Simulation evaluation method based on embedded part production planning and scheduling

Abstract

The invention provides a simulation evaluation method based on an embedded part production plan and scheduling, and belongs to the technical field of simulation evaluation, and the method comprises the steps: carrying out the production line scheme sorting of an embedded part perforation plug welding production line; establishing a simulation model for an embedded part perforation plug welding production line; carrying out production plan evaluation aiming at an embedded part perforation plug welding production line; and carrying out production line guidance aiming at the embedded part perforation plug welding production line. Professional simulation modeling software is adopted as a solving tool, a simulation model which is in high-precision fit with an actual embedded part perforation plug welding production line is built on the basis of artificial experience and field projects, and powerful support is provided for project planning verification and optimization.

Description

Technical Field

[0001] This invention belongs to the field of simulation evaluation technology, specifically relating to a simulation evaluation method based on the production planning and scheduling of embedded parts. Background Technology

[0002] As mentioned in the prior art patent publication number "CN119640951A", perforated plug welding embedded parts are still used in embedded parts. The corresponding perforated plug welding production line is an intelligent manufacturing system used in fields such as nuclear power and building curtain walls. Its core is to achieve efficient and precise welding of embedded parts through automation technology. Currently, the production planning and scheduling of perforated plug welding production lines for embedded parts mainly rely on manual experience and on-site observation. Based on different types of process products, tools such as Excel are used to roughly estimate planned capacity and calculate process cycle time. This method of roughly estimating planned capacity and calculating process cycle time has the following drawbacks: The accuracy of the assessment results of rough estimated planned capacity and process cycle time is poor; the methods for rough estimated planned capacity and process cycle time are not reusable; and the calculation speed for rough estimated planned capacity and process cycle time is slow and inefficient. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a simulation evaluation method based on the production planning and scheduling of embedded parts. This method effectively avoids the defects of existing technologies, such as poor accuracy of the evaluation results of rough estimated planned capacity and process cycle time, poor reusability of the methods for rough estimated planned capacity and process cycle time, and slow calculation speed and low efficiency.

[0004] The present invention employs the following technical solution.

[0005] A simulation evaluation method based on embedded parts production planning and scheduling includes: Step 1: Conduct a production line solution review for the embedded part perforation plug welding production line; Step 2: Build a simulation model for the pre-embedded part perforation plug welding production line; Step 3: Conduct a production plan assessment for the embedded part perforation plug welding production line; Step 4: Provide production line guidance for the embedded part perforation plug welding production line.

[0006] Furthermore, in step 1, the production operation logic and key business data of the embedded part perforation plug welding production line are sorted out and processed according to the format requirements of the simulation model.

[0007] Furthermore, in step 1, the entire format of the sorting includes the documents, drawings, material tables, acceptance cycles, and tasks of the embedded part perforation plug welding production line. Specifically, the entire format includes the production line CAD layout design, product specification sorting, material box type sorting, production line positioning design and allocation, process and layout, production line task decomposition and execution rules, as well as AGV scheduling rules and operating parameters.

[0008] Furthermore, step 1 specifically includes: Production line CAD layout design: Based on the two-dimensional or three-dimensional CAD drawings of the actual production line of the embedded part perforation plug welding production line, extract the spatial position, equipment size and path relationship of each station to form layout data that can be used for simulation. Product Specifications Review: Collect and organize information on the model, size, weight, and welding process parameters of embedded parts products from the embedded parts perforation plug welding production line, and establish a product specification database; Material bin type classification: Based on the product specifications and logistics requirements of the embedded part perforation plug welding production line, define the type, size, maximum loading quantity, and matching product rule parameters of the material bins; Production line positioning design and allocation: coordinate positioning and logical assignment of each workstation, storage location and AGV docking point of the embedded part perforation plug welding production line to ensure that the spatial relationship of each object in the simulation model is consistent with the actual production line; Process and layout analysis: Analyze the processing flow, cycle time, process path and logical relationship between each station of the embedded part perforation plug welding production line, and construct a process flow diagram; Production line task breakdown and execution rule definition: The production line operation tasks of the embedded part perforation plug welding production line are broken down into sub-tasks such as material feeding, processing, inspection, and material unloading, and the execution conditions, triggering logic and status feedback mechanism of each sub-task are defined. AGV scheduling rules and operating parameter settings: Based on the actual AGV operating parameters and scheduling logic of the embedded part perforation plug welding production line, establish an AGV scheduling strategy model; Data format standardization: All the above sorting results are output in a structured manner according to the format requirements of the simulation modeling platform, including layout files, bill of materials, task flow tables, and AGV scheduling rule files, to ensure that the data can be directly imported into the simulation model for use.

