Hull joint workshop process equipment load simulation and balancing verification method and system

Abstract

The application discloses a hull joint workshop process equipment load simulation and balancing verification method and system, comprising: through structured extraction and analysis of hull whole-process process data, constructing process-device mapping knowledge base and integrating device performance parameters; taking production plan and product characteristics as input, accurately calculating working hours of each process combined with correction coefficient, and optimally determining the optimal process route; after accurately mapping the working hours to the corresponding device, counting the load rate according to the period, identifying the bottleneck equipment and system-level bottleneck area according to the threshold value and key path rule, and then optimizing the task allocation of multiple devices in the same process under the process constraint by using the minimum maximum load difference algorithm. The application solves the problems of existing method verification lag, equipment load imbalance, inaccurate bottleneck identification and low data cooperation efficiency, and realizes the whole-process closed-loop operation from data processing, working hour deduction, load simulation, bottleneck identification to load balancing and scheme verification.

Description

Technical Field

[0001] This invention relates to the field of intelligent ship manufacturing and digital process design technology, specifically to a method and system for load simulation and balancing verification of process equipment in a ship hull integrated workshop. Background Technology

[0002] In modern shipbuilding enterprises, the hull assembly workshop is a core component for achieving efficient section construction. It handles the entire process from steel plate pretreatment, CNC cutting, component assembly and welding to section welding and final assembly. The configuration and scheduling of its process equipment directly impact production rhythm and delivery cycle. Currently, shipyards generally adopt the traditional process verification model of "experience-based design—physical trial operation—on-site adjustment," which presents the following technical challenges: 1. Validation lag: The interval between process design and actual production is short, and there is a lack of pre-production digital validation methods. After production, problems such as equipment overload and cycle time mismatch are easily exposed. 2. Lack of quantitative analysis: Relying on experience-based estimation and static production scheduling makes it difficult to dynamically reflect the actual load status of equipment under multi-variety, small-batch, segmented production. 3. Low resource utilization: Overload of key process equipment creates production bottlenecks; uneven load distribution among similar equipment results in low resource utilization. 4. High adjustment costs: Frequent rework and adjustments after the design is put into production result in long verification cycles and high costs.

[0003] While existing manufacturing execution systems or advanced planning and scheduling systems can perform production scheduling, they lack the ability to dynamically simulate and balance loads by using the performance of process equipment as a hard constraint and integrating process data at all levels from parts to components to segments, thus failing to support the pre-verification of process solutions.

[0004] Therefore, there is an urgent need for a dynamic verification system that integrates process knowledge, planning timing, and equipment capabilities to achieve a technological breakthrough of "testing the load before the plan is built". Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for load simulation and balancing verification of process equipment in a ship hull integrated workshop. This method involves structured extraction and analysis of the entire ship hull process data, constructing a process-equipment mapping knowledge base and integrating equipment performance parameters. Using production plans and product characteristics as inputs, and combining correction coefficients, the method accurately calculates the working hours of each process and selects the optimal process route. After accurately mapping the working hours to the corresponding equipment, the method periodically calculates the load rate, identifies bottleneck equipment and system-level bottleneck areas based on threshold exceedance and critical path rules, and then uses the minimum-maximum load difference algorithm to optimize the task allocation of multiple equipment in the same process under process constraints. This achieves a closed-loop operation of the entire process from data processing, working hour extrapolation, load simulation, bottleneck identification to load balancing and solution verification, solving the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: The method for load simulation and balancing verification of process equipment in the hull assembly workshop includes the following steps: S1. Structured extraction of BOM, geometric features, material properties and process specifications of hull parts, components and sections. Structured analysis of each process link of steel pretreatment, cutting and processing, component assembly and welding and section assembly and welding, extracting process sequence, standard time coefficient, equipment type requirements and process constraints. S2. Construct a process-equipment mapping knowledge base, establish the association between each process and the set of executable equipment, and integrate equipment performance parameters; S3. Based on the production plan, phased construction sequence, and delivery requirements, combined with product size, material, and changeover time correction coefficients; using the shortest working time, lowest cost, and most balanced equipment load as comprehensive evaluation indicators, calculate the precise working time of each process, and perform parallel calculation and optimization of the working time of process route branches, automatically outputting the optimal process route and process sequence. S4. Map the calculated working hour data to the implementation equipment, accumulate the equipment task time according to the planned cycle, and generate the equipment load curve; introduce equipment availability constraints and calculate the equipment load rate. S5. For multiple machines in the same process, the minimum maximum load difference optimization algorithm is adopted to adjust the task assignment under process constraints; S6. Output load heat maps, bottleneck warnings, and optimization comparison analysis for each device; establish a feasibility rating for the solution, including three levels: feasible, critical, and infeasible, and provide optimization suggestions and improvement plans.

