CN113205237A - Glass production information processing method and device, electronic equipment and storage medium thereof - Google Patents
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Abstract
The application provides a glass production information processing method, a device, an electronic device and a storage medium thereof, wherein the method comprises the following steps: acquiring data to be judged, wherein the data to be judged comprises production information of each glass in the produced glass, the production information comprises defect detection data, production history data and process parameter data, and the history data comprises production time; acquiring identification information of each piece of glass, and associating the production information of each piece of glass according to the identification information to obtain associated data to be determined; according to the associated data to be judged, counting the reject ratio data of the glass produced in a preset time period; and outputting early warning information according to the reject ratio data and a preset reject ratio threshold value. The glass production information processing method, the glass production information processing device, the electronic equipment and the storage medium thereof are convenient for management of production and processing processes, reduce internal consumption of production management, and are beneficial to achieving the purposes of monitoring production stability and reducing production cost.
Description
Technical Field
The application relates to the technical field of substrate glass production, in particular to a glass production information processing method and device, electronic equipment and a storage medium thereof.
Background
With the continuous improvement of display technologies, display panel products are continuously being promoted, the requirements of high-resolution display technologies on substrates are continuously strengthened, and as the manufacturing processes and details are more complicated, conditions are very severe especially on the aspect of glass surface defects of the substrates. At present, the number of glass defect inspection stations increases with the complexity of the manufacturing process. Because the inspection machine detects defect types more, and data information volume is great, utilizes artifical statistics, and it is great to consume the manpower, and the error appears easily in the statistics, leads to obtaining data inefficiency, credibility is lower.
In addition, the monitoring of each piece of production process information (for example, defect information of each product corresponding to a manufacturing process) is relatively independent, and since a pre-factory process and a module process may be performed in different factory areas, and different factory areas may be located in different cities, a technician generally can only analyze certain single process monitoring data to determine whether a process is abnormal, but there are many inspection test stations, and although the abnormality of the manufacturing process can be found, the reliability of the component is not greatly affected.
And if the cross-region defect data acquisition and the integrated butt joint are not carried out, customized monitoring is carried out. This makes it impossible to stably monitor the production process and to effectively reduce process loss, which not only increases the production cycle and affects productivity, but also increases the manufacturing cost.
Disclosure of Invention
The application provides a glass production information processing method, a glass production information processing device, electronic equipment and a storage medium thereof, and aims to solve the problem that the quality control efficiency is not high in the existing glass production.
In a first aspect, the present application provides a glass production information processing method comprising:
acquiring data to be judged, wherein the data to be judged comprises production information of each glass in the produced glass, the production information comprises defect detection data, production history data and process parameter data of each glass, and the history data comprises production time of each glass;
acquiring identification information of each piece of glass, and associating the defect detection data, the production record data and the process parameter data of each piece of glass according to the identification information to obtain associated data to be judged;
according to the associated data to be judged, counting the reject ratio data of the glass produced in a preset time period;
and outputting early warning information according to the reject ratio data and a preset reject ratio threshold value.
In one possible implementation manner of the present application, the production history data further includes a production line body to which each piece of glass belongs;
the step of counting the reject ratio data of the glass produced in the preset time period according to the associated data to be judged comprises the following steps of:
counting the total number of the glass produced by each production line body in the preset time period according to the production line body of each glass;
counting the number of the defective glass of each production line according to the defect detection data of each glass;
determining a first reject ratio of each production line according to the total glass number and the defective glass number;
and obtaining the reject ratio data according to the first reject ratio of each production line.
In a possible implementation manner of the present application, after the step of determining the first reject ratio of each production line according to the total number of glasses and the number of defective glasses, the method further includes:
acquiring a first query request of target glass, wherein the data query request carries target identification information of the target glass;
and inquiring target production information of the target glass according to the target identification information, wherein the target production information comprises at least one of defect detection data, production history data and process parameter data of the target glass.
In a possible implementation manner of the present application, after the step of determining the first reject ratio of each production line according to the total number of glasses and the number of defective glasses, the method further includes:
acquiring a second query request of the reject ratio of the target production line body;
and inquiring a second reject ratio from the first reject ratio of each production line, wherein the second reject ratio is the second reject ratio of the target production line.
In a possible implementation manner of the present application, after the step of determining the first reject ratio of each production line according to the total number of glasses and the number of defective glasses, the method further includes:
acquiring a third query request of the reject ratio of a production line body to which target glass belongs, wherein the third query request carries target identification information of the target glass;
inquiring the production line body to which the target glass belongs according to the target identification information;
and inquiring a third reject ratio from the first reject ratio of each production line, wherein the third reject ratio is the reject ratio of the production line to which the target glass belongs.
In one possible implementation manner of the present application, the defect detection data includes defect type information and defect level information of the defect type;
after the step of obtaining the identification information of each piece of glass, associating the defect detection data, the production history data and the process parameter data of each piece of glass according to the identification information to obtain associated data to be determined, the method further comprises the following steps:
acquiring a fourth query request of glass of a target type, wherein the target type comprises at least one of target defect type information or target defect grade information;
and inquiring the production line body to which the glass of the target type belongs according to the fourth inquiry request.
