A product quality monitoring system and method based on MES

Abstract

The present application belongs to the field of product transportation technology, and provides a product quality monitoring system and method based on MES. When the system obtains abnormal detection information, it can extract product location information from the abnormal detection information, generate image acquisition instructions based on the product location information, and determine at least two target image collectors based on the product location information. Then, at least two target image collectors are controlled by image acquisition instructions to collect product image data at a target acquisition angle, and virtual reality image data is generated based on the collected product image data, so that the staff can better observe the abnormal products by watching the virtual reality image data. In this way, by adjusting the target acquisition angle of the target image collector according to the abnormal position of the product, the abnormal state of the product can be highlighted in the virtual reality image data, which is convenient for the staff to quickly obtain the abnormal position and analyze the cause of the abnormality.

Description

Technical Field

[0001] The present application belongs to the field of product transportation technology, and in particular, relates to a product quality monitoring system and method based on MES. Background Art

[0002] The Manufacturing Execution System (MES) is a management information system for the workshop level, located between the upper-level planning management system and the lower-level industrial control. Through this system, the staff can control and optimize any process from product order placement to production completion.

[0003] Among them, a monitoring system can be added as a functional branch in the manufacturing execution system, so that the staff can monitor the progress of product production through the monitoring system. For example, the staff can watch the production and transportation of products through the real-time images collected by the image collector deployed in the product workshop. In this way, the staff can leave the product workshop to prevent the noise or other unexpected events generated in the workshop from posing a threat to the personal safety of the staff.

[0004] However, this remote monitoring method for product production and transportation makes it difficult for staff to determine what kind of abnormal phenomenon occurs during product transportation. Therefore, staff still need to go to the site to check the problems one by one, which requires staff to stay in the workshop for a long time and leads to low efficiency in abnormality checking. Summary of the invention

[0005] The present application provides a product quality monitoring system and method based on MES to solve the problem of low efficiency of staff in troubleshooting product transportation anomalies in a remote monitoring scenario.

[0006] In a first aspect, the present application provides a product quality monitoring system based on MES, comprising: At least one monitoring unit, the monitoring unit is arranged at a preset position in the product transportation line; the monitoring unit at least includes an anomaly detector; the image collector is configured to collect images of the product transportation line; the anomaly detector is configured to generate anomaly detection information when an anomaly is detected in a product in the product transportation line; A collection unit, the collection unit at least comprising an image collector, the image collector is configured to collect images of the product transportation line; Virtual reality playback device; A control unit configured to: In response to anomaly detection information generated by the anomaly detector, extracting product location information from the anomaly detection information; generating an image acquisition instruction based on the product location information, and determining at least two target image collectors according to the product location information; Sending the image acquisition instruction to the at least two target image collectors, so that the at least two target image collectors adjust the image acquisition angle to the target acquisition angle; wherein the target acquisition angles of different target image collectors are different; Receiving product image data acquired by the at least two target image collectors at the target acquisition angle; Generate virtual reality image data according to the product image data; The virtual reality image data is sent to the virtual reality playback device so that the user can watch the virtual reality image data through the virtual reality playback device; the virtual image data is used to preferentially display the abnormal products to the user.

[0007] In some feasible embodiments, a communication unit is further included; the control unit generates virtual reality image data according to the product image data, and is further configured to: Sending the product image data to a server through the communication unit, so that the server generates virtual reality image data according to the product image data; The virtual reality image data transmitted back by the server is received through the communication unit.

[0008] In some feasible embodiments, the control unit generates virtual reality image data according to the product image data, and is further configured to: Extracting local abnormality information of the product from the abnormality detection information; the local abnormality information is used to characterize the abnormal part of the product; Generate an exception flag; The abnormality mark is added to the abnormal part of the product to generate virtual reality image data.

[0009] In some feasible embodiments, the control unit executes the generating of the abnormality flag and is further configured to: Determine the abnormality type according to the local abnormality information; the abnormality type includes at least one of the abnormality of the product itself and the abnormality between the product and the transportation line; An exception identifier corresponding to the exception type is generated according to the exception type.

