Multilayer circuit board layer deviation control method for improving interlayer alignment precision
By real-time monitoring and dynamic adjustment of temperature, pressure, and resin flow rate data during the lamination process, the problem of insufficient interlayer alignment accuracy in multilayer circuit boards was solved, achieving improved stability of interlayer alignment accuracy and enhancing the electrical performance and service life of multilayer circuit boards.
Patent Information
- Application Number
- CN202511759889.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-27
- Publication Date
- 2026-02-13
AI Technical Summary
Existing lamination process control methods for multilayer circuit boards are difficult to adapt to the influence of complex factors, resulting in insufficient stability of interlayer alignment accuracy and easy occurrence of problems such as via misalignment, open circuit or short circuit of signal lines.
By monitoring temperature, pressure, and resin flow rate data in real time during the lamination process, the inadequate venting index and half-layer morphology change data are determined, a dynamic compensation coefficient is generated, and the lamination pressure is adjusted in real time to actively respond to the nonlinear changes in resin rheological properties during the phase transition process.
It significantly improves the interlayer alignment accuracy and stability of the laminated boards, effectively suppresses core board slippage and interlayer misalignment, and enhances the electrical performance and service life of multilayer circuit boards.
Smart Images
Figure CN121531601A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of process control technology, specifically to a method for controlling layer misalignment in multilayer circuit boards to improve interlayer alignment accuracy. Background Technology
[0002] Multilayer circuit boards (PCBs) construct complex interconnect networks by alternately stacking conductive circuit layers between insulating dielectric layers, thereby achieving important functions such as signal transmission, power distribution, and electromagnetic shielding. Therefore, multilayer PCBs, as the core carrier for realizing complex circuit interconnections and ensuring signal integrity, are widely used in many key fields such as communication equipment, automotive electronics, aerospace, medical instruments, and high-performance computing. The performance of multilayer PCBs directly affects the overall operational stability and reliability of electronic products.
[0003] In the manufacturing process of multilayer circuit boards, the lamination process is a crucial step to stack and interconnect multiple conductor layers. If there is a misalignment between the layers, it can easily lead to problems such as via misalignment, open or short circuits in signal lines, and impedance mismatch, which in turn affect the electrical performance and service life of the multilayer circuit board.
[0004] Currently, the lamination process control of existing multilayer circuit boards mostly adopts fixed temperature rise curves and pressure curves, and often simplifies the adjustment by using temperature or pressure as a single variable. This control method is difficult to fully adapt to the influence of various complex factors in the lamination process, resulting in insufficient stability of the interlayer alignment accuracy after lamination. Summary of the Invention
[0005] To address the technical problem of insufficient interlayer alignment accuracy stability in current laminated circuit boards, this application aims to provide a method for controlling layer misalignment in multilayer circuit boards to improve interlayer alignment accuracy. The specific technical solution adopted is as follows: Acquire monitoring data of multilayer circuit boards during the lamination process within a preset time period; wherein, the preset time period includes the time period from the start of heating to the start of resin gelation; the monitoring data includes temperature data, pressure data, and resin flow rate data within the lamination equipment; The inadequate venting index for the lamination process is determined based on monitoring data; the inadequate venting index is used to characterize the degree of insufficient gas venting during the lamination process. Determine the half-layer morphology change data of the multilayer circuit board during the resin gelation period. Based on the incomplete exhaust index and morphological change data, dynamic compensation coefficients for adjusting lamination process parameters are determined. The lamination pressure during the lamination process is adjusted based on a dynamic compensation coefficient.
[0006] As one possible approach, the insufficient venting index of the lamination process is determined based on monitoring data, including: determining the resin flow non-uniformity state of the lamination process based on monitoring data; wherein the resin flow non-uniformity state is used to characterize the degree of difference in resin flow behavior in different regions; and determining the insufficient venting index of the lamination process based on the resin flow non-uniformity state and pressure data.
[0007] As one possible approach, the resin flow non-uniformity state during the lamination process is determined based on monitoring data, including: determining the resin rheological fluctuation index for each region based on pressure and resin flow rate data from different areas of the multilayer circuit board surface, and determining the exothermic temperature curve for each region based on temperature data from different regions; the resin rheological fluctuation index is used to characterize resin flow instability; the gelation delay coefficient is determined based on the difference in resin rheological fluctuation index between different regions and the peak width of the exothermic temperature curve, and the gelation delay coefficient is used to characterize the degree of asynchrony in the gelation process in different regions; the resin flow non-uniformity state is determined based on the gelation delay coefficient and the difference in the slope of the resin flow rate curve between different regions, and the resin flow rate curve is a curve constructed based on the resin flow rate data.
[0008] As one possible implementation, based on pressure data and resin flow rate data of different regions on the multilayer circuit board, the resin rheological fluctuation index of each region is determined, including: determining the peak and valley points of the resin flow rate curve; determining the instantaneous resin flow rate change rate based on the flow rate difference and time interval between adjacent peak and valley points; and determining the resin rheological fluctuation index by multiplying the average of multiple instantaneous resin flow rate change rates with the standard deviation of the pressure data.
