CN115796436A - Production test data management system based on big data - Google Patents
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Abstract
The invention discloses a production test data management system based on big data, which is used for solving the problems of complicated data management and inconvenient use caused by the fact that the existing data management system cannot monitor production test data in real time and manage and summarize the data; according to the invention, by arranging the test acquisition and analysis module, the report management module, the billboard module, the material management module, the wafer management module, the equipment management module and the program management module, a large amount of production test data can be conveniently displayed and managed, and a user can conveniently inquire and visually know the production test data; the inquiry data of the client is analyzed through the inquiry analysis module, the signaling is processed through the signaling processing module, and the corresponding production test data is sent to the inquiry end of the client, so that the client can conveniently check the corresponding production test data through the inquiry end at the first time.
Description
Technical Field
The invention relates to the technical field of data management, in particular to a production test data management system based on big data.
Background
For the semiconductor industry, a testing procedure is a core link for producing semiconductor products, whether the products are qualified or not is determined by performing comprehensive testing, and a product interaction link can be entered; the existing data management system cannot monitor production test data in real time, manage and summarize the data, and therefore data management is complicated and inconvenient to use. To this end, a production test data management system based on big data is provided.
Disclosure of Invention
The invention aims to provide a production test data management system based on big data in order to solve the problems of complex data management and inconvenient use caused by the fact that the existing data management system cannot monitor production test data in real time, manage the data and analyze the data in a gathering way.
The purpose of the invention can be realized by the following technical scheme: the production test data management system based on big data comprises a test acquisition and analysis module, a data acquisition module, a database and an interface based on a system basic module and a system module, wherein the test acquisition and analysis module is used for carrying out test analysis on a product to obtain production test data; the data acquisition module is used for acquiring production test data through the Internet of things and sending the production test data to the database; further comprising:
the report management module is used for inputting query conditions and checking a display result, a yield and RowData corresponding to the target report; the target report comprises a product output report, a production statistics report, an FT general test report, a CP general test report, an alarm record report, a batch record report and an equipment comprehensive benefit report;
the billboard module is used for displaying equipment information, equipment states, an equipment state distribution graph, alarm information and equipment alarm monitoring information in real time;
the material management module is used for adding and editing material information or probe card information and is also used for receiving and returning the material or the probe card;
the wafer management module is used for inquiring the chip information and importing and checking the wafer map through the chip carved number, the client code and the batch number; the chip is also used for inquiring the chip map information, map information data display and data real-time updating by inputting the batch number and the equipment number;
the device management module is used for adding device reference information, adding device binding, deleting the device binding and managing the device model;
and the program management module is used for inputting test program information to be uploaded and managing the test programs, wherein the test program management comprises test program updating, test program approval, test program downloading and test program display.
As a preferred embodiment of the present invention, the material management module is configured to control a life cycle of material usage; the operation of material or probe card adoption specifically comprises the following steps: selecting a material or a probe card to be used, clicking to use, converting the state of the material or the probe card from an IN state to an OUT state, and setting the current time as ex-warehouse time; the return operation of the material or the probe card is specifically to select the material or the probe card, click the return and update the service cycle.
As a preferred embodiment of the present invention, the product output report is used to display the station-entering and station-exiting record information of all batches; the production statistical report is used for displaying detailed information of production batches; the FT general test report is used for displaying the production batch records of the FT workshop; the CP general test report is used for displaying the production batch records of the CP workshop; the alarm record report is used for displaying alarm detail information of the first ten devices; the batch record report is used for displaying the production record information of the batch; the equipment comprehensive benefit report is used for displaying OEE detailed contents of the equipment.
