Method for inspecting a lead frame and inspection template based on a standard lead frame

Abstract

A method for detecting defects in lead frames and a detection template based on a standard lead frame are disclosed. The defect detection method includes: providing a standard lead frame, the standard lead frame comprising a plurality of standard units arranged in a repeating array; acquiring a source image of the standard lead frame; establishing a first detection template based on the source image of the standard lead frame when the standard lead frame has preset attributes; providing a lead frame to be tested, the lead frame to be tested comprising a plurality of test units corresponding to the plurality of standard units of the standard lead frame; acquiring a source image of the lead frame to be tested; and performing defect detection on the plurality of test units based on the first detection template and the source image of the lead frame to be tested. This improves the accuracy of defect detection in lead frames and reduces over-detection when detecting defects in lead frames.

Description

Technical Field

[0001] This invention relates to the field of lead frame inspection technology, and in particular to a method for detecting defects in lead frames and an inspection template based on standard lead frames. Background Technology

[0002] As the chip carrier for many integrated circuits, the reliability and stability of the lead frame determines the function and performance of the final semiconductor product. Therefore, quality inspection of lead frame materials is necessary during the actual production process.

[0003] Conventional leadframe testing equipment typically uses a standard leadframe-based testing template to inspect the input leadframes for defects. Based on the defect inspection results, the equipment determines the leadframe's shipment category: those with high defects are scrapped, while those with low defects or those that do not affect functionality are considered good products.

[0004] However, when using existing detection templates and lead frame defect detection methods to detect defects in lead frames, the accuracy is poor, leading to severe overkill during lead frame detection. Summary of the Invention

[0005] The technical problem solved by this invention is to provide a defect detection method for lead frames and a detection template based on standard lead frames, so as to improve the accuracy of defect detection of lead frames and reduce over-detection when detecting defects in lead frames.

[0006] To solve the above technical problems, the present invention provides a defect detection method for a lead frame, comprising: providing a standard lead frame, the standard lead frame including a plurality of standard units arranged in an array, wherein the row direction of the array is the width direction of the standard lead frame, and the column direction of the array is the length direction of the standard lead frame; acquiring a source image of the standard lead frame; when the standard lead frame has a preset attribute, establishing a first detection template based on the source image of the standard lead frame, the first detection template including: a first template image and a first preset unit deviation range, the first template image including at least one row of standard images, the standard images being source images of defect-free standard units, and the first preset... The unit deviation range simultaneously corresponds to each standard image; a test lead frame is provided, the test lead frame includes multiple test units corresponding to multiple standard units of the standard lead frame; a source image of the test lead frame is acquired; based on the first detection template and the source image of the test lead frame, defect detection is performed on the multiple test units, the defect detection method includes: based on the position of the source image of any test unit in the source image of the test lead frame in the row direction, a standard image located at the same position in the row direction is acquired in the first template image as a designated standard image; defects of any test unit are detected based on the source image of any test unit, the designated standard image and the first preset unit deviation range.

[0007] Optionally, the preset attributes include one or more of the following: the thickness of the standard lead frame is below a preset minimum thickness, the width of the standard lead frame is above a preset maximum width, the density of the standard lead frame is above a preset maximum density, and the rigidity of the standard lead frame in the row direction is below a preset minimum rigidity.

[0008] Optionally, the method for establishing a first detection template based on the source image of the standard lead frame includes: dividing the source image of the standard lead frame into a first region, obtaining an initial standard row region in the source image of the standard lead frame, wherein the initial standard row region contains one row of standard images; dividing the initial standard row region into a second region, obtaining one standard unit region in the initial standard row region, wherein the standard unit region contains one standard image; dividing the initial standard row region into a third region based on the one standard unit region, obtaining one row of standard unit regions to form one standard row region; and after forming the one standard row region, configuring a first preset unit deviation range for each standard unit region.

[0009] Optionally, the method for dividing the initial standard row area into a second region includes: dividing the initial standard row area into an initial second region, obtaining one initial standard unit area in the initial standard row area, wherein the initial standard unit area contains one standard image; dividing the initial standard unit area into functional areas, obtaining several mutually independent standard functional areas in the initial standard unit area, wherein each standard functional area has a functional area type.

[0010] Optionally, the types of functional areas include one or more of the following: electroplating and critical areas, semi-etched areas, functional areas, non-functional areas, and low-threshold areas.

[0011] Optionally, the first preset unit deviation range includes: a plurality of first preset functional area deviation ranges corresponding one-to-one with a plurality of functional area types; the method for configuring the first preset unit deviation range for each standard unit area includes: configuring a corresponding first preset functional area deviation range for each standard functional area according to the functional area type of each standard functional area.

[0012] Optionally, before configuring the first preset unit deviation range for each standard unit area, the method of establishing a first detection template based on the source image of the standard lead frame further includes: dividing the source images of all standard lead frames outside the standard row area into a fourth region based on the one standard row area, forming a plurality of standard row areas; the method of obtaining a standard image located at the same position in the row direction in the first template image based on the position of the source image of any unit to be tested in the source image of the lead frame to be tested as a specified standard image further includes: obtaining a standard image located at the same position in the row direction and column direction in the first template image based on the position of the source image of any unit to be tested in the source image of the lead frame to be tested as a specified standard image based on the position of the source image of any unit to be tested in the row direction and column direction.

