Semiconductor device testing method and device

Abstract

The invention provides a semiconductor device testing method and device. The method comprises the steps that test data are acquired, the test data comprise data of a plurality of test devices, and the data of each test device comprises position information and various test parameters, the position information comprises a mechanical arm used for transferring the test device, a station used when the mechanical arm transfers the test device, and the position of the mechanical arm in a bearing disc during testing; based on the position information, analyzing the test data, and determining the yield; according to the yield, whether a mechanical arm fault, a station fault, a bearing disc fault or a communication fault exists or not is judged; and if the mechanical arm fault, the station fault, the bearing disc fault or the communication fault exists, outputting an instruction for stopping the test of the semiconductor device.

Description

Technical Field

[0001] This disclosure relates to the field of semiconductor technology, and in particular to a semiconductor device testing method and apparatus. Background Technology

[0002] Gallium nitride (GaN) based transistors and other gallium nitride semiconductor devices are third-generation semiconductors.

[0003] Testing gallium nitride semiconductor devices mainly involves transferring the semiconductor device to a carrier plate using a robotic arm, followed by testing. If the semiconductor device is not installed correctly, the test results may be inaccurate.

[0004] Currently, this situation usually requires manual judgment, which can easily lead to a waste of testing capacity. Summary of the Invention

[0005] This disclosure provides a semiconductor device testing method and apparatus. The technical solution is as follows: In a first aspect, embodiments of this disclosure provide a semiconductor device testing method, the method comprising: Acquire test data, which includes data from multiple test devices. The data for each test device includes position information and various test parameters. The position information includes the robotic arm used to transfer the test device, the workstation used by the robotic arm to transfer the test device, and the position in the carrier plate during the test. Based on the location information, the test data is analyzed to determine the yield rate; Based on the yield rate, determine whether there is a robot arm fault, workstation fault, carrier plate fault, or communication fault. If the robotic arm malfunctions, the workstation malfunctions, the carrier plate malfunctions, or the communication malfunctions, an instruction to stop semiconductor device testing will be output.

[0006] Optionally, based on the location information, the test data is analyzed to determine the yield, including: Select the test parameters of the test device with the same robotic arm from the test data, and determine the first yield of each robotic arm; Select the test parameters of the test devices with the same workstation from the test data, and determine the second yield of each workstation; The third yield of each carrier disk is determined by selecting the test parameters of the test device with the same carrier disk from the test data.

[0007] Optionally, based on the yield rate, it is determined whether there is a robot arm fault, workstation fault, carrier plate fault, or communication fault, including: When the first yield of the first robotic arm is less than the first threshold, it is determined that the first robotic arm has a robotic arm fault, and the first robotic arm can be any robotic arm. When the second yield rate of the first station is less than the second threshold, it is determined that there is a station fault in the first station, where the first station is any station; When the third yield of the first carrier is less than the third threshold, it is determined that the first carrier has a carrier fault, and the first carrier can be any carrier. A communication failure is determined when the first yield, the second yield, or the third yield is empty.

[0008] Optionally, the method further includes: The graphical interface outputs the yield rate in different dimensions, including the robotic arm dimension, workstation dimension, and carrier plate dimension.

[0009] Optionally, the method further includes: The test data is acquired periodically and analyzed to determine the yield rate for each period. The yield rate under different dimensions is dynamically output in the graphical interface.

[0010] Optionally, the method further includes: Receive test parameter options input by the user through the graphical interface; The acquisition of test data includes: The test parameters corresponding to the test parameter options are obtained through the interface.

[0011] Optionally, obtaining test data further includes: The position of the test device in the carrier disk during testing is obtained through the interface; Based on the position of the test device in the carrier plate during testing, the robotic arm used to transfer the test device and the workstation used by the robotic arm to transfer the test device are determined, and the position information is obtained.

[0012] Optionally, the method further includes: The mean values ​​of all the test parameters are displayed in a graphical interface; The presence or absence of a fault in the test unit is determined based on the average value of each of the aforementioned test parameters.

[0013] Secondly, embodiments of this disclosure provide a semiconductor device testing apparatus, the apparatus comprising: The acquisition module is used to acquire test data, which includes data from multiple test devices. The data of each test device includes position information and various test parameters. The position information includes the robotic arm used to transfer the test device, the workstation used by the robotic arm to transfer the test device, and the position in the carrier plate during the test. The determination module is used to analyze the test data based on the location information to determine the yield. The judgment module is used to determine whether there is a robot arm fault, workstation fault, carrier plate fault or communication fault based on the yield rate. The output module is used to output an instruction to stop semiconductor device testing if there is a fault in the robotic arm, the workstation, the carrier plate, or the communication.

