Method and device for improving stability of golden finger, computer device and storage medium

Abstract

The application relates to the technical field of gold finger production, and discloses a method and device for improving the stability of a gold finger, computer equipment and a storage medium; the method comprises the following steps: acquiring material information and environmental information of a gold finger plate; adopting a compensation model to generate a pre-compensation coefficient in combination with the material information and the environmental information; and performing production and manufacturing of the gold finger plate according to the pre-compensation coefficient. The method can effectively solve the size expansion and contraction problem of a long-size LCD plate gold finger caused by seasonal temperature and humidity changes, brings the technical effects of improving the size stability, reducing the defective product rate and improving the production efficiency, and has a wide application prospect.

Description

Technical Field

[0001] This invention relates to the field of gold finger manufacturing technology, and more specifically to methods, apparatus, computer equipment, and storage media for improving the stability of gold fingers. Background Technology

[0002] In today's era of rapid development in electronic information technology, the printed circuit board (PCB) industry, as a key foundational industry for electronic device manufacturing, is becoming increasingly important. PCBs provide electrical connections and mechanical support for electronic components and are an indispensable part of various electronic products. As electronic products continue to evolve towards miniaturization, lightweighting, and low power consumption, more stringent requirements are being placed on the performance and characteristics of PCBs.

[0003] Liquid Crystal Display (LCD) boards, as an important application form of PCBs, have been widely used in numerous fields due to their significant advantages such as small size, light weight, and low power consumption. From everyday portable consumer electronics such as smartphones and tablets, to large televisions and computer monitors, and even to professional fields such as industrial control equipment and medical instruments, LCD boards play a crucial role, greatly promoting the popularization and functional upgrades of electronic products.

[0004] However, in the actual production process of LCD boards, especially in the production of long-sized gold fingers (length ≥ 300mm), a pressing technical challenge has emerged—the dimensional stability of the gold fingers. This is because gold fingers undergo multiple complex processes during PCB manufacturing, such as substrate treatment, circuit fabrication, and surface treatment, and these processes are highly sensitive to environmental conditions.

[0005] Seasonal temperature and humidity variations are a significant environmental factor affecting the dimensional stability of PCB gold fingers. Ambient temperature and humidity fluctuate considerably throughout the year. When these conditions change, the PCB substrate expands and contracts with temperature and humidity, altering the stress distribution within the substrate. For long gold fingers, this dimensional change caused by temperature and humidity variations is amplified due to their length, resulting in expansion and contraction of the gold fingers.

[0006] The expansion and contraction of the gold fingers can have a series of serious consequences. First, expansion and contraction can reduce the precision of the fit between the gold fingers and external connectors, potentially leading to poor contact, unstable signal transmission, and other problems that affect the normal operation of the LCD board. Second, during the production process, expansion and contraction can also increase the defect rate, resulting in higher production costs and lower production efficiency.

[0007] In summary, in the PCB industry, the dimensional expansion and contraction of the gold fingers of long-size LCD boards due to seasonal temperature and humidity changes has become a key factor restricting product quality and production efficiency, and an effective technical solution is urgently needed to solve this problem. Summary of the Invention

[0008] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method, apparatus, device and medium for improving the stability of gold fingers.

[0009] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0010] Firstly, methods to improve the stability of the gold finger are provided, including:

[0011] Obtain material and environmental information for the gold finger plate;

[0012] A compensation model is used to generate pre-compensation coefficients by combining material and environmental information.

[0013] The production of the gold finger plate is carried out according to the pre-compensation coefficient.

[0014] Secondly, it provides devices to improve the stability of the gold finger, including:

[0015] The acquisition unit is used to acquire material and environmental information of the gold finger plate;

[0016] The generation unit is used to generate pre-compensation coefficients by combining material and environmental information with a compensation model.

[0017] The production unit is used to manufacture the gold finger plate according to the pre-compensation coefficient.

[0018] Thirdly, the present invention provides a computer device, the computer device including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the above-described method.

[0019] Fourthly, the present invention provides a storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0020] The beneficial effects of this invention compared with the prior art are: by acquiring material and environmental information, generating pre-compensation coefficients and applying them to production, it effectively solves the problem of dimensional expansion and contraction of gold fingers on long-size LCD panels caused by seasonal temperature and humidity changes, bringing about technical effects of improving dimensional stability, reducing defect rate and improving production efficiency, and has broad application prospects.

[0021] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart illustrating a method for improving the stability of gold fingers according to an embodiment of the present invention.

[0024] Figure 2 A schematic block diagram of a device for improving the stability of gold fingers provided in an embodiment of the present invention;

[0025] Figure 3 This is a schematic diagram of the structure of the computer device in an embodiment of the present invention. Detailed Implementation

[0026] 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, not all, of the embodiments of the present invention. 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.

[0027] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0028] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0029] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0030] Please see Figure 1 The specific embodiment shown in the present invention discloses a method for improving the stability of gold fingers, comprising the following steps:

[0031] S110. Obtain material and environmental information for the gold finger plate;

[0032] Specifically, key parameters such as material type, thickness, coefficient of thermal expansion (CTE), and moisture content of the gold finger board substrate are obtained by consulting supplier-provided materials, product manuals, or using professional testing equipment. For example, a thermomechanical analyzer (TMA) is used to measure the dimensional changes of the substrate at different temperatures to determine its CTE; a moisture content meter is used to measure the initial moisture content of the substrate. For the conductive layer of the gold finger, data such as its material (e.g., copper, gold), thickness, and coating uniformity are recorded. The microstructure of the conductive layer can be observed using a metallographic microscope, and its thickness measured; X-ray fluorescence spectrometry (XRF) is used to analyze the composition and uniformity of the coating.

[0033] Temperature and humidity sensors are installed in the gold finger plate production workshop to monitor ambient temperature and humidity in real time. The sensors should be distributed in various locations to obtain comprehensive environmental data. For example, sensors should be installed at the workshop entrance, in the central area, and near heat sources or air conditioning vents to ensure the representativeness of the monitoring data. Environmental data from the production workshop over a past period should be collected and analyzed to understand environmental variation patterns across different seasons and time periods. This helps predict potential environmental conditions during future production and provides a more comprehensive basis for establishing compensation models.

[0034] In other words, comprehensive and accurate material information provides a solid foundation for adjusting subsequent production process parameters, ensuring the use of raw materials that meet quality requirements and improving the stability of the gold finger board from the source. Furthermore, timely acquisition of environmental information allows the production process to fully consider the impact of environmental factors on the performance of the gold finger board, enabling proactive countermeasures and preventing product quality issues caused by environmental fluctuations.

