SPC quality control multi-dimensional Chart detection method and device

Abstract

The invention provides an SPC quality control multi-dimensional Chart detection method and device, and the method comprises the steps: determining a plurality of key control points for a target product in a statistical process control SPC system according to a customer demand proposed for the target product; determining each key control point as a detection dimension in the SPC system, and pre-binding a judgment rule for each detection dimension; associating the plurality of detection dimensions and the judgment rule bound with each detection dimension to a preset chart of an electronic data acquisition (EDC) system in the SPC system; executing data value receiving processing on the target product in the EDC system; and displaying a preset chart output by the EDC system in the SPC system. According to the method and the device, multi-dimensional quality checking is carried out on the target product, so that more comprehensive quality detection of the target product in the SPC system is realized.

Description

Technical Field

[0001] The present application relates to the field of production process control, and more specifically, to a SPC quality control multi-dimensional Chart detection method and device. Background Art

[0002] The current SPC (Statistical Process Control) system mainly manages by charts based on product parameter dimensions. This method is very effective in monitoring the quality of a single product or a single production line.

[0003] However, when the parameters of different products are included in the same chart for monitoring, the system may neglect abnormal monitoring when judging the upward or downward trend of multiple consecutive data points, resulting in the omission of abnormal data points, which in turn has an adverse impact on production quality. Summary of the invention

[0004] In view of this, the purpose of this application is to provide an SPC quality control multi-dimensional Chart detection method and device, aiming to overcome at least one of the above-mentioned defects.

[0005] In a first aspect, the present application provides an SPC quality control multi-dimensional Chart detection method, the method comprising: determining multiple key control points for the target product in a statistical process control (SPC) system according to customer requirements for the target product; determining each key control point as a detection dimension in the SPC system, and pre-binding a judgment rule for each detection dimension; associating multiple detection dimensions and the judgment rules bound to each detection dimension to a preset chart of an electronic data collection (EDC) system in the SPC system, the preset chart being a collection value chart corresponding to the target product; importing multiple data subsets of the target product into the SPC system; performing data collection value processing on the target product in the EDC system, the data collection value processing comprising: for each data subset, extracting the detection parameter value under each detection dimension from the data subset, and identifying the detection results of the data subset under different detection dimensions according to the judgment rules bound to each detection dimension; and displaying a preset chart output by the EDC system in the SPC system, the preset chart showing the detection results of multiple data subsets of the target product under multiple detection dimensions.

[0006] In a possible implementation, according to customer requirements for a target product, the step of determining a plurality of critical control points for the target product in a statistical process control (SPC) system includes:

[0007] In a possible implementation, in the SPC system, multiple first key control characteristic keys are obtained from the manufacturing execution system MES, and multiple second key control characteristic keys are obtained from the equipment automation EAP system; in the SPC system, based on customer requirements for the target product, multiple key control points for the target product are determined from the multiple first key control characteristic keys and / or the multiple second key control characteristic keys.

[0008] In a possible implementation, the method further includes: obtaining an original data set, the original data set including detection parameter values ​​of multiple products; classifying the original data set according to product type to obtain a data set corresponding to each product type, and forming a data subset with the detection parameter values ​​corresponding to a product sample of each product type.

[0009] In a possible implementation, for each data subset, the detection parameter value under each detection dimension is extracted from the data subset, and the detection result of the data subset under different detection dimensions is identified according to the judgment rules bound to each detection dimension. The steps include: extracting the detection parameter value under each detection dimension from the data subset; for each detection dimension, judging whether the detection parameter value under the detection dimension satisfies the judgment rule bound to the detection dimension; if the judgment rules under all detection dimensions are satisfied, determining that the detection result of the data subset is qualified; if there is at least one of the multiple detection parameter values ​​that does not satisfy the judgment rule bound to the corresponding detection dimension, determining that the detection result of the data subset is unqualified.

[0010] In a possible implementation, the horizontal axis of the preset chart indicates the number of the data subset, and the vertical axis of the preset chart indicates the comprehensive detection index of the data subset in all detection dimensions, wherein the data points of the data subset with unqualified detection results on the preset chart are presented in a first display mode, and the data points of the data subset with qualified detection results on the preset chart are presented in a second display mode.