[0014] Thirdly, embodiments of this disclosure provide a computer device, the computer device comprising: a processor; a memory configured to store processor-executable instructions; wherein the processor is configured to perform the semiconductor device testing method according to any one of the second aspects.

[0015] Fourthly, embodiments of this disclosure provide a computer-readable storage medium that, when instructions in the computer-readable storage medium are executed by a processor of a computer device, enables the computer device to perform the semiconductor device testing method according to any one of the second aspects.

[0016] The beneficial effects of the technical solutions provided in this disclosure are: In this embodiment of the disclosure, after acquiring test data, the yield of the tested devices is analyzed based on different locations. Then, by determining whether the yield at different locations is abnormal, it can be judged whether there is a robotic arm fault, workstation fault, carrier plate fault, or communication fault. For example, if the yield of a tested device transferred by a robotic arm is significantly abnormal, it indicates a robotic arm fault. If the analysis reveals the presence of such anomalies, an instruction to stop semiconductor device testing is output to avoid continuing invalid testing and wasting production capacity, thereby improving test capacity utilization and ensuring test accuracy. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a semiconductor device testing method provided in an embodiment of this disclosure; Figure 2 This is a flowchart of another semiconductor device testing method provided in this disclosure embodiment; Figure 3 This is a schematic diagram of a graphical interface provided in an embodiment of this disclosure; Figure 4 This is a schematic diagram of the structure of a semiconductor device testing apparatus provided in an embodiment of this disclosure; Figure 5 This is a structural block diagram of a computer device provided in an embodiment of this disclosure. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this disclosure clearer, the embodiments of this disclosure will be described in further detail below with reference to the accompanying drawings.

[0020] Figure 1 This is a flowchart of a semiconductor device testing method provided in an embodiment of this disclosure. See also... Figure 1 The method includes the following steps: 101: Acquire test data, which includes data from multiple test devices. The data for each test device includes position information and various test parameters. The position information includes the robotic arm used to transfer the test device, the workstation used by the robotic arm to transfer the test device, and the position in the carrier plate during testing.

[0021] For example, the robotic arm used to transfer the test device in the location information can refer to the number of the robotic arm of the sorting machine, such as two robotic arms, numbered 01 and 02 respectively.

[0022] The workstation (Site) used by the robotic arm to transfer the test device, as described in the location information, is an independent working unit in which the robotic arm (or cart) performs the gripping and placement of the test device, and is also a core indicator of the equipment's parallel processing capability. Each robotic arm (or cart) can have 4, 8, or more parallel Sites. These Sites can be numbered 1, 2, 3, 4, etc.

[0023] Multiple trays can exist simultaneously during the test. The position of the device in the tray during the test in the location information refers to the tray number corresponding to the test device. For example, the four trays are numbered 1, 2, 3, 4, etc.

[0024] Optionally, the location information may also include the coordinates of the test device within the carrier plate during testing, thus providing support for a more detailed display.

[0025] In the embodiments disclosed herein, the test device is a semiconductor device (e.g., a packaged chip or power semiconductor device), such as a GaN device.

