An air conditioner test data analysis and processing method and a test quality management system

Abstract

The present invention provides an air conditioner test data analysis and processing method and a test quality management system, belonging to the technical field of data processing, specifically including: among them, the model identification module is responsible for identifying the models of air conditioner components to obtain an identification result, the test processing module is responsible for automatically performing 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 air conditioner components. According to the analysis results of the test data of air conditioner components in different production batches, the defect types with quality problems are determined, improving the reliability of quality control processing.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and particularly relates to a method for analyzing and processing air conditioner test data and a test quality management system. Background Art

[0002] An automotive air conditioning device, abbreviated as automotive air conditioner, is used to adjust and control the temperature, humidity, air cleanliness, and air flow in the automotive cabin to the optimal state, providing a comfortable riding environment for passengers, reducing travel fatigue; creating good working conditions for the driver, and playing an important role in ensuring safe driving for the ventilation device.

[0003] In order to process the test data of the automotive air conditioning device, in the invention patent application CN202410693788.2, "A method, device, and terminal for evaluating and optimizing the operation sound of an air conditioner outlet", by formulating subjective evaluation methods and objective test methods for the automotive air conditioner outlet, forming sound development indicators, and providing optimization solutions through structural analysis, problems can be quickly and accurately solved through the optimization solutions when problems occur, reducing the optimization time cycle. However, through analysis, the following technical problems exist:

[0004] In the process of analyzing and processing air conditioner test data, when quality problems occur in air conditioner components, in addition to the self-design problems of air conditioner components, the production quality of air conditioner components will also have a certain impact on the quality defects of air conditioner components. If the production quality of different batches is ignored, it is impossible to accurately identify the design problems of air conditioner components.

[0005] In view of the above technical problems, specifically, the present application provides a method for analyzing and processing air conditioner test data and a test quality management system. Summary of the Invention

[0006] To achieve the object of the present invention, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present application provides a test quality management system for an air conditioner, specifically including:

[0008] A model identification module, a test processing module, and a test data management module;

[0009] Among them, the model identification module is responsible for identifying the model of the air conditioner component to obtain an identification result;

[0010] The test processing module is responsible for automatically performing test processing based on the identification result to obtain test data;

[0011] 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 based on the analysis results of the test data of the air-conditioning components in different production batches.

[0012] 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 ground short circuit test.

[0013] A further technical solution is that the heating control 2 includes two modes: electromagnetic control and electric control.

[0014] A further technical solution is 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.

[0015] 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.

[0016] 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.

[0017] 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:

[0018] S1 determines test defect data of different air conditioner components based on the analysis results of the air conditioner test data, and uses the analysis results of the test defect data to determine suspected defective components among the air conditioner components;

[0019] S2: determining 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 determining the defect problem type in the defect type using the distribution data;

[0020] S3 obtains test defect data of different defect types in different production batches, and combines the defect problem types of different defect types to determine the abnormal probability of different production batches and the quality defect production batches;

[0021] 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 and abnormal probabilities of the defect types in different normal production batches, and outputs the defect types with quality problems for processing.

[0022] The beneficial effects of the present invention are as follows:

[0023] By using the test defect data of different defect types and the defect problem types of the defect types, the determination of the production batches with quality defects in the production batches is carried out. It not only takes into account the number of parts with quality defects in the production batches, but also considers the differences in the distribution data of different defect types in different production batches, and the differences in the defect problem types caused by the differences in the abnormal occurrence probabilities, thereby realizing the screening of the production batches with defective production quality, and also laying a foundation for further improving the recognition accuracy of the defect types with quality defects.

[0024] Based on the test defect data and abnormal probabilities of the defect types in different normal production batches, the determination of the defect types with quality problems is carried out, thus avoiding the influence of the production batches with defective production quality, realizing the recognition of the defect types with quality problems from the test defect data of the defect types in the normal production batches, and at the same time comprehensively considering the abnormal probabilities of different normal production batches, and also realizing the comprehensive consideration of the degree of the quality defect abnormal probabilities of different normal production batches, improving the reliability of quality management.