[0007] Furthermore, in S3, the precise working time for each process is calculated using the following formula: in, For the first The segment in the first Total working hours for each process; As the baseline working hours; , These are correction factors for size and material, respectively. Time for equipment changeover / preparation.

[0008] Furthermore, in S4, equipment availability constraints are introduced to calculate the equipment load rate, and the calculation formula is as follows: in, For equipment load factor This refers to the theoretically available working hours of the equipment during the planning period.

[0009] Furthermore, S4 also includes: The bottleneck is defined as: satisfying And the equipment is located in the critical path process; in, The preset threshold; When multiple machines in the same process have a load rate exceeding the threshold for three or more consecutive cycles. If so, the entire process is marked as a system-level bottleneck area.

[0010] Furthermore, in S5, for scenarios involving multiple devices in the same process, a minimum-maximum load difference optimization algorithm is adopted, and its calculation formula is as follows: in, A collection of similar devices.

[0011] Furthermore, in S1, the structured analysis includes standardized modeling of the logical relationships, sequence, and parallel constraints of the entire process of steel plate pretreatment, CNC cutting, component assembly welding, and segmented assembly welding, forming a multi-path optional process network diagram; the process constraints include the pre- and post-process dependencies, equipment accuracy level limitations, tooling and fixture compatibility requirements, and time window constraints for shared equipment in multiple segments.

[0012] Furthermore, in S2, the equipment performance parameters include maximum processing capacity, standard cycle time, changeover preparation time, equipment accuracy level, tooling adaptation type, rated load limit and maintenance cycle. Based on the equipment performance parameters, a hard constraint rule library for process-equipment matching is constructed.

[0013] Furthermore, in S4, the planning cycle is a daily, weekly, or monthly cycle; the equipment load curve is generated with the time axis as the horizontal axis and the load rate as the vertical axis, and the equipment maintenance period, shift switching point, and replacement time window are superimposed and marked.

[0014] The hull-integrated workshop process equipment load simulation and balancing verification system includes: The data access and preprocessing module is configured to integrate data with PLM, ERP and MES systems, and to clean, convert and standardize the acquired multi-source data. The knowledge base management module is configured to store and manage process specifications, equipment parameters, and standard working time data. The load simulation engine module is configured to perform time calculation, time-to-equipment mapping, load rate statistics, and bottleneck identification calculation. The load balancing optimization algorithm module is configured to intelligently generate equipment load balancing scheduling schemes based on optimization algorithms. The visualization verification platform is configured to display simulation results in charts and heatmaps, and supports interactive scheme adjustments.

[0015] Furthermore, the visual verification platform is configured to perform the following operations: A three-dimensional visual representation of the load distribution heat map is provided, considering equipment, process, and time dimensions. Equipment with a load rate exceeding a preset threshold is marked in real time, and the affected downstream key processes are also marked in conjunction with this. The system displays the equipment load curves, number of bottleneck devices, maximum load difference, and feasibility rating comparison results before and after load balancing optimization in parallel. The system provides a human-computer interaction adjustment interface, allowing users to adjust production tasks, modify equipment assignment relationships, or correct production scheduling by dragging and dropping, and triggering the load simulation engine to perform real-time recalculation and scheme re-verification.

[0016] Compared with the prior art, the beneficial effects of the present invention are: 1. Based on the full-level process data of hull parts, components, and sections, the system extracts the full-process process data through structured processing, constructs a process-equipment mapping knowledge base and a multi-path optional process network diagram, and realizes accurate calculation of process time and parallel optimization of multi-level process routes from parts to sections. The system automatically outputs the optimal process route with the shortest time, lowest cost, and most balanced equipment load as comprehensive evaluation indicators, overcoming the shortcomings of traditional experience estimation and static scheduling, which are difficult to dynamically reflect the status of multi-variety and small-batch production.

[0017] 2. By introducing equipment availability constraints and load rate calculation formulas, and combining them with actual constraints such as equipment maintenance cycles, shift switching, and changeover times, the system can accurately generate equipment load curves and automatically identify bottleneck equipment and bottleneck areas, significantly improving the accuracy and dynamic adaptability of load prediction and bottleneck identification. Furthermore, for the minimum and maximum load difference optimization algorithm in scenarios with multiple equipment in the same process, the system adjusts task assignments under multiple hard constraints such as process dependence, equipment accuracy, and tooling compatibility, achieving a scientific balance of equipment load, effectively avoiding equipment overload or idleness, and improving overall resource utilization efficiency.

