Integrated circuit board manufacturing and packaging method and system based on laser measurement

Abstract

The invention relates to the technical field of integrated circuit board manufacturing and packaging, and discloses an integrated circuit board manufacturing and packaging method and system based on laser measurement, and the method comprises the steps: sensing arrangement: employing a focusing lens to focus a laser beam to the surface of a substrate, arranging a reflector and a spectroscope to guide the laser beam to the surface of the substrate, meanwhile, a sensor is arranged in the packaging equipment for monitoring; signal conversion: receiving a reflected light signal by adopting a silicon photodiode, and converting the reflected light signal into an electric signal; data acquisition: acquiring electric signal data, environment data and substrate information data; data calculation: calculating a warping prediction index and an offset prediction index; data evaluation: evaluating the packaging effect index; and comprehensive judgment: according to the packaging result index, judging whether automatic adjustment and compensation need to be carried out, and under the condition that automatic adjustment and compensation need to be carried out, calculating a compensation coefficient to carry out automatic compensation, so that active suppression of the substrate warping offset defect and intelligent improvement of the process efficiency are realized.

Description

Technical Field

[0001] This invention relates to the field of integrated circuit board manufacturing and packaging technology, specifically to an integrated circuit board manufacturing and packaging method and system based on laser measurement. Background Technology

[0002] Integrated circuit boards (IC substrates) are core components in electronic devices used to carry, connect, and support electronic components. They integrate conductive paths, insulating layers, and pads onto an insulating substrate (such as fiberglass, ceramic, or composite materials) using printed circuit or etching techniques, achieving electrical interconnection and mechanical fixation of components such as chips, resistors, and capacitors. Their core functions include: 1) providing signal transmission channels and power distribution networks for chips; 2) achieving high-density interconnection through multi-layer wiring, improving the performance of electronic devices; and 3) protecting chips from environmental influences (such as humidity and temperature changes) and assisting in heat dissipation within the package. Depending on their application, integrated circuit boards can be classified as single-layer, double-layer, or multi-layer boards (such as HDI high-density interconnect substrates), and are widely used in consumer electronics, communication equipment, computer hardware, and high-end chip packaging (such as FCBGA and CSP). Their manufacturing involves precision photolithography, electroplating, drilling, and surface treatment processes, requiring micron-level precision, low impedance, and high reliability. They are the foundation for the miniaturization and intelligentization of modern electronic systems.

[0003] Integrated circuit board manufacturing and packaging is a precise process that transforms microcircuits on semiconductor wafers into independent functional devices, encompassing two major stages: front-end wafer fabrication and back-end packaging. Front-end processes are based on high-purity silicon wafers, using nanoscale processing technologies such as photolithography (DUV / EUV light sources), ion implantation, etching, and thin-film deposition (CVD / PVD) to construct multi-layered circuit structures. Back-end packaging involves dicing and thinning of qualified chips, and using wire bonding (gold / copper wire interconnection) or flip-chip (solder ball interconnection) technologies to achieve electrical connections. Finally, epoxy molding compound (EMC) is used for die casting to form a protective shell, ultimately achieving advanced packaging forms such as BGA and WLCSP. The entire process integrates materials science, precision mechanics, and thermodynamic design, involving micron-level processing accuracy (±1μm) and rigorous reliability testing (temperature cycling, mechanical shock, etc.), enabling chips to possess mechanical protection, signal transmission, and heat dissipation functions, supporting various application needs from consumer electronics to high-performance computing. Modern 3D packaging and Chiplet technology further drive continuous innovation in the semiconductor industry through TSV (Through Silicon Vias) and heterogeneous integration.

