CN115982996A

CN115982996A - Digital twin modeling and simulation method and system for complex equipment manufacturing process

Info

Publication number: CN115982996A
Application number: CN202211699630.3A
Authority: CN
Inventors: 丁国富; 谢家翔; 郑庆; 张海柱; 付建林
Original assignee: Southwest Jiaotong University
Current assignee: Southwest Jiaotong University
Priority date: 2022-12-28
Filing date: 2022-12-28
Publication date: 2023-04-18

Abstract

The invention discloses a digital twin modeling and simulation method and a system in a complex equipment manufacturing process, wherein the system comprises the following steps: a workshop resource modeling module; a workshop relationship configuration module; the data interface is suitable for and managed the module; a production plan simulation and evaluation module; and a production process monitoring and adjusting module. The invention designs and realizes 5 main functional modules of workshop resource multi-dimensional modeling, workshop relation configuration modeling, data adaptation and management, production plan simulation and evaluation, production process monitoring and adjustment and the like. The system prototype developed by the research supports modeling, simulation and intelligent manufacturing execution application of a digital twin workshop, and has important reference value and reference significance for deep research, popularization and application of twin modeling and data interaction and fusion in the manufacturing stage of complex equipment.

Description

Digital twin modeling and simulation method and system for complex equipment manufacturing process

Technical Field

The invention belongs to the technical field of digital twinning, and particularly relates to a method and a system for modeling and simulating digital twinning in a complex equipment manufacturing process.

Background

The digital twin is a simulation process integrating multidisciplinary, multi-physical quantity, multi-scale and multi-probability by fully utilizing data such as a physical model, sensor updating, operation history and the like, and mapping is completed in a virtual space, so that the full life cycle process of corresponding entity equipment is reflected. Digital twinning is an beyond-realistic concept that can be viewed as a digital mapping system of one or more important, interdependent equipment systems.

The complex equipment refers to a plurality of mechanical devices such as high-speed rails, shield machines and the like with complex structural parts.

The digital twin is one of the ten-war-type technical trends in the future, provides a new concept and tool for the innovation and development of the current manufacturing industry, provides an implementation approach for the information physical fusion of a complex dynamic system, and promotes the innovation of complex equipment, the manufacturing efficiency and the operation and maintenance level to a new height. The manufacturing process is a key link for forming complex equipment, and the quality of the manufacturing process reflects the quality of product design on one hand and also has important influence on the operation and maintenance of the product on the other hand. For this reason, it is necessary to study how to realize high-quality, high-efficiency progress of product manufacturing based on digital twinning at the manufacturing stage. The complex equipment manufacturing process and environment are very complex, and relate to multiple factors such as human, machine, material, method and ring, and multivariate data such as equipment operating parameters, process information, test information and simulation data, so that great challenges are brought to the construction of products in the manufacturing stage and digital twin models in the manufacturing process.

Disclosure of Invention

In view of the above, the invention provides a digital twin modeling and simulation method and system for a complex equipment manufacturing process, which are used for quickly and efficiently building a digital twin model of the complex equipment manufacturing process.

In order to solve the technical problems, the technical scheme of the invention is to adopt a digital twin modeling and simulation system in the manufacturing process of complex equipment, which comprises the following steps:

the workshop resource modeling module is used for modeling production equipment in a physical workshop for manufacturing complex equipment to generate a production equipment model;

the workshop relation configuration module is used for calling the production equipment model to construct a virtual workshop and carrying out relation configuration on the production equipment model in the virtual workshop;

the data interface adaptation and management module is used for establishing a data channel between the actual physical workshop and the virtual workshop to realize data interaction;

the production plan simulation and evaluation module is used for previewing production plans and processes through the virtual workshop and evaluating the performance of the production system under different production plans;

and the production process monitoring and adjusting module is used for monitoring the simulation production process in real time and detecting disturbance, carrying out hypothesis analysis and possible result prediction on the detected disturbance, and carrying out corresponding adjustment on the production process based on the analysis result.

As an improvement, the plant resource modeling module comprises:

the resource creating and attribute editing module is used for creating a logic model of production equipment in a workshop and endowing the logic model with corresponding attributes; the production equipment comprises processing equipment, logistics equipment, storage equipment and auxiliary equipment;

the resource motion topology modeling module is used for creating a motion extension model for the production equipment so as to realize the operation of the production equipment model;

the appearance structure model importing and motion debugging module is used for creating an appearance structure model for the production equipment and associating the appearance structure model with the motion topology model;

and the model integration and encapsulation module is used for encapsulating the logic model, the motion topology model, the appearance structure model, the operation logic and the monitoring variable with the attribute parameters of the production equipment into a production equipment model component for calling.

