A maintenance management system and method based on intelligent diagnosis of garment production equipment

Abstract

The application provides a kind of maintenance management method and system based on clothing production equipment intelligent diagnosis, belong to maintenance management technical field, specifically include: in production line, the clothing production equipment that is handled in operation and maintenance in combination with operation and maintenance associated fault type is as reliable operation and maintenance production equipment, based on the reliable operation and maintenance production equipment in production line and the quantity of operation and maintenance associated fault type of clothing production equipment data that does not meet the requirement, determine the overall operation and maintenance management strategy in production line, based on operation and maintenance management strategy, the identification missing condition of the fault type of different clothing production equipment is obtained, based on the matching degree of identification missing condition in different clothing production equipment and operation and maintenance associated fault type and operation and maintenance management strategy, determine the updating processing method of reliable operation and maintenance production equipment, ensure the reliability and matching degree of operation and maintenance processing.

Description

Technical Field

[0001] This invention belongs to the field of maintenance management technology, and in particular relates to a maintenance management system and method based on intelligent diagnosis of garment production equipment. Background Technology

[0002] Garment manufacturing enterprises have a high equipment density; a single production line may contain dozens of different types of sewing machines, and the operating status of these machines directly affects product quality and delivery cycle. Traditional equipment maintenance mainly adopts two models: one is reactive maintenance—maintenance is arranged only after equipment failure and downtime, resulting in unplanned line stoppages and production delays; the other is periodic maintenance—all equipment is uniformly maintained at fixed intervals (such as monthly or quarterly), regardless of the actual operating status of the equipment.

[0003] To address the aforementioned technical problems, existing solutions assess the operational status of garment production equipment using monitoring data from monitoring devices and then perform targeted maintenance based on the assessment results. However, this approach suffers from the following technical issues: When performing operation and maintenance of garment production equipment, the reliability of fault identification and handling for different garment production equipment is crucial to the overall reliability of operation and maintenance. Therefore, determining the operation and maintenance management strategy for the production line and its different garment production equipment based on the reliability of fault identification and handling for different garment production equipment in the production line, thereby improving the reliability of fault identification and handling, has become an urgent technical problem to be solved.

[0004] In summary, to solve the above-mentioned technical problems, this application provides a maintenance management system and method based on intelligent diagnosis of garment production equipment. Summary of the Invention

[0005] To achieve the objectives of this invention, the following technical solution is adopted: Specifically, in the first aspect, this application provides a maintenance management method based on intelligent diagnostics of garment production equipment, which specifically includes: S1 uses fault diagnosis data of garment production equipment to determine the fault type of garment production equipment that requires operation and maintenance processing based on the diagnosis results, and uses it as the operation and maintenance associated fault type of garment production equipment. S2 determines the matching degree of operation and maintenance processing for different garment production equipment based on the operation and maintenance associated fault types of different garment production equipment. Based on the matching degree of operation and maintenance processing for different garment production equipment in the production line and the data of garment production equipment in the production line, S2 determines the garment production equipment in the production line that should be operated and maintained in combination with the operation and maintenance data under the operation and maintenance associated fault types. S3 takes the garment production equipment in the production line that is processed by combining the operation and maintenance data under the operation and maintenance associated fault type as the reliable operation and maintenance production equipment. Based on the reliable operation and maintenance production equipment in the production line and the data of garment production equipment whose number of operation and maintenance associated fault types does not meet the requirements, the overall operation and maintenance management strategy in the production line is determined. S4 obtains the identification omissions of different fault types of garment production equipment based on the operation and maintenance management strategy. Based on the matching degree between the identification omissions of different garment production equipment and the operation and maintenance related fault types, as well as the operation and maintenance management strategy, the update processing method of the reliable operation and maintenance production equipment is determined.

[0006] The beneficial effects of this invention are as follows: Based on the diagnostic results of garment production equipment under different fault types, the reliability of diagnostic processing for garment production equipment under different fault types is determined. Based on the reliability of diagnostic processing for garment production equipment under different fault types, the operation and maintenance associated fault types of garment production equipment are determined, laying the foundation for determining different operation and maintenance associated strategies for garment production equipment based on the operation and maintenance associated fault types.

[0007] Based on the omissions in the identification of garment equipment and the degree of matching between the omission risk fault types in the fault types of garment production equipment and the maintenance-related fault types, the risk of omissions in the identification of fault types of garment production equipment in the production line is determined. Based on the risk of omissions in the identification of fault types of garment production equipment in the production line, the update and processing methods for reliable maintenance production equipment are determined, thereby further ensuring the pertinence and matching degree of maintenance processing.

[0008] Furthermore, the fault diagnosis data of the garment production equipment includes the diagnostic results of the garment production equipment under different fault types.

[0009] Furthermore, the method for determining the operation and maintenance-related fault types of the garment production equipment is as follows: Based on the fault diagnosis data of the garment production equipment, determine the number of fault diagnoses of the garment production equipment under the fault type; Based on the number of fault diagnoses and the accuracy of fault diagnoses under the fault type, it is determined whether the fault type belongs to the operation and maintenance related fault type of garment production equipment.

[0010] Furthermore, when the number of fault diagnoses and the accuracy of fault diagnosis under the fault type both meet the requirements, the number of fault diagnoses is relatively large and the accuracy of fault diagnosis is also relatively high. Specifically, this is determined by a threshold method, and then the fault type is determined to belong to the operation and maintenance related fault type of garment production equipment.

[0011] Furthermore, if the fault type belongs to the operation and maintenance related fault type of the garment production equipment, then as long as the fault diagnosis model identifies the operation and maintenance management fault type, the operation and maintenance of the garment production equipment will be carried out. For other fault types identified by the fault diagnosis model, only the relevant fault type investigation and processing are required.

[0012] Furthermore, the matching degree of operation and maintenance of the garment production equipment in the production line is determined based on the matching degree between the number of operation and maintenance-related fault types of the garment production equipment in the production line and the total number of fault types.

[0013] Furthermore, the method for determining the update processing method for the reliable operation and maintenance production equipment is as follows: S41 Based on the identified omissions, determine the number of times the garment production equipment was identified in different fault types, and determine the omission risk fault type among the fault types of the garment production equipment according to the number of identified omissions; S42 determines the maintenance matching risk value of the garment production equipment based on the degree of matching between the omission risk fault type and the maintenance-related fault type in the fault types of the garment production equipment. S43 determines the update processing method for the reliable maintenance production equipment based on the operation and maintenance matching risk value of different garment production equipment and the operation and maintenance management strategy.

[0014] Secondly, this application provides a maintenance management system based on intelligent diagnostics of garment production equipment, employing the aforementioned maintenance management method based on intelligent diagnostics of garment production equipment, specifically including: Fault type filtering module, operation and maintenance management module, update processing module; The fault type filtering module is responsible for determining the operation and maintenance-related fault types of the garment production equipment. The operation and maintenance management module is responsible for determining the overall operation and maintenance management strategy for the production line; The update processing module is responsible for determining the update processing method for the reliable operation and maintenance production equipment.

[0015] Other features and advantages will be set forth in the following description, and the objects and other advantages of the invention are realized and obtained through the structures particularly pointed out in the description and the drawings.

[0016] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0017] The above and other features and advantages of the present invention will become more apparent from a detailed description of exemplary embodiments thereof with reference to the accompanying drawings.

[0018] Figure 1 This is a flowchart of a maintenance management method based on intelligent diagnostics for garment production equipment; Figure 2 This is a flowchart illustrating the method for determining the types of operation and maintenance-related faults in garment production equipment; Figure 3 This is a framework diagram of a maintenance management system based on intelligent diagnostics for garment production equipment. Detailed Implementation

[0019] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0020] Example 1 like Figure 1 As shown, this application provides a maintenance management method based on intelligent diagnostics for garment production equipment, specifically including: S1 uses fault diagnosis data of garment production equipment to determine the fault type of garment production equipment that requires operation and maintenance processing based on the diagnosis results, and uses it as the operation and maintenance associated fault type of garment production equipment. S2 determines the matching degree of operation and maintenance processing for different garment production equipment based on the operation and maintenance associated fault types of different garment production equipment. Based on the matching degree of operation and maintenance processing for different garment production equipment in the production line and the data of garment production equipment in the production line, S2 determines the garment production equipment in the production line that should be operated and maintained in combination with the operation and maintenance data under the operation and maintenance associated fault types. S3 takes the garment production equipment in the production line that is processed by combining the operation and maintenance data under the operation and maintenance associated fault type as the reliable operation and maintenance production equipment. Based on the reliable operation and maintenance production equipment in the production line and the data of garment production equipment whose number of operation and maintenance associated fault types does not meet the requirements, the overall operation and maintenance management strategy in the production line is determined. S4 obtains the identification omissions of different fault types of garment production equipment based on the operation and maintenance management strategy. Based on the matching degree between the identification omissions of different garment production equipment and the operation and maintenance related fault types, as well as the operation and maintenance management strategy, the update processing method of the reliable operation and maintenance production equipment is determined.

