A maintenance management method and device based on a digitized flowchart

Abstract

The application discloses a kind of based on digital flow chart maintenance management method and device, wherein, method includes the following steps: step S1, the system related to maintenance obtains maintenance related information, and associates the maintenance related information on digital flow chart;Step S2, based on the information associated on the flow chart and topological relationship, the maintenance influence analysis prediction of user-selected equipment to be maintained is carried out, and maintenance scheme is generated based on analysis prediction result;Step S3, the maintenance scheme is edited on the flow chart, and the flow chart of integrated maintenance management function is obtained.The application improves the efficiency and safety of maintenance management.

Description

Technical Field

[0001] This invention relates to the field of nuclear power plant maintenance management technology, and in particular to a maintenance management method and apparatus based on digital flowcharts. Background Technology

[0002] In the process of nuclear power plant maintenance management, maintenance personnel need to consult scattered work order systems, equipment files, spare parts inventory, historical maintenance records and other information to fully understand the equipment status, resulting in low information acquisition efficiency; maintenance plan preparation relies on manual experience and lacks intuitive drawings and step-by-step guidance; the scope of maintenance impact is difficult to assess quickly, which may lead to unexpected risks; maintenance experience cannot be effectively accumulated and reused; the overall efficiency and safety of maintenance management need to be improved. Summary of the Invention

[0003] In view of this, it is necessary to provide a maintenance management method and device based on digital flowcharts to effectively solve the technical problems of low efficiency and low safety in nuclear power maintenance management.

[0004] This invention provides a maintenance management method based on digital flowcharts, comprising the following steps: Step S1: Connect with maintenance-related systems to obtain maintenance-related information, and associate the maintenance-related information with the digital flowchart; Step S2: Based on the information and topological relationships associated with the flowchart, perform maintenance impact analysis and prediction on the user-selected equipment to be repaired, and generate a maintenance plan based on the analysis and prediction results; Step S3: Edit the maintenance plan on the flowchart to obtain a flowchart of integrated maintenance management functions.

[0005] Preferably, step S1 specifically comprises: The system integrates with the work order system, equipment management system, spare parts inventory system, and historical database to obtain work order information, equipment file information, spare parts information, and maintenance history information. These are used as maintenance-related information. Based on the equipment code, the maintenance-related information is associated with the equipment elements on the flowchart.

[0006] Preferably, step S1 further includes visualizing the maintenance-related information on the flowchart: The maintenance-related information includes work order information, equipment file information, spare parts information, and maintenance history information. A work order icon is displayed at the relevant equipment element in the work order information; maintenance frequency information is displayed at the maintenance equipment element; if the inventory of required spare parts is lower than a safety threshold, an inventory warning icon is displayed at the corresponding equipment element, and the corresponding spare parts information is associated; a maintenance document icon is displayed at the maintenance equipment element, and the corresponding maintenance document is associated; the maintenance history distribution is displayed on the drawing: the maintenance history distribution is displayed as a timeline trajectory, and the maintenance history is displayed in chronological order on the timeline; equipment elements of different maintenance types are classified and labeled to reflect the distribution of maintenance types; all areas of the flowchart are divided into grids, the total number of maintenance visits for equipment in each grid is counted, a heatmap overlay is generated, and displayed on the flowchart.

[0007] Preferably, step S1 further includes performing maintenance history analysis based on maintenance history information: Generate a line graph showing the number of equipment repairs over time, and identify periodic failures or aging trends of the equipment based on the line graph; calculate the average repair interval for equipment of the same model, set a threshold based on the average repair interval, and issue warnings for equipment with a repair frequency higher than the threshold; summarize the historical failure phenomena of the equipment, sort the various historical failure phenomena by frequency, generate a fault word cloud, and assist users in fault diagnosis.

[0008] Preferably, step S2 specifically comprises: The analysis and prediction include process impact analysis, production impact analysis, and schedule prediction. Process impact analysis involves identifying upstream and downstream equipment of the equipment to be maintained as isolated devices based on the equipment connection relationships in the flowchart, assessing the impact of maintenance on system operation based on the maintained equipment and isolated devices, and providing corresponding maintenance recommendations. Production impact analysis involves assessing the impact level of maintenance on unit power and safety functions based on the system where the maintained equipment is located, and providing maintenance window recommendations based on the current unit status. Schedule prediction involves calculating the average time for similar maintenance based on historical maintenance data, and predicting the schedule based on the original total schedule and the average time for similar maintenance. The repair plan is generated based on the repair suggestions predicted by the analysis.