[0035] In one embodiment, obtaining the material information and environmental information of the gold finger plate includes:

[0036] Query production records or material management system to obtain information on the board manufacturer used for the current gold finger board, and confirm the specific size of the current gold finger board through design drawings or production instructions to obtain material information;

[0037] Specifically, production personnel or relevant technical staff log into the production record system or material management system using their personal accounts and passwords through the company's internal network terminals. In the system's search interface, they enter key information such as the batch number and order number of the gold finger plates currently in production or about to be produced to quickly locate the corresponding production record or material information entry. From the retrieved records, they carefully search for and extract the information of the board manufacturer used for the current gold finger plates, including the manufacturer's name, contact information, and board model. This information is recorded in detail in a dedicated material information registration form for subsequent analysis and processing. The design department uploads the design drawings of the gold finger plates to the company's internal shared document platform or design management system. Production personnel download the corresponding design drawings from the platform according to the production task schedule. Using professional drawing viewing software, such as AutoCAD, they open the design drawings and carefully examine the specific dimensional parameters of the gold finger plates, such as length, width, thickness, and the width, spacing, and length of the gold fingers, as indicated on the drawings. Production instructions are usually formulated by the production planning department based on customer needs and the production plan and issued to the production workshop. Production personnel carefully study the production instructions to confirm whether the dimensional requirements for the gold finger plates are consistent with the design drawings. If any discrepancies exist, promptly communicate and verify with the design and production planning departments to ensure the accuracy of the obtained dimensional information. Record the confirmed dimensional information in the material information registration form.

[0038] In other words, retrieving board manufacturer information through production records or the material management system avoids errors that may occur with manual recording and information transmission, ensuring the accuracy of material information. Simultaneously, the systematic query method significantly shortens information retrieval time and improves material management efficiency. For example, under traditional material management methods, finding board manufacturer information might take hours or even days, while a system query can complete the task within minutes. Furthermore, accurately recording board manufacturer information helps companies establish stable supply chain relationships, facilitating timely communication and coordination with manufacturers during subsequent production processes to resolve material supply and quality issues. Additionally, confirming the specific dimensions of the gold finger board through design drawings and production instructions ensures that production operations strictly adhere to design requirements. This avoids product quality problems caused by dimensional deviations, such as poor fit between the gold finger and external connectors, and unstable electrical connections. Detailed dimensional records provide a basis for subsequent quality traceability and production improvement. If size-related issues arise, the cause can be quickly located by querying records, allowing for appropriate corrective measures.

[0039] An OMS system is used to collect real-time temperature and humidity data from the production line to obtain environmental information.

[0040] Specifically, companies install an OMS (Operation Management System) on their production lines and strategically place temperature and humidity sensors at key locations, such as around production equipment and material storage areas. These sensors connect to the OMS system via wired or wireless connections to ensure real-time and accurate data transmission. The OMS system automatically collects data from the temperature and humidity sensors at preset time intervals (e.g., every minute, every five minutes). The collected data includes the collection time, temperature value, and humidity value. The system stores this data in a dedicated database for subsequent querying and analysis. When the current production line's temperature and humidity data is needed, production personnel or technicians input query criteria (e.g., current time, specific production line number) through the OMS system's interface. The system retrieves data matching the criteria from the database and displays it on the interface. Production personnel record this data in an environmental information registration form and can export the data to Excel or other formats for further processing and analysis.

[0041] In other words, the OMS system collects temperature and humidity data from the production line in real time, enabling companies to understand changes in the production environment promptly. This is crucial for the production of metal finger boards that are sensitive to environmental conditions, as changes in temperature and humidity can affect the physical properties of the board, leading to dimensional expansion and contraction of the metal fingers. Real-time monitoring of environmental information helps companies take proactive measures to address adverse environmental changes, such as adjusting air conditioning and humidification equipment in the production workshop to maintain environmental stability and reduce product quality fluctuations caused by environmental factors. Furthermore, obtaining accurate environmental information is fundamental for generating pre-compensation coefficients using a compensation model. By recording temperature and humidity data at different time points, the relationship between environmental changes and metal finger dimensional changes can be analyzed, providing rich data samples for the establishment and optimization of the compensation model. Pre-compensation coefficients generated based on accurate environmental information can more effectively offset the impact of environmental factors on metal finger dimensions, improving product dimensional stability and quality.

[0042] S120. A pre-compensation coefficient is generated by combining material and environmental information using a compensation model.

[0043] Specifically, a series of experiments are designed to fabricate gold finger plate samples under different material properties and environmental conditions, and to measure their dimensional changes. For example, the material, thickness, and coefficient of thermal expansion of the substrate, as well as the ambient temperature and humidity, are changed, and the dimensional changes of each sample before and after production are recorded. Based on the experimental data, statistical methods and mathematical modeling techniques are used to establish a mathematical relationship model between the dimensional changes of the gold finger plate and material and environmental information. Algorithms such as multiple linear regression and neural networks can be used, with material and environmental information as input variables and dimensional change as the output variable. By training and optimizing the model parameters, it can accurately predict the dimensional changes of the gold finger plate. The obtained material information and real-time environmental information of the current gold finger plate are input into the compensation model. Based on the input data, the compensation model calculates the amount of dimensional adjustment that needs to be made in advance during the production stage to offset the possible dimensional expansion and contraction of the gold finger plate during subsequent production, i.e., the pre-compensation coefficient. For example, if the model predicts that the gold finger plate will expand by 0.1 mm under specific environmental conditions, then the pre-compensation coefficient may be -0.1 mm (the negative sign indicates that the size needs to be reduced in advance during production).

[0044] In other words, the compensation model can accurately predict potential deviations in the performance of the gold finger board based on real-time material and environmental information, and generate corresponding pre-compensation coefficients. This allows for early intervention and adjustment of the production process, effectively improving the stability of the gold finger board. Automated model calculations and pre-compensation coefficient generation reduce manual intervention and trial-and-error costs, enabling the rapid determination of suitable production process parameters and improving production efficiency.

[0045] In one embodiment, the step of generating pre-compensation coefficients by combining material information and environmental information using a compensation model includes:

[0046] Based on the current size of the gold finger plate, a basic compensation coefficient is determined at room temperature; for gold finger plates smaller than 300mm, a fixed compensation coefficient is used; for gold finger plates greater than or equal to 300mm, the compensation coefficient is increased by 1% for every 100mm increase in size.

