Equipment health management system

Abstract

The invention discloses an equipment health management system in the technical field of equipment management, and aims to solve the problem that linkage management is not formed among equipment management modes in the prior art. The system comprises an equipment health evaluation module used for determining an equipment health degree score, identifying a vulnerability index and pushing an index improvement promotion direction; the benchmarking management module is used for performing benchmarking management on the same equipment, generating an improvement project and pushing the improvement project; the beforehand management module is used for displaying and executing equipment point inspection and maintenance plans, generating an improvement direction and pushing the improvement direction; the in-process management module is used for performing real-time monitoring, prediction and early warning on equipment process and result parameters, and pushing improvement measures; the after-event management module is used for identifying bottleneck procedures and equipment problems of the automatic production line, generating improvement suggestions and pushing the improvement suggestions; and the closed-loop management module is used for establishing an improvement project for closed-loop management based on the improvement suggestions pushed by the modules. According to the invention, transparent management, multi-dimensional dynamic closed loop and continuous, healthy and efficient operation of equipment can be realized.

Description

Technical Field

[0001] This invention relates to the field of equipment management technology, and in particular to an equipment health management system. Background Technology

[0002] Currently, the lithium battery manufacturing industry has a high degree of automation in the cell production process. The operating status, efficiency, and maintenance level of this equipment significantly impact product quality and equipment failure rates. Therefore, comprehensive equipment status monitoring and health assessments are necessary to identify weaknesses and improve equipment health through multi-dimensional closed-loop management. Furthermore, many existing equipment management methods are offline, such as recording and improving equipment problems. These methods lack inter-management coordination and focus on core KPIs, resulting in improvement measures that fail to effectively support KPI achievement. Consequently, they fail to improve equipment operating efficiency and safety, reduce maintenance costs, and ultimately enhance the company's economic benefits. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the existing technology and provide an equipment health management system for lithium battery automated production lines. By evaluating key equipment indicators and outputting health scores, the system conducts multi-dimensional closed-loop management through internal and external benchmarking, including pre-processing, in-processing, and post-processing stages. At the same time, the improvement measures are strongly linked with the indicators, thereby providing strong support for improving the equipment health level and KPI indicators.

[0004] To achieve the above objectives, the present invention is implemented through the following technical solution:

[0005] An equipment health management system for use in an automated lithium battery production line includes:

[0006] The equipment health assessment module is used to determine the dimensions of equipment health assessment, screen the indicators of the assessment dimensions, build the assessment model and output the equipment health score, as well as identify the weak indicators and automatically push the direction of indicator improvement to the closed-loop management module.

[0007] The benchmarking management module is used to benchmark the same equipment within the base and between different bases, generate cross-base thematic improvement projects and push them to the closed-loop management module.

[0008] The pre-operation management module is used to display and execute equipment inspection and maintenance plans, record the inspection and maintenance process and results details, generate improvement directions and push them to the closed-loop management module;

[0009] The in-process management module is used for real-time monitoring, prediction, and early warning of equipment process and result parameters; and to automatically link improvement measures to the closed-loop management module.

[0010] The post-processing management module is used to identify bottleneck processes and equipment problems in automated production lines, and to classify equipment problems and push improvement suggestions to the closed-loop management module.

[0011] The closed-loop management module is used to create improvement projects based on the improvement directions and suggestions of each module, establish the linkage between improvement projects and indicators, and monitor the effectiveness of improvements.

[0012] Through the above-mentioned technical means, the present invention realizes automatic push of improvement reminders, and conducts multi-dimensional closed-loop management before, during and after the event, while strongly linking closed-loop measures with indicator improvement, ensuring that improvement measures provide key support for improving equipment health.

[0013] Preferably, the device health assessment module includes:

[0014] The evaluation dimension unit is used to determine the evaluation dimensions of equipment health and to filter the indicators for each health evaluation dimension; the equipment health evaluation dimensions include three dimensions: technical status, performance, and maintenance level.

[0015] The evaluation model unit is used to determine the weights of each health evaluation dimension indicator and to assign standard scores to the health evaluation dimension indicators based on their weights.