[0009] Preferably, step S3 specifically comprises: The repair plan includes repair annotations, multimedia attachments, and repair steps. A repair annotation tool is set on the flowchart to annotate corresponding graphic elements. Relevant multimedia attachments are associated with the repair equipment graphic elements. Repair steps are annotated on the flowchart, and each repair step is associated with a corresponding graphic element. The repair plan is saved as a template, and a template library is established to manage the repair plan templates. Based on the equipment type and fault symptoms, a corresponding template is matched in the template library, and adjustments are made based on the corresponding template to generate the repair plan.

[0010] Preferably, the method further includes intelligent spare parts recommendation based on the flowchart of the integrated maintenance management project. This intelligent spare parts recommendation includes BOM-based recommendation, history-based recommendation, similar equipment-based recommendation, and intelligent combination recommendation. The BOM-based recommendation involves extracting a spare parts list from the equipment master data and listing all spare parts as recommended spare parts. The history-based recommendation involves statistically analyzing the spare parts actually used in historical maintenance of similar faults and recommending them according to usage frequency. The similar equipment-based recommendation involves referencing the maintenance history of other equipment of the same model if the equipment being repaired has no maintenance history. The intelligent combination recommendation involves recommending spare parts combinations based on the maintenance type. The system checks the inventory of recommended spare parts and sends the inventory information back to the user, providing reminders when inventory is low. After maintenance is completed, the system automatically records the actual amount of spare parts consumed, which is used to optimize subsequent spare parts recommendations and inventory management.

[0011] Preferably, this also includes maintenance execution tracking and feedback: During the execution of a maintenance work order, the flowchart is linked with the work order system. The work order icon for the corresponding device on the flowchart is automatically updated according to the change of work order status. Completed maintenance steps are marked, and the completion time and personnel are automatically recorded. Problems encountered during the execution of the maintenance work order are marked and reported, and supplementary work orders are generated. After the maintenance is completed, user experience feedback information is collected.

[0012] Preferably, it also includes: establishing a maintenance knowledge base to structure and store experience feedback, maintenance plans, and precautions from previous maintenance operations; querying and recommending historical maintenance records and experience feedback based on the maintenance knowledge base; assisting in fault diagnosis and pushing relevant information about the same model of equipment based on the maintenance knowledge base; and calculating the number of times each piece of maintenance knowledge is viewed and the adoption rate to achieve an effectiveness evaluation of maintenance knowledge. Based on the maintenance knowledge base, multi-dimensional maintenance statistical reports are generated, including equipment-dimensional maintenance statistical reports, system-dimensional maintenance statistical reports, time-dimensional maintenance statistical reports, and personnel-dimensional maintenance statistical reports.

[0013] The present invention also provides a maintenance management device based on a digital flowchart, including a memory and a processor. The memory stores a computer program, and when the computer program is executed by the processor, it implements the maintenance management method based on the digital flowchart.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention uses digital flowcharts as the core carrier to gather maintenance-related information into a unified view, supports the editing of maintenance plans and intelligent analysis of the scope of maintenance impact, and comprehensively improves the efficiency and safety of maintenance management. Attached Figure Description

[0015] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings: Figure 1 This is a flowchart of an embodiment of a maintenance management method based on digital flowcharts provided by the present invention. Detailed Implementation

[0016] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0017] Example 1

[0018] Please see Figure 1 The maintenance management method based on digital flowcharts in this embodiment specifically includes the following steps: Step S1: Connect with maintenance-related systems to obtain maintenance-related information, and associate the maintenance-related information with the digital flowchart; Step S2: Based on the information and topological relationships associated with the flowchart, perform maintenance impact analysis and prediction on the user-selected equipment to be repaired, and generate a maintenance plan based on the analysis and prediction results; Step S3: Edit the maintenance plan on the flowchart to obtain a flowchart of integrated maintenance management functions.

