CN116974806A

CN116974806A - Method and device for pushing abnormal message, storage medium and electronic equipment

Info

Publication number: CN116974806A
Application number: CN202310956126.5A
Authority: CN
Inventors: 徐婷婷; 樊斌; 陈嘉丰; 杨堃; 何德材; 吴建民; 王洪
Original assignee: BOE Technology Group Co Ltd; Beijing BOE Technology Development Co Ltd; Beijing Zhongxiangying Technology Co Ltd
Current assignee: BOE Technology Group Co Ltd; Beijing BOE Technology Development Co Ltd; Beijing Zhongxiangying Technology Co Ltd
Priority date: 2023-07-31
Filing date: 2023-07-31
Publication date: 2023-10-31

Abstract

The disclosure relates to a pushing method and device of an abnormal message, a storage medium and electronic equipment, and relates to the technical field of computers, wherein the method comprises the following steps: determining quality monitoring results of the substrate in a plurality of different quality monitoring dimensions according to current process parameters of the substrate in the production process; determining whether the substrate has abnormal substrate quality in the production process according to the quality monitoring result; when the substrate quality abnormality occurs in the production process of the substrate, generating an abnormal graphic message according to the quality monitoring result, and determining an abnormal grade of the substrate quality abnormality according to the quality monitoring result; and determining a first target client which is required to be pushed by the abnormal graphic message according to the abnormal grade, and pushing the abnormal graphic message to the first target client. The method improves the processing efficiency of the abnormal information.

Description

Method and device for pushing abnormal message, storage medium and electronic equipment

Technical Field

The embodiment of the disclosure relates to the technical field of computers, in particular to a pushing method of an abnormal message, a pushing device of the abnormal message, a computer readable storage medium and electronic equipment.

Background

In the existing message pushing method for the quality abnormality of the substrate in the production process, abnormal messages are pushed in a text mode through mails. However, this method makes the processing efficiency of the exception message low.

It should be noted that the information of the present invention in the above background section is only for enhancing understanding of the background of the present disclosure, and thus may include information that does not form the prior art that is already known to those of ordinary skill in the art.

Disclosure of Invention

An object of the present disclosure is to provide a pushing method of an abnormal message, a pushing device of an abnormal message, a computer readable storage medium, and an electronic device, so as to overcome at least to some extent the problem of low processing efficiency of an abnormal message due to limitations and drawbacks of the related art.

According to one aspect of the present disclosure, there is provided a pushing method of an exception message, including:

determining quality monitoring results of the substrate in a plurality of different quality monitoring dimensions according to current process parameters of the substrate in the production process;

determining whether the substrate has abnormal substrate quality in the production process according to the quality monitoring result;

When the substrate quality abnormality occurs in the production process of the substrate, generating an abnormal graphic message according to the quality monitoring result, and determining an abnormal grade of the substrate quality abnormality according to the quality monitoring result;

and determining a first target client which is required to be pushed by the abnormal graphic message according to the abnormal grade, and pushing the abnormal graphic message to the first target client.

In one exemplary embodiment of the present disclosure, the quality monitoring results in the plurality of different quality monitoring dimensions include a plurality of first quality monitoring results in a first quality monitoring dimension, second quality monitoring results in a second quality monitoring dimension, and third quality monitoring results in a third quality monitoring dimension;

the first quality monitoring dimension comprises a product specification quality monitoring dimension, the second quality monitoring dimension comprises a monitoring dimension of a development trend of a current process parameter, and the third quality monitoring dimension comprises a monitoring dimension of a process capability index of the substrate;

wherein, determining quality monitoring results of the substrate in a plurality of different quality monitoring dimensions according to current process parameters of the substrate in a production process comprises:

Acquiring current process parameters with a plurality of different time nodes generated in the production process of the substrate;

and determining a first quality monitoring result of the substrate in a product specification quality monitoring dimension, a second quality monitoring result of the substrate in a monitoring dimension of a development trend of the current process parameter and a third quality monitoring result of the substrate in a monitoring dimension of a process capability index according to the current process parameter.

In an exemplary embodiment of the present disclosure, determining a first quality monitoring result of the substrate in a product specification quality monitoring dimension according to the current process parameter includes:

obtaining standard technological parameters corresponding to the current technological parameters, and determining a central line according to the current technological parameters;

determining an upper control line and a lower control line according to the current process parameters and standard process parameters of a plurality of different time nodes, and constructing a parameter reference area according to the central line, the upper control line and the lower control line;

determining a first quality monitoring result of the substrate in a product specification quality monitoring dimension according to the position of the current process parameter in the parameter reference area;

the first quality monitoring result comprises at least one of a current process parameter on the central line, the current process parameter in a region range formed by the upper control line and the lower control line, the current process parameter on the upper control line or the lower control line and the current process parameter outside the parameter reference region.

In an exemplary embodiment of the present disclosure, determining, according to the current process parameter, a second quality monitoring result of the substrate in a monitoring dimension of a development trend of the current process parameter includes:

determining a first current variation trend of the current process parameter on a time sequence according to the current process parameters of a plurality of different time nodes, and acquiring a first standard variation trend of the current process parameter;

obtaining a second quality monitoring result corresponding to the monitoring dimension of the development trend of the current process parameter according to the first current variation trend and the first standard variation trend of the current process parameter on the time sequence;

the second quality monitoring result includes that the first current change trend is consistent with the first standard change trend, or the first current change trend is inconsistent with the first standard change trend.

In one exemplary embodiment of the present disclosure, determining a third quality monitoring result of the substrate in a monitoring dimension of a process capability index according to the current process parameter includes:

calculating process capability indexes of the substrate at a plurality of different time nodes according to the current process parameters, and acquiring a second standard variation trend of the process capability indexes;

Determining a second current change trend of the process capability index on a time sequence, and obtaining a third quality monitoring result corresponding to the monitoring dimension of the process capability index according to the second current change trend and the second standard change trend;

the third quality monitoring result includes that the second current change trend is consistent with the second standard change trend, or the second current change trend is inconsistent with the second standard change trend.

In an exemplary embodiment of the present disclosure, determining whether the substrate has an abnormal substrate quality during the production process according to the quality monitoring result includes:

determining whether the substrate has abnormal substrate quality in the production process according to the position of the current process parameter included in the first quality monitoring result in the parameter reference area, the first current change trend included in the second quality monitoring result and the second current change trend included in the third quality monitoring result;

and if any one of the current process parameters is not included on the central line, and/or the first current variation trend is inconsistent with the first standard variation trend, and/or the second current variation trend is inconsistent with the second standard variation trend, determining that the substrate has abnormal substrate quality in the production process.

In an exemplary embodiment of the present disclosure, determining an abnormality level of a substrate quality abnormality according to the quality monitoring result includes:

determining whether the current process parameter of the substrate is abnormal or not according to the position of the current process parameter included in the first quality monitoring result in the parameter reference area;

if the current process parameters are abnormal, judging whether the current process parameters are all included in the area range formed by the upper control line and the lower control line, and determining that the abnormal grade of the substrate quality abnormality is a first grade when the current process parameters are determined to be all included in the area range formed by the upper control line and the lower control line;

when any one of the current process parameters is determined to be included on an upper control line or a lower control line and the current process parameters are all included in a parameter reference area, determining that the abnormal grade of the substrate quality abnormality is a second grade;

and when any one of the current process parameters is determined to be included outside a parameter reference area, determining an abnormal level of the substrate quality abnormality as a third level.

Determining whether the variation trend of the current process parameter of the substrate is abnormal or not according to the first current variation trend included in the second quality monitoring result;

if the variation trend of the current process parameter is abnormal, determining a first trend variation range between the first current variation trend and a first standard variation trend;

if the first trend change range is smaller than a first range threshold value, determining that the abnormal grade of the substrate quality abnormality is a first grade;

if the first trend change range is larger than the first range threshold value and smaller than the second range threshold value, determining that the abnormal grade of the substrate quality abnormality is a second grade;

and if the first trend change range is larger than the second range threshold value, determining the abnormal grade of the substrate quality abnormality as a third grade.

determining whether the variation trend of the process capability index of the substrate is abnormal or not according to the second current variation trend included in the third quality monitoring result;

if the change trend of the process capability index is abnormal, determining a second trend change range between the second current change trend and a second standard change trend;

If the second trend change range is smaller than a third range threshold value, determining that the abnormal grade of the substrate quality abnormality is a first grade;

if the second trend change range is larger than the third range threshold and smaller than the fourth range threshold, determining that the abnormal grade of the substrate quality abnormality is a second grade;

and if the second trend change range is larger than the fourth range threshold value, determining the abnormal grade of the substrate quality abnormality as a third grade.