[0021] Specifically, the fault diagnosis data of the garment production equipment includes the diagnostic results of the garment production equipment under different fault types.

[0022] Specifically, such as Figure 2 As shown, the method for determining the operation and maintenance associated fault types of the garment production equipment is as follows: In this embodiment, the reliability of the diagnostic processing of garment production equipment under different fault types is determined based on the diagnostic results of the garment production equipment under different fault types. Based on the reliability of the diagnostic processing of garment production equipment under different fault types, the operation and maintenance associated fault types of garment production equipment are determined, laying the foundation for determining different operation and maintenance associated strategies of garment production equipment based on the operation and maintenance associated fault types of garment production equipment.

[0023] The core objective of this embodiment is to determine the maintenance-related fault types through fault diagnosis data of garment production equipment, identify reliable maintenance production equipment and overall maintenance management strategies based on these fault types, and then update the reliable maintenance production equipment according to any omissions in fault type identification. Its core logic uses fault diagnosis data as input, first determining the maintenance-related fault types through the number of diagnoses and diagnostic accuracy, then identifying reliable maintenance production equipment through the degree of matching between maintenance processing and equipment data, subsequently determining the overall maintenance management strategy based on the reliable maintenance production equipment and the maintenance-related fault type data, and finally determining the update processing method for reliable maintenance production equipment based on the degree of matching between omissions and maintenance-related fault types. The overall logic follows the process of "determining maintenance-related fault types → determining reliable maintenance production equipment → determining maintenance management strategies → determining update processing methods."

[0024] Specifically, the fault diagnosis data of the garment production equipment includes the diagnostic results of the garment production equipment under different fault types.

[0025] The fault diagnosis data refers to the record of results obtained by the fault diagnosis model of the garment production equipment in diagnosing different types of faults during its historical operation, including information such as the number of diagnoses and the accuracy rate of diagnosis.

[0026] Suppose a garment production equipment is equipped with a fault diagnosis model. This model has diagnosed various types of faults during its historical operation, and the results of each diagnosis are recorded to form the fault diagnosis data of the equipment.

[0027] This step clarifies the content of fault diagnosis data. Its significance lies in using historical diagnosis results as an objective basis for determining the types of faults associated with operation and maintenance, thereby avoiding the one-sidedness of relying solely on theoretical fault modes for operation and maintenance decisions.

[0028] Specifically, such as Figure 2 As shown, the method for determining the operation and maintenance associated fault types of the garment production equipment is as follows: In this embodiment, the reliability of the diagnostic processing of garment production equipment under different fault types is determined based on the diagnostic results of the garment production equipment under different fault types. Based on the reliability of the diagnostic processing of garment production equipment under different fault types, the operation and maintenance associated fault types of garment production equipment are determined, laying the foundation for determining different operation and maintenance associated strategies of garment production equipment based on the operation and maintenance associated fault types of garment production equipment.

[0029] The operation and maintenance associated fault type refers to the fault type that requires operation and maintenance processing based on the diagnostic results. That is, the fault type that triggers operation and maintenance processing is the fault type that is identified by the fault diagnosis model. The reliability of the diagnostic processing refers to the credibility of the diagnostic results of the fault diagnosis model for a specific fault type, which is reflected by the number of diagnoses and the diagnostic accuracy.

[0030] If a fault diagnosis model for a certain garment production equipment diagnoses a certain type of fault frequently and with high accuracy, then the reliability of the diagnosis and handling of this fault type is high, and it is more likely to be identified as an operation and maintenance related fault type.

[0031] This step determines the type of operation and maintenance-related faults by assessing the reliability of the diagnostic process. Its significance lies in transforming the performance of the diagnostic model into a basis for operation and maintenance decisions, thereby ensuring that the operation and maintenance process targets the fault types that the diagnostic model can reliably identify.

[0032] S11. Using the fault diagnosis data of the garment production equipment, determine the number of fault diagnoses of the garment production equipment under the fault type; The number of fault diagnosis counts refers to the total number of times the fault diagnosis model diagnoses a certain type of fault during its historical operation.

[0033] Suppose that a fault diagnosis model for a certain garment production equipment has performed multiple diagnoses for a certain fault type during its historical operation. The total number of these diagnoses is then the number of fault diagnoses for that fault type.

[0034] This step, by counting the number of fault diagnoses, is significant in that it provides a quantitative basis for determining whether the fault type belongs to the operation and maintenance related fault type in the subsequent determination of the diagnostic frequency dimension.

[0035] S12 determines whether the fault type belongs to the operation and maintenance related fault type of the garment production equipment based on the number of fault diagnoses and the fault diagnosis accuracy under the fault type.

[0036] The fault diagnosis accuracy rate refers to the proportion of correct diagnoses in the fault diagnosis model's diagnostic results for a certain type of fault.

[0037] If a certain fault type has a high number of fault diagnoses and a high accuracy rate, then that fault type is identified as a maintenance-related fault type for garment production equipment.

[0038] This step combines the number of diagnostics and the diagnostic accuracy to determine whether the fault type belongs to the operation and maintenance related fault type. Its significance lies in ensuring the reliability of the operation and maintenance related fault type determination from two dimensions: diagnostic frequency and diagnostic quality.

[0039] It is understandable that when the number of fault diagnoses and the accuracy of fault diagnosis under the fault type both meet the requirements, the number of fault diagnoses is relatively large and the accuracy of fault diagnosis is also relatively high. Specifically, it is determined by a threshold method, and then the fault type is determined to belong to the operation and maintenance related fault type of garment production equipment.

[0040] The phrase "meeting the requirements" means that the number of fault diagnoses is not less than the preset threshold for the number of diagnoses and the accuracy rate of fault diagnosis is not less than the preset accuracy rate threshold.

[0041] If the number of fault diagnoses for a certain fault type reaches a preset threshold and the fault diagnosis accuracy reaches a preset accuracy threshold, then the fault type meets the requirements and belongs to the maintenance-related fault type of garment production equipment.

[0042] This step clarifies the criteria for determining operation and maintenance-related fault types. Its significance lies in ensuring, through dual threshold conditions, that the fault types identified as operation and maintenance-related fault types have sufficient reliability in terms of both diagnostic frequency and diagnostic quality.

[0043] The reference factors for the preset diagnostic frequency threshold include the historical operating time of the garment production equipment, the diagnostic cycle of the fault diagnosis model, and the frequency of occurrence of the fault type. The reference factors for determining the preset accuracy threshold include the training data scale of the fault diagnosis model, the feature discrimination of the fault type, and the verification feedback of the diagnostic results from historical operation and maintenance.

[0044] Specifically, if the fault type belongs to the operation and maintenance related fault type of the garment production equipment, then as long as the fault diagnosis model identifies the operation and maintenance management fault type, the operation and maintenance of the garment production equipment will be carried out. For other fault types identified by the fault diagnosis model, only the relevant fault type investigation and processing are required.

[0045] The operation and maintenance processing refers to the comprehensive maintenance processing triggered by operation and maintenance-related fault types; the investigation and processing refers to the preliminary inspection and processing of non-operation and maintenance-related fault types, and the processing intensity is weaker than that of operation and maintenance processing.

[0046] If a certain fault type is identified as an operation and maintenance related fault type of a certain garment production equipment, then when the fault diagnosis model identifies this fault type, it will directly carry out operation and maintenance processing. If other fault types are identified, it will only carry out troubleshooting processing.

[0047] This step clarifies the handling rules for operation and maintenance related fault types. Its significance lies in adopting differentiated handling intensity for different fault types, thereby ensuring the reliability of operation and maintenance while avoiding over-handling of low-risk fault types.