[0013] Optionally, the method for detecting defects in any unit under test based on the source image of any unit under test, the specified standard image, and the first preset unit deviation range includes: comparing the source image of any unit under test with the specified standard image to obtain corresponding unit deviation feature data; when the corresponding unit deviation feature data exceeds the first preset unit deviation range, it is detected that the any unit under test has several defects.

[0014] Optionally, when the standard lead frame does not have the preset attribute, a second detection template is established based on the source image of the standard lead frame. The second detection template includes: a standard image and a second preset unit deviation range corresponding to the standard image. Based on the second detection template and the source image of the lead frame to be tested, defect detection is performed on each unit to be tested.

[0015] Accordingly, the technical solution of the present invention also provides a detection template based on a standard lead frame, characterized in that the standard lead frame includes: a plurality of standard units arranged in a repeating array, wherein the row direction of the array arrangement is the width direction of the standard lead frame, and the column direction of the array arrangement is the length direction of the standard lead frame; the detection template includes: a first template image and a first preset unit deviation range, wherein the first template image includes at least one row of standard images, the standard images are source images of flawless standard units, and the first preset unit deviation range corresponds to each standard image.

[0016] Optionally, the first template image includes: at least one standard row area, each standard row area having one row of standard images, each standard row area including one row of standard unit areas, each standard unit area having one standard image, and the one standard image in each standard unit area being configured with the first preset unit deviation range.

[0017] Optionally, the standard unit area includes several independent standard functional areas, each standard functional area having a functional area type, the first preset unit deviation range includes several first preset functional area deviation ranges corresponding one-to-one with several functional area types, and each standard functional area is configured with a first preset functional area deviation range corresponding to the functional area type of each standard functional area.

[0018] Optionally, the types of functional areas include one or more of the following: electroplating and critical areas, semi-etched areas, functional areas, non-functional areas, and low-threshold areas.

[0019] Compared with the prior art, the technical solution of the embodiments of the present invention has the following beneficial effects:

[0020] In the defect detection method for lead frames provided by the technical solution of the present invention, when the standard lead frame has preset attributes, a first detection template is established based on the source image of the standard lead frame. The first detection template includes a first template image and a first preset unit deviation range. The first template image includes at least one row of standard images. The standard images are source images of flawless standard units. The first preset unit deviation range corresponds to each standard image. Furthermore, the method for defect detection of the plurality of units to be tested includes: based on the position of the source image of any unit to be tested in the row direction in the source image of the lead frame to be tested, obtaining standard images located at the same position in the row direction in the first template image as designated standard images; and detecting defects in any unit to be tested based on the source image of any unit to be tested, the designated standard images, and the first preset unit deviation range. Therefore, when performing defect detection, the accuracy of the benchmark (the first template image) compared with the source image of the lead frame under test is improved, and the risk of the source image of the lead frame under test being affected by changes in brightness in the row direction and exceeding the deviation range of the first preset unit is reduced. Thus, the accuracy of defect detection of the lead frame is improved, and overkill is reduced when detecting defects in the lead frame. Attached Figure Description

[0021] Figure 1 This is a top view of the feeding schematic diagram of a lead frame to be tested;

[0022] Figure 2 yes Figure 1 A side view of the feeding diagram along the X direction;

[0023] Figure 3 This is a flowchart illustrating a defect detection method for a lead frame according to an embodiment of the present invention.

[0024] Figure 4 This is a schematic diagram of the structure of a standard lead frame according to an embodiment of the present invention;

[0025] Figure 5 This is a schematic source image of a standard lead frame according to an embodiment of the present invention;

[0026] Figure 6 This is a schematic diagram of the structure of the lead frame to be tested according to an embodiment of the present invention;

[0027] Figure 7 This is a schematic source image of a lead frame under test according to an embodiment of the present invention;

[0028] Figure 8 This is a schematic diagram of the process for establishing a first detection template in one embodiment of the present invention;

[0029] Figures 9 to 13This is a schematic diagram of the steps for establishing the first detection template in one embodiment of the present invention;

[0030] Figure 14 This is a flowchart illustrating a method for defect detection based on a first detection template according to an embodiment of the present invention.

[0031] Figure 15 This is a schematic diagram of the steps for defect detection based on a first detection template in one embodiment of the present invention;

[0032] Figures 16 to 17 This is a schematic diagram of the steps for establishing a second detection template in one embodiment of the present invention. Detailed Implementation

[0033] As described in the background section, existing defect detection methods for lead frames based on detection templates and techniques suffer from poor accuracy, leading to severe over-detection during lead frame inspection. This will now be analyzed and explained in conjunction with specific embodiments.

[0034] Specifically, to perform defect detection on lead frames with multiple repeating units, a defect detection method for lead frames is proposed, including:

[0035] Step S10: Use the source image of a flawless cell as the standard template image;

[0036] Step S11: Configure a preset deviation range for the standard template image;

[0037] Step S13: Acquire source images of the lead frame through an optical platform. The source images of the lead frame include source images of the plurality of repeating units.

[0038] Step S14: Compare the standard template image with the source image of each unit of the lead frame;

[0039] When the deviation between the standard template image and the source image of any unit of the lead frame exceeds the preset deviation range, step S15 is executed to determine that the arbitrary unit has a corresponding defect.

[0040] Therefore, by using the source image of a flawless unit (the standard template image) as the comparison benchmark for the source image of each unit of the lead frame, it is determined whether the deviation of the source image of each unit of the lead frame exceeds the preset deviation range, thereby realizing the defect detection of the lead frame.