[0010] In some feasible embodiments, the control unit performs extraction of local abnormality information of the product from the abnormality detection information, and is further configured to: Generate troubleshooting recommendation information based on the local abnormality information; wherein, when the virtual reality image data is played, the troubleshooting recommendation information is displayed in an area that can be viewed by the user; the troubleshooting recommendation information is information obtained based on a historical data analysis model, and the troubleshooting recommendation information is used to prompt the user the cause of the product abnormality.

[0011] In some feasible embodiments, the control unit is further configured to: In response to the received picture scaling instruction, the virtual reality playback device is controlled to scale the playback picture of the virtual reality image data according to the scaling instruction; wherein, when the playback picture of the virtual reality image data is scaled, the target viewing angle of the virtual reality image data remains unchanged.

[0012] In some feasible embodiments, the control unit executes sending the virtual reality image data to the virtual reality playback device, and is further configured to: Determining a target viewing angle according to the local abnormal information; The target viewing angle and the virtual reality image data are sent to the virtual reality playback device; the target viewing angle is used to control the viewing angle of the playback screen when the virtual reality playback device plays the virtual reality image data, so as to give priority to displaying the abnormal position of the product.

[0013] In some feasible embodiments, the control unit is further configured to: In response to the received target viewing angle adjustment instruction, the target viewing angle adjustment instruction is sent to the image collector specified by the target viewing angle adjustment instruction, so that the capture viewing angle of the specified image collector is adjusted to a new target position.

[0014] In a second aspect, the present application provides a product quality monitoring method based on MES, which can be applied to the product quality monitoring system based on MES described in the first aspect. The method comprises: In response to anomaly detection information generated by the anomaly detector, extracting product location information from the anomaly detection information; generating an image acquisition instruction based on the product location information, and determining at least two target image collectors according to the product location information; Sending the image acquisition instruction to the at least two target image collectors, so that the at least two target image collectors adjust the image acquisition angle to the target acquisition angle; wherein the target acquisition angles of different target image collectors are different; Receiving product image data acquired by the at least two target image collectors at the target acquisition angle; Generate virtual reality image data according to the product image data; The virtual reality image data is sent to the virtual reality playback device so that the user can watch the virtual reality image data through the virtual reality playback device; the virtual image data is used to preferentially display the abnormal products to the user.

[0015] It can be seen from the above technical content that the embodiment of the present application provides a product quality monitoring system and method based on MES. When the system obtains abnormality detection information, it can extract product location information from the abnormality detection information, generate image acquisition instructions based on the product location information, and determine at least two target image collectors based on the product location information. Then, at least two target image collectors are controlled by the image acquisition instructions to collect product image data at a target acquisition angle, and virtual reality image data is generated based on the collected product image data, so that the staff can better observe the abnormal products by watching the virtual reality image data. In this way, by adjusting the target acquisition angle of the target image collector according to the abnormal position of the product, the abnormal state of the product can be highlighted in the virtual reality image data, which is convenient for the staff to quickly obtain the abnormal position and analyze the cause of the abnormality. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solution of the present application, the drawings required for use in the embodiments are briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0017] Figure 1 A schematic diagram of product transportation monitoring provided for some embodiments of the present application; Figure 2 A schematic diagram of a first abnormal identification provided in some embodiments of the present application; Figure 3 A second abnormal identification schematic diagram provided for some embodiments of the present application; Figure 4 A schematic diagram of recommended information for troubleshooting provided in some embodiments of the present application; Figure 5 A timing diagram of the interaction of various components provided for some embodiments of the present application. DETAILED DESCRIPTION

[0018] The embodiments will be described in detail below, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation methods described in the following embodiments do not represent all implementation methods consistent with the present application. They are only examples of systems and methods consistent with some aspects of the present application.

[0019] During the manufacturing process, workers can view the production or transportation process in real time through remote monitoring. For example, products can be transported on the production line, and the transportation route is pre-built and planned. Figure 1 As shown in the schematic diagram of product transportation monitoring, multiple image collectors, such as cameras, can be arranged in the product transportation workshop to collect the status of product transportation in real time. After collecting image data, the camera can feed back to the control center, so that the staff can view the real-time product transportation data from the display end connected to the control center.

