Iot-based certificate card production monitoring system and method

Abstract

The application relates to the technical field of Internet of Things, and discloses a certificate and card production monitoring system and method based on Internet of Things. The method comprises the following steps: obtaining a certificate and card production task from production plan data, periodically collecting monitoring data of each sensor to form production data; judging whether an abnormality occurs in the certificate and card production process based on the production data; if quality detection data shows that the currently produced certificate and card has a quality problem, judging whether the quality problem is caused by the quality of the certificate and card itself or by production equipment failure; if the first judgment result shows that the quality problem is caused by production equipment failure, judging in combination with equipment state data; obtaining a corresponding production process when the quality problem occurs; and adjusting the production equipment of the certificate and card production task in the production plan data based on the cause of the quality problem. The application can improve the production efficiency of certificate and card production.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Things, and in particular to a certificate card production monitoring system and method based on Internet of Things. BACKGROUND

[0002] In the production process of certificate cards, quality problems or equipment failures are prone to occur due to the involvement of multiple processes such as printing, lamination, and coding. Traditional monitoring methods rely on manual inspection or single-device alarm systems, making it difficult to achieve comprehensive monitoring.

[0003] A similar prior art is Chinese patent application CN119442069A, which provides a production quality detection and early warning method and device for saw chain gears, relating to the technical field of quality detection and early warning. The method includes: analyzing the loss parameters of the saw chain gears, positioning the loss value, and constructing a detection parameter hierarchical structure; performing core detection parameter combination extraction; taking the positioning parameters as the detection target and the comparison parameters as the collaborative following quantity, fitting into the quality detection module, and performing quality detection on the production monitoring data; performing early warning level analysis according to the parameter deviation quantity and the hierarchical relationship between the detection target and the detection parameter hierarchical structure; matching the early warning path to generate early warning feedback information. However, this application can quickly and accurately locate specific quality problems, but the judgment of quality problems is too single, and other problems cannot be accurately judged as quality problems.

[0004] Another similar prior art is Chinese patent application CN119294787A, which discloses an online production monitoring method for feed quality based on big data analysis. This invention can comprehensively grasp the quality status from the production process to the final product by comprehensively analyzing the processing procedure quality and the processing finished product quality of the target feed production process. Through strict monitoring of the processing procedure, problems in the production process can be discovered and corrected in time, avoiding the amplification of these problems in subsequent links, thereby ensuring the stability of the processing finished product quality. However, this invention can obtain quality evaluation, but the judgment of quality problems is still too single, and other problems cannot be accurately judged as quality problems. Moreover, it does not consider the problem of low production efficiency caused by quality problems. SUMMARY

[0005] To solve the above technical problems, the present application provides a certificate card production monitoring system and method based on Internet of Things, which can improve the production efficiency of certificate card production.

[0006] In a first aspect, the present application provides a certificate card production monitoring method based on Internet of Things, which deploys multiple different types of sensors on the certificate card production line and is implemented by performing the following steps:

[0007] Step S1: obtaining a card production task from production plan data, periodically collecting monitoring data of each sensor in the process of executing the card production task, and pre-processing and fusing the monitoring data to form production data;

[0008] Step S2: judging whether an abnormality occurs in the card production process based on the production data, if the quality detection data shows that the currently produced card has a quality problem, judging whether the quality problem is caused by the quality of the card itself or by a production equipment failure, and taking the judgment result as a first judgment result;

[0009] Step S3: if the first judgment result shows that the quality problem is caused by a production equipment failure, combining the equipment state data to judge, if the equipment state data shows that the production equipment fails, combining the production plan data to make a second judgment, judging whether the displayed production equipment failure is caused by a failure of the production equipment itself or by a shutdown in the production plan, if the equipment state data does not show that the production equipment fails, attributing the quality problem to a quality problem caused by the quality of the card itself;

[0010] Step S4: obtaining a corresponding production process when the quality problem occurs, defining the corresponding production process as an abnormal process, and adjusting the production equipment of the card production task in the production plan data based on the abnormal process and the cause of the quality problem.

[0011] In combination with the first aspect, in a first implementation manner of the first aspect of the present application, the production plan data in step S1 includes:

[0012] The production process of the card is divided into a first production process, a second production process, a third production process and a fourth production process, wherein each production process can be completed by one or more production equipment, and different production equipment takes different time to produce a card;

[0013] From the first production process to the fourth production process of the card production process, a production equipment combination with the shortest execution time is obtained, target production equipment is specified for the first production process, the second production process, the third production process and the fourth production process based on the shortest production equipment combination, and the card production task is completed by the target production equipment.