[0011] In a possible implementation, the target product includes a key product, and the preset detection dimension of the key product is pre-bound to a first judgment rule and a second judgment rule, the second qualified interval under the second judgment rule is included in the first qualified interval under the first judgment rule, and the first qualified interval does not overlap with the second qualified interval, wherein, for the key product, the step of data collection and processing also includes: for each data subset of the key product, extracting the detection parameter value under the preset detection dimension from the data subset; judging whether the detection parameter value under the preset detection dimension satisfies the first judgment rule, and judging whether the detection parameter value under the preset detection dimension satisfies the second judgment rule; if both the first judgment rule and the second judgment rule are satisfied, determining that the detection result of the data subset is qualified; if at least one of the first judgment rule and the second judgment rule is not satisfied, determining that the detection result of the data subset is unqualified.

[0012] In a possible implementation, the method further includes: receiving a click operation on a data point on the preset chart; and displaying an information window in response to the click operation, wherein the information window displays the detection parameter value of the data subset corresponding to the data point in each detection dimension.

[0013] In a second aspect, the present application provides an SPC quality control multi-dimensional Chart detection device, the device comprising: a determination module, for determining multiple key control points for the target product in a statistical process control SPC system according to customer requirements for the target product; a binding module, for determining each key control point as a detection dimension in the SPC system, and pre-binding a judgment rule for each detection dimension; an association module, for associating multiple detection dimensions and the judgment rules bound to each detection dimension in the SPC system to a preset chart of an electronic data collection EDC system, the preset chart being a collection value chart corresponding to the target product; an import module, for importing multiple data subsets of the target product into the SPC system; a processing module, for performing data collection value processing for the target product in the EDC system, the data collection value processing comprising: for each data subset, extracting the detection parameter value under each detection dimension from the data subset, and identifying the detection result of the data subset under different detection dimensions according to the judgment rules bound to each detection dimension; an output module, for displaying a preset chart output by the EDC system in the SPC system, the preset chart showing the detection results of multiple data subsets of the target product under multiple detection dimensions.

[0014] In a third aspect, the present application also provides an electronic device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the SPC quality control multi-dimensional Chart detection method as described above are performed.

[0015] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the SPC quality control multi-dimensional Chart detection method as described above are executed.

[0016] The present application provides a SPC quality control multi-dimensional Chart detection method and device, wherein the method includes: determining multiple key control points for the target product in a statistical process control SPC system according to customer requirements for the target product; determining each key control point as a detection dimension in the SPC system, and pre-binding a judgment rule for each detection dimension; associating multiple detection dimensions and the judgment rules bound to each detection dimension to a preset chart of an electronic data collection (EDC) system in the SPC system; performing data collection processing for the target product in the EDC system; and displaying a preset chart output by the EDC system in the SPC system, wherein the preset chart displays the detection results of multiple data subsets of the target product under multiple detection dimensions. The present application achieves more comprehensive quality inspection of the target product in the SPC system by performing multi-dimensional quality inspection of the target product.

[0017] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 A flow chart of the SPC quality control multi-dimensional Chart detection method provided in the embodiment of the present application;

[0020] Figure 2 A flow chart of the detection result of identifying a data subset provided in an embodiment of the present application;

[0021] Figure 3A flowchart of the key product data collection and processing provided in the embodiment of the present application;

[0022] Figure 4 A schematic diagram of the structure of the SPC quality control multi-dimensional Chart detection device provided in an embodiment of the present application;

[0023] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application usually described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, each other embodiment obtained by those skilled in the art without making creative work belongs to the scope of protection of the present application.

[0025] First, the application scenarios to which this application is applicable are introduced. This application can be applied in the field of production process control.

[0026] The SPC system is a quality management tool based on statistical principles. It monitors and records key parameters in the production process and plots the fluctuation trend of data, thereby helping managers to promptly detect abnormal fluctuations in the production process and take corresponding corrective measures. The SPC control chart is usually composed of elements such as the center line, upper and lower control limits, and data points. The center line represents the average level of the data, and the upper and lower control limits are set according to the degree of fluctuation of the data to determine whether the data is within the normal fluctuation range.

[0027] However, the parameters of different products have different dimensions, ranges and fluctuation characteristics. When these parameters are included in the same chart for monitoring, the readability and accuracy of the chart will be reduced due to the differences between the parameters. Due to the differences between the parameters, the SPC system will encounter difficulties in judging the upward or downward trend of multiple consecutive data points. Especially when the fluctuation ranges of parameters of different products vary greatly, the SPC system may not be able to accurately identify the real trend changes, especially when abnormal data points are submerged in a large number of normal data points, the SPC system may not be able to detect and alarm in time.

