Digital production monitoring system and method based on cloud side-end cooperation

Abstract

The invention discloses a digital production monitoring system and method based on cloud side-end collaboration, relates to the field of digital production monitoring, solves the problem that unified monitoring of a production workshop is difficult to ensure detection efficiency and monitoring accuracy, and comprises an equipment analysis unit, a product analysis unit and a terminal display module, the equipment analysis unit is used for analyzing the operation condition of production equipment corresponding to the product, generating an abnormal operation signal, a normal operation signal or a temperature abnormal signal through analysis, and sending the abnormal operation signal, the normal operation signal or the temperature abnormal signal to the terminal display module; the product analysis unit is used for analyzing the production conditions of the same batch of products, generating a product qualification signal or a product disqualification signal through analysis and sending the product qualification signal or the product disqualification signal to the terminal display module; the terminal display module is used for displaying the product qualification signal, the product disqualification signal, the operation abnormal signal, the operation normal signal or the temperature abnormal signal, digital monitoring of the production link is achieved, and the production stability and the production quality are guaranteed.

Description

Technical Field

[0001] The present invention belongs to the technical field of digital production monitoring, and specifically is a digital production monitoring system based on cloud-edge-end collaboration. Background Art

[0002] With the rapid development of information technology, digitalization has penetrated into various industries and fields, becoming an important force for economic and social development. Digital production refers to the transformation and upgrading of traditional production processes through the application of digital technology to achieve automation, intelligence and efficiency of the production process; in the field of industrial Internet, through digital technology, enterprises can automate and intelligentize the entire process from design to production, thereby improving production efficiency and product quality.

[0003] In the prior art, when factories conduct production monitoring, they usually need to monitor each link in the production process. Production workshops often implement unified monitoring of production links. However, due to the large number of production links, a unified production monitoring method is difficult to ensure detection efficiency and monitoring accuracy.

[0004] To this end, we propose a digital production monitoring system and method based on cloud-edge-end collaboration. Summary of the invention

[0005] The purpose of the present invention is to propose a digital production monitoring system and method based on cloud-edge-end collaboration to solve the problem that when a factory conducts production monitoring as proposed in the above background technology, it is usually necessary to monitor each link in the production process, and production workshops mostly implement unified monitoring of production links. However, due to the large number of production links, a unified production monitoring method is difficult to ensure detection efficiency and monitoring accuracy.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] In the first aspect, a digital production monitoring system based on cloud-edge-end collaboration includes a data acquisition module, an equipment analysis unit, a product analysis unit and a terminal display module;

[0008] The data acquisition module is used to collect real-time equipment data of the production equipment corresponding to the product and real-time product data of the product, and send the real-time equipment data to the equipment analysis unit and send the real-time product data to the product analysis unit;

[0009] The equipment analysis unit is used to analyze the operating status of the production equipment corresponding to the product, and the analysis generates an abnormal operation signal, a normal operation signal or a temperature abnormality signal and sends it to the terminal display module; the product analysis unit is used to analyze the production status of the same batch of products, and the analysis generates a product qualified signal or a product unqualified signal and sends it to the terminal display module;

[0010] The terminal display module is used to display a product qualification signal, a product failure signal, an abnormal operation signal, a normal operation signal or an abnormal temperature signal.

[0011] Furthermore, the real-time equipment data includes the real-time equipment temperature value of the production equipment corresponding to the product and the duration of the working condition in each working condition, the working condition includes equipment operation, equipment failure and equipment shutdown, and the duration of the working condition includes equipment operation time, equipment shutdown time and equipment failure time;

[0012] Real-time product data is a collection of product appearance pictures of each product in the same batch of products.

[0013] Furthermore, the collection process of the product appearance atlas is as follows:

[0014] Set the product to the corresponding ring light source, place the product in the center of the ring light source, and use eight-way control and time-sharing exposure for the ring light source to continuously capture eight images of the product;

[0015] Adjust the irradiation angle of the ring light source so that it is perpendicular to the product surface;

[0016] The product appearance pictures of the products when irradiated are collected in sequence to form a product appearance picture set of the corresponding products.

