LED semiconductor production data traceability analysis method and system

Abstract

The application relates to the technical field of LED semiconductor manufacturing, solves the problem that quality and consistency cannot be maintained in the packaging and storage process of finished LED semiconductors in the prior art, and provides an LED semiconductor production data tracing analysis method and system.The method comprises the following steps: acquiring a banding scheme according to a unique identifier of a finished LED semiconductor, the banding scheme comprising a banding mode and a banding position; performing banding treatment on the finished LED semiconductor according to the banding scheme to obtain an LED light bar; performing quality detection on the LED light bar to obtain a quality detection result, wherein the quality detection comprises optical detection, electrical detection and mechanical detection; generating a unique identifier corresponding to the LED light bar that passes the quality detection; and performing warehouse storage treatment on the LED light bar according to the unique identifier and the corresponding quality detection result to obtain an LED product.The application can maintain quality and consistency in the packaging and storage process of finished LED semiconductors.

Description

[0001] The present application is a divisional application of the invention patent application with the application number 202410986452.5, the title of which is "LED semiconductor production control method and system", and which was filed on July 23, 2024. TECHNICAL FIELD

[0002] The present application relates to the technical field of LED semiconductor, and particularly relates to an LED semiconductor production data traceability analysis method and system. BACKGROUND

[0003] During the packaging and storage of finished LED semiconductors, it is crucial to maintain quality and consistency, because LED semiconductors are extremely sensitive to environmental conditions, especially factors such as humidity, temperature and physical pressure. Strict packaging and storage specifications help to ensure the reliability, light efficiency and life consistency of LED products, thereby providing high-quality light source solutions for downstream applications.

[0004] The prior art is faced with the problem of difficulty in maintaining quality and consistency during the packaging and storage of finished LED semiconductors, mainly due to the lack of precise banding processing and strict quality detection control for LED semiconductors. On the one hand, the traditional banding process often relies on manual operation, which is prone to cause errors in the arrangement position, direction and fixing force of LED semiconductors, thereby affecting the reliability of subsequent use. On the other hand, the lack of comprehensive quality inspection of LED semiconductors in terms of optical, electrical and mechanical performance makes it difficult to screen out products with quality differences during packaging and storage. In addition, in the warehousing and storage link, the environmental control is not accurate enough (such as humidity and temperature), which can accelerate the degradation of LED performance, affect its light efficiency and life, and thus cannot effectively ensure the quality and consistency and performance stability of the products out of the factory.

[0005] Therefore, how to maintain the quality and consistency during the packaging and storage of finished LED semiconductors is a problem to be solved. SUMMARY

[0006] In view of this, the present application embodiment provides an LED semiconductor production data traceability analysis method and system to solve the problem that the quality and consistency cannot be maintained during the packaging and storage of finished LED semiconductors in the prior art.

[0007] In a first aspect, the present application embodiment provides an LED semiconductor production data traceability analysis method, which comprises:

[0008] According to the unique identifier of the finished LED semiconductor, a banding scheme is obtained, the banding scheme comprising a banding mode and a banding position;

[0009] According to the braiding scheme, the finished LED semiconductor is braided to obtain an LED light bar;

[0010] The LED light bar is subjected to quality detection to obtain a quality inspection result, wherein the quality detection includes optical detection, electrical detection and mechanical detection;

[0011] A unique identifier corresponding to the LED light bar passing the quality detection is generated;

[0012] According to the unique identifier and the corresponding quality inspection result, the LED light bar is subjected to warehouse processing to obtain an LED product.

[0013] Preferably, before the unique identifier of the finished LED semiconductor is used to obtain the braiding scheme, the braiding scheme includes a braiding method and a braiding position, and the following steps are further included:

[0014] The initial LED semiconductor and the support are subjected to preliminary processing to obtain a first LED semiconductor, wherein the first LED semiconductor is placed at a designated position of the support, the surface of the support has a unique identifier set by laser coding, and the preliminary processing includes die expansion processing and dehumidification processing of the support;

[0015] The first LED semiconductor is subjected to die bonding according to a die bonding strategy to obtain a second LED semiconductor, wherein the die bonding strategy is obtained based on the unique identifier;

[0016] According to the die bonding strategy, a die bonding detection target of the second LED semiconductor is obtained, wherein the die bonding strategy includes a die bonding method and a die bonding control parameter, and different die bonding methods correspond to different die bonding detection targets;

[0017] A first detection image including the second LED semiconductor is obtained;

[0018] According to the die bonding detection target and the first detection image, a die bonding detection result is obtained, wherein when the die bonding method is laser die bonding, the die bonding detection result includes a laser spot size deviation value, a laser spot irregularity and a laser spot size consistency, and when the die bonding method is adhesive die bonding, the die bonding detection result includes a glue drop size deviation and a glue drop distribution deviation;

[0019] According to the die bonding strategy, a preset die bonding condition is obtained;

[0020] According to the die bonding detection result, it is judged whether the second LED semiconductor meets the preset die bonding condition;

[0021] If yes, the second LED semiconductor is subjected to wire bonding according to the wire bonding strategy to obtain a third LED semiconductor;

[0022] If not, the crystal bonding control parameters are adjusted according to the crystal bonding detection result, and the first LED semiconductor is crystal bonded according to the crystal bonding strategy to obtain a second LED semiconductor;

[0023] In response to the third LED semiconductor satisfying a preset wire bonding condition, the third LED semiconductor is dispensing according to a dispensing strategy to obtain a target LED semiconductor, wherein the dispensing strategy is based on the unique identifier.

[0024] Preferably, the response to the third LED semiconductor satisfying a preset wire bonding condition, the third LED semiconductor is dispensing according to a dispensing strategy to obtain a target LED semiconductor, comprising:

[0025] A second detection image including the third LED semiconductor is obtained;

[0026] According to the second detection image, the actual wire bonding path and the actual wire bonding parameter are obtained;

[0027] According to the wire bonding strategy, the expected wire bonding path and the expected wire bonding parameter are obtained, wherein the wire bonding strategy includes wire bonding layout and wire bonding control parameter;

[0028] According to the actual wire bonding path and the expected wire bonding path, the wire bonding shape deviation is obtained;

[0029] According to the actual wire bonding parameter and the expected wire bonding parameter, the wire bonding parameter deviation is obtained;

[0030] According to the wire bonding shape deviation and the wire bonding parameter deviation, it is judged whether the third LED semiconductor satisfies the preset wire bonding condition;

[0031] If yes, the third LED semiconductor is dispensing according to the dispensing strategy to obtain a target LED semiconductor;

[0032] If not, the wire bonding control parameters are adjusted according to the wire bonding shape deviation and / or the wire bonding parameter deviation, and the second LED semiconductor is wire bonded according to the wire bonding strategy to obtain a third LED semiconductor in response to the second LED semiconductor satisfying a preset crystal bonding condition.

[0033] Preferably, after the response to the third LED semiconductor satisfying a preset wire bonding condition, the third LED semiconductor is dispensing according to a dispensing strategy to obtain a target LED semiconductor, the method further comprises:

[0034] in response to the target LED semiconductor satisfying a preset dispensing condition, performing a light splitting process on the target LED semiconductor according to a light splitting strategy to obtain an actual optical parameter of the target LED semiconductor, wherein the light splitting strategy is obtained based on the unique identifier, and the actual optical parameter includes a color temperature parameter, a light emitting wavelength, and a brightness parameter;

[0035] determining, according to the unique identifier, a target LED semiconductor and a corresponding expected optical parameter that belong to a same production batch;

[0036] screening, according to the expected optical parameter, a finished product LED semiconductor that satisfies a preset light splitting condition from the target LED semiconductor that belongs to the same production batch;

[0037] performing a post-processing on each of the finished product LED semiconductor to obtain an LED product.

[0038] Preferably, the response to the target LED semiconductor satisfying a preset dispensing condition, performing a light splitting process on the target LED semiconductor according to a light splitting strategy to obtain an actual optical parameter of the target LED semiconductor includes:

[0039] obtaining a third detection image including the target LED semiconductor;

[0040] obtaining an actual dispensing size and an actual dispensing distribution according to the third detection image;

[0041] obtaining an expected dispensing size and an expected dispensing distribution according to the dispensing strategy, wherein the dispensing strategy includes a dispensing control parameter and a dispensing distribution;

[0042] obtaining a dispensing size deviation according to the actual dispensing size and the expected dispensing size;

[0043] obtaining a dispensing distribution deviation according to the expected dispensing distribution and the actual dispensing distribution;

[0044] judging whether the target LED semiconductor satisfies a preset dispensing condition according to the dispensing distribution deviation and the dispensing size deviation;

[0045] if yes, performing a light splitting process on the target LED semiconductor according to a light splitting strategy to obtain an actual optical parameter of the target LED semiconductor;

[0046] if no, adjusting the dispensing control parameter according to the dispensing distribution deviation and / or the dispensing size deviation, and returning to the response to the third LED semiconductor satisfying a preset wire bonding condition, performing a dispensing on the third LED semiconductor according to a dispensing strategy to obtain a target LED semiconductor.

[0047] Preferably, the step of screening finished LED semiconductors that meet preset spectroscopic conditions from target LED semiconductors belonging to the same production batch according to the expected optical parameters includes:

[0048] Obtaining, based on the actual optical parameters, average values ​​of the actual optical parameters of target LED semiconductors belonging to the same production batch;

[0049] Obtaining an overall optical parameter deviation value according to the actual optical parameter mean value and the expected optical parameter;

[0050] Determining whether there is an overall deviation in target LED semiconductors belonging to the same production batch based on the overall optical parameter deviation value;

[0051] If there is an overall deviation, adjusting at least one of the die bonding strategy, the wire bonding strategy, and the glue dispensing strategy according to a preset overall deviation processing rule and the overall optical parameter deviation value;

[0052] If there is no overall deviation, obtaining a sample standard deviation of target LED semiconductors of the same production batch according to the actual optical parameter mean and the actual optical parameter;

[0053] determining, based on the sample standard deviation, whether there are abnormal LED semiconductors in the target LED semiconductors of the same production batch;

[0054] If there is an abnormal LED semiconductor, the abnormal LED semiconductor is processed according to the preset individual abnormality processing rules;

[0055] treating the target LED semiconductors other than the abnormal LED semiconductors as finished LED semiconductors;

[0056] If there are no abnormal LED semiconductors, all the target LED semiconductors are regarded as finished product LED semiconductors.

