A method for quality inspection after sorting vertical structure LED chips

Abstract

The present invention provides a quality inspection method after sorting vertical structure LED grains. The method compares and analyzes the original standard data of the wafer with the quality inspection BIN grain data, and analyzes the following items: voltage, wavelength, and brightness. The comparison is performed according to the standard range of the voltage, brightness, and wavelength data in the standard data, and the finished products are put into storage in this way. The grains in the wafer are collected by using a conductive film, and the original data of the grains in the collected wafer are thrown out at the same time. The spot measuring machine back-measures the conductive film to collect the grains in the wafer and compares them with the original standard data to obtain yield control, prevent the cutting output of defective grains from flowing into the client in advance, effectively control the product NG abnormality rate, effectively control the quality of LED grain products, solve the problems of product batch abnormality and classification confusion, and ensure the quality and reliability of LED grain products.

Description

Technical Field

[0001] The present invention belongs to the technical field of LED grain quality inspection, and in particular relates to a method for quality inspection of vertical structure LED grains after sorting. Background Art

[0002] LED chips are optical devices composed of packaged semiconductor chips. They are the core components of LED lamps. They convert electrical energy into light energy through their PN junctions to obtain efficient and stable output light sources. They play a vital role in modern semiconductor lighting applications.

[0003] Due to the huge demand in the LED market, the large-scale production technology of LED chips has become mature. With the development of the LED semiconductor chip industry, the requirements for chip quality are becoming increasingly higher. After cutting and sorting the vertical structure LED chips, it is impossible to accurately obtain product electrical data and effectively control product quality. This causes product batch abnormalities and confusion in the classification of defective and good rates. Therefore, the quality and reliability of LED chip products cannot be guaranteed, which increases customer usage difficulties and complaints. Therefore, it is necessary to design a new quality inspection method to solve the above problems. Summary of the Invention

[0004] In response to the above-mentioned problems in the prior art, the present invention provides a quality inspection method after sorting of vertical structure LED grains, which can effectively control the quality of LED grain products, solve the problems of abnormal product batches and chaotic classification, and ensure the quality and reliability of LED grain products.

[0005] The present invention is implemented through the following technical solution: A method for quality inspection after sorting vertical structure LED chips, comprising the following steps:

[0006] S1: Using a spot measuring machine to perform full measurement on the wafer, obtain test data of each die in the wafer, and upload the test data and corresponding coordinates of each die to a computer system;

[0007] S2: cutting the wafer using a cutting machine to obtain a plurality of discrete grains;

[0008] S3: Use a sorting machine to sort according to the grain coordinates, voltage, wavelength, and brightness. The coordinates are sampled at 2 / 3 of the wafer diameter. There are three production batches: P, Q, and Y. Similar features are divided into similar batches. In this way, N wafers are sorted. The computer system selects a number of wafers from each batch according to the three batches of P, Q, and Y. The sorting machine sorts a number of grains at different positions of each selected wafer onto the conductive film. According to the test data and coordinates of the grains, the grains are classified so that the grains are neatly arranged with relative coordinates on the conductive film. The grains collected on the conductive film are sent to the quality inspection BIN of the spot measuring machine for grain testing;

[0009] S4: Coordinates of multiple grains located on the wafer are collected according to the conductive film, test data corresponding to the coordinates in step S1 are obtained, the test data are defined as standard data, and the standard data are uploaded to the computer system;

[0010] S5: Use the quality inspection BIN of the spot measuring machine to perform full die testing. Specifically, the die include all the dies with similar characteristics that are divided into 2 / 3 of the diameter of the wafers of the same batch. The test conditions are the same as those in step S1 to obtain the quality inspection BIN die data.

[0011] S6: Uploading the quality inspection BIN grain data to the computer system;

[0012] S7: Compare and analyze the standard data with the quality inspection BIN grain data to determine whether the quality inspection BIN grain data is within the standard range of the standard data; if so, classify the same batch types into three categories, P, Q, and Y, based on the similar characteristics in step S3. Untested grains whose quality inspection BIN grain data meets the standard range and belong to the same batch type as the test grains in step S5 are put into storage as finished products, and are classified into good and bad grades according to the grain data yield rate, morphological integrity, and surface appearance. Among them, good products are classified as grade A, and defective products are classified as grade B.