[0017] Furthermore, the analysis process of the device analysis unit is specifically as follows:

[0018] Obtain the real-time equipment temperature value, equipment operation time and equipment downtime of the production equipment corresponding to the product;

[0019] Then, the operating parameters of the production equipment corresponding to the product are obtained, and the operating parameters include the maximum temperature threshold, the equipment standard temperature threshold, and the equipment temperature deviation threshold;

[0020] If the real-time device temperature value is greater than or equal to the maximum temperature threshold, a temperature abnormality signal is generated;

[0021] If the real-time device temperature value is less than the maximum temperature threshold, the real-time device temperature values ​​of the production equipment corresponding to the product at multiple time points are continuously recorded, and the real-time device temperature values ​​corresponding to the multiple time points are added and averaged to obtain the device average temperature value of the production equipment corresponding to the product;

[0022] The equipment temperature deviation value of the corresponding production equipment of the product is calculated by the formula. The specific formula is as follows:

[0023] Equipment temperature deviation value = equipment average temperature value - equipment standard temperature threshold;

[0024] If the device temperature deviation value is greater than or equal to the device temperature deviation threshold, a temperature abnormality signal is generated;

[0025] If the device temperature deviation value is less than the device temperature deviation threshold, proceed to the subsequent steps.

[0026] Furthermore, the analysis process of the device analysis unit also includes:

[0027] Set the operation cycle T of the production equipment corresponding to the product, count the duration of the working conditions of the production equipment corresponding to the product in each working condition during the operation cycle, and calculate the proportion of time the production equipment corresponding to the product is in each working condition through the formula. The specific formula is as follows:

[0028] Operating time ratio = operating time / equipment operation cycle*100%. Operating time ratio includes operating time ratio, downtime ratio and fault time ratio.

[0029] If the downtime ratio exceeds the downtime threshold or the fault ratio exceeds the fault threshold, an operation abnormality signal is generated;

[0030] If the downtime ratio does not exceed the downtime threshold, and the fault ratio does not exceed the fault threshold, a normal operation signal is generated.

[0031] Furthermore, the analysis process of the product analysis unit is specifically as follows:

[0032] Obtain a product appearance atlas of each product, and overlay multiple product appearance images in the product appearance atlas to form an appearance overlay image corresponding to the product;

[0033] Perform crack and scratch detection on the product surface to generate product failure signal or product qualification signal.

[0034] Furthermore, the detection steps of crack and scratch detection are as follows:

[0035] Obtain the pixel values ​​of all pixels in the product's corresponding appearance overlay image, and count the pixel values ​​of all pixels in the product's corresponding appearance overlay image to obtain the pixel value mode;

[0036] If the pixel value of a pixel point in the appearance overlay image corresponding to the product is less than the pixel value mode, the corresponding pixel point is an abnormal pixel point, and the number of abnormal pixels is counted. When the number of abnormal pixels in the appearance overlay image corresponding to the product is greater than or equal to the first pixel point threshold, a product unqualified signal is generated; when the number of abnormal pixels in the appearance overlay image corresponding to the product is less than the first pixel point threshold, a product qualified signal is generated;

[0037] If the pixel value of the pixel point in the appearance overlay image corresponding to the product is greater than or equal to the pixel value mode, a product qualified signal is generated.

[0038] Furthermore, the crack and scratch detection steps also include:

[0039] Obtain the pixel values ​​of all pixels in the appearance overlay image corresponding to the product, and record them as the first pixel values;

[0040] Perform mean filtering on the appearance overlay image, randomly select a pixel point, calculate the mean of the corresponding pixel values ​​of all adjacent pixels of the pixel point, and use the mean as the pixel value of the current pixel point;

[0041] According to the above steps, the pixel value corresponding to each pixel point in the appearance overlay image is replaced to obtain the mean filter image corresponding to the appearance overlay image;

[0042] Subtract the appearance overlay image from the mean filter image to obtain a difference image, traverse all pixels in the difference image, and obtain the difference pixel values ​​corresponding to the pixels;

[0043] If the absolute value of the differential pixel value is greater than or equal to the differential pixel threshold, the product is identified as a substandard product, and the number of substandard products in the same batch of products is counted. The number of substandard products is compared with the production volume to obtain the production qualification rate of the product. When the production qualification rate exceeds the preset production qualification rate, a product qualification signal is generated. When the production qualification rate does not exceed the preset production qualification rate, a product substandard signal is generated.

[0044] If the absolute value of the differential pixel value is less than the differential pixel threshold, a product qualified signal is generated.