[0048] Furthermore, the matching degree of operation and maintenance of the garment production equipment in the production line is determined based on the matching degree between the number of operation and maintenance-related fault types of the garment production equipment in the production line and the total number of fault types.

[0049] The matching degree of the operation and maintenance processing refers to the proportion of the number of operation and maintenance related fault types of the garment production equipment to the total number of fault types, reflecting the operation and maintenance coverage of the equipment.

[0050] Suppose a garment production equipment has multiple fault types, some of which are identified as maintenance-related fault types. The ratio of the number of maintenance-related fault types to the total number of fault types is the degree of matching between maintenance and operation.

[0051] This step clarifies the basis for calculating the matching degree of operation and maintenance, and its significance lies in quantifying the coverage of operation and maintenance-related fault types into a comparable matching degree indicator.

[0052] Specifically, the method for determining the reliable operation and maintenance production equipment is as follows: In this embodiment, the reliability of maintenance processing under the current maintenance-related fault type is determined by the matching degree of maintenance processing of different garment production equipment in the production line and the data of garment production equipment in the production line. Based on the reliability of maintenance processing under the current maintenance-related fault type, reliable maintenance production equipment in the production line is determined, thereby further improving the reliability of maintenance processing in the entire production line.

[0053] The reliable operation and maintenance production equipment refers to garment production equipment in the production line with a high degree of reliability in operation and maintenance. More precise operation and maintenance strategies are adopted for this type of equipment.

[0054] If a garment production equipment has a high degree of matching in operation and maintenance and meets other conditions, then the equipment is identified as a reliable production equipment for operation and maintenance, and a differentiated operation and maintenance strategy is adopted.

[0055] This step identifies reliable production equipment for operation and maintenance by assessing the matching degree of operation and maintenance processes and equipment data. Its significance lies in identifying equipment with high operation and maintenance reliability from the production line, providing a basis for the differentiated determination of subsequent overall operation and maintenance management strategies.

[0056] S21 determines the ratio of the number of operation and maintenance related fault types of the garment production equipment in the production line to the number of all fault types based on the matching degree of operation and maintenance processing of different garment production equipment in the production line, and uses it as the diagnostic matching coefficient of the garment production equipment. The diagnostic matching coefficient refers to the ratio of the number of operation and maintenance-related fault types of garment production equipment to the total number of fault types, and its value ranges from 0 to 1.

[0057] Suppose a garment production equipment has 10 types of faults, of which 6 are identified as maintenance-related fault types, then the diagnostic matching coefficient = 6 / 10 = 0.6.

[0058] This step calculates the diagnostic matching coefficient using a ratio. Its significance lies in quantifying the coverage of operation and maintenance-related fault types into comparable coefficient values, providing a quantitative basis for determining reliable operation and maintenance production equipment in the future.

[0059] S22 determines the number of garment production equipment in the production line based on the data of the garment production equipment in the production line; If a production line contains multiple garment production machines, the total number of machines is the number of garment production machines in the production line.

[0060] This step, by counting the number of devices, is significant because it provides a basis for determining the scale of reliable production equipment to be maintained based on the differences in the number of devices.

[0061] It is understandable that if the number of garment production equipment in the production line does not meet the requirements in the above steps, there are a large number of garment production equipment at this time. Therefore, in order to ensure the operational reliability of the garment production equipment in the production line, the reliable operation and maintenance production equipment is determined to be the production equipment whose diagnostic matching coefficient is less than the preset matching coefficient threshold.

[0062] The term "not meeting the requirements" refers to a situation where the number of garment production equipment is too large, exceeding the preset equipment quantity threshold; the preset matching coefficient threshold refers to the critical value for judging whether the diagnostic matching coefficient is too low.

[0063] Assuming there are a large number of garment production equipment in the production line, in order to ensure the overall operational reliability, equipment with a diagnostic matching coefficient less than the preset matching coefficient threshold is identified as reliable production equipment for operation and maintenance.

[0064] This step employs a simple determination strategy when there are a large number of devices. Its significance lies in the fact that when there are a large number of devices, reliable production equipment can be quickly identified by directly using the diagnostic matching coefficient as a screening condition, thereby simplifying the processing flow.

[0065] The preset matching coefficient threshold is based on factors including the total number of garment production equipment in the production line, the capacity of operation and maintenance resources, and the coverage of historical operation and maintenance.

[0066] It should also be noted that if the number of garment production equipment in the production line meets the requirements, proceed to step S23; The term "meeting the requirements" refers to the situation where the number of garment production equipment is small and does not exceed the preset equipment quantity threshold. If the number of garment production equipment in the production line is small, then proceed to S23 for more precise determination of reliable operation and maintenance production equipment.

[0067] This step moves to further analysis when the number of devices is small. Its significance lies in ensuring the accuracy of determining reliable operation and maintenance of production equipment through more refined classification judgment when the number of devices is small.

[0068] S23 uses the diagnostic matching coefficients of different garment production equipment in the production line and the number of garment production equipment to determine the reliable operation and maintenance production equipment in the production line.

[0069] Assuming that the diagnostic matching coefficients and the number of equipment for each garment production equipment have been determined, reliable production equipment for operation and maintenance are determined based on the judgment results of S231, S232 and S233.

[0070] This step, which combines diagnostic matching coefficients and the number of devices, determines reliable production equipment for operation and maintenance. Its significance lies in enabling adaptive adjustment of the strategy for determining reliable production equipment for operation and maintenance.

[0071] It is understood that, by utilizing the diagnostic matching coefficients of different garment production equipment in the production line and the number of garment production equipment, the reliable operation and maintenance production equipment in the production line is determined, specifically including: S231 uses the diagnostic matching coefficients of different garment production equipment in the production line to identify garment production equipment whose diagnostic matching coefficients meet the requirements as matching production equipment. It then determines whether there is matching production equipment in the production line. If yes, proceed to step S232. If no, determine that the reliable operation and maintenance production equipment is a production equipment whose diagnostic matching coefficient is less than the preset matching coefficient threshold. It should be noted that the matching production equipment refers to garment production equipment with a high diagnostic matching coefficient, which is specifically determined by a threshold method.

[0072] The phrase "meets the requirements" refers to a situation where the diagnostic matching coefficient is high and reaches or exceeds the preset matching coefficient threshold; the phrase "matching production equipment" refers to garment production equipment with a high diagnostic matching coefficient.

[0073] If there are devices in the production line whose diagnostic matching coefficient reaches or exceeds the preset matching coefficient threshold, these devices are considered matched production devices, and the process proceeds to S232 for further analysis. If there are no matched production devices, then devices whose diagnostic matching coefficient is less than the preset matching coefficient threshold are identified as reliable operation and maintenance production devices.

[0074] This step determines the strategy by matching whether the production equipment exists. The significance is that when highly matched equipment exists, a more detailed analysis can be performed, and when no matching equipment exists, a simple strategy can be adopted to ensure processing efficiency.

[0075] S232 Obtain the proportion of the matched production equipment in the garment production equipment in the production line, and determine whether the proportion of the matched production equipment in the garment production equipment in the production line is within the target proportion range. If so, it means that the number of matched production equipment is large and the reliability of operation and maintenance is high. Therefore, the reliable operation and maintenance production equipment is determined to be the production equipment whose diagnostic matching coefficient is less than the preset matching coefficient threshold and the number of operation and maintenance associated fault types is less than the associated fault type threshold. If not, proceed to step S233. The target ratio range refers to the range within which the proportion of matched production equipment is increased; the associated fault type threshold refers to the critical value for determining whether the number of associated fault types in operation and maintenance is relatively small.

[0076] If the proportion of matched production equipment is within the target proportion range, it indicates that there are a large number of matched equipment and the operation and maintenance reliability is high. In this case, the equipment with a diagnostic matching coefficient less than the preset matching coefficient threshold and a number of operation and maintenance related fault types less than the related fault type threshold is identified as reliable operation and maintenance production equipment. If the proportion is not within the range, proceed to S233 for further analysis.

[0077] This step determines whether a strict screening strategy should be adopted by matching the proportion of production equipment. Its significance lies in using dual-condition screening when the proportion of matched equipment is appropriate to ensure the accuracy of reliable operation and maintenance of production equipment.

[0078] The target ratio range is determined by factors including the total number of garment production equipment in the production line, the typical proportion of matching production equipment in historical operation and maintenance, and the allocation capacity of operation and maintenance resources.