[0009] As one possible implementation, the gelation delay coefficient is determined based on the difference in resin rheological fluctuation index between different regions and the peak width of the exothermic temperature curve. This includes: obtaining the absolute value of the difference in resin rheological fluctuation index between different regions; obtaining the first average value of the time width between adjacent peak points and valley points in the exothermic temperature curve; and determining the gelation delay coefficient by multiplying the average value of the absolute values of multiple differences with the first average value.
[0010] One possible approach is to determine the resin flow non-uniformity state based on the gelation delay coefficient and the difference in the slope of the resin flow rate curves between different regions, including: for each pair of regions, calculating the absolute value of the difference in the slope of the resin flow rate curves at the same time point; calculating a second average of the absolute values of multiple differences; and determining the resin flow non-uniformity state by multiplying the gelation delay coefficient by the second average.
[0011] As one possible implementation, based on the non-uniform resin flow state and pressure data, the insufficient venting index of the lamination process is determined, including: determining the inflection point in the pressure data change curve; calculating the first variance of the data corresponding to the curve segments between adjacent inflection points, and calculating the first ratio of the average amplitude after the inflection point to the average amplitude before the inflection point; determining the first product of the average of the first variances of multiple regions and the average of the first ratios of multiple regions; and determining the insufficient venting index by multiplying the first product with the product of the non-uniform resin flow state.
[0012] As one possible approach, the half-layer morphology change data of the multilayer circuit board during the resin gelation period is determined, including: acquiring local thickness data and internal structure data of the half-layer board before and after the resin gelation start time; determining the amount of local thickness change based on the local thickness data before and after gelation; determining the amount of internal structure change based on the internal structure data before and after gelation; and determining the half-layer morphology change data by multiplying the standard deviation of the local thickness change and the standard deviation of the internal structure change.
[0013] As one possible implementation, the lamination pressure during the lamination process is adjusted based on a dynamic compensation coefficient, including: multiplying the dynamic compensation coefficient by a preset maximum pressure adjustment amount as the pressure compensation increment; controlling the laminator to adjust the current lamination pressure according to the pressure compensation increment; after adjusting the current lamination pressure, verifying the compensation effect by measuring the flatness of the board surface or drilling deviation; and correcting the dynamic compensation coefficient based on the verification results.
[0014] One possible implementation involves acquiring monitoring data of a multilayer circuit board during the lamination process over a preset time period, including: dividing the surface of the multilayer circuit board into multiple regions, including a central region and edge regions; installing temperature sensors and pressure sensors at positions corresponding to the regions inside the lamination equipment; installing an online measurement device inside the lamination chamber to monitor changes in resin viscosity and curing rate characteristics; and during the lamination process, collecting temperature data of each monitoring region in real time based on the temperature sensors, collecting pressure data of each monitoring region in real time based on the pressure sensors, and collecting resin flow rate data in real time based on the online measurement device.
[0015] This application offers the following advantages: It collects real-time monitoring data, including temperature, pressure, and resin flow rate, during the critical window period from the start of heating to the initial gelation of the resin. Based on this data, it performs synergistic analysis on the incomplete venting index and half-layer morphology changes, thereby generating a dynamic compensation coefficient and adjusting the lamination pressure in real time. Therefore, the multilayer circuit board misalignment control method provided by this application, which improves interlayer alignment accuracy, actively responds to the nonlinear changes in resin rheological properties during phase transition, effectively suppressing core board slippage and interlayer misalignment caused by poor venting and asynchronous curing. This elevates interlayer misalignment control from post-compensation to in-process regulation, significantly improving the stability of interlayer alignment accuracy after lamination. Attached Figure Description
[0016] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0017] Figure 1 A flowchart illustrating a multilayer circuit board layer offset control method for improving interlayer alignment accuracy, provided as an embodiment of this application. Figure 1 ; Figure 2 A flowchart illustrating a multilayer circuit board layer offset control method for improving interlayer alignment accuracy, provided as an embodiment of this application. Figure 2 ; Figure 3 A flowchart illustrating a multilayer circuit board layer offset control method for improving interlayer alignment accuracy, provided as an embodiment of this application. Figure 3 ; Figure 4 A flowchart illustrating a multilayer circuit board layer offset control method for improving interlayer alignment accuracy, provided as an embodiment of this application. Figure 4 ; Figure 5 A flowchart illustrating a multilayer circuit board layer offset control method for improving interlayer alignment accuracy, provided as an embodiment of this application. Figure 5 . Detailed Implementation
[0018] To further illustrate the technical means and effects adopted by this application to achieve the intended inventive objective, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a multilayer circuit board layer offset control method for improving interlayer alignment accuracy proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.
[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.
[0020] The following description, in conjunction with the accompanying drawings, details a specific scheme for a multilayer circuit board layer offset control method to improve interlayer alignment accuracy provided in this application.
[0021] Please see Figure 1 This document illustrates a flowchart of a multilayer circuit board layer offset control method for improving interlayer alignment accuracy, provided in one embodiment of this application. Figure 1 As shown, the method includes the following steps: Step 101: Obtain monitoring data of the multilayer circuit board during the lamination process within a preset time period.