[0009] Furthermore, in step 2, simulation modeling tools are used to import CAD layouts, model elements, input key information, and write scheduling logic code to construct a simulation model.

[0010] Furthermore, in step 2, the model elements of the final simulation model include: processing units, storage locations, bins, products, AGVs and docking points, tracks, cycle triggers, global variables, logic code, and statistical tools.

[0011] Furthermore, step 2 specifically includes: CAD layout import: Import the CAD drawings of the actual production line of the embedded part perforation plug welding production line into the simulation modeling tool, complete the coordinate calibration and spatial mapping of the layout, and ensure that the spatial structure of the model is consistent with the actual production line; Model element modeling: Create basic model elements such as processing units, storage locations, bins, products, AGVs, docking points, and tracks in the simulation environment of the simulation modeling tool, and configure their spatial attributes and business parameters; Key information input: Import key business data such as product specifications, bin types, storage capacity, and AGV operating parameters of the embedded parts perforation plug welding production line to build a material information database; Scheduling logic code writing: Write the core logic code for the task triggering strategy, AGV scheduling strategy, and warehouse location sorting strategy of the embedded part perforation plug welding production line, and implement key functions such as task generation, AGV path planning, and warehouse location allocation. Model integration and testing: Integrate the various modules such as CAD layout import, model element modeling, key information input, and scheduling logic code writing into a complete simulation model, and conduct path testing, task flow verification, and scheduling logic debugging to ensure stable model operation; Statistical tool configuration: Configure the statistical tool module to achieve real-time collection and visualization of key performance indicators such as AGV utilization rate, warehouse turnover rate, and task completion rate.

[0012] Furthermore, in step 2, the simulation modeling tool is Tecnomatix Plant Simulation software.

[0013] Furthermore, in step 3, the evaluation content of the embedded part perforation plug welding production line is refined, and the production plan of the embedded part perforation plug welding production line is analyzed and optimized from multiple dimensions, and presented in the form of models and charts.

[0014] Furthermore, in step 3, the production plan is input into the simulation model to obtain a detailed report of the simulation output. The detailed report includes the number of completed orders, AGV scheduling tasks, AGV efficiency, maximum hanging task statistics, cache location and material box statistics, and the integration of logic code and statistical tools.

[0015] Furthermore, step 3 specifically includes: Capacity assessment: Based on the simulation operation data of the simulation model, that is, the detailed report output by the simulation, the cycle time analysis method is used to identify the bottleneck station of the production line. By statistically analyzing the processing cycle and waiting time of each station, a cycle time distribution map is constructed, and the deviation rate between the theoretical maximum capacity and the actual capacity is calculated. AGV Quantity Assessment: By combining AGV scheduling logs and path planning data, a correlation model between AGV load rate and task completion rate is constructed. Sensitivity analysis is used to assess the impact of different AGV quantities on task completion rate. Material bin quantity assessment: Based on warehouse inventory data and material bin turnover records, calculate material bin inventory turnover rate and warehouse location utilization rate; Raw material storage area assessment and post-processing loading area assessment: By using cache location statistics and bin distribution data, the rationality of the storage location configuration of raw material storage area and loading area is assessed.

[0016] Furthermore, in step 4, based on the simulation model output results, that is, the detailed simulation output report, combined with management experience and actual production conditions, the production plan is issued, the production process is monitored, and the plan is reviewed.

[0017] Furthermore, in step 4, the simulation results under different types of production scenarios were evaluated to guide production planning for various real-world scenarios.

[0018] Furthermore, step 4 specifically includes: Simulation Result Analysis and Production Scenario Matching: Using the statistical charts built into the simulation model, key indicators such as order completion rate, AGV task completion rate, and warehouse utilization rate are extracted. Combined with real-world production data, a production scenario classification model is constructed, matching the current scenario to the optimal solution in the simulation result database. Order quantity recommendation: Based on historical order data and simulation results, an order batch recommendation model is constructed to recommend order batches according to simulation data and actual production capacity; AGV Quantity Recommendation and Scheduling Task Analysis: Combine the AGV efficiency analysis module and path heatmap to adjust the AGV quantity and scheduling strategy; Recommended number of bins and recommended storage locations: Based on the inventory turnover rate model and spatial heat map, a dynamic storage location allocation strategy is constructed; Real-time monitoring and anomaly warning of the production process: Construct a real-time monitoring module to collect data on AGV operation status, workstation processing status, and warehouse inventory, and compare and analyze the data with simulation predictions. Use anomaly detection algorithms to identify abnormal fluctuations. Planned review and continuous optimization: Based on the differences between simulation and actual operation data, construct a review and analysis model; Future improvements plan: Introduce an advanced scheduling module to enable online optimization of production line guidance strategies.