In a possible implementation manner of the present application, after the step of querying the target defective rate of the target production line from the first defective rate of each production line, the method further includes:
detecting whether the defect rate data has abnormal defect rate or not;
and if the abnormal reject ratio exists in the reject ratio data, updating the abnormal reject ratio to obtain the updated reject ratio. In a possible implementation manner of the present application, the step of obtaining data to be determined includes:
acquiring defect data of the each glass detected by a sensor device as the defect detection data;
acquiring production history data of each glass recorded in an MES system as the production history data;
and acquiring the process parameters of each piece of glass recorded by the machine automation system to serve as the process parameter data.
In a second aspect, the present application provides a glass production information processing apparatus, the apparatus comprising:
the system comprises an acquisition module, a judging module and a judging module, wherein the acquisition module is used for acquiring data to be judged, the data to be judged comprises production information of each glass in the produced glass, the production information comprises defect detection data, production history data and process parameter data of each glass, and the history data comprises production time of each glass;
the association module is used for acquiring the identification information of each piece of glass, associating the defect detection data, the production record data and the process parameter data of each piece of glass according to the identification information, and obtaining associated data to be judged;
the statistical module is used for counting the reject ratio data of the glass produced in a preset time period according to the associated data to be judged;
and the early warning module is used for outputting early warning information according to the reject ratio data and a preset reject ratio threshold value.
In a third aspect, the present application provides an electronic device, comprising:
one or more processors;
a memory; and
one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the processor to implement the glass production information processing method.
In a fourth aspect, the present application also provides a computer-readable storage medium having a computer program stored thereon, the computer program being loaded by a processor to perform the steps in the glass production information processing method.
According to the glass production information processing method, the device, the electronic equipment and the storage medium thereof, the defect detection data, the production history data and the process parameter data in the production information of each piece of glass are acquired to wait for the judgment data and acquire the identification information of each piece of glass, the production information is associated through the identification information of each piece of glass, the reject ratio statistics of the glass defects is carried out according to the associated data to be judged, and the early warning information is sent according to the reject ratio data obtained by statistics and the preset reject ratio threshold value, so that the reject ratio of the produced glass can be effectively controlled according to the early warning information. This application is through establishing ties glass's production information and identification information, can release relevant personnel's work load and stop the loss in time when production is unusual, effectively reduces the production loss to can realize that the distal end looks over current dynamic data and regularly produce static data, the production and processing process management of being convenient for, the internal consumption of reduction production management is favorable to realizing the stability of control production and reduction in production cost's purpose.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic view of a scene of the glass production information processing method provided in this embodiment.
Fig. 2 is a schematic flow chart of an embodiment of the glass production information processing method provided in this embodiment.
Fig. 3 is a schematic flowchart of one embodiment of step 103 provided by the embodiment of the present application.
Fig. 4 is a schematic flowchart of an embodiment after step 303 provided by an embodiment of the present application.
Fig. 5 is a schematic flowchart of another embodiment after step 303 provided by the embodiment of the present application.
Fig. 6 is a schematic flowchart of another embodiment after step 303 provided by the embodiment of the present application.
FIG. 7 is a flowchart of one embodiment after step 102, provided by embodiments of the present application.
Fig. 8 is a schematic flowchart of another embodiment after step 303 provided by the embodiment of the present application.
FIG. 9 is a flowchart of one embodiment of step 402 provided by embodiments of the present application.
Fig. 10 is a schematic structural view of one embodiment of the glass production information processing apparatus provided in the present embodiment.
Fig. 11 is a schematic structural diagram of an embodiment of the electronic device provided in this embodiment.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention. Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
In this application, the word "exemplary" is used to mean "serving as an example, instance, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to make and use the invention. In the following description, details are set forth for the purpose of explanation. It will be apparent to one of ordinary skill in the art that the present invention may be practiced without these specific details. In other instances, well-known structures and processes are not shown in detail to avoid obscuring the description of the invention with unnecessary detail. Thus, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.
Statistical Process Control (SPC) is a Process Control tool that relies on mathematical Statistical methods. The method analyzes and evaluates the production process, timely discovers the sign of the systematic factors according to the feedback information, and takes measures to eliminate the influence, so that the process is maintained in a controlled state only influenced by the random factors, and the purpose of controlling the quality is achieved. Thousands of pieces of SPC object data may be generated by different equipments in 1 of the manufacturing processes, and thus enormous manpower and material resources are required for manual processing of such a large amount of data, and the SPC system is an effective tool for automatically processing large data.
Manufacturing Execution System (MES) is a set of production information management System facing the Execution layer of the Manufacturing enterprise workshop. The MES can provide management modules for enterprises, such as manufacturing data management, planning scheduling management, production scheduling management, inventory management, quality management, human resource management, work center/equipment management, tool and tool management, purchasing management, cost management, project bulletin board management, production process control, bottom layer data integration analysis, upper layer data integration decomposition and the like, and create a solid, reliable, comprehensive and feasible manufacturing cooperative management platform for the enterprises.
The embodiment of the application provides a glass production information processing method and device, electronic equipment and a storage medium thereof, and the following detailed description is provided.