[0019] Each step is explained in detail below.

[0020] Step S1: Maintenance Information Integration and Visualization. Integrate with the work order system, Equipment Management System (EAM), Spare Parts Inventory System (ERP), and historical database to obtain equipment-related maintenance information. This includes work order information, equipment file information, spare parts information, and maintenance history information. Work order information includes ongoing work orders and historical work orders. Ongoing work orders include those under maintenance and those awaiting maintenance. Historical work order information includes maintenance records, fault symptoms, and corrective actions. Equipment files include equipment model, serial number, installation date, design life, and maintenance manual. Spare parts information includes spare parts code, name, specifications, current inventory, storage location, and transit status. Maintenance history includes the time of each maintenance, maintenance type, maintenance personnel, and maintenance duration. Maintenance types include preventative, corrective, and overhaul.

[0021] The above information is visualized and annotated on the digital flowchart. Work order status indicators: a work order icon is displayed in the upper left corner of the equipment; for example, a yellow wrench indicates an ongoing work order, and gray indicates no work order. Clicking on the icon allows viewing work order details. Maintenance history heatmap: heat points of different colors are displayed next to the equipment based on maintenance frequency: red = high-frequency maintenance, yellow = medium-frequency, green = low-frequency. Spare parts inventory warning: if the required spare parts inventory is below the safety threshold, an inventory warning icon is displayed next to the equipment; clicking on it allows viewing spare parts details. Maintenance document links: document icons are displayed next to the equipment; clicking on them directly opens the equipment's maintenance manual, operating procedures, etc. The maintenance history distribution of the equipment is displayed on the drawing in the form of a "maintenance trajectory," including a timeline trajectory, maintenance type distribution, and a maintenance frequency heatmap. The timeline trajectory displays small dots around the equipment in chronological order; each dot represents a maintenance operation, and hovering the mouse displays the maintenance time, work order number, and a brief description of the fault. The maintenance type distribution uses different colored dots to represent different maintenance types: red = corrective maintenance, blue = preventative maintenance, and green = overhaul. The maintenance frequency heatmap divides the drawing area into grids, counts the total number of maintenance visits for equipment within each grid, and generates a heatmap overlay to visually display high-frequency maintenance areas.

[0022] Furthermore, this embodiment also provides maintenance history analysis tools, including trend analysis, comparison with similar equipment, and failure mode analysis. Trend analysis generates a line graph showing the number of equipment maintenance visits over time, identifying periodic failures or aging trends. Comparison with similar equipment statistically analyzes the average maintenance interval of equipment of the same model; if the maintenance frequency of a certain piece of equipment is significantly higher than that of similar equipment, it suggests a possible design flaw or special operating conditions. Failure mode analysis summarizes the historical failure phenomena of the equipment, sorts them by frequency, and generates a fault word cloud to assist in diagnosis.

[0023] Step S2: Intelligent Analysis of Maintenance Impact Scope. When the user selects the equipment to be maintained, or selects multiple devices, the system automatically performs an impact scope analysis based on the topology of the drawings, including process impact analysis, production impact analysis, and schedule prediction. Process impact analysis identifies upstream and downstream devices that need to be isolated due to maintenance based on equipment connection relationships, and assesses the impact of maintenance on system operation; for example, "Maintaining this pump will cause a 30% decrease in RCV system flow; it is recommended to switch to the standby pump." If the equipment to be maintained is critical, such as safety-grade equipment, the system prompts that a special approval process is required. Production impact analysis assesses the impact level of maintenance on unit power and safety functions based on the system in which the equipment is located; combined with the current unit status, such as full power, reduced power, or shutdown, it provides suggested maintenance windows. Schedule prediction predicts the time required for this maintenance based on historical maintenance data, such as "According to historical records, similar maintenance takes an average of 4.5 hours"; if multiple devices are involved, the system automatically calculates the total schedule and identifies the parts that can be operated in parallel.

[0024] The impact analysis results are displayed visually: affected areas are highlighted with semi-transparent color blocks, and the shade of the color represents the degree of impact; critical equipment affected is marked with special icons, such as red exclamation marks; an impact analysis report is generated and can be exported as a work order attachment.

