Air conditioner test data analysis processing method and test quality management system

Abstract

The invention provides an air conditioner test data analysis processing method and a test quality management system, and belongs to the technical field of data processing, and the method specifically comprises the steps that a model identification module is responsible for carrying out the model identification of air conditioner parts to obtain an identification result, and a test processing module is responsible for carrying out the automatic test processing based on the identification result to obtain test data; and the test data management module is responsible for tracing the test data of the air conditioner parts, and determining defect types with quality problems according to analysis results of the test data of the air conditioner parts in different production batches, so that the reliability of quality management and control processing is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and in particular relates to an air-conditioning test data analysis and processing method and a test quality management system. Background Art

[0002] Automobile air conditioning device is also called automobile air conditioner for short. It is used to adjust and control the temperature, humidity, air cleanliness and air flow in the car compartment to the best state, provide a comfortable riding environment for passengers, reduce travel fatigue, create good working conditions for drivers, and play an important role in ensuring safe driving.

[0003] In order to process the test data of the automobile air conditioning device, the invention patent application CN202410693788.2 "A method, device and terminal for evaluating and optimizing the operating sound of the air conditioning outlet" formulates a subjective evaluation method and an objective test method for the automobile air conditioning outlet, forms a sound development index, and provides an optimization plan through structural analysis. When problems are encountered, the optimization plan can be used to quickly and accurately solve the problems and reduce the optimization time cycle. However, the following technical problems exist through analysis: During the analysis and processing of air-conditioning test data, quality problems occur in air-conditioning parts. In addition to the design problems of the air-conditioning parts themselves, the production quality of the air-conditioning parts will also have a certain degree of impact on the quality defects of the air-conditioning parts. If the production quality of different batches is ignored, it will be impossible to accurately identify the design problems of the air-conditioning parts.

[0004] In response to the above technical problems, the present application specifically provides an air conditioning test data analysis and processing method and a test quality management system. Summary of the invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: In a first aspect, the present application provides an air conditioning test quality management system, specifically comprising: Model identification module, test processing module, test data management module; The model identification module is responsible for identifying the model of the air conditioner parts and components to obtain the identification result; The test processing module is responsible for automatically performing test processing based on the recognition result to obtain test data; The test data management module is responsible for tracing the test data of the air-conditioning components and determining the defect type of the quality problem according to the analysis results of the test data of the air-conditioning components in different production batches.

[0006] A further technical solution is that the test processing module includes 3 temperature acquisition channels, 1 cooling control channel, 2 heating control channels, damper control and product short-circuit test.

[0007] A further technical solution is that the heating control 2 includes two modes: electromagnetic control and electric control.

[0008] A further technical solution is that the test quality management system also includes a test data display module, and the test data display module is responsible for displaying the test data of the air-conditioning components.

[0009] A further technical solution is that the test quality management system also includes a product batch information management module, and can set the personnel and production line information of the test products of the air-conditioning parts.

[0010] A further technical solution is that the test data management module is responsible for statistically recording the number of tests, the number of qualified products, and the number of unqualified products, and can record corresponding unqualified information for unqualified products.

[0011] In a second aspect, the present application provides an air conditioning test data analysis and processing method, which is applied to the above-mentioned air conditioning test quality management system, specifically comprising: S1: determining test defect data of different air conditioner components based on the analysis results of the air conditioner test data, and determining suspected defective components among the air conditioner components using the analysis results of the test defect data; S2 determines the distribution data of the test defect data of different defect types in different production batches based on the test defect data of the suspected defective component, and determines the defect problem type in the defect type by using the distribution data; S3 obtains test defect data of different defect types in different production batches, and determines the abnormal probability of different production batches and quality defect production batches in combination with the defect problem types of different defect types; S4 treats the production batches excluding the production batches with quality defects as normal production batches, determines the defect types with quality problems based on the test defect data of the defect types in different normal production batches and the abnormal probability, and outputs the defect types with quality problems for processing.

[0012] The beneficial effects of the present invention are: The quality defect production batches in the production batches are determined by utilizing the test defect data of different defect types and the defect problem types of defect types. Not only the number of parts with quality defects in the production batches is taken into account, but also the differences in defect problem types caused by differences in the distribution data of different defect types in different production batches and the differences in their abnormal probabilities are taken into account. This achieves the screening of production batches with defects in production quality and lays the foundation for further improving the recognition accuracy of defect types with quality defects.