The glass production information processing method provided by the embodiment of the present application can be applied to a glass production information processing system, and exemplarily, the glass production information processing method provided by the embodiment of the present application can be applied to an SPC system, the application environment of which is shown in fig. 1, wherein the glass production information processing system includes a server 20 and a user terminal 10, the server 20 includes an interface server and a database server, and the server 20 includes a glass production information processing device. The user terminal 10 may establish a communication connection with an interface server and/or a database server, which may include, but is not limited to, Wi-Fi, bluetooth, Near Field Communication (NFC), and the like. In some embodiments, the user terminal includes, but is not limited to, a smart terminal device such as a smart phone, a tablet computer, a notebook computer, a desktop computer, and the like.
The glass production information processing method may be executed by the user terminal 10, by the server 20, or by cooperation of the user terminal 10 and the server 20. Taking the glass production information processing method as an example, the user terminal 10 may obtain data to be determined from a local or server 20, where the data to be determined includes production information of each glass in the produced glass, the production information includes defect detection data of each glass, production history data and process parameter data, and the history data includes production time of each glass; acquiring identification information of each piece of glass, and associating the defect detection data, the production record data and the process parameter data of each piece of glass according to the identification information to obtain associated data to be judged; according to the associated data to be judged, counting the reject ratio data of the glass produced in a preset time period; and outputting early warning information according to the reject ratio data and a preset reject ratio threshold value. The user terminal 10 may display the warning information on a user interface of the user terminal 10.
The user terminal 10 may be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, and the like. The server 20 may be an independent physical server, a server cluster or a distributed system including a plurality of physical servers, or a cloud server providing a cloud computing service.
It should be noted that the scenario diagram of the glass production information processing system shown in fig. 1 is only an example, and the glass production information processing system and the scenario described in the embodiment of the present application are for more clearly illustrating the technical solution of the embodiment of the present application, and do not constitute a limitation to the technical solution provided in the embodiment of the present application.
As shown in fig. 2, which is a schematic flow chart of an embodiment of a glass production information processing method in the embodiment of the present application, the glass production information processing method specifically includes the following steps 101 to 104:
The defect detection data can include, but is not limited to, data such as each defect type of each glass, and a defect grade corresponding to the defect type; the production record data comprises the in-station time and out-station time of glass production, the production line body, the production batch, production operators and other data; the process parameter data comprises data such as component data, proportioning data, and manufacturing process data (such as annealing, cleaning, etching, packaging, lighting, etc.) of the glass.
Specifically, the SPC system may acquire the production information of each glass from the server database, or may directly acquire the stored production information of each glass from the memory. For example, the terminal may perform data acquisition through a data Extraction tool, and the data Extraction tool may be an ETL (Extraction-Transformation-Loading) program, the ETL program is configured to capture data files at regular time, and the ETL program is configured to send an access request for target service data to the database server, where the access request is used to read target data such as defect detection data, production history data, and process parameter data.
102, obtaining the identification information of each glass, and associating the defect detection data, the production history data and the process parameter data of each glass according to the identification information to obtain associated data to be determined.
The identification information is used for identifying each piece of glass, the identification information can be corresponding ID numbers of the glass, and the like, an association relation is established for the production information through the identification information, namely the unique ID numbers of each piece of glass are used for associating the front and back production information in the production process of the glass, such as defect detection data, production record data, process parameter data and the like, the production process data can be fed back more efficiently, so that during subsequent analysis, the source tracing analysis can be performed on the reasons generated by the glass defects, the source of the glass defects is accurately positioned, the source tracing is facilitated, and the effective management and control of the glass production defects are facilitated.
And 103, counting the reject ratio data of the glass produced in a preset time period according to the associated data to be judged.
Wherein, the production batch comprises a plurality of glass production line bodies. The preset time period may be a single time period, or may include a plurality of sub-preset time periods. For example, the statistical time period may be a single time period of 0-24 hours, or may be in the time period of 0-24H, for example, every 4 hours, i.e., 0 point-4 point statistics is performed for the first time, 4 point-8 point statistics is performed for the second time, 8 point-12 point statistics is performed for the third time, etc., and by setting the statistical time, the produced glass can be monitored regularly, so as to effectively monitor the stability of glass production.
Specifically, the reject ratio data of the produced glass may also be different for different glass production lines, different production lots, and the like within a preset time period, and therefore, the reject ratio data may include, but is not limited to, statistics in units of a single production line, statistics in units of a single production lot, statistics in units of a single defect type, and the like, and is not limited herein.
And 104, outputting early warning information according to the reject ratio data and a preset reject ratio threshold value.
The preset reject ratio threshold is used for monitoring whether the reject ratio data exceed the standard or not, comparing the reject ratio data with the preset reject ratio threshold, and outputting early warning information according to a comparison result. Illustratively, when the reject ratio data is larger than a preset threshold value, an alarm mail is sent to an early warning notification object. Specifically, the defect rate data may include, but is not limited to, total defect rate (the defect rate of all glasses produced within a predetermined period of time), defect rate of a single production line, defect rate of a single production lot, defect rate of a single type of defect or defect rate of a single defect grade, and the like.
The condition of outputting the early warning information can be configured according to actual needs, for example, the early warning information can be output when the total reject ratio exceeds a preset reject ratio threshold; or the early warning information can be output as long as the reject ratio of the single production line exceeds a preset reject ratio threshold; the method may also output an early warning message when the defect rate of a single production lot exceeds a preset defect rate threshold, and the like, which is not limited herein.