[0020] However, with this monitoring method, the staff can only find problems and perform maintenance when there are obvious abnormalities in the product transportation. For example, when the product is off the transportation track, the transportation track collapses, and other abnormalities, the staff can intuitively find these problems from the image data displayed on the monitor, and then go to the product workshop to solve the problem. However, for some minor product quality problems, such as product labels falling off; or minor problems that are likely to gradually affect the stability of product transportation, the position of the product on the transportation track gradually shifts; it is difficult for the staff to find specific problems from the image data displayed on the monitor alone. In addition, even when the abnormality detection device in the transportation track detects that there is a problem with the product, it is difficult to actively show it to the staff, resulting in the staff only knowing that the problem has occurred but not knowing the source of the problem. Even if the staff goes to the workshop to maintain the abnormal situation at this time, it is necessary to check step by step, which not only increases the safety risks of the staff in the workshop, but also is not conducive to the staff's troubleshooting efficiency.

[0021] In order to solve the above problems, the present application provides a product quality monitoring system based on MES, which takes the MES system as the overall framework and embeds monitoring branches to focus on and display abnormal products through the monitoring branches, so that staff can quickly find abnormal parts of the products.

[0022] In some embodiments, the product quality monitoring system includes at least one monitoring unit, wherein the monitoring unit is arranged at a preset position in the product transportation line, and the monitoring unit includes at least an anomaly detector. The anomaly detector here refers to a laser detector, a displacement detector, and other electronic devices that can detect whether the positional relationship between the product and the transportation track is normal. The type of anomaly detector can be adjusted according to demand. When the anomaly detector detects an abnormality in the product transportation line (including the product), it will generate anomaly detection information.

[0023] The product quality monitoring system also includes an acquisition unit, which may include an image collector. The image collector here may refer to a general camera or a more accurate industrial camera. The image collector is used to collect images of products during the transportation stage. In some embodiments, the position of the image collector can also be changed as needed, and the image collector can be set up in a track to improve the flexibility of image acquisition. The shooting angle of the image collector can also be changed according to the received instructions.

[0024] The product quality monitoring system also includes a virtual reality playback device, which can be a VR device such as VR glasses for playing panoramic views. In this way, when a product transportation failure occurs, the staff can wear the VR device to observe the product from a panoramic view. By simulating the scene of the staff in the workshop, the staff's ability to remotely view product anomalies is enhanced, and the staff's abnormality troubleshooting efficiency is improved.

[0025] The product quality monitoring system further comprises a control unit, which is configured to: In response to anomaly detection information generated by the anomaly detector, product location information is extracted from the anomaly detection information.

[0026] An image acquisition instruction is generated based on the product location information, and at least two target image collectors are determined according to the product location information.

[0027] The image acquisition instruction is sent to the at least two target image collectors, so that the at least two target image collectors adjust the image acquisition angle to the target acquisition angle; wherein the target acquisition angles of different target image collectors are different.

[0028] Receive product image data acquired by the at least two target image collectors at the target acquisition angle.

[0029] Virtual reality image data is generated according to the product image data.

[0030] The virtual reality image data is sent to the virtual reality playback device so that the user can watch the virtual reality image data through the virtual reality playback device; the virtual image data is used to preferentially display the abnormal products to the user.

[0031] In some embodiments, when a product is transported on a transport track, an anomaly detector detects that a label of the product has fallen off. At this time, the anomaly detector can generate anomaly detection information about the falling off of the product label. The anomaly detection information can include the event of the product label falling off, and can also include the position of the product label in the product to indicate the source of the anomaly. The position where the product has an anomaly can be expressed in the form of coordinates to facilitate the control process.

[0032] It is understandable that the detection accuracy of the anomaly detector may not be sufficient, so it is necessary to use images to reflect the specific abnormal situation to the staff. Therefore, the control unit is required to control the image collector to focus on the local abnormal part of the product.

[0033] In this way, the control unit can generate an image acquisition instruction when the abnormal detection information is collected. The image acquisition instruction here contains coordinates used to characterize the abnormal position of the product. In this way, when the control unit sends the image acquisition instruction to the target image collector, the target image collector can adjust the target acquisition angle according to the abnormal position of the product to obtain images of the abnormal part of the product as much as possible, which is conducive to highlighting the abnormal part of the product and facilitating the staff to check.