[0004] In the manufacturing and packaging of integrated circuit boards, substrate warpage is a core defect affecting alignment accuracy and bonding yield. Substrate warpage is affected by a variety of factors, and existing solutions mostly rely on post-processing inspection, lacking proactive suppression of the warpage mechanism, resulting in low production efficiency, difficulty in improving quality, and increased losses. Summary of the Invention

[0005] (a) Technical problems to be solved

[0006] To address the shortcomings of existing technologies, this invention provides a laser-based integrated circuit board manufacturing and packaging method and system. Through high-precision laser sensing, multi-source data fusion, and a dynamic closed-loop compensation mechanism, it achieves proactive suppression of substrate warpage and displacement defects and intelligent improvement of process efficiency. It directly intervenes in the packaging results, avoiding the lag of post-production inspection and reducing the probability of bonding failure at its source. Compared to traditional experience-based adjustments, it significantly improves compensation accuracy and efficiency, reduces rework due to warpage or displacement, and lowers material waste. Furthermore, the closed-loop feedback mechanism avoids repeated inspections and manual intervention, accelerating the production cycle and promoting intelligent manufacturing upgrades.

[0007] (II) Technical Solution

[0008] To achieve the above objectives, the present invention provides the following technical solution: a method for manufacturing and packaging an integrated circuit board based on laser measurement, comprising the following steps:

[0009] Step 1, Sensor Arrangement: A high-precision focusing lens is used to focus the laser beam onto the substrate surface. A reflector and a beam splitter are arranged to guide the laser beam to the substrate surface. At the same time, sensors are arranged inside the packaging equipment to monitor parameters.

[0010] Step 2, Signal Conversion: A silicon photodiode is used to receive the reflected light signal and convert the information of the reflected light into an electrical signal;

[0011] Step 3: Data Acquisition: Acquire electrical signal data, environmental data, and substrate information data;

[0012] Step 4: Data Calculation: Calculate the warping prediction index and the offset prediction index based on the data obtained in Step 3;

[0013] Step 5: Data Evaluation: Calculate the encapsulation effectiveness index based on the warpage prediction index and the offset prediction index;

[0014] Step Six: Comprehensive Judgment: Determine whether automatic adjustment and compensation are needed based on the packaging result index. If automatic adjustment and compensation are needed, calculate the compensation coefficient and perform automatic compensation.

[0015] Preferably, the numbering expression for the electrical signal data XHsj is:

[0016] XHsj=Xgq, Xxw, Xbw, Xzs;

[0017] In the expression, Xgq represents light intensity, Xxw represents phase change, Xbw represents spot position deviation, and Xzd represents vibration intensity.

[0018] Preferably, the numbering expression for the environmental data HJsj is:

[0019] HJsj=Hwd, Hsd, Hqy, Hzd;

[0020] In the expression, Hwd represents temperature, Hsd represents humidity, and Hqy represents air pressure.

[0021] Preferably, the numbering expression for the substrate information data JBsj is:

[0022] JBsj=Jhd, Jmj, Jpz, Jtm, Jxs, Jrd;

[0023] In the expression, Jhd represents the substrate thickness, Jmj represents the substrate area, Jpz represents the substrate thermal expansion coefficient, Jtm represents the substrate elastic modulus, Jxs represents the substrate hygroscopicity parameter, and Jrd represents the substrate thermal conductivity.

[0024] Preferably, the formula for calculating the warpage prediction index QQyc is as follows:

[0025]

[0026] In the calculation formula, Hwd t The amount representing the change in temperature, This represents the thermal deformation of the substrate caused by temperature changes. When the temperature rises, the substrate will warp due to thermal expansion. The larger the coefficient of thermal expansion, the more significant the temperature change, and the larger the substrate area, the more obvious the thermal deformation.

[0027] It represents the elastic deformation of the substrate under stress or external force. The greater the deviation of the spot position, the more significant the substrate deformation, the greater the elastic modulus, the harder the material, the smaller the deformation, the greater the thickness, the stronger the bending resistance, and the smaller the deformation.

[0028] Jxs*Hsd represents the expansion and deformation of the substrate due to moisture absorption. The higher the humidity, the greater the hygroscopic parameter, and the more obvious the expansion of the substrate after absorbing moisture, leading to warping.

[0029] α*Xgq represents the effect of correcting light intensity on warp measurement. Too high or too low light intensity may cause the measurement signal to be distorted. α represents the correction factor for light intensity.

