An intelligent terminal-based maintenance safety quality improvement method and system

Abstract

The present application belongs to the technical field of nuclear power maintenance, and particularly relates to a method and system for improving maintenance safety and quality based on a smart terminal. The method comprises the following steps: step one, setting digital quality control points; step two, intelligent evaluation of maintenance effect and real-time monitoring of quality indicators; step three, standardization and standardized management of the whole maintenance process; step four, intelligent quality feedback and improvement feedback; step five, mandatory execution of quality standards; step six, intelligent quality inspection and verification; step seven, intelligent risk assessment and control; step eight, establishment of safety training and knowledge base; and step nine, advanced maintenance safety management. The beneficial effects are as follows: the setting of digital quality control points can guide maintenance personnel to perform necessary checks and confirmations at key steps, ensuring that the maintenance quality meets the requirements. The intelligent evaluation of maintenance effect and monitoring of quality indicators can improve the reliability and continuous improvement of maintenance quality.

Description

Technical Field

[0001] This invention belongs to the field of nuclear power maintenance technology, specifically relating to a method and system for improving maintenance safety and quality based on a smart terminal. Background Technology

[0002] Traditional paper-based work packages and procedures have the following limitations when implemented on-site in nuclear power plant maintenance: Setting up quality control points is difficult: paper-based procedures cannot enforce effective quality inspection and witnessing points at specific stages, and quality control relies on the self-discipline of personnel, making it easy to overlook key confirmation steps.

[0003] Lack of performance evaluation and indicator monitoring: Data such as operation time, resource consumption, and equipment status during the maintenance process are recorded in paper forms, making it difficult to summarize in real time, analyze trends, and evaluate performance.

[0004] Inconsistent execution of standardized procedures: Maintenance procedures rely on personnel experience, and different teams may perform the same task differently, affecting maintenance consistency and quality stability.

[0005] Delayed quality feedback loop: Information such as maintenance reports, on-site feedback, and temporary modification records is transmitted slowly, making it difficult to form a rapid and effective improvement loop.

[0006] Inadequate implementation of quality standards: The standard requirements in paper-based regulations are merely textual descriptions, lacking mandatory guidance and verification mechanisms.

[0007] The quality inspection and verification methods are limited: witnessing of key steps relies on human presence, and there is insufficient remote technical support and automated verification capabilities.

[0008] Insufficient risk assessment and control capabilities: Potential risks in maintenance tasks need to be identified manually, and there is a lack of systematic risk assessment models and dynamic early warning mechanisms.

[0009] Inconvenient access to safety training and knowledge: Safety training materials are scattered, making it difficult for maintenance personnel to obtain targeted safety knowledge and operating procedures on-site.

[0010] Safety management measures are not implemented effectively: there is a lack of follow-up and mandatory reminders regarding the implementation of safety management requirements such as personal protective equipment inspection, environmental monitoring, and emergency response.

[0011] In summary, the traditional paper-based work packages and procedures suffer from weaknesses in quality control, low data utilization, poor process rigidity, and delayed feedback. Therefore, there is an urgent need for a maintenance safety and quality improvement system and method based on smart terminals to overcome the limitations of the traditional model and improve the safety and quality of maintenance work. Summary of the Invention

[0012] The purpose of this invention is to provide a method and system for improving maintenance safety and quality based on smart terminals, which can solve the quality problems existing in maintenance management using traditional paper work packages and paper procedures, realize digital control of the maintenance process, and improve the safety and quality level of maintenance.

[0013] The technical solution of the present invention is as follows: A method for improving maintenance safety and quality based on a smart terminal, comprising the following steps: Step 1: Setting up digital quality control points; Step Two: Intelligent evaluation of repair effectiveness and real-time monitoring of quality indicators; Step 3: Standardize and regulate the entire maintenance process; Step 4: Intelligent quality feedback and improvement feedback; Step 5: Enforce quality standards; Step Six: Intelligent Quality Inspection and Verification; Step Seven: Intelligent Risk Assessment and Control; Step 8: Establish safety training and knowledge base; Step Nine: Advanced Maintenance and Safety Management; Record the safety requirements, protective measures, and emergency plans for each maintenance task, and provide real-time reminders and supervision during the execution process.

[0014] Step one includes automatically inserting digital quality control points according to a preset maintenance process, defining the inspection content, standards, and witnessing requirements for each quality control point, and prompting maintenance personnel to confirm and record in real time during the maintenance process. The data includes step number, inspection item, standard value, actual value, inspection time, and personnel information. The data integrity is automatically verified and uploaded to the cloud platform database.

[0015] Step two includes collecting real-time data during the maintenance process, including operation time, resource consumption, equipment status, and inspection results, conducting effect evaluation and quality index calculation, supporting the setting of thresholds and trend analysis, automatically triggering early warnings for abnormal data, comparing evaluation results with historical data, and generating a quality report.

[0016] Step three includes the platform establishing a standard maintenance process library. Each process includes a sequence of steps, a tool list, safety requirements, and quality milestones. When a maintenance task is started, the corresponding process is automatically matched and loaded to ensure consistent execution.

[0017] Step four includes collecting maintenance reports, user feedback, and temporary modification records, extracting key information through text analysis and data processing modules, and forming improvement suggestions.

[0018] Step five includes a built-in quality standard library, including operating procedures, safety regulations, and checklists. During the maintenance process, relevant standards are automatically retrieved and displayed according to the current step, and operations that do not meet the standards are intercepted or warned until the correction is completed.

[0019] Step six includes real-time acquisition of maintenance site images, videos, and environmental data through cameras and sensors, automatic checking of the execution of key steps, comparison with standards, real-time uploading of verification results, and support for remote expert witnessing.

[0020] Step seven includes a built-in risk assessment model that automatically identifies potential risks based on maintenance task type, equipment status, environmental conditions, and personnel qualifications, and pushes control measures and protection suggestions. Risk data is linked with maintenance records to form a risk knowledge base.

[0021] Step eight includes a terminal-integrated security training module that provides video, text, and simulated operation information. Maintenance personnel can learn and be assessed independently according to task requirements. The knowledge base is updated in real time and supports intelligent retrieval and push notifications.