[0014] In combination with the first aspect, in a second implementation manner of the first aspect of the present application, the production plan data further includes:

[0015] If the target production device is used to execute a first identification card production task, and there is a second identification card production task, other production devices than the target production device are designated for the first production procedure, the second production procedure, the third production procedure and the fourth production procedure of the second identification card production task;

[0016] Based on the total number of identification cards in the identification card production task and the time consumed by the production device to make one identification card, the start time of the identification card production task executed by each production device is calculated.

[0017] If there is only one production device corresponding to the second production procedure or the third production procedure or all production devices in the production procedure have been assigned identification card production tasks, the state of one or more production devices corresponding to the third production procedure or the fourth production procedure is set as shutdown waiting.

[0018] In a third implementation manner of the first aspect, the step S2 further includes:

[0019] The production time of the identification card with the quality problem is obtained, and a plurality of identification cards continuously produced before and after the identification card with the quality problem is obtained based on the production time. If the plurality of identification cards all have the quality problem, the first judgment result is defined as that the quality problem is caused by production device failure, otherwise, the first judgment result is defined as that the quality problem is caused by the identification card itself.

[0020] In a fourth implementation manner of the first aspect, the step S3 further includes:

[0021] The production plan data is obtained, and if the production plan data shows that the production device is shutdown waiting, the second judgment result is defined as that the quality problem is caused by the identification card itself, otherwise, the second judgment result is defined as the same as the first judgment result.

[0022] In a fifth implementation manner of the first aspect, the step S4 further includes:

[0023] When the quality problem is caused by production device failure, the abnormal production device executing the identification card production task in the abnormal procedure is obtained, and other normal production devices in the abnormal procedure are obtained. A plurality of idle production devices closest to the current time are obtained from the production plan of the other production devices as backup production devices, and the identification card production task being executed by the abnormal production device is assigned to the backup production devices.

[0024] In a sixth implementation manner of the first aspect, the step S4 further includes:

[0025] When the quality problem is caused by the quality of the ID card itself, the production of the ID card is suspended, the production equipment that is assigned with the ID card production task after the abnormal process and is used to produce the ID card is obtained as a first backup production equipment, the state of the first backup production equipment is set as idle, and the production equipment of other ID card production tasks in the production plan data is readjusted.

[0026] With reference to the first aspect, in a seventh implementation manner of the first aspect of the application, assigning the ID card production task being executed by the abnormal production equipment to the backup production equipment comprises:

[0027] If the number of the backup production equipment is greater than or equal to 2, the time consumed by each of the backup production equipment for producing one ID card is obtained, the time consumed by the second backup production equipment for producing one ID card is set as t1, the time consumed by the third backup production equipment for producing one ID card is set as t2, the time when the second backup production equipment completes the ID card production task being executed is set as t3, the time when the third backup production equipment completes the ID card production task being executed is set as t4, the completion time S1 of the ID card production task executed by the second backup production equipment and the completion time S2 of the ID card production task executed by the third backup production equipment are calculated, wherein t1 is greater than t2, and t3 is less than t4.

[0028] When S1 is greater than S2, the third backup production equipment is reassigned to execute the ID card production task in the production plan data, when S1 is less than S2, the second backup production equipment is reassigned to execute the ID card production task in the production plan data, and when S1 is equal to S2, the third backup production equipment is reassigned to execute the ID card production task in the production plan data.

[0029] With reference to the first aspect, in an eighth implementation manner of the first aspect of the application, the completion time S1 of the ID card production task executed by the second backup production equipment and the completion time S2 of the ID card production task executed by the third backup production equipment are calculated, comprising S1=t1*num+t3 and S2=t2*num+t4, wherein num represents the total number of ID cards in one ID card production task.

[0030] Secondly, the application provides an ID card production monitoring system based on Internet of Things, a plurality of different types of sensors are deployed on an ID card production line, and the system comprises the following modules.

[0031] A data acquisition unit is configured to acquire an ID card production task from production plan data, periodically acquire monitoring data of each sensor in the process of executing the ID card production task, and pre-process and fuse the monitoring data to form production data.