[0026] The test parameters of the test device may include all or some of the following parameters: Kelvin_G (Kelvin Gate): Gate voltage sampling; Kelvin_D (Kelvin Drain): Drain voltage sampling; Kelvin_S (Kelvin Source): Source voltage sampling; IGSS1 (Gate-to-Source Leakage Current 1 (forward bias)): The leakage current flowing through the gate insulating oxide layer when the drain and source are shorted (VDS=0V) and a positive rated gate voltage is applied between the gate and source. IGSS1N (Gate-to-Source Leakage Current 1 Negative): The leakage current flowing through the gate oxide layer when the drain and source are shorted (VDS=0V) and a reverse rated gate voltage is applied between the gate and source. VTH1 (Threshold Voltage 1): The minimum gate-source voltage VGS required when the channel begins to form and the source-drain junction reaches the specified on-state current; VTH2 (Threshold Voltage 2): Threshold voltage measured under different operating conditions; RON1 (ON-state Resistance 1): The DC resistance between the drain and source when fully on. RON2 (ON-state Resistance 2): On-resistance measured under different operating conditions; idoff1_1V (Off-state Drain Current 1 @ VDS=1V, Off-state Drain Current 1 @ Drain-Source Voltage 1V): When fully turned off (VGS=0V, zero gate voltage standard turn-off condition), the leakage current flowing through the drain when a voltage of 1V is applied to the drain and source. igoff1_1V (Off-state Gate Current 1 @ VDS=1V, Off-state Gate Current 1 @ Drain-Source Voltage 1V): When fully turned off (VGS=0V), the leakage current flowing through the gate when a voltage of 1V is applied to the drain and source. idoff1_101V (Off-state Drain Current 1 @ VDS=101V, Off-state Drain Current 1 @ Drain-Source Voltage 101V): Drain leakage current when a voltage of 101V is applied to the drain and source in the off-state state; igoff1_101V (Off-state Gate Current 1 @ VDS=101V, Off-state Gate Current 1 @ Drain-Source Voltage 101V): Gate leakage current when a voltage of 101V is applied to the drain and source in the off-state state; idoff1_301V (Off-state Drain Current 1 @ VDS=301V, Off-state Drain Current 1 @ Drain-Source Voltage 301V): Drain leakage current when a voltage of 301V is applied to the drain and source in the off-state state; igoff1_301V (Off-state Gate Current 1 @ VDS=301V, Off-state Gate Current 1 @ Drain-Source Voltage 301V): Gate leakage current when a voltage of 301V is applied to the drain and source in the off-state state; idoff1_501V (Off-state Drain Current 1 @ VDS=501V, Off-state Drain Current 1 @ Drain-Source Voltage 501V): Drain leakage current when a voltage of 501V is applied to the drain and source in the off-state state; igoff1_501V (Off-state Gate Current 1 @ VDS=501V, Off-state Gate Current 1 @ Drain-Source Voltage 501V): Gate leakage current when a voltage of 501V is applied to the drain and source in the off-state state; idoff1_701V (Off-state Drain Current 1 @ VDS=701V, Off-state Drain Current 1 @ Drain-Source Voltage 701V): Drain leakage current when a voltage of 701V is applied to the drain and source in the off-state state; igoff1_701V (Off-state Gate Current 1 @ VDS=701V, Off-state Gate Current 1 @ Drain-Source Voltage 701V): Gate leakage current when a voltage of 701V is applied to the drain and source in the off-state state; idoff1_901V (Off-state Drain Current 1 @ VDS=901V, Off-state Drain Current 1 @ Drain-Source Voltage 901V): Drain leakage current when a voltage of 901V is applied to the drain and source in the off-state state; igoff1_901V (Off-state Gate Current 1 @ VDS=901V, Off-state Gate Current 1 @ Drain-Source Voltage 901V): Gate leakage current when a voltage of 901V is applied to the drain and source in the off-state state.

[0027] This method can be executed by a computer device that is electrically connected to a test unit (test equipment) or a storage device (storing test data) for testing semiconductor devices, thereby obtaining test data through an interface.

[0028] The embodiments disclosed herein are mainly for the analysis of data after the test unit has completed the test, and do not limit the type or structure of the test unit.

[0029] 102: Based on the location information, analyze the test data to determine the yield.

[0030] In this embodiment of the disclosure, yield refers to the proportion of multiple test devices that pass the test.

[0031] For each test device, if all test parameters are normal (within the set range), it is considered a pass; if any test parameter is abnormal (outside the set range), it is considered a fail.

[0032] In this step, analysis based on location information means grouping test devices with the same location information into a category and analyzing the yield of that category, thereby providing a basis for subsequently determining the cause of test failures.

[0033] For example, test devices for the same robotic arm can be grouped together, and the yield rate of the test devices corresponding to that robotic arm can be analyzed. If the yield rate is normal (usually exceeding a threshold), it indicates that the robotic arm is problem-free. If the yield rate is abnormal (usually below a threshold), it indicates that the robotic arm has a problem. In this case, a fault report can be issued to facilitate timely stopping of the test and fault repair.

[0034] 103: Based on the yield rate, determine whether there is a robot arm fault, workstation fault, carrier plate fault, or communication fault.