[0028] Based on this, an embodiment of the present application provides an SPC quality control multi-dimensional Chart detection method and device, aiming to overcome the above-mentioned defects.

[0029] See also Figure 1 , Figure 1 This is a flow chart of a SPC quality control multi-dimensional Chart detection method provided in an embodiment of the present application. Figure 1 As shown in, the SPC quality control multi-dimensional Chart detection method provided in the embodiment of the present application includes:

[0030] S101. According to customer requirements for target products, multiple key control points for target products are determined in a statistical process control (SPC) system.

[0031] Here, the target product can be a variety of products, and it is necessary to analyze in detail the customer needs for each target product. These needs may include product quality characteristics, performance requirements, safety, reliability, durability and other aspects. After understanding the key quality indicators and key performance parameters of each product, multiple key control points for the target product are determined in the SPC system.

[0032] In a preferred example of the present application, in the SPC system, a plurality of first key control characteristic keys are obtained from the manufacturing execution system MES, and a plurality of second key control characteristic keys are obtained from the equipment automation EAP system.

[0033] Specifically, MES (Manufacturing Execution System) can capture data from the production site in real time and monitor production progress and status. Through the MES system, the enterprise can obtain multiple first key control characteristic keys related to the production of the target product. The first key control characteristic keys can be product (Product), technology (Technology), route (Route), operation (Oper), etc. The EAP (Equipment Automation Program) system is responsible for automatically controlling the equipment on the production line to ensure that the equipment produces according to predetermined parameters and processes. From the EAP system, multiple second key control characteristic keys can be obtained. The second key control characteristic keys can be equipment (Equipment), recipe (Recipe), sub-equipment (SubEquipment), etc. By obtaining key control characteristic keys from the MES system and the EAP system, in the SPC system, according to customer needs for the target product, multiple key control points for the target product are determined from multiple first key control characteristic keys and / or multiple second key control characteristic keys.

[0034] S102. In the SPC system, each key control point is determined as a detection dimension, and a judgment rule is pre-bound to each detection dimension.

[0035] Here, the multiple key control points determined in step S101 are converted into detection dimensions one by one. Each detection dimension represents a key monitoring point in the production process, and a set of judgment rules is pre-set for each detection dimension. The judgment rule can be a specific numerical range, which is used to evaluate whether the production data for each key control point deviates from this numerical range, so as to determine whether the production process is under control.

[0036] S103. In the SPC system, multiple detection dimensions and the judgment rules bound to each detection dimension are associated with a preset chart of the electronic data collection (EDC) system.

[0037] Here, the EDC (Electronic Data Capture) system is a platform software for data collection and transmission. The preset chart is the received value chart corresponding to the target product, which is used to intuitively display the changing trends and abnormal situations of production data.

[0038] S104. Import multiple data subsets of the target product into the SPC system.

[0039] In a preferred example of the present application, an original data set is obtained, the original data set including detection parameter values ​​of multiple products, the original data set is classified according to product type to obtain a data set corresponding to each product type, and the detection parameter values ​​corresponding to a product sample of each product type are formed into a data subset.

[0040] Specifically, the original data set refers to the detection parameter values ​​of multiple products, which may belong to different types or categories. The data subset is extracted from the data set of each product category. Each data subset contains all the detection parameter values ​​of a product sample belonging to the same product category. In this way, each data subset represents a specific product sample.

[0041] S105. Perform data value collection processing for the target product in the EDC system. The data value collection processing includes: for each data subset, extracting the detection parameter value under each detection dimension from the data subset, and identifying the detection results of the data subset under different detection dimensions according to the judgment rules bound to each detection dimension.

[0042] Here, the EDC system is used as a platform for data collection and processing. It receives data subsets from other systems or data sources and performs operations such as data extraction, verification and analysis. Data collection and processing refers to operations such as extracting test parameter values ​​and identifying test results for data subsets of target products. Using the extracted test parameter values ​​and the judgment rules bound to each test dimension, the test results of the data subset in each dimension can be identified. The test results are usually expressed as "qualified" or "unqualified", and can also include more detailed classifications, such as "excellent", "good", "general", etc.

[0043] Below through Figure 2 The specific steps of identifying the detection results of data subsets under different detection dimensions are specifically introduced.