[0057] Preferably, if there is an overall deviation, adjusting at least one of the die bonding strategy, the wire bonding strategy, and the glue dispensing strategy according to a preset overall deviation processing rule and the overall optical parameter deviation value includes:

[0058] Acquire the overall optical parameter deviation value, wherein the overall optical parameter deviation value includes a brightness deviation value, a color temperature deviation value, and a light emission wavelength deviation value;

[0059] When the absolute value of the brightness deviation value is greater than the brightness deviation threshold, the wire bonding strategy is used as a solution to be adjusted;

[0060] determining a parameter to be adjusted and a corresponding parameter adjustment value of the wire bonding strategy according to the luminance deviation value, wherein the parameter to be adjusted of the wire bonding strategy comprises an ultrasonic vibration parameter and a bonding pressure parameter;

[0061] when the absolute value of the color temperature deviation value is greater than a color temperature deviation threshold value, taking the die bonding strategy as a scheme to be adjusted;

[0062] determining a parameter to be adjusted and a corresponding parameter adjustment value of the die bonding strategy according to the color temperature deviation value, wherein when the die bonding mode is a laser die bonding, the parameter to be adjusted of the die bonding strategy comprises a laser power, a laser time and a laser frequency, and when the die bonding mode is an adhesive die bonding, the parameter to be adjusted of the die bonding strategy comprises a die bonding temperature, a die bonding time and an adhesive ratio;

[0063] when the absolute value of the light-emitting wavelength deviation value is greater than a light-emitting wavelength deviation threshold value, taking the dispensing strategy as a scheme to be adjusted;

[0064] determining a parameter to be adjusted and a corresponding parameter adjustment value of the dispensing strategy according to the light-emitting wavelength deviation value, wherein the parameter to be adjusted of the dispensing strategy comprises a dispensing amount and a dispensing material ratio;

[0065] when the number of the schemes to be adjusted is greater than one, determining an adjustment order according to the luminance deviation value, the color temperature deviation value and the light-emitting wavelength deviation value after normalization processing;

[0066] adjusting the schemes to be adjusted in sequence according to the adjustment order and the parameter adjustment value.

[0067] Preferably, when there is an abnormal LED semiconductor, processing the abnormal LED semiconductor according to a preset individual abnormal processing rule, comprising:

[0068] obtaining a ratio of the number of the abnormal LED semiconductors to the total number of LED semiconductors in the production batch;

[0069] when the ratio is less than or equal to a preset ratio, rejecting the abnormal LED semiconductor;

[0070] when the ratio is greater than the preset ratio, obtaining an individual optical parameter deviation value of each abnormal LED semiconductor according to the expected optical parameter and the actual optical parameter;

[0071] statistically analyzing the individual optical parameter deviation value to determine a key optical deviation parameter of the abnormal LED semiconductor, wherein the key optical deviation parameter comprises one of a luminance parameter, a color temperature parameter and a light-emitting wavelength parameter;

[0072] comparing the first detection image, the second detection image and the third detection image of all the abnormal LED semiconductors and any finished LED semiconductor to obtain a key control deviation parameter, wherein the key control deviation parameter comprises one of die bonding control parameter, wire bonding control parameter and dispensing control parameter;

[0073] determining a to-be-adjusted scheme and corresponding adjustment parameter according to the key optical deviation parameter and the key control deviation parameter;

[0074] adjusting the to-be-adjusted scheme according to the adjustment parameter.

[0075] Preferably, the comparing the first detection image, the second detection image and the third detection image of all the abnormal LED semiconductors and any finished LED semiconductor to obtain a key control deviation parameter comprises:

[0076] preprocessing the first detection image, the second detection image and the third detection image of all the abnormal LED semiconductors to obtain a first detection image set, a second detection image set and a third detection image set respectively;

[0077] preprocessing the first detection image, the second detection image and the third detection image of any finished LED semiconductor to obtain a first target comparison image, a second target comparison image and a third target comparison image respectively;

[0078] comparing each image in the first detection image set with the first target comparison image to obtain a deviation die bonding feature of each image in the first detection image set;

[0079] comparing each image in the second detection image set with the second target comparison image to obtain a deviation wire bonding feature of each image in the second detection image set;

[0080] comparing each image in the third detection image set with the third target comparison image to obtain a deviation dispensing feature;

[0081] performing cluster analysis on the deviation die bonding feature, the deviation wire bonding feature and the deviation dispensing feature to obtain a first significant deviation feature;

[0082] performing correlation analysis on the first significant deviation feature and the key optical deviation parameter to obtain a second significant deviation feature;

[0083] determining the key control deviation parameter according to the second significant deviation feature.

[0084] In a second aspect, the embodiments of the present application provide an LED semiconductor production data traceability analysis system, which comprises: a processing pretreatment module for performing preliminary processing on an initial LED semiconductor and a support, a die bonding module for performing die bonding on the LED semiconductor according to a die bonding strategy, a welding module for performing welding on the LED semiconductor according to a wire bonding strategy, a dispensing module for performing dispensing on the LED semiconductor according to a dispensing strategy, a sensor module for monitoring and collecting key parameters in real time during LED production, a power module for supplying power to the system, and a controller for executing the LED semiconductor production data traceability analysis method of the first aspect.

[0085] In summary, the beneficial effects of the present application are as follows:

[0086] The LED semiconductor production data traceability analysis method and system provided by the embodiments of the present application, the method comprises: obtaining a coding scheme according to a unique identifier of a finished LED semiconductor, the coding scheme comprising a coding method and a coding position; performing coding processing on the finished LED semiconductor according to the coding scheme to obtain an LED light bar; performing quality detection on the LED light bar to obtain a quality inspection result, wherein the quality detection comprises optical detection, electrical detection and mechanical detection; generating a unique identifier corresponding to the LED light bar that passes the quality detection; performing warehouse storage processing on the LED light bar according to the unique identifier and the corresponding quality inspection result to obtain an LED product. The present application realizes accurate management of each finished LED semiconductor through a unique identifier, ensures the quality and consistency of the LED semiconductor in the entire post-processing process, and realizes automation and standardization in the coding process through the coding scheme corresponding to the unique identifier, thereby avoiding errors caused by manual operation and ensuring the accuracy of the LED semiconductor in the coding position and method. Subsequent optical, electrical and mechanical detection comprehensively evaluates the performance of the LED light bar, ensures that the quality meets the requirements, and generates a new unique identifier for the light bar that passes the quality inspection, which is convenient for tracking and management, so that the product information is accurately recorded in the warehouse storage link, avoiding misplacement or quality difference in the storage and transportation process. In addition, strict quality inspection and warehouse storage environment control also effectively reduce the performance degradation of the LED light bar due to environmental factors, improve the consistency and reliability of the product, and thus ensure the quality stability and traceability of the final LED product. BRIEF DESCRIPTION OF DRAWINGS

[0087] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments of the present application will be briefly introduced as follows, and for those skilled in the art, other drawings can also be obtained without creative labor on the premise of these drawings, and these are within the protection scope of the present application.

[0088] Figure 1is a flowchart of an LED semiconductor production data trace analysis method according to an embodiment of the present application.

[0089] Figure 2 is another flowchart of an LED semiconductor production data trace analysis method according to an embodiment of the present application.

[0090] Figure 3 is a structural diagram of an LED semiconductor production data trace analysis system according to an embodiment of the present application. DETAILED DESCRIPTION

[0091] The features and exemplary embodiments of the various aspects of the present application will be described in detail below with reference to the drawings. To make the purpose, technical solutions and advantages of the present application more clear, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are configured only to explain the present application and are not configured to limit the present application. The present application can be implemented without some of the specific details by those skilled in the art. The following description of the embodiments is merely provided to provide a better understanding of the present application by showing examples of the present application.

[0092] It should be noted that, in this document, relational terms such as first and second and the like can be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without more limitations, an element preceded by "comprises... a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or apparatus that comprises the recited element.

[0093] It should be noted that all actions of acquiring signals, information or data in the present application are performed in compliance with the corresponding data protection regulations and policies of the place of residence and with the authorization given by the owner of the corresponding device.

[0094] Embodiment 1

[0095] Please refer to Figure 1 The embodiment of the present application provides an LED semiconductor production data trace analysis method, which comprises the following steps.

[0096] S1, performing pre-processing on an initial LED semiconductor and a support to obtain a first LED semiconductor, wherein the first LED semiconductor is placed at a designated position of the support, a surface of the support has a unique identifier set by laser coding, and the pre-processing includes wafer expansion processing and dehumidification processing of the support;

[0097] Specifically, in the LED semiconductor production data traceability analysis system, first, pre-processing is performed on the initial LED semiconductor and the support to obtain the first LED semiconductor. Wafer expansion processing is an important preprocessing step for changing the crystal structure of the LED chip to improve its performance and stability. In this process, the LED chip is exposed to specific environmental conditions by controlling temperature, pressure and atmosphere to promote the growth and arrangement of the crystal, thereby optimizing the performance of the LED. Dehumidification processing is to reduce the influence of humidity on the LED semiconductor during production. In this step, the surface of the support and the LED chip is treated to ensure that there is no quality problem caused by excessive humidity in the subsequent die bonding, soldering and dispensing processes.

[0098] The surface of the support is provided with a unique identifier by laser coding. This unique identifier can be used as an identity code for the LED semiconductor for subsequent data traceability and production process management.

[0099] S2, die bonding the first LED semiconductor according to a die bonding strategy to obtain a second LED semiconductor, wherein the die bonding strategy is obtained based on the unique identifier;

[0100] Specifically, the die bonding strategy is the specific operation steps and parameter settings of die bonding, including die bonding methods (such as silver glue die bonding, laser die bonding, etc.) and die bonding control parameters (such as temperature, pressure, etc.). According to the unique identifier, the specific operation steps and parameter settings of die bonding are determined, and the die bonding strategy is obtained through the unique identifier, which realizes the individual management and customized operation of each LED chip, improves the flexibility and efficiency of the production process; according to the specific die bonding strategy, the die bonding operation can ensure the die bonding quality and stability, and improve the reliability and performance consistency of the LED product.

[0101] S3, in response to the second LED semiconductor satisfying a preset die bonding condition, soldering the second LED semiconductor according to a wire bonding strategy to obtain a third LED semiconductor, wherein the wire bonding strategy is obtained based on the unique identifier;

[0102] Specifically, the second LED semiconductor is a semiconductor after die bonding. Before the next process, i.e., wire bonding, it needs to be detected to determine whether it meets the preset quality condition, i.e., the preset die bonding condition. For example, the die bonding process needs to meet specific parameter requirements, such as die bonding temperature, time, and pressure, which ensure that the LED semiconductor is firmly adhered to the support. Different conditions can be set for judgment according to different die bonding strategies.

