CN117828450B - Big data-based package test method, system and medium - Google Patents
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- 238000010998 test method Methods 0.000 title claims description 12
- 238000012360 testing method Methods 0.000 claims abstract description 360
- 238000011056 performance test Methods 0.000 claims abstract description 271
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- 238000004806 packaging method and process Methods 0.000 claims abstract description 89
- 230000002159 abnormal effect Effects 0.000 claims abstract description 33
- 238000012797 qualification Methods 0.000 claims abstract description 24
- 238000000034 method Methods 0.000 claims abstract description 17
- 238000004364 calculation method Methods 0.000 claims description 18
- 230000001052 transient effect Effects 0.000 claims description 18
- 230000017525 heat dissipation Effects 0.000 claims description 16
- 238000009863 impact test Methods 0.000 claims description 14
- 230000003044 adaptive effect Effects 0.000 claims description 12
- 230000032683 aging Effects 0.000 claims description 12
- 238000012549 training Methods 0.000 claims description 8
- 230000035882 stress Effects 0.000 claims description 7
- 238000005382 thermal cycling Methods 0.000 claims description 4
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Abstract
The application provides a package testing method, a system and a medium based on big data. The method comprises the following steps: and packaging the chip to obtain a packaged chip, testing the packaged chip by using a preset chip packaging test platform to obtain test result data, processing the test result data to obtain an electrical performance test index, a thermal performance test index and a mechanical performance test index, calculating to obtain a reliability test index, judging the qualification of the packaged chip according to the reliability test index, if the packaged chip is judged to be unqualified, acquiring historical test record data of the same type of packaged chip, extracting test abnormal record data, processing the test abnormal record data to generate a fault type identification model according to the test abnormal record data, inputting the test result data into the fault type identification model for processing, obtaining a fault type, and matching with a corresponding fault repair strategy. The application can realize the technology of intelligently detecting the packaged chip and identifying the fault category.
Description
Technical Field
The application relates to the technical field of big data and package testing, in particular to a package testing method, system and medium based on big data.
Background
The method is very important to test the packaged chips, and the test significance is to ensure that the functions, performances and reliability of the chips meet expectations and avoid faults or problems in the production and use processes. Specifically, the test can find defects and errors in the chip, evaluate the performance and stability of the chip, and provide basis for quality control and fault elimination in the production process, so that the test of the packaged chip is one of important means for ensuring the quality of the chip and improving the production efficiency. However, a technology for intelligently detecting the packaged chip and identifying the fault type based on big data is not yet available at present.
In view of the above problems, an effective technical solution is currently needed.
Disclosure of Invention
The application aims to provide a packaging test method, a system and a medium based on big data, wherein an electrical performance test index, a thermal performance test index and a mechanical performance test index are obtained according to the test result processing of a packaging chip, a reliability test index is obtained through calculation, the packaging chip is subjected to qualification judgment according to the reliability test index, if the packaging chip is judged to be unqualified, a fault class identification model is generated according to the historical test abnormal record data processing of the same type packaging chip, the test result data is input into the fault class identification model for processing, the fault class is obtained, and a corresponding fault repair strategy is matched.
The application also provides a package testing method based on big data, which comprises the following steps:
Packaging the chip to obtain a packaged chip;
testing the packaged chip by using a preset chip packaging test platform to obtain test result data, including electrical performance test data, thermal performance test data and mechanical performance test data;
Processing according to the electrical performance test data to obtain an electrical performance test index, processing according to the thermal performance test data to obtain a thermal performance test index, and processing according to the mechanical performance test data to obtain a mechanical performance test index;
Calculating according to the electrical performance test index, the thermal performance test index and the mechanical performance test index to obtain a reliability test index, and judging the qualification of the packaged chip according to the reliability test index;
If the packaging chip is judged to be unqualified, historical test record data of the same type of packaging chip are obtained, test abnormal record data are extracted, and a fault class identification model is generated according to the test abnormal record data;
and inputting the test result data into the fault category identification model for processing to obtain a fault category, and matching the fault category with a corresponding fault repair strategy.
Optionally, in the big data based packaging test method of the present application, the packaging the chip to obtain a packaged chip includes:
Acquiring chip type data and user packaging demand data;
Inputting the chip type data and the user packaging requirement data into a preset chip packaging mode database for matching and identifying to obtain an adaptive packaging mode;
And packaging the chip according to the adaptive packaging mode to obtain a packaged chip.