[0047] Specifically, after obtaining the current size of the gold finger plate, it is first classified. High-precision measuring tools, such as a coordinate measuring machine or image measuring instrument, are used to accurately measure the key dimensional parameters of the gold finger plate, such as length and width. If the gold finger plate size is less than 300mm, it is classified as a small size; if the size is greater than or equal to 300mm, it is classified as a large size. For small-sized gold finger plates less than 300mm, a fixed basic compensation coefficient is determined based on historical production data and experimental results. For example, after multiple experiments, it was found that small-sized gold finger plates usually have a certain tendency to shrink at room temperature due to material properties and other factors; therefore, the basic compensation coefficient is set to +0.05mm (the positive sign indicates that the size needs to be increased in advance during production to offset possible subsequent shrinkage). For large-sized gold finger plates greater than or equal to 300mm, the basic compensation coefficient is determined according to the rule of increasing by 1% for every 100mm increase in size, based on a fixed compensation coefficient. Assuming the basic compensation coefficient for a 300mm gold finger board is +0.1mm, when the gold finger board size is 400mm, the size increases by 100mm, and the basic compensation coefficient increases by 1%, i.e., +0.1mm × (1 + 1%) = +0.101mm; when the size is 500mm, another 100mm is added, and the basic compensation coefficient further increases by 1%, becoming +0.101mm × (1 + 1%) ≈ +0.102mm, and so on.

[0048] In other words, by classifying the size of the gold finger plate and using different methods to determine the basic compensation coefficient, the influence of size factors on the compensation coefficient can be considered more accurately. Small and large gold finger plates have different internal stress and thermal expansion characteristics, so using different compensation strategies can avoid errors caused by a one-size-fits-all approach and improve the accuracy of compensation.

[0049] The current temperature data is compared with the preset temperature range to determine the range to which the current temperature belongs;

[0050] Specifically, based on the thermal expansion characteristics of the gold finger plate material and actual production experience, multiple temperature ranges are preset. For example, the temperature is divided into a low-temperature range (-10℃ to 10℃), a normal-temperature range (10℃ to 30℃), and a high-temperature range (30℃ to 50℃). These range divisions help to more accurately analyze the impact of temperature on the dimensions of the gold finger plate. The collected current temperature data is compared with the preset temperature ranges. The current production environment temperature value is obtained through an OMS system or other temperature monitoring equipment, and then a comparison program is written using a programming language (such as Python) to determine which range the current temperature belongs to. For example, if the current temperature is 25℃, it belongs to the normal-temperature range.

[0051] In other words, dividing the temperature into multiple ranges allows for a more detailed reflection of the impact of temperature on the dimensions of the gold finger plate. The thermal expansion behavior of materials may differ across different temperature ranges; this detailed division allows for more accurate calculation of the temperature compensation amount, further improving the precision of the pre-compensation coefficient.

[0052] The temperature compensation amount is calculated based on the temperature range and the amount of temperature change.

[0053] Specifically, a reference temperature is recorded (e.g., the midpoint of the normal temperature range, 20℃), and the difference between the current temperature and the reference temperature is calculated to obtain the temperature change. For example, if the current temperature is 35℃, the temperature change is 35℃ - 20℃ = +15℃ (the positive sign indicates a temperature increase). Based on the temperature range and the temperature change, combined with parameters such as the material's coefficient of thermal expansion, the temperature compensation is calculated. Taking the normal temperature range as an example, assuming the coefficient of thermal expansion of the gold finger plate material is 10... -5 / ℃, for a gold finger board with a length of 400mm, when the temperature rises by 15℃, the temperature compensation amount = 400mm × 10 -5 / ℃×15℃=+0.006mm (The positive sign indicates that the size expands due to the increase in temperature, and the size needs to be reduced in advance during production to offset the subsequent expansion).

[0054] In other words, calculating the temperature compensation based on different temperature ranges and variations allows for a more detailed reflection of the impact of temperature on the dimensions of the gold finger plate. The thermal expansion behavior of materials may differ across different temperature ranges; this detailed approach enables more accurate calculation of the temperature compensation, further improving the precision of the pre-compensation coefficient.

[0055] The pre-compensation coefficient is generated by combining the basic compensation coefficient and the temperature compensation amount.

[0056] Specifically, the previously determined basic compensation coefficient and temperature compensation amount are combined. For example, for a 400mm gold finger board, the basic compensation coefficient is +0.101mm, and the temperature compensation amount is -0.006mm (here, temperature rises, and actual reverse compensation is needed, so it is negative). Therefore, the pre-compensation coefficient = basic compensation coefficient + temperature compensation amount = +0.101mm - 0.006mm = +0.095mm. Finally, the calculated pre-compensation coefficient is recorded in a dedicated production parameter table, and during the production process of the gold finger board, the design dimensions are adjusted according to this pre-compensation coefficient to ensure that the final produced gold finger board dimensions meet the design requirements.

[0057] In other words, a pre-compensation coefficient is generated by combining the basic compensation coefficient and the temperature compensation amount, comprehensively considering the dimensional characteristics of the gold finger board itself and the temperature factors of the production environment. This comprehensive compensation method can more fully offset the dimensional expansion and contraction that may occur in the gold finger board during the production process, effectively enhancing the dimensional stability of the product. Regardless of the production of gold finger boards of different sizes or under different temperature environments, this method can generate appropriate pre-compensation coefficients according to the actual situation, enabling the product to adapt to various production conditions and reducing the defect rate and quality problems caused by dimensional instability.

[0058] In one embodiment, for gold finger plates with a size less than 300mm: a fixed compensation coefficient is used: dynamically adjusted according to the temperature and humidity range of the production workshop, and the pre-compensation coefficient at room temperature (25℃) is taken as the fixed compensation coefficient L. When the temperature is less than 25℃, the fixed compensation coefficient needs to be increased. The specific formula is as follows:

[0059] L 补偿 =L 固定 +(K*L 固定 *ΔT);

[0060] When the temperature is above 25℃, the fixed compensation coefficient needs to be reduced. The specific formula is as follows:

[0061] L 补偿 =L 固定 -(K*L 固定 *ΔT).

[0062] Among them, L 补偿 This is a compensation value that needs to be provided; L 固定 This is a pre-compensation value obtained under normal production conditions (25℃). For example, after the entire production process of the gold finger board at 25℃, including material cutting, drilling, and packaging, one dimension of the gold finger board is L. 固定 K: is the coefficient of thermal expansion of conventional FR4 material, which is 14ppm / ℃ under normal conditions; ΔT is the temperature change value, that is, the absolute value of the current temperature minus the room temperature of 25℃. For example, if the current temperature is 15℃, ΔT is the absolute value of 15 minus 25, which is 10.

[0063] For gold finger plates with a size greater than or equal to 300mm, segmented compensation is adopted. For every 100mm increase in size, the fixed compensation coefficient increases by 1%. The compensation coefficient at room temperature (25℃) for a gripping size of 300mm is used as the fixed compensation coefficient L. The pre-compensation coefficient is dynamically adjusted according to the size range and temperature range.