[0103] After checking that the die bonding meets the condition, the wire bonding strategy is obtained by scanning the unique identifier of the second LED semiconductor. The wire bonding strategy refers to the specific operation steps and parameter settings of wire bonding, including the wire bonding path and wire bonding parameters (such as temperature, pressure, etc.). Thus, the specific operation steps and parameter settings of wire bonding are determined, and the wire bonding operation is performed to connect the wire bonding of the second LED semiconductor with the external circuit.

[0104] The wire bonding strategy is obtained through the unique identifier, which realizes individualized wire bonding operation for each LED chip and improves the flexibility and efficiency of the production process.

[0105] Preferably, the wire bonding of the second LED semiconductor according to the wire bonding strategy to obtain a third LED semiconductor in response to the second LED semiconductor meeting the preset die bonding condition comprises:

[0106] S31, obtaining a die bonding detection target of the second LED semiconductor according to the die bonding strategy, wherein the die bonding strategy includes a die bonding method and a die bonding control parameter, and different die bonding methods correspond to different die bonding detection targets;

[0107] Specifically, the system determines the detection target of the die bonding quality according to the die bonding method (laser die bonding or adhesive die bonding). Different die bonding methods may have different detection requirements. For example, laser die bonding may need to detect the shape, size, and consistency of the welding point, while adhesive die bonding may need to detect the uniformity and coverage of the adhesive.

[0108] S32, obtaining a first detection image including the second LED semiconductor;

[0109] Specifically, an appropriate image acquisition device, such as a camera or a microscope, is used to obtain an overall image including the second LED semiconductor. This image can show the die bonding state between the LED chip and the support, including possible cracks, bubbles, and other problems.

[0110] S33, obtaining a die bonding detection result according to the die bonding detection target and the first detection image, wherein when the die bonding mode is the laser die bonding, the die bonding detection result comprises a laser spot size deviation value, a laser spot irregularity and a laser spot size consistency, and when the die bonding mode is the adhesive die bonding, the die bonding detection result comprises a glue drop size deviation and a glue drop distribution deviation;

[0111] Specifically, by analyzing the first detection image, specific detection results in the die bonding process are obtained, such as a laser spot size deviation value, a laser spot irregularity and a laser spot size consistency, or a glue drop size deviation and a glue drop distribution deviation. By image analysis on the first detection image, features related to the die bonding quality are extracted, if it is laser die bonding, the features of the laser spot size and shape are extracted, and the deviation value and consistency are calculated. If it is adhesive die bonding, the size and distribution features of the glue drop are extracted, and the deviation value and uniformity are calculated.

[0112] Through image analysis and feature extraction, specific detection results in the die bonding process can be accurately obtained, and the detection accuracy is improved. Through specific detection results, problems existing in the die bonding process can be found in time, and effective adjustment can be made.

[0113] S34, obtaining the preset die bonding condition according to the die bonding strategy;

[0114] Specifically, the preset die bonding condition sets specific quality requirements in the die bonding process. By comparing with the detection result, it is judged whether the die bonding quality is qualified. According to the die bonding strategy, the quality control standard in the current die bonding process is obtained from the database, including the laser spot size range and consistency requirement of laser die bonding, the glue drop uniformity and coverage range of adhesive die bonding, etc.

[0115] S35, judging whether the second LED semiconductor satisfies the preset die bonding condition according to the die bonding detection result;

[0116] Specifically, the die bonding detection result is compared with the preset die bonding condition to judge whether the quality in the die bonding process is qualified, so as to ensure that the product meets the quality requirements. The preset die bonding condition sets specific judgment standards, such as that the laser spot size deviation value is not more than ±10%, the glue drop size deviation is not more than ±5%, etc. According to the comparison result, it is judged whether the die bonding quality of the second LED semiconductor is qualified.

[0117] S36, if yes, wire bonding is performed on the second LED semiconductor according to the wire bonding strategy to obtain a third LED semiconductor;

[0118] Specifically, under the premise that the die bonding quality is qualified, wire bonding operation is performed, and wire bonding operation is performed through the wire bonding strategy to ensure the quality and reliability of the wire bonding process, and a third LED semiconductor is obtained.

[0119] S37, if not satisfied, adjusting the die bonding control parameter according to the die bonding detection result, and returning to the die bonding of the first LED semiconductor according to the die bonding strategy to obtain a second LED semiconductor.

[0120] Specifically, in the case of unqualified die bonding quality, the die bonding control parameter is adjusted according to the detection result to optimize the die bonding process. By adjusting the die bonding control parameter, the quality problem in the die bonding process is improved to ensure the qualified die bonding quality.

[0121] The specific process of adjustment includes analyzing specific problems in the die bonding process, such as solder size deviation, uneven glue drops, etc., according to the die bonding detection result. According to the analysis result, the die bonding control parameter is adjusted, such as increasing the laser power, adjusting the adhesive ratio, etc. According to the adjusted die bonding control parameter, the die bonding operation is performed again to obtain a new second LED semiconductor. The quality of the second LED semiconductor after re-die bonding is detected to ensure that the die bonding quality meets the preset conditions.

[0122] S4, in response to the third LED semiconductor satisfying the preset wire bonding condition, dispensing the third LED semiconductor according to the dispensing strategy to obtain a target LED semiconductor, wherein the dispensing strategy is obtained based on the unique identifier.

[0123] Specifically, before dispensing, the third LED semiconductor after welding is first detected to determine whether the third LED semiconductor satisfies the preset wire bonding condition. The preset wire bonding condition can be whether the firmness of the solder joint, the welding precision, etc. meet the specific parameter requirements to ensure the wire bonding quality.

[0124] Subsequently, the third LED semiconductor after wire bonding is dispensed to encapsulate and protect the LED chip, prevent the influence of the external environment, and ensure its long-term stable operation. Based on the unique identifier, the dispensing strategy suitable for the current third LED semiconductor is obtained from the database. It is ensured that the dispensing strategy matches the specific conditions of the LED semiconductor after wire bonding. The dispensing strategy includes specific operation steps and parameter settings for dispensing the LED chip, which can include adhesive type and dispensing control parameter. The specific operation steps and parameter settings for dispensing are determined through the dispensing strategy to perform the dispensing operation.

[0125] Preferably, the response to the third LED semiconductor satisfying the preset wire bonding condition, dispensing the third LED semiconductor according to the dispensing strategy to obtain a target LED semiconductor, includes:

[0126] S41, obtaining a second detection image including the third LED semiconductor;

[0127] Specifically, a second detection image containing the third LED semiconductor is obtained by a corresponding detection device. The detection device usually uses a high-resolution camera or other imaging device to capture the image of the LED device.

[0128] S42, according to the second detection image, obtaining an actual wire bonding path and an actual wire bonding parameter;

[0129] Specifically, based on the second detection image, the path and parameters of the actual wire bonding are identified and extracted by image processing algorithms or computer vision techniques. These parameters may include the length, shape, width, etc. of the wire bonding. Through image analysis and parameter extraction, the actual path and parameters during wire bonding can be accurately obtained, improving the detection accuracy.

[0130] S43, according to the wire bonding strategy, obtaining an expected wire bonding path and an expected wire bonding parameter, wherein the wire bonding strategy includes a wire bonding layout and a wire bonding control parameter;

[0131] Specifically, according to the wire bonding strategy, the expected wire bonding path, such as the specific path of the wire bonding between the LED chip and the support, is determined, and the expected wire bonding parameters, such as the length, shape, width, etc. of the wire bonding, are set. Through the preset wire bonding path and parameters, the standardization of the wire bonding process is ensured, and the consistency and quality of the product are improved. The expected path and parameter provide a specific comparison standard, which helps accurate judgment of the subsequent detection results.

[0132] S44, according to the actual wire bonding path and the expected wire bonding path, obtaining a wire bonding shape deviation;

[0133] Specifically, by comparing the actual wire bonding path and the expected wire bonding path, the wire bonding shape deviation is obtained, which provides a basis for quality detection. By comparing the actual wire bonding path with the expected wire bonding path, the deviation between them is calculated, and the shape of the actual and expected wire bonding paths is compared to determine the deviation position and deviation amount. The deviation value, such as deviation distance, deviation angle, etc. can be calculated by algorithm. Through the calculation of the wire bonding shape deviation, the deviation of the wire bonding path can be accurately judged.

[0134] S45, according to the actual wire bonding parameter and the expected wire bonding parameter, obtaining a wire bonding parameter deviation;

[0135] Specifically, by comparing the actual wire bonding parameter and the expected wire bonding parameter, the wire bonding parameter deviation is obtained, which provides a basis for quality detection. By comparing the actual and expected wire bonding parameters, such as length, angle, etc., the deviation value is determined. According to the parameter deviation, the wire bonding control parameter can be adjusted in time, the wire bonding process can be optimized, and the product quality can be improved.

[0136] S46, according to the wire bonding shape deviation and the wire bonding parameter deviation, judging whether the third LED semiconductor meets a preset wire bonding condition;

[0137] Specifically, the wire shape deviation and the parameter deviation are compared with the preset wire condition, and specific judgment criteria can be set, such as a shape deviation of not more than ±5% and a parameter deviation of not more than ±3%. The specific judgment criteria can be set according to different wire strategies.

[0138] Subsequently, it is judged whether the wire quality of the third LED semiconductor is qualified according to the comparison result. Through the comparison of the shape deviation and the parameter deviation, it can be accurately judged whether the wire quality meets the preset condition, and the accuracy of quality control is improved.

[0139] S47, if yes, dispensing the third LED semiconductor according to the dispensing strategy to obtain a target LED semiconductor;

[0140] Specifically, under the premise that the wire quality is qualified, dispensing is performed according to the dispensing strategy to ensure the packaging quality of the LED chip.

[0141] S48, if no, adjusting the wire control parameter according to the wire shape deviation and / or the wire parameter deviation, and returning to the step of performing wire bonding on the second LED semiconductor according to the wire strategy to obtain the third LED semiconductor if the second LED semiconductor meets the preset die bonding condition.

[0142] Specifically, in the case that the wire quality is unqualified, the wire control parameter is adjusted according to the wire shape deviation and / or the wire parameter deviation to optimize the wire bonding process. The specific problems in the wire bonding process can be analyzed according to the wire shape deviation and the wire parameter deviation, and the wire control parameter is adjusted according to the analysis result, such as increasing the wire bonding temperature or adjusting the wire bonding pressure.

