Production system control method

Abstract

The application discloses a kind of production system control method, it is related to production system control technical field, wherein, the steps of the production system control method include: in production process, real-time acquisition monitoring data, and compare with preset standard data;When monitoring data and standard data exist deviation, obtain the production data corresponding to the monitoring data;According to the monitoring data and the production data, matching is carried out in the preset database, to obtain corresponding processing method and output.The application aims at presenting a kind of production system control method, to assist in reducing the probability of abnormal situation in production process.

Description

Technical Field

[0001] This invention relates to the field of production system control technology, and in particular to a production system control method. Background Technology

[0002] The SMT (Surface Mount Technology) segment of manufacturing involves processes such as solder paste printing, surface mount technology (SMT), and reflow soldering. During SMT, various factors can cause components to fail to mount successfully onto the PCB and be discarded; this anomaly is called component rejection. Component rejection leads to raw material waste and increased production costs. Equipment cycle time loss and manual maintenance further reduce production efficiency and can even have hidden negative impacts on product quality and brand image. Therefore, it is crucial to improve the rejection rate during the manufacturing stage.

[0003] In traditional scenarios for improving material rejection rates, manual intervention is often required after a rejection occurs. This approach is costly, has poor improvement results, and is subject to objective factors such as personnel capabilities and production plans, making it difficult to guarantee a continuous and stable improvement in the rejection rate. Summary of the Invention

[0004] The main objective of this invention is to propose a production system control method that aims to help reduce the probability of abnormal situations during the production process.

[0005] To achieve the above objectives, the present invention proposes a production system control method, wherein the steps of the production system control method include:

[0006] During the production process, real-time monitoring data is acquired and compared with preset standard data;

[0007] When there is a deviation between the monitoring data and the standard data, the production data corresponding to the monitoring data is obtained;

[0008] Based on the monitoring data and the production data, a matching process is performed from a preset database to obtain the corresponding processing method and output it.

[0009] In one embodiment, the step of matching the monitoring data and the production data from a preset database to obtain and output the corresponding processing method includes:

[0010] Based on the relevance of the data matching, multiple processing methods are obtained, sorted, and then output.

[0011] In one embodiment, the production system includes an alarm system, and after the step of matching the monitoring data and the production data from a preset database to obtain and output the corresponding processing method, the system further includes the step of:

[0012] Control the alarm system to trigger an alarm.

[0013] In one embodiment, the production system includes a visual dashboard, and the step of matching the monitoring data and the production data from a preset database to obtain and output the corresponding processing method includes:

[0014] The corresponding exception handling work orders are displayed through a visual dashboard.

[0015] In one embodiment, the production system includes a patching system, which includes a material suction nozzle and a pressure detection device and a vision detection device corresponding to the material suction nozzle. The monitoring data includes at least one of the following: the pressure value when the material suction nozzle picks up material, the position information of the material suction nozzle, the quantity information of the material adsorbed by the material suction nozzle, and the angle information of the material adsorbed by the material suction nozzle.

[0016] In one embodiment, the monitoring data includes the air pressure value when the material suction nozzle is sucking up material, the position information of the material suction nozzle, the quantity information of the material suction nozzle, and the angle information of the material suction nozzle.

[0017] The steps of acquiring monitoring data in real time during the production process and comparing it with preset standard data include:

[0018] The air pressure value when the material suction nozzle is sucking up the material, the position information of the material suction nozzle, the quantity information of the material suction nozzle, and the angle information of the material suction nozzle are compared with preset standard data one by one.

[0019] In one embodiment, the step of matching the monitoring data and the production data from a preset database to obtain and output the corresponding processing method includes:

[0020] Based on the monitoring data and the production data, a match is made with the preset database to obtain the corresponding reasons for material rejection and the corresponding handling methods, and these are output synchronously.

