A production line design simulation system and simulation method using digital twinning technology
By combining digital twin technology with logistics simulation and throughput simulation, the problem of separate and independent simulation in existing technologies has been solved, realizing efficient, fast and flexible production line design simulation. The simulation results are highly realistic and the learning cost has been reduced.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- E-QUALITY INFORMATION TECH (SHANGHAI) CO LTD
- Filing Date
- 2024-12-31
- Publication Date
- 2026-05-29
AI Technical Summary
In existing technologies, logistics simulation and production line throughput simulation are separate and independent, which cannot realistically simulate physical limitations. Simulation verification is slow and costly, difficult to learn, and has limited effectiveness.
By employing digital twin technology, combining industrial modeling, logistics simulation, and digital twin units, logistics simulation and throughput simulation are integrated through digital twin units. Collaborative simulation is then performed using a digital twin platform to generate simulation animations of a realistic environment.
It enables efficient, rapid, and flexible simulation verification of production line design, with simulation results that closely approximate reality, reducing learning costs and improving simulation efficiency and effectiveness.
Smart Images
Figure CN119918259B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of production line design, and in particular to a production line design simulation system and method utilizing digital twin technology. Background Technology
[0002] In automotive product development, it is necessary to design and simulate the production line and production capacity. The most common methods are logistics simulation and passability simulation testing to ensure that the designed production line can meet design requirements, produce the designed vehicle model, and achieve the target production capacity. The general steps include:
[0003] Production line throughput and logistics both require simulation; therefore, accurate modeling is necessary in specialized software during the design phase. After model creation, programming is needed to handle various operating conditions and outcomes, implementing specific simulation logic based on the model. Then, relevant simulation parameters are entered according to the production line design requirements. Finally, production line throughput and logistics simulations are performed separately, typically requiring multiple simulations for each. Finally, the production line throughput and logistics simulations are combined to determine if the production line design meets standards. If the simulation results are not achieved, the cause needs to be identified, parameters adjusted, and the simulation repeated.
[0004] The main drawback of the above method is:
[0005] 1. Logistics simulation is designed and simulated only under general conditions. Due to the limitations of the software platform, logistics simulation and production line throughput simulation are conducted separately and independently. Therefore, it is impossible to simulate some physical limitations in the real environment, such as traffic congestion.
[0006] 2. Production line design simulation mainly involves model simulation and rarely includes logical functions such as animation and collision detection. At the same time, the verification process is quite slow due to performance reasons, making it impossible to perform flexible, fast, and large-scale simulation verification.
[0007] 3. The overall simulation effect is rather monotonous, and its effect on corporate publicity is not ideal. We hope to have a simulation process that is closer to the real effect.
[0008] 4. The relevant simulation and animation production software is relatively professional, and the learning cost is high. Summary of the Invention
[0009] The purpose of this invention is to provide a production line design simulation system and simulation method using digital twin technology, which mainly solves the problems existing in the prior art.
[0010] To achieve the above objectives, the technical solution adopted by the present invention is to provide a production line design simulation system using digital twin technology, characterized in that it includes an industrial modeling unit, a logistics simulation unit, and a digital twin unit.
[0011] The industrial modeling unit establishes a logistics model and a throughput model based on the production line design input, and then sends the logistics model to the logistics simulation unit and the throughput model to the digital twin unit.
[0012] The logistics simulation unit calculates logistics process data based on the initial logistics parameters and the logistics model, and sends the logistics process data to the digital twin unit.
[0013] The digital twin unit establishes a simulated production line based on the throughput model, then receives the logistics process data and displays the logistics status on the simulated production line in the form of a simulation animation; the designer generates new logistics parameters based on the logistics status and delivers them to the logistics simulation unit for a new round of iteration until the logistics status meets the design requirements.
[0014] Furthermore, the industrial modeling unit includes a logistics modeling module and a throughput modeling module;
[0015] The logistics modeling module generates the logistics model based on the production line design input, which includes logistics scheduling information in the production line; the throughput modeling module generates the throughput model based on the production line design input, which includes the motion information of various equipment and materials on the production line.
[0016] Furthermore, the logistics simulation unit includes a model import module, a parameter input module, and a process simulation module;
[0017] The model import module initializes the process simulation module based on the logistics model, so that subsequent simulations are all based on the input logistics model; the parameter input module reads the logistics parameters and configures them into the process simulation module; the process simulation module calculates the logistics process data based on the logistics model and the logistics parameters.