As a further improvement, the plant relationship configuration module includes:

the workshop equipment layout module is used for creating a virtual workshop, arranging production equipment components, workshop facilities and identifiers in the virtual workshop and realizing mapping of a physical workshop;

the workshop logistics layout module is used for drawing a logistics path and associating a logistics equipment model in the virtual workshop to realize mapping of physical workshop logistics relation;

the service unit configuration module is used for defining virtual service nodes on the logistics path and associating the virtual service nodes with processing or warehousing equipment; generating operation logic of the virtual service node;

and the workshop instance base management module is used for managing the virtual workshop for finishing the layout of workshop equipment, the logistics layout and the configuration of the service units and the attribute information of the virtual workshop.

As another further improvement, the data interface adaptation and management module comprises:

the data interface adaptation module is used for establishing a data interface abstract class which encapsulates connection, disconnection, data reading and communication log functions, and converting the data into a uniform format by using the data interface abstract class;

the virtual sensor configuration module is used for configuring corresponding virtual sensors according to the types of data, and arranging the virtual sensors into the corresponding layers of the virtual workshop according to the layers of the physical workshop, so as to realize the synchronization of the states, the operation parameters and the positions of objects at each layer of the physical workshop and the virtual workshop;

and the virtual sensor management module is used for managing the virtual sensor.

As an improvement, the production plan simulation and evaluation module includes:

the simulation input analysis module is used for converting the production tasks, the process information and the production plans of the physical workshop into a mobile entity set;

the three-dimensional visual simulation module is used for reproducing production and logistics processes in a three-dimensional visual animation mode according to a production plan and acquiring simulation information;

the simulation result counting module is used for collecting and counting the node time of the production activity in the simulation process and calculating an evaluation index;

and the production plan evaluation module is used for processing the obtained evaluation indexes to obtain the comprehensive production system performance scores under different production plans.

As an improvement, the production process monitoring and regulating module comprises:

the equipment state monitoring module is used for monitoring the equipment state of the physical workshop through the equipment state of the virtual workshop;

the execution process monitoring module is used for monitoring the execution process of the physical workshop through the production and logistics processes of the virtual workshop;

the production progress monitoring module is used for monitoring the production progress of the physical workshop according to the workpiece condition of the virtual workshop;

and the production process adjusting module is used for detecting production disturbance and carrying out hypothesis analysis and dynamic adjustment based on the detection conditions of the equipment state, the execution process and the production progress.

The invention also provides a digital twin modeling and simulation method in the complex equipment manufacturing process, which comprises the following steps:

modeling production equipment in a physical workshop for manufacturing complex equipment to generate a production equipment model;

calling a production equipment model to construct a virtual workshop, and carrying out relationship configuration on the production equipment model in the virtual workshop;

establishing a data channel between the actual physical workshop and the virtual workshop to realize data interaction;

previewing a production plan and a production process through a virtual workshop, and evaluating the performance of a production system under different production plans;

and carrying out real-time monitoring and disturbance detection on the simulation production process, carrying out hypothesis analysis and possible result prediction on the detected disturbance, and carrying out corresponding adjustment on the production process based on the analysis result.

As an improvement, the virtual plant is reconstructed based on the update of the physical plant and the adjustment scheme of the production process.

As an improvement, a logic model of production equipment in a workshop is created and corresponding attributes are given;

creating a motion extension model for the production equipment so as to realize the operation of the production equipment model;

establishing an appearance structure model for the production equipment, and associating the appearance structure model with the motion topological model;

and packaging a logic model with attribute parameters, a motion topological model, an appearance structure model, operation logic and monitoring variables of the production equipment into a production equipment model component.

As an improvement, the method for calling the production equipment model to construct the virtual workshop and performing relationship configuration on the production equipment model in the virtual workshop comprises the following steps:

creating a virtual workshop, and arranging production equipment model components, workshop facilities and identifiers in the virtual workshop to realize mapping of a physical workshop;

drawing a logistics path and a related logistics equipment model in the virtual workshop to realize mapping of a physical workshop logistics relation;

defining a virtual service node on a logistics path, and associating the virtual service node with processing or warehousing equipment; and generating the running logic of the virtual service node.

As an improvement, the method for establishing the data channel between the actual physical workshop and the virtual workshop and realizing data interaction comprises the following steps:

establishing a data interface abstract class which encapsulates connection, disconnection, data reading and communication log functions, and converting data into a uniform format by using the data interface abstract class;

and configuring corresponding virtual sensors according to the type of the data, and arranging the virtual sensors into the corresponding layers of the virtual workshop according to the layers of the physical workshop, so as to realize the synchronization of the states, the operation parameters and the positions of the objects of the layers of the physical workshop and the virtual workshop.

