Production monitoring system of electronic ignition powder head

Abstract

The invention relates to the technical field of ignition powder head production, in particular to an electronic ignition powder head production monitoring system which comprises an electronic ignition powder head production module, an electronic ignition powder head monitoring module, an electronic ignition powder head spot test module and an electronic ignition powder head opposite test module. The electronic ignition powder head production module, the electronic ignition powder head monitoring module and the electronic ignition powder head spot check module are used for conducting spot check on the electronic ignition powder heads of the same batch, the quality check sequence steps are rapidly customized, the quality problems possibly existing in the spot check electronic ignition powder heads are rapidly determined by customizing the quality check sequence steps, and the quality check efficiency of the electronic ignition powder heads is improved. Through the electronic ignition powder head detection module, when it is determined that the casually inspected electronic ignition powder head has a quality problem, a powder head production comparison group is rapidly generated, then the electronic ignition powder head which is not casually inspected and possibly has the quality problem is rapidly and accurately positioned, and the production quality inspection step is executed on the positioned electronic ignition powder head.

Description

Technical Field

[0001] The present invention relates to the technical field of the production of ignition cartridges, and more specifically, to a production monitoring system for electronic ignition cartridges. Background Art

[0002] In the production process of electronic ignition cartridges, the production process of electronic ignition cartridges includes multiple steps such as coating, drying, baking, and various quality inspections. Each step needs to be strictly controlled to ensure that the final production quality of the electronic ignition cartridges meets the requirements.

[0003] Generally, a can of liquid medicine can be used to prepare multiple electronic ignition cartridges. These electronic ignition cartridges are usually defined as electronic ignition cartridges of the same batch. For electronic ignition cartridges of the same batch, currently, sampling inspection is usually used for quality inspection. Although certain control measures have been taken in the existing production environment to ensure the stability and consistency of the coating, drying, and baking processes, it is difficult to ensure that each process experienced by the electronic ignition cartridges of the same batch is completely the same. For example, two electronic detonator chips are dried in two drying ovens respectively, and it is impossible to ensure that the temperature, humidity, and cleanliness in the two drying ovens are exactly the same. Even if they are in the same drying oven, the temperature, humidity, and cleanliness at different positions may not be exactly the same. This may lead to corresponding quality differences between the two electronic ignition cartridges produced. However, a comprehensive quality inspection of the electronic ignition cartridges of the same batch will significantly reduce the production efficiency of the electronic ignition cartridges.

[0004] Therefore, how to ensure the production quality inspection accuracy and efficiency of electronic ignition cartridges so as to avoid the situation of quality omission is an urgent problem to be solved currently. Summary of the Invention

[0005] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a production monitoring system for electronic ignition cartridges.

[0006] To achieve the above purpose, the present invention provides the following technical solutions:

[0007] A production monitoring system for electronic ignition cartridges, comprising an electronic ignition cartridge production module, an electronic ignition cartridge monitoring module, an electronic ignition cartridge sampling module, and an electronic ignition cartridge pair testing module;

[0008] The electronic ignition cartridge production module: produces a can of medicine based on ignition medicine raw materials and an adhesive solution, numbers the can of medicine, and performs coating, drying, and baking treatments on the can of medicine, and finally prepares i electronic ignition cartridges;

[0009] The electronic ignition cartridge monitoring module: real-time collects corresponding monitoring data during the coating process, drying process, and curing process of each electronic ignition cartridge, and generates a production log for each electronic ignition cartridge;

[0010] The electronic ignition cartridge sampling and testing module: determines all production quality inspection steps of the electronic ignition cartridge, obtains the core quality inspection values of each production quality inspection step, sorts all production quality inspection steps in descending order according to the core quality inspection values, randomly selects a part of the electronic ignition cartridges from all the electronic ignition cartridges with the same agent number according to the sampling ratio, performs the production quality inspection step ranked first on the selected part of the electronic ignition cartridges, obtains the quality inspection score of the electronic ignition cartridge for this production quality inspection step, compares the quality inspection score with the quality inspection standard score, and determines whether the obtained electronic ignition cartridge is a normal-quality cartridge or an abnormal-quality cartridge;

[0011] The electronic ignition cartridge pair testing module: when there are abnormal-quality cartridges, pairs multiple cartridge production comparison groups, determines whether the electronic ignition cartridges in the cartridge production comparison groups are cartridges to be inspected for quality, performs the production quality inspection step ranked first on each cartridge to be inspected for quality, and after completion, performs the production quality inspection step ranked next on all the abnormal-quality cartridges and the selected normal-quality cartridges.