Optionally, in the big data based package testing method of the present application, the testing the packaged chip by using a preset chip package testing platform to obtain test result data, including electrical performance test data, thermal performance test data and mechanical performance test data, includes:
The electrical performance test data comprises power supply voltage test data, time sequence performance test data and transient performance test data;
the thermal performance test data comprises thermal cycle test data, high-temperature aging test data, overheat protection test data and heat dissipation test data;
The mechanical performance test data includes vibration test data, impact test data, and mechanical stress test data.
Optionally, in the big data based package testing method of the present application, the processing according to the electrical performance testing data to obtain an electrical performance testing index, processing according to the thermal performance testing data to obtain a thermal performance testing index, and processing according to the mechanical performance testing data to obtain a mechanical performance testing index includes:
Processing according to the power supply voltage test data, the time sequence performance test data and the transient performance test data to obtain an electrical performance test index;
Processing according to the thermal cycle test data, the high-temperature aging test data, the overheat protection test data and the heat dissipation test data to obtain a thermal performance test index;
and processing according to the vibration test data, the impact test data and the mechanical pressure test data to obtain a mechanical performance test index.
Optionally, in the big data based package testing method of the present application, the calculating according to the electrical performance testing index, the thermal performance testing index and the mechanical performance testing index to obtain a reliability testing index, and the performing the qualification judgment on the packaged chip according to the reliability testing index includes:
Calculating according to the electrical performance test index, the thermal performance test index and the mechanical performance test index to obtain a reliability test index;
comparing the reliability test index with a preset reliability test index threshold value to obtain a threshold value comparison result;
And if the threshold comparison result meets the preset threshold comparison requirement, judging the qualification of the packaged chip, otherwise, judging the disqualification.
Optionally, in the big data based packaging test method of the present application, if the packaged chip is determined to be unqualified, historical test record data of the same type of packaged chip is obtained, test anomaly record data is extracted, and a fault class identification model is generated according to the test anomaly record data processing, including:
If the packaged chip is judged to be unqualified, historical test record data of the same type of packaged chip is obtained;
Extracting test anomaly record data according to the historical test record data, wherein the test anomaly record data comprises electric anomaly record data, thermal anomaly record data and mechanical anomaly record data;
And training the electrical anomaly record data, the thermal anomaly record data and the mechanical anomaly record data by using a preset model training algorithm to generate a fault type identification model.
Optionally, in the big data based package testing method of the present application, the inputting the test result data into the fault category identification model for processing, obtaining a fault category, and matching a corresponding fault repair policy includes:
inputting the electrical performance test data, the thermal performance test data and the mechanical performance test data into the fault type identification model for processing to obtain fault type data;
And inputting the fault type data into a preset fault restoration strategy library for matching identification, and obtaining a fault restoration strategy.
In a second aspect, the present application provides a big data based package testing system, the system comprising: the memory comprises a program of a package testing method based on big data, and the program of the package testing method based on big data realizes the following steps when being executed by the processor:
Packaging the chip to obtain a packaged chip;
testing the packaged chip by using a preset chip packaging test platform to obtain test result data, including electrical performance test data, thermal performance test data and mechanical performance test data;
Processing according to the electrical performance test data to obtain an electrical performance test index, processing according to the thermal performance test data to obtain a thermal performance test index, and processing according to the mechanical performance test data to obtain a mechanical performance test index;
Calculating according to the electrical performance test index, the thermal performance test index and the mechanical performance test index to obtain a reliability test index, and judging the qualification of the packaged chip according to the reliability test index;
If the packaging chip is judged to be unqualified, historical test record data of the same type of packaging chip are obtained, test abnormal record data are extracted, and a fault class identification model is generated according to the test abnormal record data;
and inputting the test result data into the fault category identification model for processing to obtain a fault category, and matching the fault category with a corresponding fault repair strategy.
Optionally, in the big data based package testing system of the present application, the packaging the chip to obtain a packaged chip includes:
Acquiring chip type data and user packaging demand data;
Inputting the chip type data and the user packaging requirement data into a preset chip packaging mode database for matching and identifying to obtain an adaptive packaging mode;
And packaging the chip according to the adaptive packaging mode to obtain a packaged chip.