As a preferred embodiment of the present invention, when the target report is a product output report or a production statistics report, the input query conditions are a client code, a product number, a work station, an equipment number, a batch number, and a time period; the display result is a serial number, a batch current state, a product code, a product name, a client code, a client name, main equipment, auxiliary equipment, a work station, a station entering number, a station exiting number of good products, trackIn time and Trackout time;
when the target report is an FT general test report, the input query conditions are a client code, a product code, an equipment number, a batch number and a time period; the display result is a serial number, a batch current state, a product code, a product name, a client code, a client name, main equipment, auxiliary equipment, a work station, batch times, a good product number, trackIn time and Trackout time;
when the target report is a CP general test report, the input query conditions are a client code, a product code, a batch number, a work order number and a time period; the display result is a serial number, a work order number, a batch number, a wafer number, a batch current state, a product code, a product name, a customer code, a customer name, single-chip Die data, a good product number, trackIn time and Trackout time;
when the target report is an alarm record report, the input query conditions are equipment type, equipment model, equipment number and start-stop time; the display results are an alarm number TOP10 and an equipment alarm TOP10; wherein the TOP10 alarm number comprises a serial number, alarm times, an alarm number and alarm details; the equipment alarm TOP10 comprises a serial number, alarm times, an equipment number and an equipment model;
when the target report is a batch record report, the input query conditions are a batch number, a main device, an auxiliary device, a start time and an end time; the display result is serial number, batch number, production state, product code, product name, customer number, main equipment, auxiliary equipment, plan start date, plan end date, packaging form, stamp content and operation content;
when the target report is an equipment comprehensive benefit report, the input query conditions are equipment type, equipment model, equipment number and time period; the display result is a graph of the proportion of each state of the equipment, the equipment comprehensive efficiency OEE, yield data and numerical broken line trend; each state of the equipment comprises operation, standby, downtime, maintenance, repair, utilization rate, yield and comprehensive efficiency of the equipment.
As a preferred embodiment of the present invention, the present invention further includes:
the query statistics module is used for counting query data corresponding to the client through the query end and sending the query data to the database;
the query analysis module is used for analyzing the query data, and the specific analysis process comprises the following steps: classifying the query conditions, classifying the query conditions with the same query content into one class and marking the query conditions as the same query conditions, acquiring all query moments of the same query conditions, counting the total query number of the query moments, and sequencing all the query moments according to the time sequence when the total query number is greater than a set number;
calculating and processing the sorted query moments to obtain an adjacency-interval numerical ratio;
summing all the interval durations and taking the average to obtain a mean duration, extracting numerical values of the mean duration and the online duration, and dividing the numerical value of the online duration by the numerical value of the mean duration to obtain an interval time ratio;
extracting numerical values of the adjacent interval numerical value ratio, the time interval ratio and the total query number, and substituting the numerical values into a preset analysis model to obtain a correlation check value corresponding to the query condition;
when the check value FQ is greater than the set check threshold YQ1, the check value FQ is determined:
when YQ1 is more than FQ and less than or equal to YQ2, generating a light check signaling corresponding to the query condition and sending the light check signaling to a signaling processing module;
when YQ2 is more than FQ and less than or equal to YQ3, generating a center check signaling corresponding to the query condition and sending the center check signaling to a signaling processing module;
and when YQ3 is less than FQ, generating a rechecking signaling corresponding to the query condition and sending the rechecking signaling to the signaling processing module.
As a preferred embodiment of the present invention, the specific process of calculating and processing the sorted query time includes: calculating the time difference between two adjacent query moments to obtain interval duration, extracting numerical values corresponding to all the interval durations, sorting according to the time sequence, comparing the numerical values sorted in the front with the numerical values sorted in the back, and calculating the numerical value difference between the two numerical values to obtain a first adjacent interval value when the numerical values sorted in the front are greater than the numerical values sorted in the back; when the numerical value sorted in the front is smaller than the numerical value sorted in the rear, calculating the numerical value difference between the numerical value and the rear numerical value, and taking the absolute value to obtain a second adjacent value; summing all the adjacent separation values I and taking the average value to obtain an adjacent separation average value I, summing all the adjacent separation values II and taking the average value to obtain an adjacent separation average value II; and dividing the adjacent interval mean two by the adjacent interval mean one to obtain an adjacent interval numerical ratio.
