CN117642707A

CN117642707A - Data processing method and device, data display method and device, equipment and medium

Info

Publication number: CN117642707A
Application number: CN202280002068.6A
Authority: CN
Inventors: 杨堃; 温晶; 陈嘉丰; 徐晓冬; 何德材; 吴建民; 王洪
Original assignee: BOE Technology Group Co Ltd; Beijing Zhongxiangying Technology Co Ltd
Current assignee: BOE Technology Group Co Ltd; Beijing Zhongxiangying Technology Co Ltd
Priority date: 2022-06-30
Filing date: 2022-06-30
Publication date: 2024-03-01
Also published as: WO2024000356A1

Abstract

The invention relates to a data processing method and device, a data display method and device, equipment and medium. According to the method and the device, the plurality of measurement data of each display panel to be detected are obtained, so that whether the target measurement data for indicating the plurality of optical display panels has multi-group characteristics and/or whether the target measurement data obeys normal distribution data form information is determined based on the target parameter values determined by the plurality of measurement data, and therefore the control limit determination of the target control chart can be realized based on the data form information, the determined control limit can meet the real data form of the data, and the accuracy of the determined control limit is improved.

Description

Data processing method and device, data display method and device, equipment and medium

Technical Field

The present invention relates to the field of computer technology and the field of display panel manufacturing, and in particular, to a data processing method and apparatus, a data display method and apparatus, a device, and a medium.

Background

It is well known that display panels (e.g., liquid crystal panels) are the heart of a liquid crystal display, and the quality of the display panel directly affects the functional parameters and display effects of the display, such as color, brightness, contrast, viewing angle, etc. However, the production steps of the display panel are complicated, and a failure of one step may greatly affect the production of the display panel, so a method is needed to monitor the production process of the display panel and discover the abnormal situation in the production process in time.

In the related art, the production process of the display panel is monitored mainly by a statistical process control (Statistical Process Control, SPC) tool. When monitoring the production process of the display panel through the SPC, it is necessary to first select a product to be monitored this time and then determine product characteristics based on the selected product, so as to determine a control chart or a control limit based on the product characteristics.

However, in the production context of high efficiency and high productivity in the current display panel production process, the product is not produced by a single path, but is produced by a plurality of production lines, a plurality of devices and a plurality of device units, and the data forms of the display panels produced by different production paths may be greatly different, so that the accuracy of the control chart or the control limit determined by the above process is poor, and further, the monitoring effect of the product monitoring process is poor.

Disclosure of Invention

The invention provides a data processing method and device, a data display method and device, equipment and medium, and aims to solve the defects in the related art.

According to a first aspect of an embodiment of the present invention, there is provided a data processing method, including:

acquiring a plurality of measurement data of each display panel to be detected;

Determining data morphology information indicating whether the target measurement data of the plurality of display panels has a multi-group characteristic or not by determining target parameter values based on the plurality of measurement data, and/or indicating whether the target measurement data of the plurality of display panels obeys normal distribution or not, the target measurement data of each display panel being determined based on the plurality of measurement data of the display panels;

based on the data morphology information, a control limit of a target control chart is determined, wherein the target control chart is used for indicating the statistical data characteristics of each display panel, and the control limit is used for indicating the upper limit value and/or the lower limit value of the statistical data characteristics of the display panels meeting the production requirements.

In some embodiments, the target parameter values include first target parameter values for indicating a ratio of sum of squares of deviations to degrees of freedom between and within groups of target measurement data packets;

determining a target parameter value based on the plurality of measurement data, comprising:

for any display panel, determining the average value of a plurality of measurement data of the display panel as target measurement data of the display panel;

grouping target measurement data of a plurality of display panels according to time periods to obtain a plurality of groups of target measurement data;

Determining the sum of inter-group variation and the sum of single-point squares of multiple groups of target measurement data;

a first target parameter value is determined based on the sum of the inter-group variations, the sum of the single-point squares, and the sum.

In some embodiments, the target parameter values include second target parameter values for indicating probabilities that target measurement data of the plurality of display panels obey a normal distribution;

and carrying out normal verification on the target measurement data of the display panels to obtain a second target parameter value.

In some embodiments, the data morphology information is determined based on target parameter values, the target parameter values including first target parameter values for indicating a ratio of a sum of squares of deviations to degrees of freedom between and within groups of target measurement data packets and/or second target parameter values for indicating probabilities that target measurement data of the plurality of display panels obey a normal distribution;

determining data morphology information by determining target parameter values based on a plurality of measurement data, comprising:

Determining that the data morphology information indicates that the target measurement data of the plurality of display panels has a multi-group characteristic if the first target parameter value is greater than a first set threshold;

determining that the data morphology information indicates that the target measurement data of the plurality of display panels obeys a normal distribution when the first target parameter value is less than or equal to a first set threshold value and the second target parameter value is greater than or equal to a second set threshold value;

in the case where the first target parameter value is less than or equal to the first set threshold value and the second target parameter value is less than the second set threshold value, it is determined that the data morphology information indicates that the target measurement data of the plurality of display panels does not follow a normal distribution.

In some embodiments, the control limits of the target control graph are determined based on the data morphology information, including any one of:

under the condition that the data form information indicates that target measurement data of a plurality of display panels have multi-group characteristics, determining a set number of target measurement data as one group to obtain a plurality of groups of target measurement data, respectively calculating process capability indexes of each group of target measurement data, and determining a control limit of a target control chart based on the plurality of groups of target measurement data of which the process capability indexes meet set conditions;

If the data form information indicates that the target measurement data of the display panels have a multi-group characteristic, respectively calculating a process capability index of the target measurement data of each batch if the display panels correspond to the batches, and determining a control limit of the target control chart based on a plurality of groups of target measurement data of which the process capability index meets a set condition;

determining a control limit of a target control chart based on the plurality of target measurement data satisfying the normal distribution in a case where the data morphology information indicates that the target measurement data of the plurality of display panels obeys the normal distribution;

in the case where the data morphology information indicates that the target measurement data of the plurality of display panels does not follow the normal distribution, the plurality of target measurement data is converted into data that follows the normal distribution, and the control limit of the target control map is determined based on the converted data.

In some embodiments, the target control map is determined based on a product characteristic of the display panel, the product characteristic being used to indicate whether the measured data of the display panel is metering type data or counting type data;

the determining process of the target control chart comprises the following steps:

determining a target control chart based on the number of measurement point bits of the display panel and the inter-group difference test result under the condition that the product characteristics of the display panel indicate that the measurement data of the display panel are metering data;

In the case where the product characteristics of the display panel indicate that the measurement data of the display panel is count-type data, a target control chart is determined based on the existence of defective products and product defects in the display panel.

In some embodiments, the target control map is determined based on the number of measurement point bits of the display panel and the inter-group difference test result, including any one of the following:

when the number of measured point bits of the display panel is larger than a third set threshold value and the inter-group difference test result indicates that the inter-group difference does not exist, taking the average value-range control chart as a target control chart;

when the number of measured point bits of the display panel is larger than a third set threshold value and the inter-group difference test result indicates that the inter-group difference exists, taking the mean value-moving range-range control chart as a target control chart;

when the number of the measured point digits of the display panel is smaller than or equal to the third set threshold value, if the number of the measured point digits is the fourth set threshold value, taking the single-value-moving range control chart as a target control chart;

when the number of measurement point digits of the display panel is smaller than or equal to a third set threshold value, if the number of measurement point digits is not a fourth set threshold value and the inter-group difference test result indicates that there is no inter-group difference, taking the mean-standard deviation control chart as a target control chart;

And when the number of measurement point digits of the display panel is smaller than or equal to the third set threshold value, if the number of measurement point digits is not the fourth set threshold value and the inter-group difference detection result indicates that the inter-group difference exists, taking the mean-moving range-standard deviation control chart as a target control chart.

In some embodiments, determining the target control map based on the presence of rejects and product defects in the display panel includes:

when the defective products exist in the display panel, if the number of the defective products is constant, taking the numerical control drawing of the defective products as a target control drawing;

if the number of defective products is not constant in the case where defective products exist in the display panel, the defective rate control map is used as a target control map;

if the display panel has no unqualified products but has product defects, taking the unqualified numerical control drawing as a target control drawing if the product defects exist in the set area;

when there is no defective product in the display panel, but there is a display panel with a product defect, if the product defect is not present in the set area, the numerical control drawing of defective product per unit product is used as the target control drawing.

In some embodiments, the method further comprises:

in response to receiving the target instruction, determining a product model of the display panel to be detected based on the target instruction;

product characteristics of the display panel are determined based on the product model.

In some embodiments, the display panel to be detected is sampled from a plurality of candidate display panels according to a preset sampling interval time;

the determining process of the target sampling interval time comprises the following steps:

determining a first target probability value based on an upper control limit, a lower control limit, a center point after offset, and a historical standard deviation of the historical measurement data;

determining a desired risk value based on the first target probability value, the initial sampling interval time, the hourly output of the historical measurement data, and the failure rate and the first probability for each set time period;

and adjusting the initial sampling time interval based on the expected risk value to obtain the target sampling interval time.

In some embodiments, the method further comprises:

partitioning a plurality of measurement points in each partition of the display panel based on the plurality of measurement data to obtain partition results of the plurality of measurement points, so as to respectively process the measurement data of the measurement points in different partitions based on the partition results.

In some embodiments, the display panels are processed by a plurality of production devices, each display panel corresponds to a production information storage structure, the production information storage structure is used for storing device information of the production device for processing the corresponding display panel, the target control chart comprises data points corresponding to the display panels, and the data points are used for displaying the device information of the production device for processing the display panel in the target control chart after being triggered.

In some embodiments, the method further comprises:

and determining a plurality of display panels processed by each production device based on the device information recorded in the production information storage structure of each display panel, and respectively recording the product information of the plurality of display panels processed by each production device into a production device management model, wherein the production device management model is used for recording the display panels processed by different production devices.

According to a second aspect of an embodiment of the present invention, there is provided a data display method, including:

displaying a product management interface;

obtaining the product model of the display panel to be detected through a product management interface, and determining a target control chart based on the product model, wherein the target control chart is used for indicating the statistical data characteristics of each display panel;

In response to a submitting operation at the product management interface, displaying a target control chart and a control limit, wherein the target control chart is used for indicating the statistical data characteristics of each display panel, and the control limit is used for indicating the upper limit value and/or the lower limit value of the statistical data characteristics of the display panels meeting the production requirements;

the control limit is determined based on data form information, the data form information is determined based on target parameter values determined by a plurality of measured data of each display panel to be detected, the data form information is used for indicating whether the target measured data of the plurality of display panels has multi-group characteristics, and/or the data form information is used for indicating whether the target measured data of the plurality of display panels obeys normal distribution.

In some embodiments, the product management interface includes a product model setting control and a control diagram selection control;

the method comprises the steps of obtaining the product model of the display panel to be detected through a product management interface, determining a target control chart based on the product model, and comprising the following steps:

obtaining a product model through a product model setting control;

displaying at least one candidate control chart on the control chart selection control based on the product characteristics corresponding to the product model;

And in response to a selection operation on any candidate control graph, determining the selected candidate control graph as the target control graph.

In some embodiments, the product management interface further includes a point location number setting control;

the method further comprises the steps of:

acquiring the number of measurement point bits set by the point quantity setting control;

and displaying at least one candidate control chart on the control chart selection control based on the product characteristics corresponding to the product model and the acquired measuring point digits.

In some embodiments, the product management interface further includes a zone setting control;

the method further comprises the steps of:

and responding to the triggering operation of the partition setting control, displaying a partition management interface, wherein the partition management interface is used for partitioning a plurality of measurement points in the display panel to obtain partition results of the measurement points, and respectively processing the measurement data of the measurement points in different partitions based on the partition results.

In some embodiments, the product management interface further comprises at least one of:

the data acquisition management control is used for setting the type of the measurement data to be acquired and the data description information of the measurement data;

the device management control is used for acquiring device information of production devices of the display panel;

The data filtering control is used for setting conditions and data filtering modes which are met by the data to be filtered;

and the timing function setting control is used for setting the cycle period of the data acquisition and calculation process.

In some embodiments, the product management interface further includes a control limit management control and/or a specification limit management control;

the control limit management control is used for adjusting the determined control limit;

the specification limit management control is used for adjusting the determined specification limit;

wherein the determined specification limit is determined based on the determined control limit.

In some embodiments, the target control chart includes data points corresponding to each display panel, the display panels are processed by a plurality of production devices, each display panel corresponds to a production information storage structure, and the production information storage structure is used for storing device information of the production device for processing the corresponding display panel;

the method further comprises the steps of:

responding to the triggering operation of any data point in the displayed target control chart, and acquiring equipment information of generating equipment for processing the display panel from a production information storage structure of the display panel corresponding to the data point;

And displaying the acquired equipment information.