[0025] Step S3: Visual Editing and Template-Based Maintenance Plans. A dedicated maintenance plan editing tool is provided, supporting direct creation of maintenance plans on drawings, including maintenance annotations, multimedia attachments, and maintenance steps. Maintenance annotation tools include: weld annotation (marking weld locations on pipelines and allowing input of weld numbers and inspection requirements); support and hanger annotation (annotating maintenance requirements and adjustment parameters on support and hanger elements); disassembly sequence annotation (using numerical sequences to indicate disassembly steps, such as 1-remove bolts, 2-lift pump body); and risk point annotation (marking warning signs in hazardous areas and filling in precautions). Multimedia attachments support uploading on-site photos, operation videos, and manufacturer manuals, linked to drawing elements; clicking icons allows viewing. Step arrangement displays maintenance steps in list format, with drag-and-drop functionality to adjust the order; each step can be linked to annotated elements on the drawing.

[0026] The system features templated maintenance plans, allowing users to create and save commonly used maintenance plans such as "centrifugal pump overhaul" and "valve packing replacement" as templates, complete with annotations, steps, and attachments. A template library is also available, categorizing templates by equipment type and supporting preview, editing, and version management. For new equipment maintenance, users can select a template to generate an initial plan with a single click, then fine-tune it based on the actual situation. Finally, intelligent template recommendation automatically suggests the most suitable template based on equipment type and fault symptoms.

[0027] Furthermore, this embodiment also includes intelligent spare parts recommendation and inventory linkage. Based on equipment information and maintenance needs, the system intelligently recommends required spare parts. Based on BOM (Bill of Materials) recommendation, the spare parts list BOM is extracted from the equipment master data, listing all potentially needed spare parts. Based on historical recommendation, the system statistically analyzes the spare parts actually used in historical maintenance of similar faults and recommends them in order of usage frequency. Based on similar equipment recommendation, if this equipment has no maintenance history, spare parts are recommended by referring to the maintenance records of other equipment of the same model. Intelligent combination recommendation suggests spare parts combinations based on the maintenance type; for example, "overhaul" recommends a complete set of seals, bearings, and lubricating oil.

[0028] Real-time inventory query and alerts: The spare parts list directly displays the current inventory quantity, in-transit quantity, and storage location (i.e., warehouse shelf number); when inventory is low, it automatically highlights an alert and provides alternative spare parts suggestions or procurement links; it supports one-click generation of spare parts requisition applications, automatically filling in equipment code, spare parts code, and quantity. Spare parts consumption tracking: After maintenance is completed, the system automatically records the actual spare parts consumed for optimizing subsequent recommendations and inventory management.

[0029] Furthermore, this embodiment also includes maintenance execution tracking and feedback. During the execution of a maintenance work order, the drawings and the work order system are linked in real time, including status synchronization, step tracking, and problem reporting. Status synchronization: When the work order status changes, such as assigned, in progress, or completed, the corresponding work order icon on the drawing is automatically updated. Step tracking: Maintenance personnel can check completed steps on the drawing, and the system records the completion time and personnel. Problem reporting: If problems are found during execution, such as additional damage, a new annotation can be added to the drawing, and a supplementary work order can be generated. After the maintenance is completed, the system guides the user to fill in experience feedback: the system automatically extracts work order information, including equipment, fault, and handling measures; the user only needs to add "lessons learned from this maintenance" and "precautions"; it supports uploading on-site photos and photos of faulty parts as attachments; experience feedback is associated with equipment and fault type and stored in the knowledge base.

[0030] Furthermore, this embodiment also includes maintenance knowledge accumulation and intelligent push notifications. A maintenance knowledge base is established, storing structured feedback, solutions, and precautions from each maintenance operation. The maintenance knowledge base consists of two parts: knowledge entries and a knowledge index. Each knowledge entry includes the equipment type, fault symptoms, cause analysis, handling measures, required spare parts, precautions, and accessories. The knowledge index is built according to equipment code, fault code, and keywords, supporting rapid retrieval.