In an exemplary embodiment of the present disclosure, generating an abnormal graphic message according to the quality monitoring result includes:

and calling a message generating template required by generating the abnormal graphic message, and filling the quality monitoring result into the message generating template to obtain the abnormal graphic message.

In an exemplary embodiment of the present disclosure, invoking a message generation template required for generating the abnormal graphic message, and filling the quality monitoring result into the message generation template to obtain the abnormal graphic message, including:

if the current process parameters of the substrate are abnormal, a first message generating template corresponding to the current process parameters is called, and the current process parameters are filled into the first message template to obtain the abnormal graphic message; and/or

If the variation trend of the current process parameter of the substrate is abnormal, a second message generating template corresponding to the variation trend of the current process parameter is called, and the variation trend of the current process parameter is filled into the second message template to obtain the abnormal graphic message; and/or

And if the change trend of the process capability index of the substrate is abnormal, calling a third message generation template corresponding to the process capability index, and filling the process capability index and the change trend of the process capability index into the third message generation template to obtain the abnormal graphic message.

In an exemplary embodiment of the present disclosure, determining a first target client for pushing the abnormal graphic message according to the abnormal level includes:

and calling a first user identification list of a product responsible person corresponding to the abnormal grade, and determining a first target client which is required to be pushed by the abnormal graphic message according to a first target user identification in the first user identification list.

In an exemplary embodiment of the disclosure, after the step of determining that the substrate quality of the substrate is abnormal in the production process, the pushing method of the abnormal message further includes:

Invoking a preset substrate quality abnormality prediction model, and inputting the quality monitoring result into the substrate quality abnormality prediction model to obtain the current abnormality reason and the current abnormality treatment measure of the substrate with substrate quality abnormality;

and sending the current abnormality cause of the substrate quality abnormality and the current abnormality treatment measure to the first target client.

In an exemplary embodiment of the present disclosure, the pushing method of the exception message further includes:

acquiring stored first historical abnormal data, and extracting a first historical quality abnormal type, a first historical abnormal reason corresponding to the first historical quality abnormal type and a first historical processing measure in the first historical abnormal data;

acquiring registered second historical abnormal data, and extracting a second historical quality abnormal type, a second historical abnormal reason corresponding to the second historical quality abnormal type and a second historical processing measure in the second historical abnormal data;

constructing a data set according to a first historical quality anomaly type, a first historical anomaly cause and a first historical processing measure corresponding to the first historical quality anomaly type, a second historical anomaly cause and a second historical processing measure corresponding to the second historical quality anomaly type;

And training the network model to be trained based on the data set to obtain the substrate quality abnormality prediction model.

monitoring the processing progress of the first target user corresponding to the first target client side on the abnormal graphic message at intervals of preset time;

if the processing progress of the abnormal graphic message is unprocessed, calculating a time difference value between a current time node and a sending time node of the abnormal graphic message;

and determining a second target client side to which the abnormal graphic message needs to be pushed according to the time difference value, and pushing the abnormal graphic message to the second target client side.

According to one aspect of the present disclosure, there is provided a pushing apparatus for an exception message, including:

the quality monitoring result determining module is used for determining quality monitoring results of the substrate in a plurality of different quality monitoring dimensions according to the current process parameters of the substrate in the production process;

the substrate quality abnormality determining module is used for determining whether the substrate is abnormal in the substrate quality in the production process according to the quality monitoring result;

The abnormal graphic message generation module is used for generating an abnormal graphic message according to the quality monitoring result when the substrate quality abnormality occurs in the production process of the substrate, and determining the abnormal grade of the substrate quality abnormality according to the quality monitoring result;

and the abnormal graphic message pushing module is used for determining a first target client which is required to be pushed by the abnormal graphic message according to the abnormal grade and pushing the abnormal graphic message to the first target client.

According to one aspect of the present disclosure, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the pushing method of an exception message of any one of the above.

According to one aspect of the present disclosure, there is provided an electronic device including:

a processor; and

a memory for storing executable instructions of the processor;

wherein the processor is configured to perform the pushing method of the exception message of any one of the above via execution of the executable instructions.

According to the pushing method of the abnormal message, on one hand, quality monitoring results of the substrate in a plurality of different quality monitoring dimensions can be determined according to current technological parameters of the substrate in the production process; further determining whether the substrate quality is abnormal or not in the production process according to the quality monitoring result; then when the substrate quality abnormality occurs in the production process, generating an abnormal graphic message according to the quality monitoring result, and determining an abnormal grade of the substrate quality abnormality according to the quality monitoring result; finally, determining a first target client which needs to push the abnormal graphic message according to the abnormal grade, and pushing the abnormal graphic message to the first target client, wherein when the quality of the substrate is determined to be abnormal, the abnormal graphic message can be determined based on quality monitoring results on a plurality of different quality monitoring dimensions, so that the problem that in the prior art, whether the quality of the substrate is abnormal or not determined through a single dimension, which is caused by the fact that the quality of the substrate is determined through the single dimension is abnormal, so that the accuracy of a quality abnormality judging result is lower can be avoided; on the other hand, when the quality of the substrate is abnormal, an abnormal grade can be determined according to the quality monitoring result, and an abnormal graphic message is generated, so that the abnormal graphic message is pushed to a first target client corresponding to the abnormal grade, and the problem of low processing efficiency of the abnormal message caused by pushing the text message in a mail mode can be avoided; on the other hand, the first target client can be determined according to the abnormal grade so as to push the abnormal graphic message, so that the object pushed by the abnormal graphic message can be ensured to be a specific user side, and the abnormal graphic message can be effectively processed in time.

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 disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure. It will be apparent to those of ordinary skill in the art that the drawings in the following description are merely examples of the disclosure and that other drawings may be derived from them without undue effort.

Fig. 1 schematically illustrates a flowchart of a pushing method of an exception message according to an example embodiment of the present disclosure.

Fig. 2 schematically illustrates an exemplary diagram of a scenario for constructing a parameter reference area from current process parameters and standard process parameters according to an exemplary embodiment of the present disclosure.

Fig. 3 schematically illustrates a scene graph of a first current trend of variation according to an example embodiment of the present disclosure.

Fig. 4 schematically illustrates a scenario diagram of a second current trend of variation according to an example embodiment of the present disclosure.

Fig. 5 schematically illustrates an example diagram of a scenario in which a first target client is determined according to an anomaly level according to an example embodiment of the present disclosure.

Fig. 6 schematically illustrates an example diagram of a scenario in which a second target client is determined according to a time difference value according to an example embodiment of the present disclosure.

Fig. 7 schematically illustrates a block diagram of a pushing device of an exception message according to an example embodiment of the present disclosure.

Fig. 8 schematically illustrates an electronic device for implementing the pushing method of the above-mentioned exception message according to an exemplary embodiment of the present disclosure.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the present disclosure. One skilled in the relevant art will recognize, however, that the aspects of the disclosure may be practiced without one or more of the specific details, or with other methods, components, devices, steps, etc. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.

Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor devices and/or microcontroller devices.

Currently, TFT-LCD (Thin Film Transistor-Liquid Crystal Display, thin film transistor liquid crystal display) and OLED (Organic Light-Emitting Diode) displays are rapidly competing in the industry, the size of large-scale production lines and equipment in manufacturing workshops and the size of Glass substrates are increasingly large, and the quality demands of customers on products are increasingly strict; thus, implementing SPC (Statistical Process Control, statistical process-to-control) manages refinement and refinement is urgent.