[0143] After the adjustment is completed, the wire bonding operation is performed again according to the adjusted wire control parameter to obtain a new third LED semiconductor, and quality detection is performed on the third LED semiconductor after the wire bonding to ensure that the wire quality meets the preset condition. Through adjustment and optimization, the unqualified products in the wire bonding process are reduced, and the production qualification rate and efficiency are improved.

[0144] Preferably, referring to Figure 2 After the step of dispensing the third LED semiconductor according to the dispensing strategy to obtain the target LED semiconductor if the third LED semiconductor meets the preset wire bonding condition, the method further comprises:

[0145] S5, performing light splitting treatment on the target LED semiconductor according to a light splitting strategy to obtain actual optical parameters of the target LED semiconductor if the target LED semiconductor meets a preset dispensing condition, wherein the light splitting strategy is obtained based on the unique identifier, and the actual optical parameters include a color temperature parameter, a light emitting wavelength, and a brightness parameter.

[0146] Specifically, the target LED semiconductor after dispensing also needs to be detected before spectrometry, and it is determined that the target LED semiconductor meets the preset dispensing condition to ensure the quality of the third LED semiconductor. The preset dispensing condition can be a specific parameter requirement that needs to be met in the dispensing process, such as dispensing uniformity, dispensing position accuracy, etc. For example, the dispensing uniformity needs to reach more than 90%, and the dispensing position deviation is not more than 0.1 mm.

[0147] Subsequently, based on the unique identifier, the spectrometry strategy suitable for the current target LED semiconductor is obtained from the database, ensuring that the spectrometry strategy matches the specific conditions of the LED semiconductor after dispensing. The spectrometry strategy includes spectrometry equipment settings, measurement parameters, etc., to ensure the accuracy of the spectrometry result. Through spectrometry processing, the actual optical parameters of each target LED semiconductor, i.e. the optical characteristics of the LED semiconductor, including color temperature parameters, light wavelength and brightness parameters, can be obtained. Through spectrometry processing, the actual optical parameters of each target LED semiconductor are obtained to ensure that its optical performance meets the design requirements.

[0148] Preferably, in response to the target LED semiconductor meeting the preset dispensing condition, the target LED semiconductor is subjected to spectrometry processing according to the spectrometry strategy to obtain the actual optical parameters of the target LED semiconductor, including:

[0149] S51, obtaining a third detection image including the target LED semiconductor;

[0150] Specifically, similar to steps S31 and S41, the image of the target LED semiconductor is captured by a camera or other imaging device.

[0151] S52, obtaining actual dispensing size and actual dispensing distribution according to the third detection image:

[0152] Specifically, by analyzing the third detection image, the actual dispensing parameters are extracted for comparison with the expected dispensing parameters. The actual dispensing parameters include the actual dispensing size and the actual dispensing distribution. The third detection image is analyzed using an image processing algorithm to extract the size and distribution information of the actual dispensing, thereby providing quantitative data of the actual dispensing situation, which provides a basis for subsequent comparison and evaluation.

[0153] S53, obtaining expected dispensing size and expected dispensing distribution according to the dispensing strategy, wherein the dispensing strategy includes dispensing control parameters and dispensing distribution;

[0154] According to the dispensing strategy, the expected dispensing size and dispensing distribution are obtained. The dispensing strategy includes dispensing control parameters, which are determined by production requirements and quality standards, mainly including glue amount, dispensing frequency and dispensing speed. Glue amount refers to the amount of glue required per unit area or length, usually in units of milliliters per square centimeter or milliliters per centimeter. The determination of glue amount can be determined according to product requirements and the viscosity of glue, to ensure that enough glue is applied to the workpiece, so as to achieve the required bonding strength. Dispensing frequency refers to the number of times the dispensing head sprays glue per minute, usually expressed in dots per minute (DPM). The choice of dispensing frequency depends on factors such as the properties of the glue, the size and shape of the workpiece, and the production efficiency requirements. Dispensing speed refers to the speed at which the dispensing head moves during the dispensing process, usually in units of millimeters per second or inches per second. The choice of dispensing speed needs to consider factors such as the flowability of the glue, the surface characteristics of the workpiece, and the speed of the production line, to ensure that the glue is uniformly applied to the surface of the workpiece.

[0155] Subsequently, the expected dispensing size and dispensing distribution are calculated to determine the expected dispensing quality. Accurate setting of these parameters helps to ensure that the dispensing quality in the production process meets the requirements, improving the consistency and quality stability of the product.

[0156] S54, according to the actual dispensing size and the expected dispensing size, obtaining a dispensing size deviation;

[0157] Specifically, the dispensing size deviation is the difference between the actual dispensing size and the expected dispensing size. This value can be calculated by subtracting the expected dispensing size from the actual dispensing size. If the actual dispensing size is greater than the expected dispensing size, the deviation value is positive; if the actual dispensing size is less than the expected dispensing size, the deviation value is negative. According to the dispensing deviation value, the difference between the actual dispensing quality and the expected dispensing quality can be evaluated.

[0158] S55, according to the expected dispensing distribution and the actual dispensing distribution, obtaining a dispensing distribution deviation;

[0159] Specifically, the expected dispensing distribution is the ideal dispensing distribution calculated according to the target dispensing parameters. The expected dispensing distribution is determined according to product design and dispensing requirements, usually taking into account factors such as the shape of the workpiece surface, the flowability of the glue, and the working principle of the dispensing equipment. The actual dispensing distribution is the dispensing distribution observed in the production process, i.e. the distribution of glue actually applied to the workpiece surface. The actual dispensing distribution may be influenced by various factors, such as the accuracy of the dispensing equipment, the flowability of the glue, etc.; the dispensing distribution deviation is the difference between the actual dispensing distribution and the expected dispensing distribution, which can be obtained by similarity calculation.

[0160] S56, judging whether the target LED semiconductor satisfies a preset dispensing condition according to the dispensing distribution deviation and the dispensing size deviation;

[0161] Specifically, whether the target LED semiconductor satisfies a preset dispensing condition is judged according to the dispensing distribution deviation and the dispensing size deviation obtained in the foregoing steps, which can also be set based on a dispensing strategy and actual conditions;

[0162] S57, if yes, performing light splitting treatment on the target LED semiconductor according to a light splitting strategy to obtain actual optical parameters of the target LED semiconductor;

[0163] When the preset dispensing condition is satisfied, light splitting treatment is performed to obtain actual optical parameters of the target LED semiconductor;

[0164] S58, if no, adjusting the dispensing control parameters according to the dispensing distribution deviation and / or the dispensing size deviation, and returning to the step of performing dispensing on the third LED semiconductor according to a dispensing strategy to obtain the target LED semiconductor when the third LED semiconductor satisfies a preset wire bonding condition.

[0165] When the preset dispensing condition is not satisfied, the dispensing distribution deviation and / or the dispensing size deviation is attributed to determine the dispensing control parameters associated with the dispensing distribution deviation and / or the dispensing size deviation, and the corresponding dispensing control parameters are adjusted according to the values of the deviations, and the dispensing treatment is performed again according to the adjusted parameters.

[0166] S6, determining the target LED semiconductor and the corresponding expected optical parameters belonging to the same production batch according to the unique identifier;

[0167] Specifically, the production batch information to which the target LED semiconductor belongs is obtained from a database according to the unique identifier of the target LED semiconductor, and the expected optical parameters of the LED semiconductor of the batch, such as color temperature, light wavelength and brightness, are obtained from the database according to the production batch information. Precise acquisition and recording of the expected optical parameters of each production batch facilitate subsequent data analysis and problem tracing.

[0168] S7, screening finished product LED semiconductors satisfying a preset light splitting condition from the target LED semiconductors belonging to the same production batch according to the expected optical parameters;

[0169] Specifically, the preset light splitting condition, i.e., the optical parameter requirement for screening finished product LED semiconductors, can be a color temperature range, a light wavelength range and a brightness range obtained through the expected optical parameters, and the finished product LED semiconductors meeting the requirements are screened out. The target LED semiconductor meeting the preset light splitting condition is marked as a finished product and classified.

[0170] Preferably, the target LED semiconductors belonging to the same production batch that meet the preset light splitting conditions are screened according to the expected optical parameters, including:

[0171] S71, obtaining an actual optical parameter mean value of the target LED semiconductors belonging to the same production batch according to the actual optical parameters;

[0172] Specifically, the target LED semiconductors belonging to the same production batch are a group of LED semiconductors manufactured in the same production cycle, having the same production conditions and processes, and the actual optical parameter mean value is obtained by averaging the actual optical parameters of the target LED semiconductors belonging to the same production batch. The actual optical parameter mean value can reflect the overall optical performance of the entire batch of products and provide a basis for judging the quality of the batch of products.

[0173] S72, obtaining an overall optical parameter deviation value according to the actual optical parameter mean value and the expected optical parameters;

[0174] Specifically, the overall optical parameter deviation value is calculated by comparing the actual optical parameter mean value with the expected optical parameters, so as to judge whether the product meets the expectation. The calculation of the overall optical parameter deviation value can reveal the overall deviation in the production process and provide a basis for subsequent adjustment.

[0175] S73, judging whether there is an overall deviation in the target LED semiconductors belonging to the same production batch according to the overall optical parameter deviation value;

[0176] Specifically, the actual optical parameter mean value is compared with the expected optical parameters. For example, the deviation value of the color temperature parameter is calculated as follows: color temperature deviation = color temperature mean value - expected color temperature. The deviation value of other optical parameters is calculated in a similar manner. Through the calculation of the overall optical parameter deviation value, the overall deviation in the production process can be accurately identified, and potential problems can be found.

[0177] S74, if there is an overall deviation, adjusting at least one of the die bonding strategy, the wire bonding strategy and the dispensing strategy according to a preset overall deviation processing rule and the overall optical parameter deviation value;

[0178] Specifically, if the overall optical parameter deviation of the target LED semiconductor in the same production batch exceeds the preset standard, it indicates that there may be systematic problems in the production process, such as improper process parameter setting, raw material quality problems, etc., resulting in consistent deviation of the entire batch of LED semiconductor products. In the case of overall deviation, according to the preset processing rule, the production process is adjusted to improve product quality. For example, if the color temperature deviation in the overall optical parameter deviation value is greater than the corresponding threshold value, the laser power, time and frequency of laser die bonding, or the temperature, time and adhesive ratio of adhesive die bonding can be adjusted. If the brightness deviation is greater than the corresponding threshold value, the ultrasonic vibration parameters, bonding pressure, temperature, workbench moving speed and welding time of the wire bonding can be adjusted. If the light-emitting wavelength deviation is greater than the corresponding threshold value, the dispensing amount and dispensing material ratio can be adjusted.