[0041] In the above-mentioned defect detection method for lead frames, the optical platform needs to acquire the source image of the lead frame through a feeding mechanism.

[0042] For details, please refer to Figure 1 and Figure 2 , Figure 1 This is a top view of the feeding schematic diagram of a lead frame to be tested. Figure 2 yes Figure 1 A side view of the feeding mechanism 10 along the Y direction shows that the feeding mechanism 10 includes: two guide rails 11 arranged in the X direction and extending along the Y direction, with the X and Y directions being perpendicular to each other, and the spacing between the two guide rails 11 in the X direction being adjustable; and a clamping mechanism 12 located on one side of each guide rail 11 in the X direction.

[0043] Please continue to refer to this. Figure 1 and Figure 2 The lead frame 20 is placed on the guide rail 11, and the clamping mechanism 12 clamps the edge of the lead frame 20, so that the lead frame 20 can be stably fed in the Y direction.

[0044] The lead frame 20 includes a plurality of repeating units 21.

[0045] During the feeding process, the optical platforms (not shown) located above and below the feeding mechanism 10 scan the front 22 and back 23 of the lead frame 20 respectively to obtain the front source image (not shown) and back source image (not shown) of the lead frame 20.

[0046] For ease of understanding, the following description uses the front source image of the lead frame 20 (not shown) as the source image of the lead frame in the above-described defect detection method for the lead frame.

[0047] When the lead frame 20 has a large width in the X direction, is very thin, or has a low density, the lead frame 20 located between the two clamping mechanisms 12 is prone to sag due to gravity. This causes the area far from the guide rail 11 (i.e., the middle area near the two guide rails 11) to be darker and the area near the guide rail 11 to be brighter when scanning the lead frame 20 from the front 22. Consequently, in the front source image, the source image of each unit in the X direction will be significantly affected by the brightness, resulting in a large difference.

[0048] Meanwhile, since the source image of a flawless cell is used as the standard template image, the standard template image is basically unaffected by changes in brightness.

[0049] Therefore, during steps S14 and S15, the deviation between the standard template image and the source image of each unit of the lead frame 20 is likely to exceed the preset deviation range, leading to incorrect judgment of defects. This results in poor accuracy during defect detection and severe overkill during lead frame detection.

[0050] It is important to understand that when a reverse image (not shown) of the lead frame 20 is used as the source image for the lead frame in the aforementioned defect detection method, scanning the lead frame 20 from the reverse side 23 will result in brighter areas away from the guide rail 11 and darker areas closer to the guide rail 11. Consequently, this will also lead to poor accuracy in defect detection, resulting in severe over-detection when detecting the lead frame.

[0051] To address the aforementioned technical problems, the present invention provides a method for detecting defects in lead frames and a detection template based on a standard lead frame. The method involves detecting defects in multiple test units based on a first detection template and a source image of the lead frame under test. The defect detection method includes: obtaining a standard image located at the same position in the row direction of the source image of any test unit in the source image of the lead frame under test as a designated standard image; and detecting defects in any test unit based on the source image of any test unit, the designated standard image, and a first preset unit deviation range. Therefore, during defect detection, the accuracy of the benchmark for comparison with the source image of the lead frame under test is improved, and the risk of the source image of the lead frame under test exceeding the first preset unit deviation range due to changes in brightness in the row direction is reduced. This improves the accuracy of defect detection in lead frames and reduces over-detection of defects.

[0052] To make the above-mentioned objectives, features and beneficial effects of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0053] Figure 3 This is a flowchart illustrating a defect detection method for a lead frame according to an embodiment of the present invention.

[0054] Please refer to Figure 3 The defect detection method for the lead frame includes:

[0055] Step S100: Provide a standard lead frame, the standard lead frame including a plurality of standard units arranged in an array, the row direction of the array being the width direction of the standard lead frame, and the column direction of the array being the length direction of the standard lead frame.

[0056] Step S200: Obtain the source image of the standard lead frame;

[0057] Step S300: Provide a test lead frame, the test lead frame including a plurality of test units corresponding to a plurality of standard units of the standard lead frame respectively;

[0058] Step S400: Obtain the source image of the lead frame to be tested;

[0059] When the standard lead frame has preset properties, step S500 is executed to establish a first detection template based on the source image of the standard lead frame; and step S600 is executed to perform defect detection on the plurality of test units based on the first detection template and the source image of the lead frame to be tested.

[0060] When the standard lead frame does not have preset attributes, step S700 is executed to establish a second detection template based on the source image of the standard lead frame; and step S800 is executed to perform defect detection on each unit to be tested based on the second detection template and the source image of the lead frame to be tested.

[0061] It should be understood that steps S300 and S400 do not have a fixed execution order with steps S100, S200, S500 and S700. Steps S300 and S400 only need to be executed before steps S600 and S800.

[0062] The following is a detailed description in conjunction with the accompanying drawings.

[0063] Please refer to Figure 4 , Figure 4 This is a schematic diagram of the structure of a standard lead frame according to an embodiment of the present invention, wherein a standard lead frame 100 is provided.

[0064] The standard lead frame 100 includes a plurality of standard units 101 arranged in a repeating array.

[0065] The row direction X of the array arrangement is the width direction of the standard lead frame 100, and the column direction Y of the array arrangement is the length direction of the standard lead frame 100.

[0066] It should be noted that the standard unit 101 can be the smallest repeating unit in the standard lead frame 100, or it can include more than two smallest repeating units.