[0079] S233 determines the diagnostic matching value based on the average value of the diagnostic matching coefficients of different garment production equipment in the production line and the average proportion of the matched production equipment in the garment production line. It then determines whether the diagnostic matching value meets the requirements. If yes, the diagnostic matching coefficient is high, and the reliable maintenance production equipment is determined to be the production equipment whose diagnostic matching coefficient is less than the preset matching coefficient threshold and whose number of maintenance-related fault types is less than the associated fault type threshold. If not, the reliable maintenance production equipment is determined to be the production equipment whose diagnostic matching coefficient is less than the preset matching coefficient threshold and whose number of maintenance-related fault types is less than the associated fault type threshold, or whose number of fault types that have not undergone fault diagnosis in history is greater than the preset number of types.

[0080] The diagnostic matching value refers to a quantitative indicator calculated by combining the average of the comprehensive diagnostic matching coefficients and the proportion of matched production equipment.

[0081] The diagnostic matching value is calculated as follows: Let Mavg be the mean of the diagnostic matching coefficients of different garment production equipment in the production line, and Pmatch be the proportion of matched production equipment in the garment production line. Then: Diagnostic match value = Mavg × Pmatch.

[0082] The "meeting the requirements" refers to the situation where the diagnostic matching value is not lower than the preset diagnostic matching value threshold; the preset value for the number of types refers to the critical value for judging whether the number of fault types that have not undergone fault diagnosis and processing in the history is too large.

[0083] If the diagnostic matching value meets the requirements, it indicates that the overall diagnostic matching degree is high. In this case, a strict screening strategy with the same path as S232 is adopted. If the diagnostic matching value does not meet the requirements, a lenient screening strategy is adopted. Devices with a diagnostic matching coefficient less than the preset matching coefficient threshold, a number of operation and maintenance associated fault types less than the associated fault type threshold, or a number of fault types that have not undergone fault diagnosis and processing in history greater than the preset number of types are identified as reliable operation and maintenance production devices.

[0084] This step further refines the strategy for determining reliable production equipment by using diagnostic matching values. Its significance lies in dynamically adjusting the stringency of the screening criteria based on the diagnostic matching values ​​when the proportion of matched production equipment is not within the target proportion range, thereby achieving a balance between the accuracy and coverage of the determination of reliable production equipment.

[0085] When determining the preset diagnostic matching value threshold, the reference factors include the distribution characteristics of the diagnostic matching coefficients of garment production equipment in the production line, the historical proportion fluctuation range of matching production equipment, and the reliability requirement level of operation and maintenance.

[0086] It should be noted that if the production equipment is a reliable maintenance production equipment, then if there is no period for maintenance processing based on the fault diagnosis results of the maintenance-related fault type within the most recent preset time period, then the production equipment will be subjected to maintenance processing.

[0087] The preset duration refers to the time window for determining whether reliable maintenance production equipment needs to trigger maintenance processing.

[0088] If a reliable production equipment has not undergone maintenance processing due to the diagnosis results of maintenance-related fault types within the most recent preset time period, then maintenance processing will be performed on the equipment to ensure its operational reliability.

[0089] This step clarifies the operation and maintenance triggering rules for reliable operation and maintenance production equipment. Its significance lies in ensuring that reliable operation and maintenance production equipment can still receive regular operation and maintenance even when there is no diagnostic trigger, thereby avoiding operation and maintenance omissions caused by diagnostic model omissions.

[0090] This embodiment, through steps S21 to S23, realizes a complete process from calculating the diagnostic matching coefficient to determining the number of devices and then determining reliable operation and maintenance production equipment. Its core value is reflected in three aspects: First, it quantifies the coverage of operation and maintenance-related fault types through the diagnostic matching coefficient, providing a quantitative basis for determining reliable operation and maintenance production equipment; second, it dynamically adjusts the determination strategy when the number of devices and the degree of matching are different through the hierarchical judgment of the number of devices and the proportion of matching production equipment; and third, it adopts differentiated screening conditions when the degree of matching is different through further subdivision of the diagnostic matching value, thereby achieving an adaptive balance between the accuracy and coverage of reliable operation and maintenance production equipment determination.

[0091] A garment production line consists of eight garment production machines, E1 to E8. Each machine is equipped with a fault diagnosis model capable of identifying multiple fault types. Taking machine E1 as an example, the fault diagnosis model for E1 can identify 10 fault types, F1 to F10. Historical diagnostic data is as follows: F1: 25 diagnoses, accuracy 0.92; F2: 20 diagnoses, accuracy 0.88; F3: 15 diagnoses, accuracy 0.85; F4: 8 diagnoses, accuracy 0.75; F5: 5 diagnoses, accuracy 0.60; F6: 3 diagnoses, accuracy 0.50; F7: 12 diagnoses, accuracy 0.82; F8: 18 diagnoses, accuracy 0.90; F9: 2 diagnoses, accuracy 0.40; F10: 0 diagnoses (no fault diagnosis or handling in the past).

[0092] The preset threshold for the number of diagnoses is set at 10, and the preset accuracy threshold is set at 0.80.

[0093] Steps S11~S12: Determine whether each fault type belongs to the maintenance-related fault type of E1.

[0094] F1: The number of diagnoses is 25≥10 and the accuracy is 0.92≥0.80, which meets the requirements and belongs to the operation and maintenance related fault type.

[0095] F2: The number of diagnoses is ≥10 and the accuracy is ≥0.88, which meets the requirements and belongs to the operation and maintenance related fault type.

[0096] F3: The number of diagnoses is 15≥10 and the accuracy is 0.85≥0.80, which meets the requirements and belongs to the operation and maintenance related fault type.

[0097] F4: Number of diagnostics 8 < 10, does not meet the requirements, and does not belong to the operation and maintenance related fault type.

[0098] F5: Number of diagnostics 5 < 10, does not meet the requirements, and does not belong to the operation and maintenance related fault type.

[0099] F6: Number of diagnostics 3 < 10, does not meet the requirements, and does not belong to the operation and maintenance related fault type.

[0100] F7: The number of diagnoses is 12≥10 and the accuracy is 0.82≥0.80, which meets the requirements and belongs to the operation and maintenance related fault type.

[0101] F8: The number of diagnoses is 18≥10 and the accuracy is 0.90≥0.80, which meets the requirements and belongs to the operation and maintenance related fault type.

[0102] F9: The number of diagnostic attempts is less than 10, which does not meet the requirements and does not belong to the maintenance-related fault type.

[0103] F10: Number of diagnostics 0 < 10, does not meet the requirements, and does not belong to the operation and maintenance related fault type.

[0104] The operation and maintenance associated fault types for E1 are F1, F2, F3, F7, and F8, totaling 5 types.

[0105] Similarly, the same analysis process was applied to E2 through E8, and the number of maintenance-related fault types for each device was obtained as follows: E1: 5 types; E2: 4 types; E3: 6 types; E4: 3 types; E5: 5 types; E6: 2 types; E7: 7 types; E8: 4 types.

[0106] Assume that there are a total of 10 types of faults for each device.

[0107] Step S21: Calculate the diagnostic matching coefficients for each device.

[0108] E1:5 / 10=0.5;E2:4 / 10=0.4;E3:6 / 10=0.6;E4:3 / 10=0.3;E5:5 / 10=0.5;E6:2 / 10=0.2;E7:7 / 10=0.7;E8:4 / 10=0.4.

[0109] Step S22: The number of garment production equipment in the production line is 8.

[0110] The preset threshold for the number of devices is set at 6. The system checks whether the number of devices (8) does not meet the requirement (i.e., whether it exceeds 6): 8 > 6, therefore it does not meet the requirement (too many devices).

[0111] According to the S22 "Requirements Not Met" path, reliable maintenance production equipment is defined as equipment whose diagnostic matching coefficient is less than the preset matching coefficient threshold. The preset matching coefficient threshold is set to 0.5.

[0112] The reliable production equipment for operation and maintenance consists of four units: E2, E4, E6, and E8.

[0113] In this embodiment, the reliability of the overall operation and maintenance process in the production line is determined based on the reliable operation and maintenance production equipment and the operation and maintenance associated fault types of the reliable operation and maintenance production equipment. Using the overall reliability of the operation and maintenance process in the production line, the overall operation and maintenance process strategy in the production line is determined, thereby further improving the reliability of the operation and maintenance process.