As an improvement, the method for forecasting the production plan and the process through the virtual workshop and evaluating the performance of the production system under different production plans comprises the following steps:

converting production tasks, process information and production plans of a physical workshop into a mobile entity set;

according to the production plan, reproducing production and logistics processes in a three-dimensional visual animation mode, and acquiring simulation information;

collecting and counting the node time of the production activity in the simulation process, and calculating an evaluation index;

and processing the obtained evaluation indexes to obtain the comprehensive performance scores of the production system under different production plans.

As an improvement, the method for monitoring the simulated production process in real time and detecting the disturbance, and carrying out hypothesis analysis and possible result prediction on the detected disturbance comprises the following steps of:

monitoring the equipment state of the physical workshop through the equipment state of the virtual workshop;

monitoring the physical workshop execution process through the production and logistics process of the virtual workshop;

monitoring the production progress of a physical workshop through the workpiece condition of the virtual workshop;

and detecting the production disturbance, performing hypothesis analysis and dynamically adjusting based on the detection conditions of the equipment state, the execution process and the production progress.

The invention has the advantages that:

the invention firstly analyzes the system application background and application requirements; and then 5 main functional modules such as workshop resource multi-dimensional modeling, workshop relation configuration modeling, data adaptation and management, production plan simulation and evaluation, production process monitoring and adjustment and the like are designed and realized. The system prototype developed by the research supports modeling, simulation and intelligent manufacturing execution application of a digital twin workshop, and has important reference value and reference significance for deep research, popularization and application of twin modeling and data interaction and fusion in the manufacturing stage of complex equipment.

Drawings

FIG. 1 is a schematic diagram of the structure of the present invention.

FIG. 2 is a flow chart of the present invention.

Detailed Description

In order that those skilled in the art will better understand the technical solutions of the present invention, the present invention will be further described in detail with reference to the following embodiments.

As shown in FIG. 1, the invention provides a digital twin modeling and simulation system for a complex equipment manufacturing process, which comprises the following functional modules:

and the workshop resource modeling module is used for modeling the production equipment in the physical workshop for manufacturing the complex equipment to generate a production equipment model. The workshop resource modeling is a basic module of a digital twin workshop modeling and simulation system, and aims to form a workshop resource library for other functional modules to call through construction and encapsulation of a workshop resource multi-dimensional model. The workshop resources comprise processing equipment, logistics equipment, warehousing equipment and auxiliary equipment 4. The module supports the operations of creation of a logic model of the 4 types of equipment models, attribute editing, motion topology modeling, CAD model import, model encapsulation and management and the like.

Specifically, the module further comprises:

and the resource creating and attribute editing module is used for creating a logic model of the production equipment in the workshop and endowing the logic model with corresponding attributes.

For ease of management, plant resources are categorized into a broad class of process, logistics, warehousing and ancillary equipment 4, according to the role the manufacturing resources play in the plant. Further, each class of device may in turn derive a different object type. For example, the logistics equipment is further divided into sub-categories such as manipulators, stackers, AGVs, conveyor belts, and other logistics equipment. Each subclass has corresponding attribute parameters including resource name, resource type, mechanical structure, performance parameters, etc. The resource creating and attribute editing sub-module provides a resource newly-built operation interface and a corresponding instantiation template for a user. Taking a machine tool as an example, a corresponding machine tool logic model example is created by editing the name, type (lathe, milling machine, drilling machine, etc.), mechanical structure (three-axis, four-axis, five-axis, etc.), performance parameters (stroke, rated power, rated rotation speed, etc.), etc. of the machine tool logic model.

And the resource motion topology modeling module is used for creating a motion extension model for the production equipment so as to realize the operation of the production equipment model.

The topological structure based on the multi-body kinematics is the basis for realizing the motion modeling of complex equipment such as machine tools, robots and the like. The kinematic topology chain includes topology nodes and directional arrows between the topology nodes. The topology nodes represent moving parts of the device; and the directed arrows between the topology nodes describe the parent-child relationship between the two topology nodes, and the child nodes point to the parent nodes. Taking a machine tool as an example, the topological nodes comprise a machine tool body M, a translational axis X, Y, Z node, a rotational axis A, B, C node, a tool node T and a workpiece node W; the topological chain is a double-chain structure taking the lathe bed as a root node and points to the lathe bed M from a workpiece node W and a cutter node T respectively. The motion topological models of various machine tools can be constructed through the topological nodes and the directional arrows. The resource motion topology modeling and management submodule provides a motion topology modeling interface for equipment with complex motion structures, such as processing equipment, logistics equipment and the like, and stores the topology model into a database to realize management of adding, deleting, modifying, checking and the like of the topology model.

And the appearance structure model importing and motion debugging module is used for creating an appearance structure model for the production equipment and associating the appearance structure model with the motion topology model.