[0031] Intelligent knowledge push: Before maintenance, the system automatically pushes historical maintenance records and relevant experience feedback for a device when the user views it for maintenance; Fault diagnosis assistance: The system searches for similar cases and recommends possible causes and solutions when the user inputs the fault symptoms; Similar device push: When the user is dealing with a fault in a device, the system pushes common problems and solutions for other devices of the same model.

[0032] Knowledge effectiveness assessment records the number of times each piece of knowledge is viewed and the adoption rate. Knowledge value is evaluated regularly, and low-value knowledge is marked as pending review.

[0033] Furthermore, this embodiment also includes maintenance statistics and report generation. Various maintenance statistical reports are automatically generated, supporting multi-dimensional analysis. Equipment-level reports include maintenance frequency, average maintenance interval, and common fault types for each device. System-level reports show maintenance distribution and maintenance cost statistics for each system. Time-level reports show monthly / quarterly maintenance trends and maintenance distribution during major overhauls. Personnel-level reports show maintenance personnel workload statistics and average processing time. Reports are displayed in visual charts, such as bar charts, pie charts, and line charts, and can be exported to Excel / PDF. Anomaly alarms are also included; when the maintenance frequency of a device exceeds a preset threshold, the system automatically issues an alarm, prompting a focus on the issue.

[0034] Compared with existing technologies, this embodiment offers one-stop information integration, allowing maintenance personnel to access all equipment maintenance-related information directly from the drawings without switching between multiple systems, thus improving efficiency. Intelligent impact assessment automatically analyzes the impact of maintenance on processes and production, identifying risks in advance and preventing accidents. Standardized solution preparation, with visual annotations and templates, ensures complete and standardized maintenance plans, reducing omissions. Precise spare parts management, with intelligent recommendations and real-time inventory linkage, reduces spare parts waiting time and avoids inventory backlog. Reusable experience accumulation, with a knowledge base and intelligent push mechanism, transforms personal experience into organizational assets, shortening the training cycle for new employees. Data-driven decision support, with multi-dimensional statistical reports providing data support for maintenance strategy optimization, enables the evolution from preventative maintenance to predictive maintenance.

[0035] The following example, taking the preventive maintenance of pump P001 in the RCV system of a nuclear power plant as an example, will further illustrate this embodiment.

[0036] Scenario 1: Preparation before maintenance. The maintenance personnel log into the system and open the RCV system digital flowchart. A blue wrench icon appears next to pump P001 on the drawing, indicating that there is a preventive maintenance work order. Click the icon to view the work order details: Work order number "PM-2025-0123", maintenance type "preventive maintenance", content "replace lubricating oil, check bearing".

[0037] The drawing shows historical maintenance dots around pump P001: 2 red dots indicate corrective maintenance, and 5 green dots indicate preventative maintenance. Hovering the mouse over the last maintenance record shows: October 15, 2024, bearing replacement, taking 3 hours.

[0038] The system automatically performs an impact analysis: a prompt appears stating, "Maintaining this pump will cause a 30% decrease in RCV system flow. It is recommended to switch to the standby pump P002. The estimated maintenance time is 4.5 hours (based on historical data)." After confirmation by the maintenance personnel, the system highlights the standby pump P002 and the switching valve.

[0039] Scenario 2: Maintenance Plan Preparation. Maintenance personnel click "Prepare Maintenance Plan" to enter the plan editing mode. The system automatically recommends a "Centrifugal Pump Preventive Maintenance Template," which includes the following standard steps: Step 1, Close pump inlet valve V001; Step 2, Close pump outlet valve V002; Step 3, Power off and tag the pump; Step 4, Drain the pump medium; Step 5, Replace the lubricating oil; Step 6, Inspect the bearings; Step 7, Restore.

[0040] The maintenance personnel adjusted the procedure based on the actual situation: After step 5, add "Record the lubricant type and dosage" and upload the lubricant specification sheet as an attachment. Mark the risk points on the drawings: Draw a red cloud line around the pump body and add the label "High-temperature component, beware of burns".

[0041] Scenario 3, Spare Parts Preparation. The system automatically recommends the following spare parts: Lubricating oil (model: ISO VG 46), stock: 15L, safety threshold: 10L, location: warehouse A-12; bearing spare part (model: SKF 6308), stock: 2, safety threshold: 3, warning yellow. When maintenance personnel click on the bearing spare part warning, the system suggests, "Insufficient stock, it is recommended to requisition 2, with the remaining 1 for emergency use." A requisition form is generated with one click, automatically filling in equipment code P001, spare part code, and quantity 2.

