the functional module, thereby realizing packaged operation processing of the functional module. S3 generates an automation component model step, which collects the asset model and the function model that are related to each other under the same automation component model. By reserving a calling interface in the automation component model, the asset model inside the automation component model can be accessed according to actual use requirements, and the function model inside the automation component model can be run. By setting different levels of access rights for the calling interface, the asset model data inside the automation component model can be protected, and in the process of using the function model, only the results calculated by the function model in the team are output, and the specific calculation steps inside are hidden to avoid external influence on the automation component model. S4 establishes the internal connection step of the automation component model. This step connects the input and output interfaces reserved in the asset model with the input and output interfaces of the operation steps in the function model under the same automation component model, so as to realize the effect that the function model uses the asset model to perform data calculation and then obtains the expected production result data under the operation of the function model. By unifying the input and output interfaces of multiple asset models and function models under the same automation component model, when actually associating data, the input interface of the function model is connected with the total input interface of the automation component model, the output interface of the function model is connected with the input interface of the asset model, and the output interface of the asset model is connected with the total output interface of the automation component model, so as to realize the model calculation method inside the automation component model, and by selecting different asset models and function models for combination when calling the automation component model, so as to realize the data model calculation effect under different circumstances; S5 is a step for establishing connections between multiple automation component models. This step normalizes and unifies the input and output ports of multiple automation component models. After an automation component model performs input and output model calculations, the results obtained by the automation component model can be input into other automation component models again for recalculation, thereby obtaining multiple calculation results, thereby obtaining the integrated working effects of multiple automation component models from one data result.

2. A manufacturing resource information modeling method based on automation components according to claim 1, characterized in that: The step of establishing an asset model for the asset equipment records information about the asset equipment including hard assets and soft assets. Hard assets include equipment, controllers, modules, hardware components or other hardware products, and soft assets include firmware, software, licenses, etc.

3. A manufacturing resource information modeling method based on automation components according to claim 2, characterized in that: The equipment in the hard assets is also composed of different components. In the asset model, the different components under the hard assets are registered and the physical properties of the components are recorded.

4. A manufacturing resource information modeling method based on automation components according to claim 3, characterized in that: The step of establishing a functional model for the functional module has a self-diagnosis function when executed. When the asset model is running the functional model, the functional model diagnoses its own operating status, and calculates the actual working efficiency of the equipment corresponding to the asset model in the actual production environment based on the physical properties of the hard assets in the above-mentioned asset model, and diagnoses whether it has any unexpected situations such as overheating.

5. A manufacturing resource information modeling method based on automation components according to claim 4, characterized in that: The step of establishing the internal connection of the automation component model, in which there is a one-to-one or one-to-many association in actual association. When a one-to-many association occurs, the priority of the functional model needs to be configured when the resource model loads the functional model. When the resource model reads the functional model for operation, the functional model is sorted according to different priorities, and the functional models with different priorities are sequentially operated.

6. A manufacturing resource information modeling method based on automation components according to claim 5, characterized in that: The step of establishing connections between multiple automation component models may result in a situation where the same automation component model is called cyclically or the current automation component model is running when other automation component models call the current automation component model. At this time, when multiple automation component models are connected and combined, a relay buffer is provided, and multiple mutually related automation component models are associated through the relay buffer. The relay buffer does not have a control function for the automation component model. When the relay buffer receives a call instruction from an automation component model to another automation component model, the relay buffer will first query and access the target automation component model to determine whether the current target automation component model is in an idle state. If the target automation component model is in an idle state, a call instruction is sent to the target automation component model and the current target automation component model is marked as being in a working state. If the current target automation component model is in a busy state, the relay buffer will store the current call instruction and wait for the target automation component model to feedback the query access information before sending the call instruction. When the relay buffer stores multiple call instructions, they are arranged in the order in which the instructions are generated, and the target automation component models are queried and accessed one by one to complete the transmission of the call instruction.

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