[0019] The beneficial effects of the present invention are as follows, compared with the prior art: This invention outlines production line solutions for embedded part perforation plug welding production lines; builds simulation models for embedded part perforation plug welding production lines; evaluates production plans for embedded part perforation plug welding production lines; and provides production line guidance for embedded part perforation plug welding production lines. It employs professional simulation modeling software as a solution tool, and based on human experience and on-site projects, builds a highly accurate and stable simulation model that closely matches the actual embedded part perforation plug welding production line, providing strong support for project planning, verification, and optimization. Attached Figure Description

[0020] Figure 1 This is a flowchart of the simulation evaluation method based on the production planning and scheduling of embedded parts in this invention; Figure 2 is a schematic diagram of all the formats of step 1 of the simulation evaluation method based on the production planning and scheduling of embedded parts in this invention. Figures 2(1) to 2(8) are schematic diagrams of each format of step 1 of the simulation evaluation method based on the production planning and scheduling of embedded parts. Figure 3 This is a schematic diagram of the simulation model finally completed in step 2 of the simulation evaluation method based on the production planning and scheduling of embedded parts in this invention; Figure 4 This is a schematic diagram of step 4, the simulation summary results overview, of the simulation evaluation method based on the production planning and scheduling of embedded parts in this invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, other embodiments obtained by those skilled in the art without creative effort are all within the protection scope of this invention.

[0022] like Figure 1 As shown, a simulation evaluation method based on embedded part production planning and scheduling includes: A simulation evaluation method based on embedded parts production planning and scheduling includes: Step 1: Conduct a production line solution review for the embedded part perforation plug welding production line; In a preferred but non-limiting embodiment of the present invention, in step 1, the production operation logic and key business data of the embedded part perforation plug welding production line are sorted out and processed according to the format requirements of the simulation model.

[0023] As shown in Figure 2, in a preferred but non-limiting embodiment of the present invention, in step 1, the entire format of the sorting includes the documents, drawings, material tables, acceptance cycles, and tasks of the embedded part perforation plug welding production line. Specifically, the entire format includes the production line CAD layout design, product specification sorting, material box type sorting, production line positioning design and allocation, process and layout, production line task decomposition and execution rules, as well as AGV scheduling rules and operating parameters.

[0024] In a preferred but non-limiting embodiment of the present invention, step 1 specifically includes: Production line CAD layout design: Based on the two-dimensional or three-dimensional CAD drawings of the actual production line of the embedded part perforation plug welding production line, extract the spatial position, equipment size and path relationship of each station to form layout data that can be used for simulation. Product Specifications Review: Collect and organize information on the model, size, weight, welding process parameters, etc. of the embedded parts products of the embedded parts perforation plug welding production line, and establish a product specification database; Material bin type classification: Based on the product specifications and logistics requirements of the embedded part perforation plug welding production line, define parameters such as the type, size, maximum loading quantity, and matching product rules of the material bins; Production line positioning design and allocation: coordinate positioning and logical assignment of each workstation, storage location and AGV docking point of the embedded part perforation plug welding production line to ensure that the spatial relationship of each object in the simulation model is consistent with the actual production line; Process and layout analysis: Analyze the processing flow, cycle time, process path and logical relationship between each station of the embedded part perforation plug welding production line, and construct a process flow diagram; Production line task breakdown and execution rule definition: The production line operation tasks of the embedded part perforation plug welding production line are broken down into sub-tasks such as material feeding, processing, inspection, and material unloading, and the execution conditions, triggering logic and status feedback mechanism of each sub-task are defined. AGV scheduling rules and operating parameter settings: Based on the actual AGV operating parameters (such as maximum speed, turning radius, charging strategy, etc.) and scheduling logic (such as priority scheduling, path planning, conflict detection, etc.) of the pre-embedded part perforation plug welding production line, establish an AGV scheduling strategy model; Data format standardization: All the above sorting results are output in a structured manner according to the format requirements of the simulation modeling platform (such as TecnomatixPlant Simulation), including layout files, bill of materials, task flow tables, AGV scheduling rule files, etc., to ensure that the data can be directly imported into the simulation model for use.

[0025] The above methods enable a systematic review of the production operation logic and key business data of the embedded part perforation plug welding production line, and complete the standardized processing of the data required for simulation modeling, providing a complete and accurate data foundation for subsequent high-precision simulation modeling and production line optimization.