In a third aspect, the present application also provides a computer readable storage medium, including therein a big data based package test method program, which when executed by a processor, implements the steps of the big data based package test method as described in any of the above.
As can be seen from the above, the big data based package testing method, system and medium provided by the application are used for processing and obtaining an electrical performance testing index, a thermal performance testing index and a mechanical performance testing index according to the testing result of a package chip, calculating and obtaining a reliability testing index, judging the qualification of the package chip according to the reliability testing index, if the package chip is judged to be unqualified, processing and generating a fault type identification model according to the historical test abnormal record data of the same type package chip, inputting the testing result data into the fault type identification model for processing, obtaining a fault type, and matching with a corresponding fault repair strategy.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the embodiments of the application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a big data based package testing method according to an embodiment of the present application;
fig. 2 is a flowchart of a method for obtaining a packaged chip according to a big data based package test method according to an embodiment of the present application;
FIG. 3 is a flowchart of a method for testing a package based on big data for performing qualification judgment on a packaged chip according to an embodiment of the present application;
fig. 4 is a flowchart of a fault class identification model generated by the big data based package testing method according to the embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
It should be noted that like reference numerals and letters refer to like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.
Referring to fig. 1, fig. 1 is a flowchart of a big data based package testing method according to some embodiments of the application. The big data based packaging test method is used in terminal equipment, such as computers, mobile phone terminals and the like. The package testing method based on big data comprises the following steps:
S11, packaging the chip to obtain a packaged chip;
S12, testing the packaged chip by using a preset chip packaging test platform to obtain test result data, wherein the test result data comprises electric performance test data, thermal performance test data and mechanical performance test data;
S13, processing according to the electrical performance test data to obtain an electrical performance test index, processing according to the thermal performance test data to obtain a thermal performance test index, and processing according to the mechanical performance test data to obtain a mechanical performance test index;
s14, calculating according to the electrical performance test index, the thermal performance test index and the mechanical performance test index to obtain a reliability test index, and judging the qualification of the packaged chip according to the reliability test index;
s15, if the packaged chips are judged to be unqualified, historical test record data of the same type of packaged chips are obtained, test abnormal record data are extracted, and a fault class identification model is generated according to the test abnormal record data;
S16, inputting the test result data into the fault category identification model for processing, obtaining a fault category, and matching with a corresponding fault repair strategy.
It should be noted that the application can realize the purposes of intelligent detection and fault category identification of the packaged chip, and specifically comprises the following steps: and processing according to the test result of the packaged chip to obtain an electrical performance test index, a thermal performance test index and a mechanical performance test index, calculating to obtain a reliability test index, judging the qualification of the packaged chip according to the reliability test index, if the packaged chip is judged to be unqualified, processing according to the historical test abnormal record data of the same type of packaged chip to generate a fault type identification model, inputting the test result data into the fault type identification model for processing, obtaining a fault type, and matching with a corresponding fault repair strategy.
Referring to fig. 2, fig. 2 is a flowchart of a method for obtaining a packaged chip according to a big data based package test method in some embodiments of the application. According to an embodiment of the present application, the packaging of a chip to obtain a packaged chip includes:
S21, acquiring chip type data and user packaging demand data;
S22, inputting the chip type data and the user packaging requirement data into a preset chip packaging mode database for matching and identifying to obtain an adaptive packaging mode;
S23, packaging the chip according to the adaptive packaging mode to obtain a packaged chip.
It should be noted that, the adapted chip packaging mode is selected according to the chip type and the user packaging requirement.
According to an embodiment of the present invention, the testing of the packaged chip by using a preset chip package testing platform to obtain test result data, including electrical performance testing data, thermal performance testing data, and mechanical performance testing data, includes:
The electrical performance test data comprises power supply voltage test data, time sequence performance test data and transient performance test data;
the thermal performance test data comprises thermal cycle test data, high-temperature aging test data, overheat protection test data and heat dissipation test data;
The mechanical performance test data includes vibration test data, impact test data, and mechanical stress test data.
It should be noted that the electrical performance test data includes power supply voltage test data, which is test data obtained by checking the operation performance of the packaged chip under various power supply voltages, time series performance test data, which is test data obtained by checking the performance of the packaged chip under transient interference (including electrostatic discharge, electromagnetic interference, etc.), and transient performance test data, which is test data obtained by testing the signal transmission speed and delay time between the packaged chip and other components; the thermal performance test data includes thermal cycle test data, high temperature burn-in test data, overheat protection test data, and heat dissipation test data, which are test data obtained by simulating temperature changes that a chip may experience during long-term use, and checking whether the chip can withstand such changes without performance degradation or damage.
