LED semiconductor production data tracing analysis method and system

Abstract

The invention relates to the technical field of LED semiconductor manufacturing, solves the problem that in the prior art, quality and consistency cannot be kept in the packaging and storage process of finished LED semiconductors, and provides an LED semiconductor production data tracing analysis method and system. The method comprises the steps that according to a unique identifier of a finished LED semiconductor, a taping scheme is obtained, and the taping scheme comprises a taping mode and a taping position; the finished LED semiconductor is subjected to braiding treatment according to the braiding scheme, and an LED light bar is obtained; the LED light bar is subjected to quality detection, a quality detection result is obtained, and quality detection comprises optical detection, electrical detection and mechanical detection; generating a unique identifier corresponding to the LED light bar passing the quality detection; and according to the unique identifier and the corresponding quality inspection result, carrying out warehousing processing on the LED light bar to obtain an LED product. The quality and the consistency can be kept in the packaging and storing process of finished LED semiconductors.

Description

[0001] This invention is a divisional application of the invention patent application filed on July 23, 2024, with the invention name “LED semiconductor production control method and system” and application number 202410986452.5. Technical Field

[0002] The present invention relates to the field of LED semiconductor technology, and in particular to a method and system for tracing and analyzing LED semiconductor production data. Background Art

[0003] Maintaining quality and consistency during the packaging and storage of finished LED semiconductors is critical because LED semiconductors are extremely sensitive to environmental conditions, especially humidity, temperature, and physical pressure. Strict packaging and storage specifications help ensure the reliability, light efficacy, and life consistency of LED products, thereby providing high-quality light source solutions for downstream applications.

[0004] The existing technology faces the problem of difficulty in maintaining quality and consistency during the packaging and storage of finished LED semiconductors. The main reason is the lack of precise taping processing and strict quality inspection and control of LED semiconductors. On the one hand, the traditional taping process often relies on manual operation, which can easily lead to 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 properties makes it difficult to screen products with quality differences during packaging and storage. In addition, during the warehousing and storage process, inaccurate environmental control (such as humidity and temperature) will accelerate the degradation of LED performance, affect its luminous efficiency and life, and thus cannot effectively ensure the quality, consistency and performance stability of factory products.

[0005] To this end, how to maintain quality and consistency during the packaging and storage of finished LED semiconductors is an urgent problem to be solved. Summary of the invention

[0006] In view of this, an embodiment of the present invention provides a method and system for tracing and analyzing LED semiconductor production data, so as to solve the problem in the prior art that the quality and consistency of finished LED semiconductors cannot be maintained during packaging and storage.

[0007] In a first aspect, an embodiment of the present invention provides a method for tracing and analyzing LED semiconductor production data, the method comprising:

[0008] Obtaining a braiding scheme according to a unique identifier of a finished LED semiconductor, wherein the braiding scheme includes a braiding method and a braiding position;

[0009] Performing tape processing on the finished LED semiconductor according to the tape braiding scheme to obtain an LED light strip;

[0010] Performing quality inspection on the LED light strip to obtain a quality inspection result, wherein the quality inspection includes optical inspection, electrical inspection and mechanical inspection;

[0011] Generate a unique identifier corresponding to the LED light strip that has passed the quality inspection;

[0012] According to the unique identifier and the corresponding quality inspection result, the LED light strip is put into storage to obtain an LED product.

[0013] Preferably, before obtaining a braiding scheme according to the unique identifier of the finished LED semiconductor, wherein the braiding scheme includes a braiding method and a braiding position, the method further includes:

[0014] Performing a pre-process on the initial LED semiconductor and the bracket to obtain a first LED semiconductor, wherein the first LED semiconductor is placed at a designated position of the bracket, a surface of the bracket has a unique identifier set by laser coding, and the pre-process includes a crystal expansion process and a dehumidification process of the bracket;

[0015] Performing die bonding on 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;

[0016] According to the die bonding strategy, obtaining a die bonding detection target of the second LED semiconductor, 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] Acquire a first detection image including the second LED semiconductor;

[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 the 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; when the die bonding method is an 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, obtaining the preset die bonding conditions;

[0020] According to the die-bonding detection result, determining whether the second LED semiconductor satisfies the preset die-bonding condition;

[0021] If the conditions are met, wire bonding is performed on the second LED semiconductor according to the wire bonding strategy to obtain a third LED semiconductor;

[0022] If not satisfied, adjusting the die bonding control parameter according to the die bonding detection result, and returning to the step of performing die bonding on the first LED semiconductor according to the die bonding strategy to obtain a second LED semiconductor;

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

[0024] Preferably, in response to the third LED semiconductor meeting the preset wire bonding condition, dispensing glue on the third LED semiconductor according to the dispensing strategy to obtain the target LED semiconductor includes:

[0025] Acquire a second detection image including the third LED semiconductor;

[0026] Acquire an actual welding wire path and actual welding wire parameters according to the second detection image;

[0027] According to the wire bonding strategy, obtaining an expected wire bonding path and expected wire bonding parameters, wherein the wire bonding strategy includes a wire bonding layout and a wire bonding control parameter;

[0028] Obtaining a welding wire shape deviation according to the actual welding wire path and the expected welding wire path;

[0029] Obtaining a wire bonding parameter deviation according to the actual wire bonding parameter and the expected wire bonding parameter;

[0030] Determining whether the third LED semiconductor meets a preset wire bonding condition according to the wire bonding shape deviation and the wire bonding parameter deviation;

[0031] If the conditions are met, dispensing glue on the third LED semiconductor 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 in response to the second LED semiconductor meeting the preset die bonding conditions, the second LED semiconductor is wire bonded according to the wire bonding strategy to obtain a third LED semiconductor.

[0033] Preferably, in response to the third LED semiconductor meeting the preset wire bonding condition, after dispensing glue on the third LED semiconductor according to the dispensing strategy to obtain the target LED semiconductor, the method further includes:

[0034] In response to the target LED semiconductor meeting the preset dispensing condition, the target LED semiconductor is subjected to a spectroscopic process according to a spectroscopic strategy to obtain actual optical parameters of the target LED semiconductor, wherein the spectroscopic strategy is obtained based on the unique identifier, and the actual optical parameters include color temperature parameters, light emission wavelength, and brightness parameters;

[0035] Determining target LED semiconductors belonging to the same production batch and corresponding expected optical parameters based on the unique identifier;

[0036] According to the expected optical parameters, screening finished LED semiconductors that meet preset light-splitting conditions from target LED semiconductors belonging to the same production batch;

[0037] The finished LED semiconductors are post-processed to obtain LED products.

[0038] Preferably, in response to the target LED semiconductor meeting the preset dispensing condition, performing a spectroscopic process on the target LED semiconductor according to a spectroscopic strategy to obtain actual optical parameters of the target LED semiconductor includes:

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

[0040] According to the third detection image, the actual dispensing size and the actual dispensing distribution are obtained:

[0041] According to the dispensing strategy, an expected dispensing size and an expected dispensing distribution are obtained, wherein the dispensing strategy includes dispensing control parameters and dispensing distribution;

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

[0043] Obtain dispensing distribution deviation according to expected dispensing distribution and actual dispensing distribution;

[0044] According to the dispensing distribution deviation and the dispensing size deviation, determining whether the target LED semiconductor meets the preset dispensing condition;

[0045] If the conditions are met, the target LED semiconductor is subjected to a light splitting process according to a light splitting strategy to obtain actual optical parameters of the target LED semiconductor;

[0046] If not, the glue dispensing control parameters are adjusted according to the glue dispensing distribution deviation and / or the glue dispensing size deviation, and the third LED semiconductor is glued according to the glue dispensing strategy in response to the third LED semiconductor satisfying the preset welding wire condition to obtain the target LED semiconductor.