[0026] Step 2: Build a simulation model for the pre-embedded part perforation plug welding production line; In a preferred but non-limiting embodiment of the present invention, in step 2, a simulation modeling tool is used to import CAD layout, model elements, input key information, and write scheduling logic code to construct a simulation model.

[0027] In a preferred but non-limiting embodiment of the present invention, in step 2, the final simulation model is as follows: Figure 3 As shown, the final simulation model includes the following elements: processing unit, storage location, bin, product, AGV and docking point, track, cycle trigger, global variables, logic code, and statistical tools.

[0028] In a preferred but non-limiting embodiment of the present invention, step 2 specifically includes: CAD layout import: Import the CAD drawings of the actual production line of the embedded part perforation plug welding production line into the simulation modeling tool, complete the coordinate calibration and spatial mapping of the layout, and ensure that the spatial structure of the model is consistent with the actual production line; Model element modeling: Create basic model elements such as processing units, storage locations, bins, products, AGVs, docking points, and tracks in the simulation environment of the simulation modeling tool, and configure their spatial attributes and business parameters; Key information input: Import key business data such as product specifications, bin types, storage capacity, and AGV operating parameters of the embedded parts perforation plug welding production line to build a material information database; Scheduling logic code writing: Write core logic code such as task triggering strategy, AGV scheduling strategy, and warehouse location sorting strategy for the embedded part perforation plug welding production line, and implement key functions such as task generation, AGV path planning, and warehouse location allocation. Model integration and testing: Integrate the various modules such as CAD layout import, model element modeling, key information input, and scheduling logic code writing into a complete simulation model, and conduct path testing, task flow verification, and scheduling logic debugging to ensure stable model operation; Statistical tool configuration: Configure the statistical tool module to achieve real-time collection and visualization of key performance indicators such as AGV utilization rate, warehouse turnover rate, and task completion rate.

[0029] The simulation model constructed using the above methods can accurately reflect the physical layout and business logic of the embedded part perforation plug welding production line, supporting subsequent production plan evaluation, scheduling strategy optimization, and resource allocation decisions.

[0030] In a preferred but non-limiting embodiment of the present invention, in step 2, the simulation modeling tool is TecnomatixPlant Simulation software.

[0031] Step 2 involves using simulation modeling tools to sequentially import the CAD layout, model element modeling, input key information, and write scheduling logic code. This ultimately constructs a complete simulation model including processing units, storage locations, bins, products, AGVs and their docking points, tracks, cycle triggers, global variables, logic code, and statistical tools. This method improves modeling efficiency and accuracy, enhances the simulation model's ability to map actual production line operation logic, and provides reliable data support for subsequent production planning evaluation and scheduling optimization.

[0032] In the simulation modeling embodiment of a pre-embedded part perforation plug welding production line in step 2, Tecnomatix Plant Simulation software was used as the simulation modeling tool. Based on the production line CAD layout and business rules of the pre-embedded part perforation plug welding production line, a complete simulation model was constructed, including processing units, storage locations, material bins, products, AGVs and docking points, tracks, cycle triggers, global variables, logic code, and statistical tools. In this embodiment, the model element construction process includes steps such as CAD layout import, model element modeling, key information input, and scheduling logic code writing, as detailed below.

[0033] I. Importing CAD Layouts and Modeling Model Elements First, the 2D CAD layout drawings of the pre-embedded part perforation and plug welding production line were imported into Tecnomatix PlantSimulation software. Coordinate mapping and scaling techniques were used to ensure that the spatial relationship between the layout model and the actual production line was consistent. Subsequently, a modular modeling approach was adopted to sequentially create model elements such as processing units (e.g., loading station, perforation station, plug welding station, inspection station, unloading station), storage locations (raw material temporary storage area, semi-finished product transfer area, finished product loading area), and material bins (standard material bins, customized material bins) in the simulation environment of Tecnomatix Plant Simulation software.

[0034] The processing unit object is configured with its processing cycle, waiting logic, and status feedback interface. For example, the processing cycle of the perforation station is 8 seconds. If there are no tasks currently, it enters an idle state; if a loading completion signal is received, processing automatically starts. The storage location object sets capacity limits, priority rules, and dynamic allocation strategies. For example, the raw material temporary storage area uses a first-in, first-out (FIFO) strategy, while the finished product loading area allocates storage locations based on the shortest AGV path principle.