As a preferred embodiment of the present invention, the signaling processing module is configured to receive and process a light check signaling or a medium check signaling or a heavy check signaling corresponding to a query condition, where the specific processing procedure is as follows:
when receiving the light check signaling, analyzing the light check signaling to obtain a client code, a client name, a light check instruction, query condition content and a communication address of a query end; the production test data acquisition module is connected with the data acquisition module and monitors the production test data acquired by the data acquisition module in real time, and when the production test data corresponding to the client code, the client name and the query condition is monitored within a preset time length, the production test data is sent to a query end corresponding to the communication address;
when the inquiry signaling is received, analyzing the inquiry signaling to obtain a client code, a client name, an inquiry instruction, inquiry condition content and a communication address of an inquiry end; within the preset time length two, when monitoring production test data corresponding to the client code, the client name and the query condition, sending the production test data to a query end corresponding to the communication address;
when receiving the rechecking signaling, analyzing the rechecking signaling to obtain a client code, a client name, a rechecking instruction, query condition content and a communication address of a query end; within a preset time length III, when monitoring production test data corresponding to the client code, the client name and the query condition, sending the production test data to a query end corresponding to the communication address, acquiring a check result corresponding to the query end, and when the check result is a stop instruction, stopping monitoring the production test data corresponding to the client code, the client name and the query condition and sending the production test data; when the checking result is the first click checking time corresponding to the production test data, counting all the first click checking times within the time range corresponding to the preset time length three, calculating the time difference between the first click checking time and the time corresponding to the production test data sending to obtain the click checking time length, calculating the mean value of all the click checking time lengths to obtain the click checking mean value time length, and when the click checking mean value time length is larger than the set time length threshold value, stopping monitoring the production test data corresponding to the client code, the client name and the query condition and sending the production test data.
As a preferred embodiment of the present invention, the query statistics module is further configured to count and process product names, corresponding inbound numbers, and TrackIn time corresponding to the customer codes; setting all production names to correspond to a preset product value, extracting numerical values of station entering numbers and multiplying the numerical values by the preset product value to obtain a single-side value; summing all the unilateral values corresponding to the client codes to obtain a unilateral total value; sequencing all TrackIn times corresponding to the client codes according to the time sequence, calculating the time difference between two adjacent TrackIn times to obtain one-side time length, summing all the one-side time lengths and averaging to obtain one-side average time length; counting the number of all TrackIn times corresponding to the client codes to obtain the total time; and extracting the values of the single-side average value duration, the single-side total value and the time total, and processing the values by using the length measurement basic value corresponding to the client code.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, by arranging the report management module, the billboard module, the material management module, the wafer management module, the equipment management module and the program management module, a large amount of production test data can be conveniently displayed and managed, and a user can conveniently inquire and visually know the production test data;
2. the invention analyzes the query data of the client through the query analysis module to obtain the adjacent interval value ratio, the time interval ratio and the total query number, processes the adjacent interval value ratio, the time interval ratio and the total query number to obtain the correlation value, judges the correlation value and generates a corresponding signaling, processes the signaling through the signaling processing module, and sends the corresponding production test data to the query end of the client, thereby facilitating the client to check the corresponding production test data through the query end at the first time.
Drawings
To facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
Fig. 1 is a schematic block diagram of the present invention.
FIG. 2 is a schematic view of the circular construction of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood 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.
Example 1
Referring to fig. 1-2, the production test data management system based on big data is based on a system basic module and a system module, and includes a test acquisition and analysis module, a data acquisition module, a database, an interface, a report management module, a billboard module, a material management module, a wafer management module, an equipment management module, and a program management module;
the system basic module and the system module are used for constructing modules required by the system; the interface is used for combining and packaging the required modules;
the test acquisition and analysis module is used for carrying out test analysis on the product to obtain production test data;
the data acquisition module is connected with the test equipment through the Internet of things, acquires production test data and sends the production test data to the database; the production test data comprises the incoming and outgoing station record information of all batches, the batch detailed information, the production batch record of the FT workshop, the equipment alarm detailed information, the production record information of the batches, the OEE detailed content of the equipment and the like.
