Pipe master batch production quality data management system

Abstract

The invention relates to the technical field of production management, and discloses a pipe master batch production quality data management system, which comprises a management period module for acquiring a standard duration valley value and a standard duration peak value and calculating a management period of a master batch production line, a data acquisition module for acquiring production quality data of the master batch production line, and a graph construction module. The quality point location module is used for constructing a quality point location map of the master batch production line in a management period, the early warning judgment module is used for judging whether a production quality early warning prompt is sent or not, and the optimization management module is used for formulating a corresponding optimization management strategy; according to the invention, the phenomenon of front and back adhesion caused by excessive approaching of the collected data on the timeline can be avoided, the limitation caused by single-moment collection is avoided, and fusion analysis operation in space and time can be carried out on the production quality of the master batch in different production stages and different time periods of the master batch production line; and the accuracy of a master batch production quality analysis result is improved.

Description

Technical Field

[0001] This invention relates to the field of production management technology, and more specifically, to a data management system for the production quality of pipe masterbatch. Background Technology

[0002] Pipe masterbatch is the core raw material for plastic pipes. The quality of the masterbatch directly determines the mechanical properties, weather resistance, and service life of the final pipe product. Since the production process of pipe masterbatch involves multiple processes such as raw material ratio, melt extrusion, granulation, and drying, any abnormal operation in any of these processes may lead to a decline in the production quality of the pipe masterbatch. Therefore, it is necessary to collect, analyze, and manage the production quality data of pipe masterbatch.

[0003] Reference patent application CN118278827A discloses a pipe production equipment management method and system based on plastic pipe quality inspection. This method manages production equipment in a factory based on quality inspection information by setting up an optimization model, a backtracking method, a preliminary adjustment method, and an optimized adjustment method. This improves the coordination between production equipment, thereby enhancing product quality. The optimization model, combined with defect factors, yields corresponding problem information, which is then investigated and resolved by staff to further improve product quality. This approach facilitates addressing defect factors in plastic pipe quality inspection information from multiple perspectives, thereby improving the overall quality of plastic pipe production. Existing data management systems typically employ random and dynamic data collection methods when managing and analyzing the quality of masterbatch production. This method is prone to issues such as short collection time spans between adjacent data points, leading to overlapping data and preventing the collection from covering different process stages and time periods of the masterbatch production line. Consequently, the collected data cannot be integrated and analyzed spatially and temporally, resulting in low accuracy in the analysis of masterbatch production quality and failing to accurately reflect the changes in masterbatch production quality throughout the entire production cycle.

[0004] In view of this, the present invention proposes a quality data management system based on pipe masterbatch production to solve the above problems. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: a pipe masterbatch production quality data management system, comprising: The management cycle module collects the valley and peak values ​​of the standard-reaching time of the masterbatch production line when the real-time operating power of each production equipment in the masterbatch production line is greater than or equal to the corresponding rated operating power, and calculates the management cycle of the masterbatch production line. The data acquisition module marks the first, middle, and last moments of the management cycle and collects production quality data of the masterbatch production line at the first, middle, and last moments. The production quality data includes drying compliance rate, temperature compliance rate, color compliance rate, and particle size compliance rate. The graphics construction module constructs a quality point map of the masterbatch production line during the management cycle, based on the standard of one point corresponding to one management cycle. The quality point map includes a drying point map, a temperature point map, a color point map, and a particle size point map, and identifies abnormal points in the quality point map. The early warning judgment module analyzes the quality level of the masterbatch production line, determines the quality level of the masterbatch production line in the management cycle, including high level, general level and low level, and determines whether to issue a production quality early warning prompt. The optimization management module, if it issues a production quality warning, identifies optimization data from the production quality data and formulates corresponding optimization management strategies.

[0006] Furthermore, the calculation steps for the management cycle are as follows: By querying the timestamps one by one, we can find the start-up time of A production equipment and the time when the real-time operating power of A production equipment first reaches the corresponding A rated operating power, thus obtaining A start-up times and A achievement times. The duration between A start times and A achievement times is recorded as the achievement duration, the minimum achievement duration is recorded as the achievement duration valley, and the maximum achievement duration is recorded as the achievement duration peak. The peak duration of compliance time will be compared with the remaining durations one by one. Comparing the duration of compliance, the calculation One compliance rate; After subtracting the peak duration of compliance from the trough duration of compliance, the difference is then compared with... The management cycle is calculated by multiplying the average of the compliance rates.

[0007] Furthermore, the steps for collecting the temperature compliance rate are as follows: At the first, middle, and last moments, images of the melting equipment from a top-down perspective are captured using an infrared thermal imager, resulting in three infrared images. Mark the pixel values ​​of all pixels in the three infrared images one by one, and record the pixels whose pixel values ​​are between the lower limit and the upper limit as the standard points. Count the number of all the standard points and record it as the standard value. The total number of pixels in the three infrared images is counted and recorded as the total value. The temperature compliance rate is calculated by comparing the compliance value with the total value.

[0008] Furthermore, the steps for collecting the temperature compliance rate are as follows: At the first, middle, and last moments, images of the melting equipment from a top-down perspective are captured using an infrared thermal imager, resulting in three infrared images. Mark the pixel values ​​of all pixels in the three infrared images one by one, and record the pixels whose pixel values ​​are between the lower limit and the upper limit as the standard points. Count the number of all the standard points and record it as the standard value. The total number of pixels in the three infrared images is counted and recorded as the total value. The temperature compliance rate is calculated by comparing the compliance value with the total value.