In the practical application process, the larger the product quantity in unit time is, the larger the loss caused by abnormal product quality is; therefore, in order to effectively prevent and control quality anomalies and ensure customer product delivery period, timeliness and diversity of monitoring of SPC product anomalies, hierarchical emphasis of monitoring, progress and stagnation of problem processing, intelligent analysis of AI for problem pushing, visual imaging for problem pushing and management and control of low water level of product CPK (Complex Process Capability index, process capability index) are all the urgent. Based on this, the exemplary embodiments of the present disclosure provide a pushing method of an abnormal message, which can monitor quality anomalies of LCD and OLED substrates in a production process based on AI (Artificial Intelligence ), and timely generate an abnormal graphic message and push the abnormal graphic message to a corresponding client when the quality anomalies are monitored, so as to achieve the purposes of timely monitoring the quality anomalies of products and preventing failure of the produced substrates to cause failure in ensuring the exchange period of customer products.

In an example embodiment, a method for pushing an exception message is provided in this example embodiment, where the method may operate on a terminal device, a server cluster, or a cloud server; of course, those skilled in the art may also operate the methods of the present disclosure on other platforms as desired, which is not particularly limited in the present exemplary embodiment. Specifically, referring to fig. 1, the method for pushing the exception message may include the following steps:

s110, determining quality monitoring results of the substrate in a plurality of different quality monitoring dimensions according to current process parameters of the substrate in the production process;

s120, determining whether the substrate has abnormal substrate quality in the production process according to the quality monitoring result;

s130, when the substrate quality abnormality occurs in the production process of the substrate, generating an abnormal graphic message according to the quality monitoring result, and determining an abnormal grade of the substrate quality abnormality according to the quality monitoring result;

and S140, determining a first target client which is required to be pushed by the abnormal graphic message according to the abnormal grade, and pushing the abnormal graphic message to the first target client.

In the pushing method of the abnormal message, on one hand, the quality monitoring results of the substrate in a plurality of different quality monitoring dimensions can be determined according to the current technological parameters of the substrate in the production process; further determining whether the substrate quality is abnormal or not in the production process according to the quality monitoring result; then when the substrate quality abnormality occurs in the production process, generating an abnormal graphic message according to the quality monitoring result, and determining an abnormal grade of the substrate quality abnormality according to the quality monitoring result; finally, determining a first target client which needs to push the abnormal graphic message according to the abnormal grade, and pushing the abnormal graphic message to the first target client, wherein when the quality of the substrate is determined to be abnormal, the abnormal graphic message can be determined based on quality monitoring results on a plurality of different quality monitoring dimensions, so that the problem that in the prior art, whether the quality of the substrate is abnormal or not determined through a single dimension, which is caused by the fact that the quality of the substrate is determined through the single dimension is abnormal, so that the accuracy of a quality abnormality judging result is lower can be avoided; on the other hand, when the quality of the substrate is abnormal, an abnormal grade can be determined according to the quality monitoring result, and an abnormal graphic message is generated, so that the abnormal graphic message is pushed to a first target client corresponding to the abnormal grade, and the problem of low processing efficiency of the abnormal message caused by pushing the text message in a mail mode can be avoided; on the other hand, the first target client can be determined according to the abnormal grade so as to push the abnormal graphic message, so that the object pushed by the abnormal graphic message can be ensured to be a specific user side, and the abnormal graphic message can be effectively processed in time.

Hereinafter, a pushing method of an exception message according to an exemplary embodiment of the present disclosure will be further explained and illustrated with reference to the accompanying drawings.

First, nouns appearing in exemplary embodiments of the present disclosure are explained and illustrated.

TFT-LCD: thin film transistor liquid crystal display is a thin film transistor liquid crystal display.

OLED: organic Light-Emitting Diode, may also be referred to as Organic laser display, organic Light-Emitting semiconductor.

Push message.

Root cause analysis, root causes are analyzed.

Handling exceptions, handling exceptions.

Timely, in time.

Multitariate, multiple.

Grade, grade.

Antiski, anti-stagnation.

Anti-low water level, low water level is prevented.

SPC: statistical Process Control, statistical process control, is a quality management tool that uses statistical analysis techniques to monitor the production process in real time.

CPK: complex Process Capability Index, process capability index; wherein, the process capability index is an index used by modern enterprises to represent the process capability; meanwhile, the process capability is the ratio of the allowable maximum variation range of the process performance to the normal deviation of the process; in the practical process, the larger the CPK, the better the substrate quality.

Next, the objects of the exemplary embodiments of the present disclosure will be explained and illustrated. Specifically, the pushing method of the abnormal message recorded in the exemplary embodiment of the disclosure can automatically monitor quality abnormality of Glass substrates of large-generation large-size production lines based on TFT-LCD, OLED and the like; in the actual application process, the method can realize the monitored object, the pushing way of the abnormal graphic message, the presentation mode of the abnormal graphic message, the grading of the abnormal graphic message and the grading of the receiver, the AI intelligent analysis and processing abnormality and the closed-loop management scheme and the complete flow with the follow-up of the abnormality processing progress. That is, the method for pushing an exception message according to the exemplary embodiment of the present disclosure may achieve the following objects: in a first aspect, a multidimensional of anomaly monitoring object dimensions; in the second aspect, the abnormal graphic message pushing mode is timely and diversified; in a third aspect, visualization and patterning of a push mode of an abnormal graphic message; in the fourth aspect, the push object of the abnormal graphic message can realize grading precision and priority-grading re-dotting; in a fifth aspect, the exception handling root is intelligently analyzed by AI; in the sixth aspect, the processing progress of the abnormal graphic message is updated with the alert condition and then Check (monitoring) is prevented from being stagnated; the AI monitoring management can be realized on the product quality, so that the first time receipt of SPC early warning information can be effectively ensured, the trouble that the early warning is more and the layers are uneven is reduced, the abnormality is ensured to be processed timely and truly, the investigation direction or root cause analysis of the early warning is given out to guide the suggestion, the early warning is made on the product process capability, the product quality is effectively monitored, the product quality is effectively improved, and the customer satisfaction is improved.

In an example embodiment, first, the monitoring dimension of the CTQ (Critical to quality, quality key factor) characteristic of the product is increased, and the CPK low water level early warning of the product is monitored; in the actual application process, the traditional SPC has lower dimensionality for anomaly monitoring, and only one dimensionality monitors whether the current product (Glass) exceeds the specification limit or the control limit; however, the second monitoring dimension and the third monitoring dimension are added in the method, so that the upgrading of the product monitoring dimension is realized; meanwhile, the second monitoring dimension can be used for monitoring the historical data trend of the product so as to achieve the effect of early warning in advance; that is, the second monitoring dimension can perform early warning when the quality of the product is about to be problematic, so that the problem of the product quality can be avoided; the third monitoring dimension can be used for monitoring the process capability index of the product and predicting the future development trend; that is, by monitoring the CPK process capability index, the development trend and trend of future situation can be effectively predicted, and the quality problem can be prevented and controlled before the quality problem occurs, so as to achieve the purpose of avoiding the quality problem.

Secondly, monitoring abnormality timely and diversifying, and converting the abnormality monitoring to a mobile terminal of the mobile phone by traditional mail pushing and office computer checking; in the actual application process, the traditional SPC quality abnormality monitoring mail or portal pushes an alarm, the early warning mode has certain limitation and hysteresis, the timeliness of the mail and portal information is not high, the channel approach checked by an office computer is inconvenient, and the pushed information consumption mode is relatively passive and low-efficiency; however, the pushing mode of the enterprise WeChat and WeChat mobile phone APP is added in the embodiment of the disclosure, so that abnormal handling abnormality can be found more timely, more quickly and efficiently, quality abnormality can be avoided timely, loss is reduced to the minimum, or loss is killed in a cradle.