[0013] Based on the test defect data and abnormal probabilities of defect types in different normal production batches, the defect types with quality problems are determined, thereby avoiding the influence of production batches with defects in production quality, and realizing the identification of defect types with quality problems from the test defect data of defect types in normal production batches. At the same time, the abnormal probabilities of different normal production batches are comprehensively considered, and the degree of abnormal probability of quality defects in different normal production batches is also comprehensively considered, thereby improving the reliability of quality management.

[0014] A further technical solution is that the air-conditioning components include fan control components, temperature collection circuits, cooling control circuits, heating control circuits, damper control switches and product casings.

[0015] A further technical solution is that the test defect data includes the number of air-conditioning parts with quality defects in different production batches.

[0016] A further technical solution is that the method for determining the suspected defective parts in the air conditioner parts is: The air-conditioning parts with quality defects are regarded as defective parts, and the number of defective parts of the air-conditioning parts in different production batches is determined based on the test defect data in different production batches; Determining defective production batches among the production batches using the number of defective parts in different production batches; Determine whether the air conditioning component is a suspected defective component based on the number of the defective production batches.

[0017] A further technical solution is that when the proportion of the number of defective parts in the production batch does not meet the requirements, the production batch is determined to be a defective production batch.

[0018] A further technical solution is that when the number of defective production batches of the air-conditioning component is greater than a preset batch number, the air-conditioning component is determined to be a suspected defective component.

[0019] A further technical solution is that the method for determining the suspected defective parts in the air conditioner parts is: The air-conditioning parts with quality defects are regarded as defective parts, and the number of defective parts of the air-conditioning parts in different production batches is determined based on the test defect data in different production batches; Calculate the total number of defective parts of the air conditioner parts by using the number of defective parts in different production batches; Determine whether the air conditioning component is a suspected defective component based on the total number of the defective components.

[0020] A further technical solution is that the method for determining the defect type with quality problems is: Determine the ratio of the number of defective parts corresponding to the defect types in different normal production batches using the test defect data of the defect types in different normal production batches, and determine the defect abnormality coefficients of different normal production batches using the ratio of the number of defective parts corresponding to the defect types in different normal production batches; Determine the defect anomaly assessment amount of different normal production batches according to the abnormal probability and defect anomaly coefficient of different normal production batches; Based on the average values ​​of defect anomaly evaluation quantities of different normal production batches, a defect average value of the defect type is determined, and the defect average value is used to determine whether the defect type is a defect type with quality problems.

[0021] A further technical solution is that the defect anomaly assessment amount of the normal production batch is determined according to the product of the abnormal probability of the normal production batch and the defect anomaly coefficient.

[0022] A further technical solution is that when the defect average value is greater than a preset defect threshold, the defect type is determined to be a defect type with quality problems.

[0023] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0024] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0026] Figure 1 It is a framework diagram of an air conditioning test quality management system; Figure 2 It is a flow chart of an air conditioning test data analysis and processing method; Figure 3 is a flow chart of a method for determining suspected defective parts among air conditioner parts; Figure 4 is a flow chart of a method for determining a defect problem type of a defect type; Figure 5 is a flow chart of a method for determining the probability of abnormality of a production batch; Figure 6 It is a flowchart of a method for determining the defect type having quality problems.

[0027] Reference numerals: 1. Model identification module, 2. Test processing module, 3. Test data management module. DETAILED DESCRIPTION

[0028] In order 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 in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification. Example

[0029] like Figure 1 As shown, the present application provides an air conditioning test quality management system, which specifically includes: Model identification module (1), test processing module (2), test data management module (3); The model identification module is responsible for identifying the model of the air conditioner parts and components to obtain the identification result; The test processing module is responsible for automatically performing test processing based on the recognition result to obtain test data; The test data management module is responsible for tracing the test data of the air-conditioning components and determining the defect type of the quality problem according to the analysis results of the test data of the air-conditioning components in different production batches.

[0030] Furthermore, the test processing module includes 3 channels for temperature acquisition, 1 channel for cooling control, 2 channels for heating control, damper control and product short-circuit test to ground.

