A method and device for controlling key quality characteristics of a product manufacturing process

Abstract

The present application provides a method and device for controlling key quality characteristics of a product manufacturing process, wherein the method includes: determining each key quality characteristic of a product to be monitored; classifying each key quality characteristic to obtain the type of each key quality characteristic, which is: dimensional deviation type or defect type; when the type of the key quality characteristic is a defect type, obtaining the influencing factor values ​​of the key quality characteristics of multiple samples in the product manufacturing process; based on the influencing factor values ​​of the key quality characteristics of each sample, using a pre-established fitting function to determine the non-compliance rate of each sample; determining the residual value based on the non-compliance rate of each sample; and using an exponentially weighted moving average control chart to monitor the non-compliance rate and residual value of the key quality characteristics of multiple samples. The present application improves the reliability of the product by monitoring the key quality characteristics of the defect type of the product to be monitored during the manufacturing process.

Description

Technical Field

[0001] The present application relates to the technical field of product reliability control, and in particular to a method and device for controlling key quality characteristics of a product manufacturing process. Background Art

[0002] With the continuous innovation of new technologies, new processes and new materials, weapons and equipment have also developed rapidly. The characteristics of high precision, high complexity and high processing difficulty of weapons and equipment have become more and more prominent. Although the performance has been significantly improved, the stability of products in the manufacturing process has decreased as the products are highly sophisticated, the development technology is more difficult, the use environment is more complex and changeable, and the quality and reliability requirements are getting higher and higher. There is no effective solution to the above problems. Summary of the invention

[0003] In view of this, the present application provides a method and device for controlling key quality characteristics of a product manufacturing process to address the limitations of traditional manufacturing process reliability assurance methods, and to achieve monitoring and control of key quality characteristics of the manufacturing process with key quality characteristics as the core.

[0004] In a first aspect, an embodiment of the present application provides a method for controlling key quality characteristics of a product manufacturing process, comprising:

[0005] Determine the key quality characteristics of the product to be monitored;

[0006] Classifying each key quality characteristic to obtain a type of each key quality characteristic, wherein the type is: a dimension deviation type or a defect type, wherein the defect type has a value of 0 or 1;

[0007] When the type of the key quality characteristic is a defect type, obtaining the influencing factor values ​​of the key quality characteristics of multiple samples in the product manufacturing process; based on the influencing factor value of the key quality characteristic of each sample, determining the non-compliance rate of each sample using a pre-established fitting function;

[0008] Determine the residual value based on the non-compliance rate of each sample; use the exponentially weighted moving average control chart to monitor the non-compliance rate and residual value of key quality characteristics of multiple samples.

[0009] In one possible implementation, the key quality characteristics of the product to be monitored are determined, including:

[0010] Based on the design information and manufacturing data of the product to be monitored, multiple key quality characteristics of the product to be monitored are determined.

[0011] In a possible implementation, the method further includes: establishing a fitting function, specifically including:

[0012] Collecting sample data of the key quality characteristics of the product to be monitored, wherein the sample data includes the number of samples of the key quality characteristics of N experiments, the actual value of the non-compliance rate, and several influencing factor values;

[0013] Non-compliance rate of the key quality characteristics of the nth experiment and Impact Factor The relationship is:

[0014]

[0015] in, is the parameter to be estimated;

[0016] Set the nth experiment The observed quantities are: , where the value of the observation is 1 or 0, then the total number of standard for:

[0017]

[0018] The total number of successful experiments in N times is Joint Probability Distribution for:

[0019]

[0020] Taking the logarithm of both sides of the above equation and taking the partial derivative, we get:

[0021]

[0022] in, is the influencing factor vector of the nth experiment, is the impact factor matrix of N experiments;

[0023] make , and obtain the estimated values ​​of the parameters :

[0024]

[0025] in, for The diagonal matrix of :

[0026]

[0027]

[0028]

[0029]

[0030] in, is the true value of the non-compliance rate of the nth experiment; ; is the fitting function value of the nth experiment; is the correction value of the fitting function value of the nth experiment; is the correction value vector; is the parameter to be estimated No. Quantity;

[0031] The fitting function for:

[0032]

[0033] in, express Impact factors, It indicates the non-compliance rate; for The amount.