[0021] In one embodiment, the step of matching the monitoring data and the production data from a preset database to obtain the corresponding cause of material rejection and the handling method, and then outputting them synchronously, includes:

[0022] If the reason for the material rejection is equipment malfunction, then read the equipment's usage and maintenance information;

[0023] Determine whether the equipment's usage and maintenance information matches the preset standard usage and maintenance information;

[0024] If there is a mismatch, the corresponding device processing method will be output synchronously.

[0025] In one embodiment, before the step of acquiring monitoring data in real time during the production process and comparing it with preset standard data, the method further includes the following step:

[0026] Before production begins, production data is pre-stored, and based on the database data, the material rejection rate is estimated and output.

[0027] In one embodiment, the pre-stored production data includes work order information, which includes the required material quantity. The step of estimating and outputting the material rejection rate based on the pre-stored production data according to database data includes:

[0028] Based on the estimated rejection rate and the required material quantity, obtain and output the material preparation quantity.

[0029] In one embodiment, the pre-stored production data includes work order information, which includes multiple work orders. The step of estimating the rejection rate based on the pre-stored production data and outputting the result based on database data includes:

[0030] Estimate the rejection rate for multiple work orders with various production scheduling sequences, and output the work order scheduling sequence corresponding to the lowest rejection rate.

[0031] In one embodiment, after the step of matching the monitoring data and the production data from a preset database to obtain and output the corresponding processing method, the method further includes the step of:

[0032] After processing is completed, the actual processing method is integrated with the monitoring data and production data and recorded in the database.

[0033] The main technical solution of this invention is to add process monitoring and analysis during production to identify potential problems and provide matching solutions without interrupting production. This allows for early rectification of problems, improving the waste rate during the manufacturing stage and reducing labor costs. Specifically, in real-time, the control system acquires the necessary monitoring data during production and compares it with preset standard data. Deviations indicate potential production anomalies and a possible increase in waste rate. The control system then acquires the corresponding production data, using both as data features of the anomaly. This data is compared against a preset database to identify similar or identical anomalies and their corresponding solutions. This solution is then output. This process allows for anomaly analysis and solution development without interrupting production, reducing labor costs. Operators then analyze and adjust the solutions proposed by the control system accordingly, thus addressing the anomaly during production, improving waste rate, reducing material waste, and increasing production efficiency. Attached Figure Description

[0034] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0035] Figure 1 A schematic diagram of the analysis process for the production system control method provided by the present invention;

[0036] Figure 2 A flowchart illustrating the steps of a first embodiment of the production system control method provided by the present invention;

[0037] Figure 3 A flowchart illustrating the steps of a second embodiment of the production system control method provided by the present invention;

[0038] Figure 4 A flowchart illustrating the steps of a third embodiment of the production system control method provided by the present invention;

[0039] Figure 5 A flowchart illustrating the steps of the fourth embodiment of the production system control method provided by the present invention;

[0040] Figure 6A flowchart illustrating the steps of the fifth embodiment of the production system control method provided by the present invention;

[0041] Figure 7 A flowchart illustrating the steps of the sixth embodiment of the production system control method provided by the present invention;

[0042] Figure 8 A flowchart illustrating the steps of the seventh embodiment of the production system control method provided by the present invention;

[0043] Figure 9 A flowchart illustrating the steps of the eighth embodiment of the production system control method provided by the present invention;

[0044] Figure 10 A flowchart illustrating the steps of the ninth embodiment of the production system control method provided by the present invention;

[0045] Figure 11 A flowchart illustrating the steps of the tenth embodiment of the production system control method provided by the present invention;

[0046] Figure 12 This is a flowchart illustrating the steps of the eleventh embodiment of the production system control method provided by the present invention.

[0047] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0049] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative positional relationship and movement of the components in a specific posture. If the specific posture changes, the directional indications will also change accordingly.