According to an embodiment of the present invention, the processing according to the electrical performance test data to obtain an electrical performance test index, the processing according to the thermal performance test data to obtain a thermal performance test index, and the processing according to the mechanical performance test data to obtain a mechanical performance test index includes:
Processing according to the power supply voltage test data, the time sequence performance test data and the transient performance test data to obtain an electrical performance test index;
Processing according to the thermal cycle test data, the high-temperature aging test data, the overheat protection test data and the heat dissipation test data to obtain a thermal performance test index;
and processing according to the vibration test data, the impact test data and the mechanical pressure test data to obtain a mechanical performance test index.
It should be noted that, in order to determine the reliability of the packaged chip later, it is necessary to obtain an electrical performance test index according to electrical performance test data processing, obtain a thermal performance test index according to thermal performance test data processing, and obtain a mechanical performance test index according to mechanical performance test data processing;
The calculation formula of the electrical performance test index is as follows:
；
wherein, Is an electrical performance test index,/>For the supply voltage test data,/>For time series performance test data,/>For transient performance test data,/>、/>、/>Is a preset characteristic coefficient (can be obtained by inquiring a preset chip packaging test platform);
The calculation formula of the thermal performance test index is as follows:
；
wherein, For thermal performance test index,/>For thermal cycling test data,/>For the high temperature burn-in test data,For overheat protection test data,/>For heat dissipation test data,/>、/>、/>、/>Is a preset characteristic coefficient (can be obtained by inquiring a preset chip packaging test platform);
the calculation formula of the mechanical performance test index is as follows:
；
wherein, For the mechanical test index,/>For vibration test data,/>For impact test data,/>For mechanical stress test data,/>、/>Is a preset characteristic coefficient (which can be obtained by inquiring a preset chip package test platform).
Referring to fig. 3, fig. 3 is a flowchart of a method for testing a package based on big data according to some embodiments of the present application for performing qualification determination on a packaged chip. According to an embodiment of the present application, the calculating according to the electrical performance test index, the thermal performance test index, and the mechanical performance test index to obtain a reliability test index, and the performing the qualification judgment on the packaged chip according to the reliability test index includes:
S31, calculating according to the electrical performance test index, the thermal performance test index and the mechanical performance test index to obtain a reliability test index;
s32, comparing the reliability test index with a preset reliability test index threshold value to obtain a threshold value comparison result;
s33, if the threshold comparison result meets a preset threshold comparison requirement, judging the qualification of the packaged chip, otherwise, judging the disqualification.
The reliability test index is obtained by calculating according to the electrical performance test index, the thermal performance test index and the mechanical performance test index, and the qualification of the packaged chip is judged according to the reliability test index;
The calculation formula of the reliability test index is as follows:
；
wherein, Is a reliability test index,/>Is an electrical performance test index,/>For the thermal performance test index to be a function of,For the mechanical test index,/>、/>、/>Is a preset characteristic coefficient (which can be obtained by inquiring a preset chip package test platform).
Referring to fig. 4, fig. 4 is a flowchart illustrating a fault class identification model generation method according to a big data based package testing method according to some embodiments of the present application. According to the embodiment of the application, if the packaged chip is judged to be unqualified, the historical test record data of the same type of packaged chip is obtained, the test abnormal record data is extracted, and a fault class identification model is generated according to the test abnormal record data, and the method comprises the following steps:
s41, if the packaged chip is judged to be unqualified, historical test record data of the same type of packaged chip is obtained;
S42, extracting test abnormal record data according to the historical test record data, wherein the test abnormal record data comprises electric abnormal record data, thermal abnormal record data and mechanical abnormal record data;
S43, training the electrical anomaly record data, the thermal anomaly record data and the mechanical anomaly record data by using a preset model training algorithm to generate a fault type identification model.
If the packaged chip is judged to be unqualified, historical test record data of the same type of packaged chip is obtained, test abnormal record data are extracted, and a fault type identification model is generated according to the test abnormal record data.