[0025] A further technical solution lies in that the air-conditioning parts include fan control parts, temperature acquisition circuits, refrigeration control circuits, heating control circuits, damper control switches and product shells.

[0026] A further technical solution lies in that the test defect data includes the number of air-conditioning parts with quality defects in different production batches.

[0027] A further technical solution lies in that the method for determining the suspected defective parts in the air-conditioning parts is as follows:

[0028] Taking the air-conditioning parts with quality defects as defective parts, based on the test defect data in different production batches, determining the number of defective parts of the air-conditioning parts in different production batches;

[0029] Using the number of defective parts in different production batches to determine the defective production batches in the production batches;

[0030] Determining whether the air-conditioning parts are suspected defective parts according to the number of the defective production batches.

[0031] A further technical solution lies in that when the proportion of the number of defective parts in the production batch does not meet the requirements, the production batch is determined as a defective production batch.

[0032] 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.

[0033] A further technical solution is that the method for determining the suspected defective parts among the air-conditioning parts is as follows:

[0034] Determine the number of defective air-conditioning parts in different production batches based on test defect data of the air-conditioning parts in the different production batches;

[0035] calculating the total number of defective parts of the air conditioner parts using the number of defective parts in different production batches;

[0036] Determine whether the air conditioner component is a suspected defective component based on the total number of the defective components.

[0037] A further technical solution is that the method for determining the defect type with quality problems is:

[0038] Using the test defect data of defect types in different normal production batches, determine the percentage of defective parts corresponding to the defect types in the different normal production batches, and use the percentage of defective parts corresponding to the defect types in the different normal production batches to determine the defect abnormality coefficients of the different normal production batches;

[0039] Determine the defect anomaly assessment amount of different normal production batches based on the abnormal probability and defect anomaly coefficient of different normal production batches;

[0040] Based on the average values of defect anomaly evaluation amounts 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.

[0041] A further technical solution is that the defect anomaly assessment amount of the normal production batch is determined based on the product of the abnormality probability of the normal production batch and the defect anomaly coefficient.

[0042] 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.

[0043] Other features and advantages will be described in the following description. The objectives and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0044] 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

[0045] 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 accompanying drawings.

[0046] Figure 1 It is a framework diagram of the air conditioning test quality management system;

[0047] Figure 2 It is a flow chart of an air conditioning test data analysis and processing method;

[0048] Figure 3 A flowchart of a method for identifying suspected defective parts among air conditioner components;

[0049] Figure 4 is a flow chart of a method for determining a defect problem type of a defect type;

[0050] Figure 5 is a flow chart of a method for determining the probability of abnormality of a production batch;

[0051] Figure 6 This is a flowchart of a method for determining defect types that cause quality problems.

[0052] Reference numerals:

[0053] 1. Model identification module, 2. Test processing module, 3. Test data management module. DETAILED DESCRIPTION

[0054] To help those skilled in the art better understand the technical solutions in this specification, the following will provide a clear and complete description of the technical solutions in the embodiments of this specification, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this specification without creative work should fall within the scope of protection of this specification. Example

[0055] like Figure 1 As shown, the present application provides an air conditioning test quality management system, specifically including:

[0056] Model identification module (1), test processing module (2), test data management module (3);

[0057] The model identification module is responsible for identifying the model of the air conditioner parts and obtaining the identification result;

[0058] The test processing module is responsible for automatically performing test processing based on the recognition result to obtain test data;

[0059] 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 based on the analysis results of the test data of the air-conditioning components in different production batches.

[0060] 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.

[0061] Specifically, the heating control 2 includes two modes: electromagnetic control and electric control.

[0062] It is understandable that the test quality management system further includes a test data display module, which is responsible for displaying the test data of the air-conditioning components.

[0063] 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.

[0064] 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

[0065] 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.