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

[0048] According to the actual optical parameters, obtaining an average value of the actual optical parameters of the 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] According to the overall optical parameter deviation value, determining whether there is an overall deviation in the target LED semiconductors belonging to the same production batch;

[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 the target LED semiconductors of the same production batch according to the actual optical parameter mean and the actual optical parameter;

[0053] Determining whether there are abnormal LED semiconductors in the target LED semiconductors of the same production batch according to the sample standard deviation;

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

[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 of 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 the parameters to be adjusted of the wire bonding strategy and the corresponding parameter adjustment values ​​according to the brightness deviation value, wherein the parameters to be adjusted of the wire bonding strategy include ultrasonic vibration parameters and bonding pressure parameters;

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

[0062] Determine the parameters to be adjusted of the die bonding strategy and the corresponding parameter adjustment values ​​according to the color temperature deviation value, wherein when the die bonding method is laser die bonding, the parameters to be adjusted of the die bonding strategy include laser power, laser time and laser frequency; when the die bonding method is adhesive die bonding, the parameters to be adjusted of the die bonding strategy include die bonding temperature, die bonding time and adhesive ratio;

[0063] When the absolute value of the light emitting wavelength deviation value is greater than the light emitting wavelength deviation threshold, the dispensing strategy is used as a solution to be adjusted;

[0064] Determining the parameters to be adjusted of the dispensing strategy and the corresponding parameter adjustment values ​​according to the luminous wavelength deviation value, wherein the parameters to be adjusted of the dispensing strategy include the dispensing amount and the dispensing material ratio;

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

[0066] According to the adjustment sequence and the parameter adjustment value, the scheme to be adjusted is adjusted in sequence.

[0067] Preferably, if there is an abnormal LED semiconductor, the abnormal LED semiconductor is processed according to a preset individual abnormality processing rule, including:

[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, removing the abnormal LED semiconductor;

[0070] When the ratio is greater than the preset ratio, obtaining individual optical parameter deviation values ​​of each of the abnormal LED semiconductors according to the expected optical parameters and the actual optical parameters;

[0071] Performing statistical analysis on the individual optical parameter deviation values ​​to determine the 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 emission 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 of the finished LED semiconductors 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 glue dispensing control parameter;

[0073] Determining a scheme to be adjusted and corresponding adjustment parameters according to the key optical deviation parameters and the key control deviation parameters;

[0074] The scheme to be adjusted is adjusted according to the adjustment parameters.

[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 of the finished LED semiconductors to obtain key control deviation parameters includes:

[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 of the finished LED semiconductors 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 solidification 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 weld line 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 a correlation analysis on the first significant deviation feature and the key optical deviation parameter, a second significant deviation feature;

[0083] The key control deviation parameter is determined according to the second significant deviation feature.

[0084] In the second aspect, an embodiment of the present invention provides an LED semiconductor production data traceability and analysis system, the system comprising: a processing preprocessing module for performing pre-processing on the initial LED semiconductor and the bracket, a crystal bonding module for bonding the LED semiconductor according to the crystal bonding strategy, a welding module for welding the LED semiconductor according to the welding wire strategy, a glue dispensing module for dispensing the LED semiconductor according to the glue dispensing strategy, a sensor module for real-time monitoring and collection of key parameters in the LED production process, a power supply module for supplying energy to the system, and a controller for executing the LED semiconductor production data traceability and analysis method described in the first aspect.

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

[0086] The LED semiconductor production data traceability analysis method and system provided by the embodiment of the present invention include: obtaining a braiding scheme according to a unique identifier of a finished LED semiconductor, wherein the braiding scheme includes a braiding method and a braiding position; braiding the finished LED semiconductor according to the braiding scheme to obtain an LED light bar; performing quality inspection on the LED light bar to obtain a quality inspection result, wherein the quality inspection includes optical inspection, electrical inspection and mechanical inspection; generating a unique identifier corresponding to the LED light bar that passes the quality inspection; and performing warehousing processing on the LED light bar according to the unique identifier and the corresponding quality inspection result to obtain an LED product. The present invention achieves precise management of each finished LED semiconductor through a unique identifier, ensuring its quality and consistency throughout the entire post-processing process. By obtaining the taping scheme corresponding to the unique identifier, the taping process is automated and standardized, avoiding errors caused by manual operation and ensuring the accuracy of the LED semiconductor in the taping position and method. The subsequent optical, electrical and mechanical tests comprehensively evaluate the performance of the LED light bar to ensure that the quality meets the requirements. The light bar that passes the quality inspection generates a new unique identifier for easy tracking and management, so that product information can be accurately recorded during the warehousing process to avoid misalignment or quality differences during storage and transportation. In addition, strict quality inspection and warehousing 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, thereby ensuring that the quality of the final LED product leaving the factory is stable and traceable. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the drawings required for use in the embodiment of the present invention will be briefly introduced below. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work, and these are all within the protection scope of the present invention.

[0088] Figure 1It is a flow chart of a method for tracing and analyzing LED semiconductor production data according to an embodiment of the present invention.

[0089] Figure 2 It is another flow chart of the LED semiconductor production data traceability analysis method according to an embodiment of the present invention.

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

[0091] The features and exemplary embodiments of various aspects of the present invention will be described in detail below. In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and Examples. It should be understood that the specific embodiments described herein are only configured to explain the present invention and are not configured to limit the present invention. For those skilled in the art, the present invention can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present invention by illustrating examples of the present invention.

[0092] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

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

[0094] Example 1

[0095] See also Figure 1 The embodiment of the present invention provides a method for tracing and analyzing LED semiconductor production data, the method comprising:

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

[0097] Specifically, in the LED semiconductor production data traceability analysis system, the initial LED semiconductor and the bracket are first pre-processed to obtain the first LED semiconductor. The crystal expansion process is an important pre-processing step used to change 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, and the temperature, pressure and atmosphere are controlled to promote the growth and arrangement of the crystal, thereby optimizing the performance of the LED. The dehumidification process is to reduce the impact of humidity on the LED semiconductor during the production process. In this step, the surface of the bracket and the LED chip is processed to ensure that there will be no quality problems caused by excessive humidity during the subsequent crystal bonding, welding and dispensing processes.

[0098] The surface of the bracket is laser-coded to set a unique identifier, which can be used as the identification code of the LED semiconductor for subsequent data traceability and production process management.

[0099] S2, performing die bonding on 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 crystal bonding strategy is the specific operation steps and parameter settings of crystal bonding, including the crystal bonding method (such as silver glue crystal bonding, laser crystal bonding, etc.) and crystal bonding control parameters (such as temperature, pressure, etc.); the crystal bonding strategy is obtained according to the unique identifier, and the specific operation steps and parameter settings of the crystal bonding are determined. The crystal bonding strategy is obtained through the unique identifier, which realizes personalized management and customized operation of each LED chip, and improves the flexibility and efficiency of the production process; performing crystal bonding operations according to the specific crystal bonding strategy can ensure the quality and stability of crystal bonding, and improve the reliability and performance consistency of LED products.

[0101] S3, in response to the second LED semiconductor meeting the preset die bonding condition, performing wire bonding on 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 that has been bonded. Before the next process, i.e., wire bonding, it is necessary to detect it to determine whether the second LED semiconductor meets a preset quality condition, i.e., the preset bonding condition, for example, specific parameter requirements that need to be met during the bonding process, such as bonding temperature, time, pressure, etc. These parameters ensure that the LED semiconductor is firmly adhered to the bracket. Different conditions can be set for judgment according to different bonding strategies;

[0103] After checking that the die bonding meets the conditions, the unique identifier of the second LED semiconductor is scanned and the corresponding wire bonding strategy is obtained. The wire bonding strategy refers to the specific operation steps and parameter settings of welding, including the wire bonding path and wire bonding parameters (such as temperature, pressure, etc.), so as to determine the specific operation steps and parameter settings of the wire bonding, perform the wire bonding operation, and connect the wire of the second LED semiconductor to the external circuit;

[0104] By obtaining the wire bonding strategy through a unique identifier, personalized welding operations for each LED chip are achieved, improving the flexibility and efficiency of the production process.