[0067] It should be noted that the standard lead frame 100 has a front (not shown) and a back (not shown) opposite sides. In this embodiment, the standard unit 101 refers to the structure of the standard lead frame 100 on one side of the front or back side.

[0068] In addition, for ease of explanation and understanding, Figure 4 Only a portion of the multiple standard units 101 are schematically shown, and, although Figure 4In the row direction X, adjacent standard units 101 are adjacent (without spacing). However, whether in the row direction X or the column direction Y, the spacing between adjacent standard units 101 can be determined according to actual needs, such as the specific area where defects need to be detected, the structural design of the lead frame, etc.

[0069] Please refer to Figure 5 , Figure 5 This is a schematic diagram of the source image of a standard lead frame according to an embodiment of the present invention, wherein the source image 200 of the standard lead frame 100 is obtained.

[0070] In this embodiment, an optical platform is used to acquire the source image 200 of the standard lead frame 100, and the optical platform includes a CCD camera, etc.

[0071] It should be understood that the optical platform, related equipment, and methods for acquiring source images in this embodiment should not be considered as features that limit the scope of protection of this invention.

[0072] It should be noted that, since each standard unit 101 in this embodiment refers to the structure of a single side of the standard lead frame 100 on the front or back, the source image 200 of the standard lead frame 100 refers to the source image of a single side of the standard lead frame 100 on the front or back.

[0073] Please refer to Figure 6 , Figure 6 This is a schematic diagram of the structure of a test lead frame according to an embodiment of the present invention, providing a test lead frame 300.

[0074] The lead frame under test 300 includes multiple units under test 301 that correspond to multiple standard units 101 of the standard lead frame 100.

[0075] Specifically, the lead frame 300 under test and the standard lead frame 100 are structurally identical lead frames, and correspondingly, the unit under test 301 and the standard unit 101 are structurally identical units.

[0076] The difference between the test lead frame 300 and the standard lead frame 100 is that the standard lead frame 100 is used to establish a first or second test template. Specifically, when a first test template needs to be established, at least one row of defect-free units is included among the multiple standard units 101 in the standard lead frame 100 to establish the first test template; when a second test template needs to be established, at least one defect-free unit is included among the multiple standard units 101 in the standard lead frame 100 to establish the second test template. Meanwhile, the test lead frame 300 is the lead frame that needs to be tested for defects.

[0077] Preferably, a standard lead frame 100 is provided during the pilot production phase, and a first inspection template is established. Furthermore, a lead frame 300 to be tested is provided during the mass production phase for defect detection. This eliminates the need to spend time establishing the first inspection template during the mass production phase, thereby improving mass production efficiency.

[0078] Please refer to Figure 7 , Figure 7 This is a schematic diagram of the source image of the lead frame under test according to an embodiment of the present invention, and the source image 400 of the lead frame under test 300 is obtained.

[0079] In this embodiment, an optical platform is used to acquire the source image 400 of the lead frame 300 under test. The optical platform includes a CCD camera, etc.

[0080] It should be noted that the source image 400 of the lead frame 300 under test refers to the source image of one side of the lead frame 300 under test, either on the front or back.

[0081] Please continue to refer to this. Figure 3 In this embodiment, when the standard lead frame 100 has preset properties, a first detection template is established based on the source image 200 of the standard lead frame 100.

[0082] In this embodiment, the preset attributes include one or more of the following: the thickness of the standard lead frame 100 is below a preset minimum thickness, the width of the standard lead frame 100 is above a preset maximum width, the density of the standard lead frame 100 is above a preset maximum density, and the rigidity (in N / m) of the standard lead frame in the row direction X is below a preset minimum rigidity.

[0083] The density of the standard lead frame 100 refers to the number of standard cells 101 in a row of standard cells 101 in the X direction of the standard lead frame 100. The preset attribute is used to determine whether the standard lead frame 100 is a wide, thin, or heavy lead frame that is easily deformed by gravity.

[0084] The first detection template includes: a first template image and a first preset unit deviation range. The first template image includes at least one row of standard images. The standard images are source images 200 of flawless standard units 101. The first preset unit deviation range corresponds to each standard image.

[0085] It should be understood that, since the first template image includes at least one row of standard images, the standard lead frame 100 includes at least one row of flawless standard cells 101. Specifically, the standard lead frame 100 needs to have at least the number of flawless standard cells 101 equivalent to the number of standard images in the first template image.

[0086] Please refer to Figure 8 , Figure 8 This is a flowchart illustrating the process of establishing a first detection template in one embodiment of the present invention. The method for establishing the first detection template based on the source image of the standard lead frame includes:

[0087] Step S510: Divide the source image of the standard lead frame into a first region and obtain an initial standard row region in the source image of the standard lead frame, wherein the initial standard row region has one row of standard image.

[0088] Step S520: Divide the initial standard row area into a second region, and obtain a standard unit area in the initial standard row area, wherein the standard unit area contains a standard image;

[0089] Step S530: Divide the initial standard row area into a third region according to the one standard unit area to obtain one standard unit area, so as to form one standard row area;

[0090] Step S540: Based on the one standard row area, perform a fourth region division on the source image of all standard lead frames outside the standard row area to form several standard row areas.

[0091] Step S550: After forming several standard row areas, configure the first preset cell deviation range for each standard cell area.

[0092] Figures 9 to 13 This is a schematic diagram of the steps involved in establishing the first detection template in one embodiment of the present invention. The following is in conjunction with... Figures 9 to 13 The steps for establishing the first detection template are explained in detail.