According to an embodiment of the present invention, the inputting the test result data into the fault category identification model for processing, obtaining a fault category, and matching a corresponding fault repair policy includes:
inputting the electrical performance test data, the thermal performance test data and the mechanical performance test data into the fault type identification model for processing to obtain fault type data;
And inputting the fault type data into a preset fault restoration strategy library for matching identification, and obtaining a fault restoration strategy.
It should be noted that, the electrical performance test data, the thermal performance test data and the mechanical performance test data are input into the fault category identification model for processing, so as to obtain the fault category, and the fault category is matched with the corresponding fault repair strategy.
The invention also discloses a package testing system based on big data, which comprises a memory and a processor, wherein the memory comprises a package testing method program based on big data, and the package testing method program based on big data realizes the following steps when being executed by the processor:
Packaging the chip to obtain a packaged chip;
testing the packaged chip by using a preset chip packaging test platform to obtain test result data, including electrical performance test data, thermal performance test data and mechanical performance test data;
Processing according to the electrical performance test data to obtain an electrical performance test index, processing according to the thermal performance test data to obtain a thermal performance test index, and processing according to the mechanical performance test data to obtain a mechanical performance test index;
Calculating according to the electrical performance test index, the thermal performance test index and the mechanical performance test index to obtain a reliability test index, and judging the qualification of the packaged chip according to the reliability test index;
If the packaging chip is judged to be unqualified, historical test record data of the same type of packaging chip are obtained, test abnormal record data are extracted, and a fault class identification model is generated according to the test abnormal record data;
and inputting the test result data into the fault category identification model for processing to obtain a fault category, and matching the fault category with a corresponding fault repair strategy.
It should be noted that the application can realize the purposes of intelligent detection and fault category identification of the packaged chip, and specifically comprises the following steps: and processing according to the test result of the packaged chip to obtain an electrical performance test index, a thermal performance test index and a mechanical performance test index, calculating to obtain a reliability test index, judging the qualification of the packaged chip according to the reliability test index, if the packaged chip is judged to be unqualified, processing according to the historical test abnormal record data of the same type of packaged chip to generate a fault type identification model, inputting the test result data into the fault type identification model for processing, obtaining a fault type, and matching with a corresponding fault repair strategy.
According to an embodiment of the present invention, the packaging of a chip to obtain a packaged chip includes:
Acquiring chip type data and user packaging demand data;
Inputting the chip type data and the user packaging requirement data into a preset chip packaging mode database for matching and identifying to obtain an adaptive packaging mode;
And packaging the chip according to the adaptive packaging mode to obtain a packaged chip.
It should be noted that, the adapted chip packaging mode is selected according to the chip type and the user packaging requirement.
According to an embodiment of the present invention, the testing of the packaged chip by using a preset chip package testing platform to obtain test result data, including electrical performance testing data, thermal performance testing data, and mechanical performance testing data, includes:
The electrical performance test data comprises power supply voltage test data, time sequence performance test data and transient performance test data;
the thermal performance test data comprises thermal cycle test data, high-temperature aging test data, overheat protection test data and heat dissipation test data;
The mechanical performance test data includes vibration test data, impact test data, and mechanical stress test data.
It should be noted that the electrical performance test data includes power supply voltage test data, which is test data obtained by checking the operation performance of the packaged chip under various power supply voltages, time series performance test data, which is test data obtained by checking the performance of the packaged chip under transient interference (including electrostatic discharge, electromagnetic interference, etc.), and transient performance test data, which is test data obtained by testing the signal transmission speed and delay time between the packaged chip and other components; the thermal performance test data includes thermal cycle test data, high temperature burn-in test data, overheat protection test data, and heat dissipation test data, which are test data obtained by simulating temperature changes that a chip may experience during long-term use, and checking whether the chip can withstand such changes without performance degradation or damage.
According to an embodiment of the present invention, the processing according to the electrical performance test data to obtain an electrical performance test index, the processing according to the thermal performance test data to obtain a thermal performance test index, and the processing according to the mechanical performance test data to obtain a mechanical performance test index includes:
Processing according to the power supply voltage test data, the time sequence performance test data and the transient performance test data to obtain an electrical performance test index;
Processing according to the thermal cycle test data, the high-temperature aging test data, the overheat protection test data and the heat dissipation test data to obtain a thermal performance test index;
and processing according to the vibration test data, the impact test data and the mechanical pressure test data to obtain a mechanical performance test index.