[0031] Specifically, the heating control 2 includes two modes: electromagnetic control and electric control.

[0032] It can be understood that the test quality management system further includes a test data display module, and the test data display module is responsible for displaying the test data of the air-conditioning components.

[0033] Furthermore, the test quality management system also includes a product batch information management module, and can set the personnel and production line information of the test products of the air-conditioning parts.

[0034] It should also be noted that the test data management module is responsible for statistically recording the number of tests, the number of qualified products, and the number of unqualified products, and can record the corresponding unqualified information for unqualified products. Example

[0035] In addition to the design problems of air-conditioning parts themselves, the production quality of air-conditioning parts will also have a certain degree of impact on the quality defects of air-conditioning parts. Therefore, it is necessary to accurately identify the design problems of air-conditioning parts on the basis of excluding production batches with defects in production quality.

[0036] Suspected defective parts are air-conditioning parts in which the number of quality defects is greater than 0.1.

[0037] Production batches with quality defects in the defect type are set as defective production batches, defect problem types of defect types in which the proportion of defective production batches in the number of production batches is greater than 0.2 are set as serious problem types, and defect problem types of defect types in which the proportion of defective production batches in the number of production batches is not more than 0.2 are set as general problem types.

[0038] Using the test defect data of different defect types in the production batch, determine the quantity ratio of parts with quality defects corresponding to different defect types; using the defect problem types of different defect types, determine the preset quantity ratio of different defect types; based on the ratio of the quantity ratio of parts with quality defects corresponding to different defect types to the preset quantity ratio, determine the abnormal coefficients of different defect types; based on the weights of the abnormal coefficients of different defect types, determine the abnormal probability of the production batch; when the abnormal probability is greater than 0.6, determine that the production batch is a quality defective production batch.

[0039] The defect anomaly coefficients of different normal production batches are determined by using the proportion of defective parts corresponding to the defect types in different normal production batches. The defect anomaly assessment quantities of different normal production batches are determined based on the product of the abnormality probabilities of different normal production batches and the defect anomaly coefficients. When the average value of the defect anomaly assessment quantities of different normal production batches is greater than 0.5, the defect type is determined to be a defect type with quality problems.

[0040] To solve the above problems, according to one aspect of the present invention, Figure 2 As shown, the present application provides an air conditioning test data analysis and processing method, which is applied to the above-mentioned air conditioning test quality management system, specifically comprising: S1: determining test defect data of different air conditioner components based on the analysis results of the air conditioner test data, and determining suspected defective components among the air conditioner components using the analysis results of the test defect data; S2 determines the distribution data of the test defect data of different defect types in different production batches based on the test defect data of the suspected defective component, and determines the defect problem type in the defect type by using the distribution data; S3 obtains test defect data of different defect types in different production batches, and determines the abnormal probability of different production batches and quality defect production batches in combination with the defect problem types of different defect types; S4 treats the production batches excluding the production batches with quality defects as normal production batches, determines the defect types with quality problems based on the test defect data of the defect types in different normal production batches and the abnormal probability, and outputs the defect types with quality problems for processing.

[0041] Furthermore, the air conditioning components include fan control components, temperature collection circuits, cooling control circuits, heating control circuits, damper control switches and product casings.

[0042] Specifically, the test defect data includes the number of air-conditioning parts with quality defects in different production batches.

[0043] Specifically, Figure 3 As shown, the method for determining the suspected defective parts in the air conditioner parts is: S101 regards the air conditioner parts with quality defects as defective parts, and determines the number of defective parts of the air conditioner parts in different production batches based on the test defect data in different production batches; S102: determining defective production batches in the production batches by using the number of defective parts in different production batches; S103 determines whether the air conditioning component is a suspected defective component according to the number of the defective production batches.

[0044] Optionally, when the proportion of the number of defective parts in the production batch does not meet the requirements, the production batch is determined to be a defective production batch.

[0045] Furthermore, when the number of defective production batches of the air-conditioning component is greater than a preset batch number, the air-conditioning component is determined to be a suspected defective component.

[0046] In another embodiment, the method for determining the suspected defective parts in the air conditioner parts is: The air-conditioning parts with quality defects are regarded as defective parts, and the number of defective parts of the air-conditioning parts in different production batches is determined based on the test defect data in different production batches; Calculate the total number of defective parts of the air conditioner parts by using the number of defective parts in different production batches; Determine whether the air conditioning component is a suspected defective component based on the total number of the defective components.