[0016] The evaluation scoring unit is used to determine the actual score of the indicator based on the standard score of the indicator, and to obtain the health evaluation dimension score and the equipment health score based on the actual score of the indicator.

[0017] The countermeasure push unit is used to identify weak indicators based on the equipment health score and the actual index score, and output directions for improvement.

[0018] In this preferred embodiment, the equipment health evaluation is carried out from three dimensions: technical status, performance, and maintenance level, so as to achieve a comprehensive evaluation of the equipment.

[0019] Preferably, the technical status dimension indicators include equipment operating parameters and key process parameters; the performance dimension indicators include efficiency, equipment process capacity, energy consumption, cost and process quality related indicators; and the maintenance level indicators include inspection and maintenance related indicators.

[0020] In this preferred embodiment, the indicators included in the three evaluation dimensions are further refined. All three indicators are obtained through real-time data acquisition from the device or by retrieving data from other system modules.

[0021] Preferably, the evaluation model unit is specifically used for,

[0022] The weights of the health evaluation indicators were determined using the analytic hierarchy process (AHP) from four dimensions: efficiency, quality, cost, and energy consumption.

[0023] The impact of equipment parameters on efficiency, quality, cost, and energy consumption is quantified using the matrix method, resulting in a correlation score between equipment parameters and efficiency, quality, cost, and energy consumption.

[0024] Based on the correlation scores of equipment parameters with efficiency, quality, cost, and energy consumption, and the weights of evaluation dimension indicators, the evaluation score of the equipment parameters is obtained, expressed as: =G i1 *w 1* G i2 *w 2* G i3 *w 3* G i4 *w4, where G i1 G i1 G i1 G i1 , representing the correlation scores of the i-th device parameter with efficiency, quality, cost, and energy consumption respectively, and w1, w2, w3, and w4 representing the weights of the evaluation dimensions of efficiency, quality, cost, and energy consumption respectively;

[0025] Based on the evaluation scores of the equipment parameters, the index weights of the equipment parameters are obtained, expressed as follows: ,in, Indicates the first The weight of each device parameter index. Number of equipment parameters;

[0026] The weights of the corresponding health evaluation dimensions are obtained by summing the weights of the parameters of each device within the health evaluation dimension.

[0027] The standard scores for each indicator in the health evaluation dimension are assigned based on their weights.

[0028] In this preferred embodiment, the indicators are evaluated from four dimensions: efficiency, quality, cost, and energy consumption, making the health assessment more realistic and accurate.

[0029] Preferably, the evaluation scoring unit is specifically used for,

[0030] The values ​​of health assessment dimensions and indicators collected in real time are compared with preset target values.

[0031] Based on the comparison results and the standard scores of the health evaluation dimension indicators, the actual scores of the health evaluation dimension indicators are determined.

[0032] The sum of the actual scores of all health assessment dimensions is the score of the corresponding health assessment dimension.

[0033] The sum of the scores from the three health evaluation dimensions is the equipment health score.

[0034] In this preferred embodiment, for the technical status dimension indicators, a threshold evaluation method is used and real-time dynamic data is used to determine the actual scores of the indicators; for the performance dimension indicators and maintenance level indicators, a target percentage method is used and periodic data is used to determine the actual scores of the indicators.

[0035] Preferably, the countermeasure push unit is specifically used for,

[0036] By comparing the actual scores of the health assessment dimensions with the standard scores, indicators with scores lower than the standard scores and a difference of ≥20% from the standard scores are identified as weak indicators, and directions for improvement are provided.

[0037] In this preferred embodiment, indicators whose actual scores are lower than the standard scores and whose difference from the standard scores accounts for ≥20% of the standard scores are identified as weak indicators, and directions for improvement of these indicators are output.

[0038] Preferably, the benchmarking management module includes:

[0039] The base benchmarking unit is used to display the health scores of the same equipment in different bases, as well as to list the special improvement projects that improve the indicators of different bases, so that different bases can view, benchmark and learn from each other.

[0040] The equipment benchmarking unit is used to display a radar chart showing the health scores of similar equipment within the base.

[0041] In this preferred embodiment, data from different bases are centrally displayed, enabling different bases to view and benchmark against each other, so as to quickly identify indicators that need improvement.