The early warning information can comprise an early warning signal and a target early warning notification object, wherein the target early warning notification object can be a production-related engineer, a production line body responsible person, a product manager and other related personnel. The early warning signal can be an early warning mail or other application messages, for example, the preset reject ratio threshold value is 0.4%, the statistical reject ratio data is 1%, the reject ratio data is considered to be greater than the preset reject ratio threshold value, the production defects of the glass need to be managed and controlled, the early warning mail is sent to a target early warning notification object, and after the target early warning notification object receives the early warning signal, the target early warning notification object can notify production line machines or staff to stop glass production, and production is resumed until problems are solved, so that the waste of cost is reduced.
Wherein, the preset reject ratio threshold value can be flexibly set according to actual production requirements. For example, in actual production, there may be different defect management requirements for different production lines or different batches of glass, for example, if a certain batch of glass requires a reject ratio of 1%, the preset reject ratio threshold may be set to 1%, and for example, if another certain batch of glass requires a reject ratio of 0.5%, the preset reject ratio threshold may be set to 0.5%.
According to the glass production information processing method provided by the embodiment of the application, the defect detection data, the production history data and the process parameter data in the production information of each piece of glass are acquired to wait for the judgment data and acquire the identification information of each piece of glass, the production information is associated through the identification information of each piece of glass, the reject ratio statistics of the glass defects is carried out according to the associated data to be judged, and the early warning information is sent according to the reject ratio data obtained by statistics and the preset reject ratio threshold value, so that the reject ratio of the produced glass can be effectively controlled according to the early warning information. This application is through establishing ties glass's production information and identification information, can release relevant personnel's work load and stop the loss in time when production is unusual, effectively reduces the production loss to can realize that the distal end looks over current dynamic data and regularly produce static data, the production and processing process management of being convenient for, the internal consumption of reduction production management is favorable to realizing the stability of control production and reduction in production cost's purpose.
In some embodiments, the step 101 of acquiring data to be determined specifically includes the following steps 1) to 3):
11) and acquiring defect data of the each glass detected by the sensor device as the defect detection data.
The defect detection data comprises a plurality of defect types, defect grade data corresponding to the defect types and the like. The sensor equipment can obtain corresponding defect information of each glass according to an input glass defect image and a preset detection model, classify the defect information and obtain defect types and defect grades, wherein the glass defect image is obtained by shooting each glass by using an image acquisition device on a production line, the preset detection module can be obtained according to deep convolutional neural network training, and the defect types can include but are not limited to multiple defect types such as bubbles, scratches, foreign matter residues and the like.
It should be noted that the defect detection data may be directly obtained by the user terminal from the sensor detection device, or indirectly obtained by the user terminal from the sensor detection device, for example, the defect detection data in the sensor detection device is first stored in the database server, and then the user terminal obtains the defect detection data from the data server.
12) And acquiring production history data of each glass recorded in the MES system as the production history data.
The production history data is recorded in an information Management system, and the terminal can directly obtain the production history data from the information Management system, where the information Management system may be an MES system, or may also be one of a Product Lifecycle Management system (PLM), an Advanced Planning and Scheduling (APS), a customer relationship Management system (CRM), and the like, and is not particularly limited herein. The production history data can be directly obtained from the MES system by the user terminal or indirectly obtained from the MES system by the user terminal, for example, the production history data in the MES system is firstly stored in the database server, and then the production history data is obtained from the data server by the user terminal.
13) And acquiring the process parameters of each glass recorded by the machine automation system to serve as the process parameter data.
The machine automation system is configured to record process parameters used in each glass production, such as component data, proportioning data, and manufacturing process data (e.g., annealing, cleaning, etching, packaging, lighting, etc.) of corresponding glass, where the process parameter data may be directly obtained by a user terminal from the machine automation system, or indirectly obtained by the user terminal from the machine automation system, for example, the process parameter data in the machine automation system is stored in a database server, and then the process parameter data is obtained by the user terminal from the data server.
In some embodiments, said production resume data further comprises a production line body for each glass, as shown in fig. 3, said step 103 comprising the following steps 301-304:
for example, for a single line body with a yield of 3.6K, the yield is 150 pieces (pieces)/hour (H), the total number of glasses in 4 hours is 600 pieces, the number of defective glasses of a single defect type (e.g., blister defect) is 2 pieces, and the defect ratio R of the type in 4 hours is (number of defective glasses/total number of glasses) × 100% ═ 0.33%.
And 304, obtaining the reject ratio data according to the first reject ratio of each production line.
The first reject ratio is a reject ratio statistically obtained by each production line within a preset time period, and the reject ratio data may include a plurality of first reject ratio data, i.e., a set of first reject ratios respectively formed by a plurality of single production lines. The quantity of glass production line bodies is large, dozens of production line bodies or even hundreds of production line bodies are possible, the data quantity of the obtained production information and identification information is large, the data statistics time is long, the reject ratio data is obtained through statistics in advance, so that the reject ratio of each line body can be rapidly inquired in the following process, and the inquiry efficiency is improved.