[0013] S8: The test grains whose BIN grain data of the quality inspection in step S5 meets the standard range are put into storage as downgraded finished products and listed as C grade;

[0014] S9: Based on the result of determining whether the quality inspection BIN die data in step S7 is within the standard range of the standard data, if not, the test die whose quality inspection BIN die data in step S5 does not meet the standard range and the untested die of the same batch type are returned to the die process analysis. The die process analysis is a process in which process personnel analyze, solve, and determine whether the batch should be downgraded or scrapped.

[0015] S10: Determine whether unqualified products have flowed into the sorting and sampling products based on the die process analysis described in step S9. If so, the sorting machine has an abnormality, and the corresponding batch of die and the involved sorting machine are cleared, the sorting machine is reset, and the sorting machine is re-sorted for new materials. If not, classify the die data yield rate and morphological integrity based on the die process analysis in step S9. Among them, the good products are classified as D-grade and put into storage, and the bad products are classified as E-grade and recycled.

[0016] Furthermore, the classification process in step S3 is to classify each grain in the wafer according to the voltage, wavelength, and brightness parameters measured by the spot measuring machine, and collect the grains in the larger category into the conductive film.

[0017] Furthermore, the different positions in step S3 include multiple positions at the top, bottom, left, right and center of the selected wafer, and the radius of the circular trajectory formed by the top, bottom, left, right and center positions of the wafer is 2 / 3 of the outer diameter of the wafer.

[0018] Furthermore, in step S3, the computer system selects 2 wafers per batch according to the batch, and the sorting machine sorts 3 wafers into conductive films at the top, bottom, left, right and middle positions of each selected wafer.

[0019] Furthermore, the standard range of the voltage data in the standard data in step S7 is ±0.04v to ±0.06v.

[0020] Furthermore, the standard range of the brightness data in the standard data in step S7 is 4% to 6%.

[0021] Furthermore, the standard range of the wavelength data in the standard data in step S7 is ±0.6 nm to ±0.8 nm.

[0022] Furthermore, the die process analysis in step S9 includes one or more of data yield rate, morphology integrity, surface flatness, and appearance smoothness quality.

[0023] The beneficial effects of the present invention are: the present invention utilizes a conductive film to collect grains, and at the same time throws out the collected grain data, and the point measuring machine back-measures the grain comparison data to obtain yield control, prevent the cutting output of defective grains from flowing into the client in advance, effectively control the product NG abnormality rate, effectively control the quality of LED grain products, solve the problems of product batch abnormalities and classification confusion, and ensure the quality and reliability of LED grain products. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a flow chart of the process steps of one embodiment of the present invention;

[0025] Figure 2 This is a data comparison chart of an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The present invention will be described in further detail below with reference to the accompanying drawings and embodiments.

[0027] It should be noted that when an element is referred to as being "located on" another element, it may be directly on the other element or there may also be an element centered thereon. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may also be an element centered thereon. The terms "vertical", "horizontal", "left", "right", "up", "down", "center" and similar expressions used herein are for illustrative purposes only and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore should not be understood as limiting the present invention.

[0028] In the present invention, unless otherwise expressly specified or limited, the terms "installed," "connected," "connected," "fixed," and the like should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances. The term "and / or" as used herein includes any and all combinations of one or more of the relevant listed items.

[0029] Example 1

[0030] This embodiment provides a method for quality inspection after sorting vertical structure LED dies, including the following steps:

[0031] S1: Use a spot measuring machine to perform full measurement on the wafer to obtain test data of each die in the wafer, and upload the test data and corresponding coordinates of each die to a computer system, so as to facilitate rapid search for test data corresponding to the die according to the coordinates during later collection and sorting operations;

[0032] S2: cutting the wafer using a cutting machine to obtain a plurality of discrete grains;

[0033] S3: Use a sorting machine to sort based on the grain coordinates, voltage, wavelength, and brightness. The coordinates are sampled at 2 / 3 of the wafer diameter. Production batches are divided into three categories: P, Q, and Y. Similar features are divided into similar batches. In this way, N wafers are sorted to obtain test objects with relatively typical feature types.

[0034] The computer system selects several wafers from each batch according to the three categories of P, Q, and Y. The sorting machine sorts several grains from different positions of each selected wafer onto the conductive film. The grains are classified according to the test data and coordinates of the grains, so that the grains are neatly arranged on the conductive film with relative coordinates. The grains collected on the conductive film are sent to the quality inspection bin of the spot tester for grain testing, thereby ensuring the uniformity of the test status each time.