In order to be more intuitive and close to a physical workshop, the appearance structure of the equipment is expressed by CAD three-dimensional stereo modeling. The CAD model characterizes the geometric attributes of the device, such as shape, size, color, etc. The module comprises two main functions, namely 1) associating a three-dimensional model drawn by third-party CAD software to a created motion topological model to realize model assembly and motion modeling of equipment; 2) And editing the coordinate origin of each CAD model and the position and the posture of each relative root node, and debugging the motion function of each topological node of the equipment to verify whether the topological model and the corresponding pose parameter are correct.

The digital twin model is a multi-dimensional model that integrates geometry, logic, and data. The logic model, the attribute parameters, the topological model, the CAD model, the operation logic, the monitoring variables and the like of the workshop resources are associated, and the logic model, the attribute parameters, the topological model, the CAD model, the operation logic, the monitoring variables and the like are defined and encapsulated into a CPS-oriented component to form a workshop resource library for being called by subsequent functional modules, so that a virtual workshop is formed.

And the workshop relation configuration module is used for calling the production equipment model to construct a virtual workshop and carrying out relation configuration on the production equipment model in the virtual workshop.

The workshop relation configuration is a specific implementation of hierarchical production relation modeling based on a service unit and networked logistics relation modeling based on a logistics path network on the basis of determining a good workshop resource model. The method needs to meet the requirements of rapid generation of two-dimensional layout of a workshop, rapid modeling of a logistics path network, configuration modeling of service units, management of workshop instances and the like.

Specifically, this module includes:

and the workshop equipment layout module is used for creating a virtual workshop, arranging production equipment model components, workshop facilities and identifiers in the virtual workshop and realizing mapping of the physical workshop.

The module provides a new operation interface and a corresponding instantiation template for a workshop. A new virtual plant is created by editing attributes such as the plant name, the plant area (length x width), etc. And mapping the physical workshop plane layout drawing is realized through workshop resource layout and workshop facility and identification layout. And (3) selecting packaged resources from the created workshop resource library based on 'drag and drop' operation, putting the packaged resources into the workshop, and giving layout attributes comprising positions and postures relative to the origin of the workshop. The layout of the facilities and the marks of the workshop models facilities and marks such as factory buildings, passageways, material storage marks and the like. It is noted that the floating entities such as workpieces cannot be imported through the shop floor layout, but are dynamically created and removed in the virtual shop floor based on the production tasks. Meanwhile, the virtual workshop layout example can be stored as a unit, and the established unit is directly loaded in other more complex workshop layouts, so that the multiplexing and hierarchical layout of the workshop layouts is realized, the layout difficulty is reduced, and the layout time is shortened.

And the workshop logistics layout module is used for drawing a logistics path and associating a logistics equipment model in the virtual workshop to realize mapping of the physical workshop logistics relationship.

The module is designed and developed based on a logistics path network model, aims to realize the depiction of the logistics relationship of a physical workshop, and mainly comprises three subfunctions of logistics path drawing, logistics equipment association and logistics path management. The logistics path drawing provides a convenient logistics path drawing interface for a user, supports drawing of the paths of various logistics equipment such as an AGV, a manipulator with a guide rail, a stacker and the like, and stores the paths in a multi-communication undirected graph mode. The logistics equipment association means that the logistics equipment is associated to the corresponding logistics path. For example, a tracked robot is associated to its track. The logistics path management manages all logistics paths, including operations of adding, deleting, modifying, viewing and the like.

The service unit configuration module is used for defining virtual service nodes on the logistics path and associating the virtual service nodes with processing or warehousing equipment; and generating the running logic of the virtual service node.

The module is designed and developed based on a service unit model, aims to realize the depiction of the hierarchical production relationship of a physical workshop, and mainly comprises the following steps: 1) And configuring the service unit. By defining virtual service nodes on the logistics path and associating the virtual service nodes with the processing or warehousing equipment, corresponding processing service units or warehousing service units can be created. Taking the processing unit as an example, the corresponding input buffer station and output buffer station can be configured, and corresponding logistics equipment is selected to provide loading and unloading service. 2) And modeling the service unit behavior. The service unit automatically generates internal operation logic according to the configuration result, namely workpieces sequentially pass through an input buffer station (if the buffer station is not configured, the buffer station is skipped), a processor and an output buffer station (if the buffer station is not configured, the buffer station is skipped) under the assistance of the logistics equipment. Meanwhile, whether behavior modeling in the service unit is correct or not can be verified through the three-dimensional demonstration animation.

And the workshop instance library management module is used for managing the virtual workshop which completes the layout of workshop equipment, the logistics layout and the configuration of service units and the attribute information thereof.