[0018] Furthermore, the digital twin unit includes a layout generation module, a simulation conversion module, a data driving module, and an animation output module;
[0019] The layout generation module reads the passability model and generates simulation equipment on the digital twin production line based on the passability model; the simulation conversion module reads the logistics process data, processes the data based on the logistics process data, generates motion data for driving the simulation equipment, and sends it to the data driving module; the data driving module generates animation data corresponding to each simulation equipment based on the motion data; the animation output module generates and displays the simulation animation reflecting the real-time status of each simulation equipment based on the animation data.
[0020] Furthermore, the digital twin unit also includes a statistical output module; the statistical output module extracts and saves the video from the simulation animation for later retrieval.
[0021] Furthermore, the simulation equipment includes a simulated conveyor belt and a simulated robot.
[0022] Furthermore, the data processing in the simulation conversion module includes data interpolation.
[0023] This invention also discloses a simulation method using the above-mentioned production line design simulation system utilizing digital twin technology, characterized by comprising the following steps:
[0024] Step S10: Based on the production line design input, establish the logistics model and the throughput model using the industrial modeling unit;
[0025] Step S11: Import the passability model into the digital twin unit;
[0026] Step S12: Import the logistics model into the logistics simulation unit;
[0027] Step S13: Use the logistics simulation unit to read logistics parameters and generate the logistics process data based on the logistics model;
[0028] Step S14: Import the logistics process data into the digital twin unit;
[0029] Step S15: The digital twin unit combines the throughput model and the logistics process data to generate and display a simulation animation;
[0030] Step S16: The designer obtains the logistics status based on the simulation animation;
[0031] Step S17: The designer evaluates whether the logistics status meets the standard; if it meets the standard, proceed to step S18; otherwise, after adjusting the logistics parameters, jump to step S13.
[0032] Step S18: Complete the production line design based on the logistics model, the throughput model, and the logistics parameters.
[0033] Furthermore, step S15 includes sub-steps.
[0034] Step S151: The simulation conversion module in the digital twin unit reads the logistics process data and converts it into animation input parameters;
[0035] Step S152: The simulation conversion module performs data interpolation based on the animation input parameters to supplement the information required by the simulation device and generate motion data for each corresponding simulation device.
[0036] Step S153: The data-driven module in the digital twin unit reads the motion data and generates animation data for each simulation device;
[0037] Step S154: The animation output module in the digital twin unit generates and displays the simulation animation based on the animation data.
[0038] Furthermore, it also includes a method for production line design based on historical simulation data, comprising the following steps:
[0039] Step S20: Using the statistical output module in the digital twin unit, read the video saved from each simulation animation.
[0040] Step S21: Extract the corresponding logistics status from the video;
[0041] Step S22: Perform statistical analysis on the logistics status and select the optimal logistics parameters.
[0042] Step S23: Complete the production line design based on the logistics model, the throughput model, and the logistics parameters.
[0043] In view of the above technical features, this invention utilizes a production line design simulation system and method based on digital twin technology. With the aid of a digital twin platform system, and through a refined model, it combines process data generated from logistics simulation with digital twin production line drive data to examine whether vehicles interfere with or collide with the production line during the production process. Simultaneously, based on the logistics simulation data, it guides logistics equipment within the workshop to execute the logistics process according to simulation parameters, thereby verifying logistics efficiency and ensuring that it does not interfere with or collide with other equipment. Compared to existing technologies, this invention has the following advantages:
[0044] 1. This invention combines production line throughput simulation and logistics simulation through digital twin units to collaboratively complete the simulation process. In this way, during the simulation, both can use real data as parameters for comprehensive verification.
[0045] 2. The physical engine of the digital twin unit in this invention more realistically restores the process on site. Since the scene is consistent with the simulation data, the simulation results are very close to the final real production line and have certain reference value.
[0046] 3. The digital twin unit in this invention has exquisite graphics. The optimized model not only ensures accurate and detailed reproduction, but also reduces performance overhead and improves simulation efficiency. Attached Figure Description
[0047] Figure 1 This is a system block diagram of a preferred embodiment of the production line design simulation system utilizing digital twin technology of the present invention;
[0048] Figure 2 This is a schematic diagram of information transmission in a preferred embodiment of the production line design simulation system utilizing digital twin technology of the present invention.
[0049] Figure 3 This is a flowchart of a preferred embodiment of the simulation method of the production line design simulation system utilizing digital twin technology of the present invention.
[0050] Figure 4 This is a flowchart illustrating a preferred embodiment of the simulation method of the production line design simulation system utilizing digital twin technology of the present invention, which uses historical simulation data for production line design.