[0009] Furthermore, the steps for collecting data on color compliance rate are as follows: At the first, middle, and last moments, images of the melting equipment from a top-down perspective are captured by a camera to obtain three overhead images. Draw two diagonal lines in each of the three overhead images, and use these two diagonal lines as the basis for dividing the three overhead images into four regions. Convert the region image into a region grayscale image, mark the grayscale value of all pixels in the four region grayscale images one by one, and mark the pixels with grayscale values ​​less than the grayscale threshold as abnormal pixels. The number of abnormal pixels in the grayscale images of the four regions is counted one by one, and the number of abnormal pixels is compared with the total number of pixels in the grayscale images of the regions to obtain the region abnormality rate. The image anomaly rate of the overhead image is obtained by summing the region anomaly rates of the four grayscale images and averaging them. The color compliance rate is then calculated based on the maximum value of the image anomaly rate. The formula for calculating the color compliance rate is: ; In the formula, To ensure the color meets the standards, This represents the maximum value of the image anomaly rate.

[0010] Furthermore, the steps for collecting the particle size compliance rate are as follows: At the first, middle, and last time points, a unit weight of masterbatch product is collected from the masterbatch production line to obtain three sub-samples. The three subsamples are poured into the screening equipment and mixed. The screening equipment is kept running at its rated power to screen the subsamples until no more subsamples fall into the screening equipment within a unit of time. The screening of the subsamples is then stopped. After collecting and weighing the fallen sub-samples, the qualified weight is obtained. The qualified weight is then compared with the total weight of the three sub-samples to calculate the particle size compliance rate.

[0011] Furthermore, the steps for constructing the quality point map are as follows: According to the chronological order, the B management cycles of the masterbatch production line are sequentially numbered in ascending order. The number is used as the horizontal axis, and the drying compliance rate, temperature compliance rate, color compliance rate, and particle size compliance rate are used as the vertical axis to construct the first coordinate system, the second coordinate system, the third coordinate system, and the fourth coordinate system. Mark the drying compliance threshold on the vertical axis of the first coordinate system, draw the drying compliance line through the location of the drying compliance threshold, and mark the locations of B drying compliance rates on the first coordinate system to construct a drying point map; Mark the first temperature compliance threshold and the second temperature compliance threshold on the vertical axis of the second coordinate system. Draw the first temperature compliance line and the second temperature compliance line through the locations of the first temperature compliance threshold and the second temperature compliance threshold, respectively. Mark the locations of B temperature compliance rates on the second coordinate system to construct a temperature point map. Mark the color compliance threshold on the vertical axis of the third coordinate system, draw the color compliance line through the location of the color compliance threshold, and mark the locations of B color compliance rates on the third coordinate system to construct a color compliance point map. Mark the granularity compliance threshold on the vertical axis of the fourth coordinate system, draw the granularity compliance line through the location of the granularity compliance threshold, and mark the locations of B granularity compliance rates on the fourth coordinate system to construct a granularity point map.

[0012] Furthermore, the steps for identifying outlier locations are as follows: In the drying point map, points located below the drying standard line are marked as abnormal points; In the temperature point map, points located above the first temperature target line and below the second temperature target line are recorded as abnormal points. In the color point map, points located below the color compliance line are marked as abnormal points; In the particle size distribution map, points located below the particle size compliance line are marked as abnormal points.

[0013] Furthermore, the steps for determining the quality grade are as follows: According to the numbering from smallest to largest, the number of abnormal points in the drying point map, temperature point map, color point map and particle size point map in B management cycles is counted and recorded as the abnormal value. When the abnormal value is 0, the quality level is determined to be high. When the abnormal value is 1 or 2, the quality level is determined to be the general level; When the abnormal value is 3 or 4, the quality level is determined to be low.

[0014] Furthermore, the steps for determining whether to issue a production quality warning are as follows: When the quality level is determined to be high, it is determined that no production quality warning will be issued. When the quality level is determined to be low, a production quality warning notice will be issued. When the quality level is determined to be general, the two management cycles following the current management cycle are recorded as inspection cycles, and the quality level of the masterbatch production line in the two inspection cycles is identified. If the quality level of both inspection cycles is general, a production quality warning will be issued. If neither of the two inspection cycles has a quality grade of "general", then no production quality warning will be issued.

[0015] Further optimization management strategies include strategies to increase the rate of dryness compliance, the rate of temperature compliance, the rate of color compliance, and the rate of particle size compliance. The steps for developing an optimized management strategy are as follows: When the optimization data is the drying compliance rate, a strategy to increase the drying compliance rate is formulated. When the optimization data is the temperature compliance rate, a strategy to increase the temperature compliance rate is formulated. When the optimization data is the color compliance rate, a strategy is formulated to increase the color compliance rate. When the optimization data is the granularity compliance rate, a strategy to increase the granularity compliance rate is formulated.

[0016] The technical effects and advantages of the present invention, which is based on a pipe masterbatch production quality data management system: (1): This invention calculates the management cycle by collecting basic operating parameters, which can provide a time range limit for the data collection of the masterbatch production line, avoid the subsequent collection of production quality data with a long time span, resulting in low data relevance. By determining non-adjacent monitoring times within the management cycle, it can provide independent collection times for the subsequent collection of production quality data, avoiding the phenomenon of data being too close to each other on the timeline. At the same time, it can also achieve multi-point data collection effect at the start, middle and end times of the management cycle, thereby improving the universality of production quality data and avoiding the limitations caused by single-time collection.