[0064] In normal production, the pre-compensation coefficients provided by the production line are generally uniform, meaning that the pre-compensation coefficients for gold finger boards of 100-600mm size are consistent. This leads to the pre-compensation coefficients being too large for smaller boards during production, resulting in the finished product size being larger after STM. Similarly, larger boards are smaller after SMT. By providing segmented compensation for the two ranges, the cursor point-to-cursor point expansion and contraction data of gold finger boards of different sizes can be kept at the median value after the finished product SMT, ensuring that the tolerance is within ±100μm.

[0065] In one embodiment, temperature and humidity data of the production line are collected through the OMS system. The temperature is divided into regions of 0-10℃, 10-20℃, 20-30℃, and 30-40℃, with each region being 10℃. When the production line temperature is within a certain threshold for 72 consecutive hours, the compensation coefficient is automatically updated according to the above temperature compensation formula, and new data is sent to notify the production line to use the new data for production.

[0066] Because seasonal temperature variations affect workshop production temperature, the temperature may be only 3-8℃ in cold weather, while it can reach 35-45℃ in summer. This 30℃ difference has a significant impact on the size of the gold fingers. Therefore, it is necessary to monitor the temperature and humidity data of the production line in real time. When the data is continuously updated for 72 hours, the compensation coefficient is automatically triggered, the original data of the production line is retrieved, a new data for the corresponding temperature range is issued, and the production line personnel are notified to produce according to the new data.

[0067] In one embodiment, the compensation model is trained using big data, and the specific training steps are as follows:

[0068] Collect production data of gold finger boards from different board manufacturers and of different sizes under different temperature and humidity environments, including finished gold finger board expansion and contraction data, ambient temperature and humidity data during production, type of board used, and production batch information;

[0069] Specifically, partnerships are established with multiple board suppliers to record information on the boards provided by different manufacturers. Through the company's procurement system, detailed information such as the board manufacturer's name, contact information, and board specifications for each batch of gold finger boards is obtained. During production, high-precision measuring equipment, such as calipers and video measuring instruments, is used to measure the dimensions of different production batches of gold finger boards, recording key dimensional parameters such as length, width, thickness, and the width and spacing of the gold fingers. Temperature and humidity sensors are installed at different locations in the production workshop to collect real-time environmental temperature and humidity data during production. The sensors should possess high accuracy and stability, accurately recording temperature and humidity values ​​over different time periods. Simultaneously, the temperature and humidity data is correlated with the corresponding production batches. After the gold finger boards are produced, their actual dimensions are measured again using measuring equipment and compared with the design dimensions to calculate the finished product expansion and contraction data. The expansion and contraction data should include changes in length, width, and other directions. Through the company's production management system, production batch information for each gold finger board is obtained, including production date, production equipment number, and operator. The collected production data is stored in the company's database, with dedicated tables to store information on board manufacturers, dimensions, temperature and humidity, expansion and contraction data, and production batch information. Simultaneously, data relationships are established to ensure accurate matching of different data types through production batches.

[0070] In other words, by collecting production data from different board manufacturers and for different sizes of gold finger boards under different temperature and humidity conditions, a variety of factors that may affect the expansion and contraction of the gold finger boards are covered. This comprehensive data collection method provides rich samples for model training, enabling the model to learn more complex relationships between features and expansion and contraction, thereby improving the accuracy of the compensation model.

[0071] The collected production data is cleaned to remove outliers and missing values, and then classified and labeled to obtain a classification set.

[0072] Specifically, statistical methods, such as box plots, are used to identify outliers in the data. For data points that clearly exceed reasonable ranges, such as extreme values ​​in temperature and humidity data (temperature exceeding 100℃ or below -50℃, humidity exceeding 100%, etc.), further verification is required. If a measurement or recording error is confirmed, the data point is deleted directly; if the cause cannot be determined, the median or mean can be used as a replacement. The data is checked for missing values. For a small number of missing values, interpolation methods (such as linear interpolation or polynomial interpolation) can be used to fill them; for a large number of missing values, if the feature has little impact on subsequent analysis, the sample can be deleted directly. The cleaned data is categorized based on factors such as the size of the gold finger board, the board manufacturer, and the temperature and humidity of the production environment. For example, gold finger boards are categorized by size into small (less than 300mm), medium (300-600mm), and large (greater than 600mm); by board manufacturer into categories from different suppliers; and by temperature and humidity range into categories such as low temperature and low humidity, normal temperature and normal humidity, and high temperature and high humidity. Each sample data point is labeled with its corresponding gold finger plate expansion and contraction data. This transforms the data into the format required for supervised learning, facilitating subsequent model training.

[0073] In other words, the collected production data is cleaned, classified, and labeled, outliers and missing values ​​are removed, and the data is organized and labeled appropriately. This helps improve data quality, reduce noise interference, and enables the model to learn patterns in the data more accurately, further improving the model's accuracy.

[0074] Extract features related to the expansion and contraction of the gold finger from the classification set to obtain the feature set;

[0075] Specifically, features such as board type, material, and thickness are extracted from the board manufacturer's information. For example, different materials have different coefficients of thermal expansion and mechanical properties, which affect the expansion and contraction of the gold finger board. Dimensional parameters such as the length, width, and thickness of the gold finger board, as well as the width and spacing of the gold fingers, are used as features. Size is closely related to the internal stress and thermal expansion deformation of the board. Ambient temperature and humidity during production are also considered important features. Changes in temperature and humidity alter the physical properties of the board, thus affecting the dimensional stability of the gold finger board. The extracted features are combined to form a feature set. Each sample data point has a corresponding feature vector in the feature set, where each element represents the value of a feature.

[0076] In other words, by extracting features related to the expansion and contraction of the gold finger and constructing a feature set, the model can focus on the factors that have the greatest impact on expansion and contraction. At the same time, it avoids using irrelevant or redundant features, reduces the complexity of the model, improves the model's generalization ability, and enables the model to better adapt to data under different production conditions and make accurate predictions for new samples.

[0077] The linear regression model is trained using a feature set, and the model parameters are adjusted to minimize the prediction error, thus obtaining the compensation model.