A user inputs query conditions through a report management module and checks a display result corresponding to a target report, wherein the target report comprises a product output report, a production statistics report, an FT general test report, a CP general test report, an alarm record report, a batch history report and an equipment comprehensive benefit report;
the product output report is used for displaying the station-in and station-out record information of all batches; the production statistical report is used for displaying detailed information of production batches; the FT general test report is used for displaying the production batch records of the FT workshop; the CP general test report is used for displaying the production batch records of the CP workshop; the alarm record report is used for displaying alarm detail information of the first ten devices; the batch record report is used for displaying the production record information of the batch; the equipment comprehensive benefit report is used for displaying the detailed OEE content of the equipment; the yield report is used for displaying the yield corresponding to the product;
when the target report is a product output report or a production statistical report, the input query conditions are a client code, a product number, a work station, an equipment number, a batch number and a time period; the display result is serial number, batch current state, product code, product name, customer code, customer name, main equipment, auxiliary equipment, work station, station entering number, station exiting number, trackIn time and Trackout time;
when the target report is an FT general test report, the input query conditions are a client code, a product code, an equipment number, a batch number and a time period; the display result is serial number, batch current state, product code, product name, customer code, customer name, main equipment, auxiliary equipment, work station, batch times, non-defective product number, trackIn time and Trackout time;
when the target report is a CP general test report, the input query conditions are a client code, a product code, a batch number, a work order number and a time period; the display result is a serial number, a work order number, a batch number, a wafer number, a batch current state, a product code, a product name, a customer code, a customer name, single-chip Die data, a good product number, trackIn time and Trackout time;
when the target report is an alarm record report, the input query conditions are equipment type, equipment model, equipment number and start-stop time; the display results are an alarm number TOP10 and an equipment alarm TOP10; wherein the TOP10 alarm number comprises a serial number, alarm times, an alarm number and alarm details; the equipment alarm TOP10 comprises a serial number, alarm times, an equipment number and an equipment model;
when the target report is a batch record report, the input query conditions are a batch number, a main device, an auxiliary device, a start time and an end time; the display result is serial number, batch number, production state, product code, product name, customer number, main equipment, auxiliary equipment, plan start date, plan end date, packaging form, seal content and operation content;
when the target report is an equipment comprehensive benefit report, the input query conditions are equipment type, equipment model, equipment number and time period; the display result is a graph of the proportion of each state of the equipment, the equipment comprehensive efficiency OEE, yield data and numerical broken line trend; each state of the equipment comprises operation, standby, downtime, maintenance, repair, utilization rate, yield and comprehensive efficiency of the equipment;
wherein: operation = operation duration/total device power-on duration 100%;
standby = standby duration/total device power-on duration 100%;
downtime = downtime duration/total device power-on duration 100%;
maintenance = maintenance duration/total duration of equipment on 100%;
maintenance = maintenance duration/total equipment startup duration — 100%;
the utilization rate = 100% of the equipment operation duration/(operation duration + standby duration + downtime duration + maintenance duration +);
yield = total number of good products per total number of tests per day;
equipment integrated efficiency = utilization rate × yield rate 100%.
The billboard module displays equipment information, equipment state, an equipment state distribution diagram, alarm information and equipment alarm monitoring information in real time; wherein, the alarm information only displays the unprocessed alarm information; the equipment alarm monitoring information comprises the number of alarms, the processed and unprocessed alarm data on the same day, an alarm information list and the processed alarm information.
The user adds and edits material information or probe card information through the material management module, and is also used for the operation of getting and returning the material or the probe card; the material information comprises DUT numbers, material types, used periods, current use periods, units, states, client codes, equipment models, product models, factories, storage positions and remarks; the states include an IN state and an OUT state; the operation of material or probe card adoption specifically comprises: selecting a material or a probe card to be retrieved, clicking for retrieval, converting the state of the material or the probe card from an IN state to an OUT state, and setting the current time as ex-warehouse time; the returning operation of the material or the probe card is specifically to select the material or the probe card, click to return and update the service cycle, namely: current usage cycle = current time-ex time, used cycle = current time-ex time.
The wafer management module inquires chip information and imports and checks a wafer map through the chip carved number, the client code and the batch number; chip map information is inquired through inputting a batch number and an equipment number, map information data display, data real-time updating and merging, BIN self-defining acceptance, wafer map and Bin operation modification are carried out.
The user adds device reference information, adds and deletes the device, deletes the device binding, and manages the device model through the device management module, wherein the device reference information includes a device ID, a device state, a control state, a type, a test file path, whether to re-execute device software, a data acquisition mode, a device UPH, a factory number, an area number, and the like.