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

[0106] S31, acquiring 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, according to the die bonding method (laser die bonding or adhesive die bonding), the system determines the inspection target of the die bonding quality. Different die bonding methods may have different inspection requirements. For example, laser die bonding may require inspection of the shape, size and consistency of the solder joints, while adhesive die bonding may require inspection of the uniformity and coverage of the adhesive.

[0108] S32, acquiring 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 bonding state between the LED chip and the bracket, including possible cracks, bubbles and other problems.

[0110] S33, acquiring a die bonding detection result according to the die bonding detection target and the first detection image, wherein when the die bonding method is the 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; when the die bonding method is an adhesive die bonding, the die bonding detection result includes 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 the laser spot size deviation value, laser spot irregularity and laser spot size consistency, or glue drop size deviation and glue drop distribution deviation, etc. The first detection image can be analyzed to extract features related to the die bonding quality. If it is laser die bonding, the laser spot size, shape and other features are extracted, and the deviation value and consistency are calculated. If it is adhesive die bonding, the size and distribution characteristics of the glue drop are extracted, and the deviation value and uniformity are calculated.

[0112] Through image analysis and feature extraction, the specific test results of the die bonding process can be accurately obtained to improve the test accuracy. Through the specific test results, problems in the die bonding process can be discovered in time and effective adjustments can be made.

[0113] S34, acquiring the preset die bonding conditions according to the die bonding strategy;

[0114] Specifically, the preset die bonding conditions set specific quality requirements in the die bonding process. By comparing with the test results, it is determined whether the die bonding quality is qualified. According to the die bonding strategy, the quality control standards of the current die bonding process are obtained from the database, including the laser spot size range and consistency requirements of laser die bonding, and the glue drop uniformity and coverage of adhesive die bonding.

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

[0116] Specifically, the bonding test result is compared with the preset bonding conditions to determine whether the quality of the bonding process is qualified to ensure that the product meets the quality requirements. The preset bonding conditions set specific judgment standards, such as the laser spot size deviation value does not exceed ±10%, the glue drop size deviation does not exceed ±5%, etc., and according to the comparison result, it is determined whether the bonding quality of the second LED semiconductor is qualified.

[0117] S36, if the conditions are met, performing wire bonding on the second LED semiconductor according to the wire bonding strategy to obtain a third LED semiconductor;

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

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

[0120] Specifically, when the quality of the die bonding is unqualified, the die bonding control parameters are adjusted according to the test results to optimize the die bonding process. By adjusting the die bonding control parameters, the quality problems in the die bonding process are improved to ensure the quality of the die bonding is qualified.

[0121] The specific process of adjustment includes analyzing specific problems in the crystal bonding process, such as solder joint size deviation, uneven glue droplets, etc., according to the crystal bonding test results; adjusting the crystal bonding control parameters according to the analysis results, such as increasing laser power, adjusting the adhesive ratio, etc.; re-performing the crystal bonding operation according to the adjusted crystal bonding control parameters to obtain a new second LED semiconductor; and performing quality inspection on the second LED semiconductor after re-crystal bonding to ensure that the quality of the crystal bonding meets the preset conditions.

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

[0123] Specifically, before dispensing, the welded third LED semiconductor is first inspected to determine whether the third LED semiconductor meets the preset welding line conditions. The preset welding line conditions may be specific parameter requirements such as the firmness of the welding point and the welding accuracy, so as to ensure the quality of the welding line.

[0124] Subsequently, the third LED semiconductor after the wire bonding is glued 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 glue dispensing strategy applicable to the current third LED semiconductor is obtained from the database. Ensure that the glue dispensing strategy matches the specific conditions of the LED semiconductor after the wire bonding; the glue dispensing strategy includes specific operation steps and parameter settings for glue dispensing on the LED chip, which may include the type of adhesive and glue dispensing control parameters. The specific operation steps and parameter settings of glue dispensing are determined by the glue dispensing strategy, so as to perform the glue dispensing operation.

[0125] Preferably, in response to the third LED semiconductor meeting the preset wire bonding condition, dispensing glue on the third LED semiconductor according to the dispensing strategy to obtain the target LED semiconductor includes:

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

[0127] Specifically, a second detection image including 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, acquiring an actual welding wire path and actual welding wire parameters according to the second detection image;

[0129] Specifically, based on the second detection image, the path and parameters of the actual welding wire are identified and extracted through image processing algorithms or computer vision technology. These parameters may include the length, shape, width, etc. of the welding wire. Through image analysis and parameter extraction, the actual path and parameters in the welding process can be accurately obtained to improve the detection accuracy.

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

[0131] Specifically, according to the wire bonding strategy, determine the expected wire bonding path, such as the specific path of the wire bonding between the LED chip and the bracket, and set the expected wire bonding parameters, such as the length, shape, width, etc. of the wire bonding. 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 parameters provide a specific comparison standard, which helps to accurately judge the subsequent test results.

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

[0133] Specifically, by comparing the actual welding wire path with the expected welding wire path, the welding wire shape deviation is obtained to provide a basis for quality inspection. By comparing the actual welding wire path with the expected welding wire path, the deviation between the two is calculated, and the shapes of the actual and expected welding wire paths are compared to determine the deviation position and deviation amount. The algorithm can be used to calculate the deviation value, such as deviation distance, deviation angle, etc. By calculating the welding wire shape deviation, the deviation of the welding wire path can be accurately judged.

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

[0135] Specifically, by comparing the actual welding wire parameters with the expected welding wire parameters, the welding wire parameter deviation is obtained to provide a basis for quality inspection. By comparing the actual and expected welding wire parameters, such as length, angle, etc., the deviation value is determined. According to the parameter deviation, the welding wire control parameters can be adjusted in time to optimize the welding process and improve product quality.

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

[0137] Specifically, the shape deviation and parameter deviation of the welding wire are compared with the preset welding wire conditions, and specific judgment criteria can be set, such as the shape deviation does not exceed ±5%, the parameter deviation does not exceed ±3%, etc. The specific judgment criteria can be set according to different welding wire strategies;

[0138] Then, based on the comparison result, it is determined whether the quality of the bonding wire of the third LED semiconductor is qualified. By comparing the shape deviation and the parameter deviation, it is possible to accurately determine whether the quality of the bonding wire meets the preset conditions, thereby improving the accuracy of quality control.

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

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

[0141] S48. If not, adjust the wire bonding control parameters according to the wire bonding shape deviation and / or the wire bonding parameter deviation, and return to respond that the second LED semiconductor meets the preset die bonding condition, perform wire bonding on the second LED semiconductor according to the wire bonding strategy to obtain a third LED semiconductor.

[0142] Specifically, when the quality of the welding wire is unqualified, the welding wire control parameters are adjusted according to the welding wire shape deviation and / or welding wire parameter deviation to optimize the welding wire process. The specific problems in the welding wire process can be analyzed according to the welding wire shape deviation and welding wire parameter deviation, and the welding wire control parameters can be adjusted according to the analysis results, such as increasing the welding wire temperature, adjusting the welding wire pressure, etc.;

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

[0144] Preferably, see Figure 2 After the third LED semiconductor satisfies the preset wire bonding condition, dispensing the third LED semiconductor according to the dispensing strategy to obtain the target LED semiconductor, the method further includes:

[0145] S5, in response to the target LED semiconductor meeting the preset dispensing condition, performing a spectroscopic process on the target LED semiconductor according to a spectroscopic strategy to obtain actual optical parameters of the target LED semiconductor, wherein the spectroscopic strategy is obtained based on the unique identifier, and the actual optical parameters include color temperature parameters, light emission wavelength, and brightness parameters;

[0146] Specifically, before spectrometry, the target LED semiconductor after dispensing also needs to be inspected to determine whether the target LED semiconductor meets the preset dispensing conditions to ensure the quality of the third LED semiconductor. The preset dispensing conditions can be specific parameter requirements that need 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 must not exceed 0.1mm.