[0022] A maintenance safety and quality improvement system based on smart terminals includes: a digital quality control point setting module, a maintenance effect intelligent evaluation and quality indicator monitoring module, a full maintenance process standardization and specification management module, an intelligent quality feedback and improvement module, a mandatory quality standard enforcement module, a quality intelligent inspection and verification module, an intelligent risk assessment and control module, a safety training and knowledge base module, and an advanced maintenance safety management module. The digital quality control point setting module is used to set digital quality control points at specific stages of the maintenance process, define the requirements and standards for quality control points, guide and force maintenance personnel to perform necessary and effective checks and confirmations at key steps, and ensure that the maintenance quality meets the requirements. The intelligent evaluation and quality indicator monitoring module for maintenance effectiveness is used to intelligently evaluate maintenance effectiveness and monitor quality indicators in real time, collect and analyze relevant data of maintenance tasks, understand the performance and quality of maintenance work, and take corresponding measures to improve the reliability and continuous improvement of maintenance quality. The standardization and regulation management module for the entire maintenance process is used to promote the standardization and regulation of the maintenance process, formulate and manage standardized maintenance procedures and processes, ensure that the execution of maintenance tasks conforms to standards and regulations, improve the consistency and quality of maintenance tasks, and promote continuous improvement and optimization of maintenance. The intelligent quality feedback and improvement module is used to collect quality feedback and opinions during the maintenance process, organize and analyze them, formulate improvement actions, promote continuous optimization of quality management, and carry out intelligent closed-loop feedback management. The mandatory quality standard module is used to enforce quality standards and requirements. It has built-in quality standards and specifications to ensure that maintenance personnel follow the standards and specifications during the execution process. By enforcing the standards, human factors and arbitrariness are reduced, and the consistency and quality stability of maintenance are improved. The intelligent quality inspection and verification module is used to guide personnel, monitor and record quality inspection and verification during the maintenance process in real time, and require witnesses to inspect and verify key points to ensure that the maintenance work meets the prescribed quality requirements, reduce quality problems and correct unqualified maintenance work. The intelligent risk assessment and control module is used to conduct risk assessment and control according to the risk management requirements in the digital procedure, identify and assess potential risks in maintenance tasks, and provide corresponding control measures and protection suggestions. The safety training and knowledge base module is used to enhance safety awareness and knowledge levels, and to learn about the latest safety requirements and operating procedures by accessing safety training materials; The advanced maintenance safety management module is used for maintenance safety management, recording and managing the safety requirements and measures for maintenance tasks, including personal protective equipment, work environment safety, and emergency response, and implementing these safety requirements and measures into specific intelligent execution steps and reminders.

[0023] The beneficial effects of this invention are as follows: 1. Digital quality control point settings guide maintenance personnel to perform necessary checks and confirmations at key steps, ensuring that maintenance quality meets requirements. 2. Intelligent evaluation of maintenance results and monitoring of quality indicators improve the reliability and continuous improvement of maintenance quality. 3. Standardization and standardized management of the entire maintenance process promotes continuous improvement and optimization of maintenance. 4. Intelligent quality feedback and improvement promote continuous optimization of quality management. 5. Enforcing quality standards reduces human factors and arbitrariness, improving the consistency and stability of maintenance quality. 6. Intelligent quality inspection and verification reduces quality problems and corrects non-conforming maintenance work. 7. Intelligent risk assessment and control reduces the occurrence of accidents and injuries, improving the inherent safety of maintenance. 8. Safety training and knowledge base enhance the safety awareness and capabilities of maintenance personnel. 9. Advanced maintenance safety management improves the safety of maintenance work and protects the safety of maintenance personnel and equipment. Attached Figure Description

[0024] Figure 1 A flowchart for setting up digital quality control points; Figure 2 A schematic diagram of the intelligent evaluation of maintenance results and intelligent monitoring of quality indicators. Figure 3 This is a schematic diagram of an embodiment of the present invention; Figure 4 A schematic diagram illustrating the standardized and regulated management process for the entire maintenance process; Figure 5 This is a schematic diagram of the intelligent quality feedback and improvement process; Figure 6 A schematic diagram illustrating the process for enforcing quality standards; Figure 7 A schematic diagram of the intelligent quality inspection and verification process; Figure 8 This is a schematic diagram of the intelligent risk assessment and control process; Figure 9 A flowchart illustrating the process of establishing a safety training and knowledge base; Figure 10 This is a schematic diagram of the advanced maintenance safety management process. Detailed Implementation

[0025] The technical solution of the present invention will be fully described below: The present invention provides a method and system for improving maintenance safety and quality based on smart terminals. Its core idea is to establish a digital management and control system covering the entire maintenance process, and to transform traditional paper work packages into digital, controllable and traceable intelligent maintenance processes through smart terminals.

[0026] This invention uses smart terminals as the core entry point for data collection and process execution, connecting upwards to a cloud management platform to obtain standard procedures and configurations, and downwards to the maintenance site for operation execution. The system manages the execution procedures of various maintenance tasks uniformly through a standard maintenance process library, enforces key steps through digital quality control points, achieves quantitative evaluation of maintenance quality through an effectiveness evaluation model, and automatically identifies and prevents potential risks through a risk assessment model.

[0027] Specifically, the technical solution of the present invention revolves around the following five aspects: First, we will establish a digital standard maintenance process library to transform paper procedures into structured data, thereby achieving standardized and version-based management of maintenance processes and ensuring consistency when different work teams perform the same task.

[0028] Secondly, by using digital quality control points and intelligent inspection and verification methods, mandatory inspection and confirmation steps are set up in key maintenance procedures. Combined with image recognition and remote expert witnessing technology, quality problems can be detected and dealt with early.

[0029] Third, by using built-in effect evaluation and risk assessment models, the maintenance effect can be quantitatively evaluated in multiple dimensions, and potential risks can be identified in advance and dynamically warned, supporting the continuous improvement of maintenance quality and safety.

[0030] Fourth, through intelligent quality feedback and improvement closed-loop mechanisms, problems discovered during the maintenance process are automatically archived, analyzed, and transformed into improvement suggestions, driving the continuous optimization of standard processes and quality management systems.

[0031] Fifth, by enforcing quality standards and implementing real-time safety supervision, we can replace individual initiative with technological safeguards and process guidance to ensure that all standards and safety requirements are effectively implemented.

[0032] Example A method for improving maintenance safety and quality based on smart terminals includes the following steps: Step 1: Setting up digital quality control points The maintenance digital procedure execution terminal automatically inserts digital quality control points at key steps according to the preset maintenance process. The platform defines the inspection content, standards, and witnessing requirements for each quality control point, and the terminal prompts maintenance personnel in real time during the maintenance process to confirm and record the information. The data includes step codes, inspection items, standard values, actual values, inspection time, personnel information, etc. The system automatically verifies the integrity of the data and uploads it to the cloud database.

[0033] like Figure 1 As shown, the maintenance digital procedure execution terminal can set digital quality control points, which are used to perform quality checks and verifications at specific stages of the maintenance process. The platform can define the requirements and standards for quality control points and guide and intelligently enforce necessary and effective checks and verifications by maintenance personnel at key steps to ensure that maintenance quality meets requirements.

[0034] Input data: Maintenance process specification data: including step number, inspection item number, standard value, and allowable error range.

[0035] Equipment ledger data: equipment tag number, maintenance level, and key spare parts model.

[0036] Quality control point configuration data: control point type (witness point / stoppage pending inspection point / record point), witnessing requirements, and photo requirements.

[0037] Personnel qualification data: skill level of maintenance personnel, authorized job type, and validity period of work permit.

[0038] (2) Processing logic: After a maintenance task is initiated, the terminal downloads the digital procedure corresponding to the maintenance task from the cloud platform's process library, parses the control point markers in the procedure, extracts a list of all quality control points, loads the configurations in the order of steps, and builds a control point execution queue.

[0039] When maintenance personnel reach the control point step, the terminal displays an inspection and confirmation interface, showing the standard value and allowable deviation. After the maintenance personnel enter the actual measurement value, the system automatically compares the actual value with the standard value: if the actual value is within the allowable error range, it is recorded as qualified and written to the inspection record table; if it exceeds the allowable error, the non-conformity process is triggered, and the next step is locked.