A user inputs test program information to be uploaded through a program management module and performs test program management, wherein the test program management comprises test program updating, test program approval, test program downloading and test program display;
updating the test program by finding test program data to be edited, clicking an editing button and adding the updated test program, and clicking a confirmation button to complete the updating of the test program after the editing is completed;
the test program approval is that when a user uploads the test program, a current login user exists in the selected test approval template, and the test program is in a mass production mode, the user displays the test program to be approved on the interface; click approval: completing the examination and approval of the test program; click rejection: rejecting the test program; only after the examination and approval of the 1-4 levels, the test program can be normally used;
the test program is downloaded by inputting a batch number of production, clicking a query button, finding the test program to be downloaded, clicking a download button and downloading the test program to the local;
the test programs are displayed to show the uploaded records of all test programs.
Example 2:
on the basis of the embodiment 1, the production test data management system based on big data further comprises a query statistic module, a query analysis module and a signaling processing module;
the inquiry counting module counts inquiry data corresponding to the client through an inquiry end, a product name corresponding to a client code, a corresponding station entering number and TrackIn time and sends the inquiry data to a database; the query data comprises online time, query time and query conditions; processing the product name corresponding to the client code, the corresponding station entering number and the TrackIn time, specifically:
setting all production names to correspond to a product preset value, extracting the numerical value of the station entering number, and multiplying the numerical value by the product preset value to obtain a single-side value; summing all the unilateral values corresponding to the client codes to obtain a unilateral total value; sequencing all TrackIn times corresponding to the client codes according to the time sequence, calculating the time difference between two adjacent TrackIn times to obtain one-side time length, summing all the one-side time lengths and averaging to obtain one-side average time length; counting the number of all TrackIn time corresponding to the client code to obtain the total time; extracting numerical values of the one-side mean time length, the one-side total value and the total time length, drawing a circle by taking the numerical values of the one-side total value and the total time length as a radius to obtain a first circle and a second circle, locating the circle centers of the first circle and the second circle on the same straight line and tangent, constructing the circle by taking the tangent point of the two tangent circles as the circle centers and the numerical value of the one-side mean time length as the radius to obtain a third circle, referring to the graph shown in figure 2, calculating the first area of the intersection of the first circle and the second area of the intersection of the third circle and the second circle to obtain a second area, and calculating the intersection area of the sum of the first area and the second area; and calculating the area sum of the first circle and the second circle to obtain a total area, extracting numerical values of the total area and the intersection area, dividing the numerical value of the total area by the numerical value of the intersection area to obtain a numerical value ratio, and marking the numerical value ratio as a length measurement basic value corresponding to the client code.
The query analysis module analyzes the query data, and the specific analysis process comprises the following steps: classifying the query conditions, classifying the query conditions with the same query content into one class and marking the query conditions as the same query conditions, acquiring all query moments of the same query conditions, counting the total query number of the query moments, and sequencing all the query moments according to the time sequence when the total query number is greater than a set number;
calculating the sorted query moments, calculating the time difference between every two adjacent query moments to obtain interval duration, extracting numerical values corresponding to all the interval durations to sort according to the time sequence, comparing the numerical values sorted in the front with the numerical values sorted in the rear, and calculating the numerical value difference between the numerical values sorted in the front and the numerical values sorted in the rear to obtain an adjacent interval value I when the numerical values sorted in the front are larger than the numerical values sorted in the rear; when the numerical value sorted in the front is smaller than the numerical value sorted in the rear, calculating the numerical value difference between the numerical value and the rear numerical value, and taking the absolute value to obtain a second adjacent value; summing all the adjacent interval values I and taking the average value to obtain an adjacent interval mean value I, summing all the adjacent interval values II and taking the average value to obtain an adjacent interval mean value II; dividing the adjacent interval mean value two by the adjacent interval mean value one to obtain an adjacent interval numerical value ratio;
summing all the interval durations and averaging to obtain a mean duration, extracting numerical values of the mean duration and the online duration, and dividing the numerical value of the online duration by the numerical value of the mean duration to obtain an on-interval time ratio;
extracting values of adjacent interval value ratio, time interval ratio and query total number, marking the values as QM1, QM2 and SMC, and substituting the values into a preset analysis model
Obtaining a correlation value FQ corresponding to the query condition; wherein eq1, eq2 and eq3 are preset weight coefficients corresponding to the adjacent interval numerical ratio, the time interval ratio and the total query number, and the specific size of the preset weight coefficients is set by an administrator in a self-defined manner according to actual needs; the mu is a length measurement base value corresponding to the client code;
when the check-off value FQ is larger than the set check-off threshold YQ1, judging the check-off value FQ:
presetting a first threshold YQ2 and a second threshold YQ3; wherein YQ1< YQ2< YQ3;
when YQ1< FQ is less than or equal to YQ2, generating a light check signaling corresponding to the query condition and sending the light check signaling to a signaling processing module; the query signaling comprises a client code, a client name, a query instruction, query condition content and a communication address of a query end;
when YQ2 is more than FQ and less than or equal to YQ3, generating a center check signaling corresponding to the query condition and sending the center check signaling to a signaling processing module; the inquiry signaling comprises a client code, a client name, an inquiry command, inquiry condition content and a communication address of an inquiry end;
when YQ3 is less than FQ, generating a rechecking signaling corresponding to the query condition and sending the rechecking signaling to the signaling processing module; wherein, the rechecking signaling comprises a client code, a client name, the rechecking signaling, query condition content and a communication address of a query end; the light checking instruction, the middle checking instruction and the re-checking signaling are character strings which are used for the signaling processing module to identify and have special structures so that the signaling processing module can execute corresponding operation programs.