[0030] β*Xxw represents the effect of the correction phase change on the warp measurement, and β represents the correction factor for the laser phase change.

[0031] γ*Xzd represents the effect of vibration intensity on warp measurement. Vibration may cause fluctuations in the measurement signal, and γ represents the correction factor for vibration intensity.

[0032] δ*Hqy represents the effect of corrected air pressure on warpage measurement. Air pressure changes may affect the thermal conductivity of the substrate or the stability of the measurement signal. δ represents the air pressure correction factor.

[0033] Preferably, the formula for calculating the offset prediction index PYyc is:

[0034]

[0035] In the calculation formula, This represents the coupling effect between the corrected spot position deviation and the substrate elastic modulus, and the effect of normalized substrate thickness.

[0036] θ*Xgq represents the effect of correcting light intensity on the migration, where θ represents the weight of light intensity, used to adjust the contribution of light intensity to the migration prediction;

[0037] This represents the effect of the corrected phase change on the offset. The weights representing the amount of phase change indicate the degree of influence of the optical phase change on the offset prediction.

[0038] μ*Xzd represents the effect of corrected vibration intensity on migration, where μ represents the weight of vibration intensity, used to adjust the contribution of vibration intensity to migration prediction.

[0039] Preferably, the formula for calculating the encapsulation effect index XGzs is:

[0040] XGzs=ρ1*QQyc+ρ2*PYyc;

[0041] In the calculation formula, ρ1 represents the weight of the warping prediction index, ρ2 represents the weight of the offset prediction index, and ρ1+ρ2=1.

[0042] Preferably, the calculated result of the packaging achievement index is compared with the packaging achievement index threshold. If the packaging achievement index is greater than the packaging achievement index threshold, automatic adjustment and compensation are required.

[0043] Preferably, the formula for calculating the compensation coefficient BCxs is:

[0044] BCxs = XGzs - XGyz;

[0045] In the calculation formula, XGyz represents the maximum allowable value of the packaging achievement index.

[0046] A laser-based integrated circuit board manufacturing and packaging system, applied to integrated circuit board manufacturing and packaging methods, includes a sensor placement module, a signal conversion module, a data acquisition module, a data calculation module, a data evaluation module, and an automatic compensation module;

[0047] The sensing arrangement module is used to arrange the focusing lens, the reflecting mirror, the beam splitter, and the sensor;

[0048] The signal conversion module is used to convert the information of the reflected light into an electrical signal;

[0049] The data acquisition module is used to acquire electrical signal data, environmental data, and substrate information data.

[0050] The data calculation module calculates the warpage prediction index and the offset prediction index based on the acquired data.

[0051] The data evaluation module evaluates the encapsulation effect index based on the calculation results of the data calculation module.

[0052] The automatic compensation module determines whether automatic adjustment compensation is needed. If automatic adjustment compensation is needed, it calculates the compensation coefficient and performs automatic compensation.

[0053] Compared with the prior art, the present invention provides a method and system for manufacturing and packaging integrated circuit boards based on laser measurement, which has the following advantages:

[0054] This invention achieves proactive suppression of substrate warpage and displacement defects and intelligent improvement of process efficiency through high-precision laser sensing, multi-source data fusion, and a dynamic closed-loop compensation mechanism. First, it uses silicon photodiodes to capture reflected light signals in real time, combined with multi-dimensional monitoring of environmental parameters and substrate characteristics, to construct warpage and displacement prediction indices. This quantifies defect mechanisms such as thermal deformation, stress deformation, and moisture absorption expansion, enabling proactive risk prediction. Then, through dynamic weighting of the packaging effect index and automatic calculation of compensation coefficients, an automatic compensation mechanism is triggered, forming a closed-loop control from multi-dimensional prediction to accurate evaluation to automatic compensation. This significantly reduces the probability of bonding failure. Simultaneously, through data-driven standardized processing and algorithm optimization, it reduces reliance on human intervention, promoting the intelligent transformation of the packaging process from post-production inspection to pre-production prevention and in-process correction. This comprehensively improves alignment accuracy, yield, and production stability, providing an efficient and reliable solution for high-precision integrated circuit board manufacturing. Attached Figure Description