[0035] II. AGV and Path Modeling In Tecnomatix Plant Simulation software, an AGV resource pool was created, with 5 AGVs configured. Their maximum speed was set to 1.2 m / s, turning radius to 0.5 m, single-charge runtime to 8 hours, and charging strategy to automatically return to the charging station when battery level is low (<20%). Using a path network modeling tool, the connection between AGV stopping points and paths was set, constructing a complete AGV operation route map.

[0036] The AGV scheduling strategy employs the A* algorithm, combining task priority and AGV load status for scheduling. The scheduling logic uses a state machine model, supporting functions such as task queuing, path conflict detection, and automatic obstacle avoidance. For example, when an AGV receives a task request, it first determines its current load status. If it is empty, it proceeds to the designated storage location to load products; if it is loaded, it proceeds to the target workstation to execute the task.

[0037] III. Tick Trigger and Global Variable Settings To achieve production line rhythm control, a cycle time trigger module is set up, defining task triggering conditions and execution priority rules. For example, the task triggering condition for the piercing station is the completion signal from the loading station, and the task priority is medium. If the current piercing station is idle, the task will be executed automatically; if it is busy, it will enter the task queue to wait.

[0038] Global variables are used to manage key operating parameters such as AGV status, warehouse inventory, and task queue. For example, AGV status variables include four states: empty, loaded, charging, and waiting; warehouse inventory variables record the current number of loaded items and available capacity of the warehouse; and task queue variables store a list of tasks to be executed and sort them by priority.

[0039] IV. Integration of Logic Code and Statistical Tools The scheduling logic code is written in SimTalk to implement task flow control (such as triggering AGV scheduling upon task completion), exception handling (such as automatically pausing task generation when a workstation is blocked), and data interaction (such as real-time updating of statistical tool data sources). For example, after an AGV completes a task, the logic for the next task allocation is automatically triggered, and the task queue is updated according to the warehouse location status.

[0040] The statistics tool module integrates a real-time data acquisition framework, storing key performance indicators (KPIs) such as AGV utilization, task waiting time, and warehouse turnover rate through a time-series database. Combined with a visual dashboard, it displays information such as AGV running paths, task execution status, and warehouse usage, supporting multi-dimensional analysis (such as calculating processing time by product type and analyzing task load balancing by AGV number).

[0041] Step 3: Conduct a production plan assessment for the embedded part perforation plug welding production line; In a preferred but non-limiting embodiment of the present invention, in step 3, the evaluation content of the embedded part perforation plug welding production line is refined, and the production plan of the embedded part perforation plug welding production line is analyzed and optimized from multiple dimensions, and presented in the form of models and charts.

[0042] In a preferred but non-limiting embodiment of the present invention, in step 3, the production plan is input into the simulation model to obtain a detailed report of the simulation output. The detailed report includes the number of completed orders, AGV scheduling tasks, AGV efficiency, maximum number of pending tasks, statistics of cache locations and material boxes, integration of logic code and statistical tools, etc.

[0043] In a preferred but non-limiting embodiment of the present invention, step 3 specifically includes: Capacity Assessment: Based on simulation data from the simulation model (i.e., the detailed simulation output report), cycle time analysis is used to identify bottleneck workstations on the production line. By statistically analyzing the processing cycle and waiting time of each workstation, a cycle time distribution chart is constructed, and the deviation rate between theoretical maximum capacity and actual capacity is calculated. For example, if the average waiting time at the piercing workstation is 3 seconds, while other workstations have no waiting time, then the piercing workstation is the bottleneck. Parameter scanning technology is used to dynamically adjust the processing cycle of each workstation, optimize cycle time matching, and improve overall capacity.

[0044] AGV Quantity Assessment: Combining AGV scheduling logs and path planning data, a correlation model between AGV load rate and task completion rate is constructed. Sensitivity analysis is used to assess the impact of different AGV numbers on task completion rate; for example, increasing the number of AGVs from 5 to 6 increases the task completion rate from 92.5% to 97.8%. Path heatmaps are used to visualize congestion points on AGV operating paths, optimizing path connections or adding temporary waiting points to reduce path conflicts and idle rates. Tote box quantity assessment: Based on warehouse inventory data and tote box turnover records, calculate tote box inventory turnover rate and warehouse location utilization rate; for example, the average turnover cycle of standard tote boxes is 45 minutes, while that of customized tote boxes is 60 minutes, indicating that standard tote boxes are more efficient. Machine learning algorithms are used to analyze historical data and dynamically optimize warehouse location allocation rules (such as automatically prioritizing frequently used warehouse locations) to reduce AGV path length and waiting time.