[0040] If the control point configuration requires a witness's signature, the system sends a push notification to the witness's mobile device. After confirming their presence via fingerprint or facial recognition, the witness takes a photo, uploads it, and completes the electronic signature. All data is uploaded to the cloud platform's quality management database in real time. The control point's execution status (pending execution / in execution / passed / unqualified) is synchronized to the management dashboard.

[0041] (3) Output data: Quality Control Point Execution Record Form: Step number, inspection item, actual value, standard value, judgment result, inspection time, inspector, witness.

[0042] Non-conformity report: Non-conformity number, problem description, root cause analysis, and corrective action.

[0043] Quality trend data: Historical inspection data for similar equipment.

[0044] (4) Data interaction: Receive the procedure data issued in step three; send the inspection result data to steps two, four, and six.

[0045] Step Two: Intelligent Evaluation of Repair Results and Real-time Monitoring of Quality Indicators The terminal collects real-time data during the maintenance process, including operation time, resource consumption, equipment status, and inspection results. It then uses a built-in algorithm model to evaluate effectiveness and calculate quality indicators. The system supports setting thresholds and trend analysis; abnormal data automatically triggers alerts; and the evaluation results are compared with historical data to generate a quality report.

[0046] like Figure 2 As shown, the maintenance digital procedure execution terminal can perform intelligent evaluation of effectiveness and monitor quality indicators. The terminal can collect and analyze relevant data from maintenance tasks to assess maintenance effectiveness and quality indicators. Through evaluation and monitoring, the performance and quality of maintenance work can be understood, and corresponding measures can be taken to improve the reliability and continuous improvement of maintenance quality.

[0047] (1) Input data: Maintenance work order data: work order number, equipment tag number, planned start / end time, actual start / end time, maintenance team.

[0048] Resource consumption data: spare parts consumption list, tool usage records, and working hour reporting data.

[0049] Equipment status data: pre-maintenance status assessment, post-maintenance status assessment, and operating parameter records.

[0050] Quality control point execution record: from the pass / fail judgment result of step one.

[0051] Historical maintenance database: historical maintenance records and equipment operation index data for similar equipment.

[0052] (2) Processing logic: The terminal establishes a multi-dimensional evaluation indicator system, including: time indicators (comparison of actual working hours with planned working hours), quality indicators (first-pass rate of control points, number of non-conforming items), resource indicators (spare parts consumption deviation), and safety indicators (number of violations, implementation rate of risk control measures). Each dimension is scored according to its weight, with a maximum score of 100 points.

[0053] The overall score is derived by weighted summation of scores from each dimension, and the evaluation results are divided into four levels: Excellent (≥90 points), Good (80-89 points), Pass (70-79 points), and Unsatisfactory (<70 points).

[0054] The system is configured with the following abnormal warning rules: a yellow warning is triggered when the actual working hours exceed 1.3 times the planned working hours; a yellow warning is triggered when the first-pass rate of the control point is less than 80%; and a red warning is triggered and immediately pushed to the management personnel when a major non-conformity is found.

[0055] (3) Output data: Repair effectiveness evaluation report: overall score, scores for each dimension, evaluation level, and problem list.

[0056] Quality indicator monitoring dashboard data: Real-time updated quality indicator values.

[0057] Warning record: warning type, triggering condition, current value, warning time, and processing status.

[0058] (4) Data interaction: Receive Step 1 (Control Point Record), Step 3 (Work Order Data), and Step 4 (Feedback Data); Send Evaluation Results to Steps 4 and 5.

[0059] Step 3: Standardization and Regulation of the Entire Maintenance Process The platform establishes a standard maintenance process library, with each process including a sequence of steps, a tool list, safety requirements, and quality milestones. When a maintenance task is initiated, the terminal automatically matches and loads the corresponding process to ensure consistent execution. The system supports process version management and dynamic updates.

[0060] like Figure 3 As shown, the maintenance digital procedure execution terminal can promote the standardization and normalization of maintenance processes. The terminal platform can develop and manage standardized maintenance procedures and processes, ensuring that maintenance tasks are executed in accordance with these standards and specifications. This helps improve the consistency and quality of maintenance tasks, reduce errors and risks, enhance the quality and effectiveness of maintenance work, and promote continuous improvement and optimization of maintenance.

[0061] (1) Input data: Equipment technical data: equipment tag number, equipment type, model specifications, manufacturer.

[0062] Repair procedure data: repair manuals, manufacturer technical documents, industry standards.

[0063] Tooling and fixture data: Standard tool list, special tool requirements, and measuring instrument list.

[0064] Safety requirements data: safe operating procedures, hazard identification list, and emergency response plan.

[0065] Historical maintenance data: Feedback on maintenance experience with similar equipment and a summary of common problems.

[0066] (2) Processing logic: First, the paper-based maintenance procedures are converted into a structured data format, including process number, equipment type, version number, step sequence, tool list, safety requirements, etc. The converted procedures are then stored in the standard process library.

[0067] The workflow library employs a version control mechanism, generating a new version and archiving the old version with each modification. Before a workflow can be released, it requires three levels of approval: drafting, review (technician), approval (engineer), and release.

[0068] When a maintenance task is initiated, maintenance personnel scan a code or select the device tag number. The terminal automatically identifies the device type and queries the standard procedure library. Once a matching procedure is found, it is downloaded and loaded. If no matching procedure is found, the system marks it as a non-standard task and pushes it to the technician for approval.

[0069] The terminal guides maintenance personnel through a step-by-step sequence and can be configured to lock the next step if the current step is not completed. Upon completion of each step, the execution time and the person responsible for it are automatically recorded and synchronized to the cloud platform in real time.

[0070] (3) Output data: Standard Process Library: A complete database of maintenance processes, including version management functionality.

[0071] Task execution record: execution time, executor, and deviation status for each step.

[0072] Non-standard task list: A list of tasks requiring separate procedures. (4) Data interaction: Send process configuration data to Step 1 (as the basis for setting control points); send standard execution basis to Step 5; receive feedback and improvement suggestions from Step 4, and trigger process revision.

[0073] Step 4: Intelligent Quality Feedback and Improvement Feedback The terminal collects data such as maintenance reports, user feedback, and temporary modification records. Key information is extracted through text analysis and data processing modules to generate improvement suggestions. The system supports closed-loop management; improvement measures are automatically updated to the process library and take effect in subsequent tasks.

[0074] like Figure 4 As shown, the maintenance digital procedure execution terminal can collect quality feedback and opinions during the maintenance process, such as maintenance reports, user feedback, and temporary document modification records. It can also collaborate with maintenance personnel to organize and analyze these data. The terminal provides valuable data and references to formulate improvement actions, promote continuous optimization of quality management, and conduct intelligent closed-loop feedback management.

[0075] (1) Input data: Repair completion report: Repair content, replaced spare parts, test results, and remaining issues.

[0076] User / operator feedback: Function verification results, operation exception records, and improvement suggestions.

[0077] On-site temporary modification records: non-standard operating instructions, on-site change approval form.

[0078] Non-conformity report: Non-conformity data from step one.

[0079] Assessment report data: Assessment results from step two.

[0080] (2) Processing logic: Maintenance personnel fill out completion reports (structured forms) via terminals, while the operator submits function verification results and feedback via mobile devices. On-site temporary modification records are automatically linked to the corresponding work orders, and non-conformity data is automatically synchronized from the quality management module.