[0035] As mentioned earlier, yield analysis by classification can not only determine whether there is a robot arm malfunction, but also can be used to determine workstation malfunction, carrier plate malfunction, or communication malfunction.

[0036] The robot arm malfunction, workstation malfunction, and carrier plate malfunction mentioned here are usually caused by problems with the robot arm, workstation, or carrier plate, which lead to problems in the connection between the test device and the test unit. For example, the robot arm's running trajectory is inaccurate, the workstation is not aligned, or the carrier plate is not positioned accurately, resulting in poor contact between the test device and the test unit, which in turn causes inaccurate testing.

[0037] Communication failures can be physical link failures or software interface failures, which can prevent data from being read correctly from the test unit or storage device.

[0038] 104: If there is a fault in the robotic arm, the workstation, the carrier plate, or the communication, output an instruction to stop the semiconductor device test.

[0039] In one example, the instruction is displayed in a graphical interface, allowing staff to stop testing and perform appropriate repairs in a timely manner.

[0040] In another example, this instruction can be output to the test unit to automate the semiconductor device testing function.

[0041] In this embodiment of the disclosure, after acquiring test data, the yield of the tested devices is analyzed based on different locations. Then, by determining whether the yield at different locations is abnormal, it can be judged whether there is a robotic arm fault, workstation fault, carrier plate fault, or communication fault. For example, if the yield of a tested device transferred by a robotic arm is significantly abnormal, it indicates a robotic arm fault. If the analysis reveals the presence of such anomalies, an instruction to stop semiconductor device testing is output to avoid continuing invalid testing and wasting production capacity, thereby improving test capacity utilization and ensuring test accuracy.

[0042] Figure 2 This is a flowchart of another semiconductor device testing method provided in this disclosure. See also... Figure 2 The method includes the following steps: 201: Receive test parameter options input by the user through the graphical interface.

[0043] Figure 3 This is a schematic diagram of a graphical interface provided in an embodiment of this disclosure. For example... Figure 3 As shown, the graphical interface displays a selection of test parameters, which users can choose by clicking. For example... Figure 3 The options marked with an "X" in the selection box are the selected options.

[0044] This method involves user selection, followed by obtaining test data from the test unit (test device) or storage device (storing test data) via an interface.

[0045] In other implementations, test data can also be obtained by importing files.

[0046] 202: Obtain the test parameters corresponding to the test parameter options and the position of the test device in the carrier disk during testing through the interface.

[0047] For example, the test parameters corresponding to the test parameter options and their positions in the carrier disk are obtained through the General-Purpose Interface Bus (GPIB) / Internet Protocol (IP) serial port.

[0048] The location within the carrier plate includes the carrier plate number and its coordinates within the carrier plate.

[0049] 203: Based on the position of the test device in the carrier plate during testing, determine the robotic arm used to transfer the test device and the workstation used by the robotic arm to transfer the test device, and obtain the position information.

[0050] like Figure 3 As shown, the carrier disk includes slots arranged in an array. When transferring test devices, the correspondence between each slot, the robotic arm, and the workstation of the robotic arm is determined. Therefore, the robotic arm used to transfer the test device and the workstation used by the robotic arm to transfer the test device can be determined based on the position of the test device in the carrier disk during testing.

[0051] 204: Based on the location information, analyze the test data to determine the yield.

[0052] In this embodiment of the disclosure, step 204 may include: Select the test parameters of the test device with the same robotic arm from the test data, and determine the first yield of each robotic arm; Select the test parameters of the test devices with the same workstation from the test data, and determine the second yield of each workstation; The third yield of each carrier disk is determined by selecting the test parameters of the test device with the same carrier disk from the test data.

[0053] In this implementation, test devices with the same location information are grouped together, and the yield of this group is analyzed, thus providing a basis for determining the cause of test failures.

[0054] Among them, the test parameters of the test devices with the same robotic arm / workstation / carrying plate can be selected from the test data by searching using a specific robotic arm / workstation / carrying plate as a keyword.

[0055] In this embodiment of the disclosure, yield refers to the proportion of multiple test devices that pass the test.

[0056] For each test device, if all test parameters are normal (within the set range), it is considered a pass; if any test parameter is abnormal (outside the set range), it is considered a fail.

[0057] In this step, data can be processed and analyzed using data analysis libraries such as matplotlib, qt, and seaborns.

[0058] 205: In the graphical interface, output the yield rate under different dimensions, including the robot arm dimension, workstation dimension, and carrier plate dimension.