According to a third aspect of embodiments of the present invention, there is provided a data processing apparatus comprising:

the acquisition module is used for acquiring a plurality of measurement data of each display panel to be detected;

a determining module for determining data morphology information indicating whether the target measurement data of the plurality of display panels has a multi-group characteristic by the target parameter value determined based on the plurality of measurement data, and/or the data morphology information indicating whether the target measurement data of the plurality of display panels obeys a normal distribution, the target measurement data of each display panel being determined based on the plurality of measurement data of the display panels;

the determining module is further configured to determine, based on the data morphology information, a control limit of a target control chart, where the target control chart is used to indicate a statistical data feature of each display panel, and the control limit is used to indicate an upper limit value and/or a lower limit value of the statistical data feature of the display panel that meets the production requirement.

A determination module, when configured to determine a target parameter value based on the plurality of measurement data, is configured to:

A determining module for, when determining data morphology information by determining target parameter values based on a plurality of measurement data,:

In some embodiments, the determining module, when used to determine the control limit of the target control graph based on the data morphology information, is to use any one of:

the determining module is also used for determining a target control chart based on the product characteristics of the display panel;

a determining module, when used for determining the target control chart based on the product characteristics of the display panel, for:

In some embodiments, the determining module, when used for determining the target control chart based on the measurement point number of bits of the display panel and the inter-group difference test result, is used for any one of the following:

When the number of the measurement point digits of the display panel is smaller than or equal to the third set threshold value, if the number of the measurement point digits is not the fourth set threshold value and the inter-group difference test result indicates that the inter-group difference does not exist, taking the mean value-standard deviation control chart as a target control chart;

In some embodiments, the determining module, when configured to determine the target control map based on the presence of rejects and product defects in the display panel, is configured to:

In some embodiments, the determining module is further configured to determine a product model of the display panel to be detected based on the target instruction in response to receiving the target instruction;

and the determining module is also used for determining the product characteristics of the display panel based on the product model.

In some embodiments, the apparatus further comprises:

The processing module is used for partitioning the plurality of measurement points in each partition of the display panel based on the plurality of measurement data to obtain partition results of the plurality of measurement points, so as to respectively process the measurement data of the measurement points in different partitions based on the partition results.

In some embodiments, the determining module is further configured to determine a plurality of display panels processed by each production apparatus based on the device information recorded in the production information storage structure of each display panel, and record the product information of the plurality of display panels processed by each production apparatus into a production apparatus management model, where the production apparatus management model is used to record display panels processed by different production apparatuses.

According to a fourth aspect of an embodiment of the present invention, there is provided a data display apparatus including:

the display module is used for displaying a product management interface;

the processing module is used for acquiring the product model of the display panel to be detected through the product management interface, determining a target control chart based on the product model, and indicating the statistical data characteristics of each display panel by the target control chart;

the display module is also used for responding to the submitting operation on the product management interface, displaying a target control chart and a control limit, wherein the target control chart is used for indicating the statistical data characteristics of each display panel, the target control chart is displayed with the control limit, and the control limit is used for indicating the upper limit value and/or the lower limit value of the statistical data characteristics of the display panels meeting the production requirement;

the processing module is used for acquiring the product model of the display panel to be detected through the product management interface and determining a target control chart based on the product model, and is used for:

obtaining a product model through a product model setting control;

in response to a selection operation on any one of the candidate control charts, the selected candidate control chart is determined as the target control chart.

the processing module is also used for acquiring the number of measurement point bits set by the point number setting control;

and the display module is also used for displaying at least one candidate control chart on the control chart selection control based on the product characteristics corresponding to the product model and the acquired measuring point digits.

the display module is also used for responding to the triggering operation of the partition setting control, displaying a partition management interface, wherein the partition management interface is used for partitioning a plurality of measurement points in the display panel to obtain partition results of the measurement points, and respectively processing the measurement data of the measurement points in different partitions based on the partition results.

The processing module is also used for responding to the triggering operation of any data point in the displayed target control diagram and acquiring the equipment information of the generating equipment for processing the display panel from the production information storage structure of the display panel corresponding to the data point;

and the display module is also used for displaying the acquired equipment information.

According to a fifth aspect of embodiments of the present invention, there is provided a computing device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the operations performed by the data processing method provided in the first aspect and any one of the embodiments of the first aspect when the computer program is executed.

According to a sixth aspect of embodiments of the present invention, there is provided a computing device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the operations performed by the data display method provided in the second aspect and any one of the embodiments of the second aspect, when the computer program is executed by the processor.

According to a seventh aspect of embodiments of the present invention, there is provided a computer-readable storage medium having stored thereon a program which, when executed by a processor, implements the operations performed by the data processing method provided in the first aspect and any one of the embodiments of the first aspect.

According to an eighth aspect of the embodiments of the present invention, there is provided a computer-readable storage medium having stored thereon a program which, when executed by a processor, implements the operations performed by the data display method provided in the second aspect and any one of the embodiments of the second aspect.

According to a ninth aspect of embodiments of the present invention, there is provided a computer program product comprising a computer program which, when executed by a processor, performs the operations performed by the data processing method provided in the first aspect and any one of the embodiments of the first aspect.

According to a tenth aspect of embodiments of the present invention, there is provided a computer program product comprising a computer program which, when executed by a processor, performs the operations performed by the data display method provided in the second aspect and any one of the embodiments of the second aspect.

According to the method and the device, the plurality of measurement data of each display panel to be detected are obtained, so that whether the target measurement data for indicating the plurality of optical display panels has multi-group characteristics and/or whether the target measurement data obeys normal distribution data form information is determined based on the target parameter values determined by the plurality of measurement data, and therefore the control limit determination of the target control chart can be realized based on the data form information, the determined control limit can meet the real data form of the data, and the accuracy of the determined control limit is improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention as claimed.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.

Fig. 1 is a flow chart illustrating a data processing method according to an embodiment of the present invention.

Fig. 2 is a schematic diagram of a sampling rule according to an embodiment of the present invention.

Fig. 3 is a schematic diagram illustrating a sampling rule case according to an embodiment of the present invention.

Fig. 4 is a schematic diagram of measurement data of a display panel according to an embodiment of the present invention.

Fig. 5 is a schematic view showing a partition of a display panel according to an embodiment of the present invention.

Fig. 6 is a schematic diagram of grouping results of a Scan1 group according to an embodiment of the present invention.

Fig. 7 is a schematic diagram of grouping results of a Scan2 group according to an embodiment of the present invention.

Fig. 8 is a schematic diagram of grouping results of a Scan3 group according to an embodiment of the present invention.

Fig. 9 is a schematic diagram of grouping results of a Scan4 group according to an embodiment of the present invention.

Fig. 10 is a schematic diagram showing grouping results in a display panel surface according to an embodiment of the present invention.

Fig. 11 is a schematic diagram illustrating a process of determining data morphology information according to an embodiment of the present invention.

Fig. 12 is a schematic diagram showing a process of determining a target control map according to an embodiment of the present invention.

Fig. 13 is a schematic diagram showing a determination process of another target control map according to an embodiment of the present invention.

Fig. 14 is a schematic diagram showing a control limit calculation process according to an embodiment of the present invention.

Fig. 15 is a schematic diagram of a control diagram according to an embodiment of the present invention.

Fig. 16 is a flowchart illustrating a data processing method according to an embodiment of the present invention.

Fig. 17 is a schematic view showing a process of a display panel according to an embodiment of the present invention.

Fig. 18 is a schematic diagram showing a production information storage structure according to an embodiment of the present invention.

Fig. 19 is a schematic diagram illustrating an information entry process according to an embodiment of the present invention.

Fig. 20 is a flowchart illustrating a data display method according to an embodiment of the present invention.

FIG. 21 is an interface diagram illustrating a product management interface according to an embodiment of the present invention.

FIG. 22 is an interface diagram illustrating another product management interface according to an embodiment of the invention.

Fig. 23 is a schematic diagram showing a display form of a target control map according to an embodiment of the present invention.

FIG. 24 is a schematic diagram of an information viewing interface, according to an embodiment of the invention.

FIG. 25 is a schematic diagram illustrating a partition setting interface, according to an embodiment of the present invention.

FIG. 26 is a schematic diagram illustrating another product management interface according to an embodiment of the invention.

Fig. 27 is a block diagram of a data processing apparatus according to an embodiment of the present invention.

Fig. 28 is a block diagram of a data display device according to an embodiment of the present invention.

Fig. 29 is a schematic structural diagram of a computing device according to an embodiment of the present invention.

Fig. 30 is a schematic structural diagram of a computing device according to an embodiment of the present invention.

Detailed Description

Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the invention. Rather, they are merely examples of apparatus and methods consistent with aspects of the invention as detailed in the accompanying claims.

The invention provides a data processing method, which is used for determining control limits aiming at data forms in the production process of a thin film transistor liquid crystal display (Thin Film Transistor Liquid Crystal Display, TFT-LCD) and an Organic Light-Emitting Diode (OLED) or an Organic Light-Emitting semiconductor, so that the accuracy of the determined control limits is improved, a scientific method is provided for setting the control limits of SPC, and the accuracy degree of calculation of the control limits after data classification can be improved.

In addition, the invention also provides a data display method, which is used for determining the product model required to be subjected to data analysis from the product produced in the TFT-LCD industry production process and obtaining the product characteristics of the product corresponding to the product model, so that the display of the control chart and the control limit is realized based on the selected product model and the product characteristics, and the quality monitoring of the product production process can be realized by related technicians according to the displayed control chart and the control limit.

The data processing method and the data display method may be executed by a computing device, where the computing device may be a terminal device, such as a desktop computer, a portable computer, a smart phone, a tablet computer, or the like, and optionally, the computing device may also be a server, such as a server, a plurality of servers, a server cluster, or the like.

After the application scenario of the present invention is introduced, technical terms related to the present invention are introduced below.

Statistical process control (Statistical Process Control, SPC): is a quality management tool for monitoring the production process of products by applying the statistical principle.

SPC data morphology classification (SPC Data Form Classify) method: the data morphology is divided into multiple groups, normal, non-normal, etc. by an algorithm.

Mean-shift Range-Range (Xbar-Moving Range-Range, xbar-MR-R) control diagram: the method is an innovative SPC control chart method, and combines the mean value, the movement range and the range control chart to carry out alarm management and analysis.

Mean-shift Range-standard deviation (Xbar-Moving Range-Std, xbar-MR-S) control diagram: the method is an innovative SPC control chart method, and alarm management and analysis are carried out by combining the mean value, the movement range and the standard deviation.

Process capability index (Complex Process Capability Index, CPK): is an indicator of the process capability of modern enterprises.

Process capability: refers to the quality capability exhibited by a process under fixed production conditions and stable control.

Change process capability index (Complex Process Capability Index Between Within, CPK-BW): the method is an improved calculation method for CPK, and the management of the inter-group difference is increased, so that the sensitivity of CPK is higher.

Control limit: the method is to apply a mathematical statistics method to control limit of quality characteristic values obtained by adopting control diagram analysis on historical data so as to analyze and judge whether the state of a working procedure meets the requirement of a specification. The control limits may include an upper control limit (Upper Control Limit, UCL) and a lower control limit (Lower Control Limit, LCL), among others.

Specification limit: is specified by a customer or company, is a capability requirement for a process, and is generally wider than a control limit, otherwise, cannot meet a quality target. The specification limits may include an Upper Specification Limit (USL) and a Lower Specification Limit (LSL), among others.

Analysis of variance (Analysis of Variance, anova): the method is used for checking whether the average values of two or more samples are equal or not, and whether the difference between the average values is obvious or not is confirmed by judging the sizes of the inter-group variation and the intra-group variation of the total variation.

After technical terms related to the present invention are introduced, a scheme of the data processing method provided by the present invention is described below.

Referring to fig. 1, fig. 1 is a flowchart illustrating a data processing method according to an embodiment of the present invention, as shown in fig. 1, the method includes:

Step 101, acquiring a plurality of measurement data of each display panel to be detected.

The display panel may be a liquid crystal panel, alternatively, the display panel may be of other types, and the specific type of the display panel is not limited in the present invention.

It should be noted that, for any display panel, a plurality of measurement points may be disposed on the display panel, and one measurement data may be acquired at each measurement point, so that a plurality of measurement data may be acquired from one display panel.

The measurement data may be various types of data, for example, the measurement data may be a backlight value obtained after a voltage is applied to the display panel, or the measurement data may be alignment accuracy (Alignment Inspection, AI), alternatively, the measurement data may be other types of data, and the specific type of the measurement data is not limited in the present invention.

Step 102, determining data morphology information by determining a target parameter value based on the plurality of measurement data, the target parameter value being used for indicating data characteristics of target measurement data of the plurality of display panels, the target measurement data of each display panel being determined based on the plurality of measurement data of the display panels, the data morphology information being used for indicating whether the target measurement data of the plurality of display panels has a multi-group characteristic, and/or the data morphology information being used for indicating whether the target measurement data of the plurality of display panels obeys a normal distribution.