[0022] The preset time period includes the time between the start of heating and the start of resin gelation; the monitoring data includes temperature data, pressure data, and resin flow rate data within the laminating equipment.
[0023] As one possible implementation, this step can be specifically implemented as follows: dividing the surface of the multilayer circuit board into multiple regions, including a central region and an edge region; installing temperature sensors and pressure sensors at positions corresponding to the regions inside the lamination equipment; installing an online measurement device inside the lamination chamber to monitor changes in resin viscosity and curing rate characteristics; and during the lamination process, collecting temperature data of each monitoring region in real time based on the temperature sensors, collecting pressure data of each monitoring region in real time based on the pressure sensors, and collecting resin flow rate data in real time based on the online measurement device.
[0024] For example, in practical applications, a multi-point temperature sensor array and a pressure distribution sensing membrane are installed inside the laminating equipment before the multilayer boards are stacked. Temperature sensors are arranged in the central region, edge region, and adjacent surface of the copper foil in the PP layer to form a zoned temperature measurement structure. The pressure sensing membrane is placed between the upper pressure plate and the pre-stacked plates to monitor changes in local contact pressure distribution in real time. An infrared spectroscopy sensor or an online dielectric constant measuring device is installed in the lamination cavity to reflect the degree of curing reaction and flow state of the PP resin, thereby capturing changes in resin viscosity and curing rate characteristics.
[0025] After the lamination process is initiated, the system controls the temperature according to a preset heating curve. The control system records the temperature curves and heating rates at each measuring point, while simultaneously collecting corresponding pressure data. Based on the collected data, a complete spatiotemporal data matrix of the lamination process is formed. This complete spatiotemporal data matrix is then aligned with the actual plate surface coordinate field obtained by the subsequent flatness scanner to establish a basis for the correlation between lamination process parameters and forming deformation.
[0026] Step 102: Determine the inadequate venting index of the lamination process based on monitoring data.
[0027] The insufficient venting index is used to characterize the degree of inadequate gas venting during the lamination process. In other words, the insufficient venting index is a comprehensive indicator used to quantitatively assess the risk of product quality defects caused by the failure of gas to be vented from the resin system in a timely and complete manner during the lamination process.
[0028] Optionally, this application can determine the venting efficiency by analyzing the resin flow and pressure conditions in the monitoring data. For example, the analysis can be conducted in three dimensions: 1. Analyzing the probability of trapped air bubbles or voids forming inside the laminate (especially at resin junctions or slow-flow areas in different monitoring zones) based on monitoring data. 2. Analyzing the interrelationship between uneven resin flow and obstructed venting paths. Uneven resin flow can lead to localized blockages, hindering gas venting; conversely, the inability to vent gas occupies space, altering the resin flow path and pressure distribution. 3. Analyzing the degree of matching between the current pressure control curve and the actual rheological state of the resin; applying pressure too early, too late, or unevenly will not effectively drive gas venting. Finally, based on the above analysis results, a comprehensive venting insufficiency index for the lamination process is determined.
[0029] Step 103: Determine the half-layer morphological change data of the multilayer circuit board during the resin gelation time period.
[0030] Among them, the semi-layer morphological change data characterizes the combined degree of nonlinear and irreversible physical deformation and internal structural deterioration that occurs in the semi-layer plate during the key phase transition stage of resin gelation.
[0031] Optionally, this application can determine the morphological change data of the half-layer by comparing the state differences before and after the key nodes of resin gelation.
[0032] Optionally, half-layer morphology change data can comprehensively reflect the non-uniformity of macroscopic deformation and the degree of microstructural degradation. Non-uniformity of macroscopic deformation refers to the severity of macroscopic geometric defects such as localized warping and uneven thickness that appear after gelation of the half-layer. Higher non-uniformity of macroscopic deformation results in poorer board surface flatness and a less stable foundation for subsequent lamination alignment. The degree of microstructural degradation refers to the severity of microscopic defects such as uneven internal resin distribution, disordered glass fiber orientation, or micropores caused by insufficient resin flow and gas retention. Higher degrees of microstructural degradation indicate poorer intrinsic quality of interlayer bonding. Based on half-layer morphology change data, hidden defects and risks during the process (such as uneven flow and poor venting) can be correlated with ultimately visible product quality defects (such as layer misalignment and warping).
[0033] Step 104: Based on the inadequate exhaust index and morphological change data, determine the dynamic compensation coefficient used to adjust the lamination process parameters.
[0034] Optionally, the dynamic compensation coefficient is positively correlated with both the insufficient exhaust index and the half-layer morphology change data. Specifically, the dynamic compensation coefficient is jointly determined by the insufficient exhaust index and the half-layer morphology change data. In other words, when the process defect represented by the insufficient exhaust index is severe, and this defect has actually caused a significant half-layer morphology change, the system will determine that the interlayer alignment risk is high, thereby generating a larger dynamic compensation coefficient and driving the laminator to perform a larger pressure adjustment. Conversely, if the process is stable and the half-layer morphology change is small, a smaller dynamic compensation coefficient is generated, resulting in a small adjustment or maintaining the original parameters.
[0035] Step 105: Adjust the lamination pressure during the lamination process based on the dynamic compensation coefficient.