After the layout of workshop equipment, the layout of logistics and the configuration of service units are completed, a complete virtual workshop consistent with the composition and structure of a physical workshop can be generated. And the workshop instance management sub-module is responsible for managing the established virtual workshop instance and the attribute information thereof, including operations of adding, deleting, modifying, checking and the like.

And the data interface adaptation and management module is used for establishing a data channel between the actual physical workshop and the virtual workshop to realize data interaction.

The module aims to establish a data interaction channel between a physical workshop and a virtual workshop and realize dynamic update from the physical resource state and the operation parameters to a virtual model of the physical workshop and the virtual workshop. The method needs to meet the access and management of various heterogeneous communication protocols and databases, has expansibility and is convenient for the access of other communication protocols; the configuration and management of the multisource monitoring points are met, the adaptability is good, and batch import and unified management of the multisource monitoring points are facilitated.

Specifically, the module comprises:

and the data interface adaptation module is used for establishing a data interface abstract class which encapsulates the functions of connection, disconnection, data reading and communication log, and converting the data into a uniform format by using the data interface abstract class.

Communication protocols are various, and common communication protocols include OPC UA, UDP, MQTT, and the like. In addition, the workshop data is also distributed in different databases, such as Redis, mongoDB, oracle, mySQL, and the like. The method is used for realizing the unified management of various data communication protocols and database interfaces and facilitating the expansion of subsequent protocols. The module comprises a data adaptation function and a data management function. The data adaptation function is to encapsulate basic functions such as basic connection, disconnection, data reading, communication logs and the like by establishing a data interface abstract class, and concrete data communication classes need to be inherited from the abstract class. On the basis of data adaptation, the data management function is responsible for data communication testing and data format conversion, so that the unification of data formats is realized, and upper-layer application is independent of bottom-layer data, namely, the expansion or switching of a data communication protocol does not need to modify an upper-layer application program.

And the virtual sensor configuration module is used for configuring corresponding virtual sensors according to the types of the data, and arranging the virtual sensors into the corresponding layers of the virtual workshop according to the physical workshop layers, so that the state, the operation parameters and the positions of the objects in each layer of the physical workshop and the virtual workshop are synchronous.

The virtual sensor is a virtual model artificially abstracted for representing basic properties and characteristics of monitoring data and having a uniform data format. For example, "virtual sensor" = < plant number > < production line number > < device number > < part number > < monitoring variable name > < data type > < data unit > < numerical upper limit > < numerical lower limit > < sampling frequency > < current value > < time stamp >. The workshop number, the production line number, the equipment number and the component number define the workshop level and the distribution position corresponding to the virtual sensor; the monitoring variable name, the data type, the data unit and the sampling frequency define the basic attribute of the monitoring data; the upper and lower numerical limits define the normal range of the monitored numerical value, and alarm is triggered when the range is exceeded; the current value and the timestamp visually reflect the current state of the actual monitored variable.

The virtual sensors have uniform naming specifications and attributes, including unique numbers, corresponding virtual workshop levels (workshop-production line-equipment-component), monitoring variable names, units, upper and lower limits, monitoring threshold values and other data attributes. Meanwhile, batch import of the virtual sensors in the form of Excel is supported. And finally, mapping the data to the corresponding levels of the virtual workshop according to the physical workshop levels, thereby realizing the association and binding of the monitoring object, the monitoring variable and the virtual model.

And based on the data interface adaptation module, the data access and format conversion are realized, the data are mapped into the virtual sensor, and variable values are displayed in real time through a visual chart. Meanwhile, a communication log is established, and detailed data communication information of each data communication, such as connection results of each monitoring data point, data quality and the like, is described. The virtual sensor management submodule manages the configuration information of the virtual sensor, and the configuration information comprises operations of adding, deleting, modifying, checking and the like.

And the production plan simulation and evaluation module is used for previewing the production plan and the process through the virtual workshop and evaluating the performance of the production system under different production plans.

The production plan simulation and evaluation aims to realize the production preparation stage, pre-exercise the production plan and the process, and evaluate the performance of the production system under different production plans, so as to select the optimal production plan, and simultaneously obtain detailed simulation process information (such as logistics scheduling information, buffer information, a workpiece history chart, a simulation execution Gantt chart and the like) to guide the subsequent actual manufacturing execution process.

Specifically, the module comprises:

and the simulation input analysis module is used for converting the production tasks, the process information and the production plans of the physical workshop into a mobile entity set.

The simulation input analysis aims at converting a production task, process information and a production plan into a mobile entity Set F _ Set, a process task Set J _ Set and a current process Set Ocur _ Set. Meanwhile, for convenience of operation, auxiliary functions of importing and analyzing the information in the form of Excel, verifying data validity, managing simulation input and the like are supported.

And the three-dimensional visual simulation module is used for reproducing the production and logistics processes in a three-dimensional visual animation mode according to the production plan and acquiring simulation information.