[0012] Further, the production log includes the agent number, the coating process data set, the drying process data set, and the curing process data set.

[0013] Further, the coating process data set of the electronic ignition cartridge is obtained based on the following steps: during the process of coating the agent on the electronic detonator chip, the coating environment data, coating thickness data, coating speed data, and coating uniformity data at the position of the electronic detonator chip are collected in real time. After coating is completed, all the collected coating environment data, coating thickness data, coating speed data, and coating uniformity data are integrated into a coating process data set in the form of a data set.

[0014] Further, the drying process data set of the electronic ignition cartridge is obtained based on the following steps: during the process of drying the electronic detonator chip, the drying environment data and drying duration data at the position of the electronic detonator chip are collected in real time. After drying is completed, the collected drying duration data and all the drying environment data are integrated into a drying process data set in the form of a data set.

[0015] Further, the curing process data set of the electronic ignition cartridge is obtained based on the following steps: during the process of curing the electronic detonator chip, the curing environment data, curing hardness data, and curing uniformity data at the position of the electronic detonator chip are collected in real time. After curing is completed, all the collected curing environment data, curing hardness data, and curing uniformity data are integrated into a curing process data set in the form of a data set.

[0016] Further, the core quality inspection value of the production quality inspection step is obtained based on the following method: determine T before the current time msiFor all the electronic ignition heads produced within a certain time period, determine a production quality inspection step, and then obtain the quality inspection scores of each electronic ignition head for the production quality inspection step. Calculate the sum average of all the quality inspection scores to obtain the average quality inspection score Score(vgs). Calculate the absolute difference between each pair of all the quality inspection scores to obtain the quality inspection deviation score. Set the standard quality inspection deviation score. When the quality inspection deviation score is higher than the standard quality inspection deviation score, increase the quality inspection fluctuation quantity by one, and mark the quality inspection fluctuation quantity as Num(arp). Obtain the quality inspection core value Value(ys) of this production quality inspection step through Value(ys) = Num(arp) + 0.81 / Score(vgs).

[0017] Further, the quality inspection score of an electronic ignition head for the production quality inspection step is obtained based on the following method: Execute the production quality inspection step on the electronic ignition head. After completion, obtain the quality inspection data of this electronic ignition head, and synchronously obtain the quality inspection data analysis model of this production quality inspection step. Input the quality inspection data of the electronic ignition head into the quality inspection data analysis model, and the quality inspection data analysis model outputs to obtain the quality inspection score.

[0018] Further, pair the quality abnormal heads with each unextracted electronic ignition head with the same agent number to obtain multiple head production comparison groups.

[0019] Further, determine whether the electronic ignition head in the head production comparison group is a head to be inspected for quality: Obtain the production related value of each head production comparison group, and based on the comparison result between the production related value and the production related threshold, determine whether the electronic ignition head in the head production comparison group is a head to be inspected for quality.