[0050] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the use of "and / or" or "and / or" throughout the text includes three parallel solutions. For example, "A and / or B" includes solution A, solution B, or a solution where both A and B are satisfied simultaneously. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0051] The SMT (Surface Mount Technology) segment of manufacturing involves processes such as solder paste printing, surface mount technology (SMT), and reflow soldering. During SMT, various factors can cause components to fail to mount successfully onto the PCB and be discarded; this anomaly is called component rejection. Component rejection leads to raw material waste and increased production costs. Equipment cycle time loss and manual maintenance further reduce production efficiency and can even have hidden negative impacts on product quality and brand image. Therefore, it is crucial to improve the rejection rate during the manufacturing stage.

[0052] In traditional scenarios for improving material rejection rates, manual intervention is often required after a rejection occurs. This approach is costly, has poor improvement results, and is subject to objective factors such as personnel capabilities and production plans, making it difficult to guarantee a continuous and stable improvement in the rejection rate.

[0053] In view of this, the present invention proposes a production system control method. Figures 1 to 12 The following is a specific embodiment of the production system control method provided by the present invention, and will be described in conjunction with the specific accompanying drawings.

[0054] Please see Figures 1 to 12 The steps of the production system control method include:

[0055] S100: During the production process, real-time monitoring data is acquired and compared with preset standard data;

[0056] S200: When there is a deviation between the monitoring data and the standard data, obtain the production data corresponding to the monitoring data;

[0057] S300: Based on the monitoring data and the production data, match them from a preset database to obtain the corresponding processing method and output it.

[0058] The main technical solution of this invention is to add process monitoring and analysis during production to identify potential problems and provide matching solutions without interrupting production. This allows for early rectification of problems, improving the waste rate during the manufacturing stage and reducing labor costs. Specifically, in real-time, the control system acquires the necessary monitoring data during production and compares it with preset standard data. Deviations indicate potential production anomalies and a possible increase in waste rate. The control system then acquires the corresponding production data, using both as data features of the anomaly. This data is compared against a preset database to identify similar or identical anomalies and their corresponding solutions. This solution is then output. This process allows for anomaly analysis and solution development without interrupting production, reducing labor costs. Operators then analyze and adjust the solutions proposed by the control system accordingly, thus addressing the anomaly during production, improving waste rate, reducing material waste, and increasing production efficiency.

[0059] Specifically, step S300 includes:

[0060] S310: Based on the relevance of the data matching, obtain multiple processing methods, sort them, and output them.

[0061] It is understandable that the data in the database cannot cover all possible situations. Therefore, when the monitoring data and production data are used as data features of abnormal problems and matched with the preset database, it is more likely to match data with a certain degree of relevance, rather than matching data that is exactly the same. In the absence of a guarantee of exact match, the actual situation of the abnormal problem cannot be reliably confirmed. On this basis, the higher the degree of data relevance, the higher the probability of the abnormal problem being consistent. Therefore, as an auxiliary system for solving abnormal problems, this application proposes that after matching the monitoring data and production data with the preset database, abnormal problems with high relevance should be obtained according to the degree of data relevance, and corresponding processing methods should be obtained. At the same time, in order to improve the fault tolerance rate and provide more clues for judging abnormal problems so that operators can handle abnormalities more quickly, this application also proposes to obtain the processing methods of multiple abnormal problems with high relevance and output them simultaneously to improve the speed of abnormal problem identification, thereby improving the efficiency of abnormal problem resolution and avoiding the increase of material rejection rate.

[0062] In addition, the production system includes an alarm system, and after step S300, the system further includes the following step:

[0063] S320: Control the alarm system to give an alarm.

[0064] It can be understood that the control method proposed in this application mainly serves as an auxiliary system to assist the operator in judgment and operation, and will not and cannot actively adjust the production system to solve problems. Moreover, the control method proposed in this application continues to be carried out under the condition that the production system does not stop. When it judges that there are abnormal problems and obtains the corresponding processing methods, the production system will not stop operating either. In this state, it is impossible to ensure that the operator pays attention to the output abnormal problem processing methods. Therefore, in this application, in order to ensure that the operator can know the existence of abnormal problems in the first time, an alarm system is provided on the production system to alarm and remind the operator through the alarm system, so as to ensure that the operator can process problems in time.