[0035] S4: Coordinates of multiple grains located on the wafer are collected based on the conductive film, and test data corresponding to the coordinates in step S1 are obtained, which are defined as standard data and uploaded to a computer system to obtain a relatively typical reference standard.

[0036] S5: Use the quality inspection BIN of the spot measuring machine to perform full die testing. Specifically, the die include all the die with similar characteristics that are divided into 2 / 3 of the diameter of the wafer of the same batch. The test conditions are the same as those in step S1 to obtain the quality inspection BIN die data, which is used as the comparison data of the standard data. Since the better the die quality, the smaller the error value of the two measurements will be, the grade of the die can be determined based on the difference between the quality inspection BIN die data and the standard data.

[0037] S6: Uploading the quality inspection BIN grain data to a computer system so that the computer system can calculate and screen the difference between the quality inspection BIN grain data and the standard data in batches;

[0038] S7: Compare and analyze the standard data with the quality inspection BIN die data. Analyze the following items: voltage, wavelength, and brightness. Compare within the standard ranges of voltage ±0.05V, brightness 5%, and wavelength ±0.7nm in the standard data. Untested die whose quality inspection BIN die data meets the standard ranges and are of the same type as the test die are put into storage as finished products. Die data is classified into good and bad grades based on yield rate, morphological integrity, and surface appearance. Good quality products are classified as grade A and bad quality products as grade B. This ensures the orderly summary of the test data of each die. Die in grade A and grade B can be sold as good quality products and good quality products, respectively.

[0039] S8: The test dies whose BIN dies data of the quality inspection in step S5 meet the standard range are put into storage as downgraded finished products and listed as C-grade. The C-grade dies can be sold as ordinary products.

[0040] S9: Based on the result of determining whether the quality inspection BIN die data in step S7 is within the standard range of the standard data, if not, the test die whose quality inspection BIN die data in step S5 does not meet the standard range and the untested die of the same batch type are returned to the die process analysis. The die process analysis is a measure for process personnel to analyze, solve, and determine whether the batch should be downgraded or scrapped. The analysis and judgment can be made based on the die data yield rate, morphological integrity, surface flatness, or appearance finish quality.

[0041] S10: According to the grain process analysis described in step S9, determine whether unqualified products flow into the sorting and sampling products. If so, the sorting machine has an abnormality, and the corresponding batch of grains and the sorting machine involved are cleared, the sorting machine is reset, and the sorting machine re-sorts new materials; if not, according to the grain process analysis in step S8, the grain data yield rate and morphological integrity are used to classify the quality. Among them, the good products are listed as d file for storage, and the bad products are listed as e file for recycling.

[0042] In this embodiment, the classification process in step S3 is based on the voltage, wavelength, and brightness parameters of each grain in the wafer measured by the spot measuring machine, and the grains in the larger category are collected into the conductive film to obtain typical characteristic samples.

[0043] In this embodiment, the different positions described in step S3 include multiple positions at the top, bottom, left, right, and center positions of the selected wafer. The radius of the circular trajectory formed by the top, bottom, left, right, and center positions of the wafer is 2 / 3 of the outer diameter of the wafer. Since 2 / 3 of the outer diameter of the wafer can represent the transition area between its edge and middle, a more typical test object can be obtained by combining sampling at the middle position.

[0044] After the above steps, refer to Figure 1 The process shown uses a conductive film to collect grains, and at the same time, the collected grain data is thrown out. The spot measuring machine back-measures the grain comparison data to obtain yield control, prevent the cutting output of defective grains from flowing into the client in advance, effectively control the product NG abnormality rate, effectively control the quality of LED grain products, solve the problems of product batch abnormalities and classification confusion, and ensure the quality and reliability of LED grain products.

[0045] Example 2

[0046] The difference between this embodiment and the first embodiment is that the threshold value of the standard range is narrowed, thereby facilitating rapid classification of small batch wafer production.

[0047] When implementing small batch wafer production, the following quality inspection methods are performed:

[0048] S1: Use a spot measuring machine to perform full measurement on the wafer to obtain test data of each die in the wafer, and upload the test data and corresponding coordinates of each die to a computer system, so as to facilitate rapid search for test data corresponding to the die according to the coordinates during later collection and sorting operations;

[0049] S2: cutting the wafer using a cutting machine to obtain a plurality of discrete grains;

[0050] S3: Use a sorting machine to sort based on the grain coordinates, voltage, wavelength, and brightness. The coordinates are sampled at 2 / 3 of the wafer diameter. Production batches are divided into three categories: P, Q, and Y. Similar features are divided into similar batches. In this way, N wafers are sorted to obtain test objects with relatively typical feature types.