[0032] The first judging unit is used for judging whether an abnormality occurs in the production process of the ID card, and if the quality detection data shows that the ID card currently produced has a quality problem, judging whether the quality problem is caused by the quality of the ID card itself or by a production equipment failure, and taking the judging result as a first judging result;

[0033] The second judging unit is used for, if the first judging result shows that the quality problem is caused by the production equipment failure, judging in combination with the equipment state data, if the equipment state data shows that the production equipment failure, judging again in combination with the production plan data, judging whether the displayed production equipment failure is caused by a failure of the production equipment for producing the ID card itself or by a shutdown in the production plan, if the equipment state data does not show the production equipment failure, attributing the quality problem to a quality problem caused by the quality of the ID card itself.

[0034] The plan adjusting unit is used for obtaining a corresponding production procedure when the quality problem occurs, defining the corresponding production procedure as an abnormal procedure, and adjusting the production equipment of the ID card production task in the production plan data based on the abnormal procedure and the cause of the quality problem.

[0035] Compared with the prior art, the application has at least the following advantages:

[0036] In the technical scheme provided in the application, the ID card production task is obtained from the production plan data, the monitoring data of each sensor is periodically collected in the process of executing the ID card production task, the abnormality occurring in the production process of the ID card can be found in time, the monitoring data is preprocessed and fused, the noise in the monitoring data is eliminated, the quality of the monitoring data is improved, and the production data is formed. Based on the production data, whether an abnormality occurs in the production process of the ID card is judged, if the quality detection data shows that the ID card currently produced has a quality problem, whether the quality problem is caused by the quality of the ID card itself or by a production equipment failure is judged, and the judging result is taken as a first judging result. The root cause of the quality problem can be accurately located, the time for finding the quality problem is shortened, and the overall production efficiency is improved.

[0037] If the first judgment result shows that the quality problem is caused by the production equipment failure, the equipment state data is combined to judge, if the equipment state data shows the production equipment failure, the second judgment is combined with the production plan data, the second judgment shows that the production equipment failure is caused by the failure of the production equipment itself or the shutdown in the production plan, if the equipment state data does not show the production equipment failure, the quality problem is attributed to the quality problem caused by the card itself. Through comprehensive analysis of multiple data, the quality problem of the card can be accurately judged to be caused by what reason, when the judgment result is not accurate enough, the second judgment is performed, the judgment time is saved, the detection accuracy is improved, and the production efficiency of the card is improved. Finally, the corresponding production process when the quality problem occurs is obtained, the corresponding production process is defined as an abnormal process, and the production equipment of the card production task in the production plan data is adjusted based on the abnormal process and the cause of the quality problem, and the production efficiency of the card production is improved. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor based on these drawings.

[0039] Figure 1 An embodiment of the card production monitoring method based on the Internet of Things in the embodiment of the present application is shown.

[0040] Figure 2 A card production line deployment schematic diagram in the card production monitoring system based on the Internet of Things in the embodiment of the present application is shown.

[0041] Figure 3 A schematic diagram of one of the card production tasks allocating production equipment in the embodiment of the present application is shown.

[0042] Figure 4 An embodiment of the card production monitoring system based on the Internet of Things in the embodiment of the present application is shown. DETAILED DESCRIPTION

[0043] The embodiments of the present application provide a certificate production monitoring system and method based on Internet of Things. The terms "first", "second", "third", "fourth" and the like (if any) in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not have to be used to describe a particular order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "comprise" or "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device comprising a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0044] Embodiment one:

[0045] For the sake of understanding, the specific process of the embodiments of the present application is described below, referring to Figure 1 An embodiment of the certificate production monitoring method based on Internet of Things in the embodiments of the present application comprises, Figure 2 As shown in the certificate production line, a plurality of different types of sensors are deployed, and the implementation is realized by performing the following steps:

[0046] Step S1: Obtain the certificate production task from the production plan data, periodically collect the monitoring data of each sensor in the process of executing the certificate production task, and pre-process and fuse the monitoring data to form production data.

[0047] Specifically, by periodically collecting the monitoring data of the sensor in real time, the abnormal situation of the certificate in the production process can be found in time, such as quality problem and equipment failure. The production plan of the certificate is adjusted based on the abnormal situation, and the production efficiency of the certificate is improved. The pre-processing of the data of the sensor means cleaning and format conversion of the monitoring data, eliminating the noise in the monitoring data and improving the quality of the monitoring data. The fusion of the monitoring data is to integrate the monitoring data from different sensors into time series production data, so as to optimize the execution order of each production equipment when the abnormality occurs in the certificate production process. The sensor at least includes a quality detection sensor and an equipment state sensor, and the production data at least includes quality detection data, equipment state data and production plan data.