[0093] Please refer to Figure 9 The source image 200 of the standard lead frame 100 is divided into a first region, and an initial standard row region 210 is obtained in the source image 200 of the standard lead frame 100.

[0094] The initial standard row area has one row of standard images 201, and the standard images 201 are the source images 200 of the flawless standard units 101.

[0095] Next, the initial standard row area 210 is divided into a second region, and a standard unit region is obtained in the initial standard row area 210, wherein the standard unit region contains a standard image 201. For details on the steps of dividing the initial standard row area 210 into the second region, please refer to [link to relevant documentation]. Figure 10 and Figure 11 .

[0096] Please refer to Figure 10 The initial standard row 210 is divided into an initial second region, and an initial standard unit region 220 is obtained in the initial standard row region 210. The initial standard unit region 220 contains a standard image 201.

[0097] Preferably, the standard image 201 within the initial standard unit area 220 is: one of the standard images 201 at both ends of a row of standard images 201 (e.g., Figure 10 (As shown in the diagram). This allows the device that establishes the first detection template to perform more accurate region division when forming standard row areas.

[0098] Please refer to Figure 11 The initial standard unit area 220 is divided into functional areas, and several independent standard functional areas 221 are obtained in the initial standard unit area 220.

[0099] Thus, a standard unit area 230 is formed, which includes: a plurality of mutually independent standard functional areas 221.

[0100] In this embodiment, each standard functional area 221 has a functional area type.

[0101] In this embodiment, the types of functional areas include one or more of the following: plating and key areas, half-etched areas, functional areas, non-functional areas, and large low-value areas.

[0102] In other words, for a standard functional area 221, the functional area type can be an electroplating and critical area, a semi-etched area, a functional area, a non-functional area, or a low threshold area.

[0103] In some practical applications, the division of the first and second regions can be performed by technicians.

[0104] Please refer to Figure 12The initial standard row area 210 is divided into a third region based on the standard unit area 230 to obtain a standard unit area 230, thereby forming a standard row area 240.

[0105] Specifically, the third region division is performed by using a standard unit region 230 as a template to divide the remaining regions in the initial standard row region 210, excluding the standard unit region 230.

[0106] In some practical applications, after technicians perform the first and second region divisions to obtain the initial standard row area 210 and one standard unit area 230, the remaining area in the initial standard row area 210 is automatically divided according to the one standard unit area 230 by the device used to establish the first detection template, forming one standard unit area 230.

[0107] Please refer to Figure 13 Based on the standard row area 240, the source image 200 of all standard lead frames 100 outside the standard row area 240 is divided into a fourth region to form several standard row areas 240.

[0108] Thus, a first template image 500 is formed based on several standard row areas 240.

[0109] Specifically, the first template image 500 includes the plurality of standard row areas 240. That is, in this embodiment, the first template image 500 includes: a standard image 201 corresponding one-to-one with all the standard units 101.

[0110] Accordingly, all standard units 101 of the standard lead frame 100 in this embodiment are free of defects.

[0111] Specifically, the fourth region division is performed by using a standard row area 240 as a template to divide the remaining regions in the source image 200 of the standard lead frame 100, excluding the standard row area 240.

[0112] In some practical applications, the device used to establish the first detection template automatically divides the remaining areas of the source image 200 of the standard lead frame 100, excluding the standard row area 240, into several standard row areas 240 based on the standard row area 240.

[0113] In another embodiment, the fourth region division is not performed, and the first template image includes one standard row region 240. Therefore, the first template image includes one row of standard images 201.

[0114] Please continue to refer to this. Figure 13A first preset unit deviation range is configured for each standard unit area 230.

[0115] Specifically, reference data can be obtained based on the standard image 201 in any standard unit area 230. The first preset unit deviation range corresponding to any standard unit area 230 is a deviation range based on the reference data of the standard image 201 in any standard unit area 230.

[0116] Therefore, by dividing the standard unit area 230, it is possible to configure a first preset unit deviation range for each standard image 201.

[0117] The reference data includes at least one of an area parameter, a diagonal length parameter, and a contrast parameter. Correspondingly, the first preset unit deviation range includes at least one of a deviation range for the area parameter, a deviation range for the diagonal length parameter, and a deviation range for the contrast parameter.

[0118] In this embodiment, after the fourth region is divided, the deviation range of the first preset unit is configured.

[0119] In another embodiment, the first preset unit deviation range is configured after the third region division is performed.

[0120] In this embodiment, the first preset unit deviation range includes several first preset functional area deviation ranges that correspond one-to-one with several functional area types. That is, each functional area type has its own preset deviation range (first preset functional area deviation range).

[0121] Accordingly, the first preset functional area deviation range for each functional area type includes at least one of the following: the deviation range of the area parameter, the deviation range of the diagonal length parameter, and the deviation range of the contrast parameter.

[0122] It is important to understand that the first preset function area deviation ranges corresponding to different types of function areas are independent of each other; they may be the same or different.

[0123] In this embodiment, the method of configuring the first preset unit deviation range for each standard unit area 230 includes: configuring a corresponding first preset functional area deviation range for each standard functional area 221 according to the functional area type of each standard functional area 221.

[0124] Thus, the establishment of the first detection template is completed. Specifically, the first detection template includes: the first template image 500 and the first preset unit deviation range.

[0125] Next, based on the first detection template and the source image 400 of the lead frame 300 to be tested, defect detection is performed on the plurality of units to be tested 301.

