Reflow soldering process evaluation method and system, electronic device and storage medium

Abstract

The application belongs to the technical field of reflow soldering process evaluation, and discloses a reflow soldering process evaluation method, system, electronic device and storage medium. The method comprises the following steps: obtaining target processing product information of a reflow soldering furnace during process processing and temperature detection data of a substitute temperature measuring device, inputting the temperature detection data into a preset temperature mapping model for calculation to obtain virtual temperature measuring plate temperature data of the reflow soldering furnace, performing process stability evaluation based on the virtual temperature measuring plate temperature data and the target processing product information to obtain process stability evaluation result information, performing thermal performance analysis and processing based on the virtual temperature measuring plate temperature data and the target processing product information to obtain thermal performance analysis result information, and generating a reflow soldering furnace process evaluation report based on the process stability evaluation result information and the thermal performance analysis result information. Through the above method, the evaluation efficiency of the reflow soldering process is improved.

Description

Technical Field

[0001] This application relates to the technical field of reflow soldering process evaluation, and more specifically, to a reflow soldering process evaluation method, system, electronic device, and storage medium. Background Technology

[0002] Reflow soldering, a core process in surface mount technology, relies heavily on precise temperature profile control to determine solder joint quality and product reliability. Currently, the industry commonly uses a physical temperature sensing plate in conjunction with K-type thermocouples for reflow soldering temperature profile testing. Specifically, this method requires fabricating a dedicated physical temperature sensing plate based on the PCB's layer stack-up, copper foil distribution, and component layout, and then soldering or attaching thermocouples at key locations. Subsequently, the temperature sensing plate, along with a temperature recorder, is run through the reflow oven to collect temperature data, which is then used to verify process parameters and serve as a baseline profile for mass production.

[0003] However, the aforementioned existing technical solutions have many inherent defects, leading to challenges in practical applications. First, the production cost of physical temperature measuring plates is high, consuming not only PCB materials and components but also requiring significant labor costs for soldering. More importantly, multiple sets of temperature measuring plates of different specifications need to be manufactured for different products, making their storage and maintenance complex and inefficient. Second, thermocouples are consumables; after repeated use, their solder joints are prone to loosening, and cables may be bent, both of which significantly reduce temperature measurement accuracy. Simultaneously, the physical properties of the temperature measuring plate itself degrade after repeated high-temperature shocks, typically requiring replacement after only 30 uses, further increasing operating costs. Third, existing testing procedures heavily rely on the operational experience of professional personnel, resulting in poor data repeatability and difficulty in ensuring the consistency and reliability of test results. Furthermore, the testing method using physical temperature measuring plates is destructive, allowing only offline sampling and cannot reflect the furnace's operating condition in real time during production, making it difficult to promptly detect and intervene in potential problems during production. Finally, the existing solution can only output temperature curves and lacks the ability to quantitatively analyze the multi-dimensional thermal performance of reflow ovens, such as thermal uniformity, heat transfer efficiency, heat convection stability and thermal performance consistency. As a result, it is difficult to identify the trend of furnace aging or heating abnormalities in advance, which brings difficulties to the optimization of the production process and fault early warning.

[0004] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0005] The purpose of this application is to provide a reflow soldering process evaluation method, system, electronic device, and storage medium to solve the problems of existing reflow soldering process evaluation methods that use physical temperature measuring plates for temperature acquisition, such as high cost, easily compromised temperature measurement accuracy, reliance on experience for operation, inability to monitor in real time, and lack of thermal performance analysis capabilities. This will enable the generated reflow soldering furnace process evaluation report to comprehensively and in real time reflect the operating conditions of the reflow soldering furnace, so as to identify abnormal problems in the furnace body in advance and improve the processing efficiency of the reflow soldering process.

[0006] Firstly, this application provides a method for evaluating reflow soldering processes, including: To obtain information on the target products being processed in the reflow oven and temperature detection data from alternative temperature measuring devices; The temperature detection data is input into a preset temperature mapping model for calculation to obtain the virtual temperature measuring plate temperature data of the reflow oven; Based on the temperature data of the virtual temperature measuring plate and the information of the target processed product, a process stability assessment is performed to obtain the process stability assessment result information; Based on the temperature data of the virtual temperature measuring plate and the information of the target processed product, thermal performance analysis is performed to obtain thermal performance analysis results. Based on the process stability assessment results and the thermal performance analysis results, a reflow oven process evaluation report is generated.