[0018] 3. By displaying the load distribution of equipment, processes, and time periods in the form of a 3D heat map, the system supports users to drag and drop tasks, adjust equipment assignments, and modify production schedules through an interactive interface. This triggers real-time recalculation and verification by the simulation engine and provides specific optimization suggestions and improvement plans. It enables digital pre-verification of process solutions during the design phase, significantly reducing the risk of adjustments after production commences, and providing quantitative decision support for workshop process layout optimization, equipment purchase and technical upgrades, and capacity planning. Attached Figure Description

[0019] Figure 1This is a flowchart illustrating the overall implementation method of the present invention; Figure 2 This is a diagram showing the system architecture modules of the present invention; Figure 3 This is a flowchart of the load simulation and balancing optimization process of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] To address the technical issue that while existing systems can perform production scheduling, they lack the ability to dynamically simulate and balance loads at all levels of process data (parts, components, and segments) with process equipment performance as a hard constraint, thus failing to support pre-process scheme verification, please refer to [link to relevant documentation]. Figure 1 - Figure 3 This embodiment provides the following technical solution: The method for load simulation and balancing verification of process equipment in the hull assembly workshop includes the following steps: S1. Structured extraction of BOM, geometric features, material properties, and process specifications for hull parts, components, and sections. Structured analysis of each process step, including steel pretreatment, cutting, component assembly and welding, and section assembly and welding, extracting process sequences, standard time coefficients, equipment type requirements, and process constraints. The structured analysis includes standardized modeling of the logical relationships, sequence, and parallel constraints of the entire process, from steel plate pretreatment, CNC cutting, component assembly and welding, to section assembly and welding, forming a multi-path optional process network diagram. Process constraints include pre- and post-process dependencies, equipment accuracy level limitations, tooling and fixture compatibility requirements, and time window constraints for shared equipment across multiple sections.

[0022] S2. Construct a process-equipment mapping knowledge base, establish the association between each process and the set of executable equipment, and integrate equipment performance parameters. Among them, equipment performance parameters include maximum processing capacity, standard cycle time, changeover preparation time, equipment accuracy level, tooling adaptation type, rated load limit and maintenance cycle. Based on the equipment performance parameters, construct a process-equipment matching hard constraint rule base.

[0023] S3. Based on the production plan, phased construction sequence, and delivery requirements, combined with product dimensions, materials, and changeover time correction coefficients; using the shortest working hours, lowest cost, and most balanced equipment load as comprehensive evaluation indicators, calculate the precise working hours of each process, and perform parallel calculation and optimization of the working hours for process route branches, automatically outputting the optimal process route and process sequence; among which, the calculation formula for the precise working hours of each process is as follows: in, For the first The segment in the first Total working hours for each process; As the baseline working hours; , These are correction factors for size and material, respectively. Time for equipment changeover / preparation.

[0024] The beneficial effects achieved by the above content are as follows: Based on the full-level process data of hull parts, components, and sections, the process data of the entire process is extracted in a structured manner, and a process-equipment mapping knowledge base and a process network diagram with multiple paths are constructed. This enables accurate calculation of the time of multi-level process routes from parts to sections and parallel optimization. The optimal process route is automatically output with the shortest time, lowest cost, and most balanced equipment load as comprehensive evaluation indicators. This overcomes the shortcomings of traditional experience estimation and static scheduling, which are difficult to dynamically reflect the status of multi-variety and small-batch production.

[0025] S4. Map the calculated working hours data to the implemented equipment, accumulate the equipment task time according to the planned cycle, and generate the equipment load curve; the planned cycle can be daily, weekly, or monthly; the equipment load curve is generated with the time axis as the horizontal axis and the load rate as the vertical axis, and the equipment maintenance period, shift switch point, and changeover time window are superimposed and marked; introduce equipment availability constraints and calculate the equipment load rate, the calculation formula is: in, For equipment load factor The theoretical available working hours for the equipment during the planning period (e.g., after deducting maintenance, shifts, etc.); The bottleneck is defined as: satisfying And the equipment is located in the critical path process; in, The preset threshold is 0.95; when the load rate of multiple machines exceeds the threshold for three or more consecutive cycles within the same process. If so, the entire process is marked as a system-level bottleneck area.