[0045] Secondly, the digital production monitoring method based on cloud-edge-end collaboration is as follows:

[0046] Step S100, the data acquisition module acquires real-time equipment data of the production equipment corresponding to the product and real-time product data of the product, and sends the real-time equipment data to the equipment analysis unit and sends the real-time product data to the product analysis unit;

[0047] Step S200, the equipment analysis unit analyzes the operating status of the production equipment corresponding to the product, generates an abnormal operation signal, a normal operation signal or a temperature abnormality signal, and sends it to the terminal display module;

[0048] Step S300, the product analysis unit analyzes the production status of the same batch of products, generates a product qualified signal or a product unqualified signal and sends it to the terminal display module;

[0049] Step S400: the terminal display module displays a product qualification signal, a product failure signal, an abnormal operation signal, a normal operation signal or an abnormal temperature signal.

[0050] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0051] The present invention collects real-time equipment data of production equipment corresponding to the product and real-time product data of the product. The equipment analysis unit analyzes the operating status of the production equipment corresponding to the product in combination with the real-time equipment data, and generates an abnormal operation signal, a normal operation signal or an abnormal temperature signal through analysis. On the other hand, the product analysis unit analyzes the production status of the same batch of products in combination with the real-time product data, and generates a qualified product signal or an unqualified product signal through analysis. The production status of the product and the equipment status of the production equipment corresponding to the product are known based on different signals. The present invention realizes digital monitoring of the production links to ensure production stability and production quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0053] Figure 1 is the overall system block diagram of the present invention;

[0054] Figure 2 It is a top view of the illumination of the annular light source in the present invention;

[0055] Figure 3 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0056] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] In one embodiment, see Figure 1-2 As shown, the technical solution provided by the present invention is: a digital production monitoring system based on cloud-edge-end collaboration, which is used for product production and manufacturing, and can monitor the operating status of the production equipment corresponding to the product in real time. The production equipment is used for product production and manufacturing, and also monitors the production status of the same batch of products. The workshop technicians make corresponding adjustments to the equipment based on the product production status and the operating status of the equipment, including a data acquisition module, an equipment analysis unit, a product analysis unit and a terminal display module;

[0058] In this embodiment, the data acquisition module is used to collect real-time equipment data of the production equipment corresponding to the product and real-time product data of the product, and send the real-time equipment data to the equipment analysis unit and send the real-time product data to the product analysis unit;

[0059] It should be specifically stated that real-time equipment data includes the real-time equipment temperature value of the production equipment corresponding to the product and the duration of each working condition. The working conditions include equipment operation, equipment failure and equipment shutdown. The duration of the working condition includes equipment operation time, equipment shutdown time and equipment failure time. Real-time product data is a collection of product appearance pictures of each product in the same batch of products.

[0060] In this embodiment, if Figure 2 As shown in the figure, the collection process of the product appearance atlas is as follows:

[0061] Step S1, setting the product to correspond to the annular light source, placing the product in the center of the annular light source, the annular light source is eight-way controlled and time-sharing exposed, and the product is continuously captured eight times;

[0062] Step S2, adjusting the irradiation angle of the annular light source so that the irradiation angle of the annular light source is perpendicular to the surface of the product;

[0063] Step S3, sequentially collecting product appearance pictures when the product is irradiated to form a product appearance picture set of the corresponding product;

[0064] In this embodiment, the equipment analysis unit is used to analyze the operating status of the production equipment corresponding to the product, and the analysis process is specifically as follows:

[0065] Obtain the real-time equipment temperature value, equipment operation time and equipment downtime of the production equipment corresponding to the product;

[0066] Then, the operating parameters of the production equipment corresponding to the product are obtained, and the operating parameters include the maximum temperature threshold, the equipment standard temperature threshold, and the equipment temperature deviation threshold;

[0067] If the real-time device temperature value is greater than or equal to the maximum temperature threshold, a temperature abnormality signal is generated;

[0068] If the real-time device temperature value is less than the maximum temperature threshold, the real-time device temperature values ​​of the production equipment corresponding to the product at multiple time points are continuously recorded, and the real-time device temperature values ​​corresponding to the multiple time points are added and averaged to obtain the device average temperature value of the production equipment corresponding to the product;

[0069] The equipment temperature deviation value of the corresponding production equipment of the product is calculated by the formula. The specific formula is as follows:

[0070] Equipment temperature deviation value = equipment average temperature value - equipment standard temperature threshold;

[0071] If the device temperature deviation value is greater than or equal to the device temperature deviation threshold, a temperature abnormality signal is generated;

[0072] If the device temperature deviation value is less than the device temperature deviation threshold, proceed to the subsequent steps;

[0073] Set the operation cycle T of the production equipment corresponding to the product, count the duration of the working conditions of the production equipment corresponding to the product in each working condition during the operation cycle, and calculate the proportion of time the production equipment corresponding to the product is in each working condition through the formula. The specific formula is as follows:

[0074] Operating time ratio = operating time / equipment operation cycle*100%. Operating time ratio includes operating time ratio, downtime ratio and fault time ratio.