[0036] As one possible implementation, the process can be specifically implemented as follows: the product of the dynamic compensation coefficient and the preset maximum pressure adjustment amount is used as the pressure compensation increment; the laminator is controlled to adjust the current lamination pressure according to the pressure compensation increment; after adjusting the current lamination pressure, the compensation effect is verified by measuring the flatness of the board surface or the drilling deviation; and the dynamic compensation coefficient is corrected based on the verification results.
[0037] In the specific implementation process, the maximum pressure adjustment allowed by the current lamination process is first obtained, denoted as ΔP_max. Then, the dynamic compensation coefficient is multiplied by this maximum adjustment to calculate the pressure compensation increment required for the current lamination process. The laminator adjusts the pressure setting in real time based on this increment to achieve optimized control of resin flow behavior and venting status. Optionally, ΔP_max is determined comprehensively based on the laminator equipment specifications, prepreg material characteristics, and historical process data; for example, it can be set to 10%-20% of the initial set pressure. To verify the lamination effect after pressure adjustment, at least one of the following methods was used to monitor and evaluate the state of the board after lamination compensation: board surface flatness scanning, local thickness measurement, or subsequent laser drilling alignment deviation detection. The monitoring results were fed back to the control model in real time. If the feedback data indicated that uneven pressure distribution or deformation exceeded the tolerance after compensation, the dynamic compensation coefficient was revised based on the deviation, and the pressure parameters were adjusted again.
[0038] By constructing the aforementioned closed-loop control circuit, automatic fine-tuning of lamination pressure is achieved, ensuring that the entire process dynamically converges to the optimal process window. This global pressure adaptive control strategy not only simultaneously optimizes resin degassing efficiency and flow uniformity during the lamination stage, but also achieves precise closed-loop adjustment of process parameters in the subsequent curing stage. Ultimately, this significantly improves the morphological stability of the cured semi-laminated board and effectively reduces internal porosity, thereby ensuring an overall improvement in interlayer bonding strength and product consistency.
[0039] Based on the above technical solution, this application collects real-time monitoring data such as temperature, pressure, and resin flow rate during the critical window period from the start of heating to the beginning of resin gelation. Based on this monitoring data, it performs synergistic analysis on the incomplete venting index and half-layer morphology changes, thereby generating a dynamic compensation coefficient and adjusting the lamination pressure in real time. Therefore, the multilayer circuit board layer misalignment control method provided by this application, which improves interlayer alignment accuracy, can actively respond to the nonlinear changes in resin rheological properties during phase transition, effectively suppressing core board slippage and interlayer misalignment caused by poor venting and asynchronous curing. It elevates layer misalignment control from post-compensation to in-process regulation, significantly improving the stability of interlayer alignment accuracy after lamination.
[0040] like Figure 2 As shown, in one possible implementation, the process of determining the insufficient venting index of the lamination process based on monitoring data in step 102 above can be specifically implemented through the following steps: Step 201: Determine the non-uniform resin flow state during the lamination process based on monitoring data.
[0041] The resin flow non-uniformity state is used to characterize the degree of difference in resin flow behavior in different regions. In other words, the resin flow non-uniformity state is used to characterize the consistency and stability of the flow behavior of prepreg (PP) resin in different monitoring areas during the lamination heating process.
[0042] Optionally, this application uses the resin flow non-uniformity state to represent the synchronicity of resin flow rate and flow trend between different monitoring areas, and the stability of the overall resin flow process. A higher resin flow non-uniformity state indicates a more asynchronous resin filling process in different areas of the board surface. For example, some areas may have been rapidly filled while others are still flowing slowly, leading to local pressure imbalances and gas retention. A higher resin flow non-uniformity state also indicates a less stable overall resin flow process. This is because drastic, asynchronous flow is often accompanied by instantaneous changes in flow velocity and severe pressure fluctuations. This instability may induce core board slippage and final interlayer alignment deviations.
[0043] Step 202: Determine the inadequate venting index of the lamination process based on the non-uniform resin flow state and pressure data.
[0044] It should be noted that, on the one hand, when the resin flow in different areas is asynchronous and uneven, complex flow conditions will form within the board. Areas with high flow rates may prematurely block the gas venting path, while areas with slow flow rates may leave spaces for gas stagnation due to insufficient filling. Therefore, uneven flow directly leads to insufficient venting. On the other hand, the gas venting behavior directly affects the cavity pressure. For example, when venting is smooth, the pressure will drop steadily or release regularly; when gas is trapped due to uneven flow and cannot be vented smoothly, it will cause abnormal pressure fluctuations. Therefore, this application can estimate the insufficient venting index of the lamination process from both the resin flow unevenness and pressure data.
[0045] Optionally, this application determines characteristic parameters for characterizing exhaust efficiency by analyzing the variation characteristics of the pressure data; subsequently, the resin flow non-uniformity state is multiplied by the characteristic parameters characterizing exhaust efficiency to determine the final exhaust insufficiency index.