[0078] Specifically, a linear regression model is chosen as the foundation of the compensation model. Linear regression is simple and easy to interpret, making it suitable for analyzing the linear relationship between features and the target variable (gold finger board product fluctuation data). The parameters of the linear regression model are initialized; typically, the weight parameters are set to small random values, and the bias parameters are set to 0. The feature set is used as input, and the gold finger board product fluctuation data is used as output to train the linear regression model. During training, the gradient descent algorithm is used to minimize the prediction error. The gradient descent algorithm continuously adjusts the model's parameters, gradually reducing the gap between the model's predicted and actual values. The model's performance is evaluated using cross-validation. The dataset is divided into training and validation sets, and multiple random partitions are performed for training and validation. The average prediction error of the model on the validation set is calculated. Based on the validation results, the model parameters, such as the learning rate and regularization parameters, are adjusted. The learning rate controls the step size of parameter updates; an appropriate learning rate can accelerate the model's convergence speed. The regularization parameter can prevent overfitting and improve the model's generalization ability. By continuously adjusting the parameters until the model's prediction error on the validation set reaches its minimum, the final compensation model is obtained.

[0079] In other words, cross-validation is used to evaluate and optimize the model. By randomly splitting the training and validation sets multiple times, a more comprehensive understanding of the model's performance on different datasets can be obtained. Adjusting model parameters based on the validation results prevents overfitting and ensures the model maintains good predictive performance even with unseen data, thus enhancing its generalization ability.

[0080] S130. Production of the gold finger plate is carried out according to the pre-compensation coefficient.

[0081] Specifically, during the circuit design phase of the gold finger board, the size and position of the gold fingers are adjusted accordingly based on the pre-compensation coefficient. For example, using professional PCB design software, the width, spacing, and layout of the gold fingers are modified to ensure that the final produced gold finger dimensions meet the design requirements after considering pre-compensation. The adjusted design is then simulated and verified to check whether the electrical connections and mechanical fit between the gold fingers and other circuit components meet the requirements. Electromagnetic simulation software can be used to simulate signal transmission, and mechanical simulation software can be used to analyze the stress and deformation of the gold fingers. During the production process of the gold finger board, relevant process parameters are adjusted according to the pre-compensation coefficient. For example, in the etching process, the concentration, temperature, and etching time of the etching solution are adjusted to control the dimensional accuracy of the gold fingers; in the lamination process, pressure, temperature, and time are adjusted to ensure the lamination quality of the substrate and reduce dimensional changes caused by internal stress.

[0082] In other words, by precisely adjusting production process parameters based on pre-compensation coefficients and monitoring and providing feedback on the production process in real time, the impact of material characteristics and environmental factors on the performance of the gold finger plate can be effectively eliminated, ensuring the consistency and stability of product quality. Furthermore, it reduces rework and scrap due to product quality issues, lowering production costs. Simultaneously, it improves production efficiency and product qualification rates, further enhancing the company's economic benefits.

[0083] In one embodiment, the step of manufacturing the gold finger plate according to the pre-compensation coefficient includes:

[0084] Update the production engineering data based on the received pre-compensation coefficients;

[0085] Specifically, the production department receives the pre-compensation coefficients from the department responsible for calculating them (such as R&D or data analysis) via internal communication systems (e.g., email) or dedicated interfaces. The coefficients can be received as electronic documents (e.g., Excel spreadsheets, CSV files) or directly through data transfer interfaces between systems. Specialized software tools or programming languages ​​(e.g., Python) are used to parse the received pre-compensation coefficients. For example, if the pre-compensation coefficients are provided in Excel spreadsheet format, Python's pandas library can be used to read the spreadsheet data and extract the pre-compensation coefficient values ​​corresponding to different sizes and types of gold finger plates. Simultaneously, information on the applicable production conditions (e.g., temperature range, humidity range) for the pre-compensation coefficients is also parsed.

[0086] Retrieve the current production engineering data for the gold finger board from the company's engineering data management system. This data typically includes circuit board design drawings (such as Gerber files), process flow documents, and bills of materials (BOMs). The system's search function can be used to quickly locate and retrieve this data based on key information such as the gold finger board's model and batch number. Within the retrieved engineering data, locate the sections related to the gold finger board's dimensional design. For example, in the circuit board design drawings, find the locations where dimensional parameters such as the gold finger board's length, width, and gold finger spacing are indicated; in the process flow documents, find the descriptions of the process steps related to dimensional adjustments.

[0087] Based on the pre-compensation coefficient obtained from the analysis, calculate the updated values ​​for each dimensional parameter of the gold finger board. For example, if the original design gold finger board length is 400mm and the pre-compensation coefficient is +0.095mm (meaning that 0.095mm needs to be added in advance to offset possible subsequent shrinkage), then the updated length = original length + pre-compensation coefficient = 400mm + 0.095mm = 400.095mm. Other dimensional parameters (such as width, gold finger spacing, etc.) are calculated using the same method. Open the circuit board design drawing using professional engineering software (such as Altium Designer, Cadence Allegro, etc.) and modify the located dimensional parameters. Simultaneously, update the process parameters related to the dimensional adjustments in the process flow file, such as drilling dimensions and etching parameters, to ensure that the entire production process can be carried out according to the updated dimensional requirements. Submit the updated production engineering data to relevant reviewers (such as process engineers and quality engineers) for review. Reviewers will check whether the modifications to the dimensional parameters are reasonable and whether they meet the product design requirements and production process specifications. If any problems are found, they will be promptly reported to the production department for correction. Once approved, the updated project data will be saved to the company's project data management system, and version records will be maintained. Simultaneously, relevant file indexes and directories will be updated to ensure that other departments (such as purchasing and production planning departments) can easily access the latest project data.

[0088] In other words, by updating the production process data according to the pre-compensation coefficient and strictly following the updated data during production, the dimensions of the gold finger board can be accurately compensated effectively. The pre-compensation coefficient takes into account various factors affecting dimensional expansion and contraction, such as board characteristics and environmental factors, making the dimensions of the produced gold finger board closer to the design requirements and improving the dimensional accuracy of the product.

[0089] The production of the gold finger plate will be carried out according to the updated production engineering data.

[0090] Specifically, the production planning department analyzes the production demand for gold finger plates based on customer orders and updated production engineering data. This determines key information such as production batches, quantities, and production times. For example, based on the demand for different models of gold finger plates in the order, the production sequence and cycle are rationally arranged. According to the production plan, resources required for production are allocated, including raw materials (such as boards, chemicals, etc.), production equipment (such as printing presses, etching machines, drilling machines, etc.), and operators. This ensures a sufficient supply and reasonable allocation of resources during the production process. Production operators debug the production equipment according to the updated process flow documents. For example, they set the printing parameters of the printing press (such as squeegee pressure and printing speed), and the etching time and temperature of the etching machine, ensuring that the equipment can produce according to the updated dimensional requirements. During production, operators strictly follow the process flow, monitoring the equipment's operating status and product quality. Multiple quality inspection points are set up during production to conduct real-time inspections of the dimensions and appearance of the gold finger plates. For example, high-precision measuring instruments (such as coordinate measuring machines and optical measuring instruments) are used to randomly inspect the dimensions of the gold finger boards to ensure that their dimensions meet the updated engineering data requirements. Simultaneously, the surface quality of the gold finger boards is checked for defects such as scratches and bubbles. After the gold finger boards are produced, a comprehensive finished product inspection is conducted. In addition to dimensional and appearance inspections, electrical performance tests (such as continuity tests and insulation resistance tests) are performed to ensure that the products meet quality standards. Non-conforming products are marked and isolated, the causes are analyzed, and rework or scrapping is carried out.