[0081] The system performs text analysis on the collected unstructured text, automatically identifies problem keywords (such as excessive vibration, seal leakage, abnormal noise, etc.), and extracts problem elements, including equipment tag number, problem type, and severity. Problems are then categorized according to equipment type, problem nature, and cause.

[0082] Based on problem classification, the system matches the historical solution library: if a historical solution already exists, it is directly recommended; if no historical solution exists, it is marked as needing further study. Simultaneously, a list of improvement suggestions is generated, categorized into short-term measures (immediate on-site rectification), medium-term measures (process optimization, technology improvement), and long-term measures (requiring design changes or technical upgrades).

[0083] Each improvement suggestion is assigned a unique number and a responsible person, who periodically updates the processing status via the terminal. After rectification is completed, a technician confirms the closure of the process. Once closure is confirmed, the process library is automatically updated.

[0084] (3) Output data: Quality Issues List: Issue Number, Equipment Tag Number, Issue Description, Category, Severity.

[0085] List of improvement suggestions: suggestion number, corresponding problem, measures, responsible person, and planned completion time.

[0086] Process Change Notification: Triggers the process revision in step three and the standard update in step five.

[0087] (4) Data interaction: Receive Step 1 (Non-conforming items), Step 2 (Evaluate low-scoring items), and Step 6 (Verify failed items); send improvement suggestions to Step 3, Step 5, and Step 2.

[0088] Step 5: Enforce quality standards The platform has a built-in quality standard library, including operating procedures, safety protocols, and checklists. During the maintenance process, the terminal automatically retrieves and displays relevant standards based on the current step, intercepting or warning against operations that do not meet the standards until the problem is corrected.

[0089] like Figure 5 As shown, the maintenance digital procedure execution terminal can enforce quality standards and requirements. The platform can have built-in quality standards and specifications to ensure that maintenance personnel follow these requirements during execution. Through enforcement, the platform reduces human error and arbitrariness, improving maintenance consistency and quality stability.

[0090] (1) Input data: Quality Standards Library: National Standards, Industry Standards, Enterprise Standards, and Technical Specifications.

[0091] Maintenance personnel qualification data: certification status, skill level, and authorization status for this task.

[0092] Real-time operation data: Operation records from the terminal.

[0093] Control point inspection data: Results from step one.

[0094] (2) Processing logic: The platform inputs various standard documents in a structured manner to establish a standard database. Each standard record includes: standard number, standard name, standard document number, version number, scope of application, standard content, and associated inspection items. It also labels each standard with applicable scenario tags to facilitate matching and searching.

[0095] When a maintenance task is initiated, the system automatically loads the corresponding standard package based on the task type. During execution, the terminal automatically queries relevant standards based on the current step, displays them to the maintenance personnel in the form of text, images, or videos, and requires confirmation that the personnel have read them.

[0096] When maintenance personnel enter data, the system automatically compares it with standard values. If the data does not meet the standard requirements, a warning pops up and displays the standard clauses, while simultaneously locking the next operation. Maintenance personnel can choose to correct the operation or apply for a deviation. Deviation applications require engineer approval, and are temporarily unlocked upon approval.

[0097] The critical quality control point (step one) must be performed according to the standard to pass. Failure to meet the standard will prevent progress to the next step; this is achieved through technical means to forcibly lock the process. Once the rectification meets the standard, the system will automatically unlock.

[0098] (3) Output data: Standard execution record: work order number, step number, applied standard, standard clause, execution result.

[0099] Deviation application record: Deviation number, deviation content, cause analysis, and approval result.

[0100] Warning log: Warning type (red / yellow), triggering condition, and processing result.

[0101] (4) Data interaction: Receive the execution data from step three and determine which standards should be pushed accordingly; receive the standard update notification from step four and trigger standard library version synchronization.

[0102] Step Six: Intelligent Quality Inspection and Verification The terminal uses cameras, sensors, and other devices to collect real-time images, videos, and environmental data from the maintenance site. Combining image recognition and data analysis technologies, it automatically checks the execution of key steps and compares them with standards. Verification results are uploaded in real time and support remote expert witnessing.

[0103] like Figure 6 As shown, the maintenance digital procedure execution terminal can guide personnel, monitor and record quality inspection and verification steps during the maintenance process in real time through digital remote technology. The platform can mandate that witnesses perform inspections and verifications of key points to ensure that maintenance work meets the prescribed quality requirements. This helps reduce quality problems and correct non-conforming maintenance work.

[0104] (1) Input data: Repair site video stream: from the terminal camera.

[0105] Image data: Photos of key steps (threaded connections, sealing surfaces, terminals, etc.).

[0106] Environmental sensor data: temperature, humidity, dust concentration.

[0107] Equipment operating parameters: vibration, pressure, temperature, flow rate.

[0108] Acceptance criteria data: Inspection standards and acceptance criteria defined in step three.

[0109] (2) Processing logic: In terms of video surveillance, the entire repair process is recorded (resolution and duration are configurable), and the video stream is transmitted to the edge server in real time. The video file path, timestamp, and associated work order information are written to the database.

[0110] In terms of image recognition, key step photography can be manually triggered by maintenance personnel or automatically prompted by the terminal based on the step location. The image recognition model library covers the following scenarios: bolt tightening recognition (detecting whether tightening is to the required torque), sealing surface inspection (detecting whether gaskets are installed correctly), terminal block inspection (detecting whether wiring is loose or incorrect), and cleanliness detection (detecting the cleanliness of the work area). If the recognition is satisfactory, it is automatically approved and recorded; if it is unsatisfactory, a warning pops up requiring reprocessing.

[0111] For remote expert witnessing, when a control point is configured as a witnessing point, the system automatically sends a witnessing request to the remote expert. The expert views the real-time video stream and high-definition photos through a web interface, confirms the information, and signs the interface; the signature data is encrypted and stored. After witnessing is completed, the system automatically unlocks the next step.

[0112] Environmental sensor data is compared with standards in real time. For example, humidity must be less than 70%. If the humidity exceeds the standard, the terminal will remind you to wait or take dehumidification measures before continuing.

[0113] (3) Output data: Image inspection record: photo file path, image recognition result, manual review result, timestamp.

[0114] Video archive record: video file path, associated work order, storage period.

[0115] Remote witnessing record: expert number, witnessing time, witnessing opinion, electronic signature.

[0116] (4) Data interaction: Receive the acceptance standard configuration from step three and the control point configuration from step one; send the inspection results to steps two and four.

[0117] Step Seven: Intelligent Risk Assessment and Control The system has a built-in risk assessment model that automatically identifies potential risks based on parameters such as maintenance task type, equipment status, environmental conditions, and personnel qualifications, and then pushes control measures and protection suggestions. Risk data is linked to maintenance records to form a risk knowledge base.

[0118] like Figure 7As shown, the maintenance digital procedure execution terminal can perform risk assessment and control based on the risk management requirements in the digital procedure. It can help maintenance personnel identify and assess potential risks in maintenance tasks and provide corresponding control measures and protection recommendations. By identifying and controlling risks in advance, the occurrence of accidents and injuries can be reduced, improving the inherent safety of maintenance.

[0119] (1) Input data: Maintenance task data: work order type, equipment tag number, and description of maintenance content.

[0120] Equipment status data: running / standby status, fault history, current defect record.