[0114] The operation and maintenance management strategy refers to the decision-making scheme for the overall operation and maintenance of the production line, including the basic operation and maintenance strategy, the evaluation operation and maintenance strategy, and the second evaluation operation and maintenance strategy; the overall reliability of the operation and maintenance refers to the level of operation and maintenance reliability reflected by the proportion of reliable operation and maintenance production equipment in the production line and the coverage of operation and maintenance-related fault types.

[0115] If the proportion of reliable maintenance equipment in the production line is high and the types of maintenance-related faults are widely covered, then the overall reliability of maintenance processing is high, and a more refined maintenance management strategy can be adopted.

[0116] This step determines the operation and maintenance management strategy by reliably operating and maintaining production equipment and the data on operation and maintenance-related fault types. Its significance lies in assessing the reliability of operation and maintenance from the overall production line level and selecting appropriate operation and maintenance strategies accordingly.

[0117] S31 determines the proportion of reliable operation and maintenance production equipment in the production line based on the reliable operation and maintenance production equipment in the production line, and uses it as the reliable operation and maintenance ratio. The reliable operation and maintenance ratio refers to the proportion of reliable operation and maintenance production equipment in the production line to the total number of equipment.

[0118] Assuming there are 8 pieces of equipment on the production line, of which 4 are reliable maintenance production equipment, then the reliable maintenance ratio = 4 / 8 = 0.5.

[0119] This step, by calculating the reliable operation and maintenance ratio, is significant in that it provides a quantitative basis for determining the reliability coverage dimension for the subsequent overall operation and maintenance management strategy.

[0120] In the above steps, if the reliability ratio does not meet the requirements, the reliability ratio is small and the overall reliability of operation and maintenance is poor. Therefore, the overall operation and maintenance management strategy in the production line is determined as the basic operation and maintenance strategy, that is, to carry out operation and maintenance on all garment production equipment in the production line according to the preset time cycle.

[0121] The term "not meeting requirements" refers to a situation where the reliable maintenance ratio is low, below the preset reliable maintenance ratio threshold. The basic maintenance strategy refers to a strategy for performing maintenance on all equipment in the production line according to a preset time period. If the reliable maintenance ratio is low, it indicates that the overall maintenance reliability is poor. In this case, the basic maintenance strategy is adopted to perform maintenance on all equipment according to the preset time period.

[0122] This step employs a basic maintenance strategy when the reliability of maintenance is low. Its significance lies in ensuring the operational reliability of all equipment through full-scale regular maintenance when the overall maintenance reliability is insufficient, thereby avoiding the risk of equipment failure due to insufficient reliability.

[0123] When determining the preset reliable operation and maintenance ratio threshold, the reference factors include the scale level of the production line, the overall reliability level of historical operation and maintenance processing, and the configuration capacity of operation and maintenance processing resources.

[0124] It is also understood that if the reliability ratio meets the requirements, the process proceeds to step S32; The term "meeting the requirements" refers to the situation where the reliable operation and maintenance ratio is relatively high and not lower than the preset reliable operation and maintenance ratio threshold.

[0125] If the reliability rate is high, then switch to S32 to determine a more refined operation and maintenance management strategy.

[0126] This step proceeds to further analysis when the reliability of operations and maintenance is relatively high. Its significance lies in the fact that when the overall reliability of operations and maintenance is sufficient, appropriate operations and maintenance strategies can be selected through more refined hierarchical judgment, thereby improving operations and maintenance efficiency while ensuring reliability.

[0127] S32 determines the number of operation and maintenance associated fault types of the reliable operation and maintenance production equipment based on different operation and maintenance associated fault types of the reliable operation and maintenance production equipment; Assuming that the types of operation and maintenance associated faults for each reliable production equipment have been determined, count the number of operation and maintenance associated fault types for each equipment.

[0128] This step, by counting the number of operation and maintenance related fault types, is significant in that it provides a quantitative basis for the subsequent calculation of operation and maintenance reliability weight values ​​and operation and maintenance reliability coefficients.

[0129] S33 determines the overall operation and maintenance management strategy in the production line based on the reliable operation and maintenance ratio and the number of operation and maintenance-related fault types of different reliable operation and maintenance production equipment.

[0130] Assuming that the reliable operation and maintenance ratio and the number of operation and maintenance-related fault types of each reliable operation and maintenance production equipment have been determined, operation and maintenance management strategies are determined based on the judgment results of S331 and S332.

[0131] This step determines the operation and maintenance management strategy by comprehensively considering the proportion of reliable operation and maintenance and the number of operation and maintenance-related fault types. Its significance lies in realizing the adaptive hierarchical determination of the operation and maintenance management strategy.

[0132] It is understandable that, based on the aforementioned reliable operation and maintenance ratio and the number of operation and maintenance-related fault types of different reliable operation and maintenance production equipment, the overall operation and maintenance management strategy in the production line is determined, specifically including: S331, determine the maintenance reliability weight value of the reliable maintenance production equipment by multiplying the number of maintenance-related fault types of the reliable maintenance production equipment by a preset coefficient, and determine whether the average value of the maintenance reliability weight value of different reliable maintenance production equipment meets the requirements. If so, the number of reliable maintenance production equipment is large and the maintenance reliability is high. Therefore, the overall maintenance management strategy in the production line is determined to be the evaluation maintenance strategy. That is, if the number of garment production equipment that has been maintained in the most recent preset time period is less than the preset equipment number threshold, then all garment production equipment in the production line will be maintained according to the preset time period. If not, proceed to step S332. The operation and maintenance reliability weight value refers to the weight value calculated based on the number of operation and maintenance related fault types and preset coefficients; "meeting the requirements" refers to the situation where the average value of the operation and maintenance reliability weight value is not lower than the preset weight value threshold; the evaluation operation and maintenance strategy refers to the strategy of triggering full operation and maintenance when the number of operation and maintenance devices is insufficient in the near future; the preset device number threshold refers to the critical value for judging whether the number of operation and maintenance devices is sufficient in the near future.

[0133] The calculation method for the operation and maintenance reliability weight value is as follows: Let Ni be the number of maintenance-related fault types of the i-th reliable maintenance production equipment, and let K be the preset coefficient, then: The reliability weight value for the i-th reliable production equipment is Wi = Ni × K.

[0134] If the average value of the reliability weight of each reliable maintenance production equipment meets the requirements, it indicates that there are a large number of reliable maintenance equipment and the reliability is high. In this case, the maintenance evaluation strategy is adopted. When the number of maintenance equipment is insufficient in the near future, full maintenance is triggered. If the average value does not meet the requirements, the process will proceed to S332 for further analysis.

[0135] This step employs an evaluation strategy when the average operational reliability weight value is high. Its significance lies in the fact that when the overall reliability is high, full-scale operations are only triggered when operational coverage is insufficient, thereby reducing unnecessary operational processing while ensuring reliability.

[0136] S332 determines the maintenance reliability coefficient of garment production equipment in the production line based on the maintenance reliability weight value of different reliable maintenance production equipment and the reliable maintenance ratio. It then determines whether the maintenance reliability coefficient of the garment production equipment in the production line is greater than a preset reliability coefficient threshold. If so, the overall maintenance management strategy of the production line is determined as the second evaluation maintenance strategy. That is, if the number of garment production equipment that undergoes maintenance processing within the most recent preset time period, excluding reliable maintenance production equipment, is less than a preset equipment number threshold, then all garment production equipment in the production line will undergo maintenance processing according to a preset time period. Otherwise, all garment production equipment in the production line will undergo maintenance processing according to a preset time period.

[0137] The operation and maintenance reliability coefficient refers to a quantitative indicator calculated by combining the comprehensive operation and maintenance reliability weight value and the reliable operation and maintenance ratio; the preset reliability coefficient threshold refers to the critical value for judging whether the operation and maintenance reliability coefficient is high; the second evaluation operation and maintenance strategy refers to the strategy of triggering full operation and maintenance when the number of unreliable operation and maintenance devices is insufficient in the near future.

[0138] The operation and maintenance reliability coefficient is calculated as follows: Let the mean value of the operation and maintenance reliability weight of different reliable operation and maintenance production equipment be Wavg, and the reliable operation and maintenance ratio be Rreliable, then: Operation and maintenance reliability coefficient = (Wavg + Rreliable) / 2.