It should be noted that, for any display panel, the display panel may correspond to a plurality of measurement data, so that the target measurement data of the display panel may be determined based on the plurality of measurement data corresponding to the display panel.

And 103, determining a control limit of a target control chart based on the data form information, wherein the target control chart is used for indicating the statistical data characteristics of each display panel, and the control limit is used for indicating the upper limit value and/or the lower limit value of the statistical data characteristics of the display panels meeting the production requirements.

The statistical data can be mean value, range, movement range, standard deviation and the like, and the specific type of the statistical data is not limited by the invention. Accordingly, the statistical data features may be the data features of the statistical data such as mean, range, moving range, standard deviation, etc.

Having described the basic implementation of the data processing method provided by the present invention, various alternative embodiments of the data processing method are described below.

It should be noted that, since a plurality of different types of display panels may be produced on a production apparatus, it is necessary to determine which type of display panel is to be processed before step 101, so that the processing can be performed based on the corresponding type of display panel.

In some embodiments, prior to step 101, the method may further comprise the steps of:

and 100, responding to the received target instruction, and determining the product model of the display panel to be detected based on the target instruction.

The target instruction may be triggered by the user through the computing device, and the target instruction may carry a product model, so that the target instruction may instruct the computing device to use a display panel corresponding to the product model as a display panel to be detected.

After the product model of the display panel to be processed is determined through the above process, the computing device can obtain the produced display panel with the product model as each display panel to be detected, so that each display panel to be detected can be processed later.

It should be noted that, since the number of display panels of the same product type may be greater in the actual production process, if all the produced display panels of the product type are processed, the processing pressure of the computing device may be too great, and thus, in more possible implementation manners, after determining the product type of the display panel to be detected, the produced display panel of the product type may be used as a candidate display panel, so that sampling may be performed from multiple candidate display panels according to the target sampling interval time, so as to obtain the display panel to be detected.

The target sampling interval time may be obtained by adjusting the initial sampling interval time in advance, and in a possible implementation manner, the adjustment of the initial sampling interval time may be achieved by the following steps to obtain the target sampling interval time:

step one, determining a first target probability value based on an upper control limit, a lower control limit, a center point after offset and a historical standard deviation of historical measurement data.

It should be noted that, before the present data processing process is performed, the computing device may have processed the display panel produced by the product model in an earlier time, that is, the computing device may have determined, based on the history measurement data, data such as an upper control limit, a lower control limit, a post-offset center point, and a history standard deviation of the history measurement data, so that, during the present data processing process or before the present data processing process, the upper control limit, the lower control limit, the post-offset center point, and the history standard deviation of the measured history measurement data may be acquired, so that the determination of the first target probability value is performed based on the acquired data. The central point may be a central point of data distribution obtained by theoretical calculation based on historical measurement data, however, in an actual use process, the central point may deviate, so that in order to ensure accuracy of a data processing process, the central point after deviation may be obtained, and thus a subsequent calculation process is known by the central point after deviation.

In one possible implementation, the first target probability value may be determined by the following function:

p1= (norm.s.dist ((UCL-post-offset center point)/history standard deviation, 1) -norm.s.dist ((LCL-post-offset center point)/history standard deviation, 1))

Wherein, P1 is a first target probability (or called undiscovered probability), which may be used to indicate a probability of undiscovered defective products in the display panel produced in the set period of time, and norm.s.dist is a standard normal distribution function in table (Excel) software.

It should be noted that the set period may be a period whose duration satisfies the initial sampling interval time.

And step two, determining an expected risk value based on the first target probability value, the initial sampling interval time, the hourly output of the historical measurement data, the reject ratio and the first probability in each set time period.

In addition, during the history processing, the computing device may also determine, based on the history measurement data, an hourly output of the history measurement data and a failure rate and a first probability (or occurrence probability) in each set period, so that during the data processing, the hourly output of the history measurement data and the failure rate and the first probability in each set period may be directly obtained, so that the determination of the desired risk value may be performed based on the hourly output and the failure rate and the first probability in each set period.

The first probability is used for indicating the probability of defective products of the display panel produced in the set time period.

Referring to fig. 2, fig. 2 is a schematic diagram of a sampling rule according to an embodiment of the present invention, as shown in fig. 2, taking a case where a set period includes a first set period (i.e., a period in which an offset that may occur in H is 0 to 1), a second set period (i.e., a period in which an offset that may occur in H is 1 to 2), and a third set period (i.e., a period in which an offset that may occur in H is greater than 2), where the first set period has a failure rate of a, the first set period has a failure rate of D, the discovery probability has G, the second set period has a failure rate of B, the first set period has a failure rate of E, the discovery probability has H, and the third set period has a failure rate of C, the first set period has a failure rate of F, and the discovery probability has I, where the desired risk can be determined by the following formula:

desired risk = UPH H (a-G) +b E (1-H) +c F (1-I)

It should be noted that, the undiscovered probability can be calculated by a formula of "undiscovered probability=1-found probability", the sum of the three D, E, F values is 1, the found probability can be f (n, h, k) function, n is the sample size, h is the initial sampling time interval, k is the standard deviation control multiple, and n, f, k can be set according to the requirement.

And thirdly, adjusting the initial sampling time interval based on the expected risk value to obtain the target sampling interval time.

It should be noted that, a risk threshold may be preset, after the expected risk value is determined in the second step, the determined expected risk value may be compared with the risk threshold, and under the condition that the expected risk value is smaller than the risk threshold, the initial sampling interval time may be adjusted to obtain the target sampling interval time.

Alternatively, different expected risk values may correspond to different adjustment steps, so when the initial sampling interval time is adjusted based on the expected risk value, the adjustment step may be reduced on the basis of the initial sampling interval time according to the adjustment step corresponding to the expected risk value, so as to achieve adjustment of the initial sampling interval time, thereby obtaining the target sampling interval time.

The foregoing is merely an exemplary manner of adjusting the initial sampling interval time based on the desired risk value, and in many possible implementations, other manners of adjusting the initial sampling interval time may be used, and the present invention is not limited to what manner is specifically adopted.

Taking the alignment precision as an example of the display panel of the measurement data, values of the sample size (i.e., n), the initial sampling interval time (i.e., h), the standard deviation control multiple (i.e., k), the offset, the first probability (i.e., occurrence probability), the history center point, the history standard deviation, the reject ratio, the upper control limit, and the lower control limit obtained in the first step and the second step may be referred to as fig. 3, fig. 3 is a case schematic diagram of a sampling rule according to an embodiment of the present invention, and by using the obtained values, the values of the first step and the second step may be used to calculate the values of the discovery probability, the undiscovered probability (i.e., the first target probability), the discovery risk, the undiscovered risk, and the desired risk according to the indication of the first step and the second step, so that the desired risk value and the risk threshold (i.e., the custom risk value) may be compared in order to implement adjustment of the initial sampling interval time.

The above process is described by taking the determination of the preset sampling interval time based on the historical data as an example, alternatively, the data processing process may also be to process the display panel of the product model for the first time, where the initial sampling interval time may be directly used as the target sampling interval time without adjusting the initial sampling interval time.

Through the above process, the determination of the target sampling interval time can be realized, so that the display panel of the corresponding product model can be sampled based on the determined target sampling interval time, and the sampled display panel is used as the display panel to be detected, so that a plurality of measurement data of each display panel to be detected can be acquired through the step 101.

When acquiring a plurality of measurement data of any display panel, a plurality of measurement points may be set in the display panel, so as to acquire measurement data of each measurement point, so as to obtain a plurality of measurement data of the display panel.

Taking a display panel to be detected as a grid halftone film (HGM) as an example, 72 measurement points may be disposed in the display panel, each measurement point may include a plurality of pixel points, when obtaining measurement data of the 72 measurement points, 11664 measurement data may be extracted, that is, 162 measurement data may be extracted on each measurement point, for any measurement point, the 162 measurement data extracted from the measurement point may be averaged, so that a result obtained by the averaging is taken as measurement data of the measurement point, and so on, 72 measurement data corresponding to the 72 measurement points are obtained as a plurality of measurement data of the display panel.

Referring to fig. 4, fig. 4 is a schematic diagram of measurement data of a display panel according to an embodiment of the present invention, and as shown in fig. 4, fig. 4 is an example of a display panel to be detected, where the display panel may include 72 measurement points, each of which corresponds to one measurement data, so that 72 measurement data as shown in fig. 4 may be obtained.

After the plurality of measurement data of the display panel are acquired through the above-described process, the data morphology information may be determined through the target parameter value determined based on the plurality of measurement data through step 102.

In some embodiments, for step 102, when determining the data morphology information by determining the target parameter value based on the plurality of measurement data, the target parameter value may be determined based on the plurality of measurement data first, and then the data morphology information may be determined based on the target parameter value.

Wherein the target parameter value may be used to indicate a data characteristic of target measurement data for a plurality of display panels, the target measurement data for each display panel being determined based on the plurality of measurement data for the display panel.

Next, a process of determining target measurement data of each display panel will be described.

In one possible implementation, for any display panel, a mean value of a plurality of measurement data of the display panel may be determined as target measurement data of the display panel, that is, the plurality of measurement data of the display panel may be averaged, so that the determined mean value is taken as target measurement data of the display panel.

The above process is described by taking the case of directly processing a plurality of measurement points of the display panel as an example, and in general, the display panel produced by one production process may be divided into a plurality of screens to be sold, so that data in the display panel may be processed in a partitioned manner when the data is processed.

For example, in one possible implementation, a plurality of measurement points in the display panel may be partitioned based on the plurality of measurement data, so as to obtain partition results of the plurality of measurement points, so as to respectively process the measurement points in different partitions based on the partition results.

Referring to fig. 5, fig. 5 is a schematic diagram illustrating a partition of a display panel according to an embodiment of the present invention, and as shown in fig. 5, the display panel may be divided into 8 partitions A1, A2, A3, A4, B1, B2, B3, and B4, so that data in the 8 partitions are processed, respectively. In addition, all of the 8 partitions can be sold as a single display panel after shipment.

For example, when determining the target measurement data of the display panel based on the above-mentioned partition result, the average value of the measurement data in each partition may be determined for each partition, and then the average values corresponding to the plurality of partitions may be averaged to obtain a final average value calculation result as the target measurement data of the display panel.

In order to facilitate the processing, a plurality of partitions may be handled as one large partition (or group), and as shown in fig. 5, 2 partitions may be handled as one group, for example, partition A1 and partition A2 may be handled as a Scan1 group, partition B1 and partition B2 may be handled as a Scan2 group, partition A3 and partition A4 may be handled as a Scan3 group, and partition B3 and partition B4 may be handled as a Scan4 group, thereby obtaining 4 groups.

After the division of the groups is achieved through the above process, the processing of the measurement data can be achieved based on the groups later, for example, when the target measurement data of each display panel to be detected is determined, for any display panel, the average value of a plurality of measurement data of each group in the display panel can be calculated respectively, so that the average value of the measurement data corresponding to the plurality of groups is averaged, and the final averaged result is used as the target measurement data of the display panel.

It should be noted that, even though the measurement points in the same partition are possible to be processed by different production units of the same production device, even be processed by different production devices, in more possible implementation manners, more refined partitions (or called groups) may be performed on the measurement points in each partition of the display panel based on multiple measurement data, so as to obtain more refined partition results, and measurement data of the measurement points in different groups may be respectively processed based on the more refined partition results (i.e. the group results).

In some embodiments, a clustering algorithm such as the K-Means method may be employed in more refined (i.e., grouped) partitions of the plurality of measurement points in each partition of the display panel.

When the K-Means method is adopted to implement grouping, the grouping result can be verified based on the inter-group variance (R Square), and the grouping result can be determined to be reasonable when the inter-group variance is greater than or equal to a set variance threshold. The difference between groups can be calculated by a single factor analysis of variance (Anova) method.

Alternatively, the set difference threshold may be any value, for example, the set difference threshold may be 0.8 (i.e. 80%), or the set difference threshold may be another value, which is not limited in the present invention.