[0065] In addition, the production system includes a visual display board, and the step S300 includes:

[0066] S330: Output an abnormal handling work order corresponding to the processing method through the visual display board.

[0067] The way for the control system to output the processing method can be various, which specifically depends on the equipment supporting the control system. That is, the control system may be carried on a computer outside the production system. At this time, the output of the processing method can be exhibited by the computer. In this embodiment, in order to ensure the prominence and recognizability of the output result, the visual display board is provided in the production system, and the visual display board exhibits the processing method. Together with the alarm of the above alarm system, it can enable the operator to know and identify the abnormal problem situation and the processing method of the reference case given by the control system in the first time, which is convenient for the operator to process quickly.

[0068] Specifically, the production system includes a patch panel system, which includes a material suction nozzle and corresponding air pressure detection and vision detection devices. The monitoring data includes at least one of the following: air pressure value when the material suction nozzle picks up material, position information of the material suction nozzle, quantity information of the material suction nozzle, and angle information of the material suction nozzle. The production system control method can be applied to various production systems. In this application, the production system is mainly the patch panel system. The patch panel system is characterized by high speed and the ability to continue normal production even after material rejection. Based on these characteristics, the production system control method proposed in this application can quickly identify abnormal monitoring data and match corresponding processing methods, which can undoubtedly greatly reduce the production capacity loss caused by downtime for troubleshooting anomalies and reduce the rejection rate of the patch panel system, thereby reducing waste costs. Meanwhile, based on the production system being the patch system, the monitoring data may specifically be at least one of the following: air pressure value when the material suction nozzle picks up material, position information of the material suction nozzle, quantity information of the material suction nozzle, and angle information of the material suction nozzle. These are all key data that affect the patch rejection rate.

[0069] Specifically, the monitoring data includes the air pressure value when the material suction nozzle sucks up material, the position information of the material suction nozzle, the quantity information of the material suction nozzle, and the angle information of the material suction nozzle.

[0070] Step S100 includes:

[0071] S110: Compare the air pressure value when the material suction nozzle is sucking up the material, the position information of the material suction nozzle, the quantity information of the material suction nozzle, and the angle information of the material suction nozzle with preset standard data one by one.

[0072] See the appendix for details. Figure 1Because the air pressure value when the material suction nozzle picks up material, the position information of the material suction nozzle, the quantity information of the material adsorbed by the material suction nozzle, and the angle information of the material adsorbed by the material suction nozzle all have a significant impact on the chip ejection rate, the monitoring data in this application includes all of the above data. For monitoring multiple data points, this application proposes a method of comparing each one individually with the standard data. The specific steps include: First, reading the air pressure value when the material suction nozzle picks up material. If the air pressure value is zero, it indicates that no material was successfully picked up, and an abnormality "pickup failure" is determined. If the first step does not determine an abnormality, i.e., the air pressure value is not zero, then the second step compares the air pressure value with the set standard data. If it meets the standard data, it is determined to be normal, and subsequent steps are performed; otherwise, it does not meet the standard data. If the standard data is not found, the nozzle may be damaged or dirty, which is judged as "nozzle abnormality". If the second step does not determine the abnormality, the nozzle position image is read and its position is determined by methods such as template matching in computer vision. If the position is correct, it is considered that it will not affect the subsequent patch placement operation, and the subsequent steps are processed normally. If a position offset or angle change is detected, it is judged as "nozzle position offset". If the third step does not determine the abnormality, the patch image information adsorbed by the nozzle is read and the number and angle of the patches are detected by methods such as template matching in computer vision. If more than one patch is found to be adsorbed, it may be due to the adhesion between adjacent materials on the patch strip, which can be judged as "material adhesion abnormality". If the material angle is offset or the shape is abnormal, it may be due to the problem of the incoming material itself, which can be judged as "material abnormality". Based on the above steps, when there is a discrepancy in the data comparison of each step, the process proceeds to step S200 to obtain the production data, and then proceeds to step S300 to obtain the corresponding abnormal problems and handling methods in the database by matching the abnormal monitoring data with the obtained production data. That is, specific abnormal situations such as "suction failure" and "suction nozzle abnormality" in the above steps are obtained, and the corresponding handling methods are obtained simultaneously.

