A production operation management system and method based on digital twin

Abstract

The present application provides a production operation management system and method based on digital twins. The system according to the present application includes: a data acquisition module for collecting basic data in the production operation process; a data processing module for processing basic data; a digital twin model construction module for building a corresponding virtual model based on the processed data; a data analysis and simulation module for performing real-time data analysis and simulation on the virtual model, and transmitting the obtained real-time status and analysis results to the feedback control module and the visualization display module; a feedback control module for generating corresponding optimization suggestions based on the real-time status and analysis results and then feeding them back to the physical production system to complete closed-loop control; a visualization display module for displaying the real-time status and analysis results of the production process. The present application aims to solve the deficiencies of existing production management systems in terms of real-time, intelligence and predictability, so as to achieve comprehensive monitoring, prediction and optimization of the production process.

Description

Technical Field

[0001] The present invention relates to the technical field of production management, and in particular to a production operation management system and method based on digital twins. Background Art

[0002] Enterprises in the park produce a wide variety of products, many of which are non-standard specifications. Enterprise production equipment is prone to failure, inspection and maintenance, spare parts replacement, etc. during operation. It is impossible to grasp the equipment status and operation status in real time, and it is impossible to grasp the equipment production progress and process quality level in time. Therefore, enterprises in the park need to have network access and control system functions for existing equipment or newly purchased equipment to realize the monitoring of equipment operation status, production monitoring and fault prediction. However, the existing production management system still has the following problems:

[0003] 1. Most enterprises are constrained by funds, personnel, technology and concepts, focus on local single applications, lack overall digital planning, mainly focus on process management, have low application integration, and lack production and quality control applications;

[0004] 2. Enterprise production equipment generally does not have the ability to collect and transmit equipment data. Online monitoring of equipment status and operation monitoring based on equipment networking have not yet been carried out. Production plans and documents are transmitted manually. The production process flow, progress tracking, and abnormal feedback are still mainly manual, which cannot meet the needs of on-site refined management and timely management;

[0005] 3. Enterprises lack the integrated mining and dynamic monitoring of data from all links, lack input-output analysis, product quality analysis, visual monitoring of production processes, etc., making it difficult for enterprise managers to grasp the production and operation status in a timely manner. Summary of the invention

[0006] The purpose of the present invention is to provide a production operation management system and method based on digital twins, aiming to solve the above-mentioned problems in the prior art.

[0007] An embodiment of the present invention provides a production operation management system based on digital twins, including:

[0008] A data acquisition module, connected to the data processing module, is used to collect basic data in the production and operation process of the physical production system in real time through Internet of Things devices and several sensors, and transmit the basic data to the data processing module;

[0009] A data processing module, connected to the data acquisition module and the digital twin model construction module, for processing the acquired basic data and transmitting the processed data to the digital twin model construction module;

[0010] A digital twin model construction module, connected to the data processing module and the data analysis and simulation module, for constructing a corresponding virtual model based on the processed data;

[0011] A data analysis and simulation module, connected to the digital twin model construction module, the feedback control module and the visualization display module, for performing real-time data analysis and simulation on the virtual model using big data and machine learning technology, and transmitting the obtained real-time status and analysis results to the feedback control module and the visualization display module;

[0012] A feedback control module, connected to the data analysis and simulation module, for generating corresponding optimization suggestions according to the real-time status and analysis results, and feeding back the real-time status, analysis results and optimization suggestions to the physical production system to complete closed-loop control; and

[0013] The visualization display module is connected to the data analysis and simulation module and is used to display the real-time status and analysis results of the production process through a graphical interface.

[0014] An embodiment of the present invention provides a production operation management method based on digital twins, including:

[0015] The basic data of the production and operation process of the physical production system is collected in real time through the Internet of Things devices and several sensors of the data collection module, and the basic data is transmitted to the data processing module;

[0016] The acquired basic data is processed through the data processing module, and the processed data is transmitted to the digital twin model construction module;

[0017] Build a corresponding virtual model based on the processed data through the digital twin model building module;

[0018] The data analysis and simulation module uses big data and machine learning technology to perform real-time data analysis and simulation on the virtual model, and transmits the obtained real-time status and analysis results to the feedback control module and the visualization display module;

[0019] Generate corresponding optimization suggestions based on real-time status and analysis results through the feedback control module, and feed back the real-time status, analysis results and optimization suggestions to the physical production system to complete closed-loop control; and

[0020] The visual display module uses a graphical interface to display the real-time status and analysis results of the production process.