[0020] Further, the production related value of the head production comparison group is obtained based on the following method: Obtain the coating process data set, drying process data set, and curing process data set of the quality abnormal head, and synchronously obtain the coating process data set, drying process data set, and curing process data set of the electronic ignition head. Obtain three process comparison models for the coating process, drying process, and curing process. Input the coating process data set of the quality abnormal head and the coating process data set of the electronic ignition head into the process comparison model of the coating process, and the output obtains the process related value of the coating process. Input the drying process data set of the quality abnormal head and the drying process data set of the electronic ignition head into the process comparison model of the drying process, and the output obtains the process related value of the drying process. Input the curing process data set of the quality abnormal head and the curing process data set of the electronic ignition head into the process comparison model of the curing process, and the output obtains the process related value of the curing process. Calculate the sum average of the process related value of the coating process, the process related value of the drying process, and the process related value of the curing process to obtain the production related value of the head production comparison group.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] Through the electronic ignition head production module, the electronic ignition head monitoring module, and the electronic ignition head sampling module, comprehensive data monitoring is carried out on the coating, drying, and baking processes of the electronic ignition head. After the production of the electronic ignition head is completed, the electronic ignition heads of the same batch are sampled, and the quality inspection sequence is quickly customized. By customizing the quality inspection sequence, it is ensured that the possible quality problems of the sampled electronic ignition heads can be quickly determined;

[0023] Through the electronic ignition head pair-measurement module, when it is determined that the sampled electronic ignition head has quality problems, a production comparison group of the ignition heads is quickly generated, and then the electronic ignition heads that have not been sampled and may have quality problems are quickly and accurately located, and the production quality inspection steps are executed on the located electronic ignition heads. When it is determined that the located electronic ignition head has quality problems, subsequent production quality inspections are performed on the electronic ignition heads with quality problems and the sampled electronic ignition heads, simultaneously ensuring the production quality inspection accuracy and efficiency of the electronic ignition heads. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a system module diagram of the production monitoring system for electronic ignition heads;

[0025] Figure 2 It is a quality inspection flow chart of the electronic ignition head for a production quality inspection step;

[0026] Figure 3 It is a determination flow chart of the ignition heads to be inspected for quality. DETAILED DESCRIPTION OF THE INVENTION

[0027] Refer to Figures 1 to 3 , the production monitoring system for electronic ignition heads includes an electronic ignition head production module, an electronic ignition head monitoring module, an electronic ignition head sampling module, and an electronic ignition head pair-measurement module.

[0028] Electronic ignition head production module: Add the ignition charge raw materials and the binder solution into a blender and stir (this application does not limit the composition and ratio of the ignition charge raw materials and the binder solution. The ignition charge raw materials are usually prepared by ball milling and sieving raw materials such as potassium chlorate, and the binder solution is usually prepared by boiling or mixing polyvinyl butyral and absolute ethanol). After stirring is completed, a can of agent is obtained. Number this can of agent (the number is n, where n is a positive integer. For example, if the blender finishes stirring a can of agent at 2:00 Beijing time, the number of this can of agent is 1; if the blender finishes stirring a can of agent at 3:00 Beijing time, the number of this can of agent is 2, that is, the numbers of each can of agent produced by the blender are all different). Pour this can of agent into the medicine trough, select multiple electronic detonator chips, coat this can of agent on i electronic detonator chips, then perform a drying process on each electronic detonator chip, and finally perform a curing process on each electronic detonator chip, and finally prepare i electronic ignition heads.

[0029] Electronic ignition head monitoring module: During the coating process, drying process, and curing process of each electronic ignition head, corresponding monitoring data is collected in real time to generate a production log for each electronic ignition head. The production log includes the agent number, coating process data set, drying process data set, and curing process data set (the existing electronic ignition head production environment can ensure that the production process of each electronic ignition head meets the indicators, but it cannot ensure that the environment and reflected indicators of each electronic ignition head during the coating process, drying process, and curing process are exactly the same. Because although certain control measures have been taken in the existing production environment to ensure the stability and consistency of the production process, these measures still have certain limitations. For example, electronic detonator chip a and electronic detonator chip b are dried in two drying ovens respectively, and it is impossible to ensure that the temperature, humidity, and cleanliness in the two drying ovens are exactly the same. Even in the same drying oven, the temperature, humidity, and cleanliness at different positions are not necessarily exactly the same).

[0030] The coating process data set, drying process data set, and curing process data set of the electronic ignition head are obtained based on the following steps: During the process of coating the agent on the electronic detonator chip, the coating environment data (including temperature, humidity, cleanliness, etc.), coating thickness data, coating speed data, and coating uniformity data at the position of the electronic detonator chip are collected in real time. After coating is completed, all the collected coating environment data, coating thickness data, coating speed data, and coating uniformity data are integrated into a coating process data set in the form of a data set.