[0073] Furthermore, if any abnormality occurs during the above comparison process, the corresponding production data is read, and a data packet is formed by combining the production data and the monitoring data to describe the information of the current abnormality. This data is then matched with the data in the database, as described above. Specifically, the production data in this step refers to data that can be pre-entered into the system and affects the production process. In this embodiment, it mainly includes temperature, humidity, the number of the material suction nozzle, and the number of the material feeder. This data does not need to be refreshed in real time; it can be entered into the system before production begins. When the monitoring data is abnormal, it is used to retrieve the data packet formed with the monitoring data to complete the production-related data when the abnormality occurs, thereby enabling more accurate location of the abnormality and providing a more accurate handling method.

[0074] Specifically, step S300 includes:

[0075] S340: Based on the monitoring data and the production data, match them from the preset database to obtain the corresponding reasons for material rejection and the handling methods, and output them synchronously.

[0076] In the above embodiments, after database matching is completed, the focus is mainly on the output of the processing method, which can meet the needs of problem solving, but cannot clearly obtain information about abnormal problems. Therefore, in this embodiment, while matching and obtaining the processing method from the database, the corresponding reason for material rejection is also obtained and output simultaneously, so that operators can obtain and refer to the content for judgment, which facilitates the handling of abnormal problems. Specifically, the production system control method proposed in this application is mainly an auxiliary method. When it outputs the reason for material rejection and the processing method, the operator should judge according to its content. On the one hand, it should judge whether the output content is accurate and consistent with the current production situation, and on the other hand, it should judge whether it is necessary to immediately stop the line for rectification and adjustment.

[0077] Specifically, step S340 includes:

[0078] S341: If the reason for the material rejection is equipment malfunction, then read the equipment's usage and maintenance information;

[0079] S342: Determine whether the equipment's usage and maintenance information matches the preset standard usage and maintenance information;

[0080] S343: If there is a mismatch, the corresponding device processing method will be output synchronously.

[0081] If the system analysis indicates that the cause of material ejection is equipment malfunction, meaning the ejection issue is highly related to the overall equipment and its internal components, then adjustments to the equipment and its internal components should be made as soon as possible to prevent further problems. For example, if the analysis identifies a strong correlation between the ejection issue and the material feeder or suction nozzle, further information such as the usage frequency and maintenance records of the feeder or nozzle should be retrieved to determine if the ejection is due to damage or lack of maintenance. Specifically, after obtaining the usage and maintenance information, it should be matched with preset standard usage and maintenance information to determine if there is damage or lack of maintenance, allowing operators to quickly replace and maintain the feeder or nozzle. Additionally, the ejection rate may also be affected by parameters such as equipment cycle time; adjustments should be made based on the suggested causes and solutions provided by the data analysis.

[0082] In addition, prior to step S100, the following step is also included:

[0083] S120: Before production begins, pre-store production data and, based on the database data, estimate and output the material rejection rate using the pre-stored production data.

[0084] Based on the above description of production data, which mainly consists of production information closely related to the material rejection rate, it is not necessary to acquire and monitor it in real time during the production process. For example, the temperature, humidity, material suction nozzle number, and material feeder number mentioned in the above embodiments generally do not change during the production process. Therefore, they are pre-stored before production and do not need to be acquired during the production process, thus simplifying the control and analysis process.

[0085] Specifically, based on the production information mentioned in the above embodiments, this embodiment further proposes that the pre-stored production data include at least one of work order information, material number, production line information, equipment information, and operator information. This constructs a more comprehensive data analysis system, avoiding situations where the system cannot accurately analyze abnormal data not included in the data analysis system, leading to prolonged troubleshooting time for operators and wasted effort. Furthermore, the more relevant information collected during the production process, the more reference data is available for matching in the database, resulting in higher accuracy of the analyzed data's relevance. This ensures that the obtained reasons for material rejection and corresponding handling methods are more closely aligned with the monitored anomalies, improving system assistance progress and efficiency, thereby enhancing the efficiency of operators in handling anomalies and better reducing rejection rates to meet usage requirements.