[0026] S5. For multiple machines in the same process, the minimum-maximum load difference optimization algorithm is used to adjust task assignment under process constraints. The calculation formula is as follows: in, It is a collection of similar equipment; under the premise of meeting process constraints such as equipment accuracy level and tooling compatibility, it can adjust task assignment and support optimization with the goals of equipment utilization, delivery time and production cost, so as to achieve multi-objective optimization.

[0027] The beneficial effects achieved by the above content are as follows: By introducing equipment availability constraints and load rate calculation formulas, and combining them with actual constraints such as equipment maintenance cycles, shift switching, and changeover times, the system can accurately generate equipment load curves and automatically identify bottleneck equipment and bottleneck areas, significantly improving the accuracy and dynamic adaptability of load prediction and bottleneck identification. Furthermore, for the minimum and maximum load difference optimization algorithm in scenarios with multiple equipment in the same process, the system adjusts task assignments under multiple hard constraints such as process dependence, equipment accuracy, and tooling compatibility, achieving a scientific balance of equipment load, effectively avoiding equipment overload or idleness, and improving overall resource utilization efficiency.

[0028] S6. Output load heat maps, bottleneck warnings, and optimization comparison analysis for each device; establish a feasibility rating for the solution, including three levels: feasible, critical, and infeasible, and provide optimization suggestions and improvement plans.

[0029] In one embodiment, let's take the process design verification of a newly built planar segmented production line in a shipyard as an example.

[0030] First, in the data preprocessing stage, the system imports the 3D model of the plane segment, the production plan (e.g., 4 segments to be completed each month), and the preliminary planned process route (e.g., steel plate preprocessing, CNC cutting, small group assembly welding, intermediate assembly welding, and final assembly welding).

[0031] Then, the system proceeds to the time calculation stage. Based on the material, thickness, and cutting length of the steel plate, as well as the performance parameters of the CNC cutting machine, the system automatically calculates the total cutting time for each segment. Similarly, based on the weld length, welding process requirements such as fillet welds, bevel welds, and welding machine performance, the system calculates the welding time for each stage of assembly.

[0032] Next, load calculation and bottleneck identification are performed. The system schedules the calculated working hours according to the plan and maps them to specific equipment. Simulation results show that the load rate of the middle assembly welding station reaches 95%, while the load rate of the small assembly welding station is only 65%. Based on this, the system determines that the middle assembly welding station is the bottleneck process.

[0033] Finally, the process scheme is verified and optimized. Based on the results, the process engineer optimizes the initial scheme, for example, by moving some welding tasks of the middle assembly to the lighter small assembly station, or adjusting the workpiece flow rhythm between the two workstations. The optimized scheme is then input into the system for verification. The simulation results show that the load of each station tends to be balanced, such as between 75% and 85%, and the process scheme is finally confirmed.

[0034] The above examples demonstrate that this method can effectively and scientifically verify and optimize the process design of the hull assembly workshop.

[0035] The hull-integrated workshop process equipment load simulation and balancing verification system includes: The data access and preprocessing module is configured to integrate with the existing PLM, ERP, and MES systems of shipbuilding enterprises through standard interfaces. It automatically acquires information such as hull section BOM data, product geometric features, material properties, process specifications, production plans, equipment ledgers, shift schedules, and maintenance plans. For raw data with scattered sources and inconsistent formats, the module has built-in data cleaning, redundancy removal, anomaly verification, and format conversion mechanisms. It automatically completes data noise reduction, field mapping, and structure unification to form a standardized dataset that meets the requirements of simulation calculations. This provides an accurate and reliable data foundation for subsequent time-based simulations, load simulations, and load balancing optimizations, avoiding deviations in simulation results due to missing data, errors, or incompatible formats.

[0036] The knowledge base management module is configured to build a structured database for storing and managing process specifications, equipment parameters, and standard working time data. The stored content covers, but is not limited to, the operation specifications and sequence dependencies of processes such as steel plate pretreatment, CNC cutting, component welding, segmented welding, and assembly; maximum processing capacity of equipment, standard cycle time, changeover time, accuracy level, tooling compatibility type, rated load limit, and maintenance cycle; as well as size correction coefficients, material correction coefficients, and a working time benchmark library based on historical production data.