[0091] In other words, by rationally arranging the production process based on the updated engineering data, the production flow becomes smoother. Departments can collaborate more effectively, reducing production delays caused by inconsistencies in engineering data and improving production efficiency. Furthermore, the updated production engineering data provides a unified standard for the entire production process, ensuring consistency in the size and quality of gold finger plates produced in different batches and under different production environments. In addition, the complete process of updating and recording engineering data facilitates quality traceability. When quality problems occur, the specific production stage and engineering data version can be quickly located, the cause of the problem can be analyzed, and corresponding improvement measures can be taken to further improve product quality.

[0092] In one embodiment, the step of manufacturing the gold finger plate according to the updated production engineering data includes:

[0093] During the production process, the OMS system is used to monitor the temperature and humidity data of the production line in real time;

[0094] Specifically, a temperature and humidity monitoring module is configured in the OMS system, setting sensor parameters such as sampling frequency (e.g., once per minute) and data storage period. Simultaneously, a unique identifier is assigned to each sensor for accurate identification and management within the system. The temperature and humidity sensors collect temperature and humidity data from the production line in real time according to the set sampling frequency and transmit the data to the OMS system. The OMS system performs preliminary processing on the collected data, such as data format conversion and verification, to ensure data accuracy and integrity. The processed temperature and humidity data is stored in the OMS system's database. The database should have good storage performance and data management capabilities, capable of classifying and storing data according to dimensions such as time and sensor location for easy subsequent querying and analysis. The OMS system's monitoring interface displays the production line's temperature and humidity data in the form of charts (e.g., line graphs, bar charts) or real-time numerical values. Operators can intuitively understand the current temperature and humidity status of the production environment through the monitoring interface. Temperature and humidity alarm thresholds are set in the OMS system; when the monitored temperature and humidity data exceeds the preset range, the system automatically triggers an alarm mechanism. Alarm methods can include audible alarms, SMS notifications, and email alerts to ensure relevant personnel are promptly informed of any abnormalities.

[0095] In other words, the real-time monitoring and alarm functions of the OMS system can promptly detect abnormal situations in the production environment, enabling production managers to take swift action to address them.

[0096] If the monitored temperature and humidity data exceed the preset range, the pre-compensation coefficient will be recalculated according to the compensation model to form the latest production data;

[0097] Specifically, when the OMS system alarms and indicates that temperature and humidity data exceeds the preset range, the system automatically marks the temperature and humidity data within that time period as abnormal. Simultaneously, it records the time and location of the abnormal data occurrence for subsequent analysis. The marked abnormal data is further verified to rule out false anomalies caused by sensor malfunctions or data transmission errors. Verification can be performed by comparing data from adjacent sensors or viewing historical data trends. The verified abnormal temperature and humidity data, along with other relevant information for the current production batch (such as board type, gold finger board size, etc.), is input into the compensation model. The compensation model is a linear regression model trained on previously large datasets, capable of calculating corresponding pre-compensation coefficients based on the input feature data. The compensation model calculates new pre-compensation coefficients based on the input data. During the calculation process, the model comprehensively considers the impact of temperature and humidity changes on board expansion and contraction, as well as the relationship between features learned during previous training and expansion and contraction. Based on the recalculated pre-compensation coefficients, the current production engineering data is updated. Updated content includes dimensional parameters in the circuit board design drawings and relevant process parameters in the process flow documents. Version management is implemented for the updated production engineering data, recording the time, reason, and content of each update. At the same time, the latest version of production data is saved to the company's engineering data management system to ensure that other departments (such as production planning department and quality inspection department) can obtain the latest data in a timely manner.

[0098] In other words, recalculating the pre-compensation coefficient in a timely manner when the temperature and humidity exceed the preset range enables the production process of the gold finger board to better adapt to changes in the actual production environment, reduces the problem of inconsistent expansion and contraction of the board caused by fluctuations in ambient temperature and humidity, and improves the stability of product dimensions.

[0099] The gold finger plate is manufactured in accordance with the latest production engineering data.

[0100] Specifically, production operators adjust the production equipment according to the process parameters in the latest production engineering data. For example, they adjust the printing pressure of the printing press and the etching time of the etching machine to ensure the equipment can produce according to the new dimensional requirements. After the equipment is adjusted, operators strictly follow the latest production engineering data for production operations. During production, they closely monitor the operating status of the equipment and the quality of the products, and promptly report and handle any abnormalities.

[0101] In other words, production is carried out according to the latest production engineering data, which ensures that each production batch of products can be produced under the same quality standards, avoids quality fluctuations caused by untimely updates of production data, and improves the overall quality level of the products.

[0102] In one embodiment, during the production process, all gold finger plates are arranged in the same direction to reduce asymmetric stress during the pressing process. Abnormal plates are corrected using a "translation adjustment method" to avoid drill strip stretching deformation. The normal adjustment methods for plates with excessive expansion and contraction during pressing include "stretching" and "translation." Stretching involves stretching or shrinking the drill strip along its X and Y axes based on the designed expansion and contraction data from the pressing process, causing changes in the pre-compensation coefficient given in advance during the stretching process. "Translation" is achieved by adjusting the position of the SET within the PNL plate, moving the SET up, down, left, and right.

[0103] Fixed exposure factor: The outer layer exposure parameters are set to X:1.00005 and Y:1.00005 to ensure consistency in production across batches.

[0104] Oriented placement: During production, the PCB board is placed with the gold fingers facing in the same direction to reduce mechanical stress interference.

[0105] In one embodiment, after the production of the gold finger plate according to the pre-compensation coefficient, the process further includes:

[0106] Classify the completed gold finger plates;

[0107] Specifically, based on the design drawings of the gold finger plates and customer requirements, classification standards are established based on specifications such as size, number of gold fingers, and spacing. For example, gold finger plates with a length of 400-450mm and a gold finger spacing of 0.5mm are grouped into one category, while those with a length of 450-500mm and a gold finger spacing of 0.6mm are grouped into another. Alternatively, classification can be based on production batches. Different batches may differ in raw materials, production process parameters, etc., and separate classification helps with subsequent data analysis. For example, gold finger plates produced in the first week of October 2024 are grouped into one category, and those produced in the second week are grouped into another.