[0179] Preferably, if there is an overall deviation, at least one of the die bonding strategy, the wire bonding strategy and the dispensing strategy is adjusted according to the preset overall deviation processing rule and the overall optical parameter deviation value, including:

[0180] S741, obtaining the overall optical parameter deviation value, wherein the overall optical parameter deviation value includes a brightness deviation value, a color temperature deviation value and a light-emitting wavelength deviation value;

[0181] Specifically, the overall optical parameter deviation value refers to the difference between the mean value of the overall optical parameters (brightness, color temperature, light-emitting wavelength) in a batch of LED semiconductors and the expected value, resulting in the overall brightness deviation value, color temperature deviation value and light-emitting wavelength deviation value.

[0182] S742, when the absolute value of the brightness deviation value is greater than the brightness deviation threshold value, the wire bonding strategy is taken as the adjustment scheme;

[0183] Specifically, the precision of the wire directly affects the conduction efficiency of the current. If the wire position is not accurate or the connection is poor, it may cause uneven distribution of the current, affecting the current density of the LED chip, and further affecting its luminous efficiency and brightness. Moreover, the selection of wire material and process will affect its resistance value. If the resistance is high, part of the electric energy will be lost in the wire, resulting in a decrease in the current transmitted to the chip, thereby affecting the brightness. Therefore, when the absolute value of the brightness deviation value is greater than the brightness deviation threshold value, the wire bonding strategy is taken as the adjustment scheme;

[0184] S743, determining the adjustment parameter and the corresponding parameter adjustment value of the wire bonding strategy according to the brightness deviation value, wherein the adjustment parameter of the wire bonding strategy includes the ultrasonic vibration parameter and the bonding pressure parameter;

[0185] Specifically, according to the brightness deviation value, the wire bonding strategy parameter to be adjusted is determined. The wire bonding strategy parameter to be adjusted includes ultrasonic vibration parameter and bonding pressure parameter. These parameters have a direct impact on the wire bonding quality and the electrical performance of the LED. The ultrasonic vibration parameter affects the frequency and amplitude of ultrasonic vibration during wire bonding, thereby affecting the firmness and conductivity of the wire bonding. The bonding pressure parameter affects the mechanical pressure applied during wire bonding, thereby affecting the contact area and conductivity of the wire bonding. According to the size and direction (positive deviation or negative deviation) of the brightness deviation value, the adjustment direction (increasing or decreasing the ultrasonic vibration parameter and / or the bonding pressure parameter) is determined. The adjustment amplitude can be determined according to an empirical formula or a pre-established parameter adjustment table, and the determined adjustment value is input into the control system of the wire bonding equipment to adjust the ultrasonic vibration parameter and the bonding pressure parameter during wire bonding. After adjustment, trial production is first carried out, and the brightness of the adjusted LED is detected. If the brightness reaches the expected value, the parameter adjustment is successful; otherwise, further parameter adjustment is continued according to the newly measured brightness deviation value.

[0186] S744、when the absolute value of the color temperature deviation value is greater than the color temperature deviation threshold value, the die bonding strategy is taken as a to-be-adjusted scheme;

[0187] Specifically, the thermal conductivity of the die bonding material affects the heat dissipation efficiency of the LED chip. Poor heat dissipation can cause the chip temperature to rise, thereby changing the light-emitting efficiency and spectral characteristics of the LED, thereby affecting the color temperature. Adhesives of different compositions can have different effects on the light output and color temperature of the LED chip. For example, some adhesives may introduce stress or chemical changes during curing, thereby changing the optical properties of the chip. Similarly, temperature changes during the die bonding process can affect the difference in the coefficient of thermal expansion between the chip and the substrate, which can cause the generation of micro-stress, thereby affecting the light output and color temperature of the LED. Therefore, when the absolute value of the color temperature deviation value is greater than the color temperature deviation threshold value, the die bonding strategy is taken as a to-be-adjusted scheme;

[0188] S745、according to the color temperature deviation value, the to-be-adjusted parameter of the die bonding strategy and the corresponding parameter adjustment value are determined, wherein when the die bonding method is laser die bonding, the to-be-adjusted parameter of the die bonding strategy includes laser power, laser time and laser frequency, and when the die bonding method is adhesive die bonding, the to-be-adjusted parameter of the die bonding strategy includes die bonding temperature, die bonding time and adhesive ratio;

[0189] Specifically, according to the color temperature deviation value, the crystal fixed strategy parameter to be adjusted is determined. The crystal fixed strategy parameter to be adjusted depends on the crystal fixed method adopted, which can be laser crystal fixed or adhesive crystal fixed. When the crystal fixed method is laser crystal fixed, the crystal fixed strategy parameter to be adjusted includes laser power, laser time and laser frequency. Laser power affects the energy output of laser in the process of laser crystal fixed. Too large or too small power can affect the color temperature. Laser time affects the length of time that laser acts on the LED chip. Too long or too short time can lead to color temperature deviation. Laser frequency affects the pulse frequency of laser, which further affects the crystal fixed effect and color temperature.

[0190] When the crystal fixed method is adhesive crystal fixed, the crystal fixed strategy parameter to be adjusted includes crystal fixed temperature, crystal fixed time and adhesive ratio. Crystal fixed temperature affects the solidification process of adhesive. Too high or too low temperature can affect the optical properties and color temperature of the LED chip. Crystal fixed time affects the time of adhesive solidification. Too long or too short time can affect the color temperature. Different components of adhesive have different effects on the light output and color temperature of the LED chip. Adjusting the component ratio of adhesive can optimize the color temperature.

[0191] Similarly, according to the size and direction (positive deviation or negative deviation) of the color temperature deviation value, the adjustment direction of increasing or decreasing laser power, laser time, laser frequency, etc. is determined. The adjustment amplitude can be determined according to the empirical formula or the pre-established parameter adjustment table. Then trial production is carried out, and the adjusted LED color temperature is detected. If the color temperature reaches the expected value, the parameter adjustment is successful. Otherwise, further parameter adjustment is carried out according to the newly measured color temperature deviation value.

[0192] S746、when the absolute value of the light emitting wavelength deviation value is greater than the light emitting wavelength deviation threshold value, the dispensing strategy is taken as the adjustment scheme to be adjusted;

[0193] Specifically, the refractive index of dispensing material directly affects the propagation path of light. If the refractive index of the material is not uniform, it can cause scattering and dispersion of light, which further affects the light emitting wavelength of the LED. If the glue distribution is not uniform or the thickness is inconsistent in the dispensing process, it can cause the propagation path of light to be different at different positions, which further affects the overall light emitting wavelength of the LED.

[0194] S747、according to the light emitting wavelength deviation value, the dispensing strategy parameter to be adjusted and the corresponding parameter adjustment value are determined, wherein the dispensing strategy parameter to be adjusted includes dispensing amount and dispensing material ratio;

[0195] Specifically, the light emitting wavelength deviation value reflects the difference between the actual LED light emitting wavelength and the expected wavelength. The dispensing amount affects the thickness and uniformity of the glue layer, which further affects the propagation path and wavelength of light. The refractive index and optical properties of different materials affect the wavelength of light. Adjusting the ratio of dispensing materials can optimize the light emitting wavelength.

[0196] Similarly, according to the size and direction (positive or negative deviation) of the light-emitting wavelength deviation value, the adjustment direction (increasing or decreasing the dispensing amount, or adjusting the dispensing material ratio) is determined. The adjustment amplitude can be determined according to an empirical formula or a pre-established parameter adjustment table. After adjustment, trial production is carried out, and the adjusted LED light-emitting wavelength is detected. If the light-emitting wavelength reaches the expected value, the parameter adjustment is successful; otherwise, further parameter adjustment is continued according to the newly measured light-emitting wavelength deviation value.

[0197] S748、When the number of schemes to be adjusted is greater than one, according to the normalized brightness deviation value, the normalized color temperature deviation value and the normalized light-emitting wavelength deviation value, the adjustment order is determined;

[0198] Specifically, since the dimensions and numerical ranges of brightness, color temperature and light-emitting wavelength are different, it is necessary to normalize these deviation values so that they can be compared under the same standard. According to the size of the normalized deviation value, the adjustment order is determined. The larger the deviation value, the higher the priority of adjustment. For example, if the normalized brightness deviation value is the largest, the wire bonding strategy related to brightness is adjusted first;

[0199] S749、According to the adjustment order and the parameter adjustment value, the schemes to be adjusted are adjusted in turn.

[0200] Specifically, from the previous steps, the parameter adjustment values of each scheme have been determined. These adjustment values are calculated according to the specific deviation value. According to the determined adjustment order, the schemes to be adjusted are adjusted in turn. After each parameter adjustment, trial production and detection are carried out to ensure that each adjustment step effectively reduces the deviation of the optical parameters and finally achieves the expected optical performance. The data in all adjustment processes are recorded for future optimization and reference.

[0201] S75、If there is no overall deviation, according to the actual optical parameter mean value and the actual optical parameter, the sample standard deviation of the target LED semiconductor of the same production batch is obtained;

[0202] Specifically, according to the actual optical parameter and the mean value, the sample standard deviation of each target LED semiconductor in the batch is calculated. The sample standard deviation is a statistical index that measures the dispersion degree of a group of data. It represents the average distance of data points around the mean value. The larger the standard deviation, the greater the dispersion degree of data; the smaller the standard deviation, the more concentrated the data.

[0203] S76、According to the sample standard deviation, it is judged whether there is an abnormal LED semiconductor in the target LED semiconductor of the same production batch;

[0204] Specifically, the Z-Score can be used to quantify the degree of deviation of each LED semiconductor's optical parameters from the sample mean. Calculating the Z-Score is a well-known technique and will not be detailed here. Based on the calculated Z-Score, abnormal LED semiconductors are identified. Typically, an outlier is identified when the absolute value of the Z-Score exceeds a certain threshold (e.g., 2 or 3).

[0205] S77. If an abnormal LED semiconductor exists, process the abnormal LED semiconductor according to a preset individual abnormality processing rule;

[0206] Specifically, if an abnormal LED semiconductor exists, the abnormal LED semiconductor is processed according to the preset individual exception processing rules. The preset individual exception processing rules are a series of steps and methods for processing the detected abnormal LED semiconductor. These rules can be set according to the production process, quality control standards and actual experience. For example, but not limitation, the preset individual exception processing rules include first retesting the detected abnormal LED semiconductor to confirm whether the abnormality actually exists, and judging whether the abnormality can be corrected by adjusting the control parameters of each link based on the type and severity of the abnormality. For LED semiconductors that are confirmed to be abnormal and cannot be corrected by adjusting the process parameters, rework is performed; for abnormal LED semiconductors that still cannot meet the expected standards after rework, they are removed from the production batch to ensure the overall product quality. According to the actual production situation and quality control standards, the preset individual exception processing rules can be flexibly adjusted and optimized.