[0059] By outputting yield rates in different dimensions, staff can easily understand the testing situation.

[0060] like Figure 3 As shown, the yield rate is displayed for each robotic arm, and the yield rate is displayed separately for each workstation of each robotic arm.

[0061] The test tray can display the test status of each slot's corresponding test device, distinguished by color. For example, "none" (white) indicates that there is no test device in that slot, and "pass" (green) indicates that the test has passed. For those that have failed, different colors are used to indicate different parameters that failed. Figure 3 Colors are not shown.

[0062] exist Figure 3 In this round, the parameters of bearing plates 1 and 2 were tested, while the parameters of bearing plates 3 and 4 were not tested.

[0063] Optionally, the method also includes displaying the overall yield in a graphical interface.

[0064] like Figure 3 As shown, the overall yield rate for this round of testing was 91%.

[0065] Optionally, the method further includes displaying the mean values ​​of various test parameters in a graphical interface.

[0066] like Figure 3 As shown, the parameter mean represents the parameters selected by the user in step 201, and is displayed using a normalized method.

[0067] Optionally, the method further includes determining whether the test unit itself is faulty based on the average value of each test parameter. For example, if the average value of a certain test parameter is too low, it indicates that the maximum value deviates significantly from the average value, and in this case, it can be determined that the test unit itself is faulty. A prompt can also be output in this situation.

[0068] Optionally, the method further includes: The test data is acquired periodically and analyzed to determine the yield rate for each period. The yield rate under different dimensions is dynamically output in the graphical interface.

[0069] In this implementation, the real-time nature and validity of the data are ensured through periodic dynamic processing.

[0070] The aforementioned period can be the duration of one round of testing.

[0071] Furthermore, steps 204 and subsequent steps 206 and 207 can also be executed periodically.

[0072] 206: Based on the yield rate, determine whether there is a robot arm fault, workstation fault, carrier plate fault, or communication fault.

[0073] In this embodiment of the disclosure, step 206 may include: When the first yield of the first robotic arm is less than the first threshold, it is determined that the first robotic arm has a robotic arm fault, and the first robotic arm can be any robotic arm. When the second yield rate of the first station is less than the second threshold, it is determined that there is a station fault in the first station, where the first station is any station; When the third yield of the first carrier is less than the third threshold, it is determined that the first carrier has a carrier fault, and the first carrier can be any carrier. A communication failure is determined when the first yield, the second yield, or the third yield is empty.

[0074] In this implementation, the yield analysis by classification can not only determine whether there is a robot arm fault, but also determine the fault of the workstation, the carrier plate, or the communication fault, so that the test can be stopped in time when a fault occurs.

[0075] The thresholds corresponding to the first yield, second yield, and third yield mentioned above can be the same or different.

[0076] The thresholds corresponding to the first, second, and third yield rates mentioned above can be the same and set according to the usual yield rate. For example, if the overall yield rate is usually 90%, then the threshold can be set to a value that is obviously deviating from the usual yield rate, such as 70%.

[0077] 207: If there is a fault in the robotic arm, the workstation, the carrier plate, or the communication, output an instruction to stop the semiconductor device test.

[0078] Optionally, the method further includes: if there is no fault in the robotic arm, the workstation, the carrier plate, or the communication, then the instruction to stop the semiconductor device test is not output, and the semiconductor device test continues.

[0079] Optionally, the method further includes generating a report document, which includes yield rates for various dimensions, overall yield rates, and average values ​​of various parameters.

[0080] Optionally, the method also includes uploading the content of the report document to the cloud or a server.

[0081] The method provided in this disclosure can improve the testing efficiency of GaN devices and accelerate the research and development process; it can save costs, identify faults in a timely manner, and prevent problems from persisting; it has good compatibility and allows for easy changes to test engineering parameters and quantities.

[0082] Figure 4 This is a schematic diagram of the structure of a semiconductor device testing apparatus provided in an embodiment of this disclosure. See also... Figure 4 The device includes: an acquisition module 301, a determination module 302, a judgment module 303, and an output module 304.