[0048] Step S2: Based on the production data, it is judged whether an abnormality occurs in the certificate production process. If the quality detection data shows that the currently manufactured certificate has a quality problem, it is judged whether the quality problem is caused by the quality of the certificate itself or by the failure of the production equipment, and the judgment result is taken as the first judgment result.

[0049] Specifically, in the production process of the ID card, production data is captured by multiple different types of sensors deployed on the ID card production line. When analyzing the production data, it is found that the test data of the magnetic stripe read-write of an ID card is abnormal, indicating that the magnetic stripe information of the ID card cannot be correctly read and written, and that an abnormality has occurred in the production process of the ID card. The analysis unit begins to analyze the cause of the ID card quality problem, and determines whether the quality problem is caused by the quality of the ID card itself or by a production equipment failure. The specific determination method will be described in detail below. Through the above steps, the root cause of the quality problem can be accurately located, the time for finding the quality problem is shortened, and the overall production efficiency is improved. The first determination result may not be accurate enough, but the determination speed is very fast, which can significantly improve the efficiency.

[0050] Step S3: If the first determination result shows that the quality problem is caused by a production equipment failure, then the equipment state data is combined for determination. If the equipment state data shows a production equipment failure, then the production plan data is combined for secondary determination to determine whether the displayed production equipment failure is caused by a failure of the production equipment itself or by a stop in the production plan. If the equipment state data does not show a production equipment failure, then the quality problem is attributed to a quality problem caused by the quality of the ID card itself.

[0051] Specifically, when the quality problem is caused by a production equipment failure, further determination is needed in combination with the equipment state data, that is, the second determination. If the equipment state data shows a production equipment failure, the second determination result is obvious, and the quality problem is caused by a production equipment failure and is unrelated to the quality of the ID card itself. However, there is another case where the equipment state data shows a production equipment failure, which is not a production equipment failure, such as a normal production equipment stop or waiting for execution of the next task, in which case the production equipment is not working, and the production equipment failure is displayed. At this time, the quality problem is no longer caused by a production equipment failure, but by the quality of the ID card itself. Therefore, a third determination is needed. If the equipment state data does not show a production equipment failure, then it is obvious that the quality problem is caused by the quality of the ID card itself. Through comprehensive analysis of multiple data, the cause of the quality problem of the ID card can be accurately determined. When the determination result is not accurate enough, further determination is performed, which saves determination time and improves detection accuracy, thereby improving the production efficiency of the ID card.

[0052] Step S4: The production process corresponding to the occurrence of the quality problem is obtained, and the corresponding production process is defined as an abnormal process. Based on the abnormal process and the cause of the quality problem, the production equipment of the ID card production task in the production plan data is adjusted.

[0053] Specifically, when the produced certificate card has quality problems, it is determined that the quality problem occurs in which production process, and the corresponding production process is marked as an abnormal process. The abnormal process may correspond to one or more production devices. If the cause of the quality problem is a production device failure, the certificate card production task in the production plan data is adjusted to the production device. The specific adjustment method will be described in detail below. If the cause of the quality problem is the quality of the certificate card itself, how to handle it will be described in detail below.

[0054] In the embodiment of the application, the cooperation between the above steps can improve the production efficiency of the certificate card production.

[0055] Further, the production plan data in step S1 includes dividing the production process of the certificate card into a first production process, a second production process, a third production process, and a fourth production process, wherein each production process can be completed by one or more production devices, and different production devices have different production times for the certificate card.

[0056] From the first production process to the fourth production process of the certificate card production process, the production device combination with the shortest execution time is obtained, and the shortest production device combination is specified as the target production device for the first production process, the second production process, the third production process, and the fourth production process, respectively, as shown in Figure 3 , and the target production device completes the certificate card production task.