[0021] An embodiment of the present invention also provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps of the above-mentioned production operation management method based on digital twins when executed by the processor.

[0022] An embodiment of the present invention also provides a computer-readable storage medium, on which a program for implementing information transmission is stored. When the program is executed by a processor, the steps of the above-mentioned production operation management method based on digital twins are implemented.

[0023] The following beneficial effects can be achieved by using the embodiments of the present invention: The production operation management system based on digital twins proposed in the embodiments of the present invention is an advanced solution that uses real-time interaction between virtual models and physical systems to achieve comprehensive monitoring, optimization and management of the production process. Digital twin technology can reflect and predict the status of physical assets, systems or processes in real time by creating virtual copies of them, thereby improving production efficiency, reducing costs and improving product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0025] Figure 1 Schematic diagram of a production operation management system based on digital twins according to an embodiment of the present invention;

[0026] Figure 2 It is a flow chart of the production operation management method based on digital twins in an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the following will be combined with the drawings in one or more embodiments of this specification to clearly and completely describe the technical solutions in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this document.

[0028] System Example

[0029] According to an embodiment of the present invention, a production operation management system based on digital twin is provided. Figure 1 Schematic diagram of a production operation management system based on digital twins according to an embodiment of the present invention. Figure 1 As shown, the production operation management system based on digital twin according to an embodiment of the present invention specifically includes:

[0030] The data acquisition module 10 is connected to the data processing module and is used to collect basic data in the production and operation process of the physical production system in real time through the Internet of Things devices and several sensors, and transmit the basic data to the data processing module;

[0031] The basic data includes equipment production status, production parameters, environmental conditions, quality data, inventory data, procurement data, sales data, work order progress and employee related information;

[0032] The data processing module 11 is connected to the data acquisition module and the digital twin model construction module, and is used to process the acquired basic data and transmit the processed data to the digital twin model construction module, specifically for:

[0033] The basic data is cleaned by a data cleaning unit, the cleaned data is integrated by a data integration unit, and the integrated data is stored by a data storage unit;

[0034] A digital twin model construction module 12, connected to the data processing module and the data analysis and simulation module, for constructing a corresponding virtual model based on the processed data; the digital twin model construction module includes a geometric model construction unit, a physical model construction unit and a behavioral model construction unit that are sequentially communicatively connected;

[0035] The geometric model building unit is used to build a three-dimensional geometric shape of the physical production system based on the spatial structure of the physical production system;

[0036] The physical model building unit is used to simulate the physical characteristics and behavior laws of the physical production system through mathematical equations and physical laws;

[0037] The behavior model building unit is used to simulate the behavior mode and dynamic response of the physical production system under different operating conditions through algorithms and simulation technology;

[0038] The data analysis and simulation module 13 is connected to the digital twin model construction module, the feedback control module and the visualization display module, and is used to perform real-time data analysis and simulation on the virtual model using big data and machine learning technology, and transmit the obtained real-time status and analysis results to the feedback control module and the visualization display module;

[0039] The feedback control module 14 is connected to the data analysis and simulation module, and is used to generate corresponding optimization suggestions according to the real-time status and analysis results, and feed back the real-time status, analysis results and optimization suggestions to the physical production system to complete closed-loop control, specifically for:

[0040] Generate corresponding optimization suggestions through the optimization suggestion generation unit according to the real-time status and analysis results, and use the control instruction generation unit to perform production management, quality management, inventory management, procurement management, sales management, equipment and tooling management, financial report summary, business dimension report summary, production progress management and employee management on the physical production system based on the real-time status, analysis results and optimization suggestions;

[0041] The visualization display module 15 is connected to the data analysis and simulation module and is used to display the real-time status and analysis results of the production process through a graphical interface, specifically for:

[0042] Generate a corresponding visualization interface through a graphical interface generation unit according to the real-time status and analysis results, and convert the visualization interface into a visualization production dashboard through a status display unit;

[0043] Wherein, the visual interface displays the key indicators and status of the production process;

[0044] The style of the visual production dashboard is formulated according to user needs.

[0045] The above technical solution of the embodiment of the present invention is described in detail below in combination with the specific situation of the production operation management system based on digital twin in the embodiment of the present invention.