[0042] Preferably, the pre-management module includes:

[0043] The intelligent maintenance plan unit is used to display inspection and maintenance plans, as well as inspection and maintenance lists;

[0044] The inspection and maintenance execution unit is used to execute the inspection and maintenance checklist, generate on-time inspection and maintenance execution rate data and transmit them to the evaluation model unit; and record the inspection and maintenance operation process and result details.

[0045] In this preferred embodiment, the tracking of inspection and maintenance plans is realized.

[0046] Preferably, the in-process management module includes:

[0047] The equipment status monitoring unit is used to collect technical status index data of the equipment PLC at a fixed frequency through the smart gateway, and compare it with the preset parameter thresholds. If the threshold is exceeded, an alarm will be issued.

[0048] The equipment status prediction unit is used to make predictions based on the collected technical status dimension index data, predict the future variation time of the data, and provide early warnings.

[0049] The Andon fault reporting unit is used to automatically trigger the Andon when the equipment status monitoring unit and / or equipment status prediction unit issues a warning, or to manually trigger the Andon when an abnormality is found during inspection, maintenance and production; and to transmit the Andon time-to-off time, average repair time and average fault interval time index data to the evaluation model unit in the equipment health evaluation module.

[0050] The auxiliary decision-making unit is used to output auxiliary decisions based on historical Andon data. The auxiliary decisions include anomaly type, average repair time, average fault interval time, the top N historical causes of occurrence, the top N improvement measures, and the top N corresponding problem-solving experts.

[0051] In this preferred embodiment, early warnings are achieved through status monitoring and prediction, enabling operators to quickly resolve problems and prevent equipment failures or quality abnormalities.

[0052] Preferably, the post-event management module includes:

[0053] The bottleneck process identification unit is used to calculate the actual production cycle time based on equipment load time and real-time output, and display it by process, identifying processes that exceed the required cycle time as bottleneck processes.

[0054] The TOP problem unit is used to break down the cycle time of the bottleneck process into a waterfall chart, break down the time loss that accounts for the largest proportion, and perform Pareto analysis on the classification of the decomposed losses. The loss classifications are arranged in order of time length to display the problem categories. The time loss classifications include: unplanned downtime, cycle time loss, and defect loss.

[0055] In this preferred embodiment, the bottleneck process identification unit is interconnected with the OEE system and generates output in real time through API interface calls, realizing the identification of bottleneck process cycle time and the analysis and display of lost time.

[0056] Preferably, the closed-loop management module includes:

[0057] The event function unit is used to create events. An event refers to the process of recording a problem and tracking the processing steps of each node to manage the problem in a closed loop. A problem refers to the improvement direction and improvement suggestions received by the closed loop management module.

[0058] The closed-loop statistics unit is used to calculate the on-time closure rate of events within a certain time period based on the planned completion time and actual completion time of events, and to calculate the on-time closure rate of events for different departments based on the responsible department.

[0059] The indicator linkage unit is used to assess whether the dimension indicators have improved after the implementation of the improvement project, in order to determine whether the dimension indicator is strongly correlated with the event.

[0060] In this preferred embodiment, by tracking and recording problems, it is determined whether the improvement of indicators is strongly correlated with the event, thus achieving closed-loop management.

[0061] The beneficial effects of this invention are:

[0062] This invention provides an equipment health management system that comprehensively evaluates equipment from three dimensions—technical status, performance indicators, and maintenance level—through real-time data collection. It derives a health score based on an evaluation model, identifies weak indicators by comparing them with target values, and automatically pushes improvement reminders. Through multi-dimensional closed-loop management—before, during, and after implementation—and by strongly linking closed-loop measures with indicator improvements, it ensures that improvement measures provide crucial support for enhancing equipment health. This invention enables transparent equipment management, multi-dimensional dynamic closed-loop management, and continuous healthy and efficient operation. It requires low investment, is easy to standardize, and facilitates large-scale deployment. Attached Figure Description

[0063] Figure 1 This is a schematic diagram of the device health management system provided in an embodiment of the present invention. Detailed Implementation

[0064] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The embodiments described below with reference to the accompanying drawings are illustrative and intended to explain the present invention, and should not be construed as limiting the present invention.