Then, carrying out visualized and graphical pushing on the quality abnormality to enable the message to be concise and the information quantity to be comprehensive; specifically, in the practical application process, the traditional quality exception pushing only has text, and the information presented by a plurality of characters is ambiguous; however, the exemplary embodiments of the present disclosure may perform message pushing in a visual and/or graphical manner; by the method, corresponding personnel can effectively and comprehensively master the abnormal quality condition, and further master the abnormal degree of the product and the trend of the situation development; for example, the corresponding personnel can clearly know the deviation degree and severity degree of the abnormal condition of the product from the current value, present the trend of abnormal development, present the time of abnormal occurrence, and decide the processing and scheme of the problem through the graphical information, and the graphical information plays a vital role in solving the abnormal condition of the product.

Next, upgrading the traditional full-member coverage pushing into grading pushing and pushing aiming at different groups; specifically, in the practical application process, the traditional SPC quality abnormality pushing object is covered by a whole member, the pushing mode is simple but not accurate enough, and an engineer or a leader receives a large amount of information so as to be unable to discover the alert condition of quality abnormality in time, thereby causing serious quality accidents; however, the pushing object in the disclosed example embodiment is upgraded to alarm hierarchical pushing and pushing for different levels of groups, so that abnormal information can be properly and properly pushed to a problem handler, the abnormal alarm is prevented from disturbing the normal work of engineers, and the alarm in own responsibility is prevented from being missed due to too many alarms.

Furthermore, AI can only analyze reasons and push the processing scheme for the abnormality; specifically, in the practical application process, the traditional quality abnormality pushing can only indicate that a problem occurs, can not give directional suggestions to the root cause of the occurrence of the problem, and can not give guiding suggestions to the corresponding strategies of the problem; the AI intelligent quality abnormality monitoring method recorded in the disclosed example embodiment can analyze the abnormality cause and give a guiding processing scheme when monitoring quality abnormality; for example, when the equivalent measuring device detects abnormality, the process device with the problem can be fed back quickly, the process device with the abnormality can be fed back timely, the root cause of the problem can be positioned quickly, the solution can be deduced by combining the historical data, and the like, so that the problems can be found timely, responded quickly and solved properly.

Finally, monitoring the progress of the exception handling, and upgrading and pushing the exception handling hysteresis; specifically, in the actual application process, the traditional SPC quality monitoring can only be used for notifying the exception and ending, and an engineer can not receive the exception and timely process the exception and not follow the exception, so that the quality exception is difficult to be timely processed; meanwhile, in order to ensure that the quality abnormality is responded quickly and processed in time, the abnormality processing progress is monitored, the monitoring method in the patent carries out alert ascending on the quality abnormality which is not processed for a long time, and pushes or changes the interface theme color of the system to a higher level leader in time so as to stop damage in time and prevent the quality problem from being enlarged and minimizing the damage.

Hereinafter, a pushing method of the abnormal message shown in fig. 1 will be further explained and explained. Specific:

in step S110, quality monitoring results of the substrate in a plurality of different quality monitoring dimensions are determined according to current process parameters of the substrate during production.

Specifically, the quality monitoring results in the plurality of different quality monitoring dimensions described herein include a first quality monitoring result in a first quality monitoring dimension, a second quality monitoring result in a second quality monitoring dimension, a third quality monitoring result in a third quality monitoring dimension, and so on; meanwhile, the first quality monitoring dimension comprises a product specification quality monitoring dimension, the second quality monitoring dimension comprises a monitoring dimension of the development trend of the current process parameter, and the third quality monitoring dimension comprises a monitoring dimension of the process capability index of the substrate; that is, the first quality monitoring dimension may be used to monitor the specifications of the substrate; the second monitoring dimension can be used for monitoring the historical data trend of the product so as to achieve the effect of early warning in advance; that is, the second monitoring dimension can perform early warning when the quality of the product is about to be problematic, so that the problem of the product quality can be avoided; the third monitoring dimension can be used for monitoring the process capability index of the product and predicting the future development trend; that is, by monitoring the Cpk process capability index, the development trend and trend of future situation can be effectively predicted, and the quality problem can be prevented and controlled before the quality problem occurs, so as to achieve the purpose of avoiding the quality problem.

In an example embodiment, determining quality monitoring results of a substrate in a plurality of different quality monitoring dimensions based on current process parameters of the substrate during production may be accomplished by: firstly, acquiring current process parameters with a plurality of different time nodes generated in the production process of the substrate; and secondly, determining a first quality monitoring result of the substrate in a product specification quality monitoring dimension, a second quality monitoring result of the substrate in a monitoring dimension of the development trend of the current process parameter and a third quality monitoring result of the monitoring dimension of the process capability index according to the current process parameter. Specifically, the current process parameters described herein with a plurality of different time nodes may be uploaded by the quality monitoring device in real time during the substrate manufacturing process at intervals of corresponding time periods; that is, in the process of manufacturing the substrate, the quality monitoring device may acquire the current process parameters of the substrate in real time and upload the current process parameters to the corresponding terminal device or server; the current process parameters described herein may include, but are not limited to, substrate thickness, emission spectrum and color coordinates, emission brightness, threshold voltage, etc.; in the actual application process, the corresponding process parameters may be obtained according to actual needs, which is not particularly limited in this example.

In an example embodiment, determining the first quality monitoring result of the substrate in the product specification quality monitoring dimension according to the current process parameter may be implemented as follows: firstly, obtaining standard technological parameters corresponding to current technological parameters, and determining a central line according to the current technological parameters; secondly, determining an upper control line and a lower control line according to the current process parameters and standard process parameters of a plurality of different time nodes, and constructing a parameter reference area according to the central line, the upper control line and the lower control line; then, determining a first quality monitoring result of the substrate in a product specification quality monitoring dimension according to the position of the current process parameter in the parameter reference area; the first quality monitoring result comprises at least one of a current process parameter on the central line, the current process parameter in a region range formed by the upper control line and the lower control line, the current process parameter on the upper control line or the lower control line and the current process parameter outside the parameter reference region. Specifically, in the practical application process, the standard process parameters can be set as a center line (Upper center line), and then UCL (Upper center line) higher than the center line and LCL (Lower center line) Lower than the center line are set; meanwhile, the upper control line is a central line +3σ; wherein sigma is the standard deviation of the current process parameters; the lower control line is the central line-3 sigma; wherein, a specific example diagram of a scene may be shown with reference to fig. 2; it should be noted that, in order to obtain a relatively accurate first quality monitoring result, the data size of the current process parameters of the plurality of different time nodes to be selected herein may be the latest 25 current process parameters; in the actual application process, the current process parameters can be stored in a temporary block table; when quality monitoring is required, the latest 25 current process parameters can be obtained from the block table, and then a corresponding data comparison process is performed.

In an example embodiment, determining, according to the current process parameter, a second quality monitoring result of the substrate in a monitoring dimension of a development trend of the current process parameter may be implemented as follows: firstly, determining a first current variation trend of a current process parameter on a time sequence according to current process parameters of a plurality of different time nodes, and acquiring a first standard variation trend of the current process parameter; secondly, obtaining a second quality monitoring result corresponding to the monitoring dimension of the development trend of the current process parameter according to the first current variation trend and the first standard variation trend of the current process parameter on the time sequence; the second quality monitoring result includes that the first current change trend is consistent with the first standard change trend, or the first current change trend is inconsistent with the first standard change trend. Specifically, in the actual application process, the time point at which each current process parameter is monitored is taken as an abscissa, and the actual value of each current process parameter is taken as an ordinate, so that a first current change trend graph is drawn; wherein, a specific scene graph of the first current variation trend may be shown with reference to fig. 3; furthermore, the first current change trend graph and the first standard change trend graph can be placed into the same coordinate system for comparison, so that a second quality monitoring result is obtained. It should be noted here that the second quality monitoring result may also be determined directly from the first current trend; for example, if the trend of continuous rising or continuous falling or long term is on the same side as the target value and is not corrected in time, the occurrence of abnormality can be determined; in the actual application process, determination may be performed according to actual needs, which is not particularly limited in this example.