[0031] During the drying process of the electronic detonator chip, the drying environment data (including temperature, humidity, cleanliness, etc.) and drying duration data of the position of the electronic detonator chip are collected in real time. After drying is completed, the collected drying duration data and all drying environment data are integrated into a drying process data set in the form of a data set.

[0032] During the curing process of the electronic detonator chip, the curing environment data (including temperature, humidity, cleanliness, etc.), curing hardness data, and curing uniformity data of the position of the electronic detonator chip are collected in real time. After curing is completed, all the collected curing environment data, curing hardness data, and curing uniformity data are integrated into a curing process data set in the form of a data set.

[0033] Electronic ignition head sampling and testing module: Determine all production quality inspection steps of the electronic ignition head, and obtain the quality inspection core values of each production quality inspection step (production quality inspection steps include spark intensity detection step, thermal stability detection step, mechanical strength detection step, insulation performance detection step, ignition performance detection step). Sort all production quality inspection steps in descending order according to the quality inspection core value. Randomly select some electronic ignition heads according to the sampling ratio (the sampling ratio is set by the system and can be adjusted according to system requirements) among all electronic ignition heads with the same pharmaceutical number (i.e., the same batch). Execute the production quality inspection step ranked first on the selected electronic ignition heads (the same pharmaceutical number means belonging to the same can of pharmaceutical, and there will be no difference in raw material ratio and composition. If the first-ranked step is the spark intensity detection step, then execute the spark intensity detection step on all electronic ignition heads), and then obtain the quality inspection score of the electronic ignition head for this production quality inspection step. Set the quality inspection standard score (the quality inspection standard score is a preset score used for comparison with the quality inspection score). When the quality inspection score is higher than the quality inspection standard score, mark this electronic ignition head as a normal quality head. When the quality inspection score is not higher than the quality inspection standard score, mark this electronic ignition head as an abnormal quality head.

[0034] The quality inspection core value of the production quality inspection step is obtained based on the following method: Determine T before the current time msiFor all the electronic ignition heads produced within a certain time period, determine a production quality inspection step, and then obtain the quality inspection scores of each electronic ignition head for the production quality inspection step. Calculate the sum average of all the quality inspection scores to obtain the average quality inspection score Score(vgs). Calculate the absolute difference between each pair of all the quality inspection scores to obtain the quality inspection deviation score. Set the quality inspection standard deviation score (the quality inspection standard deviation score is a preset score used to compare with the quality inspection deviation score). When the quality inspection deviation score is higher than the quality inspection standard deviation score, increase the quality inspection fluctuation quantity by one. When the quality inspection deviation score is not higher than the quality inspection standard deviation score, do not proceed to the next step. Mark the quality inspection fluctuation quantity as Num(arp). Obtain the quality inspection core value Value(ys) of this production quality inspection step through Value(ys) = Num(arp) + 0.81 / Score(vgs).

[0035] The quality inspection score of an electronic ignition head for the production quality inspection step is obtained based on the following method: Execute the production quality inspection step on the electronic ignition head. After completion, obtain the quality inspection data of this electronic ignition head. Synchronously obtain the quality inspection data analysis model of this production quality inspection step. Input the quality inspection data of the electronic ignition head into the quality inspection data analysis model, and the quality inspection data analysis model outputs to obtain the quality inspection score.

[0036] Each production quality inspection step corresponds to a quality inspection data analysis model, and each quality inspection data analysis model is constructed based on a deep learning model. The construction process of the quality inspection data analysis model for the spark intensity detection step is as follows: Construct a deep learning model, collect multiple quality inspection data for the spark intensity detection step. The quality inspection data is set for the training of the deep learning model. Use the quality inspection data as the training data of the deep learning model, and assign a quality inspection score to each training data. The value range of the quality inspection score is (50.0 - 100.0). The higher the quality inspection score, the more compliant the spark intensity of the electronic ignition head is with the standard. The lower the quality inspection score, the less compliant the spark intensity of the electronic ignition head is with the standard. Divide the training data into a 60% training set and a 40% validation set, and train the training set and the validation set. After completion, obtain the quality inspection data analysis model for the spark intensity detection step.