[0108] In other words, classification facilitates the separate management and tracking of gold finger plates of different specifications and production batches. During subsequent production, quality inspection, and delivery processes, relevant products can be quickly located and processed, improving production management efficiency. Furthermore, the classified data is more conducive to targeted analysis, enabling more accurate identification of differences in expansion and contraction performance among different specifications and production batches, providing stronger support for optimizing production processes.

[0109] Set up or use an existing simulated client SMT environment to simulate the IR furnace scenario, including setting appropriate temperature profiles and heating times;

[0110] Specifically, if it is chosen to set up a new simulated client SMT environment, necessary equipment such as IR oven simulation equipment, temperature sensors, and heating plates need to be procured. Place the IR oven simulation equipment in a dedicated laboratory, install the heating plates and temperature sensors, and ensure stable and reliable connections between the devices. Install and configure the control software supporting the IR oven simulation equipment, and set appropriate temperature profiles and heating durations via the software. The temperature profile shall be simulated according to the process requirements of the IR oven in actual production, for example, setting the temperature and time parameters for the temperature rising stage, temperature holding stage, and temperature dropping stage.

[0111] If an existing simulated client SMT environment is used, the environment shall first be evaluated to check whether the operating status of the equipment and the temperature control accuracy meet the requirements. A standard thermometer may be used to calibrate the temperature in the environment to ensure the accuracy of measurement results. Appropriate adjustments shall be made to the temperature profile and heating duration in the existing environment according to the requirements of the current simulation. For example, if the material of the gold finger board for the current simulation is different from that in the past, the temperature rising rate and holding temperature may need to be adjusted to better simulate the actual production process.

[0112] That is, the scenario of simulating the IR oven process can detect in advance the expansion and contraction problems that may occur to the gold finger board during the actual production process, avoid a large number of unqualified products in formal production, and reduce production costs. In addition, by adjusting and optimizing the simulation environment, process parameters such as the temperature profile and heating duration most suitable for gold finger board production can be found, so as to improve the quality and stability of the products.

[0113] Perform dimensional measurement on the gold finger board that has undergone the IR oven simulation, and record the expansion and contraction data at 24H, 48H, and 72H after passing through the IR oven;

[0114] Specifically, high-precision measurement equipment such as a coordinate measuring machine and a laser scanner is used to perform dimensional measurement on the gold finger board that has undergone the IR oven simulation. Before performing the measurement, the measurement equipment is calibrated to ensure the accuracy and reliability of the measurement results. The calibration operation is performed in accordance with the operation manual of the equipment, and calibration data is recorded. After the gold finger board undergoes the IR oven simulation, initial dimensional measurement is performed immediately, and the dimensional data of the gold finger board at this time is recorded. In addition, the gold finger board is measured again at 24H, 48H, and 72H after passing through the IR oven, and the dimensional data at different time points are recorded. During the measurement process, the measurement environment (such as temperature and humidity) is kept relatively stable to reduce the impact of environmental factors on the measurement results.

[0115] In other words, recording expansion and contraction data at different time points allows for a comprehensive understanding of the dimensional changes of the gold finger plate after passing through the IR furnace, including short-term and long-term expansion and contraction trends, providing a more accurate basis for product quality control. Furthermore, analysis of expansion and contraction data can identify problems in product design and manufacturing processes, enabling timely improvements and optimizations to enhance product performance and reliability.

[0116] All categorized finished product expansion and contraction data are uploaded to the OMS system in real time to form a database;

[0117] Specifically, immediately after measurement, the expansion and contraction data is uploaded to the OMS system via a data interface. Upon receiving the data, the OMS system performs data verification and storage operations. A dedicated database is built within the OMS system to store the categorized finished product expansion and contraction data. The database should possess robust data storage and management capabilities, able to organize and store data according to classification criteria, time, and other dimensions.

[0118] In other words, by uploading expansion and contraction data to the OMS system in real time and creating a database, centralized data management and sharing are achieved. Personnel from various departments can easily query and analyze data through the OMS system, improving data utilization efficiency. The data in the database provides strong support for the company's production and quality control decisions. For example, the production department can adjust production plans based on the data, and the quality department can formulate stricter quality inspection standards based on the data.

[0119] Based on data in the database, trend reports on price fluctuations are generated periodically.

[0120] Specifically, statistical analysis methods are employed to analyze the fluctuation data in the database, such as calculating statistics like the mean, standard deviation, maximum, and minimum values, to understand the distribution and trends of the fluctuation data. Trend prediction algorithms (such as linear regression and time series analysis) are used to predict the fluctuation of the stock price over a future period. Furthermore, a template for a fluctuation data trend report is designed, including a report title, data charts (such as line charts and bar charts), and analysis conclusions. Following a predetermined time period (such as weekly or monthly), data analysis algorithms are used to process the data in the database, generating fluctuation data trend reports. These reports are then distributed to relevant departments and personnel through internal corporate communication systems (such as email and WeChat) to ensure they are promptly informed about the fluctuations of the stock price.

[0121] In other words, regularly generated price fluctuation trend reports allow companies to promptly grasp the changing trends of the price fluctuations of the gold finger plate, and identify potential problems and risks in advance. Furthermore, based on the analysis conclusions and suggestions in the trend reports, companies can continuously improve production processes and product design, thereby enhancing product quality and competitiveness.

[0122] In one embodiment, all gold finger expansion and contraction data are uploaded to the OMS system in real time, covering parameters such as production batch, size, temperature and humidity, and compensation value. The finished product expansion and contraction data are then analyzed and categorized by size, part number, and board manufacturer. A scenario simulating the client's SMT process involving an IR oven is implemented, monitoring data after the IR oven process and at 24, 48, and 72 hours post-processing. Tolerances are tightened to ±80µm, and a historical production database is established and monitored.

[0123] In addition, the factory tolerance standard was raised from ±150μm to ±80μm. When the tolerance is exceeded, the system will automatically alarm and push adjustment instructions. When the data exceeds the tolerance, the out-of-tolerance data is analyzed. When the out-of-tolerance data is at the upper limit, the difference between the mean of the out-of-tolerance data and the standard value is the pre-compensation value. The pre-compensation coefficient ((out-of-tolerance value - standard value) / standard value) is calculated simultaneously. The original pre-compensation coefficient used in production is subtracted from the out-of-tolerance pre-compensation coefficient to optimize the system. The abnormal temperature change process described above is also followed.