In an example embodiment, determining a third quality monitoring result of the substrate in a monitoring dimension of a process capability index according to the current process parameter may be implemented as follows: firstly, calculating process capability indexes of the substrate at a plurality of different time nodes according to the current process parameters, and acquiring a second standard variation trend of the process capability indexes; secondly, determining a second current change trend of the process capability index on a time sequence, and obtaining a third quality monitoring result corresponding to the monitoring dimension of the process capability index according to the second current change trend and a second standard change trend; the third quality monitoring result includes that the second current change trend is consistent with the second standard change trend, or the second current change trend is inconsistent with the second standard change trend. Specifically, the process capability index described herein may be calculated as follows:

CPK＝Min[(USL-Mu)/3σ，(Mu-LSL)/3σ]

wherein sigma is the standard deviation of the current technological parameter, USL is an upper control line, LSL is a lower control line, mu is a central value; meanwhile, the second current trend may be obtained as shown in fig. 4; it should be noted here that, by monitoring the Cpk process capability index, when data reported by the equipment is received, cpk of the last 25 data in the model is calculated, and if Cpk is less than 1 or greater than 1.33, an early warning is sent.

In step S120, it is determined whether the substrate has abnormal substrate quality during the production process according to the quality monitoring result.

Specifically, determining whether the substrate quality abnormality occurs in the production process of the substrate can be achieved by: determining whether the substrate has abnormal substrate quality in the production process according to the position of the current process parameter included in the first quality monitoring result in the parameter reference area, the first current change trend included in the second quality monitoring result and the second current change trend included in the third quality monitoring result; and if any one of the current process parameters is not included on the central line, and/or the first current variation trend is inconsistent with the first standard variation trend, and/or the second current variation trend is inconsistent with the second standard variation trend, determining that the substrate has abnormal substrate quality in the production process. Specifically, in the actual application process, if the current process parameter is consistent with the central line, the current process parameter can be considered to be normal; if the current process parameter falls between the upper control line and the lower control line, or exceeds the upper control line or the lower control line (i.e., the current process parameter is greater than the upper control line or less than the lower control line), then the current process parameter may be determined to be abnormal. Further, it may also be determined whether the substrate quality is abnormal based on the first current trend of the current process parameter and the second current trend of the process capability index. In the practical application process, a plurality of different dimensions can be comprehensively considered, and whether the substrate quality is abnormal in the production process or not is further determined based on the comprehensive considered result.

In step S130, when it is determined that the substrate quality abnormality occurs in the production process, an abnormality graphic message is generated according to the quality monitoring result, and an abnormality level of the substrate quality abnormality is determined according to the quality monitoring result.

In the present exemplary embodiment, first, an abnormal graphic message is generated according to a quality monitoring result; specifically, the method can be realized by the following steps: and calling a message generating template required by generating the abnormal graphic message, and filling the quality monitoring result into the message generating template to obtain the abnormal graphic message. Calling a message generation template required for generating the abnormal graphic message, and filling the quality monitoring result into the message generation template to obtain the abnormal graphic message, wherein the abnormal graphic message can be realized by the following steps of: the first implementation way is: if the current process parameters of the substrate are abnormal, a first message generating template corresponding to the current process parameters is called, and the current process parameters are filled into the first message template to obtain the abnormal graphic message; the second implementation mode is as follows: if the variation trend of the current process parameter of the substrate is abnormal, a second message generating template corresponding to the variation trend of the current process parameter is called, and the variation trend of the current process parameter is filled into the second message template to obtain the abnormal graphic message; the third implementation mode is as follows: and if the change trend of the process capability index of the substrate is abnormal, calling a third message generation template corresponding to the process capability index, and filling the process capability index and the change trend of the process capability index into the third message generation template to obtain the abnormal graphic message.

Hereinafter, a specific generation process of the abnormal graphic message will be further explained and explained. Specifically, in the actual application process, a plurality of different templates can be preset and stored in a corresponding database, and when an abnormal graphic message needs to be generated, a message generation template of a corresponding type can be called to generate the abnormal graphic message based on the message generation template. For example, if the specification of the current process parameter is abnormal, a first message generating template corresponding to the current process parameter can be directly called, and the current process parameter is filled into the first message template; meanwhile, the abnormal current process parameters can be identified in the first message template, so that corresponding abnormal graphic messages are obtained; for another example, if the variation trend of the current process parameter is abnormal, a second message generating template corresponding to the variation trend of the current process parameter may be directly called, and the variation trend of the current process parameter is filled into the second message template; meanwhile, the part with abnormal variation trend of the current technological parameter can be marked in the second message template, so that a corresponding abnormal graphic message is obtained; for another example, if the trend of the process capability index is abnormal, a third message generation template corresponding to the process capability index may be called, and the trend of the process capability index is filled into the third message template; meanwhile, the part with abnormal change trend of the process capability index can be identified in the third message template, so that a corresponding abnormal graphic message is obtained. Furthermore, in the process of generating the abnormal graphic message, the data in the text can be generated into a graph (a line graph, a bar graph, a pie graph and the like) through JFreeChart, highcharts-server-export and Java Chart of Java, so that the abnormal graphic message is further obtained.

In one possible example embodiment, the anomaly graphic messages described herein may include one or more, i.e., may include only anomaly graphic messages corresponding to current process parameters or anomaly graphic messages corresponding to trends in current process parameters or anomaly graphic messages corresponding to process capability indices; in the actual application process, the corresponding abnormal graphic message may be generated according to the actual situation, which is not particularly limited in this example. In a possible example embodiment, a plurality of different abnormal situations may be placed in the same message template to obtain an abnormal graphic message, or may be implemented separately, which is not particularly limited in this example.

It should be further noted that, in the actual application process, there may be a case where only the current process parameter is abnormal and the process capability index and the trend of the current process parameter are not abnormal; naturally, the current process parameters and the change trend of the current process parameters are abnormal, and the process capacity index is not abnormal; there is also a possibility that abnormality occurs in all three; other situations may also occur, which is not particularly limited by the present example.

In an example embodiment, the anomaly cause reference and the processing means reference for the substrate quality anomaly may also be included in the anomaly graphic message. That is, the pushing method of the exception message may further include: invoking a preset substrate quality abnormality prediction model, and inputting the quality monitoring result into the substrate quality abnormality prediction model to obtain the current abnormality reason and the current abnormality treatment measure of the substrate with substrate quality abnormality; and sending the current abnormality cause of the substrate quality abnormality and the current abnormality treatment measure to the first target client. That is, in the practical application process, the current abnormality cause of the substrate quality abnormality and the current abnormality treatment measure can be predicted in an artificial intelligence manner, so that corresponding personnel can adjust the production and manufacturing process of the substrate in time based on the current abnormality cause and the current abnormality treatment measure, thereby achieving the purpose of reducing loss.

In one example embodiment, the training process of the substrate quality anomaly prediction model may be implemented as follows: firstly, acquiring stored first historical abnormal data, and extracting a first historical quality abnormal type, a first historical abnormal reason corresponding to the first quality abnormal type and a first historical processing measure in the first historical abnormal data; secondly, acquiring registered second historical abnormal data, and extracting a second historical quality abnormal type, a second historical abnormal reason corresponding to the second quality abnormal type and a second historical processing measure in the second historical abnormal data; then, constructing a data set according to a first historical quality anomaly type, a first historical anomaly cause corresponding to the first quality anomaly type, a first historical processing measure, a second historical quality anomaly type, a second historical anomaly cause corresponding to the second quality anomaly type and a second historical processing measure; finally, training a network model to be trained based on the data set to obtain the substrate quality anomaly prediction model; the network model to be trained described herein can include, but is not limited to, a convolutional neural network model, a cyclic neural network model, a deep neural network model, a decision tree model and the like; in the actual application process, the corresponding model can be selected according to actual needs, and the embodiment is not particularly limited.

It should be further added that, during the construction of the data set, the corresponding data sources may include, but are not limited to, the following two aspects: in one aspect, historical data is accumulated; on the other hand, basic data of user registration is accumulated; meanwhile, because the historical data and the basic data are comprehensively considered in the model training process, when the current abnormality cause and the current abnormality treatment measure are predicted, the cause and the treatment method of the type of alarm can be directly output if the type of alarm occurs, and the scheme output is performed according to the occurrence probability; furthermore, as the user can register the corresponding abnormality of the corresponding type of alarm in the database in advance, when the current abnormality cause and the current abnormality treatment measure are predicted, the association relation between the product characteristics and the equipment state parameters can be determined through analyzing the related parameters, when the alarm occurs, the parameter information related to the current equipment state of the equipment for producing the product is pushed, and the corresponding current abnormality cause and the current abnormality treatment measure are output.