[0051] The computer system selects several wafers from each batch according to the three categories of P, Q, and Y. The sorting machine sorts several grains from different positions of each selected wafer onto the conductive film. The grains are classified according to the test data and coordinates of the grains, so that the grains are neatly arranged on the conductive film with relative coordinates. The grains collected on the conductive film are sent to the quality inspection bin of the spot tester for grain testing, thereby ensuring the uniformity of the test status each time.

[0052] S4: Coordinates of multiple grains located on the wafer are collected based on the conductive film, and test data corresponding to the coordinates in step S1 are obtained, which are defined as standard data and uploaded to a computer system to obtain a relatively typical reference standard.

[0053] S5: Use the quality inspection BIN of the spot measuring machine to perform full die testing. Specifically, the die include all the die with similar characteristics that are divided into 2 / 3 of the diameter of the wafer of the same batch. The test conditions are the same as those in step S1 to obtain the quality inspection BIN die data, which is used as the comparison data of the standard data. Since the better the die quality, the smaller the error value of the two measurements will be, the grade of the die can be determined based on the difference between the quality inspection BIN die data and the standard data.

[0054] S6: Uploading the quality inspection BIN grain data to a computer system so that the computer system can calculate and screen the difference between the quality inspection BIN grain data and the standard data in batches;

[0055] S7: Compare and analyze the standard data with the quality inspection BIN die data. Analyze the following items: voltage, wavelength, and brightness. Compare within the standard ranges of voltage ±0.04V, brightness 4%, and wavelength ±0.6nm in the standard data. Untested die whose quality inspection BIN die data meets the standard ranges and are of the same type as the test die are put into storage as finished products. Die data is classified into good and bad grades based on yield rate, morphological integrity, and surface appearance. Good quality is classified as grade A, and bad quality is classified as grade B. Die in grade A and grade B can be sold as good quality and good quality, respectively.

[0056] S8: The test dies whose BIN dies data of the quality inspection in step S5 meet the standard range are put into storage as downgraded finished products and listed as C-grade. The C-grade dies can be sold as ordinary products.

[0057] S9: Based on the result of the judgment of whether the quality inspection BIN die data in step S7 is within the standard range of the standard data, if not, the test die whose quality inspection BIN die data in step S5 does not meet the standard range and the untested die of the same batch type are returned to the die process analysis. The die process analysis is a measure for process personnel to analyze, solve, and determine whether the batch should be downgraded or scrapped. The analysis and judgment can be made based on the die data yield rate, morphological integrity, surface flatness or appearance quality.

[0058] S10: According to the grain process analysis described in step S9, determine whether unqualified products flow into the sorting and sampling products. If so, the sorting machine has an abnormality, and the corresponding batch of grains and the sorting machine involved are cleared, the sorting machine is reset, and the sorting machine re-sorts new materials; if not, according to the grain process analysis in step S8, the grain data yield rate and morphological integrity are used to classify the quality. Among them, the good products are listed as d file for storage, and the bad products are listed as e file for recycling.

[0059] After the above steps, by narrowing the thresholds of voltage, brightness, and wavelength within the standard range, it is convenient to quickly classify small batch wafer production, effectively control the product NG abnormality rate, effectively control the quality of LED chip products, solve the problems of product batch abnormalities and classification confusion, and ensure the quality and reliability of LED chip products.

[0060] Example 3

[0061] The difference between this embodiment and the first embodiment is that the threshold value of the standard range is enlarged, thereby facilitating effective classification in mass wafer production.

[0062] When implementing large-scale wafer production, the following quality inspection methods are performed:

[0063] S1: Use a spot measuring machine to perform full measurement on the wafer to obtain test data of each die in the wafer, and upload the test data and corresponding coordinates of each die to a computer system, so as to facilitate rapid search for test data corresponding to the die according to the coordinates during later collection and sorting operations;

[0064] S2: cutting the wafer using a cutting machine to obtain a plurality of discrete grains;

[0065] S3: Use a sorting machine to sort based on the grain coordinates, voltage, wavelength, and brightness. The coordinates are sampled at 2 / 3 of the wafer diameter. Production batches are divided into three categories: P, Q, and Y. Similar features are divided into similar batches. In this way, N wafers are sorted to obtain test objects with relatively typical feature types.