[0065] It should be noted that, as used in this invention, "an embodiment" or "embodiment" refers to a specific feature, structure, or characteristic that can be included in at least one implementation of this invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that excludes other embodiments.

[0066] It should be emphasized that the term "including / comprises" as used herein refers to the presence of a feature, element, step, or component, but does not exclude the presence or addition of one or more other features, elements, steps, or components.

[0067] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0068] See Figure 1 This invention provides an equipment health management system for a lithium battery production line, comprising:

[0069] The equipment health assessment module is used to determine the dimensions for evaluating equipment health, select indicators for these dimensions, build an evaluation model, and output equipment health scores. Simultaneously, based on the scores, it identifies weak indicators and automatically pushes improvement suggestions to the closed-loop management module.

[0070] The benchmarking management module is used to benchmark the same equipment within the same base and between different bases, identify equipment health gaps, conduct benchmarking learning, and create new thematic improvement projects to improve equipment health levels, achieving closed-loop management of internal and external benchmarking. By comparing the differences in equipment health scores across different bases, cross-base thematic improvement projects are automatically generated and pushed to the closed-loop management module.

[0071] The pre-operation management module is used to display and execute equipment inspection and maintenance plans, record the inspection and maintenance operation process and results details, provide improvement directions and push them to the closed-loop management module to achieve pre-operation closed-loop management.

[0072] The real-time management module is used to monitor and predict equipment process and result parameters in real time. It issues alerts when parameters are about to exceed thresholds, have already exceeded thresholds, or when malfunctions occur. It also allows for manual or automatic Andon fault reporting and provides an auxiliary decision-making interface during anomaly handling, achieving closed-loop management during the process. The top 5 improvement measures (top five by percentage) output by the auxiliary decision-making module are automatically linked to the closed-loop management module as input for special improvement projects.

[0073] The post-operation management module identifies bottleneck processes in automated production lines and automatically generates an abnormal downtime Pareto chart based on the number of downtimes or downtime duration to identify top equipment issues and achieve closed-loop post-operation management. After identifying the top issue categories through Pareto chart analysis, the issue classification and improvement suggestions are pushed to the closed-loop management module.

[0074] The closed-loop management module, based on the improvement directions identified by the above five modules, manually or automatically creates special improvement projects and conducts closed-loop tracking, and establishes a strong linkage between projects and indicators to monitor the effectiveness of improvement measures.

[0075] Specifically,

[0076] In this embodiment of the invention, the equipment health evaluation module includes an evaluation dimension unit, an evaluation model unit, an evaluation score unit, and a countermeasure push unit.

[0077] The evaluation dimension unit is used to evaluate equipment health from three dimensions: technical status, performance, and maintenance level, and to select the corresponding indicators for each dimension. Technical status indicators mainly include equipment operating parameters and key process parameters, such as temperature and wind speed; performance indicators mainly include efficiency, equipment process capacity, energy consumption, cost, and process quality-related indicators, such as OEE (Overall Equipment Effectiveness) and first-pass yield; maintenance level indicators mainly include inspection and maintenance-related indicators, such as on-time inspection and maintenance execution rates. All three dimensions of indicators are obtained through real-time equipment data acquisition or by retrieving data from other system modules.