And secondly, determining the abnormal grade of the substrate quality abnormality according to the quality monitoring result. Specifically, the determination of the anomaly level can be realized in the following centralized manner: according to the first implementation mode, whether the current process parameters of the substrate are abnormal or not is determined according to the positions of the current process parameters included in the first quality monitoring result in the parameter reference area; if the current process parameters are abnormal, judging whether the current process parameters are all included in the area range formed by the upper control line and the lower control line, and determining that the abnormal grade of the substrate quality abnormality is a first grade when the current process parameters are determined to be all included in the area range formed by the upper control line and the lower control line; when any one of the current process parameters is determined to be included on an upper control line or a lower control line and the current process parameters are all included in a parameter reference area, determining that the abnormal grade of the substrate quality abnormality is a second grade; and when any one of the current process parameters is determined to be included outside a parameter reference area, determining an abnormal level of the substrate quality abnormality as a third level. That is, in the actual application process, first, the position of the current process parameter may be determined in the parameter reference area according to the magnitude of the current process parameter, and then the corresponding level may be determined according to the position of each current process parameter in the parameter reference area; if all the current process parameters are in the upper control line and lower control line areas (excluding the upper control line and the lower control line), determining that the deviation of the current process parameters from the target value is smaller, and determining that the corresponding abnormal grade is the first grade; if the current process parameters included in the upper control line or the lower control line exist, but all the current process parameters are included in the parameter reference area, determining that the deviation of the current process parameters from the target value is slightly larger, and determining that the corresponding abnormal grade is a second grade; if the current process parameters included outside the parameter reference area range exist, the current process parameters are determined to have larger deviation from the target value, and the corresponding abnormal grade is determined to be a third grade.

The second implementation mode is as follows: determining whether the variation trend of the current process parameter of the substrate is abnormal or not according to the first current variation trend included in the second quality monitoring result; if the variation trend of the current process parameter is abnormal, determining a first trend variation range between the first current variation trend and a first standard variation trend; if the first trend change range is smaller than a first range threshold value, determining that the abnormal grade of the substrate quality abnormality is a first grade; if the first trend change range is larger than the first range threshold value and smaller than the second range threshold value, determining that the abnormal grade of the substrate quality abnormality is a second grade; and if the first trend change range is larger than the second range threshold value, determining the abnormal grade of the substrate quality abnormality as a third grade. In the practical application process, the difference between the first current change trend and the two points at the same position in the first standard change trend can be calculated, and then the corresponding trend change range is determined according to the difference, and further the corresponding grade is determined.

The third implementation mode is as follows: determining whether the variation trend of the process capability index of the substrate is abnormal or not according to the second current variation trend included in the third quality monitoring result; if the change trend of the process capability index is abnormal, determining a second trend change range between the second current change trend and a second standard change trend; if the second trend change range is smaller than a third range threshold value, determining that the abnormal grade of the substrate quality abnormality is a first grade; if the second trend change range is larger than the third range threshold and smaller than the fourth range threshold, determining that the abnormal grade of the substrate quality abnormality is a second grade; and if the second trend change range is larger than the fourth range threshold value, determining the abnormal grade of the substrate quality abnormality as a third grade. In the practical application process, the difference between the points at two identical positions in the second current change trend and the second standard change trend can be calculated, and then the corresponding trend change range is determined according to the difference, and then the corresponding grade is determined.

In step S140, a first target client that needs to push the abnormal graphic message is determined according to the abnormal level, and the abnormal graphic message is pushed to the first target client.

In the present exemplary embodiment, first, a first target client to which an abnormal graphic message needs to be pushed is determined according to an abnormal level; specifically, the method can be realized by the following steps: and calling a first user identification list of a product responsible person corresponding to the abnormal grade, and determining a first target client which is required to be pushed by the abnormal graphic message according to a first target user identification in the first user identification list. That is, in the actual application process, the responsible person of the corresponding level can be stored in the corresponding position in advance, and when the abnormality occurs, the corresponding responsible person can be directly matched according to the abnormal level, so that the purpose of timely processing the abnormal graphic message is achieved; for example, in ranking job levels and business areas of a population of people, a common engineer may be defined as a first level, a base manager may be defined as a second level, and a middle manager may be defined as a third level; in the actual application process, abnormal graphic messages of corresponding levels can be directly sent to groups of corresponding levels and lower levels, such as a first level alarm sent to a first level person, a second level alarm sent to a second level and a first level person, a third level alarm sent to a third level, a second level and the first level person, and so on; an exemplary diagram of a specific application scenario may be shown in fig. 5.

Further, after the first target client determines that the first target client is finished, the abnormal graphic message can be pushed to the first target client; specifically, in the process of pushing the abnormal graphic message, the method can be realized by the following steps: pushing an abnormal graphic message to enterprise WeChat; specifically, by calling an interface of enterprise WeChat, creating an application and pulling personnel of a corresponding group, an alarm message can be pushed at a mobile phone end (instant message sending is realized through enterprise ID (identity) and application ID agent); pushing the abnormal graphic message to a private WeChat; specifically, by calling the WeChat interface, the public number is created, and people in the corresponding group pay attention to the public number, the alarm message can be pushed at the mobile phone end (the message is sent through the APP_ID and the TOKEN). By the method, corresponding personnel can see the corresponding abnormal graphic message when viewing the WeChat message, so that timeliness of processing the abnormal graphic message is improved.

In an example embodiment, the method for pushing the exception message provided by the example embodiment of the present disclosure may further include: monitoring the processing progress of the abnormal graphic message by the first target user corresponding to the first target client at intervals of preset time; if the processing progress of the abnormal graphic message is unprocessed, calculating a time difference value between a current time node and a sending time node of the abnormal graphic message; and determining a second target client side to which the abnormal graphic message needs to be pushed according to the time difference value, and pushing the abnormal graphic message to the second target client side. That is, in the process of actual application, a timing task can be created to scan the processing progress of the abnormal graphic message at fixed time; if the processing is not finished, determining the client needing to be sent again based on the corresponding time difference value; for example, a default exception is placed for 1 hour and is sent to the personnel corresponding to the level A, and an exception is placed for 2 hours and is sent to the personnel corresponding to the level B; by analogy, the longer the interval, the higher the level of personnel corresponding to the second target client to be transmitted; wherein, a specific implementation scene graph can be shown with reference to fig. 6; when the user corresponding to the corresponding second target client receives the abnormal graphic message, the corresponding responsible person can be informed manually to process the abnormal graphic message in time, so that the purpose of processing the abnormal graphic message in time is achieved.

Thus, the method for pushing the exception message according to the exemplary embodiment of the present disclosure has been fully implemented, and based on the foregoing description, it can be known that the method for pushing the exception message according to the exemplary embodiment of the present disclosure has at least the following advantages: on one hand, the dimension of the abnormal monitoring object is three-dimensional, and the abnormal pushing mode is timely and diversified; on the other hand, the visualization and the graphics of the abnormal pushing mode are realized, the grading of the abnormal pushing object is accurate, and the abnormal pushing object is subjected to priority-based re-pointing; on the other hand, the exception handling root is intelligently analyzed by AI, and the exception handling progress is updated with the alarm condition and then Check anti-stagnation is carried out; meanwhile, the problems of inaccuracy and unreasonable production process with high productivity and high value are solved, the accuracy and the precision of control limits are further improved, the precision degree of data classification and lean calculation is improved, and the possibility of production loss and potential unknown risks caused by quality problems in the production process are reduced due to excessive analysis and insufficient analysis in the SPC analysis process.

The following are device embodiments of the present disclosure that may be used to perform method embodiments of the present disclosure. For details not disclosed in the embodiments of the apparatus of the present disclosure, please refer to the embodiments of the method of the present disclosure.