[0083] The acquisition module 301 is used to acquire test data, which includes data from multiple test devices. The data of each test device includes position information and various test parameters. The position information includes the robotic arm used to transfer the test device, the workstation used by the robotic arm to transfer the test device, and the position in the carrier plate during the test. The determination module 302 is used to analyze the test data based on the location information to determine the yield. The judgment module 303 is used to determine whether there is a robot arm fault, workstation fault, carrier plate fault or communication fault based on the yield rate. The output module 304 is used to output an instruction to stop the semiconductor device test if there is a fault in the robotic arm, the workstation, the carrier plate, or the communication.

[0084] Optionally, the determining module 302 is used to select the test parameters of the test devices having the same robotic arm from the test data, and determine the first yield of each robotic arm; Select the test parameters of the test devices with the same workstation from the test data, and determine the second yield of each workstation; The third yield of each carrier disk is determined by selecting the test parameters of the test device with the same carrier disk from the test data.

[0085] Optionally, the judgment module 303 is used to determine that the first robotic arm has a robotic arm fault when the first yield of the first robotic arm is less than a first threshold, wherein the first robotic arm is any robotic arm; When the second yield rate of the first station is less than the second threshold, it is determined that there is a station fault in the first station, where the first station is any station; When the third yield of the first carrier is less than the third threshold, it is determined that the first carrier has a carrier fault, and the first carrier can be any carrier. A communication failure is determined when the first yield, the second yield, or the third yield is empty.

[0086] Optionally, the output module 304 is also used to output the yield rate in different dimensions in the graphical interface, including the robot arm dimension, the workstation dimension, and the carrier plate dimension.

[0087] Optionally, the acquisition module 301 is further configured to periodically acquire the test data and analyze the test data to determine all the yield rates within this period; The output module 304 is also used to dynamically output the yield in different dimensions in the graphical interface.

[0088] Optionally, the acquisition module 301 is used to receive test parameter options input by the user through a graphical interface; The test parameters corresponding to the test parameter options are obtained through the interface.

[0089] Optionally, the acquisition module 301 is also used to acquire the position of the test device in the carrier disk during testing via an interface; Based on the position of the test device in the carrier plate during testing, the robotic arm used to transfer the test device and the workstation used by the robotic arm to transfer the test device are determined, and the position information is obtained.

[0090] Optionally, the output module 304 is also used to display the mean values ​​of the various test parameters in a graphical interface; The judgment module 303 is also used to determine whether the test unit has a fault based on the average value of the various test parameters.

[0091] It should be noted that the semiconductor device testing apparatus provided in the above embodiments is only illustrated by the division of the above functional modules when defining the report. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the semiconductor device testing apparatus and the semiconductor device testing method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0092] Figure 5 This is a structural block diagram of a computer device provided in an embodiment of this disclosure. The computer device can be the aforementioned host computer. The computer device 400 includes a central processing unit (CPU) 401, a system memory 404 including random access memory (RAM) 402 and read-only memory (ROM) 403, and a system bus 405 connecting the system memory 404 and the CPU 401. The computer device 400 also includes a basic input / output system (I / O system) 406 that facilitates information transfer between various devices within the computer, and a mass storage device 407 for storing the operating system 413, application programs 414, and other program modules 415.

[0093] The basic input / output system 406 includes a display 408 for displaying information and an input device 409 for user input, such as a mouse or keyboard. Both the display 408 and the input device 409 are connected to the central processing unit 401 via an input / output controller 410 connected to the system bus 405. The basic input / output system 406 may also include the input / output controller 410 for receiving and processing input from multiple other devices such as a keyboard, mouse, or electronic stylus. Similarly, the input / output controller 410 also provides output to a display screen, printer, or other types of output devices.

[0094] Mass storage device 407 is connected to central processing unit 401 via a mass storage controller (not shown) connected to system bus 405. Mass storage device 407 and its associated computer-readable media provide non-volatile storage for computer device 400. That is, mass storage device 407 may include computer-readable media (not shown) such as hard disk or CD-ROM drive.

[0095] Without loss of generality, computer-readable media can include computer storage media and communication media. Computer storage media include volatile and non-volatile, removable and non-removable media implemented using any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media include RAM, ROM, EPROM, EEPROM, flash memory or other solid-state storage technologies, CD-ROM, DVD or other optical storage, magnetic tape cassettes, magnetic tape, disk storage, or other magnetic storage devices. Of course, those skilled in the art will recognize that computer storage media are not limited to the above-mentioned types. The system memory 404 and mass storage device 407 described above can be collectively referred to as memory.