[0034] In a possible implementation, the method further includes:

[0035] When the type of the critical quality characteristic is the dimensional deviation type, the dimensional values ​​of the critical quality characteristics of multiple samples of the product to be monitored during the manufacturing process are obtained, and the dimensional values ​​of the critical quality characteristics of the multiple samples are monitored using an exponentially weighted moving average control chart.

[0036] In a possible implementation, an exponentially weighted moving average control chart is used to monitor the dimensional values ​​of key quality characteristics of multiple samples; including:

[0037] When the dimension value of the critical quality characteristic of the i-th sample is , then the i-th statistic for:

[0038]

[0039] in, is the offset coefficient;

[0040] when Between the lower limit of the control chart and upper limit When the size of the i-th sample is between is a normal value, otherwise, the size value of the i-th sample is an outlier;

[0041] Among them, the upper limit for:

[0042]

[0043] Lower limit for:

[0044]

[0045] in, Design values ​​for dimensions of critical quality characteristics, is the control limit parameter.

[0046] In a second aspect, an embodiment of the present application provides a key quality characteristic control device for a product manufacturing process, comprising:

[0047] Determination unit, used to determine the key quality characteristics of the product to be monitored;

[0048] A classification unit, used to classify each key quality characteristic to obtain a type of each key quality characteristic, wherein the type is: a dimensional deviation type or a defect type, wherein the defect type has a value of 0 or 1;

[0049] A processing unit, configured to obtain, when the type of the key quality characteristic is a defect type, influencing factor values ​​of the key quality characteristics of a plurality of samples in a product manufacturing process; and determine a non-compliance rate of each sample using a pre-established fitting function based on the influencing factor value of the key quality characteristic of each sample;

[0050] The monitoring unit is used to determine the residual value based on the non-conformity rate of each sample; and to monitor the non-conformity rate and residual value of the key quality characteristics of multiple samples using an exponentially weighted moving average control chart.

[0051] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method of the embodiment of the present application when executing the computer program.

[0052] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions implement the method of the embodiment of the present application when executed by a processor.

[0053] The present application improves product reliability by monitoring key quality characteristics of defects of the product to be monitored during the manufacturing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0055] Figure 1 A flowchart of a method for controlling key quality characteristics of a product manufacturing process provided in an embodiment of the present application;

[0056] Figure 2 A schematic diagram of EWMA control of circular runout of a shielding assembly provided in an embodiment of the present application;

[0057] Figure 3 A schematic diagram of EWMA control of the surface cleanliness of a shielding component provided in an embodiment of the present application;

[0058] Figure 4 A functional structure diagram of a key quality characteristic control device for a product manufacturing process provided in an embodiment of the present application;

[0059] Figure 5 A structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution 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 part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations.

[0061] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for which protection is sought, but merely represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0062] First, the design concept of the embodiments of the present application is briefly introduced.

[0063] Built-in Reliability (BIR) is a proactive preventive approach that focuses on carrying out quality and reliability activities as early as possible in the product life cycle, combining them with reliability work from the design stage and with various activities throughout the product life cycle. This approach can mainly solve two important problems. First, the current development process of weapons and equipment is out of touch with its quality and reliability, which is mainly manifested in the disconnection between the current product design process and the manufacturing process, maintenance, and support, the disconnection between the product design characteristics and quality characteristics, and the imbalance in the development of various quality characteristics. Second, the problem of insufficient product batch production capacity. The current research on the stability and consistency of the manufacturing process of weapons and equipment is slow, and technologies such as statistical process control, process capability analysis, and measurement system evaluation have not been promoted. The current main means of manufacturing process quality assurance are still based on post-detection methods. At the end of the manufacturing process, product quality is inspected, resulting in a large amount of resource waste, and also leading to low quality indicators, low production efficiency, frequent quality problems in the use process, and other problems, making it difficult to improve the quality and reliability level of products.

[0064] Therefore, focusing on built-in reliability, with key quality characteristics (KQC) as the core, the monitoring and control of KQC in the manufacturing process can transform the current passive quality assurance method centered on post-monitoring into active control of the manufacturing process, improve the batch production capacity of the manufacturing process, and ensure the quality and reliability of the product. With KQC as the core, the problem of disconnection between the design stage and the manufacturing process and the use process is solved, and the coordination problems of the design interface and process interface are solved, which greatly improves the product manufacturing efficiency.