[0046] The system proposed in the embodiment of the present invention can be applied to the production management of various types of manufacturing plants. Through the Internet of Things (IoT) devices in the data acquisition module and the various sensors deployed on the production line, data such as equipment status, production parameters and environmental conditions are collected in real time. The data processing module cleans and integrates these data, and then transmits them to the digital twin model construction module to build a virtual model corresponding to the actual production process. The data analysis and simulation module uses big data and machine learning technology to perform real-time data analysis and simulation on the virtual model to predict possible problems in the production process. The feedback control module proposes an optimization plan based on the analysis results, and feeds back the optimization suggestions to the actual production process to achieve closed-loop control. Finally, the visualization display module displays the real-time status and analysis results of the production process through a graphical interface, which is convenient for operators to monitor and manage.

[0047] Among them, each unit in the digital twin model building module is responsible for different modeling tasks, as follows:

[0048] 1. Geometric model building unit: It is mainly used to build the three-dimensional geometric shape of the physical production system. It represents the spatial structure of the physical production system through precise size and shape, and is the basis of the digital twin model.

[0049] 2. Physical model building unit: mainly used to describe the physical characteristics and behavior laws of the physical production system. It simulates the dynamics, thermodynamics, electromagnetism and other characteristics of the physical production system through mathematical equations and physical laws.

[0050] 3. Behavior model building unit: mainly used to describe the behavior pattern and dynamic response of the physical production system. It simulates the behavior changes of the physical production system under different operating conditions through algorithms and simulation technology.

[0051] The above three units work together to build a complete digital twin model. The geometric model provides the static structure of the physical production system, the physical model describes the dynamic characteristics of the physical production system, and the behavioral model simulates the behavior of the physical production system in actual operation. Through the comprehensive application of these models, comprehensive monitoring, prediction and optimization of the physical production system can be achieved.

[0052] Specifically, the main components of the production operation management system based on digital twins proposed in the embodiment of the present invention include:

[0053] 1. Data collection and perception:

[0054] (1) Sensors and Internet of Things (IoT) devices: Various sensors (such as temperature, pressure, and vibration sensors) installed on production equipment collect production data in real time.

[0055] (2) Data acquisition system: Sensor data is collected and transmitted to the central server through the IoT platform.

[0056] 2. Data processing and storage:

[0057] (1) Edge computing: Perform preliminary processing close to the data source to reduce the burden on the central server.

[0058] (2) Cloud computing: The processed data is transferred to the cloud for further analysis and storage.

[0059] (3) Database: used to store and manage large amounts of production data and support fast query and analysis.

[0060] 3. Digital Twin Model:

[0061] (1) Virtual Model: Create a high-precision virtual model based on the geometry, material properties, and working principles of the physical device.

[0062] (2) Simulation engine: Use simulation software (such as ANSYS, MATLAB, etc.) to dynamically simulate the virtual model and predict the operating status and performance of the equipment.

[0063] 4. Data analysis and optimization:

[0064] (1) Machine Learning and Artificial Intelligence: Apply machine learning algorithms (such as deep learning and reinforcement learning) to analyze production data and discover hidden patterns and trends.

[0065] (2) Predictive maintenance: By analyzing the operating data of the equipment, the probability of failure is predicted, maintenance is performed in advance, and downtime is reduced.

[0066] (3) Process optimization: Use optimization algorithms (such as genetic algorithms and particle swarm optimization) to improve production processes, improve production efficiency and product quality.

[0067] 5. Visualization and decision support:

[0068] (1) Real-time monitoring: The key indicators and status of the production process are displayed in real time through the dashboard and visual interface.

[0069] (2) Alarm and notification: When an abnormal situation is detected, the system automatically sounds an alarm and notifies relevant personnel.

[0070] (3) Decision support: Provide data-based decision support to help management formulate optimization strategies and improvement measures.

[0071] Since enterprises need a complete production process control system to comprehensively control the entire process of product production and manufacturing, the main functional requirements of the embodiments of the present invention include the following aspects:

[0072] Production management: helps enterprises formulate production plans and manage production processes, including production management, production progress tracking, production anomalies (equipment failure, material shortage, etc.), and monitor and adjust plans. The production module can be combined with the supply chain management module to ensure the timely supply of raw materials and parts.

[0073] Quality management: helps enterprises control the quality of the production process and provide qualified rates. This includes raw material and finished product quality management, finished product sampling management, quality report generation, defect handling, etc., which facilitates quality management personnel to control the quality of key process links such as material warehousing, process planning, and product warehousing.

[0074] Inventory management: helps enterprises manage inventory, including the management of raw materials, semi-finished products and finished products. The inventory management module can be combined with the production management module and the sales management module to ensure the accuracy of inventory quantity and quality.