[0086] Based on the richness of the entered production data, the relevant impact of each data point can be referenced during data analysis. While the data analysis process involves a large volume of data, the results obtained are more accurate and meet usage requirements. Therefore, while monitoring anomalies during the production process, the database, by pre-storing the production data, allows for the acquisition of historical rejection rates. This enables the aggregation of historical rejection rates to obtain and output an estimated rejection rate for operators' reference. Alternatively, before production begins, the production data can be adjusted based on the estimated rejection rate to initially reduce the rejection rate.

[0087] Furthermore, the work order information includes the required quantity of materials, and step S120 includes:

[0088] S121: Based on the estimated rejection rate and the required material quantity, obtain and output the material preparation quantity.

[0089] Based on the estimated rejection rate described above, the production data can be adjusted using the estimated rejection rate before production to initially reduce the rejection rate, as described above. In addition, material preparation is actually required in the early stages of production. Due to the rejection rate, the prepared material quantity must be greater than the actual required material quantity. Generally, material preparation is based on historical data at a certain ratio. It is necessary to ensure that the prepared material quantity is greater than the actual material used, and that the two are close to equal. This minimizes material waste and eliminates the need to return excess materials after production, thus facilitating on-site production operations. Based on the estimated rejection rate, given the required material quantity, the estimated prepared material quantity can be calculated. The more accurate the estimated rejection rate, the more accurate the estimated prepared material quantity will be, achieving the aforementioned reduction in waste and elimination of return operations, further facilitating on-site production operations.

[0090] Furthermore, the work order information includes multiple work orders, and based on the database data, step S120 includes:

[0091] S122: Estimate the rejection rate for multiple work orders with various production scheduling sequences, and output the work order scheduling sequence corresponding to the lowest rejection rate.

[0092] It is understandable that the products produced by the production system and the corresponding orders will be diverse, and it is also understandable that different work orders exist on the same day. Therefore, the database can record the fluctuations in the rejection rate caused by switching between different work orders. In this way, when multiple production work orders are entered, the database can provide the estimated rejection rate for various production scheduling sequences of multiple production work orders, and output the work order scheduling sequence corresponding to the lowest rejection rate. This optimizes the scheduling steps of operators, provides effective data support, and can improve the rejection rate to meet usage requirements.

[0093] Furthermore, based on data analysis, this application can also process other factors that indirectly affect the material rejection rate. For example, abnormal temperature and humidity can affect the suction pressure value of the nozzle. If the temperature and humidity exceed the set threshold, the application will output a method to adjust the temperature and humidity of the work site and remove dust to reduce the impact of dust on adsorption. Another example is that if the rejection rate of the line under the operator's responsibility is high when the operator is on duty, it will consider whether the operator lacks skills and makes improper operation when loading, unloading, or adjusting the equipment, and personnel training will be required. Yet another example is that if abnormal incoming materials are detected, the application will contact the raw material supplier to discuss countermeasures.

[0094] In addition, after step S300, the following step is also included:

[0095] S350: After processing is completed, the actual processing method is integrated with the monitoring data and production data and recorded in the database.

[0096] The reference data in the database is actually historical production data. After each production process is completed, abnormal problems, monitoring data, production data, and corresponding handling methods are recorded to improve the database. Over a long period of use, the relevant production cases in the database become richer, making its data analysis reference items more abundant. The analysis results in more accurate material rejection rates, abnormal problems, and handling methods, providing operators with better auxiliary analysis functions, thereby reducing material rejection rates, improving production efficiency, and reducing costs.