[0078] The evaluation model unit is used to perform hierarchical evaluation of the indicators obtained from the evaluation dimension unit from four perspectives: efficiency, quality, cost, and energy consumption. It then assigns weights based on the scores, determining the weights of each evaluation dimension and the weights of each indicator within each dimension, and allocating indicator scores based on these weights. In this embodiment, the evaluation model unit uses the Analytic Hierarchy Process (AHP). Expert scoring determines the weight ratios w1, w2, w3, and w4 for the four dimensions of efficiency, quality, cost, and energy consumption. For example, efficiency might have a weight of 40%, quality 30%, cost 20%, and energy consumption 10%. The influence of equipment parameters on efficiency, quality, cost, and energy consumption is quantified using a matrix method, determining the weights of each equipment parameter indicator. Specifically, the input variables are equipment parameters, and the output variables are efficiency, quality, cost, and energy consumption. The influence of the input variables on the output variables in the matrix is ​​represented by a correlation score G, which is 0 (no correlation), 1 (weak correlation), 3 (medium correlation), and 9 (strong correlation). Then, the... The formula for the weighting of each device parameter is as follows: ,in, For the first The total score of each input factor (device parameter), This represents the number of device parameters. =G i1 *w 1* G i2 *w 2* G i3 *w 3* G i4 *w4, as in G i1 G i1 G i1 G i1 Representing the first The correlation score between equipment parameters and efficiency, quality, cost, and energy consumption is used, with w1, w2, w3, and w4 representing the weights of efficiency, quality, cost, and energy consumption, respectively. The sum of the weights of the parameters within the evaluation dimension is the weight of that evaluation dimension, and the standard score is assigned based on these weights. For example, if there are three indicators in the technical status dimension, A1, A2, and A3, with A1 having a weight of 5%, A2 having a weight of 10%, and A3 having a weight of 7%, then the standard scores for parameters A1, A2, and A3 are 5, 10, and 7 points, respectively. The weight of the technical status dimension indicator is 22%, and the indicator score is 22 points. The weights of the three dimensions may differ for different types of equipment, making the health assessment more realistic and accurate. The thresholds, evaluation rules, and scoring standards for each dimension indicator are also defined.

[0079] The evaluation scoring unit displays the indicators within each evaluation dimension collected in real time, and calculates the actual score of the indicator and the score of the evaluation dimension according to the set thresholds and evaluation rules. For technical status dimension indicators, a threshold evaluation method is used, and the data is real-time dynamic. For example, if the parameter of a technical status dimension is temperature, with a weight of 5% and an assigned standard score of 5 points, and its standard range is 26-32℃, and the real-time actual value is 33℃, then the actual score of this indicator is 0 points. For performance and maintenance level dimension indicators, a target percentage method is used, and the data is periodic. For example, if the indicator of performance dimension is OEE, with a weight of 15% and an assigned standard score of 15 points, and its target value is 70%, and the real-time actual value is 65%, then the actual score of this indicator is 15*(65 / 70) = 13.9 points; if the actual value is 71%, then the actual score of this indicator is 15 points. In summary, the score of the technical status dimension = ,in This represents the total number of parameter categories within the technical status dimension. For the first Actual score of each parameter indicator; score of performance dimension = ,in This represents the total number of indicator types within the performance dimension. For the first Actual score of each parameter indicator; maintenance level dimension score = ,in This represents the total number of indicator types within the maintenance level dimension. For the first The actual scores for each parameter indicator. Ultimately, the equipment health score = technical condition score + performance score + maintenance level score.

[0080] The countermeasure push unit is used to compare the actual score of the indicator with the standard score, identify the indicator whose score is lower than the standard score and whose difference from the standard score accounts for ≥20% of the standard score, highlight the indicator, and output the direction for improvement.

[0081] If the OEE index of equipment A is only 50%, which is lower than the target value of 70%, the difference is 20% (the difference accounts for 28.6%). The system will send emails to production and equipment personnel at fixed intervals, prompting them with messages such as "The OEE level of equipment A is low. Please output a special improvement project".

[0082] In this embodiment of the invention, the benchmarking management module includes a base benchmarking unit and an equipment benchmarking unit.

[0083] The base benchmarking unit displays the health scores of the same equipment at different bases, lists improvement projects for each base aimed at enhancing key indicators, and allows bases to view and benchmark against each other. New projects can also be created to support corresponding indicator improvements, and the entire project process is recorded. It's important to note that all bases use the same equipment health management system. Data transmission logic involves uploading data from the equipment PLC or host computer via the health evaluation system's API interface. The base benchmarking unit centrally displays data from all different bases.

[0084] The equipment benchmarking unit displays a radar chart showing the health scores of similar equipment within the base. A single radar chart clearly shows the scores of all similar equipment across various indicators, facilitating the rapid identification of indicators requiring improvement. It also allows for the creation of new thematic projects to support improvements in corresponding indicators and the recording of the entire project process.