[0075] Procurement Management: Helps companies manage the procurement process, including creation of purchase orders, supplier selection, warehousing of purchased raw materials, receipt of invoices, payment, etc.

[0076] Sales Management: Helps companies manage sales processes, including sales order creation, price management, invoicing, delivery, collection, customer management, etc.

[0077] Equipment and tooling management: Help enterprises to classify tooling equipment, manage tooling, and manage equipment maintenance.

[0078] Financial statements: follow the corporate accounting standards to help companies calculate production costs and sales costs, including raw materials, labor, energy and other costs.

[0079] Statistical reports: help enterprises generate various business dimension reports, such as production reports, inventory reports, financial reports, etc., so that management can better understand the operating status and trends of the enterprise.

[0080] On-site terminal: Set up in the factory / workshop to help on-site production and quality management personnel better understand the progress of work orders, task presentation, abnormal information reporting, start and report execution, shift handover, etc. Workers scan work orders and employee barcodes / cards to work, associate people, machines, materials, etc., and record employees' processing time information.

[0081] Production dashboard: collects manufacturing information from work order module, on-site execution module, quality module, equipment automation interface and other sources, and converts it into dashboards such as equipment OEE, work order, work in progress, and production line operation status, which are displayed in the office and production site to achieve visualization and transparency of workshop operation. The dashboard can be customized according to user needs.

[0082] That is, the embodiment of the present invention aims to build a digital twin system of a park and a demonstration enterprise, aggregate the production and operation data of the park and the enterprise, realize the full-factor simulation of the production and manufacturing process within the park, intuitively understand the actual situation of the enterprise's business operations, realize the intensive management of enterprise facilities, precise industrial services, and intelligent display, and form a "managing enterprises with maps" model.

[0083] The function list of the digital twin system is shown in Table 1:

[0084] Table 1 Function list of digital twin system

[0085]

[0086]

[0087]

[0088] Method Embodiment

[0089] According to an embodiment of the present invention, a production operation management method based on digital twin is provided. Figure 2 is a flow chart of a production operation management method based on digital twins according to an embodiment of the present invention. Figure 2 As shown, the production operation management method based on digital twin according to an embodiment of the present invention specifically includes:

[0090] Step S201, collecting basic data in the production and operation process of the physical production system in real time through the Internet of Things devices and several sensors of the data collection module, and transmitting the basic data to the data processing module;

[0091] The basic data includes equipment production status, production parameters, environmental conditions, quality data, inventory data, procurement data, sales data, work order progress and employee related information;

[0092] Step S202, processing the acquired basic data through the data processing module, and transmitting the processed data to the digital twin model construction module;

[0093] Step S203, constructing a corresponding virtual model based on the processed data through a digital twin model construction module;

[0094] Step S204, using big data and machine learning technology to perform real-time data analysis and simulation on the virtual model through the data analysis and simulation module, and transmitting the obtained real-time status and analysis results to the feedback control module and the visualization display module;

[0095] Step S205, generating corresponding optimization suggestions according to the real-time status and analysis results through the feedback control module, and feeding back the real-time status, analysis results and optimization suggestions to the physical production system to complete closed-loop control; and

[0096] Step S206: Display the real-time status and analysis results of the production process using a graphical interface through a visualization module.

[0097] The embodiment of the present invention is a method embodiment corresponding to the above-mentioned system embodiment. The specific implementation of each step can be understood by referring to the description of the system embodiment, which will not be repeated here.

[0098] The production operation management system based on digital twin proposed in the embodiment of the present invention realizes the intelligent, efficient and sustainable production process through the deep integration of virtual and reality, bringing significant economic benefits and competitive advantages to enterprises, including the following beneficial effects:

[0099] 1. Improve production efficiency: monitor and optimize the production process in real time, reduce waste and downtime, and improve production efficiency.

[0100] 2. Reduce operating costs: Reduce equipment failures and maintenance costs, and reduce energy consumption through predictive maintenance and process optimization.

[0101] 3. Improve product quality: Real-time monitoring of key parameters in the production process to ensure that product quality meets standards.

[0102] 4. Enhanced decision support: Provide data-based decision support to help management formulate scientific and reasonable production plans and improvement measures.

[0103] 5. Improve safety: Through real-time monitoring and early warning mechanisms, potential safety hazards can be discovered and dealt with in a timely manner to ensure production safety.

[0104] 6. Flexible scalability: The digital twin system can be flexibly expanded according to the actual needs of the enterprise and adapt to production environments of different sizes and types.

[0105] 7. Improve customer satisfaction: Improve product delivery speed and quality by real-time monitoring and optimization of the production process.