[0075] If the downtime ratio exceeds the downtime threshold or the fault ratio exceeds the fault threshold, an operation abnormality signal is generated;

[0076] If the downtime ratio does not exceed the downtime threshold, and the fault ratio does not exceed the fault threshold, a normal operation signal is generated;

[0077] The operation analysis unit sends an operation abnormality signal, a normal operation signal or a temperature abnormality signal to a terminal display module;

[0078] In this embodiment, the product analysis unit is used to analyze the production status of the same batch of products, and the analysis process is as follows:

[0079] Obtain a product appearance atlas of each product, and superimpose multiple product appearance images in the product appearance atlas into an appearance superimposed image corresponding to the product through a software algorithm;

[0080] Perform crack and scratch detection on the product surface to generate product failure signals or product qualification signals;

[0081] It should be specifically noted that if there are cracks or scratches on the surface of the product, the cracks or scratches will be highlighted by the light when the light source is vertically irradiated on the surface of the product. According to the difficulty of detection, there are two types: one is that the cracks or scratches on the surface of the product are large, and the grayscale value of the cracks or scratches in the corresponding appearance overlay image of the product changes significantly; the other is that the cracks or scratches on the surface of the product are small, and the grayscale value of the cracks or scratches in the corresponding appearance overlay image of the product does not change significantly;

[0082] In this embodiment, the detection steps of crack and scratch detection are as follows:

[0083] Obtain the pixel values ​​of all pixels in the product's corresponding appearance overlay image, and count the pixel values ​​of all pixels in the product's corresponding appearance overlay image to obtain the pixel value mode;

[0084] If the pixel value of a pixel point in the product's corresponding appearance overlay image is less than the pixel value mode, the pixel point is considered to be an abnormal pixel point, and the number of abnormal pixels is counted. When the number of abnormal pixels in the product's corresponding appearance overlay image is greater than or equal to the first pixel point threshold, it is considered that there are cracks or scratches on the product surface, and a product unqualified signal is generated. When the number of abnormal pixels in the product's corresponding appearance overlay image is less than the first pixel point threshold, a product qualified signal is generated.

[0085] If the pixel value of a pixel point in the appearance overlay image corresponding to the product is greater than or equal to the pixel value mode, the pixel point is considered to be a normal pixel point, and a product qualified signal is generated;

[0086] In this embodiment, the crack and scratch detection step further includes:

[0087] Obtain the pixel values ​​of all pixels in the appearance overlay image corresponding to the product, and record them as the first pixel values;

[0088] Perform mean filtering on the appearance overlay image, randomly select a pixel point, calculate the mean of the corresponding pixel values ​​of all the neighboring pixels of the pixel point, take the mean as the pixel value of the current pixel point, replace the corresponding pixel value of each pixel point in the appearance overlay image according to the above steps, and obtain the corresponding mean filtering image of the appearance overlay image. In practice, 3*3 neighboring pixels around the randomly selected pixel point can be used to calculate the mean of the corresponding pixel values ​​of the neighboring pixels;

[0089] Subtract the appearance overlay image from the mean filter image to obtain a difference image, traverse all pixels in the difference image, and obtain the difference pixel values ​​corresponding to the pixels;

[0090] If the absolute value of the differential pixel value is greater than or equal to the differential pixel threshold, it is considered that there are cracks or scratches on the surface of the product, and the product is identified as a defective product. The number of defective products in the same batch of products is counted, and the number of defective products is compared with the production volume to obtain the production qualification rate of the product. When the production qualification rate exceeds the preset production qualification rate, a product qualification signal is generated. When the production qualification rate does not exceed the preset production qualification rate, a product defect signal is generated.

[0091] If the absolute value of the differential pixel value is less than the differential pixel threshold, the product is considered qualified and a product qualified signal is generated;

[0092] The product analysis module sends a product qualified signal or a product unqualified signal to the terminal display module, and the terminal display module is used to display the product qualified signal, the product unqualified signal, the operation abnormality signal, the normal operation signal or the temperature abnormality signal.