[0017] (2): By collecting production quality data of the masterbatch production line in different production processes, the present invention can collect data on the impact of masterbatch production quality in different production stages in multiple dimensions, thereby realizing the data collection effect of the whole cycle of masterbatch production quality. Combined with the construction of quality point map and quality level analysis, the masterbatch production quality of different production stages and different time periods of the masterbatch production line can be analyzed in space and time, which improves the accuracy of the masterbatch production quality analysis results and provides real and effective guidance for the subsequent optimization management of the masterbatch production line. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of a module of a pipe masterbatch production quality data management system provided in Embodiment 1 of the present invention; Figure 2 This is a drying point location diagram provided in Embodiment 1 of the present invention; Figure 3 This is a temperature point map provided in Embodiment 1 of the present invention; Figure 4 This is a color dot map provided in Embodiment 1 of the present invention; Figure 5 This is a particle size distribution map provided in Embodiment 1 of the present invention; Figure 6 This is a flowchart illustrating a method for managing production quality data of pipe masterbatch, as provided in Embodiment 2 of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Example 1: Please refer to Figures 1-5 As shown in this embodiment, a pipe masterbatch production quality data management system includes: The management cycle module collects the basic operating parameters of the masterbatch production line under safe operating conditions and calculates the management cycle of the masterbatch production line. Safe operation status refers to the normal and safe stable state of all production equipment in the production line for producing and manufacturing pipe masterbatch products, so that all production equipment in the masterbatch production line can maintain the predetermined basic operating state, thereby ensuring the reliability of the overall operation status of the masterbatch production line. The various production equipment in the masterbatch production line includes, but is not limited to, drying equipment, melting equipment, filtering equipment, granulation equipment, cooling equipment, etc. These production equipment are used to provide support for the drying, melting, impurity removal, granulation, cooling and other processes of the masterbatch involved in pipe manufacturing.

[0021] In this embodiment, in order to determine whether the masterbatch production line is in a safe operating state, it is necessary to detect the real-time operating power of the production equipment such as drying equipment, melting equipment, filtering equipment, granulation equipment, and cooling equipment in the masterbatch production line. Only when the real-time operating power of the drying equipment, melting equipment, filtering equipment, granulation equipment, and cooling equipment in the masterbatch production line is greater than or equal to the corresponding rated operating power, it is determined that the masterbatch production line is in a safe operating state.

[0022] Basic operating parameters refer to the specific parameters required to complete a production quality sampling and analysis of the masterbatch production line under safe operating conditions. This allows for the representation of the multi-dimensional basic parameters of the masterbatch production line under safe operating conditions and provides a data basis for the specific calculation of the required time to complete a production quality sampling and analysis. Specifically, the basic operating parameters include the trough and peak durations of compliance. The minimum time to reach the calibrated operating power refers to the minimum time between the start-up of the production equipment in the masterbatch production line and the moment when the real-time operating power first reaches the calibrated operating power. The calibrated operating power is the power preset by the production equipment to meet the normal production needs of masterbatch, which ensures that the production equipment can achieve safe, reliable and stable masterbatch production operation; specifically, the calibrated operating power is customized according to the different parameters of the production equipment type.

[0023] Peak time to reach the target refers to the maximum time between the start-up of the production equipment in the masterbatch production line and the moment when the real-time operating power first reaches the rated operating power.

[0024] The management cycle refers to the specific time required to complete one production quality sampling, testing, and analysis on the masterbatch production line. It serves as the time basis for subsequent sampling, testing, and analysis of the masterbatch production quality on the masterbatch production line. Therefore, the management cycle is affected by the trough and peak of the compliance time. Specifically, the calculation steps for the management cycle are as follows: By querying the timestamps one by one, we can find the start-up time of A production equipment and the time when the real-time operating power of A production equipment first reaches the corresponding A rated operating power, thus obtaining A start-up times and A achievement times. The duration between A start times and A achievement times is recorded as the achievement duration, the minimum achievement duration is recorded as the achievement duration valley, and the maximum achievement duration is recorded as the achievement duration peak. The peak duration of compliance time will be compared with the remaining durations one by one. Comparing the duration of compliance, the calculation One compliance rate; The formula for calculating the compliance rate is: ; In the formula, For the first One compliance rate, =1,2,... , To achieve the target peak duration, For the first Each time period required to meet the standard; After subtracting the peak duration of compliance from the trough duration of compliance, the difference is then compared with... The management cycle is calculated by multiplying the average of the compliance rates. The formula for calculating the management cycle is: ; In the formula, For the management cycle, The minimum duration for achieving the target.

[0025] It should be noted that the calculated specific value of the management cycle can be used as the specific duration corresponding to the management cycle. Based on the duration corresponding to the management cycle, with the current moment as the starting point, and the duration corresponding to one management cycle as the time period for data detection and analysis, subsequent corresponding management operations are carried out on the quality of masterbatch production in the masterbatch production line.