[0147] Subsequently, based on the unique identifier, the spectral strategy applicable to the current target LED semiconductor is obtained from the database to ensure that the spectral strategy matches the specific conditions of the LED semiconductor after dispensing. The spectral strategy includes spectral equipment settings, measurement parameters, etc., to ensure that the spectral results are accurate. The actual optical parameters of each target LED semiconductor can be obtained through spectral processing, that is, the optical properties of the LED semiconductor, including color temperature parameters, emission wavelength and brightness parameters. Through spectral 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, performing a spectroscopic process on the target LED semiconductor according to a spectroscopic strategy to obtain actual optical parameters of the target LED semiconductor includes:

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

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

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

[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 and providing a basis for subsequent comparison and evaluation.

[0153] S53, acquiring an expected glue dispensing size and an expected glue dispensing distribution according to the glue dispensing strategy, wherein the glue dispensing strategy includes glue dispensing control parameters and glue 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 quantity, dispensing frequency and dispensing speed. The amount of glue refers to the amount of glue required per unit area or length, usually in milliliters per square centimeter or milliliters per centimeter. The amount of glue can be determined based on product requirements and the viscosity of the glue to ensure that enough glue is applied to the workpiece to achieve the required bonding strength. The dispensing frequency indicates 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 characteristics of the glue, the size and shape of the workpiece, and production efficiency requirements. The dispensing speed refers to the speed at which the dispensing head moves during the dispensing process, usually in millimeters per second or inches per second. The selection of the dispensing speed needs to take into account factors such as the fluidity of the glue, the surface characteristics of the workpiece, and the speed of the production line to ensure that the glue is evenly applied to the surface of the workpiece.

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

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

[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 larger than the expected dispensing size, the deviation value is positive; if the actual dispensing size is smaller than the expected dispensing size, the deviation value is negative. Based on the dispensing deviation value, the degree of difference between the actual dispensing quality and the expected dispensing quality can be evaluated.

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

[0159] Specifically, the expected dispensing distribution is the ideal dispensing distribution calculated based on the target dispensing parameters. The expected dispensing distribution is determined based on the product design and dispensing requirements, usually taking into account factors such as the shape of the workpiece surface, the fluidity of the glue, and the working principle of the dispensing equipment. The actual dispensing distribution is the dispensing distribution actually observed during the production process, that is, the distribution of the glue actually applied on the workpiece surface. The actual dispensing distribution may be affected by many factors, such as the accuracy of the dispensing equipment, the fluidity 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 meets a preset glue dispensing condition according to the glue dispensing distribution deviation and the glue dispensing size deviation;

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

[0162] S57, if satisfied, performing a light splitting process 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 conditions are met, a spectroscopic process is performed to obtain the actual optical parameters of the target LED semiconductor;

[0164] S58. If not satisfied, adjust the glue dispensing control parameters according to the glue dispensing distribution deviation and / or the glue dispensing size deviation, and return to respond that the third LED semiconductor meets the preset wire bonding condition, and dispense glue to the third LED semiconductor according to the glue dispensing strategy to obtain the target LED semiconductor.

[0165] When the preset dispensing conditions are not met, attribution is made based on the dispensing distribution deviation and / or the dispensing size deviation, and the dispensing control parameters associated with the dispensing distribution deviation and / or the dispensing size deviation are determined. The corresponding dispensing control parameters are adjusted according to the deviation value, and the dispensing process is re-performed based on the adjusted parameters.

[0166] S6. Determine, based on the unique identifier, target LED semiconductors belonging to the same production batch and corresponding expected optical parameters;

[0167] Specifically, according to the unique identifier of the target LED semiconductor, the production batch information to which it belongs is obtained from the database, and according to the production batch information, the expected optical parameters of the batch of LED semiconductors, such as color temperature, emission wavelength and brightness, are obtained from the database. Accurately obtaining and recording the expected optical parameters of each production batch facilitates subsequent data analysis and problem tracing.

[0168] S7, screening finished LED semiconductors that meet preset light-splitting conditions from target LED semiconductors belonging to the same production batch according to the expected optical parameters;

[0169] Specifically, the preset spectral conditions, i.e., the optical parameter requirements for screening finished LED semiconductors, can be the color temperature range, luminous wavelength range, and brightness range obtained through the expected optical parameters, to screen out finished LED semiconductors that meet the requirements, mark the target LED semiconductors that meet the preset spectral conditions as finished products, and classify them.

[0170] Preferably, the step of screening finished LED semiconductors that meet preset light-splitting conditions from target LED semiconductors belonging to the same production batch according to the expected optical parameters includes:

[0171] S71, obtaining, according to the actual optical parameters, average values ​​of actual optical parameters of target LED semiconductors belonging to the same production batch;

[0172] Specifically, the target LED semiconductors belonging to the same production batch are a group of LED semiconductors manufactured within the same production cycle, with the same production conditions and processes, and the actual optical parameter mean is obtained by taking the average value of the actual optical parameters of each of the target LED semiconductors of the same production batch; the actual optical parameter mean 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, acquiring an overall optical parameter deviation value according to the actual optical parameter mean value and the expected optical parameter;

[0174] Specifically, by comparing the actual optical parameter mean with the expected optical parameter, the overall optical parameter deviation value is calculated to determine whether the product meets expectations. The calculation of the overall optical parameter deviation value can reveal the overall deviation in the production process and provide a basis for subsequent adjustments;

[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 mean value of the actual optical parameters is compared with the expected optical parameters. For example, the deviation value of the color temperature parameter is calculated by the formula: color temperature deviation = color temperature mean value - expected color temperature. The deviation values ​​of other optical parameters are calculated in a similar way. By calculating the deviation value of the overall optical parameters, the overall deviation in the production process can be accurately identified and potential problems can be discovered.

[0177] S74, 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;

[0178] Specifically, if the overall optical parameter deviation of the target LED semiconductor in the same production batch exceeds the preset standard, it means that there may be systemic problems in the production process, such as improper process parameter settings, raw material quality problems, etc., which lead to consistency deviations in the entire batch of LED semiconductor products; in the case of overall deviations, the production process is adjusted according to the preset processing rules to improve product quality. For example, if the color temperature deviation in the overall optical parameter deviation value is greater than the corresponding threshold, the laser power, time and frequency of the laser die bonding can be adjusted, or the temperature, time and adhesive ratio of the adhesive die bonding can be adjusted. If the brightness deviation is greater than the corresponding threshold, the ultrasonic vibration parameters, bonding pressure, temperature, workbench movement speed and welding time of the welding wire can be adjusted. If the emission wavelength deviation is greater than the corresponding threshold, the dispensing amount and dispensing material ratio can be adjusted.