In addition, the statistics of the defective rate of the glass can be performed by taking the defect type as a unit, the defect detection data comprises a plurality of defect types, and when the defect types are taken as the unit, the following steps 31) to 34) can be included:
31) counting the total number of the produced glass in the preset time period;
32) counting the number of the defective glass of each defect type;
33) determining a third reject ratio of each defect type according to the total glass number and the number of the defective glass of each defect type;
34) and obtaining the defect rate data according to the third defect rate of each defect type.
The total number of the produced glass and the types of the defects of the glass are more, and the number of the glass corresponding to various defect types is huge, so that the data volume of the obtained glass identification information production information is huge, the time consumption of data statistics is long, the reject ratio data is obtained through statistics in advance, the reject ratio of each defect type can be rapidly obtained through subsequent query, and the query efficiency is improved. According to the embodiment of the application, the reject ratio data are obtained through statistics, so that the follow-up monitoring on abnormal production data such as reject ratio and the like is facilitated, the follow-up tracing on the yield and quality conditions of each process is facilitated, and the defect type is improved in a targeted manner.
In some embodiments, after step 303, as shown in fig. 4, the following steps 311 to 312 are further included:
The target glass is the glass to be inquired, and the number of the target glass can be one or a plurality of target glasses. The target identification information may be ID code information of the glass to be queried.
And step 312, inquiring target production information of the target glass according to the target identification information, wherein the target production information comprises at least one of defect detection data, production history data and process parameter data of the target glass.
The inquired target production information may be one kind of information or multiple kinds of information. For example, the input of the ID code of the glass to be queried may include, but is not limited to, querying the corresponding defect type, defect grade, operator, arrival time, production process, etc. of the glass.
According to the embodiment of the application, the counted reject ratio data, the correlated production information and the correlated identification information can be directly obtained, and the huge glass production data volume does not need to be correlated again, so that the query efficiency is improved, and the resources are saved. The production information of the target glass is obtained through inquiry, so that the backtracking of the glass production defects and the information such as the glass production process is facilitated, and the monitoring efficiency of glass production is improved.
In some embodiments, after step 303, as shown in fig. 5, the following steps 321 to 322 are further included:
The target production line can be a single production line or a plurality of production lines.
For example, when the third query request of the target production Line is a query request carrying information of the production Line, which is Line10, a second reject ratio corresponding to the production Line, which is Line10, is queried from the counted first reject ratio of each production Line, where the second reject ratio may be a reject ratio of all defect types in the production Line, or a reject ratio of a single defect type, and is not specifically limited herein. Illustratively, the percent defective of all defect types of the production Line10 queried is 0.5%.
According to the embodiment of the application, the counted reject ratio data, the correlated production information and the correlated identification information can be directly obtained, and the huge glass production data volume does not need to be correlated again, so that the resource saving is facilitated. And the production information of the target glass can be directly acquired by inquiring the production information of the target glass from the electronic equipment, so that the production data can be favorably checked at a remote end, and the reject ratio of the produced glass can be effectively monitored.
In some embodiments, after step 303, as shown in fig. 6, the following steps 331 to 333 are further included:
and 331, acquiring a third query request of the reject ratio of the production line body to which the target glass belongs, wherein the third query request carries target identification information of the target glass.
The target glass is the glass to be inquired, and the number of the target glass can be one or a plurality of target glasses. The target identification information may be ID code information of the glass to be queried.
And 332, inquiring the production line body to which the target glass belongs according to the target identification information.
According to the embodiment of the application, the counted reject ratio data, the correlated production information and the correlated identification information can be directly obtained, and the huge glass production data volume does not need to be correlated again, so that the resource saving is facilitated. Through the production information of the input target glass, the production information of the target glass can be directly inquired and obtained, the remote checking of production data is facilitated, and the reject ratio of the produced glass is effectively monitored.
In some embodiments, the defect detection data includes defect type information and defect level information for the defect type; after the step 102, as shown in fig. 7, the method further includes the following steps 341 to 342:
The target defect type information may be one type or multiple types, and similarly, the target defect level information may also be one or multiple types. Illustratively, the defect types may include, but are not limited to, a plurality of defect types such as bubbles, scratches, foreign matter residues, and the like, and the defect grades may include, but are not limited to, a plurality of grades such as K1, K2, K3, wherein K1 represents a light grade, K2 represents a medium grade, K3 represents a heavy grade, and the like. For example, the defect types of a certain defective glass are scratches with the scratch ratings of K3 and K2.
And 342, inquiring the production line body to which the glass of the target type belongs according to the fourth inquiry request.
For example, in the embodiment of the application, all glasses with the defect type of scratch are queried, and the production Line bodies to which the defect type belongs are Line1, Line5, Line10 and the like respectively as a result of the query; or querying all glasses with the defect types of scratches and bubbles at the same time and with the defect grades of K3, and querying results show that the two defect types of scratches and bubbles at the same time exist, and production lines of all glasses with the defect grades of K3 of scratches and bubbles belong to Line1, Line5, Line10 and the like.
According to the embodiment of the application, the counted reject ratio data, the correlated production information and the correlated identification information can be directly obtained, and the huge glass production data volume does not need to be correlated again, so that the resource saving is facilitated. The production information of the target glass is obtained through inquiry, so that the reject ratio of glass production is effectively monitored.