[0046] Based on the above technical solution, when constructing the incomplete venting index evaluation model, this application conducts a correlation analysis between the resin flow non-uniformity state and pressure distribution characteristics. By revealing the intrinsic relationship between flow non-uniformity and gas retention, it can more accurately determine the gas venting efficiency during the lamination process. This upgrades the judgment of venting status from traditional single pressure monitoring to multi-parameter coupled analysis, providing a scientific basis for subsequent targeted pressure compensation and effectively avoiding resin filling inadequacy or void defects caused by local gas retention.
[0047] like Figure 3As shown, in one possible implementation, the process of determining the non-uniform resin flow state during the lamination process based on monitoring data in step 201 above can be specifically implemented through the following steps: Step 301: Based on the pressure data and resin flow rate data of different regions on the multilayer circuit board, determine the resin rheological fluctuation index of each region, and based on the temperature data of different regions, determine the exothermic temperature curve of each region.
[0048] Among them, the resin rheological fluctuation index is used to characterize the flow instability of resin.
[0049] As one possible implementation, the process of determining the resin rheological fluctuation index can be specifically implemented as follows: determine the peak and valley points of the resin flow rate curve; determine the instantaneous flow rate change rate of the resin based on the flow rate difference and time interval between adjacent peak and valley points; and determine the resin rheological fluctuation index by multiplying the average of multiple instantaneous flow rate change rates of the resin with the standard deviation of the pressure data.
[0050] Optionally, in an actual laminator, the resin flow rate can be indirectly estimated using a micro-displacement sensor or optical scanner on the plate surface. During the lamination process, the process start time corresponds to the heating start time, which is usually the moment when the prepreg contacts the mold and begins to heat up. Then, the gelation start time is determined based on the exothermic temperature curve. When the curve shows the first obvious upward slope or reaches the front of a small peak, it indicates that the resin crosslinking has begun to release heat. The time period between the heating start time and the gelation start time is taken as the observation time period (i.e., the preset time period mentioned above).
[0051] During the lamination process, a pressure sensor array arranged within the lamination chamber acquires the local pressure variation curve with temperature increase. A peak point detection algorithm is used to identify all peak and valley points in the resin flow rate curve, and the difference between each adjacent peak and valley value is recorded as... (That is, the aforementioned velocity difference); the time interval between adjacent peak-valley points is denoted as... (That is, the time interval mentioned above). The standard deviation of all pressure monitoring data is denoted as u; based on the aforementioned flow rate difference... Time interval Using the standard u of the pressure data, the resin rheological fluctuation index for the current observation period is calculated.
[0052] As an example, the resin rheological fluctuation index Satisfy the following formula: ; in, This represents the arithmetic mean calculation function, used to calculate the arithmetic mean of parameters. It reflects the amplitude of the instantaneous flow rate change of the resin during the lamination process. This is a data normalization function used to scale data to a specific range (such as [0,1]) according to rules, in order to eliminate differences in units and unify the data scale. A higher value indicates a more drastic change in resin flow rate over a short period of time; This represents the average flow velocity impact intensity during the observation period, i.e., the degree of flow instability. u represents the overall amplitude of pressure fluctuations in the system; a larger u value indicates more significant instability within the cavity and is more likely to be accompanied by stronger driving or blocking disturbances. A large product indicates that the flow not only experiences large instantaneous jumps, but these jumps are also coupled with pressure disturbances, making it highly susceptible to bubble entrainment, localized channelization, or localized stagnation. This suggests that the resin rheological fluctuations in the current region are quite strong. It should be noted that the aforementioned Δt should be greater than the system sampling interval to ensure its value is positive.
[0053] As another possible implementation, the process of determining the exothermic temperature curve can be specifically implemented as follows: Optionally, in this application, a thermocouple is arranged near the middle layer region of PP between the lamination mold and the sample, and the exothermic temperature curve during the current observation period is obtained through the thermocouple. Optionally, after determining the exothermic temperature curve, a peak point detection algorithm is used to identify all peak points and valley points in the exothermic temperature curve, and then the width between adjacent peaks and valleys is calculated using... to indicate The time width between a single adjacent peak and trough in the exothermic temperature curve. This is the arithmetic mean of the time widths of all adjacent peaks and valleys, in seconds (s).
[0054] Step 302: Determine the gelation delay coefficient based on the differences in resin rheological fluctuation index between different regions and the peak width of the exothermic temperature curve.
[0055] The gelation delay coefficient is used to characterize the degree of asynchrony in the gelation process in different regions.
[0056] As one possible implementation, the process can be specifically implemented as follows: obtaining the absolute value of the difference between the resin rheological fluctuation indexes of different regions; obtaining the first average value of the time width between adjacent peak points and valley points in the exothermic temperature curve; and determining the gelation delay coefficient by multiplying the average value of the absolute values of multiple differences with the first average value.
[0057] As an example, the gelation delay coefficient Satisfy the following formula: ; in, and These represent the resin rheological fluctuation indices in different regions; in the process of determining the gelation delay coefficient... This is used to characterize the stability difference between any two monitoring regions (denoted as region o and region y) during the resin flow stage. The larger the absolute value of this difference, the more significant the difference in resin flow behavior between the two regions; that is, one side may exhibit smooth flow while the other side experiences stagnation. This inconsistency will directly lead to spatial differences in resin migration paths and exhaust efficiency. The absolute values of the differences in resin rheological fluctuation indices between all pairs of regions are used as statistical samples. Assuming there are m sets of such differences, subsequent calculations will be based on these m sets of differences.