The signaling processing module is used for receiving and processing a light check signaling or a middle check signaling or a recheck signaling corresponding to the query condition, and the specific processing process is as follows:
when the light check signaling is received, analyzing the light check signaling to obtain a client code, a client name, a light check instruction, query condition content and a communication address of a query end; the production test data acquisition module is connected with the data acquisition module and monitors the production test data acquired by the data acquisition module in real time, and when the production test data corresponding to the client code, the client name and the query condition is monitored within a preset time length I, the production test data is sent to a query end corresponding to the communication address;
when the inquiry signaling is received, analyzing the inquiry signaling to obtain a client code, a client name, an inquiry instruction, inquiry condition content and a communication address of an inquiry end; within the preset time length two, when monitoring production test data corresponding to the client code, the client name and the query condition, sending the production test data to a query end corresponding to the communication address;
when receiving the rechecking signaling, analyzing the rechecking signaling to obtain a client code, a client name, a rechecking instruction, query condition content and a communication address of a query end; within a preset time length III, when monitoring production test data corresponding to the client code, the client name and the query condition, sending the production test data to a query end corresponding to the communication address, acquiring a check result corresponding to the query end, and when the check result is a stop instruction, stopping monitoring the production test data corresponding to the client code, the client name and the query condition and sending the production test data; when the check result is the click check time I corresponding to the production test data, counting all click check times I in a time range corresponding to a preset time length III, calculating the time difference between the click check time I and the time corresponding to the production test data sending to obtain a click check time length, calculating the mean value of all the click check time lengths to obtain a click check mean value time length, and when the click check mean value time length is larger than a set time length threshold value, stopping monitoring the production test data corresponding to the client code, the client name and the query condition and sending the production test data.
When the system is used, a report management module, a billboard module, a material management module, a wafer management module, an equipment management module and a program management module are arranged, so that a large amount of production test data can be conveniently displayed and managed, and a user can inquire and visually know the production test data; the inquiry analysis module analyzes the inquiry data of the client to obtain the adjacent interval value ratio, the time interval ratio and the inquiry total number, processes the adjacent interval value ratio, the time interval ratio and the inquiry total number to obtain the correlation value, judges the correlation value and generates a corresponding signaling, processes the signaling through the signaling processing module, and sends the corresponding production test data to the inquiry end of the client, so that the client can conveniently check the corresponding production test data through the inquiry end at the first time.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (5)
1. The production test data management system based on big data comprises a test acquisition and analysis module, a data acquisition module, a database and an interface based on a system basic module and a system module, wherein the test acquisition and analysis module is used for carrying out test analysis on a product to obtain production test data; the data acquisition module is used for acquiring production test data through the Internet of things and sending the production test data to the database; it is characterized by also comprising:
the report management module is used for inputting query conditions and checking a display result corresponding to the target report; the target report comprises a product output report, a production statistics report, an FT general test report, a CP general test report, an alarm record report, a batch history report and an equipment comprehensive benefit report;
the system comprises a billboard module, a monitoring module and a display module, wherein the billboard module is used for displaying equipment information, equipment states, an equipment state distribution map, alarm information and equipment alarm monitoring information in real time;
the material management module is used for adding and editing material information or probe card information and is also used for receiving and returning the material or the probe card;
the wafer management module is used for inquiring chip information through the chip scale number, the client code and the batch number and inquiring chip map information and map information data display through inputting the batch number and the equipment number; the wafer map importing and checking system also has the functions of importing and checking the wafer map, updating and merging data in real time, self-defining acceptance of BIN, monitoring wafer map and modifying Bin operation;
the device management module is used for adding device reference information, adding device binding, deleting the device binding and managing the device model;
the program management module is used for inputting test program information to be uploaded and carrying out test program management, wherein the test program management comprises test program updating, test program approval, test program downloading and test program display;