[0055] Figure 1 This is a diagram illustrating the steps of the method of the present invention;

[0056] Figure 2 This is a schematic diagram of the system flow of the present invention;

[0057] Figure 3 This is a schematic diagram of the data acquisition process of the system of the present invention. Detailed Implementation

[0058] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0059] Please see Figure 1-3 A laser-based integrated circuit board manufacturing and packaging method includes the following steps:

[0060] Step 1, Sensor Arrangement: A high-precision focusing lens is used to focus the laser beam onto the substrate surface. A reflector and a beam splitter are arranged to guide the laser beam to the substrate surface. At the same time, sensors are arranged inside the packaging equipment to monitor parameters.

[0061] A high-precision focusing lens is used to precisely focus the laser beam onto the substrate surface. Combined with the optical guidance design of the reflector and beam splitter, the stability of the laser path and the measurement accuracy are ensured. At the same time, sensors are arranged in the packaging equipment to monitor multiple parameters in real time. This sensor arrangement can effectively improve the accuracy of the spot positioning, reduce the impact of environmental interference on the measurement, and provide high-quality basic data for subsequent signal conversion, data acquisition and exponential calculation, thereby providing reliable support for the precise control and automatic compensation of the packaging process.

[0062] Step 2, Signal Conversion: A silicon photodiode is used to receive the reflected light signal and convert the information of the reflected light into an electrical signal;

[0063] Using silicon photodiodes to receive reflected light signals and convert them into electrical signals has the characteristics of high sensitivity, fast response and low noise. It can accurately capture the intensity changes of reflected light, convert the physical information in the light signal into a quantifiable electrical signal, provide a reliable basis for subsequent data acquisition and calculation, and ensure the real-time and accuracy of measurement results, laying the foundation for dynamic control of packaging process.

[0064] Step 3: Data Acquisition: Acquire electrical signal data, environmental data, and substrate information data;

[0065] The numbering expression for electrical signal data XHsj is:

[0066] XHsj=Xgq, Xxw, Xbw, Xzs;

[0067] In the expression, Xgq represents light intensity, Xxw represents phase change, Xbw represents spot position deviation, and Xzd represents vibration intensity.

[0068] By generating electrical signal data from multi-dimensional data, key physical characteristics in the packaging process can be comprehensively reflected. Light intensity is used to evaluate substrate surface quality, phase change reflects minute differences in substrate morphology, spot position deviation accurately identifies substrate offset or warping, and vibration intensity ensures measurement stability. Electrical signal data provides a quantitative basis for real-time control of packaging processes and defect prediction, which helps to improve bonding yield and alignment accuracy.

[0069] The numbering expression for environmental data HJsj is:

[0070] HJsj=Hwd, Hsd, Hqy, Hzd;

[0071] In the expression, Hwd represents temperature, Hsd represents humidity, and Hqy represents air pressure;

[0072] By monitoring changes in the packaging environment in real time, environmental parameters can effectively identify the impact of the external environment on process stability. Temperature fluctuations prevent thermal expansion from causing substrate deformation, humidity changes prevent condensation or electrostatic interference, and air pressure differences can quantify the interference of air flow on laser measurements. This provides data support for process condition optimization and anomaly early warning, and helps to improve the reliability and consistency of packaging results.

[0073] The numbering expression for substrate information data JBsj is:

[0074] JBsj=Jhd, Jmj, Jpz, Jtm, Jxs, jrd;

[0075] In the expression, Jhd represents the substrate thickness, Jmj represents the substrate area, JPz represents the substrate thermal expansion coefficient, Jtm represents the substrate elastic modulus, Jxs represents the substrate hygroscopicity parameter, and Jrd represents the substrate thermal conductivity.