[0034] It should be noted that the control unit can also determine the image collector that is most conducive to capturing the image of the abnormal part of the product, that is, the target image collector, through the product position information, so that the control unit can easily mobilize the image collector.

[0035] In this way, after receiving the image acquisition instruction, the image collector can collect images of abnormal positions of the product at the target acquisition angle and use them to synthesize virtual reality image data. The control unit can synthesize virtual reality image data based on the image data collected by multiple image collectors, and send the synthesized virtual reality image data to the virtual reality playback device. Then the staff can watch the playback screen of the virtual reality image data by wearing a virtual reality playback device such as VR glasses.

[0036] In other embodiments, the control unit can also send the product image data collected by the image collector to the server through the communication unit, and the server generates virtual reality image data based on the product image data, and receives the virtual reality image data sent back by the server through the communication unit again. In this way, the control unit can improve the synthesis quality of the virtual reality image data with the help of the synthesis and computing capabilities of the server, thereby facilitating the staff to quickly discover product abnormalities from the virtual reality image data.

[0037] In some embodiments, the product location information can be further refined to local abnormal information. For example, taking the abnormal event of product label falling off as an example, the local abnormal information can be used to prompt the control unit to take a picture of the product location where the label is placed. That is, the control unit generates virtual reality image data based on the product image data, and is further configured as follows: Local abnormality information of the product is extracted from the abnormality detection information.

[0038] Generate an exception flag.

[0039] The abnormality mark is added to the abnormal part of the product to generate virtual reality image data.

[0040] It is understandable that the local abnormality information can represent the abnormal part of the product, so that the control unit can generate an abnormality mark according to the local abnormality information. The abnormality mark can be a mark that is compatible with the abnormal part. For example, Figure 2 As shown in the schematic diagram of the first abnormal identification, when the product abnormality is the falling off of the label, the abnormal identification can be a box identification. When generating virtual reality image data, the box identification can be added to the position where the label should be placed on the product surface to remind the staff of the source of the abnormality.

[0041] In other embodiments, the control unit may select different abnormality identifiers according to the abnormality type to further facilitate the staff to identify the source of the abnormality. That is, the control unit performs the extraction of local abnormality information of the product from the abnormality detection information, and is further configured as follows: The abnormality type is determined according to the local abnormality information; the abnormality type includes at least one of an abnormality of the product itself and an abnormality between the product and the transportation line.

[0042] An exception identifier corresponding to the exception type is generated according to the exception type.

[0043] like Figure 3 The second abnormality identification schematic diagram shown in the figure shows that in some embodiments, the abnormality is caused by the positional relationship between the product and the transport track being offset. In this case, the abnormality identification can be a dashed line. In the virtual reality image data, the ideal positional relationship between the product and the transport track can be marked with a dashed line to remind the staff of the source of the abnormality.

[0044] In this way, by adding abnormal identification to the virtual reality image data, the staff can be effectively informed of the source of the abnormality. In this way, the staff can observe the virtual reality image data and quickly observe the source of the abnormality from the on-site perspective without being present at the scene, which is conducive to improving the efficiency of abnormality investigation.

[0045] It is understandable that the mapping relationship between the exception type and the exception identifier can be pre-stored, so that after the control unit determines the exception type based on the local exception information, it can determine the exception identifier by calling the mapping relationship between the exception type and the exception identifier, and add the exception identifier to the virtual reality image data.

[0046] like Figure 4 As shown in the schematic diagram of the troubleshooting recommendation information, the virtual reality image playback device can also display the troubleshooting recommendation information in the playback screen to assist the staff in quickly troubleshooting product abnormalities. That is, when the control unit extracts the local abnormality information of the product from the abnormality detection information, it is further configured as follows: Generate troubleshooting recommendation information based on the local abnormality information; wherein, when the virtual reality image data is played, the troubleshooting recommendation information is displayed in an area that can be viewed by the user; the troubleshooting recommendation information is information obtained based on a historical data analysis model, and the troubleshooting recommendation information is used to prompt the user the cause of the product abnormality.