[0065] To this end, this application provides a KQC control method for manufacturing processes with built-in reliability. This method realizes the identification of KQC in the design stage; and takes KQC as the core to construct a KQC monitoring and control method for the manufacturing process. According to the different KQC data types, an EWMA (Exponentially Weighted Moving-Average) control chart is constructed to achieve active control of the manufacturing process. This method is suitable for monitoring and controlling the characteristics of the manufacturing process, and provides a feasible technical framework for manufacturing enterprises to ensure the stability of the manufacturing process and product quality. The results show that this method can achieve reliability assurance of the manufacturing process and ensure the reliability of the product.

[0066] The basic assumptions of the method proposed in this application are as follows:

[0067] Assumption 1: The material flow between the chains of the manufacturing system satisfies the conservation law;

[0068] Assumption 2: Each mechanical device operates independently at the physical level of the entire manufacturing system;

[0069] Assumption 3: The corresponding key quality characteristics processed by each machine are considered independent of each other;

[0070] Assumption 4: There is an absolutely reliable checkpoint after each processing to verify the quality status of the output product;

[0071] Assumption 5: Product design information, process quality data, product failure information and other data are all available;

[0072] Assumption 6: Work-in-progress in a defective state is treated as scrapped;

[0073] Assumption 7: The manufacturing process does not consider the influence of human factors;

[0074] The advantages of this application are:

[0075] 1. This application can actively monitor the KQC of the product through control charts during the manufacturing process, achieve reliability assurance of the manufacturing process, and ensure the reliability of the product;

[0076] 2. In view of the problem that defective KQC cannot be detected by control chart, this application establishes a fitting function between the unqualified rate and each influencing factor to quantify the defective KQC, and monitors the unqualified rate and residual by control chart to achieve reliability control;

[0077] 3. The method of this application is scientific and reasonable, has good processability, and can be widely promoted in the industry.

[0078] After introducing the application scenarios and design concepts of the embodiments of the present application, the technical solutions provided by the embodiments of the present application are described below.

[0079] like Figure 1 As shown, the embodiment of the present application provides a method for controlling key quality characteristics of a product manufacturing process, including:

[0080] Step 101: Determine the key quality characteristics of the product to be monitored;

[0081] Step 102: Classify each key quality characteristic to obtain a type of each key quality characteristic, wherein the type is: a dimension deviation type or a defect type, wherein the defect type has a value of 0 or 1;

[0082] Step 103: When the type of the key quality characteristic is a defect type, the influencing factor values ​​of the key quality characteristics of multiple samples in the product manufacturing process are obtained; based on the influencing factor value of the key quality characteristic of each sample, the non-compliance rate of each sample is determined using a pre-established fitting function;

[0083] Step 104: Determine a residual value based on the non-compliance rate of each sample; and use an exponentially weighted moving average control chart to monitor the non-compliance rate and residual value of the key quality characteristics of multiple samples.

[0084] This embodiment addresses the problem that defective KQC cannot be detected using control charts. The present application establishes a fitting function between the failure rate and various influencing factors to quantify the defective KQC, and monitors the failure rate and residuals through control charts to achieve reliability control.

[0085] In some embodiments, determining each key quality characteristic of the product to be monitored includes:

[0086] Based on the design information and manufacturing data of the product to be monitored, multiple key quality characteristics of the product to be monitored are determined.

[0087] In some embodiments, the method further includes: establishing a fitting function, specifically including:

[0088] Collecting sample data of the key quality characteristics of the product to be monitored, wherein the sample data includes the number of samples of the key quality characteristics of N experiments, the actual value of the non-compliance rate, and several influencing factor values;

[0089] Non-compliance rate of the key quality characteristics of the nth experiment and Impact Factor The relationship is:

[0090]

[0091] in, is the parameter to be estimated;

[0092] Set the nth experiment The observed quantities are: , where the value of the observation is 1 or 0, then the total number of standard for:

[0093]

[0094] The total number of successful experiments in N times is Joint Probability Distribution for:

[0095]