[0037] The construction process of the quality inspection data analysis model for the thermal stability detection step is as follows: Construct a deep learning model, collect multiple quality inspection data for the thermal stability detection step. The value range of the quality inspection score is (50.0 - 100.0). The higher the quality inspection score, the more compliant the thermal stability of the electronic ignition head is with the standard. The lower the quality inspection score, the less compliant the thermal stability of the electronic ignition head is with the standard. The remaining construction process is the same as that of the quality inspection data analysis model for the spark intensity detection step.

[0038] Through the electronic ignition head production module, the electronic ignition head monitoring module, and the electronic ignition head sampling and testing module, comprehensive data monitoring is carried out on the coating, drying, and baking processes of the electronic ignition head. After the production of the electronic ignition head is completed, sampling inspections are carried out on the electronic ignition heads of the same batch, and the quality inspection sequence is quickly customized. By customizing the quality inspection sequence, it is ensured that the possible quality problems of the sampled electronic ignition heads can be quickly determined.

[0039] Electronic ignition head pair - testing module: When a quality - abnormal head appears, pair the quality - abnormal head with each un - sampled electronic ignition head with the same agent number. Multiple head production comparison groups are obtained through pairing (each head production comparison group includes a quality - abnormal head and an electronic ignition head). Obtain the production - related values of each head production comparison group, and set a production - related threshold (the production - related threshold is a preset value used for comparison). When the production - related value of a head production comparison group is greater than the production - related threshold, mark the electronic ignition head in the head production comparison group as a head to be quality - inspected. When the production - related value of a head production comparison group is less than or equal to the production - related threshold, no further processing is done. Perform the top - ranked production quality inspection steps on each head to be quality - inspected, and then determine whether the head to be quality - inspected is a quality - normal head or a quality - abnormal head. After the determination, perform the next - ranked production quality inspection steps on all quality - abnormal heads and the sampled quality - normal heads.

[0040] The production - related value of the head production comparison group is obtained based on the following method: Obtain the coating process data set, drying process data set, and curing process data set of the quality - abnormal head, synchronously obtain the coating process data set, drying process data set, and curing process data set of the electronic ignition head, obtain three process comparison models for the coating process, drying process, and curing process. Input the coating process data set of the quality - abnormal head and the coating process data set of the electronic ignition head into the process comparison model of the coating process, and output the process - related value of the coating process. Input the drying process data set of the quality - abnormal head and the drying process data set of the electronic ignition head into the process comparison model of the drying process, and output the process - related value of the drying process. Input the curing process data set of the quality - abnormal head and the curing process data set of the electronic ignition head into the process comparison model of the curing process, and output the process - related value of the curing process. Perform a sum - of - means calculation on the process - related value of the coating process, the process - related value of the drying process, and the process - related value of the curing process to calculate the production - related value of the head production comparison group.

[0041] The coating process, drying process, and curing process each correspond to a process comparison model. Each process comparison model is constructed based on a deep learning model. The construction process of the process comparison model for the coating process is as follows: Construct a deep learning model, collect multiple sets of coating process datasets. Each set of coating process datasets contains two coating process datasets. Use the sets of coating process datasets as the training data for the deep learning model. Assign a process-related value to each training data. The value range of the process-related value is (0.1 - 10.0). The larger the process-related value, the more similar the two coating processes are. The smaller the process-related value, the less similar the two coating processes are. Divide the training data into a 75% training set and a 25% validation set, and train the training set and the validation set. After training is completed, the process comparison model for the coating process is obtained.