[0179] 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:

[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 emission wavelength deviation value;

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

[0182] S742, when the absolute value of the brightness deviation value is greater than the brightness deviation threshold, taking the wire bonding strategy as a solution to be adjusted;

[0183] Specifically, the accuracy of the welding wire directly affects the efficiency of current conduction. If the position of the welding wire is not accurate or the connection is poor, it may cause uneven current distribution, affecting the current density of the LED chip, and further affecting its luminous efficiency and brightness; and the selection of welding wire materials and processes will affect its resistance value. If the resistance is high, part of the electric energy will be lost in the welding 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, the welding wire strategy is used as a solution to be adjusted;

[0184] S743, determining the parameters to be adjusted of the wire bonding strategy and the corresponding parameter adjustment values ​​according to the brightness deviation value, wherein the parameters to be adjusted of the wire bonding strategy include ultrasonic vibration parameters and bonding pressure parameters;

[0185] Specifically, according to the brightness deviation value, the parameters of the wire bonding strategy that need to be adjusted are determined. The parameters to be adjusted for the wire bonding strategy include ultrasonic vibration parameters and bonding pressure parameters. These parameters have a direct impact on the quality of the wire bonding and the electrical properties of the LED. The ultrasonic vibration parameters affect the frequency and amplitude of the ultrasonic vibration during the wire bonding process, thereby affecting the firmness and conductivity of the wire bonding. The bonding pressure parameters affect the mechanical pressure applied during the 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 parameters and / or bonding pressure parameters) 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 parameters and bonding pressure parameters during the wire bonding process. After the adjustment, trial production is first carried out to detect the adjusted LED brightness. 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, taking the die bonding strategy as a solution to be adjusted;

[0187] Specifically, the thermal conductivity of the solid crystal material will affect the heat dissipation efficiency of the LED chip. Poor heat dissipation will cause the chip temperature to rise, which will change the luminous efficiency and spectral characteristics of the LED, thereby affecting the color temperature. Adhesives with different compositions may 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 the curing process, thereby changing the optical properties of the chip. Similarly, temperature changes during the solid crystal process will affect the difference in thermal expansion coefficients between the chip and the substrate, which may cause 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, the solid crystal strategy is used as a solution to be adjusted;

[0188] S745, determining the parameters to be adjusted of the die bonding strategy and the corresponding parameter adjustment values ​​according to the color temperature deviation value, wherein when the die bonding method is laser die bonding, the parameters to be adjusted of the die bonding strategy include laser power, laser time and laser frequency; when the die bonding method is adhesive die bonding, the parameters to be adjusted of the die bonding strategy include die bonding temperature, die bonding time and adhesive ratio;

[0189] Specifically, the parameters of the solid crystal strategy that need to be adjusted are determined according to the color temperature deviation value. The parameters to be adjusted of the solid crystal strategy depend on the solid crystal method adopted, which can be laser solid crystal or adhesive solid crystal; when the solid crystal method is laser solid crystal, the parameters to be adjusted of the solid crystal strategy include laser power, laser time and laser frequency. Laser power affects the energy output of the laser during the laser solid crystal process. Too much or too little power may affect the color temperature. Laser time affects the length of time the laser acts on the LED chip. Too long or too short a time may cause color temperature deviation. The laser frequency affects the pulse frequency of the laser, which in turn affects the solid crystal effect and color temperature.

[0190] When the bonding method is bonding with an adhesive, the parameters to be adjusted of the bonding strategy include bonding temperature, bonding time and adhesive ratio. The bonding temperature affects the curing process of the adhesive. Too high or too low a temperature will affect the optical properties and color temperature of the LED chip. The bonding time affects the curing time of the adhesive. Too long or too short a time will affect the color temperature. Adhesives of different compositions have different effects on the light output and color temperature of the LED chip. Adjusting the composition ratio of the adhesive can optimize the color temperature.

[0191] Similarly, according to the size and direction of the color temperature deviation value (positive deviation or negative deviation), determine the adjustment direction to increase or decrease the laser power, laser time, laser frequency, etc. The adjustment range can be determined according to the empirical formula or the pre-established parameter adjustment table; then conduct trial production to test the adjusted LED color temperature. If the color temperature reaches the expected value, the parameter adjustment is successful; otherwise, continue to make further parameter adjustments based on 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, taking the dispensing strategy as a solution to be adjusted;

[0193] Specifically, the refractive index of the dispensing material will directly affect the propagation path of light. If the refractive index of the material is uneven, it may cause scattering and dispersion of light, thereby affecting the emission wavelength of the LED; if the glue is unevenly distributed or the thickness is inconsistent during the dispensing process, it may cause different propagation paths of light at different positions, thereby affecting the overall emission wavelength of the LED.

[0194] S747, determining the parameters to be adjusted of the dispensing strategy and the corresponding parameter adjustment values ​​according to the light emission wavelength deviation value, wherein the parameters to be adjusted of the dispensing strategy include the dispensing amount and the dispensing material ratio;

[0195] Specifically, the wavelength deviation reflects the difference between the actual LED wavelength and the expected wavelength. The amount of glue applied affects the thickness and uniformity of the glue layer, which in turn 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 the glue application material can optimize the wavelength of light.

[0196] Similarly, according to the size and direction (positive deviation or negative deviation) of the emission wavelength deviation value, determine the adjustment direction (increase or decrease the dispensing amount, or adjust the dispensing material ratio). The adjustment range can be determined according to the empirical formula or the pre-established parameter adjustment table. After the adjustment, conduct trial production and test the adjusted LED emission wavelength. If the emission wavelength reaches the expected value, the parameter adjustment is successful; otherwise, continue to make further parameter adjustments based on the newly measured emission wavelength deviation value.

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

[0198] Specifically, since the dimensions and numerical ranges of brightness, color temperature, and luminous wavelength are different, these deviation values ​​need to be normalized so that they can be compared under the same standard. The adjustment order is determined according to the deviation value after normalization. The larger the deviation value, the priority is adjusted. For example, if the brightness deviation value after normalization is the largest, the wire bonding strategy related to brightness is adjusted first.

[0199] S749: Adjust the schemes to be adjusted in sequence according to the adjustment sequence and the parameter adjustment values.

[0200] Specifically, from the previous steps, the parameter adjustment values ​​of each solution have been determined. These adjustment values ​​are calculated based on the specific deviation values. According to the determined adjustment order, the adjustment schemes to be adjusted are adjusted in turn. After each parameter adjustment, trial production and testing are carried out to ensure that each adjustment step effectively reduces the deviation of the optical parameters and ultimately achieves the expected optical performance. All data during the adjustment process are recorded for future optimization and reference.

[0201] S75. If there is no overall deviation, obtaining a sample standard deviation of the target LED semiconductors of the same production batch according to the actual optical parameter mean and the actual optical parameter;

[0202] Specifically, the sample standard deviation of each target LED semiconductor in the batch is calculated based on the actual optical parameters and the mean. The sample standard deviation is a statistical indicator to measure the dispersion of a set of data. It represents the average distance of the data points around the mean. The larger the standard deviation, the greater the dispersion of the data; the smaller the standard deviation, the more concentrated the data.

[0203] S76, judging whether there are abnormal LED semiconductors in the target LED semiconductors of the same production batch according to the sample standard deviation;

[0204] Specifically, the standard score (Z-Score) can be used to quantify the degree of deviation of each LED semiconductor optical parameter from the sample mean. The calculation of the standard score belongs to the existing technology and will not be described in detail here. According to the calculated Z-Score, it is determined whether there are abnormal LED semiconductors. Generally, if the absolute value of the Z-Score exceeds a certain threshold (such as 2 or 3), it can be considered an abnormal value.

[0205] S77, if there is an abnormal LED semiconductor, process the abnormal LED semiconductor according to a preset individual abnormality processing rule;

[0206] Specifically, if there are abnormal LED semiconductors, the abnormal LED semiconductors are 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 semiconductors. These rules can be set according to the production process, quality control standards and actual experience. For example and not limitation, the preset individual exception processing rules include re-testing the detected abnormal LED semiconductors first to confirm whether the abnormality does exist, judging whether the abnormality can be corrected by adjusting the control parameters of each link according to the type and severity of the abnormality, and reworking the LED semiconductors that are confirmed to be abnormal and cannot be corrected by adjusting the process parameters; 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 the overall deviation, systematic problems in the production process can be quickly discovered, and process parameters can be adjusted in a timely manner to ensure the stability and consistency of product quality. Overall deviation can help identify trends and patterns in the production process and provide data support for process optimization. For example, by analyzing the overall deviation, it can be determined whether production equipment or process flow needs to be adjusted. Analyzing individual deviation data and finding the cause of the deviation can help improve the production process and reduce the production of abnormal products. For example, by analyzing individual deviations, it can be determined whether a specific process step needs to be adjusted.