It should be noted that, in order to determine the reliability of the packaged chip later, it is necessary to obtain an electrical performance test index according to electrical performance test data processing, obtain a thermal performance test index according to thermal performance test data processing, and obtain a mechanical performance test index according to mechanical performance test data processing;
The calculation formula of the electrical performance test index is as follows:
；
wherein, Is an electrical performance test index,/>For the supply voltage test data,/>For time series performance test data,/>For transient performance test data,/>、/>、/>Is a preset characteristic coefficient (can be obtained by inquiring a preset chip packaging test platform);
The calculation formula of the thermal performance test index is as follows:
；
wherein, For thermal performance test index,/>For thermal cycling test data,/>For the high temperature burn-in test data,For overheat protection test data,/>For heat dissipation test data,/>、/>、/>、/>Is a preset characteristic coefficient (can be obtained by inquiring a preset chip packaging test platform);
the calculation formula of the mechanical performance test index is as follows:
；
wherein, For the mechanical test index,/>For vibration test data,/>For impact test data,/>For mechanical stress test data,/>、/>Is a preset characteristic coefficient (which can be obtained by inquiring a preset chip package test platform).
According to an embodiment of the present invention, the calculating according to the electrical performance test index, the thermal performance test index, and the mechanical performance test index to obtain a reliability test index, and the performing the qualification judgment on the packaged chip according to the reliability test index includes:
Calculating according to the electrical performance test index, the thermal performance test index and the mechanical performance test index to obtain a reliability test index;
comparing the reliability test index with a preset reliability test index threshold value to obtain a threshold value comparison result;
And if the threshold comparison result meets the preset threshold comparison requirement, judging the qualification of the packaged chip, otherwise, judging the disqualification.
The reliability test index is obtained by calculating according to the electrical performance test index, the thermal performance test index and the mechanical performance test index, and the qualification of the packaged chip is judged according to the reliability test index;
The calculation formula of the reliability test index is as follows:
；
wherein, Is a reliability test index,/>Is an electrical performance test index,/>For the thermal performance test index to be a function of,For the mechanical test index,/>、/>、/>Is a preset characteristic coefficient (which can be obtained by inquiring a preset chip package test platform).
According to the embodiment of the invention, if the packaged chip is judged to be unqualified, the historical test record data of the same type of packaged chip is obtained, the test abnormal record data is extracted, and a fault class identification model is generated according to the test abnormal record data, and the method comprises the following steps:
If the packaged chip is judged to be unqualified, historical test record data of the same type of packaged chip is obtained;
Extracting test anomaly record data according to the historical test record data, wherein the test anomaly record data comprises electric anomaly record data, thermal anomaly record data and mechanical anomaly record data;
And training the electrical anomaly record data, the thermal anomaly record data and the mechanical anomaly record data by using a preset model training algorithm to generate a fault type identification model.
If the packaged chip is judged to be unqualified, historical test record data of the same type of packaged chip is obtained, test abnormal record data are extracted, and a fault type identification model is generated according to the test abnormal record data.
According to an embodiment of the present invention, the inputting the test result data into the fault category identification model for processing, obtaining a fault category, and matching a corresponding fault repair policy includes:
inputting the electrical performance test data, the thermal performance test data and the mechanical performance test data into the fault type identification model for processing to obtain fault type data;
And inputting the fault type data into a preset fault restoration strategy library for matching identification, and obtaining a fault restoration strategy.
It should be noted that, the electrical performance test data, the thermal performance test data and the mechanical performance test data are input into the fault category identification model for processing, so as to obtain the fault category, and the fault category is matched with the corresponding fault repair strategy.
A third aspect of the present invention provides a readable storage medium having embodied therein a big data based package test method program which, when executed by a processor, implements the steps of the big data based package test method as described in any one of the above.
The invention discloses a packaging test method, a system and a medium based on big data, which are characterized in that an electrical performance test index, a thermal performance test index and a mechanical performance test index are obtained according to the processing of the test result of a packaging chip, a reliability test index is obtained through calculation, the packaging chip is subjected to qualification judgment according to the reliability test index, if the packaging chip is judged to be unqualified, a fault class identification model is generated according to the processing of historical test abnormal record data of the same type of packaging chip, the test result data is input into the fault class identification model for processing, the fault class is obtained, and a corresponding fault repair strategy is matched.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or optical disk, or the like, which can store program codes.