[0093] In this embodiment, by collecting real-time equipment data of the production equipment corresponding to the product and real-time product data of the product, the equipment analysis unit analyzes the operating status of the production equipment corresponding to the product in combination with the real-time equipment data, and generates an abnormal operation signal, a normal operation signal or an abnormal temperature signal through analysis. On the other hand, the product analysis unit analyzes the production status of the same batch of products in combination with the real-time product data, and generates a qualified product signal or an unqualified product signal through analysis. The production status of the product and the equipment status of the production equipment corresponding to the product are known based on different signals. The present invention realizes digital monitoring of the production links to ensure production stability and production quality.

[0094] In this application, if corresponding calculation formulas appear, the above calculation formulas are all dimensionless and take their numerical calculations. The weight coefficients, proportional coefficients and other coefficients in the formulas are set to a result value obtained by quantifying each parameter. The size of the weight coefficient and the proportional coefficient can be determined as long as it does not affect the proportional relationship between the parameter and the result value.

[0095] In another embodiment, if Figure 3 As shown, a digital production monitoring method based on cloud-edge-end collaboration is also provided, and the specific method is as follows:

[0096] Step S100, the data acquisition module acquires real-time equipment data of the production equipment corresponding to the product and real-time product data of the product, and sends the real-time equipment data to the equipment analysis unit and sends the real-time product data to the product analysis unit;

[0097] Step S200, the equipment analysis unit analyzes the operating status of the production equipment corresponding to the product, generates an abnormal operation signal, a normal operation signal or a temperature abnormality signal, and sends it to the terminal display module;

[0098] Step S300, the product analysis unit analyzes the production status of the same batch of products, generates a product qualified signal or a product unqualified signal and sends it to the terminal display module;

[0099] Step S400: the terminal display module displays a product qualification signal, a product failure signal, an abnormal operation signal, a normal operation signal or an abnormal temperature signal.

[0100] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A digital production monitoring system based on cloud-edge-end collaboration, characterized in that: It includes a data acquisition module, an equipment analysis unit, a product analysis unit and a terminal display module. The data acquisition module is used to collect real-time equipment data of the production equipment corresponding to the product and real-time product data of the product, and send the real-time equipment data to the equipment analysis unit and send the real-time product data to the product analysis unit; The equipment analysis unit is used to analyze the operating status of the production equipment corresponding to the product, and the analysis generates an abnormal operation signal, a normal operation signal or a temperature abnormality signal and sends it to the terminal display module; the product analysis unit is used to analyze the production status of the same batch of products, and the analysis generates a product qualified signal or a product unqualified signal and sends it to the terminal display module; The terminal display module is used to display a product qualification signal, a product failure signal, an abnormal operation signal, a normal operation signal or an abnormal temperature signal.

2. According to claim 1, a digital production monitoring system based on cloud-edge-end collaboration is characterized in that: Real-time equipment data includes the real-time equipment temperature value of the production equipment corresponding to the product and the duration of each working condition. The working conditions include equipment operation, equipment failure and equipment shutdown. The duration of the working condition includes equipment operation time, equipment shutdown time and equipment failure time. Real-time product data is a collection of product appearance pictures of each product in the same batch of products.

3. According to claim 2, a digital production monitoring system based on cloud-edge-end collaboration is characterized in that: The collection process of product appearance atlas is as follows: Set the product to the corresponding ring light source, place the product in the center of the ring light source, and use eight-way control and time-sharing exposure for the ring light source to continuously capture eight images of the product; Adjust the irradiation angle of the ring light source so that it is perpendicular to the product surface; The product appearance pictures of the products when irradiated are collected in sequence to form a product appearance picture set of the corresponding products.

4. According to claim 2, a digital production monitoring system based on cloud-edge-end collaboration is characterized in that: The analysis process of the device analysis unit is specifically as follows: Obtain the real-time equipment temperature value, equipment operation time and equipment downtime of the production equipment corresponding to the product; Then, the operating parameters of the production equipment corresponding to the product are obtained, and the operating parameters include the maximum temperature threshold, the equipment standard temperature threshold, and the equipment temperature deviation threshold; If the real-time device temperature value is greater than or equal to the maximum temperature threshold, a temperature abnormality signal is generated; If the real-time device temperature value is less than the maximum temperature threshold, the real-time device temperature values ​​of the production equipment corresponding to the product at multiple time points are continuously recorded, and the real-time device temperature values ​​corresponding to the multiple time points are added and averaged to obtain the device average temperature value of the production equipment corresponding to the product; The equipment temperature deviation value of the corresponding production equipment of the product is calculated by the formula. The specific formula is as follows: Equipment temperature deviation value = equipment average temperature value - equipment standard temperature threshold; If the device temperature deviation value is greater than or equal to the device temperature deviation threshold, a temperature abnormality signal is generated; If the device temperature deviation value is less than the device temperature deviation threshold, proceed to the subsequent steps.