[0051] In the diagram: 100 - Industrial modeling unit, 200 - Logistics simulation unit, 300 - Digital twin unit;
[0052] 101 - Logistics Modeling Module, 102 - Passability Modeling Module;
[0053] 201-Model Import Module, 202-Parameter Input Module, 203-Process Simulation Module;
[0054] 301 - Layout generation module, 302 - Simulation conversion module, 303 - Data-driven module, 304 - Animation output module, 305 - Statistical output module. Detailed Implementation
[0055] The present invention will be further described below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims.
[0056] Please see Figure 1 and Figure 2 This invention discloses a production line design simulation system utilizing digital twin technology. As shown in the figure, a preferred embodiment of the system comprises an industrial modeling unit 100, a logistics simulation unit 200, and a digital twin unit 300.
[0057] In production line design, the industrial modeling unit 100 is used to establish a logistics model and a throughput model based on the production line design input. The logistics model describes the flow of various materials in the production line and includes all logistics scheduling information. The throughput model mainly describes the characteristics of the production line, such as the setting of workstations, the layout of the site, and the motion information of each piece of equipment and material. Using the throughput model and the logistics model, designers can check for logistics conflicts in the production line, or optimize the production line layout or logistics planning. The logistics model is sent as input to the logistics simulation unit 200. Based on the logistics model, the logistics simulation unit 200 calculates the logistics process data according to the initial logistics parameters. The throughput model is sent as input to the digital twin unit 300. Based on the throughput model, the digital twin unit 300 establishes a simulated production line, and then, combined with the logistics process data, can simulate the logistics state on the simulated production line, generally displayed to the designers in animation form. Designers can adjust the parameters input to the logistics simulation unit 200 according to the logistics state, thus entering the next iteration, until the logistics state on the simulated production line finally meets the design requirements.
[0058] The industrial modeling unit 100 includes a logistics modeling module 101 and a throughput modeling module 102, which are used to build logistics models and throughput models, respectively. The industrial modeling unit 100 is primarily used for accurate model construction, with its accuracy mainly reflected in its ability to accurately reflect the contours and functional details of objects. In particular, for infrastructure such as building layouts, walls, and roads, the simulation software ensures a high degree of consistency with reality. In the scenario, the external dimensions of the equipment are consistent with the real equipment, even down to the details of each individual part. The input to the logistics modeling module 101 is the production line design input provided by the designer, and its output is the logistics model. The input to the throughput modeling module 102 is also the production line design input provided by the designer, and its output is the throughput model.
[0059] The logistics simulation unit 200 includes a model import module 201, a parameter input module 202, and a process simulation module 203. The logistics simulation unit 200 can import industrial simulation software scenarios or models, and can also construct its own models using simple geometric shapes to represent equipment or production lines. Its core function is to achieve parametric simulation of the constructed scenario through rapid configuration and programming, thereby reproducing the production or logistics process and statistically analyzing relevant data. Subsequently, statistical methods are used to analyze the simulation results to draw scientific conclusions. In the logistics simulation unit 200, the input logistics model determines the specific simulation process, while the logistics parameters, while remaining constant, influence the specific calculations. The model import module 201 is responsible for reading the logistics model and initializing the simulation process in the process simulation module 203 based on it; all subsequent simulations are based on the read logistics model. Before each logistics simulation, model import only needs to be performed once; subsequent adjustments only require adjusting the logistics parameters. Similarly, the parameter input module 202 is responsible for reading logistics parameters and configuring them into the process simulation module 203. It is used to adjust various input parameters of the process simulation module 203 during simulation calculations. In a single production line design simulation, the logistics parameters will be adjusted multiple times. Therefore, the parameter input module 202 needs to read the latest logistics parameters each time and configure them into the process simulation module 203 to guide each simulation calculation. The process simulation module 203 is the module that actually performs the simulation calculations. Based on the simulation process specified by the logistics model and the parameters specified by the logistics parameters, it calculates the logistics process data based on the current logistics model and logistics parameters, and outputs the logistics process data to the digital twin unit.
[0060] The digital twin unit 300 includes a layout generation module 301, a simulation conversion module 302, a data-driven module 303, an animation output module 304, and a statistical output module 305. The digital twin unit 300 provides a standardized set of operating functions, its displayed content is consistent with the real-world environment, and it provides data management, model management, and other functions, enabling it to drive the animation display platform using real-world data provided on-site. The layout generation module 301 is responsible for reading the passability model as input and then initializing the digital twin production line based on the passability model, such as generating simulation equipment on the digital twin production line, setting the layout of the simulation equipment, and defining the behavior of the simulation equipment. The simulation equipment includes simulation conveyor belts and simulation robots. In a simulation of a production line design, the initialization of the digital twin production line only needs to be performed once. Subsequent work involves displaying the working status of the digital twin production line to the designers, driven by logistics process data.