[0042] Scenario 4: Execution and Feedback. Maintenance personnel execute the procedure on-site, opening the maintenance plan via a mobile device and selecting each step to complete. The system records the completion time for each step. During execution, a minor leak is discovered at the pump inlet flange. The maintenance personnel take photos on-site and upload them, adding a note to the drawings: "Flange leak, recommended for future maintenance," and generating a supplementary work order. After maintenance is completed, the system prompts for feedback. The maintenance personnel input, "When changing lubricating oil, ensure the old oil is completely drained to avoid mixing different brands," and associate it with equipment P001.

[0043] Scenario 5: Knowledge Accumulation. Three months later, another maintenance technician prepared to repair pump P003 of the same model. When opening the drawings, the system automatically pushed experience feedback: "Note: When changing the lubricating oil, the old oil must be completely drained to avoid mixing different brands." The maintenance technician adopted the suggestion and successfully completed the repair.

[0044] Scenario 6: Statistical Analysis. At the end of the quarter, managers reviewed maintenance statistics reports and found an increase in the maintenance frequency of pumps in the RCV system, with bearing failures accounting for 60% of the cases. The system suggested analyzing bearing life and considering upgrading the bearing model. Based on this, managers arranged a special analysis and optimized maintenance strategies.

[0045] Example 2

[0046] This embodiment provides a maintenance management device based on a digital flowchart, including a memory and a processor. The memory stores a computer program, and when the computer program is executed by the processor, it implements the maintenance management method based on a digital flowchart as described in Embodiment 1.

[0047] The maintenance management device based on digital flowcharts provided in this embodiment is used to implement the maintenance management method based on digital flowcharts. Therefore, the maintenance management device based on digital flowcharts also has the same technical effects as the maintenance management method based on digital flowcharts, which will not be described again here.

[0048] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of the present invention.

Claims

1. A maintenance management method based on digital flowcharts, characterized in that, Includes the following steps: Step S1: Connect with maintenance-related systems to obtain maintenance-related information, and associate the maintenance-related information with the digital flowchart; Step S2: Based on the information and topological relationships associated with the flowchart, perform maintenance impact analysis and prediction on the user-selected equipment to be repaired, and generate a maintenance plan based on the analysis and prediction results; Step S3: Edit the maintenance plan on the flowchart to obtain a flowchart of integrated maintenance management functions.

2. The maintenance management method based on digital flowcharts according to claim 1, characterized in that, Step S1 specifically involves: The system integrates with the work order system, equipment management system, spare parts inventory system, and historical database to obtain work order information, equipment file information, spare parts information, and maintenance history information. These are used as maintenance-related information. Based on the equipment code, the maintenance-related information is associated with the equipment elements on the flowchart.

3. The maintenance management method based on digital flowcharts according to claim 1, characterized in that, Step S1 further includes visualizing the maintenance-related information on the flowchart: The maintenance-related information includes work order information, equipment file information, spare parts information, and maintenance history information. A work order icon is displayed at the relevant equipment element in the work order information; maintenance frequency information is displayed at the maintenance equipment element; if the inventory of required spare parts is lower than a safety threshold, an inventory warning icon is displayed at the corresponding equipment element, and the corresponding spare parts information is associated; a maintenance document icon is displayed at the maintenance equipment element, and the corresponding maintenance document is associated; the maintenance history distribution is displayed on the drawing: the maintenance history distribution is displayed as a timeline trajectory, and the maintenance history is displayed in chronological order on the timeline; equipment elements of different maintenance types are classified and labeled to reflect the distribution of maintenance types; all areas of the flowchart are divided into grids, the total number of maintenance visits for equipment in each grid is counted, a heatmap overlay is generated, and displayed on the flowchart.