[0057] Specifically, since there are many certificate card production tasks, in order to improve production efficiency, a production plan needs to be made in advance, and production plan data needs to be generated. When making the plan, the certificate card production process is divided and optimized, and the production devices used in each production process are reasonably allocated, which can improve device utilization and production efficiency. Referring to Figure 2 , the certificate card production process is divided into four production processes: the first production process: card printing (text, pattern, two-dimensional code), the second production process: card encoding (magnetic stripe encoding, chip writing), the third production process: card packaging (laminating, laminating), and the fourth production process: card personalization (photo printing, signature, etc.). The production time of the production device in making the certificate card is different, which means that different device combinations will make the time required to complete the entire certificate card production task different. In order to maximize production efficiency, the shortest device combination method needs to be found from the available production devices of each production process. For example, Figure 2In the specific example, the first production procedure has two production devices A1 and A2, which respectively need 2 minutes and 3 minutes to complete; the second production procedure has one production device B1, which needs 4 minutes; the third production procedure and the fourth production procedure also have different devices and their corresponding completion times. By comparing all possible combinations of production devices in the prior art optimization algorithm, the combination of production devices with the shortest time from the first production procedure to the fourth production procedure is found. When arranging the second card production task and the third card production task, according to the idle production devices in each production procedure, the production devices in each production procedure are combined by the above method, and if there is no idle production device, the completion time of the production devices used by other production tasks is calculated and then the production devices are allocated to the new production task. Through intelligent production device combination optimization, the overall production cycle of the card can be greatly shortened, and the production efficiency can be improved.

[0058] Further, the production plan data further includes, if the target production device is used to execute the first card production task, when there is a second card production task, designating other production devices other than the target production device for the first production procedure, the second production procedure, the third production procedure and the fourth production procedure of the second card production task; further based on the total number of cards in the card production task and the time consumed by the production device to make a card, calculate the start time of each production device to execute the card production task; if the production device corresponding to the second production procedure or the third production procedure is only one or all production devices in the production procedure have been allocated card production tasks, set the state of one or more production devices corresponding to the third production procedure or the fourth production procedure to be stopped and waiting.

[0059] Specifically, when refining the production plan data, the efficient scheduling of the production equipment in a multitasking environment also needs to be considered to further improve the production efficiency. When the target production equipment is used to execute the first ID card production task, if there is a second ID card production task, the production equipment is reassigned for the second ID card production task, ensuring that the target production equipment of the first ID card production task is not occupied to guarantee the production efficiency. That is, the first production process, the second production process, the third production process and the fourth production process of the second ID card production task will be assigned to other production equipment except the target production equipment occupied by the first ID card production task. In addition, the method also calculates the time when each production equipment starts to execute any ID card production task based on the total number of ID cards to be produced in each task in the ID card production task and the time consumed by the production equipment to produce one ID card, reducing the waiting time of the production equipment. When the production equipment corresponding to the second production process or the third production process is only one, or all production equipment in the production process has been allocated an ID card production task, the state of the production equipment corresponding to the third production process or the fourth production process will be set to stop and wait. Avoid overloading. For example, if the second production process has only one production equipment B1, and the production equipment B1 has been allocated to the first ID card production task, the production equipment H of the third production process needs to be set to the stop and wait state until the production equipment B1 completes the first ID card production task and releases it, protecting the damage of the idle use of the production equipment. The above method can achieve optimal utilization of the production equipment in the face of a multitasking environment, effectively improving the production efficiency of the ID card.

[0060] Further, step S2 further comprises judging whether the quality problem is caused by the quality of the ID card itself or by the failure of the production equipment, obtaining the production time of the ID card with the quality problem, obtaining a plurality of ID cards produced continuously before and after the ID card with the quality problem based on the production time, and defining the first judgment result as the quality problem being caused by the failure of the production equipment if the plurality of ID cards all have the quality problem, otherwise defining the first judgment result as the quality problem being caused by the quality of the ID card itself.

[0061] Specifically, when detecting that a certain card has a quality problem, first, the manufacturing time of the problematic card is located to a specific production batch and time point. Next, based on the production time of the problematic card, a plurality of cards continuously produced before and after the time point are further retrieved to determine whether a plurality of cards have quality problems in the same production batch or in a similar production time period. If a plurality of cards produced in the time period all have the same or similar quality problems, it is possible that the quality problem is caused by a production equipment failure, and the first determination result is defined as the quality problem being caused by the production equipment failure, which can be caused by equipment aging, improper maintenance, or operation error. If only one or a few cards in the same production batch or time period have problems, it is obvious that the quality problem is caused by the quality problem of the card itself, which can be caused by problems in raw materials, design, or production process. Through time positioning and batch analysis, it is quickly determined whether the problem is in the card itself or in the production equipment, thereby providing a reference for subsequent improvement and repair work, and improving production efficiency.

[0062] Further, step S3 further includes determining whether the displayed production equipment failure is caused by a failure of the production equipment itself or by a planned shutdown of the production, obtaining production plan data, and if the production plan data shows that the production equipment is in a shutdown state, defining the second determination result as the quality problem being caused by the quality of the card itself, otherwise, defining the second determination result as the same as the first determination result.