[0026] The data acquisition module marks the monitoring time of the management cycle and collects the production quality data of the masterbatch production line during the management cycle based on the monitoring time. The monitoring time refers to the data collection time within the management cycle used to detect and analyze the specific situation of the masterbatch production quality in the masterbatch production line. It serves as the analysis object for multiple consecutive times within the management cycle, so that the data collected at the monitoring time can directly represent the specific situation of the masterbatch production quality within the management cycle. Specifically, the monitoring time includes the first time, the middle time, and the last time. In this embodiment, when marking the monitoring time, all times within the management cycle are marked one by one, and the first time, the time in the middle position, and the last time among all the times are recorded as the first time, the middle time, and the last time, respectively.

[0027] After marking the monitoring time, it is necessary to collect production quality data within the management cycle based on the monitoring time, so that the production quality data can represent the data that affects the quality of masterbatch production within the corresponding duration of a management cycle. Specifically, production quality data includes drying compliance rate, temperature compliance rate, color compliance rate, and particle size compliance rate.

[0028] The drying compliance rate is used to represent the real-time drying environment temperature of the raw materials in the masterbatch production line reaching the required value during the drying process. In other words, it represents the degree to which the moisture content of the raw materials meets the drying standards. The higher the drying compliance rate, the higher the production quality of the masterbatch. Specifically, when collecting the drying compliance rate, firstly, the real-time temperature value of the drying equipment is detected by a temperature sensor at all times within the management cycle. Then, the duration for which the real-time temperature value is greater than or equal to the calibrated temperature value is recorded as the temperature attainment time. Finally, the temperature attainment time is compared with the duration of the management cycle to calculate the drying compliance rate. The calibrated temperature value refers to the temperature value preset by the drying equipment to meet the normal drying process of the raw material masterbatch; specifically, the calibrated temperature value is set according to the actual drying requirements and the model parameters of the drying equipment.

[0029] The formula for calculating the drying compliance rate is: ; In the formula, To achieve the drying compliance rate, For the duration of the warming.

[0030] Temperature compliance rate is used to represent the real-time temperature of the molten masterbatch in the masterbatch production line that meets the required value during melting and processing. In other words, it represents the degree to which the real-time processing temperature of the molten masterbatch meets the standard. The higher the temperature compliance rate, the higher the production quality of the masterbatch. Specifically, the steps for collecting the temperature compliance rate are as follows: At the first, middle, and last moments, images of the melting equipment from a top-down perspective are captured using an infrared thermal imager, resulting in three infrared images. The pixel values ​​of all pixels in the three infrared images are marked one by one, and the pixels whose values ​​fall between the lower and upper limits of the pixel value are marked as qualified points. The total number of qualified points is counted and recorded as the qualified quantity value. The lower and upper limits of the pixel value refer to the pixel values ​​in the infrared image corresponding to the minimum and maximum temperature values ​​that the melting equipment is set in advance to meet the normal melting process of the masterbatch, thus providing a basis for the subsequent identification and marking of qualified points. Specifically, the lower and upper limits of the pixel value are obtained by averaging the minimum and maximum values ​​of a large number of historically recorded qualified points. The total number of pixels in the three infrared images is counted and recorded as the total value. The temperature compliance rate is calculated by comparing the compliance value with the total value. The formula for calculating the temperature compliance rate is: ; In the formula, For temperature compliance rate, To achieve the target value, This refers to the total value.

[0031] Color compliance rate is a numerical measure of the uniformity of color of the molten masterbatch during melting and processing in the masterbatch production line. It indicates the degree of compliance of the molten masterbatch. The higher the color compliance rate, the higher the production quality of the masterbatch. The steps for collecting data on color compliance rate are as follows: At the first, middle, and last moments, images of the melting equipment from a top-down perspective are captured by a camera to obtain three overhead images. Two diagonal lines are drawn for each of the three overhead images. Using these two diagonal lines as the basis for segmentation, the three overhead images are divided into four regions. By segmenting the images by diagonal lines, the overhead images can be broken down into smaller parts, reducing the burden of pixel identification and analysis in the regions. On the other hand, it also enables localized targeted identification and analysis of the overhead images, avoiding the inaccuracies that exist in overall macroscopic analysis. The region image is converted into a region grayscale image. The grayscale values ​​of all pixels in the four region grayscale images are marked one by one, and pixels with grayscale values ​​less than the grayscale threshold are marked as abnormal pixels. The grayscale threshold is the minimum grayscale value of a pixel that is not marked as an abnormal pixel, thus providing a numerical basis for the identification of abnormal pixels. Specifically, the grayscale threshold is obtained by collecting a large number of historical minimum grayscale values ​​of pixels that are not marked as abnormal pixels and then averaging them. The number of abnormal pixels in the grayscale images of the four regions is counted one by one, and the number of abnormal pixels is compared with the total number of pixels in the grayscale images of the regions to obtain the region abnormality rate. The formula for calculating the regional anomaly rate is: ; In the formula, For regional anomaly rate, This represents the number of abnormal pixels in the grayscale image of the region. This represents the total number of pixels in the grayscale image of the region. The image anomaly rate of the overhead image is obtained by summing the region anomaly rates of the four grayscale images and averaging them. The color compliance rate is then calculated based on the maximum value of the image anomaly rate. The formula for calculating the color compliance rate is: ; In the formula, To ensure the color meets the standards, This represents the maximum value of the image anomaly rate.