[0037] The load simulation engine module is configured to perform time calculation, time-to-equipment mapping, load rate statistics, and bottleneck identification calculation. Driven by multi-level process data and with equipment performance parameters as hard constraints, it performs full-chain process time extrapolation from parts to components to segments according to a preset time model. The calculated process times are then accurately mapped to the corresponding executing equipment according to the process route and production plan. Based on this, equipment task times are statistically analyzed according to daily, weekly, and monthly planning cycles. Combined with the theoretical available time of the equipment, real-time load rates are calculated, generating equipment load time-series curves. Simultaneously, based on preset bottleneck judgment rules, equipment and processes with loads exceeding thresholds, on critical paths, or with continuous high loads are marked, forming a bottleneck equipment list and bottleneck process distribution, providing clear targets and basis for subsequent balanced optimization. The load balancing optimization algorithm module is configured to intelligently generate equipment load balancing scheduling schemes based on optimization algorithms. Under the premise of meeting hard constraints such as process dependencies, equipment accuracy levels, tooling compatibility, and production delivery time, it intelligently adjusts the task allocation among multiple devices in the same process. Through methods such as task reassignment, process cycle time optimization, and workflow adjustment, it reduces the load difference between similar devices and improves the overall load balance. It also supports generating multiple selectable load balancing schemes based on multiple optimization objectives such as equipment utilization, production cycle, and manufacturing cost, allowing process design and production management personnel to choose the optimal solution.

[0038] The visualization verification platform is configured to display simulation results using charts and heatmaps, and supports interactive scheme adjustments. The visualization verification platform is configured to perform the following operations: The system uses a 3D visualization to display load distribution heatmaps across equipment, processes, and time dimensions, clearly presenting the equipment load status of the entire workshop, processes, and lifecycle. Equipment with load rates exceeding preset thresholds is marked in real time, and the affected downstream key processes are also marked, enabling rapid bottleneck location and transmission analysis. The system displays equipment load curves before and after load balancing optimization, the number of bottleneck equipment, the maximum load difference, and the feasibility rating comparison results side-by-side. A human-computer interaction adjustment interface is provided, allowing users to adjust production tasks, modify equipment assignment relationships, or correct production scheduling by dragging and dropping, and triggering the load simulation engine to perform real-time recalculation and scheme re-verification, achieving real-time scheme re-verification and forming an adjustment-simulation-evaluation-re-optimization-rapid iteration mechanism.

[0039] The beneficial effects achieved by the above are as follows: By displaying the load distribution of equipment, processes, and time periods in the form of a 3D heat map, users can drag and drop tasks, adjust equipment assignments, and modify production schedules through an interactive interface, triggering real-time recalculation and verification by the simulation engine, and providing specific optimization suggestions and improvement plans; it realizes digital pre-verification of process solutions in the design stage, significantly reduces the risk of adjustments after production, and provides quantitative decision support for workshop process layout optimization, equipment purchase and technical transformation, and capacity planning.

[0040] Working principle: By extracting and parsing the entire process data of the ship's hull in a structured manner, a process-equipment mapping knowledge base is constructed and equipment performance parameters are integrated. Using the production plan and product characteristics as inputs, and combined with correction coefficients, the working hours of each process are accurately calculated, and the optimal process route is selected. After accurately mapping the working hours to the corresponding equipment, the load rate is statistically analyzed periodically. Bottleneck equipment and system-level bottleneck areas are identified based on the threshold and critical path rules. Then, the minimum maximum load difference algorithm is used to optimize the task allocation of multiple equipment in the same process under process constraints. Finally, the load heat map, bottleneck early warning and comparative analysis are output through visualization, and the feasibility rating is completed, realizing the closed-loop operation of the entire process from data processing, working hour extrapolation, load simulation, bottleneck identification to load balancing and scheme verification.

[0041] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or high-voltage switchgear that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or high-voltage switchgear.

[0042] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for load simulation and balancing verification of process equipment in a ship hull integrated workshop, characterized in that, Includes the following steps: S1. Structured extraction of BOM, geometric features, material properties and process specifications of hull parts, components and sections. Structured analysis of each process link of steel pretreatment, cutting and processing, component assembly and welding and section assembly and welding, extracting process sequence, standard time coefficient, equipment type requirements and process constraints. S2. Construct a process-equipment mapping knowledge base, establish the association between each process and the set of executable equipment, and integrate equipment performance parameters; S3. Based on the production plan, phased construction sequence, and delivery requirements, combined with product size, material, and changeover time correction coefficients; using the shortest working time, lowest cost, and most balanced equipment load as comprehensive evaluation indicators, calculate the precise working time of each process, and perform parallel calculation and optimization of the working time of process route branches, automatically outputting the optimal process route and process sequence. S4. Map the calculated working hour data to the implementation equipment, accumulate the equipment task time according to the planned cycle, and generate the equipment load curve; introduce equipment availability constraints and calculate the equipment load rate. S5. For multiple machines in the same process, the minimum maximum load difference optimization algorithm is adopted to adjust the task assignment under process constraints; S6. Output load heat maps, bottleneck warnings, and optimization comparison analysis for each device; establish a feasibility rating for the solution, including three levels: feasible, critical, and infeasible, and provide optimization suggestions and improvement plans.