[0096] Taking the logarithm of both sides of the above equation and taking the partial derivative, we get:

[0097]

[0098] in, is the influencing factor vector of the nth experiment, is the impact factor matrix of N experiments;

[0099] make , and obtain the estimated values ​​of the parameters :

[0100]

[0101] in, for The diagonal matrix of :

[0102]

[0103]

[0104]

[0105]

[0106] in, is the true value of the non-compliance rate of the nth experiment; ; is the fitting function value of the nth experiment; is the correction value of the fitting function value of the nth experiment; is the correction value vector; is the parameter to be estimated No. Quantity;

[0107] The fitting function for:

[0108]

[0109] in, express Impact factors, It indicates the non-compliance rate; for The amount.

[0110] For dimensional deviation KQC, monitor whether the deviation is abnormal during the manufacturing process and eliminate abnormal fluctuations in time, and monitor related KQC by building an EWMA control chart.

[0111] In some embodiments, the method further comprises:

[0112] When the type of the critical quality characteristic is the dimensional deviation type, the dimensional values ​​of the critical quality characteristics of multiple samples of the product to be monitored during the manufacturing process are obtained, and the dimensional values ​​of the critical quality characteristics of the multiple samples are monitored using an exponentially weighted moving average control chart.

[0113] In some embodiments, the dimensional values ​​of key quality characteristics of multiple samples are monitored using an exponentially weighted moving average control chart; including:

[0114] When the dimension value of the critical quality characteristic of the i-th sample is , then the i-th statistic for:

[0115]

[0116] in, is the offset coefficient;

[0117] when Between the lower limit of the control chart and upper limit When the size of the i-th sample is between is a normal value, otherwise, the size value of the i-th sample is an outlier;

[0118] Among them, the upper limit for:

[0119]

[0120] Lower limit for:

[0121]

[0122] in, Design values ​​for dimensions of critical quality characteristics, is the control limit parameter.

[0123] The specific implementation process of this application is described below in conjunction with a specific application scenario.

[0124] Taking the shielding component as an example, the manufacturing process monitoring is studied for built-in reliability. The shielding component is a high-precision assembly product and a key component. Its quality and reliability will be directly related to the safety and operational stability of the reactor. The shielding component production line has been put into operation. However, problems such as low pass rate of single rods and components and low batch production reliability have gradually been exposed during the manufacturing process, resulting in a large waste of resources. Therefore, the reliability of the shielding component manufacturing process is guaranteed by the method of this application.

[0125] KQC identification was performed by collecting data related to the manufacturing process of the shielding assembly, and four KQCs were obtained: pin spiral diameter, component circular runout, lower end plug welding current, and welding surface cleanliness.

[0126] For deviation data, an EWMA control chart can be directly constructed for monitoring. Taking the component circular runout as an example, the factory uses a circular runout detector based on a pressure sensor to detect the component circular runout, collects the component circular runout, and uses the EWMA control chart to monitor the welding surface cleanliness. The control chart is as follows: Figure 2 As shown in the figure, it can be seen that the circular runout of the shielding component is under control and the batch production reliability is high.

[0127] For defective KQC, it is not possible to monitor directly through the EWMA control chart, so a fitting function needs to be constructed. Take the welding surface cleanliness as an example for analysis. The shielding component welding surface cleanliness requirement is Sa3. Failure to meet the standard may cause defects such as pores, slag inclusions, and bulging. By analyzing these characteristics, the results are binary, with only two results: "meeting the standard" and "not meeting the standard". The welding surface cleanliness is closely related to the welding temperature. Taking the welding temperature as the explanatory variable, its fitting function is constructed:

[0128]

[0129] Collect product KQC controlled data (historical data). The collected welding surface cleanliness data is shown in Table 1:

[0130] Table 1 Controlled data of welding surface cleanliness

[0131]

[0132] According to the data in Table 1, the two parameters of the fitting function are estimated, and the fitting function obtained is:

[0133]

[0134] Collect KQC data of shielding component manufacturing process. In the actual manufacturing process, the welding temperature is controlled at about 1180K, and the surface cleanliness data of 10 batches of products are collected continuously, as shown in Table 2:

[0135] Table 2 Welding surface cleanliness data during manufacturing process

[0136]

[0137] For the monitoring and control of defective KQC, the following formula is used to calculate the value of each group of data: value:

[0138]

[0139] in Indicates the soldering temperature.