[0126] Please refer to Figure 14 , Figure 14 This is a flowchart illustrating a method for defect detection based on a first detection template according to an embodiment of the present invention. The method for defect detection of the plurality of test units based on the first detection template and the source image of the lead frame to be tested includes:

[0127] Step S610: Based on the position of the source image of any unit under test in the source image of the lead frame under test in the row direction and column direction, obtain a standard image located at the same position in the row direction and column direction in the first template image as a specified standard image.

[0128] Step S620: Detect defects in any unit under test based on the source image of any unit under test, the specified standard image, and the first preset unit deviation range.

[0129] When the standard lead frame has preset attributes, a first detection template is established based on the source image of the standard lead frame. The first detection template includes a first template image and a first preset unit deviation range. The first template image includes at least one row of standard images, where each standard image is a source image of a flawless standard unit. The first preset unit deviation range corresponds to each standard image. Furthermore, the method for defect detection of the plurality of units to be tested includes: based on the position of the source image of any unit to be tested in the row direction within the source image of the lead frame to be tested, obtaining a standard image located at the same position in the row direction within the first template image as a designated standard image; and detecting defects in any unit to be tested based on the source image of any unit to be tested, the designated standard image, and the first preset unit deviation range. Therefore, when performing defect detection, the accuracy of the benchmark (the first template image) compared with the source image of the lead frame to be tested is improved. Specifically, by using a standard image located at the same position as any unit under test in the row direction as a comparison benchmark, the risk of the source image of the lead frame under test exceeding the first preset unit deviation range due to changes in brightness in the row direction is reduced. This improves the accuracy of defect detection in the lead frame and reduces over-detection during lead frame inspection.

[0130] Furthermore, in this embodiment, since the standard image used as the comparison benchmark is located at the same position as any of the test units in the column direction, the accuracy of defect detection in the lead frame can be further improved. Moreover, because the position is the same in both the row and column directions, when performing defect detection on the source image of the lead frame under test based on the first detection template, the designated standard image can be directly determined based on absolute coordinates, avoiding the need for relative coordinate conversion. This reduces the amount of data computation during defect detection, further improving the efficiency of defect detection and thus increasing the production efficiency of the lead frame.

[0131] In another embodiment, the first template image includes one row of standard images, and the method for detecting defects in the plurality of test units based on the first detection template and the source image of the lead frame to be tested includes: based on the position of the source image of any test unit in the source image of the lead frame to be tested in the row direction, obtaining a standard image located at the same position in the row direction in the first template image as a designated standard image; and detecting defects in any test unit based on the source image of any test unit, the designated standard image, and the first preset unit deviation range.

[0132] Figure 15 This is a schematic diagram of the steps for defect detection based on a first detection template in one embodiment of the present invention. The following is in conjunction with... Figure 15 The steps for defect detection of the plurality of test units 301 based on the first detection template and the source image 400 of the test lead frame 300 are described in detail.

[0133] Please refer to Figure 15 Based on the position of the source image 400 of any test unit 301 in the source image 400 of the test lead frame 300 in the row direction X and column direction Y, a standard image 201 located at the same position in the row direction X and column direction X is obtained in the first template image 500 as a designated standard image 231.

[0134] In this embodiment, the source image 400 and the first template image 500, located at the same position in the row direction X and column direction Y, have their own origin coordinates and absolute coordinates relative to their respective origin coordinates. Therefore, based on the absolute coordinates of the source image 401 of any test unit 301 in the source image 400, the same absolute coordinates can be determined in the first template image 500, thereby obtaining a standard image 201 located at the same position in the row direction X and column direction X as the designated standard image 231.

[0135] It should be understood that the absolute coordinates are only one type of positional information used to represent the position of the source image 401 and the standard image 201 of any unit under test 301. The determination of the specified standard image 231 can also be achieved by using other positional information types such as relative coordinates and sorting positions.

[0136] In another embodiment, the first template image has origin coordinates and relative coordinates relative to the origin coordinates. The source image of each row of test units 301 in the source image 400 has origin coordinates, and the origin coordinates of the source image of each row of test units 301 are located at the same position as the origin coordinates of the first template image, at least in the row direction X. The source image of each row of test units 301 also has relative coordinates relative to the origin coordinates of the source image of each row of test units 301, at least in the row direction X. Therefore, based on the relative coordinates of the source image of any test unit 301 in the source image 400, the same relative coordinates can be determined in the first template image, thereby obtaining a standard image 201 located at the same position in the row direction X as a specified standard image.

[0137] Please continue to refer to this. Figure 15 The source image 401 of any test unit 301 is compared with the specified standard image 231 to obtain the corresponding unit deviation feature data.

[0138] Since the reference data includes at least one of the area parameter, diagonal length parameter, and contrast parameter, and the first preset unit deviation range includes at least one of the deviation range of the area parameter, the deviation range of the diagonal length parameter, and the deviation range of the contrast parameter, the corresponding unit deviation feature data includes at least one of the area deviation data, diagonal length deviation data, and contrast deviation data.

[0139] Please continue to refer to this. Figure 15 When the corresponding unit deviation feature data exceeds the first preset unit deviation range, it is detected that any unit 301 under test has several defects.

[0140] Specifically, when the unit deviation feature data obtained based on each deviation between the source image 401 of any test unit 301 and the specified standard image 231 exceeds the first preset unit deviation range, it is determined that any test unit 301 has a defect corresponding to that deviation.