2. The method for load simulation and balancing verification of process equipment in the ship hull combined workshop according to claim 1, characterized in that, In S3, the formula for calculating the precise working time of each process is as follows: in, For the first The segment in the first Total working hours for each process; As the baseline working hours; , These are correction factors for size and material, respectively. Time for equipment changeover / preparation.

3. The method for load simulation and balancing verification of process equipment in the ship hull combined workshop according to claim 1, characterized in that, In S4, equipment availability constraints are introduced to calculate equipment load rate. The calculation formula is as follows: in, For equipment load factor This refers to the theoretically available working hours of the equipment during the planning period.

4. The method for load simulation and balancing verification of process equipment in the ship hull combined workshop according to claim 3, characterized in that, S4 also includes: The bottleneck is defined as: satisfying And the equipment is located in the critical path process; in, The preset threshold; When multiple machines in the same process have a load rate exceeding the threshold for three or more consecutive cycles. If so, the entire process is marked as a system-level bottleneck area.

5. The method for load simulation and balancing verification of process equipment in the ship hull combined workshop according to claim 1, characterized in that, In S5, for scenarios with multiple devices in the same process, the minimum-maximum load difference optimization algorithm is adopted, and its calculation formula is as follows: in, A collection of similar devices.

6. The method for load simulation and balancing verification of process equipment in the ship hull integrated workshop according to claim 1, characterized in that, In S1, the structured analysis includes standardized modeling of the logical relationships, sequence and parallel constraints of the entire process of steel plate pretreatment, CNC cutting, component assembly welding, and segmented assembly welding, forming a multi-path optional process network diagram; the process constraints include the pre- and post-process dependencies, equipment accuracy level limitations, tooling and fixture compatibility requirements, and time window constraints for shared equipment in multiple segments.

7. The method for load simulation and balancing verification of process equipment in the ship hull combined workshop according to claim 1, characterized in that, In S2, the equipment performance parameters include maximum processing capacity, standard cycle time, changeover preparation time, equipment accuracy level, tooling adaptation type, rated load limit and maintenance cycle. A process-equipment matching hard constraint rule library is constructed based on the equipment performance parameters.

8. The method for load simulation and balancing verification of process equipment in the ship hull integrated workshop according to claim 1, characterized in that, In S4, the planning cycle is a daily, weekly, or monthly cycle; the equipment load curve is generated with the time axis as the horizontal axis and the load rate as the vertical axis, and the equipment maintenance period, shift switching point, and replacement time window are superimposed and marked.

9. A load simulation and balancing verification system for process equipment in a ship hull integrated workshop, applied to the load simulation and balancing verification method for process equipment in a ship hull integrated workshop as described in any one of claims 1-8, characterized in that, include: The data access and preprocessing module is configured to integrate data with PLM, ERP and MES systems, and to clean, convert and standardize the acquired multi-source data. The knowledge base management module is configured to store and manage process specifications, equipment parameters, and standard working time data. The load simulation engine module is configured to perform time calculation, time-to-equipment mapping, load rate statistics, and bottleneck identification calculation. The load balancing optimization algorithm module is configured to intelligently generate equipment load balancing scheduling schemes based on optimization algorithms. The visualization verification platform is configured to display simulation results in charts and heatmaps, and supports interactive scheme adjustments.

10. The hull-integrated workshop process equipment load simulation and balancing verification system according to claim 9, characterized in that, The visual verification platform is configured to perform the following operations: A three-dimensional visual representation of the load distribution heat map is provided, considering equipment, process, and time dimensions. Equipment with a load rate exceeding a preset threshold is marked in real time, and the affected downstream key processes are also marked in conjunction with this. The system displays the equipment load curves, number of bottleneck devices, maximum load difference, and feasibility rating comparison results before and after load balancing optimization in parallel. The system provides a human-computer interaction adjustment interface, allowing users to adjust production tasks, modify equipment assignment relationships, or correct production scheduling by dragging and dropping, and triggering the load simulation engine to perform real-time recalculation and scheme re-verification.

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