[0042] The construction process of the process comparison model for the drying process is as follows: Construct a deep learning model, collect multiple sets of drying process datasets. Each set of drying process datasets contains two drying process datasets. The value range of the quality inspection score is (50.0 - 100.0), and the value range of the process-related value is (8.0 - 10.0). The larger the process-related value, the more similar the two drying processes are. The smaller the process-related value, the less similar the two drying processes are. The process comparison models for the remaining coating processes are the same (the construction process of the process comparison model for the curing process is the same as above).

[0043] Through the electronic ignition primer pair test module, when it is determined that there are quality problems with the sampled electronic ignition primers, a primer production comparison group is quickly generated, and then the non-sampled and potentially defective electronic ignition primers are quickly and accurately located. And the production quality inspection steps are performed on the located electronic ignition primers. When it is determined that the located electronic ignition primers have quality problems, the subsequent production quality inspection is performed on the defective electronic ignition primers and the sampled electronic ignition primers, simultaneously ensuring the production quality inspection accuracy and efficiency of the electronic ignition primers.

[0044] The above formulas are all calculated by taking the numerical values after removing the dimensions. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0045] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wired or wireless (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that contains a collection of one or more available media. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0046] It should be understood that in various embodiments of the present application, the sequence numbers of the above processes do not imply the order of execution, and the order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0047] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0048] 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 foregoing method embodiments and will not be described herein again.

[0049] In several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. 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 displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the devices or units can be in electrical, mechanical, or other forms.

[0050] If the above functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs, and other various media that can store program codes.

[0051] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. Production monitoring system for electronic ignition heads, characterized in that, It includes an electronic ignition head production module, an electronic ignition head monitoring module, an electronic ignition head sampling inspection module, and an electronic ignition head paired inspection module; The electronic ignition head production module: Based on ignition charge raw materials and an adhesive solution, a can of agent is produced, numbered, coated, dried, and baked, and finally i electronic ignition heads are prepared; The electronic ignition head monitoring module: During the coating process, drying process, and curing process of each electronic ignition head, corresponding monitoring data is collected in real time to generate the production log of each electronic ignition head; The electronic ignition head sampling inspection module: Determine all production quality inspection steps of the electronic ignition head, obtain the quality inspection core values of each production quality inspection step, sort all production quality inspection steps in descending order according to the quality inspection core values, randomly select some electronic ignition heads from all electronic ignition heads with the same agent number according to the sampling ratio, perform the production quality inspection step ranked first on the selected electronic ignition heads, obtain the quality inspection score of the electronic ignition head for this production quality inspection step, compare the quality inspection score with the quality inspection standard score, and determine whether the obtained electronic ignition head is a normal quality head or an abnormal quality head; The electronic ignition head paired inspection module: When an abnormal quality head appears, multiple head production comparison groups are paired, determine whether the electronic ignition heads in the head production comparison groups are heads to be inspected for quality, perform the production quality inspection step ranked first on each head to be inspected for quality, determine whether the head to be inspected for quality is a normal quality head or an abnormal quality head. After that, perform the next production quality inspection step on all abnormal quality heads and the selected normal quality heads.

2. The production monitoring system of the electronic ignition cartridge according to claim 1, wherein The production log includes the agent number, coating process data set, drying process data set, and curing process data set.

3. The production monitoring system of the electronic ignition primer according to claim 1, characterized in that, The coating process data set of the electronic ignition head is obtained based on the following steps: During the process of coating the agent on the electronic detonator chip, the coating environment data, coating thickness data, coating speed data, and coating uniformity data at the position of the electronic detonator chip are collected in real time. After coating is completed, all the collected coating environment data, coating thickness data, coating speed data, and coating uniformity data are integrated into a coating process data set in the form of a data set.

4. The production monitoring system of the electronic ignition primer according to claim 1, wherein, The drying process data set of the electronic ignition head is obtained based on the following steps: During the process of drying the electronic detonator chip, the drying environment data and drying duration data at the position of the electronic detonator chip are collected in real time. After drying is completed, the collected drying duration data and all drying environment data are integrated into a drying process data set in the form of a data set.