[0063] Specifically, to distinguish whether the quality problem is caused by a failure of the production equipment itself or by a planned shutdown of the production, further determination is needed. For example, if the production plan data shows that the production equipment should be in a shutdown state during the time period when the quality problem occurs, and the planned shutdown or maintenance or replacement of consumables is performed, then the equipment failure is determined as a non-productive shutdown, and the second determination result is defined as the quality problem being caused by the quality of the card itself. If the production plan data does not show that the production equipment is in a shutdown state when the failure occurs, it is possible that the production equipment is truly causing the failure, and the second determination result is consistent with the first determination result, that is, the failure is caused by a problem of the production equipment itself. Through the above determination, the accuracy of abnormal problem determination is improved, the problem source can be quickly located, and a targeted solution can be taken. At the same time, by referring to the production plan data, misjudgment caused by planned shutdown is avoided, and production efficiency is ensured.

[0064] Further, step S4 further comprises, when the quality problem is caused by the production equipment failure, obtaining the abnormal production equipment performing the certificate production task in the abnormal process, obtaining other normal production equipment in the abnormal process, obtaining a plurality of idle production equipment closest to the current time from the production plan of the other normal production equipment as backup production equipment, and assigning the certificate production task being performed by the abnormal production equipment to the backup production equipment.

[0065] Specifically, when the production equipment in the same production process fails, to ensure that the certificate production task being performed can be completed as soon as possible, the certificate production task being performed can be assigned to other normal production equipment in the same production process to continue completing the task and ensure production efficiency. If all other production equipment is performing a task, a plurality of other production equipment waiting for the closest time to the current time can be selected. By reassigning the certificate production task on the abnormal production equipment to the backup production equipment, it is ensured that the production task can be completed as soon as possible, and the production efficiency is improved.

[0066] Further, step S4 further comprises, when the quality problem is caused by the certificate itself, suspending the production of the certificate, obtaining and assigning the production equipment in which the certificate production task is assigned after the abnormal process as the first backup production equipment, setting the state of the first backup production equipment as idle, and readjusting the production equipment of other certificate production tasks in the production plan data.

[0067] Specifically, when the quality problem is caused by the certificate itself, rather than the production equipment failure, the production of the certificate task is suspended to avoid more unqualified certificates flowing into the subsequent production process. Then, the production equipment in which the certificate task is originally assigned in the subsequent production process is obtained and marked as the first backup production equipment, and the state is adjusted to idle to release the resources of the first production equipment for accepting new certificate production tasks at any time, maximizing the production efficiency.

[0068] Further, assigning the certificate production task being performed by the abnormal production equipment to the backup production equipment comprises, if the backup production equipment is greater than or equal to 2, obtaining the time consumed by each backup production equipment to make a certificate, setting the time consumed by the second backup production equipment to execute a certificate as t1, setting the time consumed by the third backup production equipment to execute a certificate as t2, setting the time at which the second backup production equipment completes the certificate production task being performed as t3, setting the time at which the third backup production equipment completes the certificate production task being performed as t4, calculating the completion time S1 of the certificate production task being performed by the second backup production equipment and the completion time S2 of the certificate production task being performed by the third backup production equipment, wherein t1 is greater than t2, and t3 is less than t4.

[0069] When S1 is greater than S2, the third standby production device is reassigned to execute the ID card production task in the production plan data; when S1 is less than S2, the second standby production device is reassigned to execute the ID card production task in the production plan data; and when S1 is equal to S2, the third standby production device is reassigned to execute the ID card production task in the production plan data.

[0070] Specifically, by comprehensively considering the production time consumption of the standby production device and the completion of the current ID card production task, it can be more accurately determined which standby production device is more suitable for executing the current ID card production task. This method not only improves the execution efficiency of the production task and reduces the waiting time, but also to a certain extent, realizes the load balancing of the production device and prolongs the service life of the production device.

[0071] Further, the completion time S1 of executing the ID card production task by the second standby production device and the completion time S2 of executing the ID card production task by the third standby production device are calculated, including S1=t1*num+t3 and S2=t2*num+t4, wherein num represents the total number of ID cards in one ID card production task.

[0072] Specifically, the time consumption of the production device for executing one ID card includes not only the production time consumption, but also the intermittent time consumption between the production of each card. Accurate time consumption calculation can provide a reference basis for calculating the start time of the production device.