Taking the HGA shown in fig. 4 as an example of a display panel to be detected, in combination with the partition mode shown in fig. 5, each Scan group may be further grouped by applying K-Means according to actual engineering conditions, and the R Square result in each Scan group is guaranteed to be 80% or more, in general, the number of groupings by applying K-Means is equal to or greater than 2, and the grouping result of the Scan1 group may be referred to fig. 6, and fig. 6 is a schematic diagram of the grouping result of one Scan1 group shown in the embodiment of the present invention, as shown in fig. 6, the Scan1 group may be divided into 2 groupings; as for the grouping result of the Scan2 group, referring to fig. 7, fig. 7 is a schematic diagram of the grouping result of a Scan2 group, which is shown in fig. 7, where the Scan2 group may be divided into 2 groups according to an embodiment of the present invention; as for the grouping result of the Scan3 group, referring to fig. 8, fig. 8 is a schematic diagram of the grouping result of a Scan3 group, which is shown in fig. 8, and the Scan3 group may be divided into 3 groups according to an embodiment of the present invention; the grouping result of the Scan4 group may be referred to in fig. 9, and fig. 9 is a schematic diagram illustrating the grouping result of the Scan4 group according to an embodiment of the present invention, and as shown in fig. 9, the Scan4 group may be divided into 2 groups.

Based on this, the display panel in-plane shown in fig. 4 may be divided into 9 groups, and a schematic view of the 9 groups may be referred to in fig. 10, and fig. 10 is a schematic view of a group result in the display panel in accordance with an embodiment of the present invention.

After the in-plane grouping of the display panels is achieved through the above process, the processing of the measurement data can be achieved based on the grouping result, for example, when determining the target measurement data of each display panel to be detected, for any display panel, the display panel may include a plurality of groups, each group may include a plurality of groups, so that the average value of the plurality of measurement data of each group in the display panel may be calculated respectively, for any group, the average value of the measurement data of the plurality of groups included in the group is averaged again to obtain the average value of the measurement data of each group, and then the average value of the measurement data of the plurality of groups is averaged again, and the finally averaged result is taken as the target measurement data of the display panel.

By the method for processing the measured data according to the partition modes with different degrees, the finally determined target measured data can be more in line with the actual measured data condition of the display panel, so that the accuracy of the determined target measured data is improved, a good data basis is provided for the subsequent data processing process, and the accuracy of the subsequent data processing process is further ensured.

In any of the above modes, the determination of the target measurement data of each display panel may be realized, so that the determination of the target parameter value may be performed based on the target measurement data of a plurality of display panels.

Wherein the target parameter values may include first target parameter values that may be used to indicate a ratio of a sum of squares of deviations to degrees of freedom between groups and within groups of target measurement data packets, and/or second target parameter values that may be used to indicate probabilities that the target measurement data of the plurality of display panels obey a normal distribution.

Next, a process of determining the first target parameter value and the second target parameter value will be described, respectively.

In some embodiments, the determining of the first target parameter value may comprise the steps of:

step one, grouping target measurement data of a plurality of display panels according to time periods to obtain a plurality of groups of target measurement data.

For example, the target measurement data of a plurality of display panels generated within a period of time may be taken as one total data set (for example, may be denoted as a total data set M), and M target measurement data in total in the data set M may be divided into N groups (denoted as N1, N2, N3) at equal times, thereby obtaining a plurality of groups of target measurement data, wherein the number of target measurement data included in each group of data may be N1, N2, N3, respectively.

And step two, determining inter-group variation sum and single-point square sum of multiple groups of target measurement data.

In one possible implementation, the sum of the inter-group variations of the sets of target measurement data may be determined by the following equation (1):

wherein SSB represents the sum of inter-group variations, avg represents the average, M is a data set composed of a plurality of sets of target measurement data, the target measurement data in the data set M may be divided into N sets, and the number of the target measurement data included in each set of data is N.

Further, a single-point sum-of-squares sum of the sets of target measurement data may be determined by the following equation (2):

wherein SST represents a single-point sum of squares, avg represents averaging, M is a data set composed of a plurality of sets of target measurement data, and M target measurement data are total in the data set M.

And thirdly, determining a first target parameter value based on the sum of the inter-group variations and the sum of single-point squares.

In one possible implementation, the determination of the first target parameter value may be achieved by the following formulas (3) to (5):

F＝MS(SB)/MS(SE) (3)

MS(SB)＝SST-SSB/(m-(N-1)) (4)

MS(SE)＝SSB/(N-1) (5)

wherein F is a first target parameter value, MS (SE) represents a first parameter, MS (SB) represents a second parameter, SSB represents a sum of inter-group variations, SST represents a sum of single-point squares, and the plurality of sets of target measurement data include m target measurement data in total, which are divided into N sets.

In other embodiments, the determining of the second target parameter value may be:

In one possible implementation, an Anderson-Darling normalization check calculation method may be employed to obtain the second target parameter value (which may be denoted as P value).

After the first target parameter value and the second target parameter value are obtained through the above-mentioned process, the determination of the data morphology information can be realized based on the obtained first target parameter value and second target parameter value.

In some embodiments, for step 103, in determining the data morphology information based on the target parameter values, may include any of the following:

in one possible implementation, the determining the data morphology information indicates that the target measurement data of the plurality of display panels has a multi-group characteristic in case the first target parameter value is greater than the first set threshold.

The first target parameter may be denoted as F, and the first set threshold may be 2.65, that is, in the case where F >2.65, it may be determined that the target measurement data of the plurality of display panels has a multi-group characteristic, and correspondingly, in the case where F is less than or equal to 2.65, it may be determined that the target measurement data of the plurality of display panels has a single-group characteristic.

In another possible implementation, in a case where the first target parameter value is less than or equal to the first set threshold value and the second target parameter value is greater than or equal to the second set threshold value, it is determined that the data morphology information indicates that the target measurement data of the plurality of display panels obeys a normal distribution.

Wherein the second target parameter may be denoted as P, and the second set threshold may be 0.05, that is, in the case where F is less than or equal to 2.65 and P >0.05, it may be determined that the target measurement data of the plurality of display panels obeys the normal distribution.

In another possible implementation, in a case where the first target parameter value is less than or equal to the first set threshold value and the second target parameter value is less than the second set threshold value, determining the data morphology information indicates that the target measurement data of the plurality of display panels does not follow a normal distribution.

When the second target parameter is recorded as P and the second set threshold is 0.05, if F is less than or equal to 2.65 and P is less than 0.05, it may be determined that the target measurement data of the plurality of display panels does not follow normal distribution, or that the target measurement data of the plurality of display panels follows abnormal distribution.

As described above, the process of determining the data form information may refer to fig. 11, and fig. 11 is a schematic diagram illustrating a process of determining the data form information according to an embodiment of the present invention, as shown in fig. 11, when determining the data form information, it may follow that a multi-group check is performed on data to determine whether the data has a multi-group characteristic, and when determining that the data does not have a multi-group characteristic (or that the data has a single-group characteristic), a normal check is performed on the data to determine whether the data has a single normal characteristic.

In addition, when it is determined that the data does not have the multi-group characteristic (or the data has the single-group characteristic), the data may be subjected to the trend verification first to determine whether the data has the trend characteristic, and when it is determined that the data does not have the trend characteristic (that is, the data are independent of each other), the data is subjected to the normal verification to determine whether the data has the single normal characteristic.

After the data morphology information is determined through the above procedure, the determination of the control limit may be performed through step 104. Wherein, the control limits can be displayed in the target control chart, so that a relevant technician can intuitively observe whether the quality of each product meets the requirements.

It should be noted that the target control chart may be predetermined, for example, the corresponding target control chart may be determined based on product characteristics of the display panel, and display panels with different product characteristics may correspond to different target control charts. The product characteristics may be used to indicate that the measurement data of the display panel is metering data or counting data, the metering data may be continuous random variables, and the counting data (including counting and counting) may be discrete random variables.

In some embodiments, in making the determination of the target control map based on product characteristics, any one of the following implementations may be included:

in one possible implementation, in a case where the product characteristic of the display panel indicates that the measurement data of the display panel is metering type data, the target control map is determined based on the number of measurement point bits of the display panel and the inter-group difference check result.

It should be noted that, in the case where the measurement data is metering data, the measurement point number of the display panel and the inter-group difference test result may be used as the average value-rangeControl graph, mean-shift range-rangeControl chart, mean-standard deviationControl diagram, single value-moving range (X-MR) control diagram, mean-moving range-standard deviationThe control map is selected as a target control map.

In another possible implementation, in a case where the product characteristic of the display panel indicates that the measurement data of the display panel is count-type data, the target control map is determined based on the presence of defective products and product defects in the display panel.

When the measurement data is count-type data, the target control chart may be selected from the reject numerical control chart (NP-chart), reject ratio control chart (P-chart), reject numerical control chart (C-chart), and unit reject numerical control chart (U-chart) based on the number of rejects and the presence of product defects in the display panel.

The following describes the above two implementations in detail.

First, a description will be given of a process of determining a target control chart based on the number of measurement point bits of the display panel and the inter-group difference test result in the case where the product characteristics of the display panel indicate that the measurement data of the display panel is metering data:

The above-mentioned alternative implementations may be referred to fig. 12, fig. 12 is a schematic diagram illustrating a process of determining a target control chart according to an embodiment of the present invention, where in the case where the measurement data is metering type data, as shown in fig. 12, if the number of measurement point bits of the display panel is greater than or equal to 10 and there is a difference between groups of measurement data of the respective measurement points, it may be thatThe graph is taken as a target control graph; if the number of measurement point bits of the display panel is greater than or equal to 10 and there is no inter-group difference in measurement data of each measurement point, it is possible thatThe graph is taken as a target control graph; in the case where the number of measurement point bits is less than 10, if the number of measurement point bits is 1, it is possible toThe graph is taken as a target control graph; if the number of measurement points is 1 and the measurement data of each measurement point has group-to-group difference, the method can be as followsThe graph is taken as a target control graph; if the number of measurement points is 1 and there is no inter-group difference in the measurement data of each measurement point, it is possible to The graph serves as a target control graph.

Next, a process of determining a target control chart based on the existence of defective products and product defects in the display panel will be described:

As for each of the above-described alternative implementations, referring to fig. 13, fig. 13 is a schematic diagram illustrating a determination process of another target control map according to an embodiment of the present invention, and as shown in fig. 13, if the measurement data is count-type data, if the display panel is a defective product and the number N of display panels as the defective product is a constant, an NP-map may be used as the target control map; if the display panel is a defective product and the number N of display panels as defective products is not constant, a P-map may be used as a target control map; in the case where the display panel is a good but there is a defect in the display panel, if the product defect exists in the set area of the display panel, the C-map may be taken as the target control map; if the product defect exists in an area other than the set area of the display panel, a U-diagram may be used as the target control diagram.

The determination of the target control diagram can be realized based on the product characteristics through the process, so that the determined target control diagram is more in line with the product characteristics of the display panel, the accuracy of the determined target control diagram can be improved, and the target control diagram can better display the data characteristics of the display panel.

The determination of the target control chart can be realized through the above process, so that after the control limit is determined, the control limit can be displayed in the determined target control chart.

In some embodiments, for step 104, when determining the control limit of the target control graph based on the data morphology information, any one of the following implementations may be included:

in one possible implementation manner, in the case that the data form information indicates that the target measurement data of the plurality of display panels has a multi-group characteristic, a set number of target measurement data is determined as one group, a plurality of groups of target measurement data are obtained, a process capability index of each group of target measurement data is calculated respectively, and a control limit of the target control chart is determined based on the plurality of groups of target measurement data of which the process capability index meets a set condition.

It should be noted that, in the case that the target measurement data of the plurality of display panels has a multi-group characteristic, that is, in the case that the first target parameter (i.e., F) is equal to or greater than 2.65, a multi-group control chart (e.g. A figure (C),A graph, an X-MR graph) as a target control graph, in this case, the time may be equally divided according to the number of groups, that is, a set number of target measurement data may be determined as one group, so that a plurality of sets of target measurement data may be obtained, and CPKs for each group may be calculated so as to remove groups for which the CPKs do not satisfy the set condition, and further, control limits may be calculated based on the remaining groups, respectively, so that the maximum value of the calculated plurality of upper control limits and the minimum value of the lower control limit may be used as final control limits. In addition, the center line is a specification line.

The setting condition may be that the value of the CPK is smaller than a third setting threshold, and the third setting threshold may be 1.33, that is, the control limit of the target control chart may be determined based on multiple sets of target measurement data with CPK < 1.33.

It should be noted that, when calculating the CPK of each group, the following formula may be used to implement:

CPK＝Min(C _PU-BW ，C _PL-BW ) (6)

wherein CPK represents a process capability index, USL represents an upper specification limit, LSL represents a lower specification limit,represents the mean value of the data, MR represents the extreme difference of movement, d ₂ To set parameter values.

The CPK calculated by the method uses the data related to the movement range in the calculation process, the movement range is the absolute value of the difference between the mean value and the last SPC data acquisition mean value, and not only the intra-group variation is contained, but also the inter-group variation can be considered, so that the calculated CPK has better sensitivity, the situation that the CPK is reduced when the inter-group variation is increased is avoided, and as an early warning means, the quality personnel can pay more attention to the situation that the product quality in the production process is reduced.