5. The production monitoring system of the electronic ignition cartridge according to claim 1, characterized in that, The curing process data set of the electronic ignition head is obtained based on the following steps: During the process of curing the electronic detonator chip, the curing environment data, curing hardness data, and curing uniformity data at the position of the electronic detonator chip are collected in real time. After curing is completed, all the collected curing environment data, curing hardness data, and curing uniformity data are integrated into a curing process data set in the form of a data set.

6. The production monitoring system of the electronic ignition cartridge according to claim 1, characterized in that, The quality inspection core value of the production quality inspection steps is obtained based on the following method: Determine all the electronic ignition heads produced within the time period T before the current time, determine a production quality inspection step, and then obtain the quality inspection scores of each electronic ignition head for the production quality inspection step. Calculate the sum average of all the quality inspection scores to obtain the average quality inspection score Score(vgs). Calculate the pairwise absolute differences of all the quality inspection scores to obtain the quality inspection deviation scores. Set the quality inspection standard deviation score. When the quality inspection deviation score is higher than the quality inspection standard deviation score, increase the quality inspection fluctuation quantity by one, and mark the quality inspection fluctuation quantity as Num(arp). Obtain the quality inspection core value Value(ys) of this production quality inspection step through Value(ys)=Num(arp)+0.81 / Score(vgs). msi Determine all the electronic ignition heads produced within the time period T before the current time, determine a production quality inspection step, and then obtain the quality inspection scores of each electronic ignition head for the production quality inspection step. Calculate the sum average of all the quality inspection scores to obtain the average quality inspection score Score(vgs). Calculate the pairwise absolute differences of all the quality inspection scores to obtain the quality inspection deviation scores. Set the quality inspection standard deviation score. When the quality inspection deviation score is higher than the quality inspection standard deviation score, increase the quality inspection fluctuation quantity by one, and mark the quality inspection fluctuation quantity as Num(arp). Obtain the quality inspection core value Value(ys) of this production quality inspection step through Value(ys)=Num(arp)+0.81 / Score(vgs).

7. The production monitoring system of the electronic ignition cartridge according to claim 1, wherein, The quality inspection score for an electronic ignition primer in the production quality inspection steps is obtained based on the following method: perform the production quality inspection steps on the electronic ignition primer. After completion, obtain the quality inspection data of the electronic ignition primer, synchronously obtain the quality inspection data analysis model for this production quality inspection step, input the quality inspection data of the electronic ignition primer into the quality inspection data analysis model, and the quality inspection data analysis model outputs the quality inspection score.

8. The production monitoring system of the electronic ignition cartridge according to claim 1, characterized in that, Pair the defective quality primers with each unselected electronic ignition primer in the same primer formulation to obtain multiple primer production comparison groups.

9. The production monitoring system of the electronic ignition cartridge according to claim 1, characterized in that, Determine whether the electronic ignition primer in the primer production comparison group is a primer to be inspected for quality: obtain the production-related values of each primer production comparison group, and based on the comparison result between the production-related values and the production-related threshold, determine whether the electronic ignition primer in the primer production comparison group is a primer to be inspected for quality.

10. The production monitoring system of the electronic ignition cartridge according to claim 9, characterized in that, The production-related values of the primer production comparison group are obtained based on the following method: obtain the coating process dataset, drying process dataset, and curing process dataset of the defective quality primer, synchronously obtain the coating process dataset, drying process dataset, and curing process dataset of the electronic ignition primer, obtain three process comparison models for the coating process, drying process, and curing process, input the coating process dataset of the defective quality primer and the coating process dataset of the electronic ignition primer into the process comparison model of the coating process, and the output is the process-related value of the coating process. Input the drying process dataset of the defective quality primer and the drying process dataset of the electronic ignition primer into the process comparison model of the drying process, and the output is the process-related value of the drying process. Input the curing process dataset of the defective quality primer and the curing process dataset of the electronic ignition primer into the process comparison model of the curing process, and the output is the process-related value of the curing process. Perform a summation and averaging calculation on the process-related value of the coating process, the process-related value of the drying process, and the process-related value of the curing process to calculate the production-related value of the primer production comparison group.

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