[0207] By monitoring overall deviations, systemic problems in the production process can be quickly identified, allowing timely adjustments to process parameters to ensure stable and consistent product quality. Overall deviations can help identify trends and patterns in the production process, providing data support for process optimization. For example, analyzing overall deviations can determine whether production equipment or process flow adjustments are necessary. Analyzing individual deviation data to identify the causes of deviations helps improve production processes and reduce the production of abnormal products. For example, analyzing individual deviations can determine whether a specific process step requires adjustment.

[0208] By simultaneously monitoring both overall and individual deviations, production management can comprehensively understand product quality at both macro and micro levels, achieving total quality management. When overall deviations are detected, systematic adjustments can be made to optimize the production process. When individual deviations are detected, rapid responses can be made to address abnormal products and prevent them from impacting overall quality.

[0209] Long-term accumulation of data on overall and individual deviations, followed by analysis and modeling, will help improve the predictive and preventive capabilities of production processes and establish a more intelligent production management system.

[0210] Preferably, if there is an abnormal LED semiconductor, the abnormal LED semiconductor is processed according to a preset individual abnormality processing rule, including:

[0211] S771, obtaining a ratio of the number of abnormal LED semiconductors to the total number of LED semiconductors in the production batch;

[0212] Specifically, first, the ratio of the number of abnormal LED semiconductors to the total number of LED semiconductors in the production batch is obtained. This ratio is used to measure the proportion of abnormal LED semiconductors in the entire production batch.

[0213] S772, when the ratio is less than or equal to a preset ratio, the abnormal LED semiconductor is rejected;

[0214] If the ratio is less than or equal to the preset ratio, the abnormal LED semiconductors are directly rejected because they have less impact on the overall batch, and the product quality can be ensured by rejection.

[0215] S773, when the ratio is greater than the preset ratio, an individual optical parameter deviation value of each abnormal LED semiconductor is obtained according to the expected optical parameter and the actual optical parameter;

[0216] If the ratio is greater than the preset ratio, it means that the proportion of abnormal LED semiconductors is high, and further analysis and processing are needed. Next, according to the expected optical parameter and the actual optical parameter, the individual optical parameter deviation value of each abnormal LED semiconductor is obtained. These deviation values show the difference between each abnormal LED semiconductor and the expected performance.

[0217] S774, statistically analyzing the individual optical parameter deviation values to determine a key optical deviation parameter of the abnormal LED semiconductor, wherein the key optical deviation parameter includes one of a brightness parameter, a color temperature parameter, and a light emitting wavelength parameter;

[0218] Specifically, the individual optical parameter deviation values are statistically analyzed to determine the key optical deviation parameter of the abnormal LED semiconductor, which may include one of the brightness parameter, the color temperature parameter, and the light emitting wavelength parameter. Through statistical analysis, it can be identified which optical parameter deviation is the most significant.

[0219] S775, comparing the first detection image, the second detection image, and the third detection image of all the abnormal LED semiconductors and any finished product LED semiconductor to obtain a key control deviation parameter, wherein the key control deviation parameter includes one of a die bonding control parameter, a wire bonding control parameter, and a dispensing control parameter;

[0220] Specifically, the first detection image, the second detection image and the third detection image of all abnormal LED semiconductors and any finished LED semiconductor are compared to find key control deviation parameters that cause optical deviation. These control deviation parameters include one of die bonding control parameters, wire bonding control parameters and dispensing control parameters;

[0221] To make effective comparison, first, all detection images need to be preprocessed, including grayscale, denoising, contrast enhancement, etc., to highlight important features;

[0222] For the first detection image, the main features include the accuracy of die bonding position, the uniformity of die bonding material, the size and shape of die bonding points, etc.

[0223] For the second detection image, the main features include the position of the wire, the size and shape of the solder joint, the wire routing, etc.

[0224] For the third detection image, the main features include the distribution of dispensing, the size and shape of the glue droplet, the thickness of the glue layer, etc.

[0225] Compare the extracted features, compare the feature values of abnormal LED semiconductors and finished LED semiconductors, and calculate the difference value of each feature. The difference value can be expressed as absolute difference or relative difference. Cluster analysis is performed on all difference values to identify which feature difference is most significant. This can be achieved through clustering algorithms such as K-means, DBSCAN, to find the feature cluster with the largest difference. Statistical analysis of the clustering results determines the main control deviation parameters. For example, if the difference in die bonding position is most significant in clustering, the die bonding control parameter may be the main deviation parameter.

[0226] Preferably, the first detection image, the second detection image and the third detection image of all the abnormal LED semiconductors and any of the finished LED semiconductors are compared to obtain key control deviation parameters, including:

[0227] S7751, pre-process the first detection image, the second detection image and the third detection image of all the abnormal LED semiconductors to obtain a first detection image set, a second detection image set and a third detection image set, respectively;

[0228] Specifically, the first detection image, the second detection image and the third detection image of all abnormal LED semiconductors are obtained. The first detection image is usually collected after die bonding, the second detection image is collected after wire bonding, and the third detection image is collected after dispensing;

[0229] The preprocessing includes grayscale processing, noise removal, image enhancement, edge detection and image normalization, etc. The grayscale processing can reduce the complexity of image processing, retain important shape and texture features, remove noise in the image by applying a filter (such as Gaussian filter, median filter, etc.), enhance image quality, enhance image contrast by using contrast stretching or histogram equalization, make features more obvious, then the edge detection algorithm detects the edges in the image, extracts important contour information, and finally normalizes the image to make different images comparable at the same scale. Normalization can eliminate the differences in brightness and contrast between different images.

[0230] S7752, preprocessing the first detection image, the second detection image and the third detection image of any finished LED semiconductor to obtain a first target contrast image, a second target contrast image and a third target contrast image respectively;

[0231] Specifically, the processing process of this step is the same as step S7751, only the processing object is different. The same preprocessing step ensures the consistency and comparability of the images. If different preprocessing methods are used for the images of abnormal LED semiconductors and finished LED semiconductors, additional variables and errors may be introduced, affecting the accuracy of the comparison analysis. Through consistent preprocessing steps, all images are processed under the same conditions, eliminating systematic bias introduced by different processing methods.

[0232] S7753, comparing each image in the first detection image set with the first target contrast image to obtain the deviation die bonding features of each image in the first detection image set;

[0233] Specifically, the first detection image of each abnormal LED semiconductor and the first target contrast image are aligned to ensure that they are compared in the same coordinate system. Image registration technology can be used for alignment. The die bonding related features are extracted from each image in the first detection image set and the first target contrast image. The die bonding features of each abnormal LED semiconductor are compared with the die bonding features in the target contrast image, and the difference between them is calculated. The difference value can include position deviation, size deviation and shape deviation, etc. The die bonding feature deviation of each image is recorded to form a die bonding feature deviation data set. These deviation data will be used for subsequent analysis and adjustment.

[0234] S7754, comparing each image in the second detection image set with the second target contrast image to obtain the deviation wire bonding features of each image in the second detection image set;

[0235] Similarly, the second detection image and the second target comparison image of each abnormal LED semiconductor are aligned to ensure that they are compared in the same coordinate system, and the wire bonding features of each abnormal LED semiconductor and the wire bonding features in the target comparison image are compared to calculate the differences between them. The difference values can include position deviation, length deviation, angle deviation, and bending deviation, etc. The wire bonding feature deviations of each image are recorded to form a wire bonding feature deviation dataset. These deviation data will be used for subsequent analysis and adjustment.

[0236] S7755, comparing each image in the third detection image set with the third target comparison image to obtain the deviation dispensing feature;

[0237] Specifically, the dispensing-related features are extracted from each image in the third detection image set and the third target comparison image. These features can include the position, size, uniformity, etc. of the dispensing. The dispensing features of each abnormal LED semiconductor and the dispensing features in the target comparison image are compared to calculate the differences between them. The difference values can include position deviation, size deviation, and uniformity deviation, etc. to obtain the deviation dispensing feature;

[0238] S7756, clustering analysis of the deviation die bonding feature, the deviation wire bonding feature, and the deviation dispensing feature to obtain a first significant deviation feature;

[0239] Specifically, the deviation die bonding features, deviation wire bonding features, and deviation dispensing features of all abnormal LED semiconductors are summarized to form a dataset containing multi-dimensional features. Each data point represents the feature deviation of an abnormal LED semiconductor. According to the characteristics of the data, a suitable clustering algorithm is selected, such as K-means, DBSCAN, hierarchical clustering, etc. K-means clustering is commonly used because it is simple and efficient. In order to ensure the consistency of the scales of different features, the feature data is standardized to make the mean of each feature 0 and the standard deviation 1. This can avoid the excessive influence of certain features on the clustering results. The standardized feature data is clustered using the selected clustering algorithm to obtain different feature deviation clusters. Through the clustering results, the dominant feature deviations in each cluster are identified, which are the first significant deviation features. The first significant deviation features refer to those features whose deviations are most obvious and concentrated in abnormal LED semiconductors.

[0240] S7757, correlation analysis of the first significant deviation feature and the key optical deviation parameter to obtain a second significant deviation feature;

[0241] Specifically, the first significant deviation feature and the key optical deviation parameter data are organized into a dataset. Each data point contains a significant deviation feature and the corresponding optical deviation parameter. An appropriate correlation analysis method is selected, such as Pearson correlation coefficient, Spearman rank correlation coefficient, etc. Pearson correlation coefficient is suitable for linear relationship, and Spearman rank correlation coefficient is suitable for non-linear relationship. The correlation coefficient between each significant deviation feature and the key optical deviation parameter is calculated using the selected method. The correlation coefficient ranges from [-1, 1], and the closer the value is to 1 or -1, the stronger the correlation; the closer the value is to 0, the weaker the correlation. According to the absolute value of the correlation coefficient, the significant deviation features with strong correlation with the key optical deviation parameter are screened out. The stronger the correlation, the more likely these features are the main cause of optical deviation.

[0242] S7758, determining the key control deviation parameter according to the second significant deviation feature.