[0061] The simulation conversion module 302 is responsible for reading logistics process data, processing it to generate status data for the digital twin production line—specifically, generating motion data to drive each simulated device on the digital twin production line—and then sending it to the data driving module 303. During data processing, the simulation conversion module 302 also performs data interpolation to bridge the gap between the rate of change in the logistics process data and the refresh rate of the digital twin production line. In a single simulation of the production line design, the simulation conversion module 302 reads the logistics process data multiple times, continuously outputting motion data to drive the continuous updating of the digital twin production line's status.
[0062] The data-driven module 303 generates animation data for each simulation device on the digital twin production line based on the motion data provided by the simulation conversion module 302, and delivers this data to the animation output module 303. The animation output module 303 then generates and displays simulation animations based on the animation data. These simulation animations reflect the real-time status of each simulation device on the digital twin production line.
[0063] The statistical output module 304 is connected to the animation output module 303, which saves the simulation animation in the form of video or images. This allows for later retrieval of each simulation, facilitating comparison of differences in design inputs for different production lines. It also makes it easier to introduce new tools for further analysis of simulation results, such as using statistical methods or combining artificial intelligence to process each simulation and obtain the optimal result, rather than being limited to manual optimization by designers in a single simulation.
[0064] Please see Figure 3 The present invention also discloses a simulation method using a production line design simulation system utilizing digital twin technology. A preferred embodiment includes the following steps:
[0065] Step S100: Establish the model.
[0066] Designers generate production line design inputs based on requirements. Then, using industrial modeling modules, they build logistics and throughput models based on the production line design inputs.
[0067] Step S101: Initialize the digital twin unit.
[0068] The passability model is imported into the digital twin unit, which then uses the passability model to complete its initialization.
[0069] Step S102: Initialize the logistics simulation unit.
[0070] The logistics model is imported into the logistics simulation unit, which then uses the model to complete the initialization.
[0071] Step S103: The logistics simulation unit generates logistics process data.
[0072] The logistics simulation unit reads logistics parameters and generates logistics process data based on the logistics model.
[0073] Step S104: The digital twin unit reads logistics process data.
[0074] Import logistics process data into the digital twin unit.
[0075] Step S105: Generate animation input parameters.
[0076] The simulation conversion module in the digital twin unit reads logistics process data and converts it into animation input parameters.
[0077] Step S106: Generate motion data.
[0078] The simulation conversion module performs data interpolation based on the animation input parameters, supplements the information required by the simulation equipment, and generates motion data for each corresponding simulation equipment.
[0079] Step S107: Generate animation data.
[0080] The data-driven module in the digital twin unit reads motion data and generates animation data for each simulation device.
[0081] Step S108: Display the simulation animation.
[0082] The animation output module in the digital twin unit generates and displays simulation animations for each simulation device based on the animation data.
[0083] Step S109: Obtain the logistics status.
[0084] Based on the simulation animation, the designers obtained the logistics status of the digital twin production line under the current configuration.
[0085] Step S110: Assess the logistics status.
[0086] Designers assess whether the logistics status meets the standards; if it does, proceed to step S111; otherwise, manually adjust the logistics parameters and jump to step S103 to re-simulate.
[0087] Step S111: Complete the production line design.
[0088] Read the current logistics model, throughput model, and logistics parameters to determine the parameters for the current production line design, thereby completing the production line design.
[0089] Please see Figure 4In this invention, after completing multiple simulations using the above steps, production line design can also be performed based on historical simulation data using statistical algorithms. This includes the following steps:
[0090] Step S200: Read the simulation animations from previous simulations.
[0091] The statistical output module in the digital twin unit is used to read the video saved from previous simulation animations.
[0092] Step S201: Extract the flow status.
[0093] Using software tools, we can extract the corresponding logistics status from these videos.
[0094] Step S202: Optimize logistics parameters.
[0095] Each simulation includes multiple sets of logistics states. Multiple simulations result in even more logistics states. Statistical tools or artificial intelligence are used to analyze all logistics states and select the optimal logistics parameters.
[0096] Step S203: Determine the production line design.
[0097] Based on the selected optimal logistics parameters, record the corresponding logistics model and throughput model, and then combine them with the logistics parameters to finalize the production line design.