[0032] Particle size compliance rate is a numerical representation of the consistency of particle diameter in the masterbatch granules during the cutting and granulation process in the masterbatch production line. It can be used to represent the particle size quality of the masterbatch granules. The higher the particle size compliance rate, the higher the production quality of the masterbatch. Specifically, the steps for collecting particle size compliance rate data are as follows: At the first, middle, and last time points, a unit weight of masterbatch product is collected from the masterbatch production line to obtain three sub-samples. The three subsamples are poured into the screening equipment and mixed. The screening equipment is controlled to maintain its rated power and run continuously to screen the subsamples until no more subsamples fall into the screening equipment within a unit time. The screening of the subsamples is then stopped. The unit time is the maximum interval during which the masterbatch product does not fall when the screening equipment is normally screening the masterbatch product, thus providing a time basis for the screening operation of the screening equipment. After collecting and weighing the fallen sub-samples, the qualified weight is obtained, and the qualified weight is compared with the total weight of the three sub-samples to calculate the particle size compliance rate. The formula for calculating the particle size compliance rate is: ; In the formula, To achieve the particle size compliance rate, For acceptable weight, This represents the total weight of the three subsamples.

[0033] The graph construction module, based on production quality data and graph construction criteria, constructs a quality point map of the masterbatch production line and identifies abnormal points in the quality point map. After obtaining the production quality data, a quality point map of the masterbatch production line in different management cycles can be constructed based on the production quality data. This allows the quality point map to reflect the specific production status of the masterbatch in different management cycle periods and serve as a basis for judging the quality of the masterbatch in different management cycles. When constructing the quality point map, in order to ensure that the points in the quality point map can accurately represent each management cycle, it is necessary to ensure that each point in the quality point map corresponds to an independent management cycle. Therefore, the drawing needs to be carried out under the constraints of the image construction criteria to achieve the precise indication effect of each management cycle of the masterbatch production line.

[0034] Specifically, the image construction principle is: one management cycle corresponds to one location; this achieves a one-to-one correspondence between management cycles and locations.

[0035] The quality point map includes a drying point map, a temperature point map, a color point map, and a particle size point map; The drying point map is used to show the distribution of points corresponding to the drying compliance rate of the masterbatch production line in each management cycle. The temperature point map is used to show the distribution of points corresponding to the temperature compliance rate of the masterbatch production line in each management cycle. The color point map is used to show the distribution of points corresponding to the color compliance rate of the masterbatch production line in each management cycle. The particle size point map is used to show the distribution of points corresponding to the particle size compliance rate of the masterbatch production line in each management cycle.

[0036] Specifically, the steps for constructing the quality point map are as follows: According to the chronological order, the B management cycles of the masterbatch production line are sequentially numbered in ascending order. The number is used as the horizontal axis, and the drying compliance rate, temperature compliance rate, color compliance rate, and particle size compliance rate are used as the vertical axis to construct the first coordinate system, the second coordinate system, the third coordinate system, and the fourth coordinate system. Mark the drying compliance threshold on the vertical axis of the first coordinate system, draw the drying compliance line through the location of the drying compliance threshold, and mark the locations of B drying compliance rates on the first coordinate system to construct a drying point map; the drying compliance threshold refers to the minimum drying compliance rate that maintains the masterbatch production quality at a high level, and is used to provide a lower limit for the drying process. Mark the first temperature compliance threshold and the second temperature compliance threshold on the vertical axis of the second coordinate system. Draw the first temperature compliance line and the second temperature compliance line through the locations of the first temperature compliance threshold and the second temperature compliance threshold, respectively. Mark the locations of B temperature compliance rates on the second coordinate system to construct a temperature point map. The first temperature compliance threshold and the second temperature compliance threshold refer to the maximum and minimum values ​​of the temperature compliance rate at which the masterbatch production quality is maintained at a high level. They are used to provide numerical upper and lower limits for the melting process. Mark the color compliance threshold on the vertical axis of the third coordinate system, draw the color compliance line through the location of the color compliance threshold, and mark the points where the color compliance rate is B on the third coordinate system to construct the color compliance point map; the color compliance threshold refers to the minimum value of the color compliance rate when the quality of the masterbatch production is kept at a high level, and is used to provide a lower limit for the impurity removal process. Mark the particle size compliance threshold on the vertical axis of the fourth coordinate system. Draw a particle size compliance line through the location of the particle size compliance threshold, and mark the points where B particle size compliance rates are located on the fourth coordinate system to construct a particle size point map. The particle size compliance threshold refers to the minimum particle size compliance rate that maintains the masterbatch production quality at a high level, and is used to provide a numerical lower limit for the granulation process.

[0037] In this embodiment, multiple sets of production quality data collected from the masterbatch production line over 10 management cycles are used to calculate the drying compliance rate, temperature compliance rate, color compliance rate, and particle size compliance rate for the 10 management cycles. The 10 management cycles are numbered 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 in chronological order. The aforementioned quality point map construction steps are then used to construct drying point maps, temperature point maps, color point maps, and particle size point maps for the masterbatch production line over the 10 management cycles. Figure 2 This is a map showing the locations of the drying points. Figure 3 This is a temperature point map. Figure 4 This is a color point map. Figure 5 This is a particle size distribution map.

[0038] After the quality point map is constructed, it can represent the various quality indicators of the masterbatch in different management cycles of the masterbatch production line. By judging whether the point is an abnormal point by the location of different points in the quality point map. It should be noted that abnormal points refer to the points located above and below the corresponding compliance lines on the drying point map, temperature point map, color point map, and particle size point map, thus enabling the representation of the masterbatch production quality of the masterbatch production line in different dimensions and from different perspectives during different management cycles.