[0121] Environmental data: temperature, humidity, flammable gas concentration, and radiation level at the maintenance site.

[0122] Personnel data: Maintenance personnel qualifications, team safety score, and most recent safety training time.

[0123] Historical risk data: Records of historical risk events for similar tasks.

[0124] (2) Processing logic: The system establishes a risk factor weight matrix, mainly considering four categories of factors: equipment factors (failure type, historical accident rate), task factors (high-altitude operations, hot work, confined space operations, etc.), environmental factors (high temperature, dust, radiation, etc.), and personnel factors (experience level, training duration). The comprehensive risk score is calculated by weighting the risk scores of each factor.

[0125] Risk levels are divided into four categories: low risk (less than 30 points), medium risk (30-60 points), high risk (60-80 points), and extremely high risk (greater than 80 points). When the risk level reaches medium or above, a risk warning card is automatically generated; when the risk level reaches high or extremely high, a special operation permit is mandatory.

[0126] Based on the identified risk type, the system automatically matches corresponding measures from the control measure library: hot work corresponds to fire-fighting equipment preparation and fire alarm confirmation; high-altitude work corresponds to safety belt inspection and scaffolding acceptance; confined space work corresponds to gas detection and personnel monitoring. After the measure list is pushed to the terminal, maintenance personnel confirm and implement each measure, and the execution time and person of each measure are recorded.

[0127] During maintenance, the system continuously collects data from environmental sensors. When environmental parameters exceed safety thresholds, the terminal issues an audible and visual alarm, simultaneously sending a warning to all personnel on site, and the associated work order is automatically suspended. Work can only resume after maintenance personnel confirm and rectify the issues.

[0128] Upon completion of each maintenance task, the risk assessment record is automatically archived in the risk knowledge base. If an unidentified risk event occurs, the knowledge base supplementation process is triggered, requiring review and confirmation by an engineer before the record is added to the database.

[0129] (3) Output data: Risk warning card: Task number, risk level, main risk sources, and list of control measures.

[0130] Implementation record of measures: content of measures, confirmation of implementation, time of implementation, and person responsible for implementation.

[0131] Environmental alarm records: alarm time, alarm parameter exceeding the standard value, and recovery time.

[0132] (4) Data interaction: Send risk warning data to step eight (triggering targeted security training); send risk warning data to step nine (triggering security execution supervision); receive task configuration issued in step three and trigger risk assessment.

[0133] Step 8: Establish safety training and knowledge base The terminal integrates a safety training module, providing training content in various formats such as videos, text, and simulated operations. Maintenance personnel can learn and assess themselves according to task requirements. The knowledge base is updated in real time and supports intelligent retrieval and push notifications.

[0134] like Figure 8 As shown, the maintenance digital procedure execution terminal can help maintenance personnel improve their safety awareness and knowledge. Maintenance personnel can access safety training materials through the terminal, understand the latest safety requirements and operating procedures, thereby enhancing their safety awareness and capabilities in their work.

[0135] (1) Input data: Training resource data: video courseware, graphic tutorials, simulated operation procedures, and assessment question bank.

[0136] Maintenance task data: current task type and risk characteristics from step three.

[0137] Personnel training records: Training records, assessment results, and skill levels have been completed.

[0138] Risk warning data: Risk characteristics of the current task from step seven.

[0139] (2) Processing logic: Before a maintenance task begins, the system automatically analyzes the task's risk characteristics, compares them with personnel training records, and generates a personal training checklist. If personnel have not completed the relevant training, they must complete the training and pass the assessment before they can begin the task.

[0140] The training formats include four types: first, video training, which supports online playback or cached playback on the terminal and automatically remembers the playback progress; second, text and image tutorials, which use H5 format and support keyword search; third, simulated operation, which supports augmented reality guidance for step-by-step simulation exercises; and fourth, online assessment, where the system randomly selects questions from the question bank, and the system automatically scores the answers after maintenance personnel answer them online.

[0141] After each training session, the system automatically records the trainee's ID, training resource ID, completion time, and assessment score. Training records are linked to maintenance work orders for traceable management. The system periodically checks the training validity period and automatically sends a retraining reminder before it expires.

[0142] The knowledge base supports full-text search; entering keywords will return relevant technical documents and experience feedback. It also intelligently recommends relevant knowledge items based on the current task context. The knowledge base content is updated and supplemented in real time based on the improvement suggestions from step four.

[0143] (3) Output data: Training completion record: Personnel number, training resource number, completion time, assessment score, whether passed.

[0144] Training reminder list: Training courses that are about to expire, and required training courses that have not been completed.

[0145] Training effectiveness statistical analysis: completion rate and assessment pass rate for each type of training.

[0146] (4) Data interaction: Upon receiving the risk warning from step seven, targeted security training will be pushed to the system; upon receiving the improvement suggestions from step four, the knowledge base content will be updated.

[0147] Step Nine: Advanced Maintenance Safety Management The system records the safety requirements, protective measures, and emergency plans for each maintenance task, and provides real-time reminders and monitoring during execution. The terminal supports safety equipment status detection, environmental monitoring, and anomaly alarms, and interfaces with the enterprise's safety management system.

[0148] like Figure 9 As shown, the maintenance digital procedure execution terminal can manage maintenance safety. The terminal platform can record and manage the safety requirements and measures for maintenance tasks, including personal protective equipment, work environment safety, and emergency response, and implement these safety requirements and measures into specific intelligent execution steps and reminders. By managing maintenance safety, the safety of maintenance work can be improved, protecting the safety of maintenance personnel and equipment.

[0149] (1) Input data: Safety requirements data: from the risk warning card and control measures in step seven.

[0150] Safety equipment data: Personal protective equipment requisition records and condition.

[0151] Environmental monitoring data: Real-time environmental sensor data from step seven.

[0152] Emergency response plan data: emergency response procedures and contact lists for various emergencies.

[0153] Enterprise safety management system data: hazard log, violation records, and safety assessment results.

[0154] (2) Processing logic: When a maintenance task is initiated, the system integrates the safety requirements output in step seven, including control measures in the risk warning card, special operation permit requirements (such as hot work permits, high-altitude permits, etc.), and emergency escape route maps, generates a task-specific safety list, and pushes it to the terminal.

[0155] Real-time security monitoring includes three aspects: PPE (Personal Protective Equipment) Inspection: Before entering the site, maintenance personnel scan their work badges or QR codes at the terminal. The system checks the personnel's PPE training records; if no records are found, a training reminder pops up. If the task requires special PPE, the system requires scanning or taking photos to confirm the equipment's status.

[0156] Environmental monitoring alarm: After receiving the environmental anomaly alarm from step seven, the terminal immediately displays the alarm information and pushes evacuation or shelter instructions.

[0157] Violation identification: Combined with video surveillance from step six, image recognition is used to identify behaviors such as not wearing a seat belt and illegal operations, and the violation time and personnel information are recorded in real time and automatically reported to the safety management system.

[0158] In terms of emergency management, the terminal displays key points of the emergency plan before the mission begins, including fire response procedures, personal injury response procedures, and environmental pollution response procedures. In an emergency, maintenance personnel can use the terminal to call for help with one click. The system sends the location and mission information to the emergency contact person, and simultaneously displays the location of the nearest emergency supplies (such as fire hydrants, first aid kits, etc.).