It should be noted that the first query, the second query, the third query, or the fourth query may be generated locally by the electronic device, the electronic device may display a user interface, and the user inputs the information corresponding to the query on the user interface and then clicks the query button, so as to obtain the corresponding query generated by the terminal device.
In some embodiments, after step 303, as shown in fig. 8, the following steps 401 to 402 are further included:
currently, during the production process or before shipment, one or more OQC (out Quality Control) sampling checks are generally required for the substrate glass. Generally, the OQC spot check may include a comprehensive check and verification of the defect type or defect level of the shipment to ensure that the customer is in compliance with the order and shipped in a fully qualified manner. Further inspection of the glass quality is generally required in order to confirm the quality of the goods again before shipment. The inspection may be performed by a spot inspection, for example, a certain production line is counted again for the first defect rate, or a production line with an abnormal defect rate is reviewed.
The identification rule of the abnormal reject ratio can be configured according to the actual requirement of glass production, and exemplarily, the abnormal reject ratio can be a first reject ratio higher than that in other sub-preset time periods in a certain production line in a certain sub-preset time period, or a first reject ratio with large fluctuation in a plurality of sub-preset time periods in a certain production line, and the like.
In some embodiments, as shown in fig. 9, the step 402 may further include the following steps 411 to 413:
for example, before the preset time period includes 0 point-4 point, 4 point-8 point and the like, that is, every 4 hours, every 0 point-4 point statistics is performed for the first time, every 4 points-8 point statistics is performed for the second time, every 8 points-12 point statistics is performed for the third time, and the like, the target time period may include 0 point-3 point, 3 point-5 point and the like, that is, every 3 hours, every 0 point-3 point statistics is performed for the first time, every 3 points-5 point statistics is performed for the second time, every 5 points-7 point statistics is performed for the third time, that is, whether the abnormal defective rate is erroneously counted is further determined by increasing the statistics frequency.
And step 412, counting the target defective glass number of the defective production line according to the defect detection data of each glass in the defective production line.
And 413, determining the reject ratio after the updating of the defective production line body according to the total number of the target glass and the number of the target defective glass.
The abnormal reject ratio is updated, so that the glass production can be monitored more accurately, abnormal data can be responded in time, and the data processing efficiency is improved.
In order to better implement the glass production information processing method in the embodiment of the present application, in addition to the glass production information processing method, the embodiment of the present application further provides a glass production information processing apparatus, as shown in fig. 10, the glass production information processing apparatus including:
an obtaining module 501, configured to obtain data to be determined, where the data to be determined includes production information of each glass in produced glasses, the production information includes defect detection data, production history data, and process parameter data of each glass, and the history data includes production time of each glass;
the association module 502 is configured to obtain identification information of each glass, and associate the defect detection data, the production history data, and the process parameter data of each glass according to the identification information to obtain associated data to be determined;
a statistic module 503, configured to count reject ratio data of the glass produced within a preset time period according to the associated data to be determined;
and the early warning module 504 is configured to output early warning information according to the reject ratio data and a preset reject ratio threshold.
In some embodiments, the production resume data further comprises a production line body to which the each glass belongs; the statistics module 503 is configured to:
counting the total number of the glass produced by each production line body in the preset time period according to the production line body of each glass;
counting the number of the defective glass of each production line according to the defect detection data of each glass;
determining a first reject ratio of each production line according to the total glass number and the defective glass number;
and obtaining the reject ratio data according to the first reject ratio of each production line.
In some embodiments, the statistics module 503 is further configured to:
acquiring a first query request of target glass, wherein the data query request carries target identification information of the target glass;
and inquiring target production information of the target glass according to the target identification information, wherein the target production information comprises at least one of defect detection data, production history data and process parameter data of the target glass.
In some embodiments, the statistics module 503 is further configured to: acquiring a second query request of the reject ratio of the target production line body;
and inquiring a second reject ratio from the first reject ratio of each production line, wherein the second reject ratio is the second reject ratio of the target production line.
In some embodiments, the statistics module 503 is further configured to:
acquiring a third query request of the reject ratio of a production line body to which target glass belongs, wherein the third query request carries target identification information of the target glass;
inquiring the production line body to which the target glass belongs according to the target identification information;
and inquiring a third reject ratio from the first reject ratio of each production line, wherein the third reject ratio is the reject ratio of the production line to which the target glass belongs.
In some embodiments, the defect detection data includes defect type information and defect level information for the defect type; the association module 502 is configured to:
acquiring a fourth query request of glass of a target type, wherein the target type comprises at least one of target defect type information or target defect grade information;
and inquiring the production line body to which the glass of the target type belongs according to the fourth inquiry request.
In some embodiments, the statistics module 503 is further configured to:
detecting whether the defect rate data has abnormal defect rate or not;
and if the abnormal reject ratio exists in the reject ratio data, updating the abnormal reject ratio to obtain the updated reject ratio.
In some embodiments, the statistics module 501 is further configured to:
counting the total number of target glass produced by the defective production line body within a target preset time period according to the defective production line body to which the abnormal defective rate belongs;
counting the number of target defective glasses of the defective production line according to the defect detection data of each glass in the defective production line;
and determining the reject ratio of the updated defective production line body according to the total number of the target glass and the number of the target defective glass.