And decomposing the process into a logistics task and a service task by traversing and dynamically updating the current process Set Ocur _ Set, and distributing the logistics task and the service task to corresponding logistics equipment and service units for execution until all the process tasks are completed. On the other hand, the three-dimensional model of the workpiece is dynamically created under the triggering of the simulation event based on the animation technology of the OSG, and the position and the posture of the logistics equipment are changed to realize the simulation of the logistics process.

And the simulation result counting module is used for collecting and counting the node time of the production activity in the simulation process and calculating the evaluation index.

The module aims to collect and count the starting time and the ending time of activities such as logistics, processing, warehousing and the like in the simulation process, calculate various indexes according to the starting time and the ending time, and display and analyze the indexes from different angles in a visual chart mode. The method mainly comprises the following steps: 1) The workpiece record chart records the moving process of each workpiece from the creation process, the circulation process and the warehousing process from the view angle of the workpiece; 2) Simulating Gantt charts, recording the starting time and the ending time of each machine tool and all the operations thereof from the view angle of the machine tool, and obtaining the maximum completion time; 3) The equipment utilization rate comprises the utilization rates of all processing equipment, logistics equipment and storage equipment so as to identify bottleneck stations and evaluate the balance of the production line; 4) And (3) equipment blocking rate, calculating the time ratio of the workpiece waiting for unloading on the machine tool so as to optimize the number of buffer stations and set reasonable capacity of the buffer stations.

The module aims to process the obtained evaluation indexes by a comprehensive evaluation method based on subjective and objective empowerment to obtain comprehensive scores of the performance of the production system under different production plans so as to quantitatively evaluate the production plans, and the method mainly comprises the following steps: 1) Performing index standardization, namely performing normalization on all indexes according to principles such as 'maximum optimal' and 'minimum optimal' to obtain dimensionless sample parameters; 2) Subjective weighting based on an analytic hierarchy process is carried out to obtain the subjective weight of each index; 3) Obtaining objective weights of all indexes based on objective weighting of an entropy value method and an improved CRITI method; 4) And obtaining a combination weight based on the subjective and objective weights and linear weighting, thereby calculating to obtain a comprehensive score of each production plan. And finally, outputting the data in the form of a simulation report. And forming a simulation example by the virtual workshop, the simulation input, the simulation process information, the simulation output, the simulation report and the like related to the simulation, and storing the simulation example into a simulation example library.

The production process monitoring and adjusting aim to realize the production operation stage, carry out real-time monitoring and disturbance detection on the production process, carry out hypothesis analysis and possible result prediction on the detected disturbance, and make corresponding adjustment based on the analysis result so as to ensure the delivery of the product according to the schedule to the maximum extent.

Specifically, the module comprises:

and the equipment state monitoring module is used for monitoring the equipment state of the physical workshop through the equipment state of the virtual workshop.

The module control aims at monitoring the running state of a physical workshop from the perspective of equipment, and comprises functional items such as equipment real-time state monitoring, running parameter monitoring, virtual and real synchronous monitoring, historical data analysis and the like. The real-time state of the equipment comprises fault, operation, standby and debugging, the different states are marked clearly in the virtual workshop through state balls with different colors, the occurrence time and the ending time of the states are recorded in real time, and the states are stored in a database. The equipment operation parameter monitoring is that real-time visual chart display is carried out on the equipment operation parameters acquired by a sensor and a numerical control system, taking a machine tool as an example, the equipment operation parameter monitoring comprises a plurality of parameters such as main shaft power, main shaft rotating speed, real-time pose of each movement axis and the like, and the parameters are acquired at the frequency of 1 time/second and stored in a database. And the virtual-real synchronous monitoring is to assign the data of each motion axis of the equipment to the corresponding motion axis of the virtual equipment and realize the synchronous motion effect of the virtual equipment through interpolation calculation. The historical data analysis is based on the equipment state, the operation parameters and other data, and is applied to equipment state analysis, OEE analysis, equipment key part fault prediction and residual life prediction, equipment energy consumption analysis and the like.

And the execution process monitoring module is used for monitoring the execution process of the physical workshop through the production and logistics processes of the virtual workshop.

The module control aims at monitoring the running conditions of the physical workshop from the perspective of the production and logistics processes, including virtual-real synchronization of the warehousing process, virtual synchronization of the logistics process and virtual-real synchronization of the service process. The virtual-real synchronization of the warehousing process refers to the visualization and informatization management of the types, the number and the goods grid positions of the workpieces cached by each piece of warehousing equipment, and the time when each workpiece enters and leaves the buffer station is recorded. The virtual and real synchronization of the logistics process refers to sensing and synchronizing the key positions (such as turning points, stopping points and the like) of each logistics device, such as an AGV, a stacker and a robot, and recording the time when the logistics device arrives/leaves each key position. Virtual-real synchronization of the service process refers to the process synchronization visualization display of the workpiece receiving service (e.g., processing, detecting, pre-installing, etc.) in the service unit, and records the time when the workpiece starts/ends the service. The key time and the key event can describe the complete process of caching, serving and circulating the workpiece in a workshop, so that the subsequent applications such as scene reproduction, quality tracing and the like can be performed.