the query statistical module is used for counting query data corresponding to the client through the query end and sending the query data to the database;
the query analysis module is used for analyzing the query data to generate a corresponding signaling, and the specific process is as follows:
classifying the query conditions, classifying the query conditions with the same query content into one class and marking the query conditions as the same query conditions, acquiring all query moments of the same query conditions, counting the query total number of the query moments, and sequencing all the query moments according to the time sequence when the query total number is greater than a set number;
calculating and processing the sorted query moments to obtain an adjacency-interval numerical ratio; the specific process is as follows: calculating the time difference between two adjacent query moments to obtain interval duration, extracting numerical values corresponding to all the interval durations, sorting according to the time sequence, comparing the numerical values sorted in the front with the numerical values sorted in the back, and calculating the numerical value difference between the two numerical values to obtain a first adjacent interval value when the numerical values sorted in the front are greater than the numerical values sorted in the back; when the numerical value sorted in the front is smaller than the numerical value sorted in the rear, calculating the numerical value difference between the numerical value and the rear numerical value, and taking the absolute value to obtain a second adjacent value; summing all the adjacent separation values I and taking the average value to obtain an adjacent separation average value I, summing all the adjacent separation values II and taking the average value to obtain an adjacent separation average value II; dividing the adjacent-interval mean value two by the adjacent-interval mean value one to obtain an adjacent-interval numerical value ratio;
summing all the interval durations and taking the average to obtain a mean duration, extracting numerical values of the mean duration and the online duration, and dividing the numerical value of the online duration by the numerical value of the mean duration to obtain an interval time ratio;
extracting numerical values of the adjacent interval numerical value ratio, the time interval ratio and the total query number, and substituting the numerical values into a preset analysis model to obtain a correlation check value corresponding to the query condition;
when the check value FQ is greater than the set check threshold YQ1, the check value FQ is determined:
when YQ1< FQ is less than or equal to YQ2, generating a light check signaling corresponding to the query condition and sending the light check signaling to a signaling processing module;
when YQ2 is more than FQ and less than or equal to YQ3, generating a center check signaling corresponding to the query condition and sending the center check signaling to a signaling processing module;
when YQ3 is less than FQ, generating a rechecking signaling corresponding to the query condition and sending the rechecking signaling to the signaling processing module;
the signaling processing module is used for receiving and processing the light check signaling or the middle check signaling or the recheck signaling corresponding to the query condition, and the specific processing process is as follows:
when the light check signaling is received, analyzing the light check signaling to obtain a client code, a client name, a light check instruction, query condition content and a communication address of a query end; the production test data acquisition module is connected with the data acquisition module and monitors the production test data acquired by the data acquisition module in real time, and when the production test data corresponding to the client code, the client name and the query condition is monitored within a preset time length, the production test data is sent to a query end corresponding to the communication address;
when the inquiry signaling is received, analyzing the inquiry signaling to obtain a client code, a client name, an inquiry instruction, inquiry condition content and a communication address of an inquiry end; within the preset time length two, when monitoring production test data corresponding to the client code, the client name and the query condition, sending the production test data to a query end corresponding to the communication address;
when receiving the rechecking signaling, analyzing the rechecking signaling to obtain a client code, a client name, a rechecking instruction, query condition content and a communication address of a query end; within the preset time length III, when monitoring production test data corresponding to the client code, the client name and the query condition, sending the production test data to a query end corresponding to the communication address, acquiring a check result corresponding to the query end, and when the check result is a stop instruction, stopping monitoring the production test data corresponding to the client code, the client name and the query condition and sending the production test data; when the check result is the click check time I corresponding to the production test data, counting all click check times I in a time range corresponding to a preset time length III, calculating the time difference between the click check time I and the time corresponding to the production test data sending to obtain a click check time length, calculating the mean value of all the click check time lengths to obtain a click check mean value time length, and when the click check mean value time length is larger than a set time length threshold value, stopping monitoring the production test data corresponding to the client code, the client name and the query condition and sending the production test data.