[0085] In this embodiment of the invention, the pre-maintenance management module includes an intelligent maintenance planning unit and a point-of-care maintenance execution unit.

[0086] The intelligent maintenance plan unit is used to display inspection and maintenance plans and inspection and maintenance lists (the plans and lists are manually maintained into the system and can be imported in batches via standard Excel format).

[0087] The inspection and maintenance execution unit automatically pops up the inspection and maintenance interface on the mobile device based on the inspection and maintenance plan. Operators perform inspections and maintenance according to the detailed checklist. After completion, the inspection and maintenance records are synchronized to the equipment health management system, automatically generating on-time inspection and maintenance execution rate data for review, analysis, and application. The on-time inspection and maintenance execution rate indicators are then transmitted to the evaluation model unit within the equipment health evaluation module to calculate indicator scores.

[0088] In this embodiment of the invention, the real-time management module includes an equipment status monitoring unit, an equipment status prediction unit, an Andon fault reporting unit, and an auxiliary decision-making unit.

[0089] The equipment status monitoring unit is used to collect technical status index data of the equipment PLC at a fixed frequency through the smart gateway, and compare it with the preset parameter thresholds. If the threshold is exceeded, the system will issue an alarm and trigger the Andon.

[0090] The equipment status prediction unit is used to import the collected technical status dimension index data into the prediction model, predict the future variation time of the index parameters, and provide early warnings so that operators can quickly solve problems and prevent equipment failures or quality abnormalities. It should be noted that the prediction model of existing technology is used to predict the technical status dimension index data.

[0091] The Andon alarm unit is used to automatically trigger the Andon alarm when the equipment status monitoring unit and / or equipment status prediction unit issue a warning, or to manually trigger it when abnormalities or problems are found during inspection, maintenance, or production that require immediate handling. The Andon function mainly includes four modules: quality abnormality, equipment failure, process abnormality, and production line material shortage. After the Andon alarm is triggered, it automatically notifies the pre-set responsible person, who then handles and resolves the problem on-site. The person then fills in the cause, improvement measures, and implementation effects in the system. The Andon initiator evaluates and scores the actual handling situation in the system, or can choose to reject the alarm. The Andon alarm is turned off on time, and the MTTR (Mean Time To Repair) and MTBF (Mean Time Between Failures) data indicators are transmitted to the evaluation model unit in the equipment health evaluation module to calculate the indicator scores.

[0092] The decision support unit automatically imports historical Andon data (production line name, production line code, equipment name, equipment code, Andon module, Andon code & name, cause analysis, improvement measures, Andon start time, end time, duration, Andon reporter, and problem solver's name) into the decision support algorithm model. When the responsible person receives an Andon alert, they can see the decision support interface, which displays information such as the anomaly type, MTTR, MTBF, the top 5 historical causes (top 5 by percentage), the top 5 improvement measures, and the top 5 problem solvers, providing decision support for the responsible person to quickly resolve the problem.

[0093] In this embodiment of the invention, the post-process management module includes a bottleneck process identification unit and a top problem unit.

[0094] The bottleneck process identification unit is used to calculate the actual production cycle time based on equipment load time and real-time output, and display it in a bar chart by process. The bar chart of processes that exceed the required cycle time is marked in red for further improvement analysis. It should be noted that the bottleneck process identification unit is interconnected with the OEE system and can call the equipment load time and real-time output through the API interface.

[0095] The TOP Problem Unit is used to break down the cycle time of bottleneck processes using a waterfall chart. It further breaks down and analyzes the largest component, time loss, and then performs Pareto analysis on the resulting loss categories, arranging them in order of time duration to quickly display the top problem categories. The time loss categories mainly include: unplanned downtime, cycle time loss, and defect loss.

[0096] In this embodiment of the invention, the closed-loop management module includes an event function unit, a closed-loop statistics unit, and an indicator linkage unit.

[0097] The Event Function Unit is used to create events. Events are used to record problems and track the processing steps at each node, enabling closed-loop management of problems. Problems refer to items identified by the five modules above that require improvement. The nodes mainly include four key points: creating a new event, the responsible person conducting root cause analysis and filling out the form, the responsible person filling out the action plan, and the person who created the event approving or rejecting the issue to ensure it is closed-loop. The Event Function Unit achieves closed-loop management by outputting improvement directions and then combining the four nodes and indicators to determine whether improvements have truly been made.