[0106] Device Example 1

[0107] An embodiment of the present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps described in the method embodiment when executed by the processor.

[0108] Device Example 2

[0109] An embodiment of the present invention provides a computer-readable storage medium, on which a program for implementing information transmission is stored. When the program is executed by a processor, the steps described in the method embodiment are implemented.

[0110] The computer-readable storage medium in this embodiment includes, but is not limited to, ROM, RAM, magnetic disk or optical disk, etc.

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A production operation management system based on digital twin, characterized by include: A data acquisition module, connected to the data processing module, is used to collect basic data in the production and operation process of the physical production system in real time through Internet of Things devices and several sensors, and transmit the basic data to the data processing module; A data processing module, connected to the data acquisition module and the digital twin model construction module, for processing the acquired basic data and transmitting the processed data to the digital twin model construction module; A digital twin model construction module, connected to the data processing module and the data analysis and simulation module, for constructing a corresponding virtual model based on the processed data; A data analysis and simulation module, connected to the digital twin model construction module, the feedback control module and the visualization display module, for performing real-time data analysis and simulation on the virtual model using big data and machine learning technology, and transmitting the obtained real-time status and analysis results to the feedback control module and the visualization display module; A feedback control module is connected to the data analysis and simulation module, and is used to generate corresponding optimization suggestions according to the real-time status and analysis results, and feed back the real-time status, analysis results and optimization suggestions to the physical production system to complete closed-loop control; as well as The visualization display module is connected to the data analysis and simulation module and is used to display the real-time status and analysis results of the production process through a graphical interface.

2. The system according to claim 1, characterized in that The basic data includes equipment production status, production parameters, environmental conditions, quality data, inventory data, procurement data, sales data, work order progress and employee-related information.

3. The system according to claim 1, characterized in that The data processing module is specifically used for: The basic data is cleaned by a data cleaning unit, the cleaned data is integrated by a data integration unit, and the integrated data is stored by a data storage unit.

4. The system according to claim 1, characterized in that The digital twin model construction module includes a geometric model construction unit, a physical model construction unit and a behavioral model construction unit which are sequentially communicatively connected; The geometric model building unit is used to build a three-dimensional geometric shape of the physical production system based on the spatial structure of the physical production system; The physical model building unit is used to simulate the physical characteristics and behavior laws of the physical production system through mathematical equations and physical laws; The behavior model building unit is used to simulate the behavior mode and dynamic response of the physical production system under different operating conditions through algorithms and simulation technology.

5. The system according to claim 1, characterized in that The feedback control module is specifically used for: According to the real-time status and analysis results, the optimization suggestion generation unit generates corresponding optimization suggestions. Based on the real-time status, analysis results and optimization suggestions, the control instruction generation unit is used to perform production management, quality management, inventory management, procurement management, sales management, equipment and tooling management, financial report summary, business dimension report summary, production progress management and employee management on the physical production system.

6. The system according to claim 1, characterized in that The visual display module is specifically used for: Generate a corresponding visualization interface through a graphical interface generation unit according to the real-time status and analysis results, and convert the visualization interface into a visualization production dashboard through a status display unit; Wherein, the visual interface displays the key indicators and status of the production process; The style of the visual production dashboard is formulated according to user needs.

7. A production operation management method based on digital twins, characterized in that include: The basic data of the production and operation process of the physical production system is collected in real time through the Internet of Things devices and several sensors of the data collection module, and the basic data is transmitted to the data processing module; The acquired basic data is processed through the data processing module, and the processed data is transmitted to the digital twin model construction module; Build a corresponding virtual model based on the processed data through the digital twin model building module; The data analysis and simulation module uses big data and machine learning technology to perform real-time data analysis and simulation on the virtual model, and transmits the obtained real-time status and analysis results to the feedback control module and the visualization display module; The feedback control module generates corresponding optimization suggestions based on the real-time status and analysis results, and feeds back the real-time status, analysis results and optimization suggestions to the physical production system to complete closed-loop control; as well as The visual display module uses a graphical interface to display the real-time status and analysis results of the production process.

8. The method according to claim 7, characterized in that The basic data includes equipment production status, production parameters, environmental conditions, quality data, inventory data, procurement data, sales data, work order progress and employee-related information.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the production operation management method based on digital twins as described in any one of claims 7 to 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores an implementation program for information transmission, and when the program is executed by the processor, the steps of the production operation management method based on digital twins as described in any one of claims 7 to 8 are implemented.

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