[0139] If the maintenance reliability coefficient is greater than the preset reliability coefficient threshold, the second evaluation maintenance strategy is adopted. When the number of maintenance devices other than reliable maintenance devices is insufficient in the near future, full maintenance is triggered. If the maintenance reliability coefficient is not greater than the threshold, maintenance is performed on all devices according to the preset time period.

[0140] This step further refines the operation and maintenance management strategy through the operation and maintenance reliability coefficient. Its significance lies in the fact that when the average operation and maintenance reliability weight value does not meet the requirements, the strictness of the strategy is dynamically adjusted according to the operation and maintenance reliability coefficient, thereby achieving a fine balance between operation and maintenance coverage and operation and maintenance efficiency.

[0141] It should be noted that the omission of fault type identification for the garment production equipment is determined based on the fault types identified during the operation and maintenance management of the garment production equipment, but which were not identified by the fault diagnosis model of the garment production equipment.

[0142] The omissions mentioned refer to fault types that are identified manually or by other means during operation and maintenance management, but which are not identified by the fault diagnosis model, reflecting the blind spots of the diagnosis model.

[0143] If a certain type of fault is found during the operation and maintenance of a device, but the fault diagnosis model fails to identify the fault type during the diagnosis process, then the fault type is considered to be an omission in identification.

[0144] This step clarifies the method for identifying omissions. Its significance lies in using the blind spots in the diagnostic model identification discovered during operation and maintenance management as the basis for subsequent update processing, thereby making up for the risk of omissions in the diagnostic model.

[0145] Specifically, the omissions in identifying the fault types of the garment production equipment include the number of times the garment production equipment was missed in identifying different fault types.

[0146] The number of times a certain fault type is missed refers to the number of times a fault type is identified during operation and maintenance management but not by the diagnostic model.

[0147] If a certain fault type is found to be unidentified by the diagnostic model in multiple maintenance processes of a certain device, then the number of these instances is the number of times that fault type has been missed in identification.

[0148] This step identifies the number of omissions by statistics, and its significance lies in providing a quantitative basis for determining the types of omission-risk faults in the future.

[0149] Specifically, the method for determining the update and processing method for the reliable operation and maintenance production equipment is as follows: In this embodiment, based on the omissions in the identification of garment equipment and the degree of matching between the omission risk fault types in the fault types of garment production equipment and the maintenance-related fault types, the risk of omissions in the identification of fault types of garment production equipment in the production line is determined. Based on the risk of omissions in the identification of fault types of garment production equipment in the production line, a reliable maintenance update processing method for production equipment is determined, thereby further ensuring the pertinence and matching degree of maintenance processing.

[0150] The update processing method refers to a decision-making scheme for updating the set of reliable operation and maintenance production equipment based on the identification of omission risks; the identification of omission risks refers to the degree of risk of insufficient targeting of operation and maintenance processing due to omissions in the diagnostic model.

[0151] If a device has a serious problem with missing identifications and the types of faults with identified risks match the types of faults associated with operation and maintenance, then the device needs to be upgraded to a reliable operation and maintenance production device to enhance operation and maintenance processes.

[0152] This step determines the update processing method by identifying omissions and matching degree. Its significance lies in feeding back the diagnostic blind spot information found in the operation and maintenance process to the update of reliable operation and maintenance production equipment, thereby realizing targeted and continuous optimization of operation and maintenance processing.

[0153] S41, based on the identified omissions, determine the number of times the garment production equipment was identified in different fault types, and determine the omission risk fault type among the fault types of the garment production equipment according to the number of identified omissions; The omission risk fault type refers to the fault type where the number of omissions does not meet the requirement, i.e., the number of omissions is too high.

[0154] If a certain fault type is missed a lot, exceeding the preset threshold for the number of missed identifications, then the fault type is identified as a fault type with a risk of being missed.

[0155] This step filters out the types of faults with missing risks by identifying the number of times they are missed. Its significance lies in identifying the fault types with higher risks from the identified omissions, providing a basis for the calculation of risk values ​​for subsequent operation and maintenance. The preset threshold for the number of omissions is determined based on factors such as the frequency of operation and maintenance of the garment production equipment, the identification capability level of the fault diagnosis model, and the typical number of historical omissions.

[0156] S42 determines the maintenance matching risk value of the garment production equipment based on the degree of matching between the omission risk fault type and the maintenance-related fault type in the fault types of the garment production equipment. The operation and maintenance matching risk value refers to an indicator that quantifies the degree of risk in equipment operation and maintenance matching, calculated based on the ratio of omitted risk fault types to operation and maintenance related fault types.

[0157] The calculation method for the operation and maintenance matching risk value is as follows: Let the number of missing risk fault types of garment production equipment be Nr, the preset weight value be Wp, and the number of operation and maintenance associated fault types be Na, then the target value = Wp + Na; the operation and maintenance matching risk value = Nr / (Wp + Na).

[0158] If a device has a large number of missing fault types and a small number of maintenance-related fault types, then the maintenance matching risk value is high, indicating that the maintenance matching risk of the device is large. This step calculates the maintenance matching risk value by ratio. Its significance is to quantify the matching relationship between missing risks and maintenance-related factors into a comparable risk indicator, providing a quantitative basis for determining the subsequent update processing method.

[0159] S43 determines the update processing method for the reliable maintenance production equipment based on the operation and maintenance matching risk value of different garment production equipment and the operation and maintenance management strategy.

[0160] Assuming that the operation and maintenance matching risk values ​​and operation and maintenance management strategies for each device have been determined, the update processing methods are determined based on the judgment results of scenario 1, scenario 2 and scenario 3 respectively.

[0161] This step integrates operational risk values ​​and operational management strategies to determine the update processing method, and its significance lies in achieving adaptive hierarchical determination of the update processing method.

[0162] It is understandable that, based on the operation and maintenance matching risk values ​​of different garment production equipment and the aforementioned operation and maintenance management strategy, the update processing method for the reliable operation and maintenance production equipment is determined, specifically including: It should be noted that the update processing method for S43 includes the following three cases.

[0163] Case 1: If the operation and maintenance management strategy is the basic operation and maintenance strategy, the reliability of operation and maintenance processing is relatively high. Therefore, the update processing method for reliable operation and maintenance production equipment is determined to be to update the garment production equipment with operation and maintenance matching risk value greater than the preset risk threshold and with multiple omission risk fault types to reliable operation and maintenance production equipment. Case 1 refers to the situation where the update processing method is determined when the operation and maintenance management strategy is the basic operation and maintenance strategy. In this case, the equipment with the operation and maintenance matching risk value greater than the preset risk threshold and with multiple missing risk fault types will be updated to reliable operation and maintenance production equipment.

[0164] Assuming the operation and maintenance management strategy is a basic operation and maintenance strategy, then equipment with an operation and maintenance matching risk value greater than the preset risk threshold and with multiple missed risk fault types will be updated to reliable operation and maintenance production equipment to enhance their operation and maintenance processing.

[0165] This step employs strict update conditions under the basic operation and maintenance strategy. Its significance lies in the fact that when the overall operation and maintenance reliability is high, only high-risk equipment is included in the reliable operation and maintenance production equipment set, thereby avoiding resource waste caused by excessive updates.

[0166] Additionally, it should be noted that in case 2: if the operation and maintenance management strategy is not a basic operation and maintenance strategy, the proportion of garment production equipment with identification omissions in the production line is used as the proportion of identified omissions based on the different identification omission situations of garment production equipment. If the proportion of identified omissions is greater than the preset omissions proportion threshold, then the update processing method for reliable operation and maintenance production equipment is determined to be to update the garment production equipment with operation and maintenance matching risk value greater than the preset risk threshold as reliable operation and maintenance production equipment. Situation 2 refers to the situation where the operation and maintenance management strategy is not a basic operation and maintenance strategy and the proportion of identified missing devices is relatively high. The proportion of identified missing devices refers to the proportion of devices with identified omissions to the total number of devices. The preset threshold for the proportion of missing devices refers to the critical value for judging whether the proportion of identified missing devices is relatively high.

[0167] If the operation and maintenance management strategy is not part of the basic operation and maintenance strategy and the proportion of missed devices is high, then devices with operation and maintenance matching risk values ​​greater than the preset risk threshold will be updated to reliable operation and maintenance production devices.