2. The big data based production test data management system of claim 1, wherein the material management module is configured to control a life cycle of material usage; the operation of material or probe card adoption specifically comprises the following steps: selecting a material or a probe card to be used, clicking to use, converting the state of the material or the probe card from an IN state to an OUT state, and setting the current time as ex-warehouse time; the return operation of the material or the probe card is specifically to select the material or the probe card, click the return and update the service cycle.
3. The big data based production test data management system as claimed in claim 1, wherein the product output report is used to display the in-and-out record information of all batches; the production statistical report is used for displaying detailed information of production batches; the FT general test report is used for displaying the production batch records of the FT workshop; the CP general test report is used for displaying the production batch records of the CP workshop; the alarm record report is used for displaying alarm detail information of the first ten devices; the batch record report is used for displaying the production record information of the batch; the equipment comprehensive benefit report is used for displaying OEE detailed contents of the equipment.
4. The big-data-based production test data management system according to claim 3, wherein when the target report is a product yield report or a production statistics report, the input query conditions are a customer code, a product number, a workstation, an equipment number, a batch number, and a time period; the display result is a serial number, a batch current state, a product code, a product name, a client code, a client name, main equipment, auxiliary equipment, a work station, a station entering number, a station exiting number of good products, trackIn time and Trackout time;
when the target report is an FT general test report, the input query conditions are a client code, a product code, an equipment number, a batch number and a time period; the display result is serial number, batch current state, product code, product name, customer code, customer name, main equipment, auxiliary equipment, work station, batch times, non-defective product number, trackIn time and Trackout time;
when the target report is a CP general test report, the input query conditions are a client code, a product code, a batch number, a work order number and a time period; the display result is a serial number, a work order number, a batch number, a wafer number, a batch current state, a product code, a product name, a customer code, a customer name, single-chip Die data, a good product number, trackIn time and Trackout time;
when the target report is an alarm record report, the input query conditions are equipment type, equipment model, equipment number and start-stop time; the display results are an alarm number TOP10 and an equipment alarm TOP10; wherein the TOP10 alarm number comprises a serial number, alarm times, an alarm number and alarm details; the equipment alarm TOP10 comprises a serial number, alarm times, an equipment number and an equipment model;
when the target report is a batch record report, the input query conditions are a batch number, a main device, an auxiliary device, a start time and an end time; the display result is serial number, batch number, production state, product code, product name, customer number, main equipment, auxiliary equipment, plan start date, plan end date, packaging form, seal content and operation content;
when the target report is an equipment comprehensive benefit report, the input query conditions are equipment type, equipment model, equipment number and time period; the display result is a graph with the proportion of each state of the equipment, the comprehensive efficiency OEE of the equipment, the yield data and the numerical broken line trend; the states of the equipment comprise operation, standby, downtime, maintenance, repair, utilization rate, yield and comprehensive efficiency of the equipment.
5. The big data based production test data management system according to claim 1, wherein the query statistics module is further configured to count and process product names, corresponding inbound times, and TrackIn times corresponding to customer codes; setting all production names to correspond to a product preset value, extracting the numerical value of the station entering number, and multiplying the numerical value by the product preset value to obtain a single-side value; summing all the unilateral values corresponding to the client codes to obtain a unilateral total value; sequencing all TrackIn times corresponding to the client codes according to the time sequence, calculating the time difference between two adjacent TrackIn times to obtain one-side time length, summing all the one-side time lengths and averaging to obtain one-side average time length; counting the number of all TrackIn times corresponding to the client codes to obtain the total time; and extracting the values of the average time length of the single side, the total value of the single side and the total time and processing the values to obtain a length measurement basic value corresponding to the client code.
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