[0076] Substrate parameters provide key information for packaging process optimization by comprehensively characterizing the physical and chemical properties of the substrate. They can accurately predict substrate behavior and provide data support for process parameter adjustment and defect prevention, thereby improving the yield and reliability of packaging results.

[0077] Step 4: Data Calculation: Calculate the warping prediction index and the offset prediction index based on the data obtained in Step 3;

[0078] The formula for calculating the warpage prediction index QQyc is as follows:

[0079]

[0080] In the calculation formula, Hwd t The amount representing the change in temperature. This represents the thermal deformation of the substrate caused by temperature changes. When the temperature rises, the substrate will warp due to thermal expansion. The larger the coefficient of thermal expansion, the more significant the temperature change, and the larger the substrate area, the more obvious the thermal deformation.

[0081] It represents the elastic deformation of the substrate under stress or external force. The greater the deviation of the spot position, the more significant the substrate deformation, the greater the elastic modulus, the harder the material, the smaller the deformation, the greater the thickness, the stronger the bending resistance, and the smaller the deformation.

[0082] Jxs*Hsd represents the expansion and deformation of the substrate due to moisture absorption. The higher the humidity, the greater the hygroscopic parameter, and the more obvious the expansion of the substrate after absorbing moisture, leading to warping.

[0083] α*Xgq represents the effect of correcting light intensity on warp measurement. Too high or too low light intensity may cause the measurement signal to be distorted. α represents the correction factor for light intensity.

[0084] β*Xxw represents the effect of the correction phase change on the warp measurement, and β represents the correction factor for the laser phase change.

[0085] γ*Xzd represents the effect of vibration intensity on warp measurement. Vibration may cause fluctuations in the measurement signal, and γ represents the correction factor for vibration intensity.

[0086] δ*Hqy represents the effect of corrected air pressure on warpage measurement. Air pressure changes may affect the thermal conductivity of the substrate or the stability of the measurement signal. δ represents the air pressure correction factor.

[0087] The calculation formula of the warpage prediction index integrates substrate material properties, environmental factors, and laser measurement parameters to construct a multi-dimensional coupled warpage risk assessment model. This model can predict the deformation trend of the substrate in advance, rather than relying on post-event detection, thereby reducing the risk of warpage from the root. It correlates environmental humidity, vibration, and substrate hygroscopicity and vibration resistance to achieve accurate identification of warpage causes under complex working conditions. This avoids the limitations of traditional methods that analyze environmental factors and material properties separately. At the same time, it dynamically adjusts the measurement results to address laser signal distortion or noise issues, improving the accuracy of spot positioning and phase analysis, and providing a reliable data foundation for warpage prediction.

[0088] The formula for calculating the offset prediction index PYyc is:

[0089]

[0090] In the calculation formula, This represents the coupling effect between the corrected spot position deviation and the substrate elastic modulus, and the effect of normalized substrate thickness.

[0091] θ*Xgq represents the effect of correcting light intensity on the migration, where θ represents the weight of light intensity, used to adjust the contribution of light intensity to the migration prediction;

[0092] This represents the effect of the corrected phase change on the offset. The weights representing the amount of phase change indicate the degree of influence of the optical phase change on the offset prediction.

[0093] μ*Xzd represents the effect of corrected vibration intensity on migration, where μ represents the weight of vibration intensity, used to adjust the contribution of vibration intensity to migration prediction.

[0094] By quantifying the coupling effect of spot position deviation, substrate elastic modulus, light intensity, phase change, and vibration intensity, a multi-parameter collaborative offset risk assessment model was constructed. This model correlates spot position deviation with substrate elastic modulus and thickness, revealing the direct impact of material mechanical properties on offset. It guides the optimization of substrate thickness or elastic modulus to improve bending resistance, thereby reducing offset risk at its source rather than relying on post-detection. By adjusting the contribution of light intensity, phase change, and vibration intensity using weighting coefficients, dynamic compensation for signal distortion, phase noise, and environmental vibration in laser measurement is achieved, significantly improving the accuracy of offset prediction.