And the production progress monitoring module is used for monitoring the production progress of the physical workshop through the workpiece condition of the virtual workshop.

The production progress monitoring is to monitor the running conditions of the physical workshop from the perspective of the workpieces, including the number of workpieces to be processed, WIP and the number of finished workpieces. The data and the time when each workpiece enters/leaves the workshop can completely depict the completion condition of the workshop task by combining the equipment state data and the execution process data and generate a current execution Gantt chart; by comparing the running process and the production progress of the synchronous simulation (the virtual workshop running at the multiplying power of 1:1), whether the execution process of the physical workshop deviates from the original production plan or not can be judged, wherein the plan is advanced and delayed, and corresponding countermeasure processing is adopted.

Production process tuning aims at detecting production disturbances (e.g., equipment failures, production plan deviations, etc.) and making assumptions analysis and dynamic adjustments based on the three different levels of monitoring described above. The dynamic adjustment process of the production process comprises three main steps of disturbance detection, hypothesis analysis and dynamic adjustment: firstly, whether disturbance exists or not is detected based on virtual-real comparative analysis of three different levels of equipment state, execution process and production progress. Then, the detected disturbance is subjected to hypothesis analysis, namely, the maximum influence of the production disturbance on the production progress under different coping strategies is simulated. For example, for a device failure disturbance, the possible impact on the production plan is assumed in the case of 30 minute repair, 1 hour repair, irreparable, etc. Finally, based on the hypothesis analysis result, a corresponding scheduling policy is selected, such as no scheduling, time-shifting scheduling, rolling window scheduling, and the like.

As shown in fig. 2, the present invention further provides a digital twin modeling and simulation method for a complex equipment manufacturing process, comprising the following steps:

s1, modeling production equipment in a physical workshop for manufacturing complex equipment to generate a production equipment model; the method specifically comprises the following steps:

s11, creating a logic model of production equipment in a workshop and endowing the logic model with corresponding attributes;

s12, creating a motion extension model for the production equipment, so as to realize the operation of the production equipment model;

s13, establishing an appearance structure model for the production equipment, and associating the appearance structure model with the motion topological model;

s14, packaging the logic model with the attribute parameters, the motion topology model, the appearance structure model, the operation logic and the monitoring variables of the production equipment into a production equipment model assembly.

S2, calling a production equipment model to construct a virtual workshop, and carrying out relationship configuration on the production equipment model in the virtual workshop; has the following steps:

s21, creating a virtual workshop, and arranging production equipment model components, workshop facilities and identifiers in the virtual workshop to realize mapping of the physical workshop;

s22, drawing a logistics path and a related logistics equipment model in the virtual workshop to realize mapping of a physical workshop logistics relationship;

s23, defining a virtual service node on the logistics path, and associating the virtual service node with processing or warehousing equipment; and generating the running logic of the virtual service node.

S3, establishing a data channel between the actual physical workshop and the virtual workshop to realize data interaction; the method specifically comprises the following steps:

s31, establishing a data interface abstract class which encapsulates connection, disconnection, data reading and communication log functions, and converting data into a uniform format by using the data interface abstract class;

s32, configuring corresponding virtual sensors according to the types of the data, and arranging the virtual sensors in the corresponding layers of the virtual workshop according to the layers of the physical workshop to realize the synchronization of the states, the operation parameters and the positions of objects in each layer of the physical workshop and the virtual workshop.

S4, previewing the production plan and the production process through the virtual workshop, and evaluating the performance of the production system under different production plans; the method specifically comprises the following steps:

s41, converting the production tasks, the process information and the production plan of the physical workshop into a mobile entity set;

s42, reproducing production and logistics processes in a three-dimensional visual animation mode according to the production plan, and acquiring simulation information;

s43, collecting and counting the node time of the production activity in the simulation process, and calculating an evaluation index;

and S44, processing the obtained evaluation indexes to obtain the comprehensive performance scores of the production system under different production plans.

S5, real-time monitoring and disturbance detection are carried out on the simulation production process, hypothesis analysis and possible result prediction are carried out on the detected disturbance, and corresponding adjustment is carried out on the production process based on the analysis result; the method specifically comprises the following steps:

s51, monitoring the equipment state of the physical workshop through the equipment state of the virtual workshop;

s52, monitoring the execution process of the physical workshop through the production and logistics processes of the virtual workshop;

s53, monitoring the production progress of the physical workshop according to the workpiece condition of the virtual workshop;

and S54, detecting the production disturbance, performing hypothesis analysis and dynamically adjusting based on the detection conditions of the equipment state, the execution process and the production progress.