[0141] In this embodiment, the unit deviation feature data obtained based on each deviation between the source image 401 of any test unit 301 and the specified standard image 231, exceeding the first preset unit deviation range means that the unit deviation feature data obtained based on any deviation exceeds the first preset functional area deviation range corresponding to the standard functional area 221 where the deviation is located.

[0142] Please continue to refer to this. Figure 3 In this embodiment, when the standard lead frame 100 does not have the preset attribute, a second detection template is established based on the source image 200 of the standard lead frame 100.

[0143] The second detection template includes: a standard image 201 and a second preset unit deviation range corresponding to the standard image 201.

[0144] In other words, in this embodiment, when the standard lead frame 100 is a wide, thin, and heavy lead frame that is easily deformed by gravity, a first detection template is established. When the standard lead frame 100 is not a wide, thin, and heavy lead frame that is easily deformed by gravity, a second detection template is established.

[0145] Therefore, based on the characteristics of the standard lead frame 100, a targeted detection template can be established: when the standard lead frame 100 is easily deformed by gravity, a first detection template with higher accuracy can be established to reduce the impact of light intensity; when the standard lead frame 100 is not easily deformed by gravity, a second detection template with lower complexity can be established to improve the efficiency of detection template establishment.

[0146] In other embodiments, the first detection template is also established when the standard lead frame 100 does not have the preset attribute.

[0147] The method for establishing the second detection template in this embodiment includes: dividing the source image 200 of the standard lead frame 100 into a fifth region, obtaining a standard unit region 230 in the source image 200 of the standard lead frame 100; and configuring a second preset unit deviation range for the standard unit region 230.

[0148] Figures 16 to 17 This is a schematic diagram illustrating the steps involved in establishing the second detection template in one embodiment of the present invention. The following is in conjunction with... Figures 16 to 17 The steps for establishing the second detection template in this embodiment are described in detail.

[0149] Please refer to Figure 16An initial standard cell region 220 is obtained from the source image 200 of the standard lead frame 100, and the initial standard cell region 220 contains a standard image 201.

[0150] Please refer to Figure 17 The initial standard unit area 220 is divided into functional areas, and several independent standard functional areas 221 are obtained in the initial standard unit area 220.

[0151] Thus, the fifth region division is completed, forming the second template image 600, which includes one standard unit region 230. For a detailed explanation of the standard unit region 230, please refer to the explanation of the standard unit region 230 in the aforementioned first detection template, which will not be repeated here.

[0152] Please continue to refer to this. Figure 17 A second preset unit deviation range is configured for the one standard unit area 230.

[0153] In this embodiment, the second preset unit deviation range is a deviation range based on the reference data of the standard image 201 in the standard unit area 230.

[0154] Accordingly, the deviation range of the second preset unit includes at least one of the deviation range of the area parameter, the deviation range of the diagonal length parameter, and the deviation range of the contrast parameter.

[0155] In this embodiment, the second preset unit deviation range includes: a plurality of second preset functional area deviation ranges corresponding one-to-one with a plurality of functional area types.

[0156] Correspondingly, the second preset functional area deviation range for each functional area type includes at least one of the following: the deviation range of the area parameter, the deviation range of the diagonal length parameter, and the deviation range of the contrast parameter.

[0157] In this embodiment, the method for configuring a second preset unit deviation range for the one standard unit area 230 includes: configuring a corresponding second preset functional area deviation range for each standard functional area 221 according to the functional area type of each standard functional area 221 of the one standard unit area 230.

[0158] Please continue to refer to this. Figure 3 Next, based on the second detection template and the source image 200 of the lead frame 100 under test, defect detection is performed on each unit 301 under test.

[0159] In this embodiment, the method for detecting defects in the plurality of test units based on the second detection template and the source image of the lead frame to be tested includes: comparing the source image 401 of each test unit 301 with the standard image 201 in the standard unit area 230 to obtain the unit deviation feature data of the source image 401 of each test unit 301; when the unit deviation feature data of the source image 401 of any test unit 301 exceeds the second preset unit deviation range, it is detected that any test unit 301 has several defects.

[0160] Since the reference data includes at least one of the area parameter, diagonal length parameter, and contrast parameter, and the second preset unit deviation range includes at least one of the deviation range of the area parameter, the deviation range of the diagonal length parameter, and the deviation range of the contrast parameter, the corresponding unit deviation feature data includes at least one of the area deviation data, diagonal length deviation data, and contrast deviation data.

[0161] It should be noted that the defect detection method for the lead frame in this embodiment can be applied independently to detect defects in the structure of the lead frame 300 under test on the front side, or independently to detect defects in the structure of the lead frame 300 under test on the back side.

[0162] Accordingly, one embodiment of the present invention also provides a detection template based on a standard lead frame formed by the above method. Please refer to [further details]. Figure 13 The first template image 500 includes a first template image 500 and a first preset unit deviation range. The first template image 500 includes at least one row of standard images 201. The standard images 201 are source images 200 of flawless standard units 101. The first preset unit deviation range corresponds to each standard image 201.

[0163] In this embodiment, the first template image 500 includes: a plurality of standard row areas 240, each standard row area 240 having one row of standard images 201.

[0164] Specifically, the first template image 500 includes a standard image 201 that corresponds one-to-one with all the standard units 101.

[0165] In this embodiment, each standard row area 240 includes one standard unit area 230, each standard unit area 230 has one standard image 201, and the standard image in each standard unit area 230 is configured with the first preset unit deviation range.