[0047] Optionally, the method for determining the suspected defective parts in the air conditioner parts is: S11 regards the air conditioner parts with quality defects as defective parts, and determines the number of defective parts of the air conditioner parts in different production batches based on the test defect data in different production batches; S12 determines the quality defect coefficient of the air conditioner parts in different production batches according to the number of defective parts in different production batches and the proportion of the number of defective parts; S13 determines the comprehensive defect coefficient of the air-conditioning component according to the quality defect coefficients of the air-conditioning component in different production batches, and uses the comprehensive defect coefficient to determine whether the air-conditioning component is a suspected defective component.

[0048] Optionally, the above step S11 includes the following contents: S111 regards the air-conditioning component with quality defects as a defective component, and determines the number of defective components of the air-conditioning component in different production batches based on the test defect data in different production batches. When the total number of defective components in different production batches does not meet the requirement, the air-conditioning component is determined to be a suspected defective component. When the total number of defective components in different production batches meets the requirement, the process proceeds to step S112; S112: When determining the production batch in which the number of defective parts is greater than the preset number of defective parts by the number of defective parts in different production batches, proceed to step S113; when there is no production batch in which the number of defective parts is greater than the preset number of defective parts, proceed to step S12; S113 regards the production batch in which the number of defective parts is greater than the preset number of defective parts as a defective production batch. When the number of the defective production batch does not meet the requirement, the air-conditioning parts are determined to be suspected defective parts. When the number of the defective production batch meets the requirement, proceed to step S12.

[0049] Optionally, the above step S12 includes the following contents: S121 determines the quality defect coefficient of the air-conditioning component in different production batches according to the number of defective components in different production batches and the proportion of the number of defective components. When the average value of the quality defect coefficient of the air-conditioning component in different production batches does not meet the requirements, the air-conditioning component is determined to be a suspected defective component. When the average value of the quality defect coefficient of the air-conditioning component in different production batches meets the requirements, the process proceeds to step S122; S122: When the quality defect coefficients of different production batches are all less than the preset defect coefficient threshold, it is determined that the air conditioner component is not a suspected defective component. When there is a production batch whose quality defect coefficient is not less than the preset defect coefficient threshold, the process proceeds to step S123; S123 takes the production batch whose quality defect coefficient is not less than the preset defect coefficient threshold as the screening defect batch. When the screening defect batch is greater than the preset defect batch quantity threshold, it is determined that the air-conditioning component is a suspected defective component. When the screening defect batch is not greater than the preset defect batch quantity threshold, proceed to step S13.

[0050] Furthermore, the comprehensive defect coefficient of the air-conditioning component is determined based on the weighted sum of the quality defect coefficients of the air-conditioning component in different production batches.

[0051] It should be noted that when the comprehensive defect coefficient of the air-conditioning component is greater than a preset defect coefficient threshold, the air-conditioning component is determined to be a suspected defective component.

[0052] Furthermore, the distribution data of the test defect data of the defect type in different production batches includes the distribution quantity of air-conditioning parts with the defect type in different production batches.

[0053] Specifically, Figure 4 As shown, the method for determining the defect problem type of the defect type is: S21 regards the air conditioner parts with quality defects of the above defect types as defective parts; S22 determines defect coefficients of the defect types in different production batches based on the percentage of defective parts in different production batches; S23 determines an average defect coefficient of the defect type according to average values ​​of the defect coefficients of the defect type in different production batches, and determines the defect problem type of the defect type using the average defect coefficient.

[0054] Further, the defect problem type of the defect type is determined by using the average defect coefficient, specifically including: The defect problem type of the defect type is determined based on the preset problem type corresponding to the average defect coefficient of the defect type.

[0055] Specifically, the defect problem types include general problem types, serious problem types and key problem types.

[0056] It may be understood that the severity of the defect problem type of the key problem type is greater than that of the serious problem type, and the severity of the defect problem type of the serious problem type is greater than that of the general problem type.