[0045] Raw material storage area assessment and post-processing loading area assessment: By analyzing buffer location statistics and bin distribution data, the rationality of the location configuration in the raw material storage area and loading area is evaluated. For example, if 30% of the locations in the raw material temporary storage area have a utilization rate below 50%, it is recommended to adjust the location priority rules or reduce the number of locations. A spatial heatmap is used to display location usage frequency, and the location layout is optimized in conjunction with AGV path optimization to improve location turnover efficiency and AGV scheduling efficiency.

[0046] Step 4: Provide production line guidance for the embedded part perforation plug welding production line.

[0047] In a preferred but non-limiting embodiment of the present invention, in step 4, based on the output results of the simulation model, that is, the detailed report of the simulation output, combined with management experience and production status, the production plan is issued, the production process is monitored, and the plan is reviewed.

[0048] In a preferred but non-limiting embodiment of the present invention, in step 4, simulation results under different types of production scenarios are evaluated to guide production planning for various real-world scenarios. An overview of the summarized simulation results is as follows: Figure 4 As shown.

[0049] In a preferred but non-limiting embodiment of the present invention, step 4 specifically includes: Simulation Result Analysis and Production Scenario Matching: Using the statistical charts built into the simulation model (some chart content can be further developed using the program), key indicators such as order completion rate, AGV task completion rate, and warehouse utilization rate are extracted. Combined with real-world production data (such as order type, equipment status, and personnel configuration), a production scenario classification model is constructed, matching the current scenario to the optimal solution in the simulation result database; for example, if the current order is for high-precision customized parts and the AGV failure rate is high, the solution in the simulation is to increase the number of AGVs by 10%.

[0050] Order quantity recommendation: Based on historical order data and simulation results, an order batch recommendation model is constructed. Based on simulation data and actual production capacity, order batches are recommended. For example, if it is predicted that the order volume will increase by 20% in the next 3 days, it is recommended to adjust the single batch order from 100 pieces to 120 pieces, and optimize the cycle time of each workstation to match the production capacity demand.

[0051] AGV Quantity Recommendation and Scheduling Task Analysis: Combining the AGV efficiency analysis module and path heatmap, the number of AGVs and scheduling strategies can be flexibly adjusted. For example, when simulation shows that the AGV idle rate exceeds 20%, it is recommended to reduce one AGV and optimize the task allocation logic. If AGV path conflicts are frequent, it is recommended to adjust the priority rules or add temporary waiting points. Based on the scheduling rules, the impact of different AGV quantities on task completion rate is evaluated, and the optimal configuration is dynamically recommended.

[0052] Recommended hopper quantity and storage location: Based on inventory turnover rate model and spatial heat map, a dynamic storage location allocation strategy is constructed. For example, if the turnover cycle of standard hoppers is 45 minutes, while that of customized hoppers is 60 minutes, it is recommended to increase the inventory of standard hoppers and prioritize their allocation to frequently used storage locations. A multi-objective optimization algorithm (such as NSGA-II) is used to comprehensively consider inventory turnover rate, path distance, and storage location priority to dynamically optimize the storage location allocation rules, reducing AGV path length and waiting time.

[0053] Real-time monitoring and anomaly warning of the production process: Construct a real-time monitoring module to collect data on AGV running status, workstation processing status, and warehouse inventory, and compare and analyze the data with the simulation prediction values. Use anomaly detection algorithms (such as random forest) to identify abnormal fluctuations. For example, trigger an alarm when the AGV task completion rate is 10% lower than the simulation value, and recommend adjusting the number of AGVs or optimizing the scheduling strategy. Planned review and continuous optimization: Based on the differences between simulation and actual operation data, a review analysis model is built; for example, if the actual order completion rate is 5% lower than the simulation value, bottlenecks are analyzed through causal reasoning (such as increased waiting time at the perforation station), and scheduling strategies are optimized or resource allocation is adjusted. Digital twin technology is used to achieve two-way data synchronization between the simulation model and the actual production line, supporting continuous iterative improvement.

[0054] Future improvements include: introducing an advanced scheduling module to enable online optimization of production line guidance strategies. For example, dynamically adjusting AGV scheduling rules and warehouse allocation strategies based on actual operational data to improve model generalization capabilities. Furthermore, leveraging digital twin technology to build a virtual-physical integrated production line guidance platform that supports rapid adaptation and decision optimization across multiple scenarios.

[0055] Key advantages of this invention include: 1. The evaluation results are highly accurate. Through data integration and logical analysis, a model with a high degree of accuracy matching the actual production line is built, providing effective data support for production planning.

[0056] 2. The model is highly reusable and can provide guidance for the production of different types of orders and future new product orders.