[0166] Specifically, the standard unit area 230 includes several independent standard functional areas 221, each of which has a functional area type.

[0167] In this embodiment, the types of functional areas include one or more of the following: electroplating and critical areas, semi-etched areas, functional areas, non-functional areas, and low-threshold areas.

[0168] In this embodiment, the first preset unit deviation range includes: a plurality of first preset functional area deviation ranges corresponding one-to-one with a plurality of functional area types.

[0169] In this embodiment, each standard functional area 221 is configured with a first preset functional area deviation range corresponding to the functional area type of each standard functional area 221.

[0170] It should be understood that the detailed description of the deviation range between the first template image 500 and the first preset unit in this embodiment can be found in the explanation of the deviation range between the first template image 500 and the first preset unit in the aforementioned embodiment of the defect detection method for the lead frame, and will not be repeated here.

[0171] In another embodiment, the first template image includes: one standard row area 240. That is: the first template image includes one row of standard images 201.

[0172] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the invention; therefore, the scope of protection of the present invention should be determined by the scope defined in the claims.

Claims

1. A method of inspecting a lead frame for defects, the method comprising: include: A standard lead frame is provided, the standard lead frame comprising a plurality of standard units arranged in a repeating array, wherein the row direction of the array is the width direction of the standard lead frame, and the column direction of the array is the length direction of the standard lead frame. Obtain the source image of the standard lead frame; When the standard lead frame has preset attributes, a first detection template is established based on the source image of the standard lead frame. The first detection template includes: a first template image and a first preset unit deviation range. The first template image includes at least one row of standard images. The standard images are source images of flawless standard units. The first preset unit deviation range corresponds to each standard image. A test lead frame is provided, the test lead frame including a plurality of test units corresponding to a plurality of standard units of the standard lead frame; Obtain the source image of the lead frame to be tested; Based on the first detection template and the source image of the lead frame to be tested, defect detection is performed on the plurality of units to be tested. The defect detection method includes: based on the position of the source image of any unit to be tested in the source image of the lead frame to be tested in the row direction, obtaining a standard image located at the same position in the row direction in the first template image as a specified standard image; and detecting defects in any unit to be tested based on the source image of any unit to be tested, the specified standard image, and the first preset unit deviation range. When the standard lead frame does not have the preset attribute, a second detection template is established based on the source image of the standard lead frame. The second detection template includes: a standard image and a second preset unit deviation range corresponding to the standard image. Based on the second detection template and the source image of the lead frame to be tested, defect detection is performed on each unit to be tested; The preset attributes include one or more of the following: the thickness of the standard lead frame is below a preset minimum thickness, the width of the standard lead frame is above a preset maximum width, the density of the standard lead frame is above a preset maximum density, and the rigidity of the standard lead frame in the row direction is below a preset minimum rigidity.

2. The method of claim 1, wherein the step of detecting the defect of the lead frame is performed by using a camera. The method for establishing a first detection template based on the source image of the standard lead frame includes: The source image of the standard lead frame is divided into a first region, and an initial standard row region is obtained in the source image of the standard lead frame, wherein the initial standard row region has one row of standard image; The initial standard row area is divided into a second region, and a standard unit area is obtained in the initial standard row area, wherein the standard unit area contains a standard image; The initial standard row area is divided into a third region based on the first standard unit area to obtain one standard unit area, thus forming one standard row area. After forming the standard row area, the first preset cell deviation range is configured for each standard cell area.

3. The defect detection method for lead frames as described in claim 2, characterized in that, The method for dividing the initial standard row area into a second region includes: The initial standard row area is divided into an initial second region, and an initial standard unit area is obtained in the initial standard row area, wherein the initial standard unit area contains a standard image; The initial standard unit area is divided into functional areas, and several independent standard functional areas are obtained in the initial standard unit area, each standard functional area having a functional area type.

4. The defect detection method for lead frame as described in claim 3, characterized in that, The types of functional areas include one or more of the following: electroplating and critical areas, semi-etched areas, functional areas, non-functional areas, and low-threshold areas.

5. The defect detection method for lead frame as described in claim 3, characterized in that, The first preset unit deviation range includes: a number of first preset functional area deviation ranges that correspond one-to-one with a number of functional area types; The method for configuring the first preset unit deviation range for each standard unit area includes: configuring a corresponding first preset functional area deviation range for each standard functional area according to the functional area type of each standard functional area.

6. The defect detection method for lead frames as described in claim 5, characterized in that, Before configuring the first preset unit deviation range for each standard unit area, the method of establishing a first detection template based on the source image of the standard lead frame further includes: dividing the source images of all standard lead frames outside the standard row area into a fourth region based on the one standard row area to form a number of standard row areas. The method of obtaining a standard image located at the same position in the row direction of the source image of any unit under test in the source image of the lead frame under test as a specified standard image in the first template image further includes: obtaining a standard image located at the same position in the row direction and column direction of the source image of any unit under test in the source image of the lead frame under test as a specified standard image in the first template image, based on the position in the row direction and column direction of the source image of any unit under test in the source image of the lead frame under test.

7. The defect detection method for lead frames as described in any one of claims 1 to 6, characterized in that, The method for detecting defects in any test unit based on the source image of any test unit, the specified standard image, and the first preset unit deviation range includes: The source image of any unit under test is compared with the specified standard image to obtain the corresponding unit deviation feature data; When the corresponding unit deviation feature data exceeds the first preset unit deviation range, it is detected that any unit under test has several defects.

Images