[0057] Optionally, the method for determining the defect problem type of the defect type is: Air-conditioning parts with quality defects in the defect type are regarded as defective parts. When the number of defective parts of the defect type does not meet the requirement, the defect problem type of the defect type is determined as the key problem type; When the number of defective parts of the defect type meets the requirement: When the number of defective parts of the defect type is less than a preset number threshold, determining that the defect problem type of the defect type is a general problem type; When the number of defective parts of the defect type is not less than the preset number threshold: Get the number of defective parts in different production batches. When there is a production batch with a number of defective parts greater than the preset part number threshold: When the number of defective parts is greater than the preset part number threshold and the number of production batches does not meet the requirement, the defect problem type of the defect type is determined to be a key problem type; When the number of defective parts is greater than the number of production batches of the preset part number threshold and the requirement is met, the defect problem type of the defect type is determined to be a serious problem type; When there are no production batches with a number of defective parts greater than the preset part quantity threshold: Based on the percentage and quantity of defective parts in different production batches, the defect coefficients of the defect types in different production batches are determined. When there is a production batch with a defect coefficient greater than the set value of the defect coefficient for the defect type: When the number of production batches whose defect coefficient is greater than the set value of the defect coefficient does not meet the requirement, the defect problem type of the defect type is determined to be a key problem type; When the number of production batches whose defect coefficient is greater than the set value of the defect coefficient meets the requirement, the defect problem type of the defect type is determined to be a serious problem type; When the defect type has a production batch with a defect coefficient but no defect coefficient setting value: The defect coefficient evaluation amount of the defect type is determined according to the average value of the defect coefficient of the defect type in different production batches and the proportion of the production batches with test defect data, and the defect problem type of the defect type is determined using the defect coefficient evaluation amount.

[0058] Specifically, Figure 5 As shown, the method for determining the abnormal probability of the production batch is: S31 determines the quantity ratio of parts with quality defects corresponding to different defect types based on the test defect data of different defect types in the production batch; S32 determines preset quantity ratios of different defect types based on defect problem types of different defect types, and determines abnormal coefficients of different defect types based on the ratio of the quantity ratios of parts with quality defects corresponding to different defect types to the preset quantity ratios; S33 determines the abnormal probability of the production batch based on the weights of the abnormal coefficients of different defect types.

[0059] Furthermore, the abnormal probability of the production batch ranges from 0 to 1, wherein when the abnormal probability of the production batch is greater than a preset probability threshold, the production batch is determined to be a quality defective production batch.

[0060] The test defect data of different defect types in different production batches are obtained, and the abnormal probabilities of different production batches and the quality defect production batches are determined in combination with the defect problem types of different defect types.

[0061] In another embodiment, the method for determining the abnormal probability of the production batch is: Determine the parts with quality defects in the production batch based on the test defect data of different defect types in the production batch, and treat them as defective parts; When the number of defective parts is greater than the preset number of parts, it is determined that the production batch is a quality defective production batch; When the number of defective parts is not greater than the preset number of parts, the defect quantity ratios of different production batches are determined based on the quantity ratios of defective parts in different production batches, and the average value of the defect quantity ratios of different production batches is taken as the defect quantity ratio average value; when the quantity ratio of defective parts in the production batch is greater than the defect quantity ratio average value, it is determined that the production batch is a quality defect production batch; When the percentage of defective parts in the production batch is not greater than the average defect percentage: Determine the quantity ratio of parts with quality defects corresponding to different defect types based on the test defect data of different defect types in the production batch; when the quantity ratio of parts with quality defects corresponding to different defect types are all within a preset ratio range, determine that the production batch is a quality defect production batch; When the proportion of parts with quality defects is not within the preset proportion range, the defect type: Determine the preset quantity ratios of different defect types based on the defect problem types of different defect types. When there is a defect type whose quantity ratio is greater than the preset quantity ratio, determine that the production batch belongs to a quality defect production batch. When there is no defect type whose quantity ratio is greater than the preset quantity ratio, the abnormality coefficients of different defect types are determined based on the ratio of the quantity ratio of parts and components with quality defects corresponding to different defect types to the preset quantity ratio, and the abnormality probability of the production batch is determined based on the weights of the abnormality coefficients of different defect types.