[0208] By monitoring both overall deviations and individual deviations, production management can fully grasp the product quality status from both macro and micro levels and achieve total quality management. When overall deviations are found, systematic adjustment measures can be taken to optimize the production process; when individual deviations are found, a quick response can be made to handle abnormal products to avoid affecting the overall quality.

[0209] Long-term accumulation of data on overall and individual deviations, 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, it is first necessary to obtain the ratio of the number of abnormal LED semiconductors to the total number of LED semiconductors in the production batch. 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, removing the abnormal LED semiconductor;

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

[0215] S773, when the ratio is greater than the preset ratio, obtaining individual optical parameter deviation values ​​of each abnormal LED semiconductor 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 is required. Next, based on the expected optical parameters and the actual optical parameters, the individual optical parameter deviation values ​​of each abnormal LED semiconductor are obtained. These deviation values ​​show the difference between each abnormal LED semiconductor and the expected performance.

[0217] S774, performing statistical analysis on the individual optical parameter deviation values ​​to determine the 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 emission wavelength parameter;

[0218] Specifically, statistical analysis of these individual optical parameter deviation values ​​can determine the key optical deviation parameters of abnormal LED semiconductors, which may include one of brightness parameters, color temperature parameters, and emission wavelength parameters. 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 of the finished LED semiconductors 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 glue 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 out the key control deviation parameters that cause the optical deviation. These control deviation parameters include one of the die bonding control parameters, the wire bonding control parameters, and the glue dispensing control parameters;

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

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

[0223] For the second inspection image, its main features include the position of the welding wire, the size and shape of the welding spot, the routing of the welding wire, etc.;

[0224] For the third inspection image, its main features include the distribution of glue dots, the size and shape of glue drops, the thickness of the glue layer, etc.;

[0225] The extracted features are compared and analyzed, and the feature values ​​of abnormal LED semiconductors and finished LED semiconductors are compared to calculate the difference value of each feature. The difference value can be expressed as an absolute difference or a relative difference. All the difference values ​​are clustered to identify which features have the most significant differences. This can be achieved by clustering algorithms (such as K-means, DBSCAN) to find the feature clusters with the largest differences. The clustering results are statistically analyzed to determine the main control deviation parameters. For example, if the difference in the die bonding position is the most significant in the cluster, the die bonding control parameter may be the main deviation parameter.

[0226] Preferably, the comparing 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 to obtain key control deviation parameters includes:

[0227] S7751, preprocessing the first detection images, the second detection images, and the third detection images 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 glue dispensing;

[0229] Preprocessing includes grayscale processing, noise removal, image enhancement, edge detection and image normalization. Grayscale can reduce the complexity of image processing, retain important shape and texture features, apply filters (such as Gaussian filtering, median filtering, etc.) to remove noise in the image and enhance image quality, use contrast stretching or histogram equalization to enhance image contrast and make features more obvious, then edge detection algorithm detects edges in the image and extracts important contour information, and finally normalizes the image so that different images can be compared at the same scale. Normalization can eliminate brightness and contrast differences between different images.

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

[0231] Specifically, the processing process of this step is the same as step S7751, except that the objects processed are different. The same preprocessing steps ensure the consistency and comparability of the images. If different preprocessing methods are used for images of abnormal LED semiconductors and finished LED semiconductors, additional variables and errors may be introduced, affecting the accuracy of comparative analysis. Through consistent preprocessing steps, all images are ensured to be processed under the same conditions, eliminating systematic deviations introduced by different processing methods.

[0232] S7753, comparing each image in the first detection image set with the first target comparison image to obtain a deviation solidification feature of each image in the first detection image set;

[0233] Specifically, the first detection image and the first target comparison image of each abnormal LED semiconductor are aligned to ensure that the two are compared in the same coordinate system, and the alignment can be performed using image registration technology. Extract the solid crystal related features from each image in the first detection image set and the first target comparison image, compare the solid crystal features of each abnormal LED semiconductor with the solid crystal features in the target comparison image, and calculate the difference between them. The difference value may include position deviation, size deviation, shape deviation, etc. The solid crystal feature deviation of each image is recorded to form a solid crystal 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 comparison image to obtain deviation weld line features of each image in the second detection image set;

[0235] Similarly, the second detection image of each abnormal LED semiconductor is aligned with the second target comparison image to ensure that the two are compared in the same coordinate system, and the wire bonding features of each abnormal LED semiconductor are compared with the wire bonding features in the target comparison image to calculate the difference between them. The difference value may include position deviation, length deviation, angle deviation, and curvature deviation. The wire bonding feature deviation of each image is recorded to form a wire bonding feature deviation data set. 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 a deviation dispensing feature;

[0237] Specifically, extract dispensing-related features from each image in the third detection image set and the third target comparison image. These features may include the location, size, uniformity, etc. of the dispensing. Compare the dispensing features of each abnormal LED semiconductor with the dispensing features in the target comparison image, and calculate the difference between them. The difference value may include position deviation, size deviation, uniformity deviation, etc., to obtain the deviation dispensing feature;

[0238] S7756, 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;

[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 data set containing multidimensional features. Each data point represents the feature deviation of an abnormal LED semiconductor. According to the characteristics of the data, an appropriate clustering algorithm is selected, such as K-means, DBSCAN, hierarchical clustering, etc. K-means clustering is a common choice because it is simple and efficient. In order to ensure that the scales of different features are consistent, the feature data is standardized so that the mean of each feature is 0 and the standard deviation is 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 feature deviations that dominate in each cluster are identified, and these feature deviations are the first significant deviation features. The first significant deviation features refer to those features in which the deviations of specific features are most obvious and concentrated in abnormal LED semiconductors.

[0240] S7757, performing correlation analysis on the first significant deviation feature and the key optical deviation parameter, a second significant deviation feature;

[0241] Specifically, the first significant deviation feature and the key optical deviation parameter data are organized into a data set. Each data point contains a significant deviation feature and a corresponding optical deviation parameter. Select an appropriate correlation analysis method, such as the Pearson correlation coefficient, the Spearman rank correlation coefficient, etc. The Pearson correlation coefficient is applicable to linear relationships, and the Spearman rank correlation coefficient is applicable to nonlinear relationships. The correlation coefficient between each significant deviation feature and the key optical deviation parameter is calculated using the selected method. The correlation coefficient range is [-1,1]. The closer the value is to 1 or -1, the stronger the correlation is; the closer the value is to 0, the weaker the correlation is. According to the absolute value of the correlation coefficient, screen out significant deviation features that have a strong correlation with the key optical deviation parameters. The stronger the correlation, the more likely these features are to be the main cause of the optical deviation.

[0242] S7758. Determine the key control deviation parameter based on the second significant deviation feature.

[0243] According to the production process and characteristic 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 parameter (such as wire pressure, ultrasonic vibration frequency) may be the key control deviation parameter.

[0244] Through the above steps, using cluster analysis, correlation analysis and other methods, systematically determining and adjusting key control deviation parameters 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 plans for actual production.

[0245] S776, determining a to-be-adjusted scheme and corresponding adjustment parameters according to the key optical deviation parameters and the key control deviation parameters;

[0246] According to the identified key optical deviation parameters and key control deviation parameters, determine the adjustment plan and the corresponding adjustment parameters. This step is to link the optical deviation and the control deviation to find an adjustment plan that can solve the problem. The key optical deviation parameters are obtained by comparing the expected value and the individual actual parameters, which can accurately point out the specific problems that occur in the production process. For example, the deviation of brightness, color temperature or luminous wavelength. The key control deviation parameters are obtained by comparing the detection images, which can clarify the specific deviations of process parameters (such as die bonding, wire bonding, dispensing, etc.) in production. This dual 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 the key optical deviation parameters and the 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 the key optical deviation parameters and the key control deviation parameters is established. Regression analysis can help quantify the impact of control parameters on optical parameters. According to the relationship model, determine the direction and amplitude of adjusting the key control deviation parameters. For example, if the brightness deviation is negative (lower than expected), and the regression analysis shows that increasing the wire pressure can improve the brightness, then adjust the wire pressure upward.