[0140] The residuals are calculated as shown in Table 3:

[0141] Table 3 Residual data of welding surface cleanliness during manufacturing process

[0142]

[0143] The EWMA control chart is used to monitor the surface cleanliness of the shielding components, such as Figure 3 As shown. It can be seen that the surface cleanliness of the parts is under control.

[0144] Therefore, the method of this embodiment is used to monitor and control the manufacturing process of the shielding component, and the manufacturing process monitoring can achieve product built-in reliability.

[0145] Based on the above embodiments, the present application provides a key quality characteristic control device for a product manufacturing process. Figure 4 As shown, the key quality characteristic control device 200 of the product manufacturing process provided by the embodiment of the present application at least includes:

[0146] A determination unit 201, used to determine each key quality characteristic of the product to be monitored;

[0147] A classification unit 202 is used to classify each key quality characteristic to obtain a type of each key quality characteristic, wherein the type is: a dimension deviation type or a defect type, wherein the defect type has a value of 0 or 1;

[0148] The processing unit 203 is used to obtain the influencing factor values ​​of the key quality characteristics of multiple samples in the product manufacturing process when the type of the key quality characteristic is a defect type; based on the influencing factor value of the key quality characteristic of each sample, determine the non-compliance rate of each sample using a pre-established fitting function;

[0149] The monitoring unit 204 is used to determine the residual value based on the non-compliance rate of each sample; and use an exponentially weighted moving average control chart to monitor the non-compliance rate and residual value of the key quality characteristics of multiple samples.

[0150] It should be noted that the principle of solving the technical problem by the device 200 for controlling key quality characteristics of the product manufacturing process provided in the embodiment of the present application is similar to the method provided in the embodiment of the present application. Therefore, the implementation of the device 200 for controlling key quality characteristics of the product manufacturing process provided in the embodiment of the present application can refer to the implementation of the method provided in the embodiment of the present application, and the repeated parts will not be repeated.

[0151] like Figure 5As shown, the electronic device 300 provided in the embodiment of the present application includes at least: a processor 301, a memory 302, and a computer program stored in the memory 302 and executable on the processor 301. When the processor 301 executes the computer program, the key quality characteristic control method of the product manufacturing process provided in the embodiment of the present application is implemented.

[0152] The electronic device 300 provided in the embodiment of the present application may further include a bus 303 connecting different components (including the processor 301 and the memory 302). The bus 303 represents one or more of several types of bus structures, including a memory bus, a peripheral bus, a local bus, and the like.

[0153] The memory 302 may include a readable medium in the form of a volatile memory, such as a random access memory (RAM) 3021 and / or a cache memory 3022 , and may further include a read-only memory (ROM) 3023 .

[0154] The memory 302 may also include a program tool 3024 having a set (at least one) of program modules 3025, the program modules 3025 including but not limited to: an operating subsystem, one or more application programs, other program modules, and program data, each of which or some combination may include the implementation of a network environment.

[0155] The electronic device 300 may also communicate with one or more external devices 304 (e.g., keyboards, remote controls, etc.), and may also communicate with one or more devices that enable a user to interact with the electronic device 300 (e.g., mobile phones, computers, etc.), and / or communicate with any device that enables the electronic device 300 to communicate with one or more other electronic devices 300 (e.g., routers, modems, etc.). Such communication may be performed through an input / output (I / O) interface 305. Furthermore, the electronic device 300 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 306. Figure 5 As shown, the network adapter 306 communicates with other modules of the electronic device 300 via the bus 303. It should be understood that although Figure 5Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 300, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, disk arrays (Redundant Arrays of Independent Disks, RAID) subsystems, tape drives, and data backup storage subsystems.

[0156] It should be noted that Figure 5 The electronic device 300 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0157] The embodiment of the present application also provides a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed by a processor, the key quality characteristic control method of the product manufacturing process provided by the embodiment of the present application is implemented.