In some embodiments, the obtaining module 501 is configured to:
acquiring defect data of the each glass detected by a sensor device as the defect detection data;
acquiring production history data of each glass recorded in an MES system as the production history data;
and acquiring the process parameters of each glass recorded by the machine automation system to serve as the process parameter data.
The glass production information processing device provided by the embodiment of the application waits for judging data and obtains the identification information of each glass through the defect detection data, the production record data and the process parameter data in the production information of each glass, associates the production information through the identification information of each glass, carries out the fraction defective statistics of the glass defects according to the associated data to be judged, and sends the early warning information according to the fraction defective data and the preset fraction defective threshold value obtained by statistics, thereby realizing effective management and control on the fraction defective of the produced glass according to the early warning information. This application is through establishing ties glass's production information and identification information, can release relevant personnel's work load and stop the loss in time when production is unusual, effectively reduces the production loss to can realize that the distal end looks over current dynamic data and regularly produce static data, the production and processing process management of being convenient for, the internal consumption of reduction production management is favorable to realizing the stability of control production and reduction in production cost's purpose.
An embodiment of the present application further provides an electronic device, which integrates any one of the glass production information processing apparatuses provided in the embodiments of the present application, please refer to fig. 11, where fig. 11 shows a schematic structural diagram of the electronic device according to the embodiments of the present application, specifically:
the electronic device may include components such as a processor 601 of one or more processing cores, memory 602 of one or more computer-readable storage media, a power supply 603, and an input unit 604. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 11 does not constitute a limitation of the electronic device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components. Wherein:
the processor 601 is a control center of the electronic device, connects various parts of the whole electronic device by using various interfaces and lines, and performs various functions of the electronic device and processes data by operating or executing software programs and/or modules stored in the memory 602 and calling data stored in the memory 602, thereby performing overall monitoring of the electronic device. Optionally, processor 601 may include one or more processing cores; in some embodiments, processor 601 may integrate an application processor, which primarily handles operating systems, user interfaces, applications, etc., and a modem processor, which primarily handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 601.
The memory 602 may be used to store software programs and modules, and the processor 601 executes various functional applications and data processing by operating the software programs and modules stored in the memory 602. The memory 602 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to use of the electronic device, and the like. Further, the memory 602 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 602 may also include a memory controller to provide the processor 601 with access to the memory 602.
The electronic device further includes a power source 603 for supplying power to each component, and the power source 603 may be logically connected to the processor 601 through a power management system, so as to implement functions of managing charging, discharging, and power consumption management through the power management system. The power supply 603 may also include any component of one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and the like.
The electronic device may further include an input unit 604, and the input unit 604 may be used to receive input numeric or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.
Although not shown, the electronic device may further include a display unit and the like, which are not described in detail herein. Specifically, in the embodiment of the present application, the processor 601 in the electronic device loads the executable file corresponding to the process of one or more application programs into the memory 602 according to the following instructions, and the processor 601 runs the application program stored in the memory 602, thereby implementing various functions as follows:
acquiring data to be judged, wherein the data to be judged comprises production information of each glass in the produced glass, the production information comprises defect detection data, production history data and process parameter data of each glass, and the history data comprises production time of each glass; acquiring identification information of each piece of glass, and associating the defect detection data, the production record data and the process parameter data of each piece of glass according to the identification information to obtain associated data to be judged; according to the associated data to be judged, counting the reject ratio data of the glass produced in a preset time period; and outputting early warning information according to the reject ratio data and a preset reject ratio threshold value.
The electronic equipment provided by the embodiment of the application waits for judging data and obtains the identification information of each glass by obtaining the defect detection data, the production record data and the process parameter data in the production information of each glass, associates the production information through the identification information of each glass, carries out the reject ratio statistics of the glass defects according to the associated data to be judged, and sends the early warning information according to the reject ratio data obtained by statistics and the preset reject ratio threshold value, thereby realizing effective control on the reject ratio of the produced glass according to the early warning information. This application is through establishing ties glass's production information and identification information, can release relevant personnel's work load and stop the loss in time when production is unusual, effectively reduces the production loss to can realize that the distal end looks over current dynamic data and regularly produce static data, the production and processing process management of being convenient for, the internal consumption of reduction production management is favorable to realizing the stability of control production and reduction in production cost's purpose.
It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions or by associated hardware controlled by the instructions, which may be stored in a computer readable storage medium and loaded and executed by a processor.
To this end, embodiments of the present application provide a computer-readable storage medium having stored therein a plurality of instructions that can be loaded by a processor to perform the steps of any of the methods for processing glass production information provided by embodiments of the present application. For example, the instructions may perform the steps of:
acquiring data to be judged, wherein the data to be judged comprises production information of each glass in the produced glass, the production information comprises defect detection data, production history data and process parameter data of each glass, and the history data comprises production time of each glass; acquiring identification information of each piece of glass, and associating the defect detection data, the production record data and the process parameter data of each piece of glass according to the identification information to obtain associated data to be judged; according to the associated data to be judged, counting the reject ratio data of the glass produced in a preset time period; and outputting early warning information according to the reject ratio data and a preset reject ratio threshold value.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and parts that are not described in detail in a certain embodiment may refer to the above detailed descriptions of other embodiments, and are not described herein again.