[0057] 3. The model is easy to operate, requiring only simple steps to run and allowing users to intuitively view the simulation results, making it user-friendly for factory users.

[0058] 4. The calculation and derivation speed is fast. The model combines the advantages of software and adopts the simplification of the number of modules and optimization of code logic in the development process. It can simulate continuous production for many hours multiple times on a time basis of minutes, avoiding long waiting time.

[0059] The beneficial effects of the present invention are as follows, compared with the prior art: This invention outlines production line solutions for embedded part perforation plug welding production lines; builds simulation models for embedded part perforation plug welding production lines; evaluates production plans for embedded part perforation plug welding production lines; and provides production line guidance for embedded part perforation plug welding production lines. It employs professional simulation modeling software as a solution tool, and based on human experience and on-site projects, builds a highly accurate and stable simulation model that closely matches the actual embedded part perforation plug welding production line, providing strong support for project planning, verification, and optimization.

[0060] This invention constructs a virtual pre-embedded part production and logistics model as a prediction of the actual production plan. It can assist in production management and guide the production plan before the project is implemented, thereby achieving efficient production line production and assisting in monitoring the production process and reviewing the production plan.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention without departing from the spirit and scope of the present invention. Any modifications or equivalent substitutions should be covered within the scope of protection of the claims of the present invention.

Claims

1. A simulation evaluation method based on the production planning and scheduling of embedded parts, characterized in that, include: Step 1: Conduct a production line solution review for the embedded part perforation plug welding production line; Step 2: Build a simulation model for the pre-embedded part perforation plug welding production line; Step 3: Conduct a production plan assessment for the embedded part perforation plug welding production line; Step 4: Provide production line guidance for the embedded part perforation plug welding production line.

2. The simulation evaluation method based on pre-embedded part production planning and scheduling according to claim 1, characterized in that, In step 1, the production operation logic and key business data of the embedded part perforation plug welding production line are sorted out and processed according to the format requirements of the simulation model; In step 1, the entire format of the sorting includes the documents, drawings, material tables, acceptance cycles, and tasks of the embedded part perforation plug welding production line. Specifically, the entire format includes the production line CAD layout design, product specification sorting, material box type sorting, production line positioning design and allocation, process and layout, production line task breakdown and execution rules, as well as AGV scheduling rules and operating parameters.

3. The simulation evaluation method based on embedded part production planning and scheduling according to claim 2, characterized in that, Step 1 specifically includes: Production line CAD layout design: Based on the two-dimensional or three-dimensional CAD drawings of the actual production line of the embedded part perforation plug welding production line, extract the spatial position, equipment size and path relationship of each station to form layout data that can be used for simulation. Product Specifications Review: Collect and organize information on the model, size, weight, and welding process parameters of embedded parts products from the embedded parts perforation plug welding production line, and establish a product specification database; Material bin type classification: Based on the product specifications and logistics requirements of the embedded part perforation plug welding production line, define the type, size, maximum loading quantity, and matching product rule parameters of the material bins; Production line positioning design and allocation: coordinate positioning and logical assignment of each workstation, storage location and AGV docking point of the embedded part perforation plug welding production line to ensure that the spatial relationship of each object in the simulation model is consistent with the actual production line; Process and layout analysis: Analyze the processing flow, cycle time, process path and logical relationship between each station of the embedded part perforation plug welding production line, and construct a process flow diagram; Production line task breakdown and execution rule definition: The production line operation tasks of the embedded part perforation plug welding production line are broken down into sub-tasks such as material feeding, processing, inspection, and material unloading, and the execution conditions, triggering logic and status feedback mechanism of each sub-task are defined. AGV scheduling rules and operating parameter settings: Based on the actual AGV operating parameters and scheduling logic of the embedded part perforation plug welding production line, establish an AGV scheduling strategy model; Data format standardization: All the above sorting results are output in a structured manner according to the format requirements of the simulation modeling platform, including layout files, bill of materials, task flow tables, and AGV scheduling rule files, to ensure that the data can be directly imported into the simulation model for use.

4. The simulation evaluation method based on embedded part production planning and scheduling according to claim 3, characterized in that, In step 2, simulation modeling tools are used to import CAD layouts, model elements, input key information, and write scheduling logic code to construct a simulation model. In step 2, the final simulation model elements include: processing units, storage locations, bins, products, AGVs and docking points, tracks, cycle triggers, global variables, logic code, and statistical tools.