The embodiment of the disclosure also provides a pushing device of the abnormal message. Specifically, referring to fig. 7, the pushing device for the abnormal message may include a quality monitoring result determining module 710, a substrate quality abnormality determining module 720, an abnormal graphic message generating module 730, and an abnormal graphic message pushing module 740. Wherein:

the quality monitoring result determining module 710 may be configured to determine quality monitoring results of the substrate in a plurality of different quality monitoring dimensions according to current process parameters of the substrate during a production process;

the substrate quality abnormality determining module 720 may be configured to determine whether a substrate quality abnormality occurs in the substrate during the production process according to the quality monitoring result;

the abnormal graphic message generating module 730 may be configured to generate an abnormal graphic message according to the quality monitoring result when it is determined that the substrate quality is abnormal in the production process of the substrate, and determine an abnormal level of the substrate quality abnormality according to the quality monitoring result;

the abnormal graphic message pushing module 740 may be configured to determine a first target client that needs to be pushed by the abnormal graphic message according to the abnormal level, and push the abnormal graphic message to the first target client.

In one exemplary embodiment of the present disclosure, the quality monitoring results in the plurality of different quality monitoring dimensions include a plurality of first quality monitoring results in a first quality monitoring dimension, second quality monitoring results in a second quality monitoring dimension, and third quality monitoring results in a third quality monitoring dimension; the first quality monitoring dimension comprises a product specification quality monitoring dimension, the second quality monitoring dimension comprises a monitoring dimension of a development trend of a current process parameter, and the third quality monitoring dimension comprises a monitoring dimension of a process capability index of the substrate;

wherein, determining quality monitoring results of the substrate in a plurality of different quality monitoring dimensions according to current process parameters of the substrate in a production process comprises: acquiring current process parameters with a plurality of different time nodes generated in the production process of the substrate; and determining a first quality monitoring result of the substrate in a product specification quality monitoring dimension, a second quality monitoring result of the substrate in a monitoring dimension of a development trend of the current process parameter and a third quality monitoring result of the substrate in a monitoring dimension of a process capability index according to the current process parameter.

In an exemplary embodiment of the present disclosure, determining a first quality monitoring result of the substrate in a product specification quality monitoring dimension according to the current process parameter includes: obtaining standard technological parameters corresponding to the current technological parameters, and determining a central line according to the current technological parameters; determining an upper control line and a lower control line according to the current process parameters and standard process parameters of a plurality of different time nodes, and constructing a parameter reference area according to the central line, the upper control line and the lower control line; determining a first quality monitoring result of the substrate in a product specification quality monitoring dimension according to the position of the current process parameter in the parameter reference area; the first quality monitoring result comprises at least one of a current process parameter on the central line, the current process parameter in a region range formed by the upper control line and the lower control line, the current process parameter on the upper control line or the lower control line and the current process parameter outside the parameter reference region.

In an exemplary embodiment of the present disclosure, determining, according to the current process parameter, a second quality monitoring result of the substrate in a monitoring dimension of a development trend of the current process parameter includes: determining a first current variation trend of the current process parameter on a time sequence according to the current process parameters of a plurality of different time nodes, and acquiring a first standard variation trend of the current process parameter; obtaining a second quality monitoring result corresponding to the monitoring dimension of the development trend of the current process parameter according to the first current variation trend and the first standard variation trend of the current process parameter on the time sequence; the second quality monitoring result includes that the first current change trend is consistent with the first standard change trend, or the first current change trend is inconsistent with the first standard change trend.

In one exemplary embodiment of the present disclosure, determining a third quality monitoring result of the substrate in a monitoring dimension of a process capability index according to the current process parameter includes: calculating process capability indexes of the substrate at a plurality of different time nodes according to the current process parameters, and acquiring a second standard variation trend of the process capability indexes; determining a second current change trend of the process capability index on a time sequence, and obtaining a third quality monitoring result corresponding to the monitoring dimension of the process capability index according to the second current change trend and the second standard change trend; the third quality monitoring result includes that the second current change trend is consistent with the second standard change trend, or the second current change trend is inconsistent with the second standard change trend.

In an exemplary embodiment of the present disclosure, determining whether the substrate has an abnormal substrate quality during the production process according to the quality monitoring result includes: determining whether the substrate has abnormal substrate quality in the production process according to the position of the current process parameter included in the first quality monitoring result in the parameter reference area, the first current change trend included in the second quality monitoring result and the second current change trend included in the third quality monitoring result; and if any one of the current process parameters is not included on the central line, and/or the first current variation trend is inconsistent with the first standard variation trend, and/or the second current variation trend is inconsistent with the second standard variation trend, determining that the substrate has abnormal substrate quality in the production process.

In an exemplary embodiment of the present disclosure, determining an abnormality level of a substrate quality abnormality according to the quality monitoring result includes: determining whether the current process parameter of the substrate is abnormal or not according to the position of the current process parameter included in the first quality monitoring result in the parameter reference area; if the current process parameters are abnormal, judging whether the current process parameters are all included in the area range formed by the upper control line and the lower control line, and determining that the abnormal grade of the substrate quality abnormality is a first grade when the current process parameters are determined to be all included in the area range formed by the upper control line and the lower control line; when any one of the current process parameters is determined to be included on an upper control line or a lower control line and the current process parameters are all included in a parameter reference area, determining that the abnormal grade of the substrate quality abnormality is a second grade; and when any one of the current process parameters is determined to be included outside a parameter reference area, determining an abnormal level of the substrate quality abnormality as a third level.

In an exemplary embodiment of the present disclosure, determining an abnormality level of a substrate quality abnormality according to the quality monitoring result includes: determining whether the variation trend of the current process parameter of the substrate is abnormal or not according to the first current variation trend included in the second quality monitoring result; if the variation trend of the current process parameter is abnormal, determining a first trend variation range between the first current variation trend and a first standard variation trend; if the first trend change range is smaller than a first range threshold value, determining that the abnormal grade of the substrate quality abnormality is a first grade; if the first trend change range is larger than the first range threshold value and smaller than the second range threshold value, determining that the abnormal grade of the substrate quality abnormality is a second grade; and if the first trend change range is larger than the second range threshold value, determining the abnormal grade of the substrate quality abnormality as a third grade.

In an exemplary embodiment of the present disclosure, determining an abnormality level of a substrate quality abnormality according to the quality monitoring result includes: determining whether the variation trend of the process capability index of the substrate is abnormal or not according to the second current variation trend included in the third quality monitoring result; if the change trend of the process capability index is abnormal, determining a second trend change range between the second current change trend and a second standard change trend; if the second trend change range is smaller than a third range threshold value, determining that the abnormal grade of the substrate quality abnormality is a first grade; if the second trend change range is larger than the third range threshold and smaller than the fourth range threshold, determining that the abnormal grade of the substrate quality abnormality is a second grade; and if the second trend change range is larger than the fourth range threshold value, determining the abnormal grade of the substrate quality abnormality as a third grade.

In an exemplary embodiment of the present disclosure, generating an abnormal graphic message according to the quality monitoring result includes: and calling a message generating template required by generating the abnormal graphic message, and filling the quality monitoring result into the message generating template to obtain the abnormal graphic message.

In an exemplary embodiment of the present disclosure, invoking a message generation template required for generating the abnormal graphic message, and filling the quality monitoring result into the message generation template to obtain the abnormal graphic message, including: if the current process parameters of the substrate are abnormal, a first message generating template corresponding to the current process parameters is called, and the current process parameters are filled into the first message template to obtain the abnormal graphic message; and/or if the variation trend of the current process parameter of the substrate is abnormal, calling a second message generating template corresponding to the variation trend of the current process parameter, and filling the variation trend of the current process parameter into the second message template to obtain the abnormal graphic message; and/or if the change trend of the process capability index of the substrate is abnormal, calling a third message generation template corresponding to the process capability index, and filling the process capability index and the change trend of the process capability index into the third message generation template to obtain the abnormal graphic message.