[0098] Utilizing statistical output modules to optimize parameters across multiple simulations yields more generalizable results than parameters obtained from a single simulation. When multiple production line designs share similar requirements, this method can generate a more reasonable production line design solution faster than a single simulation. However, if a new production line design involves new factors, the results of a single simulation are more reliable.
[0099] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.
Claims
1. A production line design simulation system utilizing digital twin technology, characterized in that, It includes industrial modeling units, logistics simulation units, and digital twin units; The industrial modeling unit establishes a logistics model and a throughput model based on the production line design input, and then sends the logistics model to the logistics simulation unit and the throughput model to the digital twin unit. The logistics simulation unit calculates logistics process data based on the initial logistics parameters and the logistics model, and sends the logistics process data to the digital twin unit. The digital twin unit establishes a simulated production line based on the passability model, and then receives the logistics process data to display the logistics status on the simulated production line in the form of a simulation animation. Based on the logistics status, the designers generate new logistics parameters and deliver them to the logistics simulation unit for a new round of iteration until the logistics status meets the design requirements. The industrial modeling unit includes a logistics modeling module and a throughput modeling module; The logistics modeling module generates the logistics model based on the production line design input, which includes logistics scheduling information in the production line. The throughput modeling module generates the throughput model based on the production line design input, which includes the motion information of various equipment and materials on the production line; The logistics simulation unit includes a model import module, a parameter input module, and a process simulation module; The model import module initializes the process simulation module based on the logistics model, so that all subsequent simulations are based on the input logistics model. The parameter input module reads the logistics parameters and configures them into the process simulation module; The process simulation module calculates the logistics process data based on the logistics model and the logistics parameters. The digital twin unit includes a layout generation module, a simulation conversion module, a data driving module, and an animation output module; The layout generation module reads the passability model and generates simulation equipment on the digital twin production line based on the passability model; the simulation conversion module reads the logistics process data, processes the data based on the logistics process data, generates action data for driving the simulation equipment, and sends it to the data driving module. The data-driven module generates animation data corresponding to each of the simulation devices based on the motion data; The animation output module generates and displays the simulation animation based on the animation data, which reflects the real-time status of each simulation device.
2. The production line design simulation system utilizing digital twin technology as described in claim 1, characterized in that, The digital twin unit also includes a statistical output module; the statistical output module extracts and saves the video from the simulation animation for later retrieval.
3. The production line design simulation system utilizing digital twin technology as described in claim 1 or 2, characterized in that, The simulation equipment includes a simulated conveyor belt and a simulated robot.
4. The production line design simulation system utilizing digital twin technology as described in claim 1 or 2, characterized in that, The data processing in the simulation conversion module includes data interpolation.
5. A simulation method using the production line design simulation system based on digital twin technology as described in claim 1, characterized in that, Includes the following steps: Step S10: Based on the production line design input, establish the logistics model and the throughput model using the industrial modeling unit; Step S11: Import the passability model into the digital twin unit; Step S12: Import the logistics model into the logistics simulation unit; Step S13: Use the logistics simulation unit to read logistics parameters and generate the logistics process data based on the logistics model; Step S14: Import the logistics process data into the digital twin unit; Step S15: The digital twin unit combines the throughput model and the logistics process data to generate and display a simulation animation; Step S16: The designer obtains the logistics status based on the simulation animation; Step S17: The designer evaluates whether the logistics status meets the standard; if it meets the standard, proceed to step S18; otherwise, after adjusting the logistics parameters, jump to step S13. Step S18: Complete the production line design based on the logistics model, the throughput model, and the logistics parameters.
6. The simulation method using a production line design simulation system based on digital twin technology as described in claim 5, characterized in that, Step S15 includes sub-steps. Step S151: The simulation conversion module in the digital twin unit reads the logistics process data and converts it into animation input parameters; Step S152: The simulation conversion module performs data interpolation based on the animation input parameters to supplement the information required by the simulation device and generate motion data for each corresponding simulation device. Step S153: The data-driven module in the digital twin unit reads the motion data and generates animation data for each simulation device; Step S154: The animation output module in the digital twin unit generates and displays the simulation animation based on the animation data.
7. The simulation method using a production line design simulation system based on digital twin technology as described in claim 5, characterized in that, It also includes methods for production line design based on historical simulation data, comprising the following steps: Step S20: Using the statistical output module in the digital twin unit, read the video saved from each simulation animation. Step S21: Extract the corresponding logistics status from the video; Step S22: Perform statistical analysis on the logistics status and select the optimal logistics parameters. Step S23: Complete the production line design based on the logistics model, the throughput model, and the logistics parameters.