[0066] The computer system selects several wafers from each batch according to the three categories of P, Q, and Y. The sorting machine sorts several grains from different positions of each selected wafer onto the conductive film. The grains are classified according to the test data and coordinates of the grains, so that the grains are neatly arranged on the conductive film with relative coordinates. The grains collected on the conductive film are sent to the quality inspection bin of the spot tester for grain testing, thereby ensuring the uniformity of the test status each time.

[0067] S4: Coordinates of multiple grains located on the wafer are collected based on the conductive film, and test data corresponding to the coordinates in step S1 are obtained, which are defined as standard data and uploaded to a computer system to obtain a relatively typical reference standard.

[0068] S5: Use the quality inspection BIN of the spot measuring machine to perform full die testing. Specifically, the die include all the die with similar characteristics that are divided into 2 / 3 of the diameter of the wafer of the same batch. The test conditions are the same as those in step S1 to obtain the quality inspection BIN die data, which is used as the comparison data of the standard data. Since the better the die quality, the smaller the error value of the two measurements will be, the grade of the die can be determined based on the difference between the quality inspection BIN die data and the standard data.

[0069] S6: Uploading the quality inspection BIN grain data to a computer system so that the computer system can calculate and screen the difference between the quality inspection BIN grain data and the standard data in batches;

[0070] S7: Compare and analyze the standard data with the quality inspection BIN die data. Analyze the following items: voltage, wavelength, and brightness. Compare within the standard ranges of voltage ±0.06V, brightness 6%, and wavelength ±0.7nm in the standard data. Untested die whose quality inspection BIN die data meets the standard ranges and are of the same type as the test die are put into storage as finished products. Die data is classified into good and bad grades based on yield rate, morphological integrity, and surface appearance. Good quality is classified as grade A, and bad quality is classified as grade B. Die in grade A and grade B can be sold as good quality and good quality, respectively.

[0071] S8: The test dies whose BIN dies data of the quality inspection in step S5 meet the standard range are put into storage as downgraded finished products and listed as C-grade. The C-grade dies can be sold as ordinary products.

[0072] S9: Based on the result of the judgment of whether the quality inspection BIN die data in step S7 is within the standard range of the standard data, if not, the test die whose quality inspection BIN die data in step S5 does not meet the standard range and the untested die of the same batch type are returned to the die process analysis. The die process analysis is a measure for process personnel to analyze, solve, and determine whether the batch should be downgraded or scrapped. The analysis and judgment can be made based on the die data yield rate, morphological integrity, surface flatness or appearance quality.

[0073] S10: According to the grain process analysis described in step S9, determine whether unqualified products flow into the sorting and sampling products. If so, the sorting machine has an abnormality, and the corresponding batch of grains and the sorting machine involved are cleared, the sorting machine is reset, and the sorting machine re-sorts new materials; if not, according to the grain process analysis in step S8, the grain data yield rate and morphological integrity are used to classify the quality. Among them, the good products are listed as d file for storage, and the bad products are listed as e file for recycling.

[0074] Through the above steps, by enlarging the thresholds of voltage, brightness, and wavelength within the standard range, it is beneficial to effectively classify large-scale wafer production, effectively control the product NG abnormality rate, effectively control the quality of LED chip products, solve the problems of product batch abnormalities and classification confusion, and ensure the quality and reliability of LED chip products.

[0075] Example 4

[0076] The difference between this embodiment and the first embodiment is that the working process of the grain spot measuring machine is refined to ensure the effectiveness of the actual operation.

[0077] This embodiment provides a method for quality inspection after sorting vertical structure LED dies, including the following steps:

[0078] S1: Use a spot measuring machine to perform full measurement on the wafer to obtain test data of each die in the wafer, and upload the test data and corresponding coordinates of each die to a computer system, so as to facilitate rapid search for test data corresponding to the die according to the coordinates during later collection and sorting operations;

[0079] S2: cutting the wafer using a cutting machine to obtain a plurality of discrete grains;

[0080] S3: Use a sorting machine to sort based on the grain coordinates, voltage, wavelength, and brightness. The coordinates are sampled at 2 / 3 of the wafer diameter. Production batches are divided into three categories: P, Q, and Y. Similar features are divided into similar batches. In this way, N wafers are sorted to obtain test objects with relatively typical feature types.