[0168] This step uses a moderate update condition when the proportion of missed devices is high. The significance of this is that when the situation of missing devices is more common, the update condition can be appropriately relaxed to cover more risky devices.

[0169] It also includes the following: Case 3: If the proportion of identified missing devices is not greater than the preset missing device proportion threshold, the operation and maintenance management risk value is determined based on the proportion of identified missing devices and the operation and maintenance matching risk value of different garment production equipment. It is then determined whether the operation and maintenance management risk value is greater than the preset risk threshold. If so, the update processing method for reliable operation and maintenance production equipment is determined to be to update the garment production equipment with the operation and maintenance matching risk value greater than the preset risk threshold to reliable operation and maintenance production equipment. If not, the update processing method for reliable operation and maintenance production equipment is determined according to the operation and maintenance management strategy.

[0170] Situation 3 refers to the situation where the update processing method is determined when the proportion of identified missing devices is not high; the operation and maintenance management risk value refers to the quantitative indicator calculated by comprehensively identifying the proportion of missing devices and the operation and maintenance matching risk value.

[0171] The calculation method for the operation and maintenance management risk value is as follows: Let Po be the proportion of identified missing equipment, and Mrisk_avg be the average of the operation and maintenance matching risk values ​​of different garment production equipment. Then: Operation and maintenance management risk value = Po + Mrisk_avg.

[0172] Assuming the proportion of identified missing devices is not high, calculate the operation and maintenance management risk value. If the operation and maintenance management risk value is greater than the preset risk threshold, then update the devices with operation and maintenance matching risk values ​​greater than the preset risk threshold to reliable operation and maintenance production devices; if not, further determine the update processing method according to the operation and maintenance management strategy.

[0173] This step, when the proportion of missing devices is not high, further assesses the situation through operation and maintenance management risk values. Its significance lies in dynamically adjusting the update strategy based on the comprehensive risk value when the identification of missing devices is not widespread, thereby achieving a balance between update coverage and resource efficiency.

[0174] It should be noted that the update processing method for the reliable operation and maintenance production equipment determined according to the aforementioned operation and maintenance management strategy specifically includes: If the operation and maintenance management strategy is the second evaluation operation and maintenance strategy, then the update processing method for the reliable operation and maintenance production equipment is determined to be to update the garment production equipment with an operation and maintenance matching risk value greater than the preset risk threshold and with multiple omission risk fault types to reliable operation and maintenance production equipment. If the operation and maintenance management strategy is to evaluate the operation and maintenance strategy, then the method for updating the reliable operation and maintenance production equipment is to update the garment production equipment that has multiple missed risk fault types or whose number of missed identifications does not meet the requirements (i.e., the number of missed identifications is too high) when the operation and maintenance matching risk value is greater than the preset risk threshold to reliable operation and maintenance production equipment.

[0175] If the operation and maintenance management strategy is the second evaluation operation and maintenance strategy, then the equipment with an operation and maintenance matching risk value greater than the preset risk threshold and with multiple missed risk fault types will be updated to reliable operation and maintenance production equipment; if it is the evaluation operation and maintenance strategy, then the equipment with an operation and maintenance matching risk value greater than the preset risk threshold and with multiple missed risk fault types or with a large number of missed identifications will be updated to reliable operation and maintenance production equipment.

[0176] This step determines the update processing method according to different operation and maintenance management strategies. Its significance lies in the fact that when the operation and maintenance control risk value is not high, differentiated update conditions are adopted according to the strictness of the operation and maintenance management strategy, thereby achieving a refined determination of the update processing method.

[0177] This embodiment, through steps S31 to S33 and S41 to S43, realizes a complete process from calculating the reliable operation and maintenance ratio to determining the operation and maintenance management strategy and then to determining the update processing method. Its core value is reflected in three aspects: First, by classifying and judging the reliable operation and maintenance ratio and the operation and maintenance reliability weight value, the operation and maintenance management strategy is dynamically adjusted when the overall reliability is different; second, by identifying omissions and quantitatively analyzing the operation and maintenance matching risk value, the blind spot information of the diagnostic model is fed back to the update processing; third, by differentiating the processing of cases 1, 2 and 3 and further subdividing the operation and maintenance management strategy, an adaptive balance is achieved between update coverage and resource efficiency.

[0178] Continuing with the calculation results of S2, the reliable production equipment for operation and maintenance is E2, E4, E6, and E8, a total of 4 units. The number of operation and maintenance-related fault types for each unit is as follows: E2 has 4 types, E4 has 3 types, E6 has 2 types, and E8 has 4 types.

[0179] Step S31: Reliable maintenance ratio = 4 / 8 = 0.5. Determine if the reliable maintenance ratio of 0.5 does not meet the requirement (i.e., below 0.4): 0.5 is not less than 0.4, which meets the requirement, proceed to S32.

[0180] Step S32: Determine the number of maintenance-related fault types for each reliable production equipment. E2: 4 types; E4: 3 types; E6: 2 types; E8: 4 types.

[0181] Step S33: Step S331: Calculate the reliability weight value of each reliable production equipment (preset coefficient 0.1). E2: 4 × 0.1 = 0.4; E4: 3 × 0.1 = 0.3; E6: 2 × 0.1 = 0.2; E8: 4 × 0.1 = 0.4.

[0182] Average reliability weight for operations and maintenance = (0.4 + 0.3 + 0.2 + 0.4) / 4 = 1.3 / 4 = 0.325 Determine if the average value of 0.325 meets the requirement (i.e., not lower than the preset weight threshold of 0.4): 0.325 < 0.4, does not meet the requirement, proceed to S332.

[0183] Step S332: Calculate the operation and maintenance reliability coefficient. The mean reliability weight value (Wavg) is 0.325, the reliable operation and maintenance ratio (Rreliable) is 0.5, and the operation and maintenance reliability coefficient is 0.41. Determine if the reliability coefficient of 0.41 is greater than the preset reliability coefficient threshold of 0.6. If not, according to the "No" path in S332, the overall operation and maintenance management strategy for the production line is determined to be to perform operation and maintenance on all garment production equipment on the production line according to a preset time cycle, i.e., the basic operation and maintenance strategy. Therefore, the operation and maintenance management strategy is determined to be the basic operation and maintenance strategy.

[0184] During operation and maintenance management, the identification omissions of each device are statistically analyzed. Taking devices E1 and E3 as examples (these two devices are currently not considered reliable production equipment): E1: During the operation and maintenance process, it was found that F4 had 3 identification omissions, F5 had 2 identification omissions, F6 had 4 identification omissions, and F9 had 1 identification omission.

[0185] E3: During the operation and maintenance process, it was found that F4 had 5 missed identifications and F9 had 2 missed identifications.

[0186] Step S41: Determine the type of missing fault for each device (number of missed faults > preset threshold of 3).

[0187] E1: F4 (3 times, not greater than 3, not belonging), F5 (2 times, not greater than 3, not belonging), F6 (4 times > 3, belonging), F9 (1 ​​time, not greater than 3, not belonging). The omission risk fault type of E1 is F6, which is 1 type.

[0188] E3: F4 (5 times > 3, belongs to), F9 (2 times, not greater than 3, does not belong to). The omission risk fault type of E3 is F4, which is 1 type.

[0189] Similarly, statistics are performed on other equipment. Assume that E5 has two types of missed fault risks: F5 and F9, and E7 has one type of missed fault risk: F4. The omission status of E2, E4, E6, and E8 (reliable maintenance production equipment) is as follows: E2 has no omissions, E4 has no omissions, E6 has no omissions, and E8 has one type of missed fault risk: F9.

[0190] Step S42: Calculate the operation and maintenance matching risk value for each device (target value = preset weight value 2 + number of operation and maintenance related fault types).

[0191] E1: Number of missed risk fault types = 1, Number of operation and maintenance related fault types = 5, Target value = 2 + 5 = 7, Operation and maintenance matching risk value = 1 / 7 ≈ 0.143.

[0192] E3: Number of missed risk fault types = 1, Number of operation and maintenance related fault types = 6, Target value = 2 + 6 = 8, Operation and maintenance matching risk value = 1 / 8 = 0.125.

[0193] E5: Number of missed risk fault types = 2, Number of operation and maintenance related fault types = 5, Target value = 2 + 5 = 7, Operation and maintenance matching risk value = 2 / 7 ≈ 0.286.