[0248] After adjusting the plan, conduct experiments or small batch production to verify the effect of the adjustment plan. Measure the adjusted optical parameters to ensure that the adjusted parameters reach the expected values.

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

[0250] Adjust the adjustment plan based on these adjustment parameters to 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 processed to improve product quality and production efficiency.

[0251] S78, treating the target LED semiconductors other than the abnormal LED semiconductors as finished LED semiconductors;

[0252] Specifically, the identified abnormal LED semiconductors are removed from the target LED semiconductor list. The numbers and test results of these abnormal LED semiconductors are recorded for further analysis and processing. After the abnormal LED semiconductors are removed, the remaining target LED semiconductors are finished LED semiconductors that meet the quality requirements. The optical parameters of these finished LED semiconductors are within the expected range and have been strictly tested and verified.

[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 optical parameter detection and screening of the finished LED semiconductors, a series of post-processing steps are required to ensure that they maintain quality and consistency during packaging and storage. Taping refers to loading LED semiconductors into a tape carrier for subsequent storage, transportation and use. During the taping process, LED semiconductors are usually arranged on a tape carrier according to certain specifications and quantities, and are automatically fixed and packaged using a machine. Warehousing means storing LED semiconductors in a designated warehouse or storage area 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, obtaining a braiding scheme according to the unique identifier of the finished LED semiconductor, wherein the braiding scheme includes a braiding method and a braiding position;

[0259] Specifically, the taping scheme includes the taping method and the 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 in the 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, braiding the finished LED semiconductor according to the braiding scheme to obtain an LED light strip;

[0261] Specifically, the finished LED semiconductors are arranged and fixed on the tape according to the tape plan. The tape processing requires precise control to ensure that each LED semiconductor is in the correct position to avoid damage or misalignment.

[0262] S83, performing quality inspection on the LED light strip to obtain a quality inspection result, wherein the quality inspection includes optical inspection, electrical inspection and mechanical inspection;

[0263] Specifically, first test the optical properties of the LED light strip, including parameters such as brightness, color temperature, and luminous wavelength. Use professional equipment to measure these optical parameters to ensure that they meet the expected standards. Test the electrical properties of the LED light strip, including parameters such as current, voltage, and power. Ensure that the electrical connection is stable without short circuits or open circuits. Test the mechanical properties of the LED light strip, including the firmness of the braiding and the physical integrity of the LED semiconductor, to ensure that the LED semiconductor is not damaged or its performance is affected during the braiding process. The quality inspection results are obtained based on the above quality tests.

[0264] S84, generating a unique identifier corresponding to the LED light strip that has passed the quality inspection;

[0265] For LED light strips that pass quality inspection, a new unique identifier is generated. This identifier can be used to track and manage the subsequent processes of the LED light strip. The generated unique identifier is marked on the corresponding LED light strip. The marking method can be labeling, laser engraving, etc.

[0266] S85. According to the unique identifier and the corresponding quality inspection result, the LED light strip is put into storage.

[0267] Specifically, confirm the quality inspection results of each LED light bar to ensure that it meets the warehousing standards. Light bars that fail the quality inspection need to be reworked or scrapped. Register the LED light bars that meet the standards for warehousing. Record the unique identifier, quality inspection results, production batch and other information of each light bar. Store the LED light bars in the designated warehouse location according to the warehouse management process. Ensure that the warehouse environment meets the storage requirements of LED light bars (such as temperature, humidity, etc.).

[0268] Through the above steps, the traceability analysis of LED semiconductor production data is completed, including taping, quality inspection and warehousing. Each step requires precise operation and detailed records to ensure the quality and consistency of the finished LED semiconductors. At the same time, the unique identifier is used to track and manage each LED light bar to ensure the transparency and traceability of the production process.

[0269] Example 2

[0270] See also Figure 3 The embodiment of the present invention provides a system for tracing and analyzing the production data of LED semiconductors, the system comprising: a processing preprocessing module for performing pre-processing on the initial LED semiconductors and the bracket, a solid crystal module for solidifying the LED semiconductors according to the solid crystal strategy, a welding module for welding the LED semiconductors according to the welding wire strategy, including the control and adjustment of the welding wire path and welding wire parameters, a dispensing module for dispensing the LED semiconductors according to the dispensing strategy, a sensor module for real-time monitoring and collecting key parameters in the LED production process, a power supply module for supplying energy to the system, and a controller for executing the LED semiconductor production data tracing and analysis method described in Example 1.

[0271] The processing pre-treatment module, die bonding module, welding module and dispensing module work together to achieve a high degree of automation in the production process, reduce manual intervention and improve production efficiency. The sensor module monitors key parameters in real time, and the controller automatically adjusts the die bonding, wire bonding and dispensing parameters according to the detection results to ensure 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 to adapt to different types of LED semiconductor production.

[0272] In summary, the system achieves high automation, precise control and real-time adjustment of the production process through integrated automation modules and control methods, improves production efficiency and product quality, reduces production costs, and ensures the stability and flexibility of the production process. It is an efficient, reliable and economical LED semiconductor production solution.

[0273] It should be clear that the present invention is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present invention.

[0274] The functional blocks shown in the above-described 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 function card, etc. When implemented in software, the elements of the present invention are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "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 segment 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 invention describe some methods or systems based on a series of steps or devices. However, the present invention 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 a different order from the embodiments, or several steps can be performed simultaneously.

[0276] The above is only a specific implementation of the present invention. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the system, module and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. It should be understood that the protection scope of the present invention is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be covered within the protection scope of the present invention.

Claims

1. A method for tracing and analyzing LED semiconductor production data, characterized in that: The method comprises: Obtaining a braiding scheme according to a unique identifier of a finished LED semiconductor, wherein the braiding scheme includes a braiding method and a braiding position; Performing tape processing on the finished LED semiconductor according to the tape braiding scheme to obtain an LED light strip; Performing quality inspection on the LED light strip to obtain a quality inspection result, wherein the quality inspection includes optical inspection, electrical inspection and mechanical inspection; Generate a unique identifier corresponding to the LED light strip that has passed the quality inspection; According to the unique identifier and the corresponding quality inspection result, the LED light strip is put into storage to obtain an LED product.

2. The LED semiconductor production data tracing and analysis method according to claim 1, characterized in that: Before obtaining a braiding scheme according to the unique identifier of the finished LED semiconductor, wherein the braiding scheme includes a braiding method and a braiding position, the following steps are further included: Performing a pre-process on the initial LED semiconductor and the bracket to obtain a first LED semiconductor, wherein the first LED semiconductor is placed at a designated position of the bracket, a surface of the bracket has a unique identifier set by laser coding, and the pre-process includes a crystal expansion process and a dehumidification process of the bracket; Performing die bonding on 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; According to the die bonding strategy, obtaining a die bonding detection target of the second LED semiconductor, 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; Acquire a first detection image including the second LED semiconductor; 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 the 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; when the die bonding method is an adhesive die bonding, the die bonding detection result includes a glue drop size deviation and a glue drop distribution deviation; According to the die bonding strategy, obtaining preset die bonding conditions; According to the die-bonding detection result, determining whether the second LED semiconductor satisfies the preset die-bonding condition; If the conditions are met, wire bonding is performed on the second LED semiconductor according to the wire bonding strategy to obtain a third LED semiconductor; If not satisfied, adjusting the die bonding control parameter according to the die bonding detection result, and returning to the step of performing die bonding on the first LED semiconductor according to the die bonding strategy to obtain a second LED semiconductor; In response to the third LED semiconductor satisfying the preset wire bonding condition, dispensing is performed on the third LED semiconductor according to a dispensing strategy to obtain a target LED semiconductor, wherein the dispensing strategy is obtained based on the unique identifier.