[0047] It is understandable that the troubleshooting recommendation information can be text information embedded in the virtual reality image data. When embedding the troubleshooting recommendation information, the control unit can adaptively adjust the troubleshooting recommendation information in combination with the display screen affected by the virtual reality. For example, when the main screen is on the left side of the display screen, the troubleshooting recommendation information can be preferentially displayed on the right side of the display screen to avoid blocking the main screen. For another example, when the main screen occupies a large area of ​​the display screen, the troubleshooting recommendation information can be set in combination with the straight line mark and the dotted line mark, so that one end of the straight line mark points to the abnormal part of the product, and the other end of the straight line mark points to the troubleshooting recommendation information. In this way, a rich and diverse prompt can be formed for the staff to improve the troubleshooting efficiency of the staff.

[0048] In some embodiments, the troubleshooting recommendation information can be obtained by analyzing the anomaly detection information (including product anomaly type and product anomaly location) generated by the anomaly detector using the historical data analysis model. In this way, by deploying the historical data analysis model, the anomaly source can be inferred online based on the product anomalies that have occurred during the production and transportation process, which is helpful for assisting staff to quickly discover the source of product anomalies and improve maintenance efficiency.

[0049] In some embodiments, when using the virtual reality playback device, the staff can scale the display image to meet the observation needs. That is, the control unit is also configured as follows: In response to the received picture scaling instruction, the virtual reality playback device is controlled to scale the playback picture of the virtual reality image data according to the scaling instruction; wherein, when the playback picture of the virtual reality image data is scaled, the target viewing angle of the virtual reality image data remains unchanged.

[0050] It is understandable that the staff can input the zoom command (zoom in or zoom out command) through a keyboard, mouse, handle or other external devices that can be connected to the virtual reality playback device. The zoom command can also be input by voice input or other methods. In this way, the virtual reality playback device can zoom in or out the display screen to meet the needs of the staff. Furthermore, by enhancing the flexibility of the display screen adjustment, it is helpful to improve the efficiency of the staff in discovering product abnormalities and troubleshooting the causes of abnormalities.

[0051] It should be noted that during the zooming process, the viewing angle of the display remains unchanged, so as to show the staff the location where the product anomaly occurs first, so that the staff can quickly find the anomaly of the product and then trace the product problem based on the product anomaly. For example, when a product label falls off, the staff can inspect the production line where the product label is deployed.

[0052] In other embodiments, when the display screen displays the recommended information for investigation, a trigger control corresponding to the recommended information for investigation may also be additionally displayed. The trigger control is used to trigger the virtual reality image corresponding to the recommended information for investigation. For example, after the staff selects the trigger control, the control unit can determine the source of the product abnormality corresponding to the recommended information for investigation according to the trigger control, such as the product label binding corresponding to the label shedding, and then the control unit can determine the image collector set near the product label binding, and then control these image collectors to collect image data of the product label binding to generate virtual reality image data. In this way, the staff can watch the virtual reality image data corresponding to the recommended information for investigation after selecting the trigger control, so that the staff can remotely watch the operating status of the product label binding according to the virtual reality image data. Even if the staff is finally required to go to the product label binding for investigation, since the location has been observed in advance, it is also beneficial to improve the staff's investigation efficiency to a certain extent.

[0053] It is understandable that the virtual reality image data corresponding to the trigger control can replace the virtual reality image data corresponding to the abnormal part of the product when playing. The screen can also be split in the display screen to facilitate the staff to compare and observe the two screens, which is conducive to improving the staff's troubleshooting efficiency.

[0054] In some embodiments, the control unit can control the viewing angle provided by the virtual reality playback device for the staff according to the abnormal position of the product. That is, the control unit executes sending the virtual reality image data to the virtual reality playback device, and is further configured as follows: A target viewing angle is determined according to the local abnormality information.

[0055] The target viewing angle and the virtual reality image data are sent to the virtual reality playback device; the target viewing angle is used to control the viewing angle of the playback screen when the virtual reality playback device plays the virtual reality image data, so as to give priority to displaying the abnormal position of the product.

[0056] In some embodiments, after determining the abnormal part, the control unit can determine the viewing angle provided by the virtual reality playback device, that is, the target viewing angle, according to the abnormal part of the product. In this way, when an abnormality occurs in the product, the acquisition angle is first adjusted by controlling the image collector to obtain image data of the abnormal product and the surrounding area of ​​the product, which is conducive to preferentially showing the abnormal part to the user and facilitating the staff to troubleshoot the problem. Secondly, according to the location where the product is abnormal, the target viewing angle is adjusted, which can provide the staff with the best viewing angle for observing product abnormalities from the perspective of machine analysis, thereby further improving the efficiency of the staff in troubleshooting problems. This allows the staff to observe product abnormalities more concentratedly. It avoids the need for the staff to adjust the picture angle affected by the virtual reality to the optimal observation angle by inputting adjustment instructions multiple times when watching virtual reality images.