In another possible implementation manner, in a case where the data morphology information indicates that the target measurement data of the plurality of display panels has a multi-group characteristic, if the plurality of display panels correspond to the plurality of batches, the process capability index of the target measurement data of each batch is calculated separately, and the control limit of the target control chart is determined based on the plurality of sets of target measurement data in which the process capability index satisfies the set condition.

It should be noted that, in the case that the target measurement data of the plurality of display panels has a multi-group characteristic, that is, in the case that the first target parameter (that is, F) is equal to or greater than 2.65, a batch control chart (such asA figure (C),Graph, X-MR graph) as a target control graph, in this case, a plurality of display panels may be divided into different batches in units of time (time division is determined by a factory according to actual production conditions, for example, divided into one batch every more than 12 hours), so that CPKs of target measurement data within each batch (i.e., each divided period of time) are calculated to remove groups of set conditions that the CPKs do not satisfy, and control limits are calculated based on the remaining groups, respectively, so that the maximum value of the calculated plurality of upper control limits and the minimum value of the lower control limit are taken as final control limits. In addition, the center line is a specification line.

It should be noted that, when dividing a plurality of display panels into different batches, the following procedure may be implemented:

for any display panel, the production time of the display panel can be compared with the SPC data acquisition time of the last time, if the time difference between the production time and the SPC data acquisition time is more than 24 hours, the production time and the SPC data acquisition time are considered as different batches, and the operation personnel and the taking materials of the display panel are obviously different from the SPC data acquisition time, so that the difference of the process capability of the equipment can be locked on the operation personnel and the materials; if the time difference between the two is greater than 24 hours, the two batches are considered to be the same batch, and the related data (such as date) of the last batch are continued.

It should be noted that, the control limits may be calculated by the normal control limit calculation method for the multiple batches, so that the calculation result of CPK >1.33 and the data amount N >10 in the batch may be taken as the calculation result of the control limit meeting the requirements, and if all the upper data limits meeting the requirements are set as UCL, all the lower data limits meeting the requirements are set as LCL, and the center line is CL, when the final control limit is determined, the maximum value of the upper control limit in the group meeting the requirements may be taken as the upper control limit, the minimum value of the lower control limit in the group meeting the requirements may be taken as the lower control limit, and the average value of the upper control limit and the lower control limit may be taken as the center line.

For example, the determination of the upper control limit, the lower control limit, and the center line may be achieved by the following formulas (10) to (12):

UCL＝Max(UCL) (10)

LCL＝Min(LCL) (11)

CL＝(Max(UCL)+Min(LCL))/2 (12)

wherein UCL is the upper control limit, LCL is the lower control limit, CL is the center line.

In another possible implementation, in a case where the data morphology information indicates that the target measurement data of the plurality of display panels obeys a normal distribution, the control limit of the target control map is determined based on the plurality of target measurement data satisfying the normal distribution.

In the case where the target measurement data of the plurality of display panels is subjected to normal distribution, that is, in F<2.65, P.gtoreq.0.05, normal control charts (e.gA figure (C),Map, X-MR map) as a target control map, in which case,and a control limit may be calculated based on a plurality of target measurement data satisfying the normal distribution using a conventional manner.

In another possible implementation, in a case where the data morphology information indicates that the target measurement data of the plurality of display panels does not follow a normal distribution, the plurality of target measurement data is converted into data that follows the normal distribution, and the control limit of the target control map is determined based on the converted data.

In the case where the target measurement data of the plurality of display panels does not follow the normal distribution, that is, in F <2.65、P<In the case of 0.05, a non-normal control map (e.gA figure (C),Graph, X-MR graph) as a target control graph, in this case, data which does not follow normal distribution may be converted into data which conforms to normal distribution by the JohnSon/BoxCox method, then data located in a 99.73% trust interval may be taken out of the converted data as data to be used, and further, based on the taken out data, a control limit may be calculated using a conventional manner.

If the control limit is calculated according to the same method as the normal data, the calculated control limit may deviate entirely, so that the calculated control limit does not conform to the alarm control.

In the case of converting the non-normal data into the normal data, the normalization of the non-normal data may be achieved by using the method of the open root, but considering that the average value may have a negative value, the normalization of the non-normal data may be achieved by using the following 4 steps:

and step 1, shifting the average value data upwards by 2 times of the specification limit width to enable the average value data to be positive.

It should be noted that, before this step, the values with the difference of more than 2 times of the specification width from the 0 value may be removed in advance, so as to ensure that the remaining mean value data are positive values after being shifted, so that the smooth proceeding of the data processing process may be ensured, and the accuracy of the data processing process may be improved.

And step 2, opening root numbers for the offset data to generate a new average value and a new extremely bad movement.

It should be noted that the original values of the polar error and standard deviation can still be used to ensure that the sigma value of the data will not deviate, thereby ensuring the accuracy of the data processing process.

And 3, calculating the control limit based on the data subjected to the offset processing according to a method for calculating the control limit of the normal data.

And 4, shifting the control limit downwards by 2 times of the specification limit width.

The control limits obtained after the processing in the steps 1 to 4 may be used as the control limits of the non-normal data.

As described above, the process of calculating the control limits may be referred to fig. 14, fig. 14 is a schematic diagram of a control limit calculation process shown in an embodiment of the present invention, and as shown in fig. 14, it may be determined whether the data has a multi-group characteristic, in which case the data has a multi-group characteristic, the batches may be cut in a regular manner so that the control limits are calculated using a conventional manner for each batch, for any batch, if the CPK of the batch is less than 1.33, the calculation of the control limits is not required using the data of the batch, and if the CPK of the batch is not less than 1.33, it is determined whether the control limit calculated based on the data of the batch is the maximum upper limit of the upper control limit or the minimum lower limit of the control limit, and if so, the control limit may be regarded as the final control limit, and if not, the calculation of the control limit is not required as the final control limit. In addition, in the case where the data does not have the multi-group characteristic, it is determined whether the data is subject to normal distribution, if the data is subject to normal distribution, calculation of the control limit may be performed in a conventional manner of calculating the control limit using normal data, and CPK of these data is determined, if the CPK is greater than 1.33, the control limit is taken as a final control limit, and if the CPK is not greater than 1.33, the control limit is not required as a final control limit; if the data does not follow the normal distribution, the control limits can be calculated in a conventional manner by calculating the control limits using the non-normal data, and determining the CPK of the data, wherein if the CPK is greater than 1.33, the control limit is taken as the final control limit, and if the CPK is not greater than 1.33, the control limit is not required as the final control limit.

It should be noted that, for different types of control charts, the conventional manner of calculating the control limits is different, and a description is given below of how to calculate the control limits of the different types of control charts, respectively.

For the followingControl map, control limit can be calculated according to the following formulas (13) to (18):

wherein,the mean value of the data is represented,center line representing data mean, R represents the extreme difference, CL _R Representing a very poor centre line of the line,the mean value of the extreme differences is indicated,upper control limit representing data mean, UCL _R An upper control limit representing a very poor is indicated,lower control limit representing data mean value, LCL _R Lower control limit indicating the extreme difference, A ₂ 、D ₃ 、D ₄ Are all set parameter values.

For the followingControl map, control limit can be calculated according to the following formulas (19) to (24):

wherein,the mean value of the data is represented,center line representing data mean, S represents standard deviation, CL _s The center line representing the standard deviation is indicated,sign markThe mean value of the quasi-differences,upper control limit representing data mean, UCL _s The upper control limit of the standard deviation is indicated,lower control limit representing data mean value, LCL _s Represents the lower control limit of standard deviation, A ₃ 、B ₃ 、B ₄ Are all set parameter values.

For the followingControl map, control limit can be calculated according to the following formulas (25) to (33):

Wherein,the mean value of the data is represented,center line representing data mean, MR represents the very bad movement, CL _MR A center line indicating the movement limit, R indicates the limit, and CL _R Representing a very poor centre line of the line,the mean value of the extreme differences is indicated,upper control limit representing data mean, UCL _MR Upper control limit indicating movement margin, UCL _R An upper control limit representing a very poor is indicated,lower control limit representing data mean value, LCL _MR Lower control limit indicating movement margin, LCL _R Lower control limit indicating the extreme difference, E ₂ 、D ₃ 、D ₄ Are all set parameter values.

For the followingControl map, control limits may be calculated according to the following formulas (34) to (42):

wherein,the mean value of the data is represented,center line representing data mean, MR represents the very bad movement, CL _MR The center line representing the movement range, S represents the standard deviation, CL _s The center line representing the standard deviation is indicated,the mean value of the standard deviation is represented,upper control limit representing data mean, UCL _MR Upper control limit indicating movement margin, UCL _s The upper control limit of the standard deviation is indicated,lower control limit representing data mean value, LCL _MR Lower control limit indicating movement margin, LCL _s Represents the lower control limit of standard deviation, E ₂ 、B ₃ 、B ₄ 、D ₃ 、D ₄ Are all set parameter values.

For an X-MR control map, the control limits may be calculated according to the following formulas (43) to (48):

Wherein X represents a data unit value, CL _x Represents the centerline of the data unit value, MR represents the movement range, CL _MR A center line representing the extremely poor movement is shown,mean value of motion limit, UCL _x Representing the upper control limit of the data sheet value, _U CLMR represents the upper control limit of the movement range, LCL _x Lower control limit representing data sheet value, LCLM _R A lower control limit indicating the movement limit E ₂ 、D ₃ 、D ₄ Are all set parameter values.

For the NP-graph, the control limit may be calculated according to the following formulas (49) to (51):

wherein CL is _NP Center line of NP-diagram, UCL _NP Upper control limit, LCL, representing NP-diagram _NP Represents the lower control limit of the NP-graph,the mean of the failure rates is shown.

For the P-map, the control limit may be calculated according to the following formulas (52) to (54):

wherein CL is _P Center line of P-graph, UCL _P Upper control limit, LCL, representing P-diagram _P Represents the lower control limit of the P-graph,the mean of the failure rates is shown.

For the V-diagram, the control limit may be calculated according to the following formulas (55) to (57):

wherein CL is _C Center line of C-diagram, UCL _C Upper control limit, LCL, representing C-diagram _C The lower control limit of the C-diagram is indicated,the mean of the failure rates is shown.

For the U-diagram, the control limits may be calculated according to the following formulas (58) to (60):

Wherein CL is _U Representing the centerline of the U-diagram, UCL _U Upper control limit, LCL, representing U-diagram _U Representing the lower control limit of the U-diagram,representing the average value of the area of the region where the product defect occurs.

For ease of understanding, the target control map and the control limits are further explained below by taking the control map related to the mean in the mean-shift range-standard deviation control map as an example.

Referring to fig. 15, fig. 15 is a schematic diagram of a control chart, which uses a mean value as a statistical data feature, and as shown in fig. 15, an abscissa of each data point in the chart may represent which display panel corresponds, and an ordinate may represent a mean value of measurement data of the corresponding display panel, so that the control chart may represent a mean value feature of each display panel.

In addition, the control map may also be displayed with control limits determined based on the methods provided in the above embodiments. Still taking the control diagram as shown in fig. 15 as an example, the control diagram shows an upper control limit, a lower control limit and a central line, wherein the upper control limit is a straight line with an ordinate 8.750904, the lower control limit is a straight line with an ordinate 3.2619267, and the central line is a straight line with an ordinate 6.006415.

The product quality of the display panel can be monitored through the control limit displayed in the control chart.

In one possible implementation, the computing device displays the target control chart and the control limits in the target control chart, and the related technician can determine whether the quality of each display panel is qualified according to the displayed target control chart and the control limits.

In another possible implementation, the computing device may also monitor the product quality of the display panel based on the target control graph and the control limits by itself.

For example, the computing device may detect whether there is a data value that exceeds the lower and upper control limits, and in the event that it is detected that there is a data value that exceeds the lower and upper control limits, issue an alarm message so that the relevant technician, upon receiving the alarm message, may determine that there is a product of unacceptable quality in the display panel that has just been detected.

Alternatively, the computing device may obtain product identifications of display panels whose data values exceed the lower and upper control limits, thereby alerting based on the obtained product identifications so that a relevant technician can quickly determine which of the quality-failed display panels is.

The foregoing various alternative embodiments may be combined according to the order shown in fig. 16 to implement the data processing method provided by the present invention, referring to fig. 16, fig. 16 is a flowchart of a data processing method shown in an embodiment of the present invention, a product model of a display panel to be detected may be selected first, so as to determine a product characteristic of the display panel to be detected according to the selected product model, and an equipment model corresponding to the display panel may be built based on the product model, where the equipment model may include a host station, a sub-station, an intra-equipment mechanism (i.e., a processing unit in each station), and an intra-Glass plane group, so as to implement determination of a minimum management unit (i.e., a grouping result), so as to perform data morphology classification based on the grouping result, so as to obtain data morphology information (including normal check, trend check, multi-group check, etc.) of target measurement data of each display panel, so as to process the display panel obtained according to a sampling rule (i.e., a target sampling interval) based on the data morphology information, so as to implement determination of a control chart and a control limit.