[0097] The above description is merely an exemplary embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural transformations made using the contents of the present invention specification and drawings under the technical concept of the present invention, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. A production system control method, characterized in that, The steps of the production system control method include: During the production process, real-time monitoring data is acquired and compared with preset standard data; When there is a deviation between the monitoring data and the standard data, the production data corresponding to the monitoring data is obtained; Based on the monitoring data and the production data, a matching process is performed from a preset database to obtain the corresponding processing method and output it. After processing is completed, the actual processing method is integrated with the monitoring data and production data and recorded in the database; The step of matching the monitoring data and the production data from a preset database to obtain the corresponding processing method and output it includes: The monitoring data and the production data are used as data features of this anomaly. The data features are compared in a preset database to obtain and output the handling method for the anomaly recorded in the preset database that corresponds to this anomaly. Before the step of acquiring monitoring data in real time during the production process and comparing it with preset standard data, the method further includes the following step: Before production begins, production data is pre-stored, and based on the database data, the material rejection rate is estimated and output. The pre-stored production data includes work order information, which includes the required material quantity. The step of pre-stored production data before production begins, and estimating and outputting the rejection rate based on the pre-stored production data using database data, includes: Based on the estimated rejection rate and the required material quantity, obtain and output the material preparation quantity.

2. The production system control method as described in claim 1, characterized in that, The step of matching the monitoring data and the production data from a preset database to obtain the corresponding processing method and output it includes: Based on the relevance of the data matching, multiple processing methods are obtained, sorted, and then output.

3. The production system control method as described in claim 1, characterized in that, The production system includes an alarm system. After the step of matching the monitoring data and the production data from a preset database to obtain and output the corresponding processing method, the system further includes the step of: Control the alarm system to trigger an alarm.

4. The production system control method as described in claim 1, characterized in that, The production system includes a visual dashboard. The step of matching the monitoring data and the production data from a preset database to obtain the corresponding processing method and output it includes: The corresponding exception handling work orders are displayed through a visual dashboard.

5. The production system control method as described in claim 1, characterized in that, The production system includes a patch system, which includes a material suction nozzle and a pressure detection device and a vision detection device corresponding to the material suction nozzle. The monitoring data includes at least one of the following: the pressure value when the material suction nozzle picks up material, the position information of the material suction nozzle, the quantity information of the material adsorbed by the material suction nozzle, and the angle information of the material adsorbed by the material suction nozzle.

6. The production system control method as described in claim 5, characterized in that, The monitoring data includes the air pressure value when the material suction nozzle sucks up material, the position information of the material suction nozzle, the quantity information of the material suction nozzle, and the angle information of the material suction nozzle. The steps of acquiring monitoring data in real time during the production process and comparing it with preset standard data include: The air pressure value when the material suction nozzle is sucking up the material, the position information of the material suction nozzle, the quantity information of the material suction nozzle, and the angle information of the material suction nozzle are compared with preset standard data one by one.

7. The production system control method as described in claim 1, characterized in that, The step of matching the monitoring data and the production data from a preset database to obtain the corresponding processing method and output it includes: Based on the monitoring data and the production data, a match is made with the preset database to obtain the corresponding reasons for material rejection and the corresponding handling methods, and the results are output synchronously.

8. The production system control method as described in claim 7, characterized in that, The step of matching the monitoring data and production data from a preset database to obtain the corresponding reasons for material rejection and the handling methods, and then outputting them synchronously, includes: If the reason for the material rejection is a machine malfunction, then read the machine's usage and maintenance information; Determine whether the equipment's usage and maintenance information matches the preset standard usage and maintenance information; If there is a mismatch, the corresponding device processing method will be output synchronously.

9. The production system control method as described in claim 1, characterized in that, The pre-stored production data includes work order information, which includes multiple work orders. The step of pre-stored production data before production begins, and estimating and outputting the rejection rate based on the pre-stored production data according to database data, includes: Estimate the rejection rate for multiple work orders with various production scheduling sequences, and output the work order scheduling sequence corresponding to the lowest rejection rate.

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