[0044] Figure 2 A flowchart of the detection results of identifying a data subset provided in an embodiment of the present application.

[0045] S201. Extract detection parameter values ​​in each detection dimension from the data subset.

[0046] Here, the system needs to access the data subset and extract the corresponding detection parameter values ​​under each detection dimension.

[0047] S202: For each detection dimension, determine whether the detection parameter value under the detection dimension satisfies the determination rule bound to the detection dimension.

[0048] Here, the detection parameter value under each detection dimension is evaluated according to the preset judgment rules. The judgment rules define the pass and fail criteria under each detection dimension. The detection parameter value is compared with the threshold, range or condition defined in the judgment rule to determine whether the requirements are met.

[0049] S203: If the judgment rules under all detection dimensions are satisfied, it is determined that the detection result of the data subset is qualified.

[0050] S204: If at least one of the multiple detection parameter values ​​does not satisfy the judgment rule bound to the corresponding detection dimension, determine that the detection result of the data subset is unqualified.

[0051] return Figure 1 S106: Display a preset chart output by the EDC system in the SPC system, where the preset chart displays the detection results of multiple data subsets of the target product under multiple detection dimensions.

[0052] Here, the EDC system will summarize the test results of all data subsets and generate a preset chart, which is displayed in the SPC system. This preset chart provides an intuitive representation of the test results of the target product under multiple test dimensions. The preset chart can be a bar chart, line chart or scatter chart, etc., which helps relevant personnel quickly understand the product quality status, identify potential problems, and take corresponding improvement measures.

[0053] In a preferred example of the present application, the horizontal axis of the preset chart indicates the number of the data subset, and the vertical axis of the preset chart indicates the comprehensive detection index of the data subset in all detection dimensions, wherein the data points on the preset chart for the data subset with unqualified detection results are presented in a first display mode, and the data points on the preset chart for the data subset with qualified detection results are presented in a second display mode.

[0054] Specifically, the horizontal axis of the preset chart is used to indicate the number of the data subset, each data subset represents a sample of a target product, and its number can be a serial number, batch number or other unique identifier. The corresponding data subset can be identified by the number corresponding to the horizontal axis, and the vertical axis of the preset chart is used to indicate the comprehensive detection index of the data subset under all detection dimensions. The comprehensive detection index is a comprehensive indicator with the same measurement that summarizes the detection results under all detection dimensions. It can be a weighted average, total score or qualified rate under the detection dimension. This index reflects the overall quality status of the data subset at the corresponding multiple key control points.

[0055] For the data subsets whose test results are unqualified, their data points on the preset chart will be presented in a first display mode, which can be red, flashing, bold or other eye-catching marks to highlight these unqualified data points. For the data subsets whose test results are qualified, their data points on the preset chart will be presented in a second display mode, which can be green, normal display, thin lines or other less conspicuous marks to indicate that these data points are qualified.

[0056] In a preferred example of the present application, the user is allowed to obtain detailed information about the test results of the data subset under each test dimension by clicking on the data point on the chart. This interactivity enhances the usability and user satisfaction of the system, while supporting more in-depth data analysis and decision making.

[0057] In a preferred example of the present application, the target products include key products, and the preset detection dimensions of the key products are pre-bound to the first judgment rule and the second judgment rule. The second qualified interval under the second judgment rule is included in the first qualified interval under the first judgment rule, and the first qualified interval does not overlap with the second qualified interval.

[0058] Specifically, key products are considered key or special because of their importance, value, safety or other factors. Therefore, key products require stricter testing standards to ensure quality, and two judgment rules are bound to each preset testing dimension of each key commodity: the first judgment rule and the second judgment rule. The second qualified interval under the second judgment rule is a stricter subset of the first qualified interval under the first judgment rule, that is, the second qualified interval is completely included in the first qualified interval, but the two do not overlap, which means that products that meet the second judgment rule not only meet the looser first judgment rule, but also meet higher quality standards.

[0059] Below through Figure 3 This section introduces the steps for data collection and processing for key products.

[0060] Figure 3 This is a flowchart of the key product data collection and processing provided in the embodiment of the present application.

[0061] S301. For each data subset of a key product, extract a detection parameter value under a preset detection dimension from the data subset.

[0062] S302: Determine whether the detection parameter value under the preset detection dimension satisfies the first judgment rule, and determine whether the detection parameter value under the preset detection dimension satisfies the second judgment rule.