[0081] The computer system selects several wafers from each batch according to the three categories of P, Q, and Y. The sorting machine sorts several grains from different positions of each selected wafer onto the conductive film. The grains are classified according to the test data and coordinates of the grains, so that the grains are neatly arranged on the conductive film with relative coordinates. The grains collected on the conductive film are sent to the quality inspection bin of the spot tester for grain testing, thereby ensuring the uniformity of the test status each time.

[0082] S4: Coordinates of multiple grains located on the wafer are collected based on the conductive film, and test data corresponding to the coordinates in step S1 are obtained, which are defined as standard data and uploaded to a computer system to obtain a relatively typical reference standard.

[0083] S5: Power on the die through the spot tester to make the die conduct and emit light. The quality inspection BIN of the spot tester is used to perform full die testing. Specifically, the die include all the die with similar characteristics that are divided into 2 / 3 of the diameter of the wafer of the same batch. The test conditions are the same as those in step S1. The quality inspection BIN die data is obtained and used as the comparison data of the standard data. Since the better the die quality, the smaller the error value of the two measurements will be. The grade of the die can be determined based on the difference between the quality inspection BIN die data and the standard data.

[0084] S6: Uploading the quality inspection BIN grain data to a computer system so that the computer system can calculate and screen the difference between the quality inspection BIN grain data and the standard data in batches;

[0085] S7: As Figure 2 As shown, the LED chip light data and electrical data (VF is voltage, LOP is brightness, WLD is wavelength) are collected and processed by the spot tester, and a complete mapping diagram data is given by the spot tester; the standard data (such as Figure 2 Data table on the left) and quality inspection BIN grain data (such as Figure 2 Comparative analysis is performed on the data table on the right, analyzing the following items: voltage, wavelength, and brightness. Comparison is performed within the standard ranges of voltage ±0.05V, brightness 5%, and wavelength ±0.7nm in the standard data. Untested dies whose quality inspection BIN die data meet the standard ranges and are of the same type as the tested dies are put into storage as finished products. Die data is then classified into good and bad grades based on yield rate, morphological integrity, and surface appearance. Good quality dies are classified as grade A, and bad quality dies are classified as grade B. Dices in grade A and grade B can be sold as good quality and good quality, respectively.

[0086] S8: The test dies whose BIN dies data of the quality inspection in step S5 meet the standard range are put into storage as downgraded finished products and listed as C-grade. The C-grade dies can be sold as ordinary products.

[0087] S9: Based on the result of determining whether the quality inspection BIN die data in step S7 is within the standard range of the standard data, if not, the test die whose quality inspection BIN die data in step S5 does not meet the standard range and the untested die of the same batch type are returned to the die process analysis. The die process analysis is a measure for process personnel to analyze, solve, and determine whether the batch should be downgraded or scrapped. The analysis and judgment can be made based on the die data yield rate, morphological integrity, surface flatness, or appearance finish quality.

[0088] S10: Clean the batches of grains corresponding to step S8 and the sorting machines involved. According to the grain process analysis, the grains are classified into good and bad categories according to the grain data yield rate, morphological integrity and surface appearance. The good products are classified as D-grade and put into storage, and the bad products are classified as E-grade and recycled. The D-grade grains are sold as inferior products, and the E-grade grains are recycled as raw materials.

[0089] After the above steps, the working process of the die spot measuring machine was refined using the mapping data provided by the spot measuring machine to ensure the effectiveness of the actual operation, thereby effectively controlling the quality of LED die products, solving the problems of product batch abnormalities and classification confusion, and ensuring the quality and reliability of LED die products.

[0090] The above description is only a preferred embodiment of the present invention and does not constitute a formal limitation to the present invention. It should be understood that for ordinary technicians in this field, the embodiments may be replaced by other equivalent forms, which should be included in the scope of protection of the present invention as long as they meet the feature range defined in the claims.