[0194] E7: Number of missed risk fault types = 1, Number of operation and maintenance related fault types = 7, Target value = 2 + 7 = 9, Operation and maintenance matching risk value = 1 / 9 ≈ 0.111.

[0195] E8: Number of missed risk fault types = 1, Number of operation and maintenance related fault types = 4, Target value = 2 + 4 = 6, Operation and maintenance matching risk value = 1 / 6 ≈ 0.167.

[0196] Step S43: Determine the update processing method.

[0197] Operation and maintenance management strategy is a basic operation and maintenance strategy, belonging to case 1.

[0198] Based on scenario 1, garment production equipment with an operation and maintenance matching risk value greater than the preset risk threshold of 0.4 and with multiple missed risk fault types will be updated to reliable operation and maintenance production equipment.

[0199] This embodiment implements a maintenance management method based on intelligent diagnosis of garment production equipment through the complete process from S1 to S4. S1 determines the types of maintenance-related faults for each piece of equipment by using dual threshold judgments of the number of fault diagnoses and diagnostic accuracy, focusing maintenance processing on fault types that the diagnostic model can reliably identify. S2 determines reliable maintenance production equipment in the production line by using diagnostic matching coefficients and equipment quantity classification judgments, achieving accurate identification of equipment with high maintenance reliability. S3 determines the overall maintenance management strategy for the production line through classification analysis of reliable maintenance ratios and maintenance reliability weight values, dynamically adjusting the scope of maintenance processing when overall reliability varies. S4 determines the update processing method for reliable maintenance production equipment through quantitative analysis of omissions and maintenance matching risk values, feeding back the identification blind spots of the diagnostic model into equipment updates. Overall, this method constructs a complete technical closed loop from data collection to update processing through the coordinated linkage of fault diagnosis data quantification, maintenance-related fault type determination, reliable maintenance production equipment identification, maintenance management strategy hierarchical determination, and dynamic management of update processing methods. Its core value is reflected in four aspects: First, it ensures the reliability of maintenance-related fault type determination through dual judgment of diagnosis frequency and accuracy; second, it achieves accurate identification of reliable maintenance production equipment through hierarchical analysis of diagnosis matching coefficients and equipment quantity; third, it enables adaptive selection of maintenance management strategies through hierarchical judgment of reliable maintenance ratio and maintenance reliability weight value; and fourth, it achieves continuous optimization of the reliable maintenance production equipment set through feedback analysis of omission identification and maintenance matching risk values, thereby improving overall maintenance efficiency while ensuring targeted maintenance processing.

[0200] Example 2 Secondly, such as Figure 3 As shown, this application provides a maintenance management system based on intelligent diagnostics for garment production equipment. The aforementioned maintenance management method based on intelligent diagnostics for garment production equipment specifically includes: Fault type filtering module, operation and maintenance management module, update processing module; The fault type filtering module is responsible for determining the operation and maintenance-related fault types of the garment production equipment. The operation and maintenance management module is responsible for determining the overall operation and maintenance management strategy for the production line; The update processing module is responsible for determining the update processing method for the reliable operation and maintenance production equipment.

[0201] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and non-volatile computer storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0202] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0203] The above description is merely one or more embodiments of this specification and is not intended to limit this specification. Various modifications and variations can be made to the one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of this specification.

Claims

1. A maintenance management method based on intelligent diagnostics of garment production equipment, characterized in that, Specifically, it includes: Based on the fault diagnosis data of the garment production equipment, determine the fault type in the garment production equipment that requires operation and maintenance processing based on the diagnosis results, and use it as the operation and maintenance associated fault type of the garment production equipment. Based on the different operation and maintenance associated fault types of garment production equipment, the matching degree of operation and maintenance treatment for different garment production equipment in the production line is determined. Based on the matching degree of operation and maintenance treatment for different garment production equipment in the production line and the data of garment production equipment in the production line, the garment production equipment in the production line that is to be operated and maintained in combination with the operation and maintenance data under the operation and maintenance associated fault types is determined. In the production line, garment production equipment that undergoes maintenance processing based on maintenance data under maintenance-related fault types is considered reliable maintenance production equipment. Based on the data of reliable maintenance production equipment and garment production equipment in the production line whose number of maintenance-related fault types does not meet the requirements, the overall maintenance management strategy for the production line is determined. Based on the operation and maintenance management strategy, the identification omissions of different fault types of garment production equipment are obtained. Based on the matching degree between the identification omissions of different garment production equipment and the operation and maintenance related fault types, as well as the operation and maintenance management strategy, the update processing method of the reliable operation and maintenance production equipment is determined.

2. The maintenance management method based on intelligent diagnosis of garment production equipment as described in claim 1, characterized in that, The fault diagnosis data of the garment production equipment includes the diagnostic results of the garment production equipment under different fault types.

3. The maintenance management method based on intelligent diagnosis of garment production equipment as described in claim 1, characterized in that, The method for determining the operation and maintenance-related fault types of the garment production equipment is as follows: Based on the fault diagnosis data of the garment production equipment, determine the number of fault diagnoses of the garment production equipment under the fault type; Based on the number of fault diagnoses and the accuracy of fault diagnoses under the fault type, it is determined whether the fault type belongs to the operation and maintenance related fault type of garment production equipment.

4. The maintenance management method based on intelligent diagnosis of garment production equipment as described in claim 3, characterized in that, When the number of fault diagnoses and the accuracy of fault diagnosis under the fault type both meet the requirements, the fault type is determined to belong to the operation and maintenance related fault type of garment production equipment.

5. The maintenance management method based on intelligent diagnosis of garment production equipment as described in claim 4, characterized in that, If the fault type belongs to the operation and maintenance related fault type of garment production equipment, then as long as the fault diagnosis model identifies the operation and maintenance management fault type, the operation and maintenance of the garment production equipment will be carried out. For other fault types identified by the fault diagnosis model, only the relevant fault type investigation and processing are required.

6. The maintenance management method based on intelligent diagnosis of garment production equipment as described in claim 1, characterized in that, The matching degree of operation and maintenance of the garment production equipment in the production line is determined based on the matching degree between the number of operation and maintenance-related fault types of the garment production equipment in the production line and the total number of fault types.

7. The maintenance management method based on intelligent diagnosis of garment production equipment as described in claim 1, characterized in that, The method for determining the reliable operation and maintenance production equipment is as follows: Based on the matching degree of operation and maintenance processing of different garment production equipment in the production line, the ratio of the number of operation and maintenance related fault types of garment production equipment in the production line to the number of all fault types is determined, and this ratio is used as the diagnostic matching coefficient of the garment production equipment. Based on the data of the garment production equipment in the production line, determine the number of garment production equipment in the production line; By using the diagnostic matching coefficients of different garment production equipment in the production line and the number of garment production equipment, the reliable operation and maintenance production equipment in the production line is determined.

8. The maintenance management method based on intelligent diagnosis of garment production equipment as described in claim 7, characterized in that, If the production equipment is a reliable maintenance production equipment, then if there is no period for maintenance processing based on the fault diagnosis results of the maintenance-related fault type within the most recent preset time period, then the production equipment will be subjected to maintenance processing.

9. The maintenance management method based on intelligent diagnosis of garment production equipment as described in claim 1, characterized in that, The method for determining the update processing method for the reliable operation and maintenance production equipment is as follows: Based on the identified omissions, the number of times the garment production equipment was identified in different fault types is determined, and the omission risk fault type in the fault types of the garment production equipment is determined according to the number of identified omissions. The maintenance matching risk value of the garment production equipment is determined by the degree of matching between the omission risk fault type and the maintenance-related fault type in the fault types of the garment production equipment. Based on the operation and maintenance matching risk values ​​of different garment production equipment and the operation and maintenance management strategy, the update processing method for the reliable operation and maintenance production equipment is determined.

10. A maintenance management system based on intelligent diagnostics of garment production equipment, employing the maintenance management method based on intelligent diagnostics of garment production equipment as described in any one of claims 1-9, characterized in that, Specifically, it includes: Fault type filtering module, operation and maintenance management module, update processing module; The fault type filtering module is responsible for determining the operation and maintenance-related fault types of the garment production equipment. The operation and maintenance management module is responsible for determining the overall operation and maintenance management strategy for the production line; The update processing module is responsible for determining the update processing method for the reliable operation and maintenance production equipment.

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