[0159] The system interfaces with the enterprise's safety management system via a data interface. Maintenance task data is synchronized to the safety management system, and hazard data from the safety management system is synchronized to the terminal for maintenance personnel to view.

[0160] (3) Output data: Safety supervision record: task number, supervision and inspection time, inspection type, inspection result.

[0161] Violation record: Violator number, violation type, violation time, and handling result.

[0162] Emergency response record: trigger time, emergency type, response measures, and result evaluation.

[0163] Security management system integration logs: data synchronization time, synchronized content, and exception records.

[0164] (4) Data interaction: Receive the risk warnings and control measures from step seven as the basis for implementation; receive the video surveillance violation identification data from step six as a supervision record.

[0165] A maintenance safety and quality improvement system based on smart terminals includes: a digital quality control point setting module, a maintenance effect intelligent evaluation and quality indicator monitoring module, a full maintenance process standardization and specification management module, an intelligent quality feedback and improvement module, a mandatory quality standard enforcement module, a quality intelligent inspection and verification module, an intelligent risk assessment and control module, a safety training and knowledge base module, and an advanced maintenance safety management module. The specific implementation of each module is as follows: (a) Digital Quality Control Point Setting Module like Figure 1 As shown, this module is used to set digital quality control points at specific stages of the maintenance process, define the requirements and standards for quality control points, guide and enforce maintenance personnel to perform necessary and effective checks and verifications at key steps, and ensure that the maintenance quality meets the requirements.

[0166] The specific implementation steps for this module are as follows: Step 1: Configure quality control points for each critical step in the standard maintenance process library. Configuration details include: control point type (witness point, downtime inspection point, and record point), inspection content, standard values, allowable error range, whether a witness is required, and whether photographs are required.

[0167] Step 2: When a maintenance task is started, the smart terminal downloads digital procedures from the cloud platform process library, parses the quality control point markers in the procedures, extracts a list of all quality control points, loads the configurations in the order of steps, and builds a control point execution queue.

[0168] Step 3: When the maintenance personnel reach the control point step, the smart terminal automatically pops up an inspection and confirmation interface, displaying the standard value and allowable deviation. After the maintenance personnel enter the actual measurement value, the system automatically compares the actual value with the standard value. If the actual value is within the allowable error range, it is recorded as qualified and written to the inspection record sheet; if it exceeds the allowable error, the non-conformity process is triggered and the next step is locked.

[0169] Step 4: If the control point configuration requires a witness's signature, the system sends a push notification to the witness's mobile device. After confirming their presence via fingerprint or facial recognition, the witness takes a photo, uploads it, and completes the electronic signature. All data is uploaded to the cloud platform's quality management database in real time.

[0170] Step 5: The execution status of control points (pending execution, in execution, passed, unqualified) is synchronized to the management dashboard in real time for managers to view.

[0171] Intelligent evaluation and quality indicator monitoring module for repair results like Figure 2 As shown, this module is used to intelligently evaluate the maintenance effect and monitor the quality indicators in real time, collect and analyze relevant data of maintenance tasks, understand the performance and quality of maintenance work, and take corresponding measures to improve the reliability and continuous improvement of maintenance quality.

[0172] The specific implementation steps for this module are as follows: Step 1: The smart terminal automatically collects real-time data during the maintenance process, including operation time, resource consumption, equipment status, quality control point inspection results, etc., and automatically links them to the corresponding work orders.

[0173] Step 2: The system establishes a multi-dimensional evaluation indicator system, including: time indicators (comparison of actual working hours and planned working hours), quality indicators (first-pass rate of control points), resource indicators (deviation in spare parts consumption), and safety indicators (number of violations and implementation rate of risk control measures). Each dimension is scored according to its weight, with a maximum score of 100 points.

[0174] Step 3: The overall score is obtained by weighted summation of the scores from each dimension. The evaluation results are divided into four levels: Excellent (90 points and above), Good (80-89 points), Satisfactory (70-79 points), and Unsatisfactory (below 70 points).

[0175] Step 4: Set up system anomaly warning rules. A yellow warning is triggered when the actual working hours exceed 1.3 times the planned working hours; a yellow warning is triggered when the first-pass rate of control points is less than 80%; a red warning is triggered and immediately pushed to the management personnel when a major non-conformity is found.

[0176] Step 5: Compare the evaluation results with historical data, generate a quality report, and synchronize it to the management dashboard and quality indicator monitoring dashboard.

[0177] Standardization and Regulation Management Module for the Entire Maintenance Process like Figure 3 As shown, this module is used to promote the standardization and normalization of the maintenance process, formulate and manage standardized maintenance procedures and processes, ensure that the execution of maintenance tasks conforms to standards and specifications, improve the consistency and quality of maintenance tasks, and promote continuous improvement and optimization of maintenance.

[0178] The specific implementation steps for this module are as follows: Step 1: Convert paper maintenance manuals, manufacturer technical documents, and industry standards into structured data format. The conversion includes: process number, equipment type, version number, step sequence (each step includes operation details, tool list, safety requirements, and quality checkpoints), and a list of applicable equipment.

[0179] Step 2: Store the structured data in the standard process library, and associate each sub-table (step table, tool table, safety requirement table, quality node table) with the process number as the primary key to ensure data integrity.

[0180] Step 3: The workflow library uses a version control mechanism. Each modification generates a new version and archives the old version. Before a workflow is released, it must undergo three levels of approval: drafting, technician review, engineer approval, and system release.

[0181] Step 4: When a maintenance task is initiated, maintenance personnel scan a code or select the equipment tag number. The system automatically identifies the equipment type and queries the standard procedure library. Once a matching procedure is found, it is downloaded and loaded into the smart terminal. If no matching procedure is found, the system marks it as a non-standard task and pushes it to the technician for approval.

[0182] Step 5: The smart terminal guides maintenance personnel through the steps in sequence, and can be configured to lock the next step if the current step is not completed. Upon completion of each step, the execution time and the person performing the action are automatically recorded and synchronized to the cloud platform in real time.

[0183] Intelligent quality feedback and improvement module like Figure 4 As shown, this module is used to collect quality feedback and opinions during the maintenance process, such as maintenance reports, user feedback, and temporary modification records, to organize and analyze them, formulate improvement actions, promote continuous optimization of quality management, and conduct intelligent closed-loop feedback management.

[0184] The specific implementation steps for this module are as follows: Step 1: Receive multi-source data from smart terminals, including completion reports, operator feedback, temporary modification records, non-conformity reports, and evaluation reports. The data is then uniformly aggregated through a data platform.

[0185] Step 2: Perform text analysis on unstructured text (feedback, descriptions of outstanding issues, etc.), automatically identify problem keywords (such as high vibration, seal leakage), and extract elements such as equipment tag number, problem type, and severity.

[0186] Step 3: Categorize problems according to equipment type, problem nature, and stage of occurrence to provide a basis for matching subsequent improvement suggestions.

[0187] Step 4: Match the problem to the historical solution library based on problem classification. Problems with existing historical solutions are directly recommended; those without are marked as requiring further investigation, and relevant technical personnel are notified to follow up. Simultaneously, a list of short-term (immediate rectification), medium-term (process optimization), and long-term (design change) improvement suggestions is generated.