[0096] According to various embodiments of this disclosure, computer device 400 can also be connected to a remote computer on a network, such as the Internet. That is, computer device 400 can be connected to network 412 via network interface unit 411 connected to system bus 405, or network interface unit 411 can be used to connect to other types of networks or remote computer systems (not shown).

[0097] The memory also includes one or more programs, which are stored in the memory. The central processing unit 401 implements these programs by executing them. Figure 1 or Figure 2 The semiconductor device testing method is shown.

[0098] In exemplary embodiments, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory including instructions that can be executed by a processor of a computer device to perform the semiconductor device testing methods shown in various embodiments of this disclosure. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0099] The above description is merely an optional embodiment of this disclosure and is not intended to limit this disclosure. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the protection scope of this disclosure.

Claims

1. A method for testing semiconductor devices, characterized in that, The method includes: Acquire test data, which includes data from multiple test devices. The data for each test device includes position information and various test parameters. The position information includes the robotic arm used to transfer the test device, the workstation used by the robotic arm to transfer the test device, and the position in the carrier plate during the test. Based on the location information, the test data is analyzed to determine the yield rate; Based on the yield rate, determine whether there is a robot arm fault, workstation fault, carrier plate fault, or communication fault. If the robotic arm malfunctions, the workstation malfunctions, the carrier plate malfunctions, or the communication malfunctions, an instruction to stop semiconductor device testing will be output.

2. The method according to claim 1, characterized in that, Based on the location information, the test data is analyzed to determine the yield, including: Select the test parameters of the test device with the same robotic arm from the test data, and determine the first yield of each robotic arm; Select the test parameters of the test devices with the same workstation from the test data, and determine the second yield of each workstation; The third yield of each carrier disk is determined by selecting the test parameters of the test device with the same carrier disk from the test data.

3. The method according to claim 2, characterized in that, Based on the yield rate, determine whether there are any faults such as robotic arm failure, workstation failure, carrier plate failure, or communication failure, including: When the first yield of the first robotic arm is less than the first threshold, it is determined that the first robotic arm has a robotic arm fault, and the first robotic arm can be any robotic arm. When the second yield rate of the first station is less than the second threshold, it is determined that there is a station fault in the first station, where the first station is any station; When the third yield of the first carrier is less than the third threshold, it is determined that the first carrier has a carrier fault, and the first carrier can be any carrier. A communication failure is determined when the first yield, the second yield, or the third yield is empty.

4. The method according to any one of claims 1 to 3, characterized in that, The method further includes: The graphical interface outputs the yield rate in different dimensions, including the robotic arm dimension, workstation dimension, and carrier plate dimension.

5. The method according to claim 4, characterized in that, The method further includes: The test data is acquired periodically and analyzed to determine the yield rate for each period. The yield rate under different dimensions is dynamically output in the graphical interface.

6. The method according to any one of claims 1 to 3, characterized in that, The method further includes: Receive test parameter options input by the user through the graphical interface; The acquisition of test data includes: The test parameters corresponding to the test parameter options are obtained through the interface; The position of the test device in the carrier disk during testing is obtained through the interface; Based on the position of the test device in the carrier plate during testing, the robotic arm used to transfer the test device and the workstation used by the robotic arm to transfer the test device are determined, and the position information is obtained.

7. The method according to any one of claims 1 to 3, characterized in that, The method further includes: The mean values ​​of all the test parameters are displayed in a graphical interface; The presence or absence of a fault in the test unit is determined based on the average value of each of the aforementioned test parameters.

8. A semiconductor device testing apparatus, characterized in that, The device includes: The acquisition module is used to acquire test data, which includes data from multiple test devices. The data of each test device includes position information and various test parameters. The position information includes the robotic arm used to transfer the test device, the workstation used by the robotic arm to transfer the test device, and the position in the carrier plate during the test. The determination module is used to analyze the test data based on the location information to determine the yield. The judgment module is used to determine whether there is a robot arm failure, workstation failure, carrier plate failure or communication failure based on the yield rate. The output module is used to output an instruction to stop semiconductor device testing if there is a fault in the robotic arm, the workstation, the carrier plate, or the communication.

9. A computer device, characterized in that, The computer device includes: a processor; a memory configured to store processor-executable instructions; wherein the processor is configured to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by the processor of a computer device, the computer device is able to perform the method according to any one of claims 1 to 7.

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