[0073] Further, when the third standby production device is reassigned to execute the ID card production task, it includes that if the completion time S2 of the third standby production device executing the ID card production task is later than the start time of the next ID card production task of the ID card production task, no more than one-third of the total number of ID card production tasks in the ID card production task is allocated to the second standby production device, wherein the start time of the next ID card production task is obtained from the production plan data.

[0074] While improving the execution efficiency of the production task, the load balancing of the production device can also be realized to a certain extent.

[0075] Embodiment two:

[0076] The above describes the ID card production monitoring method based on the Internet of Things in the embodiments of the present application. The ID card production monitoring system based on the Internet of Things in the embodiments of the present application is described below, which is described with reference to Figure 4 An embodiment of the ID card production monitoring system based on the Internet of Things in the embodiments of the present application is realized by deploying multiple sensors of different types on the ID card production line and the following modules in cooperation:

[0077] The data acquisition unit is used for obtaining a card production task from production plan data, periodically acquiring monitoring data of each sensor in the process of executing the card production task, and pre-processing and fusing the monitoring data to form production data.

[0078] The first judging unit is used for judging whether an abnormality occurs in the card production process. If the quality detection data shows that the currently produced card has a quality problem, the first judging unit judges whether the quality problem is caused by a quality problem of the card itself or a quality problem caused by a production equipment failure, and takes the judging result as a first judging result.

[0079] The second judging unit is used for judging, if the first judging result shows that the quality problem is caused by a production equipment failure, in combination with the equipment state data. If the equipment state data shows that the production equipment failure, the second judging unit judges, in combination with the production plan data, whether the displayed production equipment failure is caused by a failure of the production equipment for producing the card itself or a stop in the production plan. If the equipment state data does not show the production equipment failure, the second judging unit attributes the quality problem to a quality problem caused by the quality of the card itself.

[0080] The plan adjusting unit is used for obtaining a corresponding production process when the quality problem occurs, defining the corresponding production process as an abnormal process, and adjusting a production equipment of the card production task in the production plan data based on the abnormal process and a cause of the quality problem.

[0081] Through the cooperation between the above-mentioned various modules, the production efficiency of the card production can be improved.

[0082] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-mentioned system, system and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be described herein.

[0083] The integrated unit, if realized in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of 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 the embodiments of the present application. The foregoing storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0084] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A card production monitoring method based on the Internet of Things, which deploys multiple different types of sensors on the card production line, is characterized by: The method comprises: Step S1: Obtain a card production task from production plan data. During the execution of the card production task, periodically collect monitoring data from various sensors, and pre-process and fuse the monitoring data to form production data. Step S2: Based on the production data, determining whether an abnormality occurs during the card production process; if the quality inspection data indicates that the currently produced card has a quality problem, determining whether the quality problem is caused by the quality of the card itself or a quality problem caused by a production equipment failure, and using the determination result as a first determination result; The step S2 further includes: obtaining the production time of the card with the quality problem, obtaining multiple cards produced continuously before and after the card with the quality problem based on the production time, and if the multiple cards all have the quality problem, defining the first judgment result as being caused by a production equipment failure; otherwise, defining the first judgment result as being caused by the quality of the card itself; Step S3: If the first judgment result shows that the quality problem is caused by a production equipment failure, a judgment is made in combination with the equipment status data. If the equipment status data shows that the production equipment has failed, a second judgment is made in combination with the production plan data to determine whether the displayed production equipment failure is caused by a failure of the production equipment producing the card itself or by a shutdown within the production plan. If the equipment status data does not show that the production equipment has failed, the quality problem is attributed to a quality problem caused by the quality of the card itself. Step S4: Obtain the production process corresponding to when the quality problem occurs, and define the corresponding production process as an abnormal process, and adjust the production equipment of the card production task in the production plan data based on the abnormal process and the cause of the quality problem.

2. The method according to claim 1, characterized in that The production plan data in step S1 includes: The card production process is divided into a first production process, a second production process, a third production process, and a fourth production process, wherein each production process can be completed by one or more production equipment, and different production equipments take different time to produce the card; From the first production process to the fourth production process in the card production process, obtain the production equipment combination with the shortest execution time, and based on the shortest production equipment combination, specify target production equipment for the first production process, the second production process, the third production process and the fourth production process respectively, and the card production task is completed by the target production equipment.