[0098] The closed-loop statistics unit tracks a complete event, including the event initiation time, planned completion time, actual completion time, and responsible department. It calculates the on-time closure rate of events within a specific time period by comparing the planned and actual completion times. It also calculates the on-time closure rate for different departments based on their responsibility. The on-time closure rate, or on-time loop closure rate, is calculated using the formula: On-time Loop Closure Rate = Number of On-time Loop Closure Times / Total Number of Events Expected to be Closed Within the Statistical Time Scope. The previous modules analyze equipment, and identified issues are either manually created or automatically exported as improvement directions, thus forming events. The closed-loop statistics unit tracks these events in a closed-loop manner, currently supporting the closure and improvement of the aforementioned issues.

[0099] The indicator linkage unit is used to assess whether the indicator has significantly improved after the implementation of the improvement project, in order to determine whether the improvement of the indicator is strongly correlated with the event.

[0100] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. An equipment health management system for use in an automated lithium battery production line, characterized in that, include: The equipment health assessment module is used to determine the dimensions of equipment health assessment, screen the indicators of the assessment dimensions, build the assessment model and output the equipment health score, as well as identify the weak indicators and automatically push the direction of indicator improvement to the closed-loop management module. The benchmarking management module is used to benchmark the same equipment within the base and between different bases, generate cross-base thematic improvement projects and push them to the closed-loop management module. The pre-operation management module is used to display and execute equipment inspection and maintenance plans, record the inspection and maintenance process and results details, generate improvement directions and push them to the closed-loop management module; The real-time management module is used for real-time monitoring, prediction, and early warning of equipment process and result parameters; And automatically link improvement measures to the closed-loop management module; The post-processing management module is used to identify bottleneck processes and equipment problems in automated production lines, and to classify equipment problems and push improvement suggestions to the closed-loop management module. The closed-loop management module is used to create improvement projects based on the improvement directions and suggestions of each module, establish the linkage between improvement projects and indicators, and monitor the effectiveness of improvements.

2. The equipment health management system according to claim 1, characterized in that, The equipment health assessment module includes: The evaluation dimension unit is used to determine the evaluation dimensions of equipment health and to filter the indicators for each health evaluation dimension; the equipment health evaluation dimensions include three dimensions: technical status, performance, and maintenance level. The evaluation model unit is used to determine the weights of each health evaluation dimension indicator and to assign standard scores to the health evaluation dimension indicators based on their weights. The evaluation scoring unit is used to determine the actual score of the indicator based on the standard score of the indicator, and to obtain the health evaluation dimension score and the equipment health score based on the actual score of the indicator. The countermeasure push unit is used to identify weak indicators based on the equipment health score and the actual index score, and output directions for improvement.

3. The equipment health management system according to claim 2, characterized in that, The technical status dimension indicators include equipment operating parameters and key process parameters; the performance dimension indicators include efficiency, equipment process capacity, energy consumption, cost and process quality related indicators; and the maintenance level indicators include inspection and maintenance related indicators.

4. The equipment health management system according to claim 3, characterized in that, The evaluation model unit is specifically used for, The weights of the health evaluation indicators were determined using the analytic hierarchy process (AHP) from four dimensions: efficiency, quality, cost, and energy consumption. The impact of equipment parameters on efficiency, quality, cost, and energy consumption is quantified using the matrix method, resulting in a correlation score between equipment parameters and efficiency, quality, cost, and energy consumption. Based on the correlation scores of equipment parameters with efficiency, quality, cost, and energy consumption, and the weights of evaluation dimension indicators, the evaluation score of the equipment parameters is obtained, expressed as: =G i1 *w 1* G i2 *w 2* G i3 *w 3* G i4 *w4, where G i1 G i1 G i1 G i1 , representing the correlation scores of the i-th device parameter with efficiency, quality, cost, and energy consumption respectively, and w1, w2, w3, and w4 representing the weights of the evaluation dimensions of efficiency, quality, cost, and energy consumption respectively; Based on the evaluation scores of the equipment parameters, the index weights of the equipment parameters are obtained, expressed as follows: ,in, Indicates the first The weight of each device parameter index. Number of equipment parameters; The weights of the corresponding health evaluation dimensions are obtained by summing the weights of the parameters of each device within the health evaluation dimension. The standard scores for each indicator in the health evaluation dimension are assigned based on their weights.