[0039] Specifically, the steps for identifying abnormal locations are as follows: Analyze the positional relationship between the points in the drying point map, temperature point map, color point map, and particle size point map and the corresponding compliance line; In the drying point map, points located below the drying standard line are marked as abnormal points; In the temperature point map, points located above the first temperature target line and below the second temperature target line are recorded as abnormal points. In the color point map, points located below the color compliance line are marked as abnormal points; In the particle size distribution map, points located below the particle size compliance line are marked as abnormal points.

[0040] It should be noted that after identifying abnormal points, it is necessary to classify and summarize the abnormal points with the same number in the drying point map, temperature point map, color point map, and particle size point map. This will allow for a comprehensive representation of the specific situation of the masterbatch production quality in the same management cycle and ensure the synchronous summary of the corresponding data within the same management cycle.

[0041] The early warning judgment module analyzes the quality level of the masterbatch production line, determines the quality level of the masterbatch production line in the management cycle, and determines whether to issue a production quality early warning prompt. After identifying the anomaly points, it is necessary to analyze the actual production quality of the masterbatch in each management cycle based on the anomaly points, and then analyze and determine the quality level of the masterbatch production line based on the production quality of the masterbatch. Specifically, the quality grades include high, medium, and low. A high quality grade indicates that the masterbatch produced by the masterbatch production line is of high quality and meets the high-quality production requirements. A medium quality grade indicates that the masterbatch produced by the masterbatch production line is of average quality and may not meet the high-quality production requirements. A low quality grade indicates that the masterbatch produced by the masterbatch production line is of low quality and does not meet the high-quality production requirements.

[0042] The steps for determining the quality grade are as follows: According to the numbering from smallest to largest, the number of abnormal points in the drying point map, temperature point map, color point map and particle size point map in B management cycles is counted and recorded as the abnormal value. When the abnormal value is 0, it means that there are no abnormal parameters in the masterbatch production line during the management cycle. At this time, the production quality of the masterbatch product is high, and the quality level of the masterbatch production line is determined to be high level. When the abnormal value is 1 or 2, it indicates that the number of abnormal parameters in the masterbatch production line is moderate during the management cycle. At this time, the production quality of the masterbatch product is average, and the quality level of the masterbatch production line is determined to be average. When the abnormal value is 3 or 4, it indicates that the number of abnormal parameters in the masterbatch production line is relatively large during the management cycle. At this time, the production quality of the masterbatch product is low, and the quality level of the masterbatch production line is determined to be low.

[0043] After determining the quality level of the masterbatch production line, it is necessary to use the specific results of the quality level in each management cycle to determine whether to issue a production quality warning. This will enable timely and accurate warnings when serious negative situations occur in the masterbatch production line, and provide a basis for subsequent optimization and improvement of the production quality of the masterbatch production line. Specifically, the steps for determining whether to issue a production quality warning are as follows: When the quality level of the masterbatch production line is determined to be high, the quality of the masterbatch produced by the masterbatch production line is relatively high, and it is determined that no production quality warning will be issued. When the quality level of the masterbatch production line is determined to be low, the quality of the masterbatch produced by the masterbatch production line is low, and a production quality warning is issued. When the quality level of the masterbatch production line is determined to be general, the quality of the masterbatch produced by the masterbatch production line within the management cycle is general. Then, the two management cycles following the management cycle are recorded as inspection cycles, and the quality level of the masterbatch production line in the two inspection cycles is identified. If two pending inspection cycles have both of the quality grade being "general", and the masterbatch production line has experienced three consecutive management cycles of "general" grade, it indicates that the quality of the masterbatch produced by the masterbatch production line is low, and a production quality warning is issued. If there are no two inspection cycles with the same quality level (general grade), and the masterbatch production line does not have three consecutive management cycles with the general grade, then it is determined that no production quality warning will be issued.

[0044] It should be noted that issuing a production quality warning indicates a negative phenomenon in the masterbatch production line, meaning the quality of the masterbatch products produced by the production line is low, and the production line needs to be optimized and improved. Conversely, issuing a positive warning indicates that the quality of the masterbatch products produced by the production line is high, and no optimization or improvement is required.

[0045] The optimization management module, if a production quality warning is issued, will identify optimization data from the production quality data and formulate corresponding optimization management strategies. After issuing a production quality warning, it is necessary to identify the negative data that causes the low quality of the masterbatch produced by the masterbatch production line, and record the negative data as optimization data, so as to serve as the data basis for subsequent optimization and improvement measures for the masterbatch production line. In this embodiment, when optimized data appears in the production quality data, it means that abnormal points have appeared in the drying point map, temperature point map, color point map and particle size point map of the masterbatch production line within the management cycle. At this time, the production quality data corresponding to the abnormal point is optimized data. Specifically, the optimized data includes the drying compliance rate, temperature compliance rate, color compliance rate, and / or particle size compliance rate corresponding to abnormal points in the drying point map, temperature point map, color point map, and particle size point map.