5. The simulation evaluation method based on pre-embedded part production planning and scheduling according to claim 4, characterized in that, Step 2 specifically includes: CAD layout import: Import the CAD drawings of the actual production line of the embedded part perforation plug welding production line into the simulation modeling tool, complete the coordinate calibration and spatial mapping of the layout, and ensure that the spatial structure of the model is consistent with the actual production line; Model element modeling: Create basic model elements such as processing units, storage locations, bins, products, AGVs, docking points, and tracks in the simulation environment of the simulation modeling tool, and configure their spatial attributes and business parameters; Key information input: Import key business data such as product specifications, bin types, storage capacity, and AGV operating parameters of the embedded parts perforation plug welding production line to build a material information database; Scheduling logic code writing: Write the core logic code for the task triggering strategy, AGV scheduling strategy, and warehouse location sorting strategy of the embedded part perforation plug welding production line, and implement key functions such as task generation, AGV path planning, and warehouse location allocation. Model integration and testing: Integrate the various modules such as CAD layout import, model element modeling, key information input, and scheduling logic code writing into a complete simulation model, and conduct path testing, task flow verification, and scheduling logic debugging to ensure stable model operation; Statistical tool configuration: Configure the statistical tool module to achieve real-time collection and visualization of key performance indicators such as AGV utilization rate, warehouse turnover rate, and task completion rate.

6. The simulation evaluation method based on embedded part production planning and scheduling according to claim 5, characterized in that, In step 2, the simulation modeling tool is Tecnomatix Plant Simulation software.

7. The simulation evaluation method based on embedded part production planning and scheduling according to claim 6, characterized in that, In step 3, the evaluation content of the embedded part perforation plug welding production line is refined, and the production plan of the embedded part perforation plug welding production line is analyzed and optimized from multiple dimensions, and presented in the form of models and charts. In step 3, the production plan is input into the simulation model, and a detailed report of the simulation output is obtained. The detailed report includes the number of orders completed, AGV scheduling tasks, AGV efficiency, maximum number of pending tasks, statistics of cache locations and material boxes, and integration of logic code and statistical tools.

8. The simulation evaluation method based on embedded part production planning and scheduling according to claim 7, characterized in that, Step 3 specifically includes: Capacity assessment: Based on the simulation operation data of the simulation model, that is, the detailed report output by the simulation, the cycle time analysis method is used to identify the bottleneck station of the production line. By statistically analyzing the processing cycle and waiting time of each station, a cycle time distribution map is constructed, and the deviation rate between the theoretical maximum capacity and the actual capacity is calculated. AGV Quantity Assessment: By combining AGV scheduling logs and path planning data, a correlation model between AGV load rate and task completion rate is constructed. Sensitivity analysis is used to assess the impact of different AGV quantities on task completion rate. Material bin quantity assessment: Based on warehouse inventory data and material bin turnover records, calculate material bin inventory turnover rate and warehouse location utilization rate; Raw material storage area assessment and post-processing loading area assessment: By using cache location statistics and bin distribution data, the rationality of the storage location configuration of raw material storage area and loading area is assessed.

9. The simulation evaluation method based on pre-embedded part production planning and scheduling according to claim 8, characterized in that, In step 4, based on the simulation model output results, that is, the detailed simulation output report, combined with management experience and actual production conditions, the production plan is issued, the production process is monitored, and the plan is reviewed. The simulation results were evaluated under different types of production scenarios to guide production planning in various real-world scenarios.

10. The simulation evaluation method based on pre-embedded part production planning and scheduling according to claim 9, characterized in that, Step 4 specifically includes: Simulation results analysis and production scenario matching: The detailed report of the simulation output is analyzed using the statistical charts built into the simulation model, and key indicators such as order completion rate, AGV task completion rate, and warehouse space utilization rate are extracted. By combining real-time production data, a production scenario classification model is constructed, and the current scenario is matched to the optimal solution in the simulation result database. Order quantity recommendation: Based on historical order data and simulation results, an order batch recommendation model is constructed to recommend order batches according to simulation data and actual production capacity; AGV Quantity Recommendation and Scheduling Task Analysis: Combine the AGV efficiency analysis module and path heatmap to adjust the AGV quantity and scheduling strategy; Recommended number of bins and recommended storage locations: Based on the inventory turnover rate model and spatial heat map, a dynamic storage location allocation strategy is constructed; Real-time monitoring and anomaly warning of the production process: Construct a real-time monitoring module to collect data on AGV operation status, workstation processing status, and warehouse inventory, and compare and analyze the data with simulation predictions. Use anomaly detection algorithms to identify abnormal fluctuations. Planned review and continuous optimization: Based on the differences between simulation and actual operation data, a review and analysis model is constructed; Future improvements plan: Introduce an advanced scheduling module to enable online optimization of production line guidance strategies.

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