5. The equipment health management system according to claim 4, characterized in that, The evaluation scoring unit is specifically used for, The values ​​of health assessment dimensions and indicators collected in real time are compared with preset target values. Based on the comparison results and the standard scores of the health evaluation dimension indicators, the actual scores of the health evaluation dimension indicators are determined. The sum of the actual scores of all health assessment dimensions is the score of the corresponding health assessment dimension. The sum of the scores from the three health evaluation dimensions is the equipment health score.

6. The equipment health management system according to claim 5, characterized in that, The countermeasure push unit is specifically used for, By comparing the actual scores of the health assessment dimensions with the standard scores, indicators with scores lower than the standard scores and a difference of ≥20% from the standard scores are identified as weak indicators, and directions for improvement are provided.

7. The equipment health management system according to claim 2, characterized in that, The benchmarking management module includes: The base benchmarking unit is used to display the health scores of the same equipment in different bases, as well as to list the special improvement projects that improve the indicators of different bases, so that different bases can view, benchmark and learn from each other. The equipment benchmarking unit is used to display a radar chart showing the health scores of similar equipment within the base.

8. The equipment health management system according to claim 2, characterized in that, The pre-management module includes: The intelligent maintenance plan unit is used to display inspection and maintenance plans, as well as inspection and maintenance lists; The inspection and maintenance execution unit is used to execute the inspection and maintenance checklist, generate on-time inspection and maintenance execution rate data and transmit them to the evaluation model unit; and record the inspection and maintenance operation process and result details.

9. The equipment health management system according to claim 2, characterized in that, The in-process management module includes: The equipment status monitoring unit is used to collect technical status index data of the equipment PLC at a fixed frequency through the smart gateway, and compare it with the preset parameter thresholds. If the threshold is exceeded, an alarm will be issued. The equipment status prediction unit is used to make predictions based on the collected technical status dimension index data, predict the future variation time of the data, and provide early warnings. The Andon fault reporting unit is used to automatically trigger the Andon when the equipment status monitoring unit and / or equipment status prediction unit issues a warning, or to manually trigger the Andon when an abnormality is found during inspection, maintenance and production; and to transmit the Andon time-to-off time, average repair time and average fault interval time index data to the evaluation model unit in the equipment health evaluation module. The auxiliary decision-making unit is used to output auxiliary decisions based on historical Andon data. The auxiliary decisions include anomaly type, average repair time, average fault interval time, the top N historical causes of occurrence, the top N improvement measures, and the top N corresponding problem-solving experts.

10. The equipment health management system according to claim 2, characterized in that, The post-event management module includes: The bottleneck process identification unit is used to calculate the actual production cycle time based on equipment load time and real-time output, and display it by process, identifying processes that exceed the required cycle time as bottleneck processes. The TOP problem unit is used to break down the cycle time of the bottleneck process into a waterfall chart, break down the time loss that accounts for the largest proportion, and perform Pareto analysis on the classification of the decomposed losses. The loss classifications are arranged in order of time length to display the problem categories. The time loss classifications include: unplanned downtime, cycle time loss, and defect loss.

11. The equipment health management system according to claim 2, characterized in that, The closed-loop management module includes: The event function unit is used to create events. An event refers to the process of recording a problem and tracking the processing steps of each node to manage the problem in a closed loop. A problem refers to the improvement direction and improvement suggestions received by the closed loop management module. The closed-loop statistics unit is used to calculate the on-time closure rate of events within a certain time period based on the planned completion time and actual completion time of events, and to calculate the on-time closure rate of events for different departments based on the responsible department. The indicator linkage unit is used to assess whether the dimension indicators have improved after the implementation of the improvement project, in order to determine whether the dimension indicator is strongly correlated with the event.

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