[0095] Step 5: Data Evaluation: Calculate the encapsulation effectiveness index based on the warpage prediction index and the offset prediction index;

[0096] The formula for calculating the encapsulation performance index XGzs is:

[0097] XGzs=ρ1*QQyc+ρ2*PYyc;

[0098] In the calculation formula, ρ1 represents the weight of the warping prediction index, ρ2 represents the weight of the offset prediction index, and ρ1+ρ2=1;

[0099] By constructing a packaging effect index and integrating the warpage prediction index and the offset prediction index according to weights, a multi-dimensional comprehensive evaluation of packaging quality is achieved, which improves bonding yield from the root cause. Through forward prediction rather than post-correction, rework or scrap caused by warpage or offset is avoided, significantly improving production efficiency.

[0100] Step Six: Comprehensive Judgment: Determine whether automatic adjustment and compensation are needed based on the packaging result index. If automatic adjustment and compensation are needed, calculate the compensation coefficient and perform automatic compensation.

[0101] The calculation result of the packaging achievement index is compared with the packaging achievement index threshold. When the packaging achievement index is greater than the packaging achievement index threshold, automatic adjustment and compensation are required.

[0102] The formula for calculating the compensation coefficient BCxs is:

[0103] BCxs = XGzs - XGyz;

[0104] In the calculation formula, XGyz represents the maximum allowable value of the packaging achievement index;

[0105] By comparing the packaging result index with the packaging result index threshold and combining it with the compensation coefficient, dynamic closed-loop control of substrate warpage and offset is achieved. This directly intervenes in the risk of warpage and offset exceeding the standard, avoiding the lag of post-event detection and reducing the probability of bonding failure from the root. The compensation coefficient quantifies the deviation between the actual packaging result and the allowable threshold, providing a precise adjustment basis for the automatic compensation system. Compared with traditional experience-based adjustment, it significantly improves the accuracy and efficiency of compensation. Through real-time judgment and automatic compensation, it reduces the rework of scrap products caused by warpage or offset and reduces material loss. At the same time, the closed-loop feedback mechanism avoids repeated detection and manual intervention, accelerates the production cycle, and promotes the upgrade of intelligent manufacturing.

[0106] The aforementioned laser measurement-based integrated circuit board manufacturing and packaging method has the following application system: including a sensor placement module, a signal conversion module, a data acquisition module, a data calculation module, a data evaluation module, and an automatic compensation module;

[0107] The sensor arrangement module is used to arrange focusing lenses, reflectors, beam splitters, and sensors. A high-precision focusing lens focuses the laser beam onto the substrate surface, ensuring that the spot size and energy density meet measurement accuracy requirements. Simultaneously, the reflectors and beam splitters work together to precisely guide the laser beam to the substrate surface and distribute the reflected light signal to the signal conversion module according to a specific ratio. Furthermore, the module integrates multiple types of monitoring devices to capture environmental parameters and substrate dynamic characteristics in real time, providing multi-dimensional input for subsequent data calculations. Through the coordinated arrangement of optical components and sensors, high precision and stability of laser measurements are ensured, while comprehensive monitoring of environmental interference and substrate deformation is achieved, providing reliable hardware support for warpage prediction and automatic compensation.

[0108] The signal conversion module relies on the photoelectric effect of silicon photodiode semiconductor material to convert optical parameters such as light intensity, phase and spot position deviation in the reflected light signal into electrical signals. The subsequent data acquisition module provides electrical signal data to ensure that the calculation of warpage prediction index and offset prediction index has reliable raw input.

[0109] The data acquisition module is used to collect electrical signal data, environmental data, and substrate information data. By simultaneously acquiring electrical signal data, environmental parameters, and substrate characteristics, a multi-dimensional data system is constructed, providing comprehensive input for the prediction of warpage and offset. Electrical signal data directly reflects substrate deformation and optical path deviation, environmental data is used to quantify the impact of temperature, humidity, and air pressure on material thermal expansion, hygroscopic expansion, and measurement stability, and substrate information provides benchmark parameters for material mechanical and physical properties. This multi-source data fusion improves the accuracy of defect prediction, thereby reducing the risk of packaging failure and improving production efficiency and yield.