[0058] This reflects the degree of dispersion of the resin curing reaction over time. The larger the average value, the more asynchronous the process of resin transitioning from a fluid state to a gel state in different micro-regions, the wider the time distribution of the overall curing reaction, and the worse the concentration of the gelation process.
[0059] The larger the product, the more inconsistent the resin flow behavior is in space and the more asynchronous its curing process is in time within the current observation period. The combined effect of these two factors leads to a severe gelation delay effect, i.e., the larger the gelation delay coefficient.
[0060] Step 303: Determine the non-uniform resin flow state based on the gelation delay coefficient and the difference in the slope of the resin flow rate curve between different regions.
[0061] The resin flow rate curve is constructed based on the resin flow rate data.
[0062] As one possible implementation, the process can be specifically implemented as follows: for every two regions, calculate the absolute value of the difference between the slopes of the resin flow rate curves of the two regions at the same time point; calculate the second average value of the absolute values of multiple differences; and determine the resin flow non-uniformity state by multiplying the gelation delay coefficient by the second average value.
[0063] Optionally, this application analyzes the resin flow behavior under the coupled effects of heating and pressure to identify the resin filling rate, flow direction, and local stagnation phenomena in each monitoring area. Since alignment errors are usually significantly aggravated in areas with insufficient resin filling or gas stagnation, the high-risk areas identified through this analysis can provide a key basis for subsequent targeted compensation strategies.
[0064] During the current observation period, resin flow rate curves in different regions are acquired. Then, a set of slope values between two adjacent data points on the resin flow rate curve in each region is denoted as K, resulting in a total of M sets of slope values, where M is greater than or equal to 1. Following this, based on the gelation delay coefficient... The slope value K and the number of slope value groups M determine the non-uniform state of resin flow.
[0065] As an example, the non-uniform resin flow state f satisfies the following formula: ; , Let represent the slope values at the c-th time point in the resin flow rate curves of the 0-th and y-th regions, respectively. The difference between the slopes at the same time point is calculated as follows: The larger the difference, the more asynchronous the resin flow behavior at the two locations, with some areas filling faster and others slower. Assume there are M sets of slope values in the flow rate monitoring curves of region o and region y. Any two regions form a control group, and the average flow rate of all control groups is... Represented by functions; The larger the value, the more significant the difference in flow response between different regions, and the worse the spatial uniformity of resin filling; The greater the product of the flow rate difference and the gelation hysteresis, the stronger the non-uniformity of different regions during the flow and curing process, which ultimately leads to a higher risk of interlayer migration.
[0066] Based on the above technical solution, this application establishes a multi-level evaluation system based on resin rheological fluctuation index, exothermic temperature curve analysis, and gelation delay coefficient, achieving comprehensive monitoring of the resin's phase transition process from flow to curing. In this way, this application can keenly capture the temporal differences in resin viscosity changes and crosslinking reactions in different regions, accurately quantify the degree of asynchrony in the gelation stage of each region, and provide key data support for identifying internal stress concentration caused by differences in curing sequence, thereby achieving early warning and precise location of layer deviation risks.
[0067] like Figure 4 As shown, in one possible implementation, the process of determining the insufficient venting index of the lamination process based on the resin flow non-uniformity and pressure data in step 202 above can be specifically achieved through the following steps: Step 401: Determine the inflection point in the pressure data change curve.
[0068] Step 402: Calculate the first variance of the data corresponding to the curve segments between adjacent inflection points, and calculate the first ratio of the average amplitude after the inflection point to the average amplitude before the inflection point.
[0069] As one possible implementation, the above steps can be implemented as follows: During the observation period, pressure data between the layers in different monitoring areas are collected, and the changes in this pressure data are monitored to characterize the resin's venting state. For the pressure data curve of any monitoring area, the following processing is performed: identifying characteristic inflection points in the pressure curve; for the curve segment between adjacent inflection points, calculating the variance of the pressure data in that segment, denoted as T; calculating the average amplitude of the pressure data in the interval before a single inflection point, denoted as h; calculating the average amplitude of the pressure data in the interval after a single inflection point, denoted as H. The ratio of h to H is calculated as the first ratio. This represents the ratio of the average amplitude after the inflection point to the average amplitude between inflection points at a single inflection point. The larger the ratio, the less significant the pressure drop after the inflection point, i.e., the insufficient pressure release.
[0070] Step 403: Determine the first product of the average of the first variances of the multiple regions and the average of the first ratios of the multiple regions.
[0071] Step 404: The product of the first product and the resin flow non-uniformity state is determined as the incomplete venting index.