[0066] Suspected defective parts are air-conditioning parts with quality defects accounting for more than 0.1.

[0067] Production batches with quality defects in the defect type are defined 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 defined 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 greater than 0.2 are defined as general problem types.

[0068] Using the test defect data of different defect types in the production batch, determine the proportion of the number of parts with quality defects corresponding to different defect types. Based on the defect problem types of different defect types, determine the preset proportion of the number of different defect types. Based on the ratio of the proportion of the number of parts with quality defects corresponding to different defect types to the preset proportion, determine the anomaly coefficient of different defect types. Based on the weighted sum of the anomaly coefficients of different defect types, determine the anomaly probability of the production batch. When the anomaly probability is greater than 0.6, determine that the production batch is a quality defect production batch.

[0069] Using the proportion of the number of defective parts corresponding to the defect types in different normal production batches, determine the defect anomaly coefficient of different normal production batches. According to the product of the anomaly probability and the defect anomaly coefficient of different normal production batches, determine the defect anomaly evaluation amount of different normal production batches. When the average value of the defect anomaly evaluation amounts of different normal production batches is greater than 0.5, determine that the defect type is a defect type with quality problems.

[0070] To solve the above problems, according to one aspect of the present invention, as Figure 2 shown, the present application provides an air conditioner test data analysis and processing method, which is applied to the above-mentioned air conditioner test quality management system, and specifically includes:

[0071] S1 Based on the analysis results of the air conditioner test data, determine the test defect data of different air conditioner parts, and use the analysis results of the test defect data to determine the suspected defective parts in the air conditioner parts;

[0072] S2 Based on the test defect data of the suspected defective parts, 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 types in the defect types;

[0073] S3 Obtain the test defect data of different defect types in different production batches, and combine the defect problem types of different defect types to determine the anomaly probability of different production batches and the quality defect production batches;

[0074] S4 Use the production batches excluding the quality defect production batches as normal production batches. Based on the test defect data and the anomaly probability of the defect types in different normal production batches, determine the defect types with quality problems, and output the defect types with quality problems.

[0075] Further, the air conditioner parts include fan control parts, temperature acquisition circuits, refrigeration control circuits, heating control circuits, damper control switches and product shells.

[0076] Specifically, the test defect data includes the quantity of air conditioner components with quality defects in different production batches.

[0077] Specifically, as Figure 3 shown, the method for determining suspected defective components among the air conditioner components is as follows:

[0078] S101 Take the air conditioner components with quality defects as defective components, and based on the test defect data in different production batches, determine the quantity of defective components of the air conditioner components in different production batches;

[0079] S102 Use the quantity of defective components in different production batches to determine the defective production batches in the production batches;

[0080] S103 Determine whether the air conditioner components are suspected defective components according to the quantity of the defective production batches.

[0081] Optionally, when the proportion of the quantity of defective components in the production batch does not meet the requirements, then determine the production batch as a defective production batch.

[0082] Further, when the quantity of defective production batches of the air conditioner components is greater than the preset batch quantity, then determine the air conditioner components as suspected defective components.

[0083] In another embodiment, the method for determining suspected defective components among the air conditioner components is as follows:

[0084] Take the air conditioner components with quality defects as defective components, and based on the test defect data in different production batches, determine the quantity of defective components of the air conditioner components in different production batches;

[0085] Use the quantity of defective components in different production batches to calculate the total quantity of defective components of the air conditioner components;

[0086] Determine whether the air conditioner components are suspected defective components according to the total quantity of the defective components.

[0087] Optionally, the method for determining suspected defective components among the air conditioner components is as follows:

[0088] S11 Take the air conditioner components with quality defects as defective components, and based on the test defect data in different production batches, determine the quantity of defective components of the air conditioner components in different production batches;

[0089] S12 determines the quality defect coefficient of the air conditioner component parts in different production batches based on the number of defective parts and the proportion of the number of defective parts in different production batches;

[0090] S13 determines the comprehensive defect coefficient of the air conditioner component parts according to the quality defect coefficient of the air conditioner component parts in different production batches, and uses the comprehensive defect coefficient to determine whether the air conditioner component parts are suspected defective parts.