[0110] The data calculation module calculates the warpage prediction index and offset prediction index based on the acquired data. By integrating multi-dimensional data such as electrical signals, environment, and substrate characteristics, the module calculates the warpage prediction index and offset prediction index, transforming the complex physical process into a quantitative indicator. This enables accurate assessment of defect risks, improves the foresight of defect prediction, and also offsets the influence of environmental and measurement noise through correction factors. This allows compensation decisions to focus more on key risk factors, thereby reducing trial and error costs, optimizing process parameters, and ultimately improving packaging yield and production efficiency.

[0111] The data evaluation module evaluates the encapsulation effect index based on the calculation results of the data calculation module;

[0112] The automatic compensation module determines whether automatic adjustment compensation is needed. If automatic adjustment compensation is needed, it calculates the compensation coefficient and performs automatic compensation.

[0113] The data evaluation module and the automatic compensation module achieve intelligent control of the packaging process through closed-loop linkage from prediction to evaluation to execution. The data evaluation module generates a packaging effect index based on the weighted calculation of the warp prediction index and the offset prediction index, unifying multi-dimensional risks into quantitative indicators and providing intuitive criteria for process optimization. The automatic compensation module triggers the dynamic calculation of the compensation coefficient by comparing the packaging effect index with the threshold and automatically compensates, correcting substrate deformation and positioning deviation in real time. This collaborative mechanism not only improves the accuracy of defect prediction, but also transforms traditional passive detection into proactive prevention through closed-loop feedback, significantly reducing the probability of bonding failure and reducing material waste and rework costs.

[0114] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for manufacturing and packaging an integrated circuit board based on laser measurement, characterized in that, Includes the following steps: Step 1, Sensor Arrangement: A high-precision focusing lens is used to focus the laser beam onto the substrate surface. A reflector and a beam splitter are arranged to guide the laser beam to the substrate surface. At the same time, sensors are arranged inside the packaging equipment to monitor parameters. Step 2, Signal Conversion: A silicon photodiode is used to receive the reflected light signal and convert the information of the reflected light into an electrical signal; Step 3: Data Acquisition: Acquire electrical signal data, environmental data, and substrate information data; Step 4: Data Calculation: Calculate the warping prediction index and the offset prediction index based on the data obtained in Step 3; Step 5: Data Evaluation: Calculate the encapsulation effectiveness index based on the warpage prediction index and the offset prediction index; Step Six: Comprehensive Judgment: Determine whether automatic adjustment and compensation are needed based on the packaging result index. If automatic adjustment and compensation are needed, calculate the compensation coefficient and perform automatic compensation.

2. The integrated circuit board manufacturing and packaging method based on laser measurement according to claim 1, characterized in that: The numbering expression for the electrical signal data XHsj is: XHsj=Xgq, Xxw, Xbw, Xzd; In the expression, Xgq represents light intensity, Xxw represents phase change, Xbw represents spot position deviation, and Xzd represents vibration intensity.

3. The integrated circuit board manufacturing and packaging method based on laser measurement according to claim 2, characterized in that: The numbering expression for the environmental data HJsj is: HJsj=Hwd, Hsd, Hqy, Hzd; In the expression, Hwd represents temperature, Hsd represents humidity, and Hqy represents air pressure.

4. The integrated circuit board manufacturing and packaging method based on laser measurement according to claim 3, characterized in that: The numbering expression for the substrate information data JBsj is: JBsj=Jhd, Jmj, Jpz, Jtm, Jxs, jrd; In the expression, Jhd represents the substrate thickness, Jmj represents the substrate area, JPz represents the substrate thermal expansion coefficient, Jtm represents the substrate elastic modulus, Jxs represents the substrate hygroscopicity parameter, and Jrd represents the substrate thermal conductivity.