[0124] In addition, trend reports are generated based on the database, and the compensation model is optimized to improve long-term stability. Specifically, monthly trend reports are generated annually based on monthly fluctuation data. This allows for the optimization of the required fluctuation data for the current year's production based on the monthly fluctuation data from previous years, preventing deviations caused by temporary temperature changes.

[0125] This invention effectively solves the problem of dimensional expansion and contraction of gold fingers on long-size LCD panels caused by seasonal temperature and humidity changes by acquiring material and environmental information, generating pre-compensation coefficients, and applying them to production. It brings about technical effects such as improving dimensional stability, reducing defect rate, and increasing production efficiency, and has broad application prospects.

[0126] Figure 2 This is a schematic block diagram of a device 300 for improving the stability of gold fingers according to an embodiment of the present invention. Figure 2 As shown, corresponding to the above-described method for improving the stability of gold fingers, the present invention also provides an apparatus 300 for improving the stability of gold fingers. This apparatus 300 includes a unit for performing the above-described method for improving the stability of gold fingers, and the apparatus can be configured in a server. Specifically, please refer to... Figure 2 The device 300 for improving the stability of the gold finger includes:

[0127] Acquisition unit 301 is used to acquire material information and environmental information of the gold finger plate;

[0128] Generation unit 302 is used to generate pre-compensation coefficients by combining material information and environmental information with a compensation model;

[0129] Production unit 303 is used to produce the gold finger plate according to the pre-compensation coefficient.

[0130] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the device 300 for improving the stability of the gold finger and each unit can be referred to the corresponding description in the foregoing method embodiments. For the sake of convenience and brevity, it will not be repeated here.

[0131] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external clients via a network connection. When the computer program is executed by the processor, it implements server-side functions or steps of a method to improve the stability of a gold finger.

[0132] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps:

[0133] Obtain material and environmental information for the gold finger board; generate pre-compensation coefficients by combining the material and environmental information using a compensation model; and execute the production of the gold finger board based on the pre-compensation coefficients.

[0134] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0135] Obtain material and environmental information for the gold finger board; generate pre-compensation coefficients by combining the material and environmental information using a compensation model; and execute the production of the gold finger board based on the pre-compensation coefficients.

[0136] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions on the server side and client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0137] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0138] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0139] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for improving the stability of gold fingers, characterized in that, include: Obtain material and environmental information for the gold finger plate; A compensation model is used to generate pre-compensation coefficients by combining material and environmental information. The production of the gold finger plate is carried out according to the pre-compensation coefficient; The acquisition of material and environmental information for the gold finger plate includes: Query production records or material management system to obtain information on the board manufacturer used for the current gold finger board, and confirm the specific size of the current gold finger board through design drawings or production instructions to obtain material information; An OMS system is used to collect real-time temperature and humidity data from the production line to obtain environmental information. The method of generating pre-compensation coefficients by combining material and environmental information using a compensation model includes: Based on the current size of the gold finger plate, a basic compensation coefficient is determined at room temperature; for gold finger plates smaller than 300mm, a fixed compensation coefficient is used; for gold finger plates greater than or equal to 300mm, the compensation coefficient is increased by 1% for every 100mm increase in size. The current temperature data is compared with the preset temperature range to determine the range to which the current temperature belongs; The temperature compensation amount is calculated based on the temperature range and the amount of temperature change. The pre-compensation coefficient is generated by combining the basic compensation coefficient and the temperature compensation amount.

2. The method for improving the stability of gold fingers according to claim 1, characterized in that, The compensation model is trained using big data, and the specific training steps are as follows: Collect production data of gold finger boards from different board manufacturers and of different sizes under different temperature and humidity environments, including finished gold finger board expansion and contraction data, ambient temperature and humidity data during production, type of board used, and production batch information; The collected production data is cleaned to remove outliers and missing values, and then classified and labeled to obtain a classification set. Extract features related to the expansion and contraction of the gold finger from the classification set to obtain the feature set; The linear regression model is trained using a feature set, and the model parameters are adjusted to minimize the prediction error, thus obtaining the compensation model.

3. The method for improving the stability of gold fingers according to claim 1, characterized in that, The process of manufacturing the gold finger plate according to the pre-compensation coefficient includes: Update the production engineering data based on the received pre-compensation coefficients; The production of the gold finger plate will be carried out according to the updated production engineering data.

4. The method for improving the stability of gold fingers according to claim 3, characterized in that, The process of manufacturing the gold finger plate according to the updated production engineering data includes: During the production process, the OMS system is used to monitor the temperature and humidity data of the production line in real time; If the monitored temperature and humidity data exceed the preset range, the pre-compensation coefficient will be recalculated according to the compensation model to form the latest production data; The gold finger plate is manufactured in accordance with the latest production engineering data.

5. The method for improving the stability of gold fingers according to claim 1, characterized in that, After the gold finger plate is manufactured according to the pre-compensation coefficient, the process also includes: Classify the completed gold finger plates; Set up or use an existing simulated client SMT environment to simulate the IR furnace scenario, including setting appropriate temperature profiles and heating times; The dimensions of the gold finger plate after IR furnace simulation were measured, and the expansion and contraction data after IR were recorded at 24H, 48H and 72H. All categorized finished product expansion and contraction data are uploaded to the OMS system in real time to form a database; Based on data in the database, trend reports on price fluctuations are generated periodically.

6. A device for improving the stability of gold fingers, characterized in that, include: The acquisition unit is used to acquire material and environmental information of the gold finger plate; The generation unit is used to generate pre-compensation coefficients by combining material and environmental information with a compensation model. The production unit is used to manufacture the gold finger plate according to the pre-compensation coefficient. The acquisition unit includes: The query and confirmation module is used to query production records or the material management system to obtain information on the board manufacturer used for the current gold finger board, and to confirm the specific size of the current gold finger board through design drawings or production instructions to obtain material information. The data acquisition module is used to collect real-time temperature and humidity data of the production line using the OMS system to obtain environmental information; The generation unit includes: The determination module is used to determine a basic compensation coefficient at room temperature based on the current size of the gold finger board. For gold finger boards smaller than 300mm, a fixed compensation coefficient is used. For gold finger boards greater than or equal to 300mm, the compensation coefficient is determined according to the rule that it increases by 1% for every 100mm increase in size. The comparison and determination module is used to compare the current temperature data with a preset temperature range to determine the range to which the current temperature belongs; The calculation module is used to calculate the temperature compensation amount based on the temperature range and the amount of temperature change. The generation module is used to generate pre-compensation coefficients by combining the basic compensation coefficient and the temperature compensation amount.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 5.

8. A storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 5.

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