[0062] Specifically, Figure 6 As shown, the method for determining the defect type with quality problems is: S41 determines the ratio of the number of defective parts corresponding to the defect types in different normal production batches using the test defect data of the defect types in different normal production batches, and determines the defect abnormality coefficients of different normal production batches using the ratio of the number of defective parts corresponding to the defect types in different normal production batches; S42 determines defect anomaly assessment quantities of different normal production batches according to the abnormal probabilities and defect anomaly coefficients of different normal production batches; S43 determines a defect average value of the defect type based on average values ​​of defect anomaly evaluation amounts of different normal production batches, and uses the defect average value to determine whether the defect type is a defect type with quality problems.

[0063] Furthermore, the defect anomaly assessment amount of the normal production batch is determined according to the product of the abnormal probability of the normal production batch and the defect anomaly coefficient.

[0064] Optionally, when the defect average value is greater than a preset defect threshold, the defect type is determined to be a defect type with quality problems.

[0065] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0066] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0067] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. An air conditioning test quality management system, characterized in that: Specifically include: Model identification module, test processing module, test data management module; The model identification module is responsible for identifying the model of the air conditioner parts and components to obtain the identification result; The test processing module is responsible for automatically performing test processing based on the recognition result to obtain test data; The test data management module is responsible for tracing the test data of the air-conditioning components and determining the defect type of the quality problem according to the analysis results of the test data of the air-conditioning components in different production batches.

2. The air conditioning test quality management system according to claim 1, characterized in that: The test processing module includes 3 temperature acquisition channels, 1 cooling control channel, 2 heating control channels, damper control and product short-circuit test.

3. The air conditioning test quality management system according to claim 2, characterized in that: The heating control 2 includes two modes: electromagnetic control and electric control.

4. The air conditioning test quality management system according to claim 1, characterized in that: The test quality management system also includes a product batch information management module, and can set the personnel and production line information of the test products of the air-conditioning parts.

5. An air conditioning test data analysis and processing method, applied to an air conditioning test quality management system according to any one of claims 1 to 4, characterized in that: Specifically include: Determining test defect data of different air conditioner components based on the analysis results of the air conditioner test data, and determining suspected defective components among the air conditioner components using the analysis results of the test defect data; Based on the test defect data of the suspected defective component, determine the distribution data of the test defect data of different defect types in different production batches, and use the distribution data to determine the defect problem type in the defect type; Obtain test defect data of different defect types in different production batches, and determine the abnormal probability of different production batches and quality defect production batches based on the defect problem types of different defect types; The production batches excluding the production batches with quality defects are regarded as normal production batches. The defect types with quality problems are determined based on the test defect data of the defect types in different normal production batches and the abnormal probability, and the defect types with quality problems are output for processing.

6. The air conditioning test data analysis and processing method according to claim 5, characterized in that: The air conditioning components include fan control components, temperature collection circuits, cooling control circuits, heating control circuits, damper control switches and product casings.

7. The air conditioning test data analysis and processing method according to claim 5, characterized in that: The test defect data includes the number of air conditioner parts with quality defects in different production batches.

8. The air conditioning test data analysis and processing method according to claim 5, characterized in that: The method for determining the suspected defective parts in the air conditioner parts is: The air-conditioning parts with quality defects are regarded as defective parts, and the number of defective parts of the air-conditioning parts in different production batches is determined based on the test defect data in different production batches; Determining defective production batches among the production batches using the number of defective parts in different production batches; Determine whether the air conditioning component is a suspected defective component based on the number of the defective production batches.

9. The air conditioning test data analysis and processing method according to claim 8, characterized in that: When the proportion of the number of defective parts in the production batch does not meet the requirement, the production batch is determined to be a defective production batch.

10. The air conditioning test data analysis and processing method according to claim 5, characterized in that: The method for determining the defect type with quality problems is: Determine the ratio of the number of defective parts corresponding to the defect types in different normal production batches using the test defect data of the defect types in different normal production batches, and determine the defect abnormality coefficients of different normal production batches using the ratio of the number of defective parts corresponding to the defect types in different normal production batches; Determine the defect anomaly assessment amount of different normal production batches according to the abnormal probability and defect anomaly coefficient of different normal production batches; Based on the average values ​​of defect anomaly evaluation quantities of different normal production batches, a defect average value of the defect type is determined, and the defect average value is used to determine whether the defect type is a defect type with quality problems.

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