[0046] After identifying the optimization data, it is necessary to provide a basis for subsequent optimization and improvement measures for the masterbatch production line based on the specific type of optimization data, so as to formulate an optimization management strategy that can improve the quality of masterbatch produced by the masterbatch production line. Specifically, the optimization management strategies include strategies to increase the drying compliance rate, temperature compliance rate, color compliance rate, and particle size compliance rate. These optimization management strategies can correspond to the drying process, melting process, impurity removal process, and granulation process of the masterbatch production line within the management cycle, thereby optimizing and improving the production equipment of each process in the masterbatch production line, and thus improving the final production quality of the masterbatch.

[0047] The steps for developing an optimized management strategy are as follows: When the optimization data is the drying compliance rate, it is necessary to optimize and improve the drying process and drying equipment of the masterbatch production line, and then formulate a strategy to increase the drying compliance rate. When the optimization data is the temperature compliance rate, it is necessary to optimize and improve the melting process and melting equipment of the masterbatch production line, and then formulate a strategy to increase the temperature compliance rate. When the optimization data is the color compliance rate, it is necessary to optimize and improve the filtration process and filtration equipment of the masterbatch production line, and then formulate a strategy to increase the color compliance rate. When the optimization data is the particle size compliance rate, it is necessary to optimize and improve the granulation process and granulation equipment of the masterbatch production line, and then formulate a strategy to increase the particle size compliance rate.

[0048] It should be noted that after the corresponding optimization management strategy is formulated, the production management personnel will use the optimization management strategy as a basis to optimize and improve each process and production equipment in the masterbatch production line, so as to achieve the optimization and improvement effect corresponding to the optimization management strategy and ultimately achieve the production effect of high-quality masterbatch products. For example, when a strategy to increase the drying compliance rate is formulated, the drying environment temperature of the drying equipment can be increased or decreased so that the drying environment temperature can be kept as close as possible to the value corresponding to the preset optimal drying temperature of the raw material of the masterbatch. This improves the drying efficiency of the drying equipment on the raw material of the masterbatch, reduces the moisture content in the raw material of the masterbatch as much as possible, and lays the foundation for the drying process in order to improve the quality of the masterbatch production in the future.

[0049] Example 2: Please refer to Figure 6 As shown, parts not described in detail in this embodiment are described in Embodiment 1. A method for managing production quality data based on pipe masterbatch is provided, implemented based on a management system for production quality data based on pipe masterbatch, including: S01: When the real-time operating power of each production equipment in the masterbatch production line is greater than or equal to the corresponding rated operating power, collect the valley value and peak value of the standard-reaching time of the masterbatch production line, and calculate the management cycle of the masterbatch production line. S02: Mark the first, middle, and last moments of the management cycle, and collect production quality data of the masterbatch production line at the first, middle, and last moments; S03: Using one point corresponding to one management cycle as the standard, construct a quality point map of the masterbatch production line in the management cycle, and identify abnormal points in the quality point map; S04: Perform quality level analysis on the masterbatch production line, determine the quality level of the masterbatch production line in the management cycle, and determine whether to issue a production quality warning; if a production quality warning is issued, proceed to S05; if no production quality warning is issued, repeat S04. S05: Identify optimization data from production quality data and formulate corresponding optimization management strategies.

[0050] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A data management system for the production quality of pipe masterbatch, characterized in that, include: The management cycle module collects the valley and peak values ​​of the standard-reaching time of the masterbatch production line when the real-time operating power of each production equipment in the masterbatch production line is greater than or equal to the corresponding rated operating power, and calculates the management cycle of the masterbatch production line. The data acquisition module marks the first, middle, and last moments of the management cycle and collects production quality data of the masterbatch production line at the first, middle, and last moments. The production quality data includes drying compliance rate, temperature compliance rate, color compliance rate, and particle size compliance rate. The graphics construction module constructs a quality point map of the masterbatch production line during the management cycle, based on the standard of one point corresponding to one management cycle. The quality point map includes a drying point map, a temperature point map, a color point map, and a particle size point map, and identifies abnormal points in the quality point map. The early warning judgment module analyzes the quality level of the masterbatch production line, determines the quality level of the masterbatch production line in the management cycle, including high level, general level and low level, and determines whether to issue a production quality early warning prompt. The optimization management module, if it issues a production quality warning, identifies optimization data from the production quality data and formulates corresponding optimization management strategies.

2. The pipe masterbatch production quality data management system according to claim 1, characterized in that, The steps for calculating the management cycle are as follows: By querying the timestamps one by one, we can find the start-up time of A production equipment and the time when the real-time operating power of A production equipment first reaches the corresponding A rated operating power, thus obtaining A start-up times and A achievement times. The duration between A start times and A achievement times is recorded as the achievement duration, the minimum achievement duration is recorded as the achievement duration valley, and the maximum achievement duration is recorded as the achievement duration peak. The peak duration of compliance time will be compared with the remaining durations one by one. Comparing the duration of compliance, the calculation One compliance rate; After subtracting the peak duration of compliance from the trough duration of compliance, the difference is then compared with... The management cycle is calculated by multiplying the average of the compliance rates.

3. The pipe masterbatch production quality data management system according to claim 2, characterized in that, The steps for collecting temperature compliance rate data are as follows: At the first, middle, and last moments, images of the melting equipment from a top-down perspective are captured using an infrared thermal imager, resulting in three infrared images. Mark the pixel values ​​of all pixels in the three infrared images one by one, and record the pixels whose pixel values ​​are between the lower limit and the upper limit as the standard points. Count the number of all the standard points and record it as the standard value. The total number of pixels in the three infrared images is counted and recorded as the total value. The temperature compliance rate is calculated by comparing the compliance value with the total value.