5. According to claim 4, a digital production monitoring system based on cloud-edge-end collaboration is characterized in that: The analysis process of the device analysis unit also includes: Set the operation cycle T of the production equipment corresponding to the product, count the duration of the working conditions of the production equipment corresponding to the product in each working condition during the operation cycle, and calculate the proportion of time the production equipment corresponding to the product is in each working condition through the formula. The specific formula is as follows: Operating time ratio = operating time / equipment operation cycle*100%. Operating time ratio includes operating time ratio, downtime ratio and fault time ratio. If the downtime ratio exceeds the downtime threshold or the fault ratio exceeds the fault threshold, an operation abnormality signal is generated; If the downtime ratio does not exceed the downtime threshold, and the fault ratio does not exceed the fault threshold, a normal operation signal is generated.

6. According to claim 2, a digital production monitoring system based on cloud-edge-end collaboration is characterized in that: The analysis process of the product analysis unit is as follows: Obtain a product appearance atlas of each product, and overlay multiple product appearance images in the product appearance atlas to form an appearance overlay image corresponding to the product; Perform crack and scratch detection on the product surface to generate product failure signal or product qualification signal.

7. A digital production monitoring system based on cloud-edge-end collaboration according to claim 6, characterized in that: The specific steps of crack and scratch detection are as follows: Obtain the pixel values ​​of all pixels in the product's corresponding appearance overlay image, and count the pixel values ​​of all pixels in the product's corresponding appearance overlay image to obtain the pixel value mode; If the pixel value of a pixel point in the appearance overlay image corresponding to the product is less than the pixel value mode, the corresponding pixel point is an abnormal pixel point, and the number of abnormal pixels is counted. When the number of abnormal pixels in the appearance overlay image corresponding to the product is greater than or equal to the first pixel point threshold, a product unqualified signal is generated; when the number of abnormal pixels in the appearance overlay image corresponding to the product is less than the first pixel point threshold, a product qualified signal is generated; If the pixel value of the pixel point in the appearance overlay image corresponding to the product is greater than or equal to the pixel value mode, a product qualified signal is generated.

8. The digital production monitoring system based on cloud-edge-end collaboration according to claim 6 is characterized in that: The crack and scratch detection steps also include: Obtain the pixel values ​​of all pixels in the appearance overlay image corresponding to the product, and record them as the first pixel values; Perform mean filtering on the appearance overlay image, randomly select a pixel point, calculate the mean of the corresponding pixel values ​​of all adjacent pixels of the pixel point, and use the mean as the pixel value of the current pixel point; According to the above steps, the pixel value corresponding to each pixel point in the appearance overlay image is replaced to obtain the mean filter image corresponding to the appearance overlay image; Subtract the appearance overlay image from the mean filter image to obtain a difference image, traverse all pixels in the difference image, and obtain the difference pixel values ​​corresponding to the pixels; If the absolute value of the differential pixel value is greater than or equal to the differential pixel threshold, the product is identified as a substandard product, and the number of substandard products in the same batch of products is counted. The number of substandard products is compared with the production volume to obtain the production qualification rate of the product. When the production qualification rate exceeds the preset production qualification rate, a product qualification signal is generated. When the production qualification rate does not exceed the preset production qualification rate, a product substandard signal is generated. If the absolute value of the differential pixel value is less than the differential pixel threshold, a product qualified signal is generated.

9. A digital production monitoring method based on cloud-edge-end collaboration is characterized in that: Utilizing the digital production monitoring system based on cloud-edge-end collaboration as described in any one of claims 1 to 8, the digital production monitoring method is specifically as follows: Step S100, the data acquisition module acquires real-time equipment data of the production equipment corresponding to the product and real-time product data of the product, and sends the real-time equipment data to the equipment analysis unit and sends the real-time product data to the product analysis unit; Step S200, the equipment analysis unit analyzes the operating status of the production equipment corresponding to the product, generates an abnormal operation signal, a normal operation signal or a temperature abnormality signal, and sends it to the terminal display module; Step S300, the product analysis unit analyzes the production status of the same batch of products, generates a product qualified signal or a product unqualified signal and sends it to the terminal display module; Step S400: the terminal display module displays a product qualification signal, a product failure signal, an abnormal operation signal, a normal operation signal or an abnormal temperature signal.

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