[0072] As an example, the exhaust incompleteness index Satisfy the following formula: ; The larger the variance between inflection points, the more drastic the pressure changes, and the more likely the pressure will exhibit intermittent release, localized stagnation, or repeated rises. The larger the value; This represents the average of the ratios at all inflection points within a single region. A larger value indicates strong pressure fluctuations and insufficient pressure reduction in a single area, suggesting low exhaust efficiency. This indicates that the average value is taken over all regions during the observation period. A larger product indicates that the local flow is highly uneven, the pressure fluctuations in the region are large and the decrease is insufficient. In other words, the more significant the incomplete exhaust, the larger the incomplete exhaust index.
[0073] Based on the above technical solution, this application extracts the inflection point characteristics of the pressure curve, calculates the product of the variance between inflection points and the ratio of the amplitude before and after the inflection points, and combines this with the non-uniform flow state to establish a quantitative evaluation model for the insufficient exhaust state. Based on this, this application can identify abnormal areas of insufficient pressure release and drastic fluctuations, accurately reflect the risk of local gas stagnation, achieve precise diagnosis of gas exhaust efficiency during lamination, and provide a clear direction for targeted pressure adjustment.
[0074] like Figure 5As shown, in one possible implementation, the process of determining the half-layer morphology change data of the multilayer circuit board during the resin gelation time period in step 103 above includes: Step 501: Obtain local thickness data and internal structure data of the half-layer plate before and after the resin gelation initiation time.
[0075] Step 502: Determine the amount of change in local thickness based on the local thickness data before and after gelation.
[0076] Step 503: Determine the amount of change in internal structure based on the internal structure data before and after gelation.
[0077] As one possible implementation, the above process can be specifically implemented as follows: obtaining the local thickness of the half-layer plate before and after gelation using a high-precision flatness scanner or thickness measuring instrument.
[0078] Suppose there is a certain location, and the coordinates of that location are... The local thickness of the first half of the gelation plate is denoted as . The local thickness of the gelled half-layer plate is denoted as . These two parameters constitute the aforementioned local thickness data. Resin distribution and glass fiber orientation data are obtained using X-ray CT scans or micro-fluoroscopic imaging. , These two parameters are the internal structure data mentioned above.
[0079] Following this, the local morphological changes at each location were determined. (That is, the aforementioned local thickness variation), which satisfies: Calculate the differences in internal structure at each location. (That is, the aforementioned changes in internal structure), satisfying: .
[0080] Step 504: The product of the standard deviation of the local thickness change and the standard deviation of the internal structure change is determined as the half-layer morphological change data.
[0081] As an example, half-layer morphological change data Satisfy the following formula: ; The more uneven the change (i.e.) The larger the value, the more non-linear the morphology of the two halves of the gelation layer is, with severe local warping; while... The more uneven the distribution (i.e.) The larger the value, the more likely it is to indicate structural abnormalities caused by locally retained resin or air bubbles. By combining the magnitude of local morphological changes with the spatial fluctuations of internal structural differences, an overall index is obtained to characterize the nonlinear morphological evolution of the semilayer before and after gelation. The larger the value, the more significant the morphological / structural changes of the semilayer and the higher the potential risk of interlayer displacement.
[0082] Based on the above technical solution, this application constructs a half-layer morphological deformation index based on the standard deviation of thickness change and the standard deviation of internal structure change by comparing and analyzing the local thickness and internal structure data of the half-layer before and after gelation. This index comprehensively reflects the spatial distribution characteristics of deformation caused by resin flow, gas discharge and internal structure reorganization during the curing process. It can effectively assess the nonlinear deformation risk generated during lamination and provides a reliable morphological basis for predicting the alignment accuracy between layers.
[0083] As one possible implementation, in determining the incomplete exhaust index as described above... and half-layer morphological change data Then, as an example, the dynamic compensation coefficient Satisfy the following formula: ; Combining inadequate exhaust index and half-layer morphological change data can highlight the magnitude of interlayer migration risk. A larger value indicates that the pressure data needs to be adjusted more during the gelation stage to effectively reduce the risk of layer deviation. The larger the compensation coefficient, the greater the pressure across the entire plate or the longer the holding time, resulting in more complete resin flow, more thorough removal of trapped air, and further improvement in interlayer alignment accuracy.
[0084] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.
[0085] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.
Claims
1. A method for improving the accuracy of interlayer alignment of a multilayer wiring board layer deviation control, characterized by, The method includes: Acquire monitoring data of multilayer circuit boards during the lamination process within a preset time period; wherein, the preset time period includes the time period from the start of heating to the start of resin gelation; the monitoring data includes temperature data, pressure data, and resin flow rate data within the lamination equipment; The insufficient venting index of the lamination process is determined based on the monitoring data; wherein the insufficient venting index is used to characterize the degree of insufficient gas venting during the lamination process; Determine the half-layer morphological change data of the multilayer circuit board during the resin gelation time period. Based on the inadequate exhaust index and the morphological change data, a dynamic compensation coefficient for adjusting the lamination process parameters is determined. Based on the aforementioned dynamic compensation coefficient, the lamination pressure during the lamination process is adjusted.
2. The method for controlling layer misalignment in multilayer circuit boards to improve interlayer alignment accuracy according to claim 1, characterized in that, Determining the inadequate venting index of the lamination process based on the monitoring data includes: The resin flow non-uniformity state during the lamination process is determined based on the monitoring data; wherein, the resin flow non-uniformity state is used to characterize the degree of difference in resin flow behavior in different regions. Based on the non-uniform resin flow state and the pressure data, the insufficient venting index of the lamination process is determined.