In an exemplary embodiment of the present disclosure, determining a first target client for pushing the abnormal graphic message according to the abnormal level includes: and calling a first user identification list of a product responsible person corresponding to the abnormal grade, and determining a first target client which is required to be pushed by the abnormal graphic message according to a first target user identification in the first user identification list.

In an exemplary embodiment of the present disclosure, the pushing device of the exception message further includes:

the abnormal cause determining module can be used for calling a preset substrate quality abnormal prediction model, and inputting the quality monitoring result into the substrate quality abnormal prediction model to obtain the current abnormal cause of the substrate quality abnormality and the current abnormal treatment measure of the substrate;

and the abnormality cause sending module is used for sending the current abnormality cause of the substrate quality abnormality and the current abnormality processing measure to the first target client.

the first data acquisition module can be used for acquiring stored first historical abnormal data and extracting a first historical quality abnormal type, a first historical abnormal reason corresponding to the first historical quality abnormal type and a first historical processing measure in the first historical abnormal data;

the second data acquisition module can be used for acquiring registered second historical abnormal data and extracting a second historical quality abnormal type, a second historical abnormal reason corresponding to the second historical quality abnormal type and a second historical processing measure in the second historical abnormal data;

The data set construction module can be used for constructing a data set according to a first historical quality anomaly type, a first historical anomaly cause corresponding to the first historical quality anomaly type, a first historical processing measure, a second historical quality anomaly type, a second historical anomaly cause corresponding to the second historical quality anomaly type and a second historical processing measure;

the network model training module can be used for training the network model to be trained based on the data set to obtain the substrate quality abnormality prediction model.

the processing progress monitoring module can be used for monitoring the processing progress of the first target user corresponding to the first target client on the abnormal graphic message at intervals of preset time;

the time difference value determining module may be configured to calculate a time difference value between a current time node and a sending time node of the abnormal graphic message if the processing progress of the abnormal graphic message is unprocessed;

and the second target client determining module can be used for determining a second target client needing to be pushed by the abnormal graphic message according to the time difference value and pushing the abnormal graphic message to the second target client.

The specific details of each module in the pushing device of the abnormal message are described in detail in the pushing method of the corresponding abnormal message, so that the details are not repeated here.

It should be noted that although in the above detailed description several modules or units of a device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.

Furthermore, although the steps of the methods in the present disclosure are depicted in a particular order in the drawings, this does not require or imply that the steps must be performed in that particular order or that all illustrated steps be performed in order to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform, etc.

In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

Those skilled in the art will appreciate that the various aspects of the present disclosure may be implemented as a system, method, or program product. Accordingly, various aspects of the disclosure may be embodied in the following forms, namely: an entirely hardware embodiment, an entirely software embodiment (including firmware, micro-code, etc.) or an embodiment combining hardware and software aspects may be referred to herein as a "circuit," module "or" system.

An electronic device 800 according to such an embodiment of the present disclosure is described below with reference to fig. 8. The electronic device 800 shown in fig. 8 is merely an example and should not be construed to limit the functionality and scope of use of embodiments of the present disclosure in any way.

As shown in fig. 8, the electronic device 800 is embodied in the form of a general purpose computing device. Components of electronic device 800 may include, but are not limited to: the at least one processing unit 810, the at least one storage unit 820, a bus 830 connecting the different system components (including the storage unit 820 and the processing unit 810), and a display unit 840.

Wherein the storage unit stores program code that is executable by the processing unit 810 such that the processing unit 810 performs steps according to various exemplary embodiments of the present disclosure described in the above section of the present specification. For example, the processing unit 810 may perform step S110 as shown in fig. 1: determining quality monitoring results of the substrate in a plurality of different quality monitoring dimensions according to current process parameters of the substrate in the production process; step S120: determining whether the substrate has abnormal substrate quality in the production process according to the quality monitoring result; step S130: when the substrate quality abnormality occurs in the production process of the substrate, generating an abnormal graphic message according to the quality monitoring result, and determining an abnormal grade of the substrate quality abnormality according to the quality monitoring result; step S140: and determining a first target client which is required to be pushed by the abnormal graphic message according to the abnormal grade, and pushing the abnormal graphic message to the first target client.

The storage unit 820 may include readable media in the form of volatile storage units, such as Random Access Memory (RAM) 8201 and/or cache memory 8202, and may further include Read Only Memory (ROM) 8203.

Storage unit 820 may also include a program/utility 8204 having a set (at least one) of program modules 8205, such program modules 8205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.

Bus 830 may be one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

The electronic device 800 may also communicate with one or more external devices 900 (e.g., keyboard, pointing device, bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 800, and/or any device (e.g., router, modem, etc.) that enables the electronic device 800 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 850. Also, electronic device 800 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through network adapter 860. As shown, network adapter 860 communicates with other modules of electronic device 800 over bus 830. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 800, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.

From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, including several instructions to cause a computing device (may be a personal computer, a server, a terminal device, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.

In an exemplary embodiment of the present disclosure, a computer-readable storage medium having stored thereon a program product capable of implementing the method described above in the present specification is also provided. In some possible implementations, various aspects of the disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps according to the various exemplary embodiments of the disclosure as described in the "exemplary methods" section of this specification, when the program product is run on the terminal device.

A program product for implementing the above-described method according to an embodiment of the present disclosure may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

The computer readable signal medium may include a data signal propagated in baseband or as part of a carrier wave with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).

Furthermore, the above-described figures are only schematic illustrations of processes included in the method according to the exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily appreciated that the processes shown in the above figures do not indicate or limit the temporal order of these processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, for example, among a plurality of modules.

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

Claims

1. The pushing method of the abnormal message is characterized by comprising the following steps:

2. The method of pushing an exception message of claim 1, wherein the quality monitoring results in the plurality of different quality monitoring dimensions include a plurality of first quality monitoring results in a first quality monitoring dimension, second quality monitoring results in a second quality monitoring dimension, and third quality monitoring results in a third quality monitoring dimension;

3. The method for pushing an exception message according to claim 2, wherein determining a first quality monitoring result of the substrate in a product specification quality monitoring dimension according to the current process parameter comprises:

4. The method for pushing an exception message according to claim 2, wherein determining, according to the current process parameter, a second quality monitoring result of the substrate in a monitoring dimension of a development trend of the current process parameter includes:

5. The method of pushing an anomaly message according to claim 2, wherein determining a third quality monitoring result of the substrate in a monitoring dimension of a process capability index according to the current process parameter comprises:

6. The method for pushing an anomaly message according to claim 1, wherein determining whether the substrate is abnormal in quality during the production process according to the quality monitoring result comprises:

7. The pushing method of the anomaly message according to claim 1, wherein determining an anomaly level of substrate quality anomaly based on the quality monitoring result comprises:

8. The pushing method of the anomaly message according to claim 1, wherein determining an anomaly level of substrate quality anomaly based on the quality monitoring result comprises:

9. The pushing method of the anomaly message according to claim 1, wherein determining an anomaly level of substrate quality anomaly based on the quality monitoring result comprises:

10. The method for pushing an exception message according to claim 1, wherein generating an exception graphic message according to the quality monitoring result comprises:

11. The method for pushing an abnormal message according to claim 10, wherein calling a message generation template required for generating the abnormal graphic message, and filling the quality monitoring result into the message generation template, and obtaining the abnormal graphic message, comprises:

12. The method for pushing an exception message according to claim 1, wherein determining a first target client to which the exception graphic message needs to be pushed according to the exception level comprises:

13. The pushing method of an anomaly message according to claim 1, wherein after the step of determining that the substrate quality of the substrate is abnormal in the production process, the pushing method of an anomaly message further comprises:

14. The method for pushing an exception message according to claim 13, wherein the method for pushing an exception message further comprises:

15. The method for pushing an exception message according to claim 1, wherein the method for pushing an exception message further comprises:

16. A pushing device for an exception message, comprising:

17. A computer readable storage medium having stored thereon a computer program, which when executed by a processor implements the pushing method of an exception message according to any of claims 1-15.

18. An electronic device, comprising:

a processor; and

A memory for storing executable instructions of the processor;

wherein the processor is configured to perform the push method of the exception message of any one of claims 1-15 via execution of the executable instructions.