[0091] Optionally, the above step S11 includes the following content:

[0092] S111 takes the air conditioner component parts with quality defects as defective parts, and based on the test defect data in different production batches, determines the number of defective parts of the air conditioner component parts in different production batches. When the total number of defective parts in different production batches does not meet the requirements, it is determined that the air conditioner component parts are suspected defective parts. When the total number of defective parts in different production batches meets the requirements, it proceeds to step S112;

[0093] S112 determines the production batches with the number of defective parts greater than the preset number of defective parts based on the number of defective parts in different production batches. When there are production batches with the number of defective parts greater than the preset number of defective parts, it proceeds to step S113. When there are no production batches with the number of defective parts greater than the preset number of defective parts, it proceeds to step S12;

[0094] S113 takes the production batches with the number of defective parts greater than the preset number of defective parts as defective production batches. When the number of defective production batches does not meet the requirements, it is determined that the air conditioner component parts are suspected defective parts. When the number of defective production batches meets the requirements, it proceeds to step S12.

[0095] Optionally, the above step S12 includes the following content:

[0096] S121 determines the quality defect coefficient of the air conditioner component parts in different production batches based on the number of defective parts and the proportion of the number of defective parts in different production batches. When the average value of the quality defect coefficient of the air conditioner component parts in different production batches does not meet the requirements, it is determined that the air conditioner component parts are suspected defective parts. When the average value of the quality defect coefficient of the air conditioner component parts in different production batches meets the requirements, it proceeds to step S122;

[0097] S122 determines that the air conditioner component parts do not belong to suspected defective parts when the quality defect coefficients of different production batches are all less than the preset defect coefficient threshold. When there are production batches with quality defect coefficients not less than the preset defect coefficient threshold, it proceeds to step S123;

[0098] 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.

[0099] 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.

[0100] 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.

[0101] 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.

[0102] Specifically, such as Figure 4 As shown, the method for determining the defect problem type of the defect type is:

[0103] S21 treats air conditioner parts with quality defects of the above defect types as defective parts;

[0104] S22 determines defect coefficients of the defect types in different production batches based on the percentage of defective parts in different production batches;

[0105] S23 determines an average defect coefficient of the defect type according to the 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.

[0106] Furthermore, the defect problem type of the defect type is determined by using the average defect coefficient, specifically including:

[0107] The defect problem type of the defect type is determined based on a preset problem type corresponding to the average defect coefficient of the defect type.

[0108] Specifically, the defect problem types include general problem types, serious problem types and key problem types.

[0109] 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.

[0110] Optionally, the method for determining the defect problem type of the defect type is:

[0111] Take the air conditioner parts with quality defects in the defect type as defective parts. When the number of defective parts of the defect type does not meet the requirements, determine that the defect problem type of the defect type is a key problem type;

[0112] When the number of defective parts of the defect type meets the requirements:

[0113] When the number of defective parts of the defect type is less than the preset quantity threshold, determine that the defect problem type of the defect type is a general problem type;

[0114] When the number of defective parts of the defect type is not less than the preset quantity threshold:

[0115] Obtain the number of defective parts in different production batches. When there is a production batch with the number of defective parts greater than the preset part quantity threshold:

[0116] When the number of production batches with the number of defective parts greater than the preset part quantity threshold does not meet the requirements, determine that the defect problem type of the defect type is a key problem type;

[0117] When the number of production batches with the number of defective parts greater than the preset part quantity threshold meets the requirements, determine that the defect problem type of the defect type is a serious problem type;

[0118] When there is no production batch with the number of defective parts greater than the preset part quantity threshold:

[0119] Based on the proportion and quantity of the number of defective parts in different production batches, determine the defect coefficient of the defect type in different production batches. When there is a production batch with the defect coefficient of the defect type greater than the defect coefficient setting value:

[0120] When the number of production batches with the defect coefficient greater than the defect coefficient setting value does not meet the requirements, determine that the defect problem type of the defect type is a key problem type;

[0121] When the number of production batches with the defect coefficient greater than the defect coefficient setting value meets the requirements, determine that the defect problem type of the defect type is a serious problem type;

[0122] When there is a production batch with the defect coefficient of the defect type not existing the defect coefficient setting value:

[0123] Determine the defect coefficient evaluation quantity of the defect type according to the average value of the defect coefficient of the defect type in different production batches and the proportion of the number of production batches with test defect data, and use the defect coefficient evaluation quantity to determine the defect problem type of the defect type.

[0124] Specifically, as Figure 5 shown, the method for determining the abnormal probability of the production batch is as follows:

[0125] S31: Based on the test defect data of different defect types in the production batch, determine the proportion of the number of parts with quality defects corresponding to different defect types;

[0126] S32: Based on the defect problem types of different defect types, determine the preset proportion of the number of different defect types. Based on the ratio of the proportion of the number of parts with quality defects corresponding to different defect types to the preset proportion of the number of parts, determine the abnormal coefficient of different defect types;

[0127] S33: Based on the sum of the weights of the abnormal coefficients of different defect types, determine the abnormal probability of the production batch.

[0128] Furthermore, the value range of the abnormal probability of the production batch is between 0 and 1. When the abnormal probability of the production batch is greater than the preset probability threshold, it is determined that the production batch is a production batch with quality defects.

[0129] Obtain the test defect data of different defect types in different production batches, and combine the defect problem types of different defect types to determine the abnormal probability of different production batches and the production batches with quality defects.

[0130] In another embodiment, the method for determining the abnormal probability of the production batch is as follows:

[0131] Based on the test defect data of different defect types in the production batch, determine the parts with quality defects in the production batch and use them as defective parts;

[0132] When the number of defective parts is greater than the preset number of parts, it is determined that the production batch belongs to the production batch with quality defects;

[0133] When the number of defective parts is not greater than the preset number of parts, based on the proportion of the number of defective parts in different production batches, determine the proportion of the number of defective parts in different production batches, and use the average value of the proportion of the number of defective parts in different production batches as the average proportion of defective parts. When the proportion of the number of defective parts in the production batch is greater than the average proportion of defective parts, it is determined that the production batch belongs to the production batch with quality defects;

[0134] When the proportion of the number of defective parts in the production batch is not greater than the average proportion of defective parts:

[0135] Using the test defect data of different defect types in the production batch, determine the proportion of the number of parts with quality defects corresponding to different defect types. When the proportion of the number of parts with quality defects corresponding to different defect types is within the preset proportion range, it is determined that the production batch belongs to the quality defect production batch;

[0136] When there is a defect type in which the proportion of the number of parts with quality defects is not within the preset proportion range:

[0137] Using the defect problem types of different defect types, determine the preset quantity proportion of different defect types. When there is a defect type with a quantity proportion greater than the preset quantity proportion, it is determined that the production batch belongs to the quality defect production batch;

[0138] When there is no defect type with a quantity proportion greater than the preset quantity proportion, based on the ratio of the proportion of the number of parts with quality defects corresponding to different defect types to the preset quantity proportion, determine the abnormality coefficient of different defect types, and determine the abnormality probability of the production batch based on the weighted sum of the abnormality coefficients of different defect types.

[0139] Specifically, as Figure 6 shown, the method for determining the defect type with quality problems is:

[0140] S41 Using the test defect data of defect types in different normal production batches, determine the proportion of the number of defective parts corresponding to the defect types in different normal production batches, and use the proportion of the number of defective parts corresponding to the defect types in different normal production batches to determine the defect abnormality coefficient of different normal production batches;

[0141] S42 According to the abnormality probability and defect abnormality coefficient of different normal production batches, determine the defect abnormality evaluation amount of different normal production batches;

[0142] S43 Based on the average value of the defect abnormality evaluation amounts of different normal production batches, determine the defect average value of the defect type, and use the defect average value to determine whether the defect type is a defect type with quality problems.