Or the above-described integrated units of the invention may be stored in a readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solution of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
Claims (6)
1. The package testing method based on big data is characterized by comprising the following steps:
Packaging the chip to obtain a packaged chip;
testing the packaged chip by using a preset chip packaging test platform to obtain test result data, including electrical performance test data, thermal performance test data and mechanical performance test data;
Processing according to the electrical performance test data to obtain an electrical performance test index, processing according to the thermal performance test data to obtain a thermal performance test index, and processing according to the mechanical performance test data to obtain a mechanical performance test index;
Calculating according to the electrical performance test index, the thermal performance test index and the mechanical performance test index to obtain a reliability test index, and judging the qualification of the packaged chip according to the reliability test index;
If the packaging chip is judged to be unqualified, historical test record data of the same type of packaging chip are obtained, test abnormal record data are extracted, and a fault class identification model is generated according to the test abnormal record data;
Inputting the test result data into the fault category identification model for processing to obtain a fault category, and matching a corresponding fault repair strategy;
The step of packaging the chip to obtain a packaged chip comprises the following steps:
Acquiring chip type data and user packaging demand data;
Inputting the chip type data and the user packaging requirement data into a preset chip packaging mode database for matching and identifying to obtain an adaptive packaging mode;
Packaging the chip according to the adaptive packaging mode to obtain a packaged chip;
the method for testing the packaged chip by using the preset chip packaging test platform to obtain test result data, including electrical performance test data, thermal performance test data and mechanical performance test data, comprises the following steps:
The electrical performance test data comprises power supply voltage test data, time sequence performance test data and transient performance test data;
the thermal performance test data comprises thermal cycle test data, high-temperature aging test data, overheat protection test data and heat dissipation test data;
the mechanical performance test data comprises vibration test data, impact test data and mechanical pressure test data;
The processing according to the electrical performance test data to obtain an electrical performance test index, the processing according to the thermal performance test data to obtain a thermal performance test index, and the processing according to the mechanical performance test data to obtain a mechanical performance test index includes:
Processing according to the power supply voltage test data, the time sequence performance test data and the transient performance test data to obtain an electrical performance test index;
Processing according to the thermal cycle test data, the high-temperature aging test data, the overheat protection test data and the heat dissipation test data to obtain a thermal performance test index;
Processing according to the vibration test data, the impact test data and the mechanical pressure test data to obtain a mechanical performance test index;
The calculation formula of the electrical performance test index is as follows:
；
wherein, Is an electrical performance test index,/>For the supply voltage test data,/>For time series performance test data,/>For transient performance test data,/>、/>、/>Is a preset characteristic coefficient;
The calculation formula of the thermal performance test index is as follows:
；
wherein, For thermal performance test index,/>For thermal cycling test data,/>For high temperature aging test data,/>For overheat protection test data,/>For heat dissipation test data,/>、/>、/>、/>Is a preset characteristic coefficient;
the calculation formula of the mechanical performance test index is as follows:
；
wherein, For the mechanical test index,/>For vibration test data,/>For impact test data,/>For mechanical stress test data,/>、/>Is a preset characteristic coefficient;
The calculation formula of the reliability test index is as follows:
；
wherein, Is a reliability test index,/>Is an electrical performance test index,/>For thermal performance test index,/>For the mechanical test index,/>、/>、/>Is a preset characteristic coefficient.
2. The big data based package testing method of claim 1, wherein the calculating according to the electrical performance test index, the thermal performance test index, and the mechanical performance test index to obtain a reliability test index, and the performing the qualification judgment on the packaged chip according to the reliability test index comprises:
Calculating according to the electrical performance test index, the thermal performance test index and the mechanical performance test index to obtain a reliability test index;
comparing the reliability test index with a preset reliability test index threshold value to obtain a threshold value comparison result;
And if the threshold comparison result meets the preset threshold comparison requirement, judging the qualification of the packaged chip, otherwise, judging the disqualification.