[0188] Step 5: Each improvement suggestion is assigned a unique number and a responsible person. The responsible person regularly updates the processing status via the smart terminal. After rectification is completed, the technician confirms the closure of the process. Once the closure is confirmed, the standard maintenance process library is automatically updated.

[0189] Enforcement of quality standards module like Figure 5 As shown, this module is used to enforce quality standards and requirements. It has built-in quality standards and specifications to ensure that maintenance personnel follow the standards and specifications during the execution process. By enforcing the standards, human factors and arbitrariness are reduced, and the consistency and quality stability of maintenance are improved.

[0190] The specific implementation steps for this module are as follows: Step 1: Structure and input national standards, industry standards, enterprise standards, technical specifications, and other standard documents into the database. Each standard record includes: standard number, standard name, standard document number, version number, scope of application, standard content, and associated inspection items. Applicable scenario tags are also added to each standard for easy matching and searching.

[0191] Step 2: When a maintenance task is initiated, the system automatically loads the corresponding standard package based on the task type. During execution, the smart terminal automatically queries the standard clauses that should be displayed based on the current step, presents them to the maintenance personnel in the form of text, images, or videos, and requests confirmation that they have read them.

[0192] Step 3: When maintenance personnel enter data, the system automatically compares the entered values ​​with the standard allowable range. If the data does not meet the standard requirements, a warning will pop up and the standard clause will be displayed, while the next step will be locked. Maintenance personnel can choose to correct the operation or apply for a deviation. Deviation applications require engineer approval, and the deviation will be temporarily unlocked after approval.

[0193] Step 4: Key quality control points must be performed according to standards to pass. Failure to meet standards will prevent progress to the next step; this is achieved through technical means to forcibly lock the system. Once rectification meets the standards, the system will automatically unlock.

[0194] Step 5: All standard execution records, deviation application records, and warning records are permanently saved for subsequent analysis and traceability.

[0195] Quality intelligent inspection and verification module like Figure 6As shown, this module is used to guide personnel through digital remote technology, monitor and record quality inspection and verification steps in the maintenance process in real time, and require witnesses to check and verify key points to ensure that maintenance work meets the prescribed quality requirements, reduce quality problems and correct unqualified maintenance work.

[0196] The specific implementation steps for this module are as follows: Step 1: The entire repair process is recorded as video (resolution and duration are configurable), and the video stream is transmitted to the edge server in real time. The video file path, timestamp, and associated work order information are written to the database.

[0197] Step 2: After completing critical steps (such as bolt tightening, sealing installation, and terminal connection), maintenance personnel take and upload images via the smart terminal. Taking photos can be triggered manually or automatically by the terminal based on the step's location.

[0198] Step 3: The image recognition engine determines the type of shooting scene (bolt tightening, sealing surface, wiring terminal, cleanliness, etc.) based on image features and calls the corresponding algorithm for detection. Qualified images are automatically approved and recorded; unqualified images trigger a warning and require reprocessing.

[0199] Step 4: When the control point is configured as a witness point, the system automatically sends a witness request to the remote expert. The expert views the real-time video stream and high-definition photos through a web interface, confirms, and electronically signs. After witnessing is completed, the system automatically unlocks the next step.

[0200] Step 5: Compare environmental sensor data with standards in real time. For example, humidity should be less than 70%. If it exceeds the standard, the smart terminal will remind you to wait or take dehumidification measures before continuing.

[0201] Intelligent risk assessment and control module like Figure 7 As shown, this module is used to conduct risk assessment and control according to the risk management requirements in digital procedures, helping maintenance personnel to identify and assess potential risks in maintenance tasks, providing corresponding control measures and protection suggestions, reducing the occurrence of accidents and injuries, and improving the inherent safety of maintenance by identifying and controlling risks in advance.

[0202] The specific implementation steps for this module are as follows: Step 1: The system establishes a risk factor weight matrix, calculating risk scores from four dimensions: equipment factors (failure type, historical accident rate), task factors (high altitude / hot work / confined space), environmental factors (high temperature / dust / radiation), and personnel factors (experience level / training status). The comprehensive risk score is obtained by weighted summation of each dimension.

[0203] Step 2: Risk levels are divided into four categories: low risk (below 30 points), medium risk (30-60 points), high risk (60-80 points), and extremely high risk (above 80 points). Medium and higher risk levels automatically generate risk warning cards; high or extremely high risk levels require a special operation permit.

[0204] Step 3: Match the corresponding measures from the control measures library according to the risk type: hot work corresponds to fire-fighting equipment preparation and fire alarm confirmation; high-altitude work corresponds to safety belt inspection and scaffolding acceptance; confined space work corresponds to gas detection and personnel monitoring. After the control measures list is pushed to the smart terminal, maintenance personnel confirm and implement each item.

[0205] Step 4: During maintenance, the system continuously collects environmental sensor data. When environmental parameters exceed safety thresholds, the smart terminal issues an audible and visual alarm, simultaneously pushing a warning to all personnel on site, and the associated work order is automatically paused. Work can only resume after maintenance personnel confirm rectification.

[0206] Step 5: After each maintenance task is completed, the risk assessment record is automatically archived to the risk knowledge base. If an unidentified risk event occurs, the knowledge base supplementation process is triggered, and the record must be reviewed and confirmed by an engineer before being added to the database.

[0207] Safety training and knowledge base module like Figure 8 As shown, this module is designed to help maintenance personnel improve their safety awareness and knowledge, access safety training materials through smart terminals, and understand the latest safety requirements and operating procedures, thereby enhancing their safety awareness and capabilities in their work.

[0208] The specific implementation steps for this module are as follows: Step 1: Before a maintenance task begins, the system automatically analyzes the task's risk characteristics, compares them with personnel training records, and generates a personal training checklist. If personnel have not completed the relevant training, they must complete the training and pass the assessment before starting the task.

[0209] Step 2: The training formats include four types: First, video training, which supports online playback or cached playback on smart terminals and automatically remembers the playback progress; second, text and image tutorials, which use H5 format and support keyword search; third, simulated operation, which supports augmented reality guidance for step-by-step simulation exercises; and fourth, online assessment, where the system randomly selects questions from the question bank, and the system automatically scores the answers after the maintenance personnel answer them online.

[0210] Step 3: After each training session, the system automatically records the trainee's ID, training resource ID, completion time, and assessment score. Training records are linked to maintenance work orders for traceable management. The system periodically checks the training validity period and automatically sends a retraining reminder before expiration.

[0211] Step 4: The knowledge base supports full-text search. Maintenance personnel can enter keywords to return relevant technical documents and experience feedback. Simultaneously, it intelligently recommends relevant knowledge entries based on the current task context.

[0212] Step 5: The knowledge base content is updated and supplemented in real time based on intelligent quality feedback and improvement suggestions from the improvement module.

[0213] Advanced Maintenance Safety Management Module like Figure 9 As shown, this module is used for maintenance safety management, recording and managing the safety requirements and measures for maintenance tasks, including personal protective equipment, work environment safety, emergency response, etc., and implementing these safety requirements and measures into specific intelligent execution steps and reminders to improve the safety of maintenance work and protect the safety of maintenance personnel and equipment.