3. The LED semiconductor production data traceability analysis method according to claim 2, characterized in that: In response to the third LED semiconductor meeting the preset wire bonding condition, dispensing glue on the third LED semiconductor according to the dispensing strategy to obtain the target LED semiconductor includes: Acquire a second detection image including the third LED semiconductor; Acquire an actual welding wire path and actual welding wire parameters according to the second detection image; According to the wire bonding strategy, obtaining an expected wire bonding path and expected wire bonding parameters, wherein the wire bonding strategy includes a wire bonding layout and a wire bonding control parameter; Obtaining a welding wire shape deviation according to the actual welding wire path and the expected welding wire path; Obtaining a wire bonding parameter deviation according to the actual wire bonding parameter and the expected wire bonding parameter; Determining whether the third LED semiconductor meets a preset wire bonding condition according to the wire bonding shape deviation and the wire bonding parameter deviation; If the conditions are met, dispensing glue on the third LED semiconductor according to the dispensing strategy to obtain a target LED semiconductor; If not, the wire bonding control parameters are adjusted according to the wire bonding shape deviation and / or the wire bonding parameter deviation, and in response to the second LED semiconductor meeting the preset die bonding conditions, the second LED semiconductor is wire bonded according to the wire bonding strategy to obtain a third LED semiconductor.

4. The LED semiconductor production data traceability analysis method according to claim 3, characterized in that: After dispensing glue on the third LED semiconductor according to the dispensing strategy in response to the third LED semiconductor meeting the preset wire bonding condition to obtain the target LED semiconductor, the method further includes: In response to the target LED semiconductor meeting the preset dispensing condition, the target LED semiconductor is subjected to a spectroscopic process according to a spectroscopic strategy to obtain actual optical parameters of the target LED semiconductor, wherein the spectroscopic strategy is obtained based on the unique identifier, and the actual optical parameters include color temperature parameters, light emission wavelength, and brightness parameters; Determining target LED semiconductors belonging to the same production batch and corresponding expected optical parameters based on the unique identifier; According to the expected optical parameters, finished LED semiconductors that meet preset light-splitting conditions are screened from target LED semiconductors belonging to the same production batch.

5. The LED semiconductor production data traceability analysis method according to claim 4, characterized in that: In response to the target LED semiconductor meeting the preset dispensing condition, performing a spectroscopic process on the target LED semiconductor according to a spectroscopic strategy to obtain actual optical parameters of the target LED semiconductor, including: Acquire a third detection image including the target LED semiconductor; According to the third detection image, the actual dispensing size and the actual dispensing distribution are obtained: According to the dispensing strategy, an expected dispensing size and an expected dispensing distribution are obtained, wherein the dispensing strategy includes dispensing control parameters and dispensing distribution; Obtaining a dispensing size deviation according to the actual dispensing size and the expected dispensing size; Obtain dispensing distribution deviation according to expected dispensing distribution and actual dispensing distribution; According to the dispensing distribution deviation and the dispensing size deviation, determining whether the target LED semiconductor meets the preset dispensing condition; If the conditions are met, the target LED semiconductor is subjected to a light splitting process according to a light splitting strategy to obtain actual optical parameters of the target LED semiconductor; If not, the glue dispensing control parameters are adjusted according to the glue dispensing distribution deviation and / or the glue dispensing size deviation, and the third LED semiconductor is glued according to the glue dispensing strategy in response to the third LED semiconductor satisfying the preset welding wire condition to obtain the target LED semiconductor.

6. The LED semiconductor production data traceability analysis method according to claim 5, characterized in that: The step of screening, according to the expected optical parameters, finished LED semiconductors that meet preset light-splitting conditions from target LED semiconductors belonging to the same production batch comprises: According to the actual optical parameters, obtaining an average value of the actual optical parameters of the target LED semiconductors belonging to the same production batch; Obtaining an overall optical parameter deviation value according to the actual optical parameter mean value and the expected optical parameter; According to the overall optical parameter deviation value, determining whether there is an overall deviation in the target LED semiconductors belonging to the same production batch; 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; If there is no overall deviation, obtaining a sample standard deviation of the target LED semiconductors of the same production batch according to the actual optical parameter mean and the actual optical parameter; Determining whether there are abnormal LED semiconductors in the target LED semiconductors of the same production batch according to the sample standard deviation; If there is an abnormal LED semiconductor, the abnormal LED semiconductor is processed according to a preset individual abnormality processing rule; treating the target LED semiconductors other than the abnormal LED semiconductors as finished LED semiconductors; If there are no abnormal LED semiconductors, all of the target LED semiconductors are regarded as finished product LED semiconductors.

7. The LED semiconductor production data traceability analysis method according to claim 6, characterized in that: 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, comprises: 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; 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; Determining the parameters to be adjusted of the wire bonding strategy and the corresponding parameter adjustment values ​​according to the brightness deviation value, wherein the parameters to be adjusted of the wire bonding strategy include ultrasonic vibration parameters and bonding pressure parameters; When the absolute value of the color temperature deviation value is greater than the color temperature deviation threshold, the die bonding strategy is used as a solution to be adjusted; Determine the parameters to be adjusted of the die bonding strategy and the corresponding parameter adjustment values ​​according to the color temperature deviation value, wherein when the die bonding method is laser die bonding, the parameters to be adjusted of the die bonding strategy include laser power, laser time and laser frequency; when the die bonding method is adhesive die bonding, the parameters to be adjusted of the die bonding strategy include die bonding temperature, die bonding time and adhesive ratio; When the absolute value of the light emitting wavelength deviation value is greater than the light emitting wavelength deviation threshold, the dispensing strategy is used as a solution to be adjusted; Determining the parameters to be adjusted of the dispensing strategy and the corresponding parameter adjustment values ​​according to the luminous wavelength deviation value, wherein the parameters to be adjusted of the dispensing strategy include the dispensing amount and the dispensing material ratio; When the number of the to-be-adjusted schemes is greater than one, determining an adjustment order according to the brightness deviation value, the color temperature deviation value, and the light emission wavelength deviation value after normalization; According to the adjustment sequence and the parameter adjustment value, the scheme to be adjusted is adjusted in sequence.

8. The LED semiconductor production data traceability analysis method according to claim 6, characterized in that: If there is an abnormal LED semiconductor, the abnormal LED semiconductor is processed according to a preset individual abnormality processing rule, including: Obtaining a ratio of the number of the 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, removing the abnormal LED semiconductor; When the ratio is greater than the preset ratio, obtaining individual optical parameter deviation values ​​of each of the abnormal LED semiconductors according to the expected optical parameters and the actual optical parameters; Performing statistical analysis on the individual optical parameter deviation values ​​to determine the 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 emission wavelength parameter; Comparing 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 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 glue dispensing control parameter; Determining a scheme to be adjusted and corresponding adjustment parameters according to the key optical deviation parameters and the key control deviation parameters; The scheme to be adjusted is adjusted according to the adjustment parameters.

9. The LED semiconductor production data tracing and analysis method according to claim 8, characterized in that: The step of comparing 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 to obtain key control deviation parameters includes: 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; Preprocessing the first detection image, the second detection image, and the third detection image of any of the finished LED semiconductors to obtain a first target comparison image, a second target comparison image, and a third target comparison image, respectively; Comparing each image in the first detection image set with the first target comparison image to obtain a deviation solidification feature of each image in the first detection image set; Comparing each image in the second detection image set with the second target comparison image to obtain a deviation weld line feature of each image in the second detection image set; Comparing each image in the third detection image set with the third target comparison image to obtain a deviation dispensing feature; 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; performing a correlation analysis on the first significant deviation feature and the key optical deviation parameter, a second significant deviation feature; The key control deviation parameter is determined according to the second significant deviation feature.

10. A LED semiconductor production data traceability analysis system, characterized in that: The system is used to execute the LED semiconductor production data traceability analysis method according to any one of claims 1 to 9.

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