Fig. 16 is only a flowchart illustrating the present invention, and the specific implementation of each step may be referred to the above embodiment, which is not described herein.

The above embodiments describe a process of implementing control limit determination by the data processing method provided by the present invention, and in addition, in the production process of the display panel, the display panel is processed by a plurality of production devices, and the data processing method provided by the present invention can also be used for tracing the data source.

It should be noted that, the data source trace needs history information, and the measurement data appearing in the production process can be divided into two types, one is the measurement data obtained by the production equipment with the testing machine, and the other is the measurement data obtained by the special testing machine. For the measurement data acquired by the production equipment with the tester, the measurement data contains the equipment information of the production equipment, so that no redundant processing is needed, and for the measurement data acquired by the special tester, the measurement data does not contain the equipment information of the production equipment, so that the equipment information of the production equipment needs to be recorded by oneself.

In addition, it should be noted that, for the measurement data acquired by the dedicated inspection machine, although the measurement data does not include the equipment information of the production equipment, the measurement data may include the product identifier (i.e., the product Lot ID), and thus, in some embodiments, each display panel may correspond to one production information storage structure, that is, each product identifier may correspond to one production information storage structure, and the production information storage structure may be used to store the equipment information of the production equipment that processes the corresponding display panel.

Referring to fig. 17, fig. 17 is a schematic diagram illustrating a processing procedure of a display panel according to an embodiment of the present invention, taking a detection parameter DI CD as an example, a production device may include 5APPH01 and 5APPH02, a test device may include 5AMCD01, 5AMCD02 and 5AMCD03, where the production device 5APPH01 may be used to produce display panels with product identifiers of Lot1, lot2 and Lot3, the production device 5APPH02 may be used to produce display panels with product identifiers of Lot a, lot b and Lot c, as shown in fig. 17, the measurement data of the display panels with product identifiers of Lot1, lot2 and Lot a all incorporate test data sets corresponding to the test device 5AMCD01, the measurement data of the display panels with product identifiers of Lot3 and Lot b all incorporate test data sets corresponding to the test device 5AMCD02, the measurement data of the display panels with product identifiers of Lot3 and Lot b all incorporate test data sets corresponding to the test device 5AMCD03, where the test device 5AMCD01 and 5AMCD02 all correspond to the display panels with different product identifiers of Lot1, lot2 and Lot b, and Lot of information cannot be distinguished from each other, so that it is difficult to calculate the capability of the device to distinguish between the test device and the device 5 apc 01 and the device.

The data processing method provided by the invention maintains a production information storage structure for each display panel (namely, each product identifier) so as to realize the distinction of the production equipment information through the production information storage structure.

Referring to fig. 18, fig. 18 is a schematic view showing a production information storage structure according to an embodiment of the present invention, and fig. 18 shows a production information storage structure corresponding to a display panel of which product is identified as LotA and a production information storage structure corresponding to a display panel of which product is identified as Lot1, wherein a production apparatus for processing the display panel of which product is identified as LotA includes an unpacking apparatus 1 (specifically, unpacking apparatus 1-unit 1), a cleaning apparatus 2 (specifically, cleaning apparatus 2-unit 1), a production apparatus 5APPH04 (specifically, 5APPH 04-units 1 and 5APPH 04-unit 3), and a testing apparatus 5AMCD01; the production equipment for processing the display panel with the product mark of Lot1 comprises unpacking equipment 1 (particularly unpacking equipment 1-unit 1), cleaning equipment 2 (particularly cleaning equipment 2-unit 1), production equipment 5APPH01 (particularly 5APPH 01-unit 1 and 5APPH 01-unit 2) and test equipment 5AMCD01, so that the establishment of a storage structure containing the production equipment and even equipment units is realized, and data acquisition of a machine level and a unit (Chamber) level of the distinguishing equipment is realized, so that the control limit and CPK are concentrated on the processing capacity of the production equipment level or the Chamber level.

In addition, a production equipment management model (or SPC minimum unit model) may be generated based on the production equipment information storage structure of each display panel, and display panels processed by different production equipment may be recorded through the production equipment management model.

The production device management model may be a tree-like storage structure associated with the computing device, or the production device management model may be a table-form storage structure associated with the computing device, or alternatively, the production device management model may be of another type, which is not limited in the present invention.

Taking a storage structure in a form of a table, where the production equipment management model may be associated with a computing device, an equipment identifier may be used as a table index (e.g., a header), so that a product identifier of a display panel processed by a corresponding device is stored in a corresponding position in the table, so as to obtain the production equipment management model.

In addition, the production equipment management structure may also record a display panel processed by the production equipment 5APPH01, specifically a display panel processed by the unit 2 in the production equipment 5APPH01, in the production equipment management model shown in fig. 18, as shown in the SPC minimum unit model in fig. 18.

The foregoing describes specific forms of the production information storage structure and the production equipment management model, alternatively, when the production equipment management model is generated based on the production information storage structure, a plurality of display panels processed by the respective production equipment may be determined based on the equipment information recorded in the production information storage structure of the respective display panels, and the product information of the plurality of display panels processed by the respective production equipment may be recorded in the production equipment management model, respectively.

It should be noted that, because the processing of multiple devices and multiple units is generally performed by overlapping multiple exposure processes during the processing of the display panel, the detection device generally detects the corresponding measured value to upload after each exposure process or sputtering process or time is performed, and for facilitating the subsequent processing, the production device management model only needs to record the production device that performs a certain processing last time, so as to reduce the processing pressure of the computing device.

Referring to fig. 19, fig. 19 is a schematic diagram of an information input process according to an embodiment of the present invention, as shown in fig. 19, when tracing data, a corresponding production equipment management model may be searched for based on equipment identifiers, so as to determine whether a product identifier to be queried exists in the production equipment management model (i.e. whether the product identifier to be queried is registered in the production equipment management model), and if it is determined that the product identifier to be queried does not exist in the production equipment management model, the processing process may be directly ended; if the product identifier to be queried exists in the production equipment management model, the corresponding production information storage structure can be searched based on the product identifier, so that the latest production equipment (namely, the production equipment for processing the display panel for the last time) is matched in the corresponding production information storage structure, and equipment units of the latest production equipment are further matched, and therefore a control chart or a control limit is calculated according to a result obtained by matching, and a corresponding data processing process is realized.

By maintaining a production equipment information storage structure for each display panel, the data points corresponding to the display panels can be displayed in the target control chart, so that the related technicians can acquire the equipment information of the production equipment for processing the display panel from the corresponding display panel by triggering the corresponding data points, and the equipment information of the production equipment for processing the display panel is displayed in the target control chart for viewing by the related technicians.

The invention provides a data processing scheme aiming at the production process of TFT-LCD and OLED industries, which solves the problem that the control limit is inaccurate due to unclassified data form in the related art by classifying the data form and adopting a corresponding control chart and a corresponding control limit based on the data form classification result. Moreover, a new method for calculating CPK is provided, and the sensitivity of the CPK is improved, so that the problem of insufficient referenceability of the CPK can be solved.

In addition, the invention also innovatively provides two combined control diagrams, namelyDrawing and graphThe graph is composed of a mean control graph, a movable range control graph and a range or standard deviation control graph, and can monitor the mean value of the process and variation among groups and in groups under the condition that each subgroup belongs to different points or batches, so that the problem that the conventional Huhattan control graph requires that the in-plane variation is random variation and the same point position is required to be measured, and when the conditions cannot be met, the in-plane variation is caused to be non-random variation, the standard deviation is overlarge, and finally the technical problem of influencing the performance of the control graph is solved, and the problem that the double-graph observation capability is limited in the TFT-LCD and OLED production process is solved.

In addition, the invention also innovatively provides a production information storage structure and a production equipment management model, introduces a product production equipment tracing method, enables equipment of the same type to be managed separately according to equipment identification, and enables the calculation result of the control limit and the calculation result of the CPK not to be mixed data of a plurality of equipment any more so as to solve the problem of confusion management of production equipment data in the related art.

In other embodiments, the present invention further provides a data display method, referring to fig. 20, and fig. 20 is a flowchart of a data display method according to an embodiment of the present invention, where, as shown in fig. 20, the method may include the following steps:

step 2001, displaying a product management interface.

Step 2002, obtaining the product model of the display panel to be detected through the product management interface, and determining a target control chart based on the product model, wherein the target control chart is used for indicating the statistical data characteristics of each display panel.

Step 2003, in response to the submitting operation at the product management interface, displaying a target control chart and a control limit, wherein the target control chart is used for indicating the statistical data characteristics of each display panel, the target control chart is displayed with a control limit, and the control limit is used for indicating the upper limit value and/or the lower limit value of the statistical data characteristics of the display panels meeting the production requirement.

It should be noted that, in response to the submitting operation at the product management interface, the computing device may implement the determination of the target control chart and the control limit by using the data processing method, so as to display the target control chart and the control limit.

In some embodiments, a product model setting control and a control chart selecting control may be set in the product management interface, based on which, for step 2002, when obtaining a product model of a display panel to be detected through the product management interface, and determining a target control chart based on the product model, where the target control chart is used to indicate a statistical data feature of each display panel, the method may include the following steps:

and 2002-1, obtaining the product model through a product model setting control.

Referring to fig. 21, fig. 21 is an interface schematic diagram of a product management interface according to an embodiment of the present invention, as shown in fig. 21, a "product model" and a corresponding drop-down box are product model setting controls, in which a plurality of candidate product models are displayed in the drop-down box, a related technician may select from the plurality of candidate product models, and a computing device may respond to a triggering operation of the related technician to obtain the selected product model.

And 2002-2, displaying at least one candidate control chart on the control chart selection control based on the product characteristics corresponding to the product model.

It should be noted that, the product characteristics of the display panels of different product types are preset, so that after the product types are obtained in step 2002-1, the corresponding product characteristics can be determined, and the types of control charts usable under different product characteristics are preset, so that the computing device can display at least one candidate control chart usable under the product characteristics in the control chart selection control according to the determined product characteristics.

Referring to fig. 22, fig. 22 is an interface schematic diagram of another product management interface according to an embodiment of the present invention, as shown in fig. 21, a "chart type" and a corresponding drop-down box are control chart selection controls, after determining a product characteristic corresponding to a product model, selectable control chart types corresponding to the product characteristic of the display panel may be displayed in the drop-down box, and a related technician may select from multiple control chart types, and the computing device may respond to a trigger operation of the related technician to implement determination of a target control chart.

Step 2002-3, in response to a selection operation on any candidate control map, determining the selected candidate control map as a target control map.

The above process is described by taking the example of displaying the candidate control charts directly based on the product characteristics corresponding to the product model after determining the product model, in more possible implementation manners, the computing device may further provide a point location number setting control in the product management interface, so that a related technician may set the number of measurement points of the display panel through the point location number setting control, and the control charts that can be used by the display panels with different measurement point location numbers are different, so that the computing device may display the candidate control charts based on the number of measurement points set by the related technician.

In some embodiments, the related technician may set the number of measurement points through the point location number setting control, and the computing device may obtain the number of measurement points set through the point location number setting control, and further display at least one candidate control graph in the control graph selection control based on the product characteristics corresponding to the product model number and the obtained number of measurement points.

Taking the product management interface shown in fig. 22 as an example, the control with the display text of "point number not less than 1" is the point number setting control, and related technicians can set the number of measurement points through the control, so that the candidate control diagram can be displayed based on the product model number and the number of measurement points.

It should be noted that, after completing the selection of the control chart, the relevant technician may perform the submitting operation in the product management interface, so that the computing device may start the process of data acquisition and processing to calculate the control limit, thereby implementing the display of the target control chart and the control limit through step 2003.

Still taking the product management interface shown in fig. 22 as an example, a related technician may trigger a submit control (i.e. the "submit" button in fig. 22) in the product management interface shown in fig. 22 to trigger a submit operation in the product management interface, thereby triggering the processes of data collection and data processing to realize the display of the target control chart and the control limit.

Referring to FIG. 23, FIG. 23 is a schematic diagram showing a target control diagram according to an embodiment of the present invention, and FIG. 23 is a diagram showing the target control diagram The figures are examples showing examples of a target control graph, which are easily understood by those skilled in the art. Further, limited control limits (including an upper control limit, a lower control limit, and a center line) are displayed in the target control chart as shown in fig. 23, so that product quality monitoring can be achieved based on the displayed control limits.

When the target control chart is displayed, data points corresponding to each display panel may be displayed in the target control chart (as shown in fig. 23, 50 data points corresponding to 50 display panels are displayed in the target control chart of fig. 23, that is, 50 data points), and a related technician may trigger any one data point to view the equipment information of the production equipment for processing the display panel corresponding to the data point.