4. The pipe masterbatch production quality data management system according to claim 3, characterized in that, The steps for collecting data on color compliance rate are as follows: At the first, middle, and last moments, images of the melting equipment from a top-down perspective are captured by a camera to obtain three overhead images. Draw two diagonal lines in each of the three overhead images, and use these two diagonal lines as the basis for dividing the three overhead images into four regions. Convert the region image into a region grayscale image, mark the grayscale value of all pixels in the four region grayscale images one by one, and mark the pixels with grayscale values ​​less than the grayscale threshold as abnormal pixels. The number of abnormal pixels in the grayscale images of the four regions is counted one by one, and the number of abnormal pixels is compared with the total number of pixels in the grayscale images of the regions to obtain the region abnormality rate. The image anomaly rate of the overhead image is obtained by summing the region anomaly rates of the four grayscale images and averaging them. The color compliance rate is then calculated based on the maximum value of the image anomaly rate. The formula for calculating the color compliance rate is: ； In the formula, To ensure the color meets the standards, This represents the maximum value of the image anomaly rate.

5. A data management system for pipe masterbatch production quality according to claim 4, characterized in that, The steps for collecting particle size compliance rate data are as follows: At the first, middle, and last time points, a unit weight of masterbatch product is collected from the masterbatch production line to obtain three sub-samples. The three subsamples are poured into the screening equipment and mixed. The screening equipment is kept running at its rated power to screen the subsamples until no more subsamples fall into the screening equipment within a unit of time. The screening of the subsamples is then stopped. After collecting and weighing the fallen sub-samples, the qualified weight is obtained. The qualified weight is then compared with the total weight of the three sub-samples to calculate the particle size compliance rate.

6. A data management system for pipe masterbatch production quality according to claim 5, characterized in that, The steps for constructing a mass point map are as follows: According to the chronological order, the B management cycles of the masterbatch production line are sequentially numbered in ascending order. The number is used as the horizontal axis, and the drying compliance rate, temperature compliance rate, color compliance rate, and particle size compliance rate are used as the vertical axis to construct the first coordinate system, the second coordinate system, the third coordinate system, and the fourth coordinate system. Mark the drying compliance threshold on the vertical axis of the first coordinate system, draw the drying compliance line through the location of the drying compliance threshold, and mark the locations of B drying compliance rates on the first coordinate system to construct a drying point map; Mark the first temperature compliance threshold and the second temperature compliance threshold on the vertical axis of the second coordinate system. Draw the first temperature compliance line and the second temperature compliance line through the locations of the first temperature compliance threshold and the second temperature compliance threshold, respectively. Mark the locations of B temperature compliance rates on the second coordinate system to construct a temperature point map. Mark the color compliance threshold on the vertical axis of the third coordinate system, draw the color compliance line through the location of the color compliance threshold, and mark the locations of B color compliance rates on the third coordinate system to construct a color compliance point map. Mark the granularity compliance threshold on the vertical axis of the fourth coordinate system, draw the granularity compliance line through the location of the granularity compliance threshold, and mark the locations of B granularity compliance rates on the fourth coordinate system to construct a granularity point map.

7. A data management system for pipe masterbatch production quality according to claim 6, characterized in that, The steps for identifying abnormal locations are as follows: In the drying point map, points located below the drying standard line are marked as abnormal points; In the temperature point map, points located above the first temperature target line and below the second temperature target line are recorded as abnormal points. In the color point map, points located below the color compliance line are marked as abnormal points; In the particle size distribution map, points located below the particle size compliance line are marked as abnormal points.

8. A data management system for pipe masterbatch production quality according to claim 7, characterized in that, The steps for determining the quality grade are as follows: According to the numbering from smallest to largest, the number of abnormal points in the drying point map, temperature point map, color point map and particle size point map in B management cycles is counted and recorded as the abnormal value. When the abnormal value is 0, the quality level is determined to be high. When the abnormal value is 1 or 2, the quality level is determined to be the general level; When the abnormal value is 3 or 4, the quality level is determined to be low.

9. A data management system for pipe masterbatch production quality according to claim 8, characterized in that, The steps for determining whether to issue a production quality warning are as follows: When the quality level is determined to be high, it is determined that no production quality warning will be issued. When the quality level is determined to be low, a production quality warning notice will be issued. When the quality level is determined to be general, the two management cycles following the current management cycle are recorded as inspection cycles, and the quality level of the masterbatch production line in the two inspection cycles is identified. If the quality level of both inspection cycles is general, a production quality warning will be issued. If there are no two inspection cycles where the quality level is both at the general level, then no production quality warning will be issued.

10. A data management system for pipe masterbatch production quality according to claim 9, characterized in that, Optimization management strategies include strategies to increase the rate of achieving drying targets, strategies to increase the rate of achieving temperature targets, strategies to increase the rate of achieving color targets, and strategies to increase the rate of achieving particle size targets. The steps for developing an optimized management strategy are as follows: When the optimization data is the drying compliance rate, a strategy to increase the drying compliance rate is formulated. When the optimization data is the temperature compliance rate, a strategy to increase the temperature compliance rate is formulated. When the optimization data is the color compliance rate, a strategy is formulated to increase the color compliance rate. When the optimization data is the granularity compliance rate, a strategy to increase the granularity compliance rate is formulated.

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