Claims

1. A method for quality inspection after sorting vertical structure LED die, characterized by: The following steps are involved: S1: Using a spot measuring machine to perform full measurement on the wafer, obtain test data of each die in the wafer, and upload the test data and corresponding coordinates of each die to a computer system; S2: cutting the wafer using a cutting machine to obtain a plurality of discrete grains; S3: Use a sorting machine to sort according to the grain coordinates, voltage, wavelength, and brightness. The coordinates are sampled at 2 / 3 of the wafer diameter. There are three production batches: P, Q, and Y. Similar features are divided into similar batches. In this way, N wafers are sorted. The computer system selects a number of wafers from each batch according to the three batches of P, Q, and Y. The sorting machine sorts a number of grains at different positions of each selected wafer onto the conductive film. According to the test data and coordinates of the grains, the grains are classified so that the grains are neatly arranged with relative coordinates on the conductive film. The grains collected on the conductive film are sent to the quality inspection BIN of the spot measuring machine for grain testing; S4: Coordinates of multiple grains located on the wafer are collected according to the conductive film, test data corresponding to the coordinates in step S1 are obtained, the test data are defined as standard data, and the standard data are uploaded to the computer system; S5: Use the quality inspection BIN of the spot tester to perform full die testing. Specifically, the die include all the die with similar characteristics that are divided into 2 / 3 of the diameter of the wafer of the same batch. The test conditions are the same as those in step S1 to obtain the quality inspection BIN die data. S6: Uploading the quality inspection BIN grain data to the computer system; S7: Compare and analyze the standard data with the quality inspection BIN grain data to determine whether the quality inspection BIN grain data is within the standard range of the standard data; if so, divide the data into three similar batch types of P, Q, and Y according to the similar characteristics in step S3, and put the untested grains whose quality inspection BIN grain data meets the standard range and belong to the same batch type as the test grains in step S5 into the warehouse as finished products, and classify them into good and bad grades according to the grain data yield achievement rate, morphological integrity and surface appearance, among which the good products are classified as grade a and the bad products are classified as grade b.

2. The method for quality inspection after sorting vertical structure LED die according to claim 1, characterized in that: After step S7, the method further includes: S8: The test grains whose quality inspection BIN grain data in step S5 meet the standard range are put into storage as downgraded finished products and listed as C grade.

3. The method for quality inspection after sorting vertical structure LED die according to claim 1, characterized in that: After step S7, the method further includes: S9: Based on the judgment result of whether the quality inspection BIN grain data in step S7 is within the standard range of the standard data, if not, the test grains whose quality inspection BIN grain data in step S5 do not meet the standard range and the untested grains of the same batch type are returned to the grain process analysis. The grain process analysis is a measure in which process personnel analyze, solve and determine whether the batch should be downgraded or scrapped.

4. The method for quality inspection after sorting vertical structure LED die according to claim 3, characterized in that: After step S9, the method further includes: S10: According to the grain process analysis described in step S9, determine whether unqualified products flow into the sorting and sampling products. If so, the sorting machine has an abnormality, and the corresponding batch of grains and the sorting machine involved are cleared, the sorting machine is reset, and the sorting machine re-sorts new materials; if not, according to the grain process analysis in step S9, the grain data yield rate and morphological integrity are used to classify the quality. Among them, the good products are listed as d file for storage, and the bad products are listed as e file for recycling.

5. The method for quality inspection after sorting vertical structure LED die according to claim 1, characterized in that: The step of classifying according to the test data and coordinates of the grains includes: The voltage, wavelength and brightness data of each grain in the wafer are measured by a spot tester and classified. Grains with the same electrical property, such as voltage, wavelength and brightness, are concentrated at 2 / 3 of the wafer diameter and are collected and placed on the conductive film.

6. The method for quality inspection after sorting vertical structure LED die according to claim 1, characterized in that: The different positions include multiple positions of the top, bottom, left, right, and center of the selected wafer.

7. The method for quality inspection after sorting vertical structure LED die according to claim 6, characterized in that: The upper, lower, left and right positions of the selected wafer form a circular track, the center of the circular track is the center of the selected wafer, and the diameter of the circular track is 2 / 3 of the outer diameter of the wafer.

8. The method for quality inspection after sorting vertical structure LED die according to claim 7, characterized in that: The computer system selects 2 pcs of wafers per batch according to the batch, and the sorting machine sorts 3 grains into the conductive film at the top, bottom, left, right and middle positions of each selected wafer.

9. The method for quality inspection after sorting vertical structure LED die according to claim 1, characterized in that: The standard range of the voltage data in the standard data is ±0.04v to ±0.06v; the standard range of the brightness data in the standard data is 4% to 6%; and the standard range of the wavelength data in the standard data is ±0.6nm to ±0.8nm.

10. The method for quality inspection after sorting vertical structure LED die according to claim 4, characterized in that: The die process analysis includes one or more of data yield rate, morphology integrity, surface flatness, and appearance smoothness quality.

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