[0063] Here, it is necessary to check whether the detection parameter values ​​under each preset detection dimension meet both the first judgment rule and the second judgment rule. This is a double check process to ensure that key products not only meet the basic qualification standards, but also meet higher quality requirements.

[0064] If both the first judgment rule and the second judgment rule are satisfied, step S303 is executed to determine whether the detection result of the data subset is qualified.

[0065] If at least one of the first judgment rule and the second judgment rule is not satisfied, step S304 is executed to determine that the detection result of the data subset is unqualified.

[0066] Here, if the detection parameter values ​​of the data subset under all preset detection dimensions simultaneously meet the first judgment rule and the second judgment rule, then the detection result of the data subset is determined to be qualified. This means that the product has met the dual quality standards and can be considered to be of high quality. If the detection parameter values ​​of the data subset under any preset detection dimension do not simultaneously meet the first judgment rule and the second judgment rule (that is, at least one rule is not met), then the detection result of the data subset is determined to be unqualified, which means that the key product does not meet at least one quality standard and requires further investigation or processing. This data collection and processing step for key products reflects strict quality requirements. Through the dual judgment rules, it can be ensured that only truly high-quality products can pass the inspection.

[0067] Based on the same inventive concept, an SPC quality control multi-dimensional Chart detection device corresponding to the SPC quality control multi-dimensional Chart detection method is also provided in the embodiment of the present application. Since the principle of solving the problem by the device in the embodiment of the present application is similar to the above-mentioned SPC quality control multi-dimensional Chart detection method in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0068] See also Figure 4 , Figure 4 A schematic diagram of the structure of a multi-dimensional chart detection device for SPC quality control provided in an embodiment of the present application. Figure 4 This is a schematic diagram of the structure of another SPC quality control multi-dimensional Chart detection device provided in the embodiment of the present application. Figure 4 As shown in , the SPC quality control multi-dimensional Chart detection device 400 includes:

[0069] The determination module 401 is used to determine a plurality of critical control points for the target product in a statistical process control (SPC) system according to customer requirements for the target product.

[0070] The binding module 402 is used to determine each key control point as a detection dimension in the SPC system, and pre-bind a judgment rule to each detection dimension.

[0071] The association module 403 is used to associate multiple detection dimensions and the judgment rules bound to each detection dimension with a preset chart of the electronic data collection EDC system in the SPC system, and the preset chart is a received value chart corresponding to the target product.

[0072] The import module 404 is used to import multiple data subsets of the target product into the SPC system.

[0073] Processing module 405 is used to perform data value collection processing for the target product in the EDC system. The data value collection processing includes: for each data subset, extracting the detection parameter value under each detection dimension from the data subset, and identifying the detection results of the data subset under different detection dimensions according to the judgment rules bound to each detection dimension.

[0074] The output module 406 is used to display a preset chart output by the EDC system in the SPC system, where the preset chart displays the detection results of multiple data subsets of the target product under multiple detection dimensions.

[0075] See also Figure 5 , Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 5 As shown in , the electronic device 500 includes a processor 510 , a memory 520 and a bus 530 .

[0076] The memory 520 stores machine-readable instructions executable by the processor 510. When the electronic device 500 is running, the processor 510 communicates with the memory 520 via the bus 530. When the machine-readable instructions are executed by the processor 510, the above-mentioned Figure 1 to Figure 3 The steps of the SPC quality control multi-dimensional Chart detection method in the method embodiment shown, the specific implementation method can be found in the method embodiment, and will not be repeated here.

[0077] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the computer program can execute the above-mentioned Figure 1 to Figure 3 The steps of the SPC quality control multi-dimensional Chart detection method in the method embodiment shown, the specific implementation method can be found in the method embodiment, and will not be repeated here.

[0078] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0079] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0080] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0081] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0082] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application can essentially be embodied in the form of a software product, or in other words, the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0083] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A SPC quality control multi-dimensional Chart detection method, characterized in that: The method comprises: According to customer requirements for the target product, multiple critical control points for the target product are determined in a statistical process control (SPC) system; In the SPC system, each key control point is determined as a detection dimension, and a judgment rule is pre-bound for each detection dimension; In the SPC system, multiple detection dimensions and the judgment rules bound to each detection dimension are associated with a preset chart of the electronic data collection (EDC) system, where the preset chart is a received value chart corresponding to the target product; Importing multiple data subsets of the target product into an SPC system; Performing data value collection processing for the target product in the EDC system, the data value collection processing comprising: for each data subset, extracting a detection parameter value under each detection dimension from the data subset, and identifying a detection result of the data subset under different detection dimensions according to a judgment rule bound to each detection dimension; A preset chart output by the EDC system is displayed in the SPC system, wherein the preset chart shows the detection results of multiple data subsets of the target product under multiple detection dimensions.