In one possible implementation manner, in response to a trigger operation on any data point in the displayed target control chart, equipment information of production equipment for processing the display panel is acquired from a production information storage structure of the display panel corresponding to the data point, and the acquired equipment information is displayed.

Referring to fig. 24, fig. 24 is a schematic diagram of an information viewing interface according to an embodiment of the present invention, if a related technician triggers a data point with an abscissa 38 in a target control chart, a computing device may display an ordinate value of the data point in the target control chart, acquire device information of a production device for processing a display panel corresponding to the data point, and display the acquired device information in an information display area below the target control chart, so that the related technician may directly see the production device for processing the display panel, thereby implementing data tracing.

It should be noted that the foregoing embodiments simply describe a few controls in the product management interface, and in more possible implementations, other controls may be included in the product management interface to provide more functionality for the relevant technician.

In some embodiments, the product management interface further includes a partition setting control, so that a related technician can divide the display panel into a plurality of partitions through the partition setting control, thereby enabling the partition processing of the measurement data. The relevant description of the partition can be found in the above embodiments, and will not be repeated here.

In one possible implementation manner, in response to a triggering operation of the partition setting control, a partition management interface is displayed, and the partition management interface is used for partitioning a plurality of measurement points in the display panel to obtain partition results of the plurality of measurement points, so that in the process of processing the acquired data, the computing device can respectively process the measurement data of the measurement points in different partitions based on the partition results.

Taking the product management interface as shown in fig. 21 as an example, as shown in fig. 21, the "point location partition" control is a partition management control, and the related technician can trigger the "point location partition" control, and the computing device can respond to the triggering operation of the "point location partition" control to display the partition setting interface, so that the related technician can partition the display panel through the partition setting interface.

Referring to fig. 25, fig. 25 is a schematic view of a partition setting interface according to an embodiment of the present invention, i.e., a display panel may be partitioned by the partition setting interface shown in fig. 25.

In other embodiments, the product management interface may further include at least one of the following controls:

for example, the product management interface may include a data collection management control that may be used to set the type of measurement data to be collected and the data descriptive information of the measurement data.

Taking the product management interface as shown in fig. 21 as an example, the "data acquisition parameters" and the corresponding drop-down controls in the product management interface may be used as the data acquisition management controls, where the "data acquisition parameters" and the corresponding drop-down controls may be used to set the types of measurement data to be acquired, and the "parameter descriptions" and the corresponding drop-down controls may be used to add data description information to the measurement data to be acquired.

For another example, the product management interface may further include a device management control for acquiring device information of the production device of the display panel;

Referring to fig. 26, fig. 26 is a schematic diagram of another product management interface according to an embodiment of the present invention, where as shown in fig. 26, controls included under the "SPC modeling" category, such as "test station", "test equipment", "test Recipe", "process station", "process equipment", "process Chamber/Recipe" controls, are all equipment management controls, and related technicians can implement settings of related production equipment and production processes through these equipment management controls, so that the display panel can be processed based on information set by the related technicians later.

For another example, the product management interface may further include a data filtering control, where the data filtering control is configured to set conditions that are satisfied by the data to be filtered and a data filtering manner.

Taking the product management interface as shown in fig. 21 as an example, the "upper filter line" and the corresponding adjustment control, the "lower filter line" and the corresponding adjustment control, the "OOT time limit" and the corresponding adjustment control in the product management interface can be used as the data filtering control. Wherein, the 'upper filter line' and the corresponding adjustment control can be used for setting the maximum value of the measurement data used in the data processing; the "lower filter line" and corresponding adjustment control may be used to set a minimum value for the measurement data used in the data processing; the OOT time limit and the corresponding adjustment control can be used for setting acquisition time conditions which need to be met for measurement data used in data processing; the "remove beyond filter limit" and the corresponding drop-down control may be used to set a data filtering manner, for example, when data that does not meet the data processing requirement appears, only the data that does not meet the data processing requirement is removed, or all the data collected this time is discarded.

For another example, the product management interface can also include a timing functionality setting control for setting the cycle period of the data collection and calculation process.

Taking the product management interface as shown in fig. 21 as an example, the "cycle type" and the corresponding drop-down control, the "weekly day" and the corresponding drop-down control, the "monthly day" and the corresponding drop-down control in the product management interface can be used as timing function setting controls, so that the data acquisition and processing process can be performed every long time through the timing function setting controls.

In addition, the product management interface may also include a start condition setting control for setting conditions for starting the data processing process.

Taking the product management interface as shown in fig. 21 as an example, the "automatic calculation minimum number" and the corresponding adjustment control in the product management interface can be used as a start condition setting control, and when the automatic calculation minimum data is set to 25, that is, when the acquired data is data corresponding to 25 display panels, data processing can be performed based on the acquired data, so as to determine the control limit.

In more possible implementation manners, after the control limit is determined by the data processing method, the specification limit may be determined based on the determined control limit, for example, a set value may be increased on the basis of the upper control limit to obtain an upper specification limit, a set value may be decreased on the basis of the lower control limit to obtain a lower specification limit, and the center line is determined as a center value, so as to determine the specification limit, where the set value is any positive value.

The foregoing is merely an exemplary manner of determining the specification limit, and alternatively, the specification limit may be determined by other manners, for example, by formulating the specification limit according to the requirement of the customer, etc., which manner is not limited by the present invention.

The product management interface also comprises a control limit management control and/or a specification limit management control, and the computing equipment can display the determined control limit and specification limit in the control limit management control and specification limit management control respectively after determining the control limit and specification limit, so that related technicians can adjust the control limit and the specification limit through the product management interface. The control limit management control is used for adjusting the determined control limit, and the specification limit management control is used for adjusting the determined specification limit.

Taking the product management interface as shown in fig. 21 as an example, in the product management interface, "upper Limit UCL" and corresponding adjustment control, "center line CL" and corresponding adjustment control, "lower Limit LCL" and corresponding adjustment control in the three functional partitions of "main diagram-Limit", "auxiliary diagram-Limit" and "three diagram-Limit" can be used as control Limit management control for adjusting the determined control Limit. The "upper Limit USL" and the corresponding adjustment control, the "center line" and the corresponding adjustment control, the "lower Limit LSL" and the corresponding adjustment control in the "specification-Limit" functional partition can be used as specification Limit management control for adjusting the determined specification Limit.

The control limit management control and the specification limit management control are arranged in the product management interface, so that related technicians can adjust the determined control limit and specification limit according to actual requirements, and the flexibility of the data processing process can be improved.

An embodiment of the present invention also proposes a data processing apparatus, referring to fig. 27, fig. 27 is a block diagram of a data processing apparatus according to an embodiment of the present invention, as shown in fig. 27, the apparatus including:

An acquisition module 2701, configured to acquire a plurality of measurement data of each display panel to be detected;

a determining module 2702 configured to determine data morphology information indicating whether the target measurement data of the plurality of display panels has a multi-group characteristic by determining the target parameter value based on the plurality of measurement data, and/or whether the target measurement data of the plurality of display panels is subject to normal distribution, the target measurement data of each display panel being determined based on the plurality of measurement data of the display panels;

the determining module 2702 is further configured to determine, based on the data morphology information, a control limit of a target control chart, where the target control chart is used to indicate a statistical data feature of each display panel, and the control limit is used to indicate an upper limit value and/or a lower limit value of the statistical data feature of the display panel that meets the production requirement.

a determination module 2702, when configured to determine a target parameter value based on a plurality of measurement data, is configured to:

The determining module 2702, when configured to determine data morphology information by determining a target parameter value based on a plurality of measurement data, is configured to:

In some embodiments, the determination module 2702, when used to determine control limits for a target control graph based on data morphology information, is used for any of:

a determining module 2702, further configured to determine a target control chart based on product features of the display panel;

the determining module 2702, when configured to determine a target control chart based on product features of a display panel, is configured to:

In some embodiments, the determining module 2702, when used to determine the target control map based on the number of measurement points of the display panel and the inter-group difference test result, is used to either:

In some embodiments, the determining module 2702, when used to determine the target control map based on the presence of rejects and product defects in the display panel, is to:

When there is no defective product in the display panel, but there is a display panel with a product defect, if the product defect is not present in the set area, the numerical control chart of defective products per unit product is used as the target control chart.

In some embodiments, the determining module 2702 is further configured to determine a product model of the display panel to be detected based on the target instruction in response to receiving the target instruction;

the determining module 2702 is further configured to determine a product characteristic of the display panel based on the product model.

In some embodiments, the apparatus further comprises:

In some embodiments, the determining module 2702 is further configured to determine a plurality of display panels processed by each production apparatus based on the device information recorded in the production information storage structure of each display panel, and record the product information of the plurality of display panels processed by each production apparatus into a production apparatus management model, where the production apparatus management model is used to record display panels processed by different production apparatuses.

An embodiment of the present invention also proposes a data display device, referring to fig. 28, fig. 28 is a block diagram of a data display device according to an embodiment of the present invention, as shown in fig. 28, the device includes:

a display module 2801 for displaying a product management interface;

the processing module 2802 is configured to obtain a product model of a display panel to be detected through a product management interface, and determine a target control chart based on the product model, where the target control chart is used to indicate statistical data features of each display panel;

the display module 2801 is further configured to display, in response to a submitting operation at the product management interface, a target control chart and a control limit, where the target control chart is used to indicate the statistical data feature of each display panel, and the target control chart displays a control limit, and the control limit is used to indicate an upper limit and/or a lower limit of the statistical data feature of the display panel that meets the production requirement;

the processing module 2802, when used for obtaining a product model of a display panel to be detected through a product management interface, and determining a target control chart based on the product model, is used for:

obtaining a product model through a product model setting control;

the processing module 2802 is further configured to obtain a measurement point bit number set by the point location number setting control;

the display module 2801 is further configured to display at least one candidate control chart in the control chart selection control based on the product characteristics corresponding to the product model number and the obtained measurement point number.

the display module 2801 is further configured to respond to a triggering operation of the partition setting control, and display a partition management interface, where the partition management interface is configured to partition a plurality of measurement points in the display panel, and obtain partition results of the plurality of measurement points, so as to respectively process measurement data of the measurement points in different partitions based on the partition results.

The processing module 2802 is further configured to obtain, in response to a trigger operation on any data point in the displayed target control chart, device information of a generating device that processes the display panel from a production information storage structure of the display panel corresponding to the data point;

the display module 2801 is further configured to display the acquired device information.

The implementation process of the functions and roles of each module in the above device is specifically shown in the implementation process of the corresponding steps in the above method, and will not be described herein again.

For the device embodiments, reference is made to the description of the method embodiments for the relevant points, since they essentially correspond to the method embodiments. The apparatus embodiments described above are merely illustrative, wherein the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purposes of the present description. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

The present invention also provides a computing device, referring to fig. 29, and fig. 29 is a schematic structural diagram of a computing device according to an embodiment of the present invention. As shown in fig. 29, the computing device includes a processor 2901, a memory 2902, and a network interface 2903, the memory 2902 being configured to store computer program code executable on the processor 2901, the processor 2901 being configured to implement a data processing method provided by any of the embodiments of the present invention when the computer program code is executed, and the network interface 2903 being configured to implement input-output functions. In further possible implementations, the computing device may also include other hardware, as the invention is not limited in this regard.

The present invention also provides a computer-readable storage medium, which may take many forms, for example, in various examples, the computer-readable storage medium may be: RAM (Radom Access Memory, random access memory), volatile memory, non-volatile memory, flash memory, a storage drive (e.g., hard drive), a solid state drive, any type of storage disk (e.g., optical disk, DVD, etc.), or a similar storage medium, or a combination thereof. In particular, the computer readable medium may also be paper or other suitable medium capable of printing the program. The computer readable storage medium stores a computer program which, when executed by a processor, implements the data processing method provided by any of the embodiments of the present invention.

The invention also provides a computer program product comprising a computer program which, when executed by a processor, implements the data processing method provided by any of the embodiments of the invention.

The present invention also provides a computing device, referring to fig. 30, and fig. 30 is a schematic structural diagram of a computing device according to an embodiment of the present invention. As shown in fig. 30, the computing device includes a processor 3001, a memory 3002, and a network interface 3003, the memory 3002 being for storing computer program code executable on the processor 3001, the processor 3001 being for implementing a data display method provided by any one of the embodiments of the present invention when the computer program code is executed, the network interface 3003 being for implementing input-output functions. In further possible implementations, the computing device may also include other hardware, as the invention is not limited in this regard.

The present invention also provides a computer-readable storage medium, which may take many forms, for example, in various examples, the computer-readable storage medium may be: RAM (Radom Access Memory, random access memory), volatile memory, non-volatile memory, flash memory, a storage drive (e.g., hard drive), a solid state drive, any type of storage disk (e.g., optical disk, DVD, etc.), or a similar storage medium, or a combination thereof. In particular, the computer readable medium may also be paper or other suitable medium capable of printing the program. The computer readable storage medium stores a computer program which, when executed by a processor, implements the data display method provided by any of the embodiments of the present invention.