[0158] In addition, although the operations of the method of the present application are described in a specific order in the drawings, this does not require or imply that the operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0159] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0160] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for controlling key quality characteristics of a product manufacturing process, characterized in that: include: Determine the key quality characteristics of the product to be monitored; Classifying each key quality characteristic to obtain a type of each key quality characteristic, wherein the type is: a dimension deviation type or a defect type, wherein the defect type has a value of 0 or 1; When the type of the key quality characteristic is a defect type, obtaining the influencing factor values ​​of the key quality characteristics of multiple samples in the product manufacturing process; based on the influencing factor value of the key quality characteristic of each sample, determining the non-compliance rate of each sample using a pre-established fitting function; Determine the residual value based on the non-conformance rate of each sample; use the exponentially weighted moving average control chart to monitor the non-conformance rate and residual value of the key quality characteristics of multiple samples; The method further comprises: When the type of the critical quality characteristic is the dimensional deviation type, the dimensional values ​​of the critical quality characteristics of multiple samples of the product to be monitored during the manufacturing process are obtained, and the dimensional values ​​of the critical quality characteristics of the multiple samples are monitored using an exponentially weighted moving average control chart.

2. The method for controlling key quality characteristics of a product manufacturing process according to claim 1, characterized in that: Identify the key quality characteristics of the product to be monitored, including: Based on the design information and manufacturing data of the product to be monitored, multiple key quality characteristics of the product to be monitored are determined.

3. The method for controlling key quality characteristics of a product manufacturing process according to claim 1, characterized in that: The method further comprises: establishing a fitting function, specifically comprising: Collecting sample data of the key quality characteristics of the product to be monitored, the sample data including the number of samples of the key quality characteristics of N experiments, the actual value of the non-compliance rate and several influencing factor values; Non-compliance rate of the key quality characteristics of the nth experiment and Impact Factor The relationship is: in, is the parameter to be estimated; Set the nth experiment The observed quantities are: , where the value of the observation is 1 or 0, then the total number of standard for: The total number of successful experiments in N times is Joint Probability Distribution for: Taking the logarithm of both sides of the above equation and taking the partial derivative, we get: in, is the influencing factor vector of the nth experiment, is the impact factor matrix of N experiments; make , and obtain the estimated values ​​of the parameters : in, for The diagonal matrix of : in, is the true value of the non-compliance rate of the nth experiment; ; is the fitting function value of the nth experiment; is the correction value of the fitting function value of the nth experiment; is the correction value vector; is the parameter to be estimated No. Quantity; The fitting function for: in, express Impact factors, It indicates the non-compliance rate; for The amount.

4. The method for controlling key quality characteristics of a product manufacturing process according to claim 1, characterized in that: Use exponentially weighted moving average control charts to monitor the dimensional values ​​of key quality characteristics of multiple samples; including: When the dimension value of the critical quality characteristic of the i-th sample is , then the i-th statistic for: in, is the offset coefficient; when Between the lower limit of the control chart and upper limit When the size of the i-th sample is between is a normal value, otherwise, the size value of the i-th sample is an outlier; Among them, the upper limit for: Lower limit for: in, Design values ​​for dimensions of critical quality characteristics, is the control limit parameter.

5. A critical quality characteristic control device for a product manufacturing process, characterized in that: include: Determination unit, used to determine the key quality characteristics of the product to be monitored; A classification unit, used to classify each key quality characteristic to obtain a type of each key quality characteristic, wherein the type is: a dimensional deviation type or a defect type, wherein the defect type has a value of 0 or 1; A processing unit, configured to obtain, when the type of the key quality characteristic is a defect type, influencing factor values ​​of the key quality characteristics of a plurality of samples in a product manufacturing process; and determine a non-compliance rate of each sample using a pre-established fitting function based on the influencing factor value of the key quality characteristic of each sample; A first monitoring unit is used to determine a residual value based on the non-conformity rate of each sample; and to monitor the non-conformity rate and residual value of the key quality characteristics of the multiple samples using an exponentially weighted moving average control chart; The device also includes: a second monitoring unit, which is used to obtain the dimensional values ​​of the key quality characteristics of multiple samples of the product to be monitored during the manufacturing process when the type of the key quality characteristic is the dimensional deviation type, and monitor the dimensional values ​​of the key quality characteristics of the multiple samples using an exponentially weighted moving average control chart.

6. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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