[0057] In some embodiments, the staff can actively adjust the acquisition angle of the image collector by human-computer interaction to adjust the image capture range of the image collector according to the needs. That is, the control unit is also configured as follows: In response to the received target viewing angle adjustment instruction, the target viewing angle adjustment instruction is sent to the image collector specified by the target viewing angle adjustment instruction, so that the capture viewing angle of the specified image collector is adjusted to a new target position.

[0058] It should be noted that by adjusting the target viewing angle, a wider range of images can be obtained, which makes the display screen content corresponding to the virtual reality image data richer. For example, the anomaly detector is usually set in segments, so even if the product anomaly can be displayed in the virtual reality image, the image of a certain position may not be able to fully display when the product anomaly occurs. In this way, the staff can adjust the shooting angle of the image collector, and on the basis of determining the location of the product anomaly, by viewing the images of other shooting angles, try to determine the location of the anomaly.

[0059] For example, the relative position deviation between the product and the transport track may be caused by an abnormal bulge in the transport track, resulting in abnormal bumps in the transport process, and then the relative position of the product and the transport track at the location where the anomaly detector is deployed deviates. The staff can find the deviation of the product position by relying on the display screen of the virtual reality data, but cannot find out which position of the product deviates during the operation process. Then, by adjusting the viewing angle of the image collector, they can watch a more complete process of product transportation to find the cause of the product abnormality.

[0060] This will help staff to first determine the location of product abnormalities through virtual reality image data, and then determine the source location of the product abnormality, thereby improving the staff's efficiency in troubleshooting abnormalities.

[0061] like Figure 5 As shown in the timing diagram of the interaction between the components, some embodiments of the present application also provide a product quality monitoring method based on MES, including: In response to anomaly detection information generated by the anomaly detector, product location information is extracted from the anomaly detection information.

[0062] An image acquisition instruction is generated based on the product location information, and at least two target image collectors are determined according to the product location information.

[0063] The image acquisition instruction is sent to the at least two target image collectors, so that the at least two target image collectors adjust the image acquisition angle to the target acquisition angle; wherein the target acquisition angles of different target image collectors are different.

[0064] Receive product image data acquired by the at least two target image collectors at the target acquisition angle.

[0065] Virtual reality image data is generated according to the product image data.

[0066] The virtual reality image data is sent to the virtual reality playback device so that the user can watch the virtual reality image data through the virtual reality playback device; the virtual image data is used to preferentially display the abnormal products to the user.

[0067] The embodiment of the present application provides a product quality monitoring system and method based on MES. When the system obtains abnormality detection information, it can extract product location information from the abnormality detection information, generate image acquisition instructions based on the product location information, and determine at least two target image collectors based on the product location information. Then, at least two target image collectors are controlled by the image acquisition instructions to collect product image data at a target acquisition angle, and virtual reality image data is generated based on the collected product image data, so that the staff can better observe the abnormal products by watching the virtual reality image data. In this way, by adjusting the target acquisition angle of the target image collector according to the abnormal position of the product, the abnormal state of the product can be highlighted in the virtual reality image data, which is convenient for the staff to quickly obtain the abnormal position and analyze the cause of the abnormality.

[0068] Similar parts between the embodiments provided in this application can be referenced to each other. The specific implementation methods provided above are only a few examples under the general concept of this application and do not constitute a limitation on the protection scope of this application. For those skilled in the art, any other implementation methods expanded based on the scheme of this application without creative work belong to the protection scope of this application.