The invention also provides a computer program product comprising a computer program which, when executed by a processor, implements the data display method provided by any of the embodiments of the invention.

In the present invention, the terms "first", "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. The term "plurality" refers to two or more, unless explicitly defined otherwise.

Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.

It is to be understood that the invention is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the invention is limited only by the appended claims.

Claims

A method of data processing, the method comprising:

acquiring a plurality of measurement data of each display panel to be detected;

determining data morphology information indicating whether the target measurement data of the plurality of display panels has a multi-group characteristic and/or whether the target measurement data of the plurality of display panels is subject to normal distribution, the target measurement data of each display panel being determined based on the plurality of measurement data of the display panels, by determining the target parameter value based on the plurality of measurement data;

and determining a control limit of a target control chart based on the data form information, wherein the target control chart is used for indicating the statistical data characteristics of each display panel, and the control limit is used for indicating the upper limit value and/or the lower limit value of the statistical data characteristics of the display panels meeting the production requirements.
The method of claim 1, wherein the target parameter values comprise first target parameter values indicating a ratio of sum of squares of deviations to degrees of freedom between and within groups of the target measurement data packets;

The determining a target parameter value based on the plurality of measurement data includes:

for any display panel, determining the average value of a plurality of measurement data of the display panel as target measurement data of the display panel;

grouping the target measurement data of the display panels according to the time period to obtain a plurality of groups of target measurement data;

determining the sum of inter-group variation and the sum of single-point squares of the multiple groups of target measurement data;

the first target parameter value is determined based on the sum of inter-group variations, the sum of single-point squares, and the sum of single-point squares.
The method of claim 1, wherein the target parameter values comprise second target parameter values for indicating a probability that target measurement data of the plurality of display panels obeys a normal distribution;

the determining a target parameter value based on the plurality of measurement data includes:

for any display panel, determining the average value of a plurality of measurement data of the display panel as target measurement data of the display panel;

and carrying out normal verification on the target measurement data of the display panels to obtain the second target parameter value.
The method according to claim 1, wherein the data morphology information is determined based on the target parameter values, the target parameter values comprising a first target parameter value for indicating a ratio of a sum of squares of deviations and degrees of freedom between and within groups of the target measurement data packets and/or a second target parameter value for indicating a probability that the target measurement data of the plurality of display panels obeys a normal distribution;

the determining data morphology information by determining the target parameter value based on the plurality of measurement data includes:

determining that the data morphology information indicates that target measurement data of the plurality of display panels has a multi-group characteristic if the first target parameter value is greater than a first set threshold;

determining that the data morphology information indicates that target measurement data of the plurality of display panels obeys a normal distribution when the first target parameter value is less than or equal to a first set threshold value and the second target parameter value is greater than or equal to a second set threshold value;

in the case where the first target parameter value is less than or equal to a first set threshold value and the second target parameter value is less than a second set threshold value, determining that the data morphology information indicates that target measurement data of the plurality of display panels does not follow a normal distribution.
The method of claim 1, wherein determining a control limit for a target control map based on the data morphology information comprises any one of:

under the condition that the data form information indicates that the target measurement data of the display panels have multi-group characteristics, determining a set number of target measurement data as one group to obtain a plurality of groups of target measurement data, respectively calculating a process capability index of each group of target measurement data, and determining a control limit of the target control chart based on the plurality of groups of target measurement data of which the process capability index meets a set condition;

if the data form information indicates that the target measurement data of the display panels have multi-group characteristics, respectively calculating a process capability index of the target measurement data of each batch if the display panels correspond to a plurality of batches, and determining a control limit of the target control chart based on a plurality of groups of target measurement data of which the process capability index meets a set condition;

determining a control limit of the target control map based on the plurality of target measurement data satisfying the normal distribution, in a case where the data morphology information indicates that the target measurement data of the plurality of display panels obeys the normal distribution;

And converting the target measurement data of the display panels into data conforming to normal distribution when the data form information indicates that the target measurement data of the display panels do not conform to normal distribution, and determining the control limit of the target control chart based on the converted data.
The method of claim 1, wherein the target control map is determined based on a product characteristic of the display panel, the product characteristic being used to indicate whether the measured data of the display panel is metering type data or counting type data;

the determining process of the target control chart comprises the following steps:

determining the target control chart based on the number of measurement points of the display panel and an inter-group difference test result under the condition that the product characteristic of the display panel indicates that the measurement data of the display panel is metering data;

and determining the target control chart based on the existence of unqualified products and product defects in the display panel when the product characteristics of the display panel indicate that the measured data of the display panel are counting data.
The method of claim 6, wherein the determining the target control map based on the number of measurement points of the display panel and the inter-group difference test result includes any one of:

When the number of measurement point bits of the display panel is larger than a third set threshold value and the inter-group difference detection result indicates that the inter-group difference does not exist, taking a mean-range control chart as the target control chart;

when the number of measurement point bits of the display panel is larger than a third set threshold value and the inter-group difference detection result indicates that the inter-group difference exists, taking a mean value-moving range-range control chart as the target control chart;

when the number of the measured point bits of the display panel is smaller than or equal to a third set threshold value, if the number of the measured point bits is a fourth set threshold value, a single-value-moving range control chart is used as the target control chart;

when the number of measurement point bits of the display panel is smaller than or equal to a third set threshold, if the number of measurement point bits is not a fourth set threshold and the inter-group difference test result indicates that there is no inter-group difference, taking a mean-standard deviation control chart as the target control chart;

and when the number of the measurement point bits of the display panel is smaller than or equal to a third set threshold value, if the number of the measurement point bits is not a fourth set threshold value and the inter-group difference test result indicates that the inter-group difference exists, taking a mean-moving range-standard deviation control chart as the target control chart.
The method of claim 6, wherein the determining the target control map based on the presence of rejects and product defects in the display panel comprises:

when the defective products exist in the display panel, if the number of the defective products is constant, using a defective product numerical control chart as the target control chart;

if the number of defective products is not constant in the case where defective products exist in the display panel, using a defective rate control chart as the target control chart;

if the display panel has no unqualified products but has product defects, taking a unqualified numerical control chart as the target control chart if the product defects exist in a set area;

and when the display panel has no defective products but has a product defect, if the product defect does not exist in a set area, taking a numerical control drawing of defective products of unit product as the target control drawing.
The method of claim 6, wherein the method further comprises:

in response to receiving a target instruction, determining a product model of a display panel to be detected based on the target instruction;

And determining product characteristics of the display panel based on the product model.
The method of claim 1, wherein the display panel to be detected is sampled from a plurality of candidate display panels at a target sampling interval;

the determining process of the target sampling interval time comprises the following steps:

determining a first target probability value based on an upper control limit, a lower control limit, a center point after offset, and a historical standard deviation of the historical measurement data;

determining a desired risk value based on the first target probability value, an initial sampling interval time, hourly output of the historical measurement data, and the failure rate and first probability for each set time period;

and adjusting the initial sampling time interval based on the expected risk value to obtain the target sampling interval time.
The method according to claim 1, wherein the method further comprises:

partitioning a plurality of measurement points in the display panel based on the plurality of measurement data to obtain partition results of the plurality of measurement points, so as to respectively process the measurement data of the measurement points in different partitions based on the partition results.
The method according to claim 1, wherein the display panels are processed by a plurality of production devices, each display panel corresponds to a production information storage structure, the production information storage structure is used for storing device information of a production device for processing the corresponding display panel, the target control chart comprises data points corresponding to the display panels, and the data points are used for displaying the device information of the production device for processing the display panel in the target control chart after being triggered.
The method according to claim 1, wherein the method further comprises:

and determining a plurality of display panels processed by each production device based on the device information recorded in the production information storage structure of each display panel, and respectively recording the product information of the plurality of display panels processed by each production device into a production device management model, wherein the production device management model is used for recording the display panels processed by different production devices.
A data display method, the method comprising:

displaying a product management interface;

acquiring the product model of the display panel to be detected through the product management interface, and determining a target control chart based on the product model, wherein the target control chart is used for indicating the statistical data characteristics of each display panel;

In response to the submitting operation at the product management interface, displaying a target control chart and a control limit, wherein the target control chart is used for indicating the statistical data characteristics of each display panel, and the control limit is used for indicating the upper limit value and/or the lower limit value of the statistical data characteristics of the display panels meeting the production requirements;

the control limit is determined based on data form information, the data form information is determined based on target parameter values determined by a plurality of measured data of each display panel to be detected, the data form information is used for indicating whether the target measured data of the plurality of display panels has multi-group characteristics, and/or the data form information is used for indicating whether the target measured data of the plurality of display panels obeys normal distribution.
The method of claim 14, wherein the product management interface includes a product model setting control and a control diagram selection control;

the obtaining, through the product management interface, a product model of a display panel to be detected, and determining a target control chart based on the product model, includes:

acquiring the product model through the product model setting control;

Displaying at least one candidate control chart on the control chart selection control based on the product characteristics corresponding to the product model;

and in response to a selection operation on any candidate control graph, determining the selected candidate control graph as the target control graph.
The method of claim 15, wherein the product management interface further comprises a point location number setting control;

the method further comprises the steps of:

acquiring the number of measurement point bits set by the point position number setting control;

and displaying at least one candidate control chart on the control chart selection control based on the product characteristics corresponding to the product model and the acquired measuring point digits.
The method of claim 14, wherein the product management interface further comprises a zone setting control;

the method further comprises the steps of:

and responding to the triggering operation of the partition setting control, displaying a partition management interface, wherein the partition management interface is used for partitioning a plurality of measurement points in the display panel to obtain partition results of the measurement points, and respectively processing measurement data of the measurement points in different partitions based on the partition results.
The method of claim 14, wherein the product management interface further comprises at least one of:

the data acquisition management control is used for setting the type of the measurement data to be acquired and the data description information of the measurement data;

the device management control is used for acquiring device information of production devices of the display panel;

the data filtering control is used for setting conditions and data filtering modes which are met by the data to be filtered;

and the timing function setting control is used for setting the cycle period of the data acquisition and calculation process.
The method of claim 14, wherein the product management interface further comprises a control limit management control and/or a specification limit management control;

the control limit management control is used for adjusting the determined control limit;

the specification limit management control is used for adjusting the determined specification limit;

wherein the determined specification limit is determined based on the determined control limit.
The method according to claim 14, wherein the target control chart includes data points corresponding to each display panel, the display panels are processed by a plurality of production devices, each display panel corresponds to a production information storage structure, and the production information storage structure is used for storing device information of a production device for processing the corresponding display panel;

The method further comprises the steps of:

responding to triggering operation of any data point in a displayed target control chart, and acquiring equipment information of generating equipment for processing the display panel from a production information storage structure of the display panel corresponding to the data point;

and displaying the acquired equipment information.
A data processing apparatus, the apparatus comprising:

the acquisition module is used for acquiring a plurality of measurement data of each display panel to be detected;

a determining module configured to determine data morphology information indicating whether the target measurement data of the plurality of display panels has a multi-group characteristic by the target parameter value determined based on the plurality of measurement data, and/or whether the target measurement data of the plurality of display panels obeys a normal distribution, the target measurement data of each display panel being determined based on the plurality of measurement data of the display panels;

the determining module is further configured to determine, based on the data morphology information, a control limit of a target control chart, where the target control chart is used to indicate a statistical data feature of each display panel, and the control limit is used to indicate an upper limit and/or a lower limit of the statistical data feature of the display panel that meets a production requirement.
A data display device, the device comprising:

the display module is used for displaying a product management interface;

the processing module is used for acquiring the product model of the display panel to be detected through the product management interface, and determining a target control chart based on the product model, wherein the target control chart is used for indicating the statistical data characteristics of each display panel;

the display module is further used for responding to the submitting operation on the product management interface, displaying a target control chart and a control limit, wherein the target control chart is used for indicating the statistical data characteristics of each display panel, and the control limit is used for indicating the upper limit value and/or the lower limit value of the statistical data characteristics of the display panels meeting the production requirement;

the control limit is determined based on data form information, the data form information is determined based on target parameter values determined by a plurality of measured data of each display panel to be detected, the data form information is used for indicating whether the target measured data of the plurality of display panels has multi-group characteristics, and/or the data form information is used for indicating whether the target measured data of the plurality of display panels obeys normal distribution.
A computing device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor performs the operations performed by the data processing method of any one of claims 1 to 13 when the computer program is executed, or the operations performed by the data display method of any one of claims 14 to 20 when the computer program is executed.
A computer-readable storage medium, wherein a program is stored thereon, which when executed by a processor, implements operations performed by the data processing method according to any one of claims 1 to 13, or which when executed by a processor, implements operations performed by the data display method according to any one of claims 14 to 20.