4. The maintenance management method based on digital flowcharts according to claim 1, characterized in that, Step S1 further includes performing maintenance history analysis based on maintenance history information: Generate a line graph showing the number of equipment repairs over time, and identify periodic failures or aging trends of the equipment based on the line graph; calculate the average repair interval for equipment of the same model, set a threshold based on the average repair interval, and issue warnings and reminders for equipment with a repair frequency higher than the threshold; The system summarizes historical fault phenomena of the equipment, sorts them by frequency, generates a fault word cloud, and assists users in fault diagnosis.

5. The maintenance management method based on digital flowcharts according to claim 1, characterized in that, Step S2 specifically involves: The analysis and prediction include process impact analysis, production impact analysis, and schedule prediction. Process impact analysis involves identifying upstream and downstream equipment of the equipment to be maintained as isolated devices based on the equipment connection relationships in the flowchart, assessing the impact of maintenance on system operation based on the maintained equipment and isolated devices, and providing corresponding maintenance recommendations. Production impact analysis involves assessing the impact level of maintenance on unit power and safety functions based on the system where the maintained equipment is located, and providing maintenance window recommendations based on the current unit status. Schedule prediction involves calculating the average time for similar maintenance based on historical maintenance data, and predicting the schedule based on the original total schedule and the average time for similar maintenance. The repair plan is generated based on the repair suggestions predicted by the analysis.

6. The maintenance management method based on digital flowcharts according to claim 1, characterized in that, Step S3 specifically involves: The repair plan includes repair annotations, multimedia attachments, and repair steps; a repair annotation tool is set on the flowchart to annotate the corresponding graphic elements; relevant multimedia attachments are associated with the repair equipment graphic elements; repair steps are annotated on the flowchart, and each repair step is associated with a corresponding graphic element; The repair plan is saved as a template, and a template library is established to manage the repair plan templates. According to the equipment type and fault symptoms, the corresponding template is matched in the template library, and the repair plan is generated after adjustment based on the corresponding template.

7. The maintenance management method based on digital flowcharts according to claim 1, characterized in that, It also includes intelligent spare parts recommendation based on the flowchart of the integrated maintenance management project. The intelligent spare parts recommendation includes BOM-based recommendation, historical recommendation, similar equipment-based recommendation, and intelligent combination recommendation. The BOM recommendation is: extracting a spare parts list from the equipment master data and listing all spare parts as recommended spare parts. The history-based recommendation involves: statistically analyzing the actual spare parts used in historical repairs of similar faults and recommending them in order of usage frequency; the similar equipment-based recommendation involves: if the equipment being repaired has no repair history, recommending spare parts by referring to the repair history of other equipment of the same model; the intelligent combination recommendation involves: recommending spare parts combinations based on the repair type. Check the inventory of recommended spare parts and provide feedback on the spare parts inventory to the user, and remind them when the inventory is low; After maintenance is completed, the actual consumption of spare parts is automatically recorded to optimize subsequent spare parts recommendations and inventory management.

8. The maintenance management method based on digital flowcharts according to claim 1, characterized in that, This also includes maintenance execution tracking and feedback: During the execution of a maintenance work order, the flowchart is linked with the work order system. The work order icon for the corresponding device on the flowchart is automatically updated according to the change of work order status. Completed maintenance steps are marked, and the completion time and personnel are automatically recorded. Problems encountered during the execution of the maintenance work order are marked and reported, and supplementary work orders are generated. After the maintenance is completed, user experience feedback information is collected.

9. The maintenance management method based on digital flowcharts according to claim 1, characterized in that, It also includes establishing a maintenance knowledge base to structure and store experience feedback, maintenance plans, and precautions from previous maintenance operations; querying and recommending historical maintenance records and experience feedback based on the maintenance knowledge base; and assisting in fault diagnosis and pushing relevant information about the same model of equipment based on the maintenance knowledge base. The effectiveness of maintenance knowledge can be evaluated by tracking the number of views and adoption rate of each piece of maintenance knowledge. Based on the maintenance knowledge base, multi-dimensional maintenance statistical reports are generated, including equipment-dimensional maintenance statistical reports, system-dimensional maintenance statistical reports, time-dimensional maintenance statistical reports, and personnel-dimensional maintenance statistical reports.

10. A maintenance management device based on a digital flowchart, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, which, when executed by the processor, implements the maintenance management method based on a digital flowchart as described in any one of claims 1-9.

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