[0243] According to the production process and feature deviation, the second significant deviation feature is mapped to a specific process control parameter. For example, if the wire length deviation is the second significant deviation feature, the wire control parameters (such as wire pressure, ultrasonic vibration frequency) may be the key control deviation parameters.

[0244] Through the above steps, using clustering analysis, correlation analysis and other methods, the key control deviation parameters are systematically determined and adjusted, which can effectively optimize the production process, reduce optical deviation, and improve product quality and consistency. This process not only ensures the scientificity and accuracy of the analysis, but also provides specific improvement schemes for actual production.

[0245] S776, determining the adjustment scheme and corresponding adjustment parameters according to the key optical deviation parameter and the key control deviation parameter;

[0246] According to the identified key optical deviation parameter and key control deviation parameter, the adjustment scheme and corresponding adjustment parameters are determined. This step is to link optical deviation and control deviation, and find the adjustment scheme that can solve the problem. The key optical deviation parameter is obtained by comparing the expected value and the individual actual parameter, which can accurately point out the specific problems in the production process. For example, brightness, color temperature or wavelength deviation. The key control deviation parameter is obtained by comparing the detection image, which can clearly indicate the specific deviation of the process parameters (such as die bonding, wire bonding, dispensing, etc.) in production. This double identification method can accurately locate the source of the problem and ensure that the adjustment measures are targeted.

[0247] Specifically, it can be based on the relationship model between key optical deviation parameters and key control deviation parameters. This can be achieved through experimental data and statistical analysis. Through regression analysis or other statistical methods, a relationship model between key optical deviation parameters and key control deviation parameters is established. Regression analysis can help quantify the impact of control parameters on optical parameters. Based on the relationship model, the direction and magnitude of adjusting the key control deviation parameters are determined. For example, if the brightness deviation is negative (lower than expected) and the regression analysis shows that increasing the wire bond pressure can improve the brightness, then the wire bond pressure is adjusted upward.

[0248] After adjusting the solution, conduct experiments or small-batch production to verify the effectiveness of the adjustment. Measure the adjusted optical parameters to ensure that the adjusted parameters meet the expected values.

[0249] S777: Adjust the solution to be adjusted according to the adjustment parameters.

[0250] Adjustments to the proposed solution based on these adjustment parameters ensure that the production process can correct the problem of abnormal LED semiconductors and optimize the optical performance and consistency of the entire production batch. Through the above steps, abnormal LED semiconductors can be systematically identified and handled, improving product quality and production efficiency.

[0251] S78. Target LED semiconductors other than the abnormal LED semiconductors are used as finished LED semiconductors.

[0252] Specifically, identified abnormal LED semiconductors are removed from the list of target LED semiconductors. The serial numbers and test results of these abnormal LED semiconductors are recorded for further analysis and processing. After removing the abnormal LED semiconductors, the remaining target LED semiconductors are finished products that meet quality requirements. The optical parameters of these finished LED semiconductors are within the expected range and have undergone rigorous testing and verification.

[0253] S79: If there are no abnormal LED semiconductors, treat all the target LED semiconductors as finished product LED semiconductors.

[0254] During the inspection and analysis process, if no abnormal LED semiconductors are identified, that is, the optical parameters of all target LED semiconductors are within the expected range, then all target LED semiconductors can be directly marked as finished LED semiconductors. These products have passed the quality inspection and meet the production standards.

[0255] S8, performing post-processing on each of the finished LED semiconductors to obtain an LED product;

[0256] Specifically, during the production process, after the finished LED semiconductors complete optical parameter detection and screening, a series of post-processing steps are needed to ensure their quality and consistency during packaging and storage. Taping refers to the process of loading LED semiconductors into a tape carrier for subsequent storage, transportation, and use. During the taping process, LED semiconductors are usually arranged on the tape carrier according to certain specifications and quantities, and fixed and packaged automatically using machines. Warehousing refers to the storage of LED semiconductors in designated warehouses or storage areas for future production or sales needs

[0257] Preferably, the post-processing of each of the finished LED semiconductors to obtain an LED product comprises:

[0258] S81, according to the unique identifier of the finished LED semiconductor, obtaining a taping scheme, the taping scheme comprising a taping method and a taping position;

[0259] Specifically, the taping scheme includes a taping method and a taping position. The taping method may include automatic taping or manual taping, and the taping position refers to the specific arrangement position of the LED semiconductor during taping. According to the unique identifier, the corresponding taping scheme is queried from the production database or management system. The taping scheme is usually pre-set according to the model, specification and application requirements of the LED semiconductor.

[0260] S82, according to the taping scheme, taping processing the finished LED semiconductor to obtain an LED light bar;

[0261] Specifically, according to the taping scheme, the finished LED semiconductor is arranged and fixed on the taping. Taping processing needs to be accurately controlled to ensure that each LED semiconductor is in the correct position and avoid damage or misplacement.

[0262] S83, quality detection of the LED light bar to obtain a quality inspection result, wherein the quality detection comprises optical detection, electrical detection and mechanical detection;

[0263] Specifically, first, the optical performance of the LED light bar is detected, including brightness, color temperature and light wavelength parameters. Professional equipment is used to measure these optical parameters to ensure that they meet the expected standards. The electrical performance of the LED light bar is detected, including current, voltage and power parameters. Ensure stable electrical connection, no short circuit or open circuit phenomenon. The mechanical performance of the LED light bar is detected, including the firmness of the taping, the physical integrity of the LED semiconductor, etc., to ensure that the LED semiconductor is not damaged or its performance is affected during the taping process. The quality inspection result is obtained according to the above quality detection.

[0264] S84, generating a unique identifier corresponding to the LED light bar passing the quality detection;

[0265] For LED light bars detected by quality inspection, a new unique identifier is generated. This identifier can be used to track and manage the subsequent processes of the LED light bar. The generated unique identifier is marked on the corresponding LED light bar. The marking method can be labeling, laser coding, etc.

[0266] S85, according to the unique identifier and the corresponding quality inspection result, the LED light bar is processed into the warehouse.

[0267] Specifically, the quality inspection result of each LED light bar is confirmed to ensure that it meets the warehouse standard. The light bar that does not meet the quality inspection standard needs to be reworked or scrapped. The LED light bar that meets the standard is registered into the warehouse. Record the unique identifier, quality inspection result, production batch, etc. of each light bar. According to the warehouse management process, the LED light bar is stored in the designated warehouse location. Ensure that the warehouse environment meets the storage requirements of the LED light bar (such as temperature, humidity, etc.).

[0268] Through the above steps, the LED semiconductor production data traceability analysis is completed, including the steps of coding, quality inspection and warehousing. Each step needs to be operated accurately and recorded in detail to ensure the quality and consistency of the finished LED semiconductor. At the same time, through the unique identifier, the tracking and management of each LED light bar are realized, and the transparency and traceability of the production process are ensured.

[0269] Embodiment 2

[0270] Referring to Figure 3 , the embodiment of the present application provides an LED semiconductor production data traceability analysis system, the system comprises: a processing pretreatment module for preprocessing the initial LED semiconductor and the support, a die bonding module for die bonding the LED semiconductor according to the die bonding strategy, a welding module for welding the LED semiconductor according to the wire bonding strategy, including the control and adjustment of wire bonding path and wire bonding parameter, a dispensing module for dispensing the LED semiconductor according to the dispensing strategy, a sensor module for real-time monitoring and collecting key parameters in the LED production process, a power module for supplying power to the system, and a controller for executing the LED semiconductor production data traceability analysis method described in embodiment 1.

[0271] The processing pretreatment module, the die bonding module, the welding module and the dispensing module work cooperatively to realize high automation of the production process, reduce manual intervention and improve production efficiency. The sensor module monitors the key parameters in real time, and the controller automatically adjusts the die bonding, wire bonding and dispensing parameters according to the detection results, ensuring the continuity and efficiency of the production process. The system can flexibly adjust the die bonding, wire bonding and dispensing strategies according to different production needs, and adapt to different types of LED semiconductor production.

[0272] In summary, the system realizes high automation, precise control and real-time adjustment of the production process by integrating the automation module and control method, improves production efficiency and product quality, reduces production cost, and ensures the stability and flexibility of the production process, and is a high-efficiency, reliable and economical LED semiconductor production solution.

[0273] It should be noted that the present application is not limited to the specific configurations and processes described above and illustrated in the drawings. For the sake of brevity, detailed descriptions of known methods are omitted. In the above embodiments, several specific steps are described and illustrated as examples. However, the method processes of the present application are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications and additions, or change the order of the steps, after understanding the spirit of the present application.

[0274] The functional blocks shown in the above structural block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a functional card, etc. When implemented in software, the elements of the present application are program or code segments used to perform the required tasks. The program or code segments can be stored in a machine-readable medium or transmitted through a data signal carried in a carrier wave over a transmission medium or communication link. The "machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segments can be downloaded via a computer network such as the Internet, an intranet, etc.

[0275] It should also be noted that the exemplary embodiments mentioned in the present application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiments, or in an order different from the embodiments, or several steps can be performed simultaneously.

[0276] The above is only a specific implementation of the present application, and those skilled in the art can clearly understand that, for the sake of convenience and brevity of description, the specific working process of the above-described system, module and unit can refer to the corresponding process in the foregoing method embodiments, which will not be described here. It should be understood that the protection scope of the present application is not limited thereto, and any skilled person in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A method of LED semiconductor production data traceability analysis, characterized by, The method comprises: obtaining a taping scheme according to a unique identifier of a finished LED semiconductor, the taping scheme comprising a taping mode and a taping position; taping processing the finished LED semiconductor according to the taping scheme to obtain an LED light bar; quality detection of the LED light bar to obtain a quality inspection result, wherein the quality detection comprises optical detection, electrical detection and mechanical detection; generating a unique identifier corresponding to the LED light bar passing the quality detection; warehouse processing of the LED light bar according to the unique identifier and the corresponding quality inspection result to obtain an LED product; wherein, before the step of obtaining a taping scheme according to a unique identifier of a finished LED semiconductor, the taping scheme comprising a taping mode and a taping position, there is further comprising: preliminary processing of an initial LED semiconductor and a support to obtain a first LED semiconductor, wherein the first LED semiconductor is placed at a designated position of the support, the surface of the support has a unique identifier set by laser coding, and the preliminary processing comprises die expansion processing and dehumidification processing of the support; die bonding of the first LED semiconductor according to a die bonding strategy to obtain a second LED semiconductor, wherein the die bonding strategy is obtained based on the unique identifier; obtaining a die bonding detection target of the second LED semiconductor according to the die bonding strategy, wherein the die bonding strategy comprises a die bonding mode and a die bonding control parameter, and different die bonding modes correspond to different die bonding detection targets; obtaining a first detection image comprising the second LED semiconductor; obtaining a die bonding detection result according to the die bonding detection target and the first detection image, wherein when the die bonding mode is laser die bonding, the die bonding detection result comprises a laser spot size deviation value, a laser spot irregularity and a laser spot size consistency, and when the die bonding mode is adhesive die bonding, the die bonding detection result comprises a glue drop size deviation and a glue drop distribution deviation; obtaining a preset die bonding condition according to the die bonding strategy; judging whether the second LED semiconductor meets the preset die bonding condition according to the die bonding detection result; if yes, wire bonding of the second LED semiconductor according to a wire bonding strategy to obtain a third LED semiconductor; if not, adjusting the die bonding control parameter according to the die bonding detection result, and returning to the step of die bonding of the first LED semiconductor according to a die bonding strategy to obtain a second LED semiconductor; in response to the third LED semiconductor meeting a preset wire bonding condition, adhesive dispensing of the third LED semiconductor according to an adhesive dispensing strategy to obtain a target LED semiconductor, wherein the adhesive dispensing strategy is obtained based on the unique identifier.