[0143] Furthermore, the defect abnormality evaluation amount of the normal production batch is determined according to the product of the abnormality probability and defect abnormality coefficient of the normal production batch.

[0144] Optionally, when the defect average value is greater than the preset defect threshold, it is determined that the defect type is a defect type with quality problems.

[0145] Each embodiment in this specification is described in a progressive manner. For the identical or similar parts among the embodiments, reference can be made to each other, and the differences between each embodiment and other embodiments are emphasized. In particular, for the embodiments of the apparatus, device, and non-volatile computer storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments.

[0146] The specific embodiments of this specification are described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0147] The above description is only for one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, various changes and modifications can be made to one or more embodiments of this specification. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. An air conditioner test quality management system, characterized in that Specifically, it includes: Model identification module, test processing module, test data management module; Among them, the model identification module is responsible for identifying the models of air-conditioning components to obtain identification results; The test processing module is responsible for performing automatic test processing based on the identification results 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 types with quality problems according to the analysis results of the test data of the air-conditioning components in different production batches; Among them, the method for determining the defect types with quality problems is: Based on the analysis results of the air-conditioning test data, determine the test defect data of different air-conditioning components, and use the analysis results of the test defect data to determine the suspected defective components in the air-conditioning components; Based on the test defect data of the suspected defective components, 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 types in the defect types; Obtain the test defect data of different defect types in different production batches, and combine the defect problem types of different defect types to determine the abnormal probability of different production batches and the production batches with quality defects; Take the production batches excluding the production batches with quality defects as normal production batches, and based on the test defect data and abnormal probability of the defect types in different normal production batches, determine the defect types with quality problems, and output the defect types with quality problems.

2. The air conditioner test quality management system according to claim 1, wherein The test processing module includes 3 channels for temperature acquisition, 1 channel for refrigeration control, 2 channels for heating control, air damper control and product-to-ground short-circuit test.

3. The air conditioner test quality management system according to claim 2, wherein, The 2 channels of heating control include two methods: electromagnetic control and electric control.

4. The air conditioner 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 information of the personnel and production lines of the test products of the air-conditioning components.

5. The air conditioner test quality management system according to claim 1, characterized in that, The air-conditioning components include fan control components, temperature acquisition circuits, refrigeration control circuits, heating control circuits, air damper control switches and product shells.

6. The air conditioner test quality management system according to claim 1, characterized in that, The test defect data includes the number of air-conditioning components with quality defects in different production batches.

7. The air conditioner test quality management system according to claim 1, characterized in that The method for determining the suspected defective components in the air-conditioning components is: Take the air-conditioning components with quality defects as defective components, and based on the test defect data in different production batches, determine the number of defective components of the air-conditioning components in different production batches; Use the number of defective components in different production batches to determine the defective production batches in the production batches; Determine whether the air-conditioning components are suspected defective components according to the number of defective production batches; 8. The air conditioner test quality management system according to claim 7, characterized in that, When the proportion of the number of defective components in the production batch does not meet the requirements, it is determined that the production batch is a defective production batch.

9. The air conditioner test quality management system according to claim 1, characterized in that, The method for determining the defect types with quality problems is: Using the test defect data of defect types in different normal production batches, determine the proportion of the number of defective parts corresponding to the defect types in different normal production batches, and use the proportion of the number of defective parts corresponding to the defect types in different normal production batches to determine the defect abnormality coefficients of different normal production batches; According to the abnormal probabilities and defect abnormality coefficients of different normal production batches, determine the defect abnormality evaluation amounts of different normal production batches; Based on the average value of the defect abnormality evaluation amounts of different normal production batches, determine the defect average value of the defect type, and use the defect average value to determine whether the defect type is a defect type with quality problems.

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