And S6, reconstructing the virtual workshop based on the updating of the physical workshop and the production process adjusting scheme.

Steps S1-S3 are the construction process of the virtual workshop, step S4 is the simulation and evaluation of the production plan, step S5 is the monitoring and dynamic adjustment of the production process, and step S6 is the reconstruction of the virtual workshop. S1-S3 provide a virtual workshop for subsequent steps, and S4-S6 enable simulation verification before workshop manufacturing execution, process monitoring during execution and system reconfiguration optimization after execution respectively.

The above is only a preferred embodiment of the present invention, and it should be noted that the above preferred embodiment should not be considered as limiting the present invention, and the protection scope of the present invention should be subject to the scope defined by the claims. It will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the spirit and scope of the invention, and should be considered to be within the scope of the invention.

Claims

1. A digital twin modeling and simulation system for a complex equipment manufacturing process is characterized by comprising:

the workshop resource modeling module is used for modeling production equipment in a physical workshop for manufacturing complex equipment to generate a production equipment model; the production equipment comprises processing equipment, logistics equipment, storage equipment and auxiliary equipment;

2. The complex equipment manufacturing process digital twin modeling and simulation system of claim 1 wherein the shop floor resource modeling module comprises:

the resource creating and attribute editing module is used for creating a logic model of production equipment in a workshop and endowing the logic model with corresponding attributes;

3. The digital twin modeling and simulation system for complex equipment manufacturing process of claim 1, wherein the shop relationship configuration module comprises:

the workshop equipment layout module is used for creating a virtual workshop, arranging production equipment model components, workshop facilities and identifiers in the virtual workshop and realizing mapping of a physical workshop;

the workshop logistics layout module is used for drawing a logistics path and associating a logistics equipment model in the virtual workshop to realize mapping of a physical workshop logistics relation;

4. The digital twinning modeling and simulation system for a complex equipment manufacturing process of claim 1, wherein the data interface adaptation and management module comprises:

5. The digital twin modeling and simulation system for complex equipment manufacturing process of claim 1, wherein the production plan simulation and evaluation module comprises:

6. The digital twin modeling and simulation system for a complex equipment manufacturing process of claim 1, the production process monitoring and adjusting module comprising:

7. A digital twin modeling and simulation method for a complex equipment manufacturing process is characterized by comprising the following steps:

modeling production equipment in a physical workshop for manufacturing complex equipment to generate a production equipment model; the production equipment comprises processing equipment, logistics equipment, storage equipment and auxiliary equipment;

establishing a data channel between an actual physical workshop and a virtual workshop to realize data interaction;

previewing a production plan and a production process through a virtual workshop, and evaluating the performance of the production system under different production plans;

8. The digital twinning modeling and simulation method for complex equipment manufacturing process of claim 7, wherein:

and reconstructing the virtual workshop based on the updating of the physical workshop and the production process adjusting scheme.

9. The method of claim 7, wherein the step of modeling the production equipment in the physical plant for manufacturing the complex equipment to generate the production equipment model comprises:

creating a logic model of production equipment in a workshop and endowing the logic model with corresponding attributes;

10. The method of claim 7, wherein the method for calling the production equipment model to construct the virtual plant and configuring the relationship between the production equipment models in the virtual plant comprises:

drawing a logistics path and a related logistics equipment model in the virtual workshop to realize mapping of a physical workshop logistics relationship;

11. The digital twin modeling and simulation method for complex equipment manufacturing process according to claim 7, wherein the method for establishing data channel between the actual physical workshop and the virtual workshop and realizing data interaction comprises:

and configuring corresponding virtual sensors according to the type of the data, and arranging the virtual sensors into corresponding layers of the virtual workshop according to the layers of the physical workshop, so as to realize the synchronization of the states, the operation parameters and the positions of objects at each layer of the physical workshop and the virtual workshop.

12. The digital twin modeling and simulation method for complex equipment manufacturing process of claim 7, wherein the method for forecasting the production plan and process through the virtual workshop and evaluating the performance of the production system under different production plans comprises:

13. The method of claim 7, wherein the method of real-time monitoring and disturbance detection of the simulated production process, hypothesis analysis and possible outcome prediction of the detected disturbance, and corresponding adjustments to the production process based on the analysis results comprises:

monitoring the execution process of a physical workshop through the production and logistics processes of the virtual workshop;

monitoring the production progress of a physical workshop according to the workpiece condition of the virtual workshop;