2. The LED semiconductor production data traceability analysis method according to claim 1, characterized in that, The adhesive dispensing of the third LED semiconductor according to the adhesive dispensing strategy to obtain the target LED semiconductor in response to the third LED semiconductor meeting the preset wire bonding condition comprises: obtaining a second detection image comprising the third LED semiconductor; obtaining an actual wire bonding path and an actual wire bonding parameter according to the second detection image; According to the wire bonding strategy, an expected wire bonding path and an expected wire bonding parameter are obtained, wherein the wire bonding strategy comprises a wire bonding layout and a wire bonding control parameter; According to the actual wire bonding path and the expected wire bonding path, a wire bonding shape deviation is obtained; According to the actual wire bonding parameter and the expected wire bonding parameter, a wire bonding parameter deviation is obtained; According to the wire bonding shape deviation and the wire bonding parameter deviation, it is judged whether the third LED semiconductor satisfies a preset wire bonding condition; If yes, the third LED semiconductor is glued according to the glue dispensing strategy, to obtain a target LED semiconductor; If no, the wire bonding control parameter is adjusted according to the wire bonding shape deviation and / or the wire bonding parameter deviation, and the method returns to the step of responding to the second LED semiconductor satisfying the preset die bonding condition, and bonding the second LED semiconductor according to the wire bonding strategy to obtain the third LED semiconductor.

3. The LED semiconductor production data traceability analysis method according to claim 2, characterized in that, After the step of responding to the third LED semiconductor satisfying the preset wire bonding condition, the third LED semiconductor is glued according to the glue dispensing strategy to obtain the target LED semiconductor, the method further comprises: According to the unique identifier, the target LED semiconductor and the corresponding expected optical parameter belonging to the same production batch are determined; According to the expected optical parameter, the finished product LED semiconductor satisfying the preset light splitting condition is screened from the target LED semiconductor belonging to the same production batch. The step of responding to the target LED semiconductor satisfying the preset glue dispensing condition, and performing light splitting processing on the target LED semiconductor according to the light splitting strategy to obtain the actual optical parameter of the target LED semiconductor comprises:

4. The LED semiconductor production data traceability analysis method according to claim 3, characterized in that, A third detection image comprising the target LED semiconductor is obtained; According to the third detection image, an actual glue dispensing size and an actual glue dispensing distribution are obtained; According to the glue dispensing strategy, an expected glue dispensing size and an expected glue dispensing distribution are obtained, wherein the glue dispensing strategy comprises a glue dispensing control parameter and a glue dispensing distribution; According to the actual glue dispensing size and the expected glue dispensing size, a glue dispensing size deviation is obtained; According to the expected glue dispensing distribution and the actual glue dispensing distribution, a glue dispensing distribution deviation is obtained; According to the glue dispensing distribution deviation and the glue dispensing size deviation, it is judged whether the target LED semiconductor satisfies a preset glue dispensing condition; If yes, the target LED semiconductor is subjected to light splitting processing according to the light splitting strategy to obtain the actual optical parameter of the target LED semiconductor; If no, the glue dispensing control parameter is adjusted according to the glue dispensing distribution deviation and / or the glue dispensing size deviation, and the method returns to the step of responding to the third LED semiconductor satisfying the preset wire bonding condition, and gluing the third LED semiconductor according to the glue dispensing strategy to obtain the target LED semiconductor. ​ 5. The LED semiconductor production data traceability analysis method according to claim 4, characterized in that, The method comprises the following steps: According to the expected optical parameters, screening the finished LED semiconductors meeting the preset light splitting conditions from the target LED semiconductors belonging to the same production batch; According to the actual optical parameters, obtaining the actual optical parameter mean value of the target LED semiconductors belonging to the same production batch; According to the actual optical parameter mean value and the expected optical parameters, obtaining the overall optical parameter deviation value; According to the overall optical parameter deviation value, judging whether there is an overall deviation in the target LED semiconductors belonging to the same production batch; If there is an overall deviation, according to the preset overall deviation processing rule and the overall optical parameter deviation value, adjusting at least one of the die bonding strategy, the wire bonding strategy and the dispensing strategy; If there is no overall deviation, according to the actual optical parameter mean value and the actual optical parameters, obtaining the sample standard deviation of the target LED semiconductors belonging to the same production batch; According to the sample standard deviation, judging whether there is an abnormal LED semiconductor in the target LED semiconductors belonging to the same production batch; If there is an abnormal LED semiconductor, according to the preset individual abnormal processing rule, processing the abnormal LED semiconductor; Taking the target LED semiconductors other than the abnormal LED semiconductor as finished LED semiconductors; 6. The LED semiconductor production data traceability analysis method according to claim 5, characterized in that, If there is no abnormal LED semiconductor, taking all the target LED semiconductors as finished LED semiconductors. If there is an overall deviation, according to the preset overall deviation processing rule and the overall optical parameter deviation value, adjusting at least one of the die bonding strategy, the wire bonding strategy and the dispensing strategy, which comprises the following steps: Obtaining the overall optical parameter deviation value, wherein the overall optical parameter deviation value comprises a brightness deviation value, a color temperature deviation value and a light-emitting wavelength deviation value; When the absolute value of the brightness deviation value is greater than a brightness deviation threshold value, taking the wire bonding strategy as the scheme to be adjusted; According to the brightness deviation value, determining the to-be-adjusted parameter of the wire bonding strategy and the corresponding parameter adjustment value, wherein the to-be-adjusted parameter of the wire bonding strategy comprises an ultrasonic vibration parameter and a bonding pressure parameter; When the absolute value of the color temperature deviation value is greater than a color temperature deviation threshold value, taking the die bonding strategy as the scheme to be adjusted; According to the color temperature deviation value, determining the to-be-adjusted parameter of the die bonding strategy and the corresponding parameter adjustment value, wherein when the die bonding mode is laser die bonding, the to-be-adjusted parameter of the die bonding strategy comprises laser power, laser time and laser frequency, and when the die bonding mode is adhesive die bonding, the to-be-adjusted parameter of the die bonding strategy comprises die bonding temperature, die bonding time and adhesive ratio; When the absolute value of the light-emitting wavelength deviation value is greater than a light-emitting wavelength deviation threshold value, taking the dispensing strategy as the scheme to be adjusted; According to the light-emitting wavelength deviation value, determining the to-be-adjusted parameter of the dispensing strategy and the corresponding parameter adjustment value, wherein the to-be-adjusted parameter of the dispensing strategy comprises dispensing amount and dispensing material ratio; When the number of the schemes to be adjusted is greater than one, according to the brightness deviation value, the color temperature deviation value and the light-emitting wavelength deviation value after normalization processing, determining the adjustment sequence; According to the adjustment sequence and the parameter adjustment value, the to-be-adjusted scheme is adjusted in sequence.

7. The LED semiconductor production data traceability analysis method according to claim 5, characterized by, If there are abnormal LED semiconductors, the abnormal LED semiconductors are processed according to preset individual abnormal processing rules, including: Obtaining the ratio of the number of abnormal LED semiconductors to the total number of LED semiconductors in the production batch; When the ratio is less than or equal to a preset ratio, the abnormal LED semiconductors are rejected; When the ratio is greater than the preset ratio, individual optical parameter deviation values of each of the abnormal LED semiconductors are obtained according to the expected optical parameters and the actual optical parameters; Statistical analysis is performed on the individual optical parameter deviation values to determine a key optical deviation parameter of the abnormal LED semiconductors, wherein the key optical deviation parameter includes one of a brightness parameter, a color temperature parameter, and a light-emitting wavelength parameter; The first detection image, the second detection image, and the third detection image of all the abnormal LED semiconductors and any of the finished product LED semiconductors are compared to obtain a key control deviation parameter, wherein the key control deviation parameter includes one of a die bonding control parameter, a wire bonding control parameter, and a dispensing control parameter; According to the key optical deviation parameter and the key control deviation parameter, a to-be-adjusted scheme and corresponding adjustment parameters are determined; According to the adjustment parameters, the to-be-adjusted scheme is adjusted.

8. The LED semiconductor production data traceability analysis method according to claim 7, characterized in that, The comparison of the first detection image, the second detection image, and the third detection image of all the abnormal LED semiconductors and any of the finished product LED semiconductors to obtain a key control deviation parameter includes: The first detection image, the second detection image, and the third detection image of all the abnormal LED semiconductors are preprocessed to obtain a first detection image set, a second detection image set, and a third detection image set, respectively; The first detection image, the second detection image, and the third detection image of any of the finished product LED semiconductors are preprocessed to obtain a first target comparison image, a second target comparison image, and a third target comparison image, respectively; Each image in the first detection image set is compared with the first target comparison image to obtain a deviation die bonding feature of each image in the first detection image set; Each image in the second detection image set is compared with the second target comparison image to obtain a deviation wire bonding feature of each image in the second detection image set; Each image in the third detection image set is compared with the third target comparison image to obtain a deviation dispensing feature; The deviation die bonding feature, the deviation wire bonding feature, and the deviation dispensing feature are subjected to cluster analysis to obtain a first significant deviation feature; The first significant deviation feature and the key optical deviation parameter are subjected to correlation analysis to obtain a second significant deviation feature; The key control deviation parameter is determined according to the second significant deviation feature.

9. An LED semiconductor production data traceability analysis system, characterized by, The system is used to perform the LED semiconductor production data traceability analysis method of any one of claims 1-8.

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