3. The method for controlling layer misalignment in multilayer circuit boards to improve interlayer alignment accuracy according to claim 2, characterized in that, Determining the non-uniform resin flow state during the lamination process based on the monitoring data includes: Based on the pressure data and resin flow rate data of different regions on the multilayer circuit board, the resin rheological fluctuation index of each region is determined, and based on the temperature data of different regions, the exothermic temperature curve of each region is determined; the resin rheological fluctuation index is used to characterize the resin flow instability. Based on the differences in resin rheological fluctuation index and the peak width of the exothermic temperature curve between the different regions, the gelation delay coefficient is determined. The gelation delay coefficient is used to characterize the degree of asynchrony in the gelation process of different regions. The resin flow non-uniformity state is determined based on the gelation delay coefficient and the difference in the slope of the resin flow rate curve between different regions, and the resin flow rate curve is a curve constructed based on the resin flow rate data.
4. The method for controlling layer misalignment in multilayer circuit boards to improve interlayer alignment accuracy according to claim 3, characterized in that, Based on pressure data and resin flow rate data from different regions of the multilayer circuit board, the resin rheological fluctuation index for each region is determined, including: Determine the peak and trough points of the resin flow rate curve; The instantaneous flow rate change rate of the resin is determined based on the flow rate difference between adjacent peak and valley points and the time interval. The resin rheological fluctuation index is determined by multiplying the average of the multiple instantaneous flow rate changes of the resin with the standard deviation of the pressure data.
5. The method for controlling layer misalignment of multilayer circuit boards to improve interlayer alignment accuracy according to claim 3, characterized in that, Based on the differences in resin rheological fluctuation index between the different regions and the peak width of the exothermic temperature curve, the gelation delay coefficient is determined, including: Obtain the absolute value of the difference in the resin rheological fluctuation index between different regions; Obtain the first average value of the time width between adjacent peak points and valley points in the heat release temperature curve; The product of the average of the absolute values of the multiple differences and the first average value is determined as the gelation delay coefficient.
6. The method for controlling layer misalignment in multilayer circuit boards to improve interlayer alignment accuracy according to claim 3, characterized in that, The non-uniform resin flow state is determined based on the gelation delay coefficient and the difference in the slope of the resin flow rate curves between different regions, including: For each pair of regions, calculate the absolute value of the difference in the slope of the resin flow rate curves at the same time point for those two regions. Calculate a second average of the absolute values of the plurality of said differences; The product of the gelation delay coefficient and the second average value is used to determine the non-uniform resin flow state.
7. The method for controlling layer misalignment in multilayer circuit boards to improve interlayer alignment accuracy according to claim 2, characterized in that, Based on the non-uniform resin flow state and the pressure data, the inadequate venting index of the lamination process is determined, including: Determine the inflection point in the curve of the pressure data change; Calculate the first variance of the data corresponding to the curve segments between adjacent inflection points, and calculate the first ratio of the average amplitude after the inflection point to the average amplitude before the inflection point. Determine a first product of the average of the first variances of the multiple regions and the average of the first ratios of the multiple regions; The product of the first product and the resin flow non-uniformity state is determined as the inadequate venting index.
8. The method for controlling layer misalignment in multilayer circuit boards to improve interlayer alignment accuracy according to claim 1, characterized in that, Determining the half-layer morphology change data of the multilayer circuit board during the resin gelation time period includes: Obtain local thickness data and internal structure data of the half-layer plate before and after the resin gelation initiation time; Based on the local thickness data before and after gelation, determine the amount of change in local thickness; The amount of change in internal structure is determined based on the internal structure data before and after gelation; The product of the standard deviation of the local thickness variation and the standard deviation of the internal structure variation is determined as the half-layer morphological variation data.
9. The method for controlling layer misalignment in multilayer circuit boards to improve interlayer alignment accuracy according to claim 1, characterized in that, Based on the aforementioned dynamic compensation coefficient, the lamination pressure during the lamination process is adjusted, including: The product of the dynamic compensation coefficient and the preset maximum pressure adjustment amount is used as the pressure compensation increment; The control laminator adjusts the current lamination pressure according to the pressure compensation increment; After adjusting the current lamination pressure, the compensation effect is verified by measuring the flatness of the board surface or the drilling deviation. The dynamic compensation coefficient is corrected based on the verification results.
10. The method for controlling layer misalignment in multilayer circuit boards according to claim 1, characterized in that, Acquire monitoring data of the multilayer circuit board during the lamination process within a preset time period, including: The surface of the multilayer circuit board is divided into multiple regions, including a central region and an edge region; Temperature and pressure sensors are installed inside the laminating equipment at locations corresponding to the area described above. An online measuring device is installed in the lamination chamber to monitor changes in resin viscosity and curing rate characteristics; During the lamination process, temperature data of each monitoring area is collected in real time based on the temperature sensor, pressure data of each monitoring area is collected in real time based on the pressure sensor, and resin flow rate data is collected in real time based on the online measuring device.