3. The method according to claim 2, characterized in that The production plan data also includes: If the target production equipment is used to perform the first card production task, when there is a second card production task, specify other production equipment other than the target production equipment for the first production process, the second production process, the third production process, and the fourth production process of the second card production task; The method further calculates the start time of each of the production devices for executing the card production task based on the total number of cards in the card production task and the time taken by the production device to produce one card; If there is only one production device corresponding to the second production process or the third production process or all production devices in the production process have been assigned card production tasks, the status of one or more production devices corresponding to the third production process or the fourth production process is set to stop waiting.

4. The method according to claim 1, wherein The step S3 further comprises: The production plan data is obtained. If the production plan data shows that the production equipment is stopped and waiting, the second judgment result is defined as the quality problem being caused by the quality of the card itself. Otherwise, the second judgment result is defined to be the same as the first judgment result.

5. The method according to claim 1, wherein The step S4 further includes: When the quality problem is caused by a failure of production equipment, the abnormal production equipment that performs the card production task in the abnormal process is obtained, and other normal production equipment in the abnormal process is also obtained. A plurality of idle production equipment closest to the current time is obtained from the production plans of the other production equipment as backup production equipment, and the card production task being performed by the abnormal production equipment is assigned to the backup production equipment.

6. The method according to claim 1, characterized in that The step S4 further includes: When the quality problem is caused by the quality of the card itself, the production of the card is suspended, the production equipment allocated to the card production task in the production process after the abnormal process is obtained and used as the first backup production equipment, the status of the first backup production equipment is set to idle, and the production equipment of other card production tasks in the production plan data is readjusted.

7. The method according to claim 5, characterized in that Allocating the card production task currently being executed by the abnormal production device to the standby production device includes: If there are two or more backup production devices, obtain the time it takes for each backup production device to produce a card. Set the time it takes for the second backup production device to produce a card to be t1, and the time it takes for the third backup production device to produce a card to be t2. Set the time it takes for the second backup production device to complete the card production task it is currently executing to be t3, and the time it takes for the third backup production device to complete the card production task it is currently executing to be t4. Calculate the completion time S1 of the card production task performed by the second backup production device and the completion time S2 of the card production task performed by the third backup production device, where t1 is greater than t2 and t3 is less than t4. When S1 is greater than S2, the third backup production equipment is reallocated in the production plan data to execute the card production task; when S1 is less than S2, the second backup production equipment is reallocated in the production plan data to execute the card production task; when S1 is equal to S2, the third backup production equipment is reallocated in the production plan data to execute the card production task.

8. The method according to claim 7, characterized in that Calculating the completion time S1 of executing the card production task using the second backup production equipment and the completion time S2 of executing the card production task using the third backup production equipment, including: , , where num represents the total number of cards in the card production task.

9. An Internet of Things-based card production monitoring system, used to implement the method according to any one of claims 1 to 8, deploying multiple sensors of different types on the card production line, characterized in that: The system includes the following modules: A data acquisition unit is used to obtain card production tasks from production plan data, periodically collect monitoring data from various sensors during the execution of the card production tasks, and pre-process and fuse the monitoring data to form production data; The first judgment unit is configured to judge whether an abnormality occurs during the card production process; if the quality inspection data shows that the currently produced card has a quality problem, determine whether the quality problem is caused by the quality of the card itself or by a failure of the production equipment, and use the judgment result as a first judgment result; obtain the production time of the card with the quality problem, and based on the production time, obtain multiple cards produced continuously before and after the card with the quality problem; if the quality problem occurs on all the multiple cards, define the first judgment result as the quality problem being caused by the failure of the production equipment; otherwise, define the first judgment result as the quality problem being caused by the quality of the card itself; a second judgment unit configured to, if the first judgment result indicates that the quality problem is caused by a production equipment failure, perform a judgment based on the equipment status data; if the equipment status data indicates that the production equipment failure is caused by the production equipment itself, or is caused by a shutdown within the production plan, and if the equipment status data does not indicate that the production equipment failure is caused by the production equipment itself, perform a secondary judgment based on the production plan data to determine whether the displayed production equipment failure is caused by a failure of the production equipment producing the card itself or is caused by a shutdown within the production plan; and if the equipment status data does not indicate that the production equipment failure is caused by the production equipment itself, classify the quality problem as a quality problem caused by the quality of the card itself; The plan adjustment unit is used to obtain the corresponding production process when the quality problem occurs, and define the corresponding production process as an abnormal process, and adjust the production equipment of the card production task in the production plan data based on the abnormal process and the cause of the quality problem.

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