Claims

1. A product quality monitoring system based on MES, characterized in that: include: At least one monitoring unit, which is arranged at a preset position in the product transportation line; The monitoring unit includes at least an anomaly detector configured to generate anomaly detection information when an anomaly is detected in a product in the product transportation line; A collection unit, the collection unit at least comprising an image collector, the image collector is configured to collect images of the product transportation line; Virtual reality playback device; A control unit configured to: In response to anomaly detection information generated by the anomaly detector, extracting product location information from the anomaly detection information; generating an image acquisition instruction based on the product location information, and determining at least two target image collectors according to the product location information; Sending the image acquisition instruction to at least two of the target image collectors, so that at least two of the target image collectors adjust the image acquisition angle to a target acquisition angle; wherein the target acquisition angles of different target image collectors are different; Receiving product image data acquired by the at least two target image collectors at the target acquisition angle; Generate virtual reality image data according to the product image data; The virtual reality image data is sent to the virtual reality playback device so that the user can watch the virtual reality image data through the virtual reality playback device; the virtual reality image data is used to preferentially display the abnormal products to the user.

2. The MES-based product quality monitoring system according to claim 1, characterized in that: It also includes a communication unit; the control unit generates virtual reality image data according to the product image data, and is further configured to: Sending the product image data to a server through the communication unit, so that the server generates virtual reality image data according to the product image data; The virtual reality image data transmitted back by the server is received through the communication unit.

3. The MES-based product quality monitoring system according to claim 1, characterized in that: The control unit generates virtual reality image data according to the product image data, and is further configured to: Extracting local abnormality information of the product from the abnormality detection information; the local abnormality information is used to characterize the abnormal part of the product; Generate an exception flag; The abnormality mark is added to the abnormal part of the product to generate virtual reality image data.

4. The MES-based product quality monitoring system according to claim 3 is characterized in that: The control unit executes the generating of the abnormality mark, and is further configured to: Determine the abnormality type according to the local abnormality information; the abnormality type includes at least one of the abnormality of the product itself and the abnormality between the product and the transportation line; An exception identifier corresponding to the exception type is generated according to the exception type.

5. The MES-based product quality monitoring system according to claim 3 is characterized in that: The control unit performs extraction of local abnormality information of the product from the abnormality detection information, and is further configured to: Generate troubleshooting recommendation information based on the local abnormality information; wherein, when the virtual reality image data is played, the troubleshooting recommendation information is displayed in an area that can be viewed by the user; the troubleshooting recommendation information is information obtained based on a historical data analysis model, and the troubleshooting recommendation information is used to prompt the user the cause of the product abnormality.

6. The MES-based product quality monitoring system according to claim 3 is characterized in that: The control unit is further configured to: In response to the received picture scaling instruction, the virtual reality playback device is controlled to scale the playback picture of the virtual reality image data according to the scaling instruction; wherein, when the playback picture of the virtual reality image data is scaled, the target viewing angle of the virtual reality image data remains unchanged.

7. The MES-based product quality monitoring system according to claim 3 is characterized in that: The control unit executes sending the virtual reality image data to the virtual reality playback device, and is further configured to: Determining a target viewing angle according to the local abnormal information; The target viewing angle and the virtual reality image data are sent to the virtual reality playback device; the target viewing angle is used to control the viewing angle of the playback screen when the virtual reality playback device plays the virtual reality image data, so as to give priority to displaying the abnormal position of the product.

8. The MES-based product quality monitoring system according to claim 3, characterized in that: The control unit is further configured to: In response to the received target viewing angle adjustment instruction, the target viewing angle adjustment instruction is sent to the image collector specified by the target viewing angle adjustment instruction, so that the capture viewing angle of the specified image collector is adjusted to a new target position.

9. A product quality monitoring method based on MES, characterized in that: The MES-based product quality monitoring system applied to any one of claims 1 to 8 comprises: In response to anomaly detection information generated by the anomaly detector, extracting product location information from the anomaly detection information; generating an image acquisition instruction based on the product location information, and determining at least two target image collectors according to the product location information; Sending the image acquisition instruction to at least two of the target image collectors, so that at least two of the target image collectors adjust the image acquisition angle to a target acquisition angle; wherein the target acquisition angles of different target image collectors are different; Receiving product image data acquired by the at least two target image collectors at the target acquisition angle; Generate virtual reality image data according to the product image data; The virtual reality image data is sent to the virtual reality playback device so that the user can watch the virtual reality image data through the virtual reality playback device; the virtual reality image data is used to preferentially display the abnormal products to the user.

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