3. The big data based package testing method according to claim 2, wherein if the packaged chip is determined to be unqualified, the method obtains historical test record data of the same type of packaged chip and extracts test anomaly record data, and generates a fault category recognition model according to the test anomaly record data processing, and comprises the steps of:
If the packaged chip is judged to be unqualified, historical test record data of the same type of packaged chip is obtained;
Extracting test anomaly record data according to the historical test record data, wherein the test anomaly record data comprises electric anomaly record data, thermal anomaly record data and mechanical anomaly record data;
And training the electrical anomaly record data, the thermal anomaly record data and the mechanical anomaly record data by using a preset model training algorithm to generate a fault type identification model.
4. The big data based package testing method according to claim 3, wherein inputting the test result data into the fault class identification model for processing, obtaining a fault class, and matching a corresponding fault repair policy, comprises:
inputting the electrical performance test data, the thermal performance test data and the mechanical performance test data into the fault type identification model for processing to obtain fault type data;
And inputting the fault type data into a preset fault restoration strategy library for matching identification, and obtaining a fault restoration strategy.
5. A big data based package testing system, comprising a memory and a processor, wherein the memory comprises a program of a big data based package testing method, and the program of the big data based package testing method is executed by the processor to realize the following steps:
Packaging the chip to obtain a packaged chip;
testing the packaged chip by using a preset chip packaging test platform to obtain test result data, including electrical performance test data, thermal performance test data and mechanical performance test data;
Processing according to the electrical performance test data to obtain an electrical performance test index, processing according to the thermal performance test data to obtain a thermal performance test index, and processing according to the mechanical performance test data to obtain a mechanical performance test index;
Calculating according to the electrical performance test index, the thermal performance test index and the mechanical performance test index to obtain a reliability test index, and judging the qualification of the packaged chip according to the reliability test index;
If the packaging chip is judged to be unqualified, historical test record data of the same type of packaging chip are obtained, test abnormal record data are extracted, and a fault class identification model is generated according to the test abnormal record data;
Inputting the test result data into the fault category identification model for processing to obtain a fault category, and matching a corresponding fault repair strategy;
The step of packaging the chip to obtain a packaged chip comprises the following steps:
Acquiring chip type data and user packaging demand data;
Inputting the chip type data and the user packaging requirement data into a preset chip packaging mode database for matching and identifying to obtain an adaptive packaging mode;
Packaging the chip according to the adaptive packaging mode to obtain a packaged chip;
the method for testing the packaged chip by using the preset chip packaging test platform to obtain test result data, including electrical performance test data, thermal performance test data and mechanical performance test data, comprises the following steps:
The electrical performance test data comprises power supply voltage test data, time sequence performance test data and transient performance test data;
the thermal performance test data comprises thermal cycle test data, high-temperature aging test data, overheat protection test data and heat dissipation test data;
the mechanical performance test data comprises vibration test data, impact test data and mechanical pressure test data;
The processing according to the electrical performance test data to obtain an electrical performance test index, the processing according to the thermal performance test data to obtain a thermal performance test index, and the processing according to the mechanical performance test data to obtain a mechanical performance test index includes:
Processing according to the power supply voltage test data, the time sequence performance test data and the transient performance test data to obtain an electrical performance test index;
Processing according to the thermal cycle test data, the high-temperature aging test data, the overheat protection test data and the heat dissipation test data to obtain a thermal performance test index;
Processing according to the vibration test data, the impact test data and the mechanical pressure test data to obtain a mechanical performance test index;
The calculation formula of the electrical performance test index is as follows:
；
wherein, Is an electrical performance test index,/>For the supply voltage test data,/>For time series performance test data,/>For transient performance test data,/>、/>、/>Is a preset characteristic coefficient;
The calculation formula of the thermal performance test index is as follows:
；
wherein, For thermal performance test index,/>For thermal cycling test data,/>For high temperature aging test data,/>For overheat protection test data,/>For heat dissipation test data,/>、/>、/>、/>Is a preset characteristic coefficient;
the calculation formula of the mechanical performance test index is as follows:
；
wherein, For the mechanical test index,/>For vibration test data,/>For impact test data,/>For mechanical stress test data,/>、/>Is a preset characteristic coefficient;
The calculation formula of the reliability test index is as follows:
；
wherein, Is a reliability test index,/>Is an electrical performance test index,/>For thermal performance test index,/>For the mechanical test index,/>、/>、/>Is a preset characteristic coefficient.
6. A computer readable storage medium, characterized in that the computer readable storage medium comprises therein a big data based package test program, which when executed by a processor, implements the steps of the big data based package test method according to any of claims 1 to 4.
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