Wherein the computer-readable storage medium may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.
Since the instructions stored in the computer-readable storage medium can execute the steps in any of the glass production information processing methods provided in the embodiments of the present application, the beneficial effects that can be achieved by any of the glass production information processing methods provided in the embodiments of the present application can be achieved, which are detailed in the foregoing embodiments and will not be described again here.
In a specific implementation, each unit or structure may be implemented as an independent entity, or may be combined arbitrarily to be implemented as one or several entities, and the specific implementation of each unit or structure may refer to the foregoing method embodiment, which is not described herein again.
The above detailed description is provided for a glass production information processing method, device, electronic device and storage medium thereof, and the principle and implementation of the present invention are explained herein by applying specific examples, and the description of the above embodiments is only used to help understanding the method and core ideas of the present invention; meanwhile, for those skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (11)
1. A glass production information processing method characterized by comprising:
acquiring data to be judged, wherein the data to be judged comprises production information of each glass in the produced glass, the production information comprises defect detection data, production history data and process parameter data of each glass, and the history data comprises production time of each glass;
acquiring identification information of each piece of glass, and associating the defect detection data, the production record data and the process parameter data of each piece of glass according to the identification information to obtain associated data to be judged;
according to the associated data to be judged, counting the reject ratio data of the glass produced in a preset time period;
and outputting early warning information according to the reject ratio data and a preset reject ratio threshold value.
2. The glass production information processing method according to claim 1, wherein the production history data further includes a production line body to which each of the glasses belongs;
the step of counting the reject ratio data of the glass produced in the preset time period according to the associated data to be judged comprises the following steps of:
counting the total number of the glass produced by each production line body in the preset time period according to the production line body of each glass;
counting the number of the defective glass of each production line according to the defect detection data of each glass;
determining a first reject ratio of each production line according to the total glass number and the defective glass number;
and obtaining the reject ratio data according to the first reject ratio of each production line.
3. The method of processing glass production information of claim 2, further comprising, after the step of determining a first reject rate for each production line based on the total number of glasses and the number of defective glasses:
acquiring a first query request of target glass, wherein the data query request carries target identification information of the target glass;
and inquiring target production information of the target glass according to the target identification information, wherein the target production information comprises at least one of defect detection data, production history data and process parameter data of the target glass.
4. The method of processing glass production information of claim 2, further comprising, after the step of determining a first reject rate for each production line based on the total number of glasses and the number of defective glasses:
acquiring a second query request of the reject ratio of the target production line body;
and inquiring a second reject ratio from the first reject ratio of each production line, wherein the second reject ratio is the second reject ratio of the target production line.
5. The method of processing glass production information of claim 2, further comprising, after the step of determining a first reject rate for each production line based on the total number of glasses and the number of defective glasses:
acquiring a third query request of the reject ratio of a production line body to which target glass belongs, wherein the third query request carries target identification information of the target glass;
inquiring the production line body to which the target glass belongs according to the target identification information;
and inquiring a third reject ratio from the first reject ratio of each production line, wherein the third reject ratio is the reject ratio of the production line to which the target glass belongs.
6. The glass production information processing method according to claim 2, wherein the defect detection data includes defect type information and defect grade information of the defect type;
after the step of obtaining the identification information of each piece of glass, associating the defect detection data, the production history data and the process parameter data of each piece of glass according to the identification information to obtain associated data to be determined, the method further comprises the following steps:
acquiring a fourth query request of glass of a target type, wherein the target type comprises at least one of target defect type information or target defect grade information;
and inquiring the production line body to which the glass of the target type belongs according to the fourth inquiry request.
7. The method of claim 2, wherein after the step of querying the target defect rate of the target production line from the first defect rate of each production line, the method further comprises:
detecting whether the defect rate data has abnormal defect rate or not;
and if the abnormal reject ratio exists in the reject ratio data, updating the abnormal reject ratio to obtain the updated reject ratio.
8. The glass production information processing method according to claim 1, wherein the step of acquiring data to be determined includes:
acquiring defect data of the each glass detected by a sensor device as the defect detection data;
acquiring production history data of each glass recorded in an MES system as the production history data;
and acquiring the process parameters of each piece of glass recorded by the machine automation system to serve as the process parameter data.
9. A glass production information processing apparatus characterized by comprising:
the system comprises an acquisition module, a judging module and a judging module, wherein the acquisition module is used for acquiring data to be judged, the data to be judged comprises production information of each glass in the produced glass, the production information comprises defect detection data, production history data and process parameter data of each glass, and the history data comprises production time of each glass;
the association module is used for acquiring the identification information of each piece of glass, associating the defect detection data, the production record data and the process parameter data of each piece of glass according to the identification information, and obtaining associated data to be judged;
the statistical module is used for counting the reject ratio data of the glass produced in a preset time period according to the associated data to be judged;
and the early warning module is used for outputting early warning information according to the reject ratio data and a preset reject ratio threshold value.
10. An electronic device, characterized in that the electronic device comprises:
one or more processors;
a memory; and
one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the processor to implement the glass manufacturing information processing method of any of claims 1-8.
11. A computer-readable storage medium, having stored thereon a computer program which is loaded by a processor to execute the steps in the glass production information processing method according to any one of claims 1 to 8.
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