2. The method according to claim 1, characterized in that: According to customer requirements for a target product, the steps of determining a plurality of critical control points for the target product in a statistical process control (SPC) system include: In the SPC system, a plurality of first key control characteristic keys are obtained from a manufacturing execution system MES, and a plurality of second key control characteristic keys are obtained from an equipment automation EAP system; In the SPC system, according to customer requirements for the target product, a plurality of critical control points for the target product are determined from the plurality of first critical control characteristic keys and / or the plurality of second critical control characteristic keys.

3. The method according to claim 1, characterized in that Also includes: Acquire an original data set, wherein the original data set includes detection parameter values ​​of multiple products; The original data set is classified according to product types to obtain a data set corresponding to each product type, and the detection parameter values ​​corresponding to a product sample of each product type are formed into a data subset.

4. The method according to claim 1, characterized in that: For each data subset, the steps of extracting the detection parameter value in each detection dimension from the data subset, and identifying the detection result of the data subset in different detection dimensions according to the judgment rules bound to each detection dimension include: Extract the detection parameter value under each detection dimension from the data subset; For each detection dimension, determine whether the detection parameter value under the detection dimension satisfies the determination rule bound to the detection dimension; If the judgment rules under all detection dimensions are satisfied, the detection result of the data subset is determined to be qualified; If at least one of the multiple detection parameter values ​​does not satisfy the judgment rule bound to the corresponding detection dimension, the detection result of the data subset is determined to be unqualified.

5. The method according to claim 4, characterized in that The horizontal axis of the preset chart indicates the number of the data subset, and the vertical axis of the preset chart indicates the comprehensive detection index of the data subset in all detection dimensions, wherein the data points of the data subset with unqualified detection results on the preset chart are presented in a first display mode, and the data points of the data subset with qualified detection results on the preset chart are presented in a second display mode.

6. The method according to claim 1, characterized in that The target product includes a key product, the preset detection dimension of the key product is pre-bound to a first judgment rule and a second judgment rule, the second qualified interval under the second judgment rule is included in the first qualified interval under the first judgment rule, and the first qualified interval does not overlap with the second qualified interval, Among them, for the key products, the step of data collection and processing also includes: For each data subset of the key product, extracting the detection parameter value under the preset detection dimension from the data subset; Determine whether the detection parameter value under the preset detection dimension satisfies the first judgment rule, and determine whether the detection parameter value under the preset detection dimension satisfies the second judgment rule; If both the first judgment rule and the second judgment rule are satisfied, determining that the detection result of the data subset is qualified; If at least one of the first judgment rule and the second judgment rule is not satisfied, it is determined that the detection result of the data subset is unqualified.

7. The method according to claim 5, characterized in that Also includes: Receiving a click operation on a data point on the preset chart; In response to the click operation, an information window is displayed, in which the detection parameter values ​​of the data subset corresponding to the data point in each detection dimension are displayed.

8. A SPC quality control multi-dimensional Chart detection device, characterized in that: The device comprises: A determination module, for determining a plurality of critical control points for a target product in a statistical process control (SPC) system according to customer requirements for the target product; A binding module is used to determine each key control point as a detection dimension in the SPC system and pre-bind a judgment rule to each detection dimension; An association module, used to associate multiple detection dimensions and the judgment rules bound to each detection dimension with a preset chart of an electronic data collection (EDC) system in the SPC system, wherein the preset chart is a received value chart corresponding to the target product; An import module, used for importing a plurality of data subsets of the target product into the SPC system; A processing module is used to perform data value collection processing on the target product in the EDC system, wherein the data value collection processing includes: for each data subset, extracting the detection parameter value under each detection dimension from the data subset, and identifying the detection result of the data subset under different detection dimensions according to the judgment rules bound to each detection dimension; The output module is used to display a preset chart output by the EDC system in the SPC system, wherein the preset chart displays the detection results of multiple data subsets of the target product under multiple detection dimensions.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate via the bus, and the processor executes the machine-readable instructions to perform the steps of any method as claimed in claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are executed.

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