5. The integrated circuit board manufacturing and packaging method based on laser measurement according to claim 4, characterized in that: The formula for calculating the warpage prediction index QQyc is as follows: In the calculation formula, Hwd t The amount representing the change in temperature. This represents the thermal deformation of the substrate caused by temperature changes. When the temperature rises, the substrate will warp due to thermal expansion. The larger the coefficient of thermal expansion, the more significant the temperature change, and the larger the substrate area, the more obvious the thermal deformation. It represents the elastic deformation of the substrate under stress or external force. The greater the deviation of the spot position, the more significant the substrate deformation, the greater the elastic modulus, the harder the material, the smaller the deformation, the greater the thickness, the stronger the bending resistance, and the smaller the deformation. Jxs*Hsd represents the expansion and deformation of the substrate due to moisture absorption. The higher the humidity, the greater the hygroscopic parameter, and the more obvious the expansion of the substrate after absorbing moisture, leading to warping. α*Xgq represents the effect of correcting light intensity on warp measurement. Too high or too low light intensity may cause the measurement signal to be distorted. α represents the correction factor for light intensity. β*Xxw represents the effect of the correction phase change on the warp measurement, and β represents the correction factor for the laser phase change. γ*Xzd represents the effect of vibration intensity on warp measurement. Vibration may cause fluctuations in the measurement signal, and γ represents the correction factor for vibration intensity. δ*Hqy represents the effect of corrected air pressure on warpage measurement. Air pressure changes may affect the thermal conductivity of the substrate or the stability of the measurement signal. δ represents the air pressure correction factor.

6. The integrated circuit board manufacturing and packaging method based on laser measurement according to claim 5, characterized in that: The formula for calculating the offset prediction index PYyc is as follows: In the calculation formula, This represents the coupling effect between the corrected spot position deviation and the substrate elastic modulus, and the effect of normalized substrate thickness. θ*Xgq represents the effect of correcting light intensity on the migration, where θ represents the weight of light intensity, used to adjust the contribution of light intensity to the migration prediction; This represents the effect of the corrected phase change on the offset. The weights representing the amount of phase change indicate the degree of influence of the optical phase change on the offset prediction. μ*Xzd represents the effect of corrected vibration intensity on migration, where μ represents the weight of vibration intensity, used to adjust the contribution of vibration intensity to migration prediction.

7. The integrated circuit board manufacturing and packaging method based on laser measurement according to claim 6, characterized in that: The formula for calculating the encapsulation effect index XGzs is as follows: XGzs=ρ1*QQyc+ρ2*PYyc; In the calculation formula, ρ1 represents the weight of the warping prediction index, ρ2 represents the weight of the offset prediction index, and ρ1+ρ2=1.

8. The integrated circuit board manufacturing and packaging method based on laser measurement according to claim 7, characterized in that: The calculated result of the packaging achievement index is compared with the packaging achievement index threshold. If the packaging achievement index is greater than the packaging achievement index threshold, automatic adjustment and compensation are required.

9. The integrated circuit board manufacturing and packaging method based on laser measurement according to claim 8, characterized in that: The formula for calculating the compensation coefficient BCxs is as follows: BCxs = XGzs - XGyz; In the calculation formula, XGyz represents the maximum allowable value of the packaging achievement index.

10. A laser-based integrated circuit board manufacturing and packaging system, applied to the integrated circuit board manufacturing and packaging method according to any one of claims 1 to 9, characterized in that: It includes a sensor deployment module, a signal conversion module, a data acquisition module, a data calculation module, a data evaluation module, and an automatic compensation module; The sensing arrangement module is used to arrange the focusing lens, the reflecting mirror, the beam splitter, and the sensor; The signal conversion module is used to convert the information of the reflected light into an electrical signal; The data acquisition module is used to acquire electrical signal data, environmental data, and substrate information data. The data calculation module calculates the warpage prediction index and the offset prediction index based on the acquired data. The data evaluation module evaluates the encapsulation effect index based on the calculation results of the data calculation module. The automatic compensation module determines whether automatic adjustment compensation is needed. If automatic adjustment compensation is needed, it calculates the compensation coefficient and performs automatic compensation.

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