[0214] The specific implementation steps for this module are as follows: Step 1: When a maintenance task is initiated, the system integrates the safety requirements output by the intelligent risk assessment and control module, including control measures in the risk warning card, special operation permit requirements (such as hot work permit, high-altitude permit, etc.), and emergency escape route map, generates a task-specific safety list and pushes it to the smart terminal.

[0215] Step 2: Regarding personal protective equipment (PPE) inspection, maintenance personnel scan their work badges using a smart terminal before entering the site. The system checks the personnel's PPE training records and the validity period of their special operation certificate. If the task requires special PPE, photos are required to confirm the equipment's condition.

[0216] Step 3: In terms of violation identification, the video surveillance data from the quality intelligent inspection and verification module is combined to identify behaviors such as not wearing a seat belt and illegal operation, record the time of violation and personnel information in real time, and automatically report to the enterprise safety management system.

[0217] Step 4: In terms of emergency management, the smart terminal displays the key points of the emergency plan before the task begins. In an emergency, maintenance personnel can use the terminal to call for help with one click. The system automatically sends the location and task information to the emergency contact person, and displays the location of the nearest emergency supplies.

[0218] Step 5: The system connects with the enterprise safety management system via a data interface. Maintenance task data is synchronized to the safety management system, and hazard data in the safety management system is synchronized to the smart terminal for maintenance personnel to view.

[0219] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications to the technical solutions described in the foregoing embodiments, or equivalent substitutions for some or all of the technical features, do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for improving maintenance safety and quality based on smart terminals, characterized in that, Includes the following steps: Step 1: Setting up digital quality control points; Step Two: Intelligent evaluation of repair effectiveness and real-time monitoring of quality indicators; Step 3: Standardize and regulate the entire maintenance process; Step 4: Intelligent quality feedback and improvement feedback; Step 5: Enforce quality standards; Step Six: Intelligent Quality Inspection and Verification; Step Seven: Intelligent Risk Assessment and Control; Step 8: Establish safety training and knowledge base; Step Nine: Advanced Maintenance and Safety Management; Record the safety requirements, protective measures, and emergency plans for each maintenance task, and provide real-time reminders and supervision during the execution process.

2. The method for improving maintenance safety and quality based on a smart terminal as described in claim 1, characterized in that: Step one includes automatically inserting digital quality control points according to a preset maintenance process, defining the inspection content, standards, and witnessing requirements for each quality control point, and prompting maintenance personnel to confirm and record in real time during the maintenance process. The data includes step number, inspection item, standard value, actual value, inspection time, and personnel information. The data integrity is automatically verified and uploaded to the cloud platform database.

3. The method for improving maintenance safety and quality based on a smart terminal as described in claim 1, characterized in that: Step two includes collecting real-time data during the maintenance process, including operation time, resource consumption, equipment status, and inspection results, conducting effect evaluation and quality index calculation, supporting the setting of thresholds and trend analysis, automatically triggering early warnings for abnormal data, comparing evaluation results with historical data, and generating a quality report.

4. The method for improving maintenance safety and quality based on a smart terminal as described in claim 1, characterized in that: Step three includes the platform establishing a standard maintenance process library. Each process includes a sequence of steps, a tool list, safety requirements, and quality milestones. When a maintenance task is started, the corresponding process is automatically matched and loaded to ensure consistent execution.

5. The method for improving maintenance safety and quality based on a smart terminal as described in claim 1, characterized in that: Step four includes collecting maintenance reports, user feedback, and temporary modification records, extracting key information through text analysis and data processing modules, and forming improvement suggestions.

6. The method for improving maintenance safety and quality based on a smart terminal as described in claim 1, characterized in that: Step five includes a built-in quality standard library, including operating procedures, safety regulations, and checklists. During the maintenance process, relevant standards are automatically retrieved and displayed according to the current step, and operations that do not meet the standards are intercepted or warned until the correction is completed.

7. The method for improving maintenance safety and quality based on a smart terminal as described in claim 1, characterized in that: Step six includes real-time acquisition of maintenance site images, videos, and environmental data through cameras and sensors, automatic checking of the execution of key steps, comparison with standards, real-time uploading of verification results, and support for remote expert witnessing.

8. The method for improving maintenance safety and quality based on a smart terminal as described in claim 1, characterized in that: Step seven includes a built-in risk assessment model that automatically identifies potential risks based on maintenance task type, equipment status, environmental conditions, and personnel qualifications, and pushes control measures and protection suggestions. Risk data is linked with maintenance records to form a risk knowledge base.

9. The method for improving maintenance safety and quality based on a smart terminal as described in claim 1, characterized in that: Step eight includes a terminal-integrated security training module that provides video, text, and simulated operation information. Maintenance personnel can learn and be assessed independently according to task requirements. The knowledge base is updated in real time and supports intelligent retrieval and push notifications.

10. A maintenance safety and quality improvement system based on a smart terminal, characterized in that, include: The module includes: digital quality control point setting module, intelligent maintenance effect evaluation and quality indicator monitoring module, standardization and regulation management module for the entire maintenance process, intelligent quality feedback and improvement module, mandatory quality standard enforcement module, intelligent quality inspection and verification module, intelligent risk assessment and control module, safety training and knowledge base module, and advanced maintenance safety management module. The digital quality control point setting module is used to set digital quality control points at specific stages of the maintenance process, define the requirements and standards for quality control points, guide and force maintenance personnel to perform necessary and effective checks and confirmations at key steps, and ensure that the maintenance quality meets the requirements. The intelligent evaluation and quality indicator monitoring module for maintenance effectiveness is used to intelligently evaluate maintenance effectiveness and monitor quality indicators in real time, collect and analyze relevant data of maintenance tasks, understand the performance and quality of maintenance work, and take corresponding measures to improve the reliability and continuous improvement of maintenance quality. The standardization and regulation management module for the entire maintenance process is used to promote the standardization and regulation of the maintenance process, formulate and manage standardized maintenance procedures and processes, ensure that the execution of maintenance tasks conforms to standards and regulations, improve the consistency and quality of maintenance tasks, and promote continuous improvement and optimization of maintenance. The intelligent quality feedback and improvement module is used to collect quality feedback and opinions during the maintenance process, organize and analyze them, formulate improvement actions, promote continuous optimization of quality management, and carry out intelligent closed-loop feedback management. The mandatory quality standard module is used to enforce quality standards and requirements. It has built-in quality standards and specifications to ensure that maintenance personnel follow the standards and specifications during the execution process. By enforcing the standards, human factors and arbitrariness are reduced, and the consistency and quality stability of maintenance are improved. The intelligent quality inspection and verification module is used to guide personnel, monitor and record quality inspection and verification during the maintenance process in real time, and require witnesses to inspect and verify key points to ensure that the maintenance work meets the prescribed quality requirements, reduce quality problems and correct unqualified maintenance work. The intelligent risk assessment and control module is used to conduct risk assessment and control according to the risk management requirements in the digital procedure, identify and assess potential risks in maintenance tasks, and provide corresponding control measures and protection suggestions. The safety training and knowledge base module is used to enhance safety awareness and knowledge levels, and to learn about the latest safety requirements and operating procedures by accessing safety training materials; The advanced maintenance safety management module is used for maintenance safety management, recording and managing the safety requirements and measures for maintenance tasks, including personal protective equipment, work environment safety, and emergency response, and implementing these safety requirements and measures into specific intelligent execution steps and reminders.

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