[0007] The reflow soldering process evaluation method provided in this application can evaluate the reflow soldering process. By inputting temperature detection data into a preset temperature mapping model to calculate virtual temperature plate temperature data, process stability assessment and thermal performance analysis are performed to obtain process stability assessment results and thermal performance analysis results, thereby generating a reflow soldering furnace process evaluation report. This method solves the problems of existing reflow soldering process evaluation methods that use physical temperature plates for temperature acquisition, such as high cost, easily compromised temperature measurement accuracy, reliance on experience for operation, inability to monitor in real time, and lack of thermal performance analysis capabilities. By introducing alternative temperature measurement devices and virtual temperature plate technology, and performing process stability assessment and thermal performance analysis, the generated reflow soldering furnace process evaluation report can comprehensively and in real time reflect the operating conditions of the reflow soldering furnace, thereby identifying furnace abnormalities in advance and improving the evaluation efficiency of the reflow soldering process.

[0008] Optionally, the preset temperature mapping model is constructed through the following steps: Acquire historical temperature data of the physical temperature measuring plate of the reflow oven and historical temperature detection data corresponding to the historical temperature measuring plate; the historical temperature detection data is historical data detected by temperature detection through the alternative temperature measuring device. The historical temperature data of the physical temperature measuring plate and the historical temperature detection data are time-aligned to obtain aligned historical temperature data. Construct an initial temperature calculation model corresponding to the aligned historical temperature data; Based on the aligned historical temperature data, the initial temperature calculation model is trained and validated to obtain the preset temperature mapping model.

[0009] Optionally, based on the temperature data of the virtual temperature measuring plate and the target processed product information, a process stability assessment is performed to obtain process stability assessment result information, including: Determine the reference temperature information corresponding to the target processed product information; By comparing the temperature data from the virtual temperature measuring plate with the reference temperature information, the process stability assessment results are obtained.

[0010] Optionally, based on the temperature data of the virtual temperature measuring plate and the target processed product information, thermal performance analysis is performed to obtain thermal performance analysis results, including: Based on the target processed product information, determine the target parameter type information and the target parameter calculation method corresponding to the target parameter type information; Based on the temperature data of the virtual temperature measuring plate and the target parameter type information, the thermal performance parameters corresponding to the target parameter type information are calculated using the target parameter calculation method. Based on the aforementioned thermal performance parameters, thermal performance analysis is performed to obtain thermal performance analysis results.

[0011] The reflow soldering process evaluation method provided in this application can evaluate the reflow soldering process. Through the calculation and analysis of thermal performance parameters, it can deeply explore the thermal performance characteristics of the reflow soldering furnace, making up for the shortcomings of traditional methods that can only output temperature curves, and providing richer data support for the comprehensive evaluation of furnace condition and fault early warning.

[0012] Optionally, based on the target processed product information, determining the target parameter type information and the target parameter calculation method corresponding to the target parameter type information includes: Based on a preset thermal performance analysis strategy, the target parameter type information corresponding to the target processed product information is determined; Determine the initial parameter calculation method corresponding to the target parameter type information; Based on the target processed product information, the initial parameter calculation method is adjusted to obtain the target parameter calculation method.

[0013] The reflow soldering process evaluation method provided in this application can evaluate the reflow soldering process. By flexibly adjusting the parameter calculation method, it can better adapt to different product and process requirements, improve the pertinence and accuracy of thermal performance analysis, and thus make the evaluation results more instructive.

[0014] Optionally, based on the thermal performance parameters, thermal performance analysis is performed to obtain thermal performance analysis results, including: Determine the reference thermal performance parameter information corresponding to the aforementioned thermal performance parameters; By comparing the thermal performance parameters with the reference thermal performance parameters, the thermal performance analysis results are obtained.

[0015] Optionally, based on the process stability assessment results and the thermal performance analysis results, a reflow oven process evaluation report is generated, including: When there are abnormal prompts in the process stability assessment results and the thermal performance analysis results, warning information and abnormal suggestion information are determined according to the type and severity of the abnormal indication information. Identify process deviation data of the reflow oven from the process stability assessment results and the thermal performance analysis results; Identify the potential causes of the process deviation data and provide process adjustment recommendations; Based on the process stability assessment results and the thermal performance analysis results, combined with the early warning information, the anomaly suggestion information, the process deviation, the potential cause information, and the process adjustment suggestion information, a reflow oven process evaluation report is generated.

[0016] Secondly, this application provides a reflow soldering process evaluation system, comprising: The acquisition module is used to acquire information about the target product being processed in the reflow oven during the process, as well as temperature detection data from the alternative temperature measuring device. The calculation module is used to input the temperature detection data into a preset temperature mapping model for calculation to obtain the virtual temperature measuring plate temperature data of the reflow oven; The evaluation module is used to perform a process stability evaluation based on the temperature data of the virtual temperature measuring plate and the target processed product information, and obtain the process stability evaluation result information. The analysis module is used to perform thermal performance analysis based on the temperature data of the virtual temperature measuring plate and the information of the target processed product, and to obtain thermal performance analysis results. The generation module is used to generate a reflow oven process evaluation report based on the process stability assessment results and the thermal performance analysis results.

[0017] This reflow soldering process evaluation system calculates virtual temperature data from a pre-set temperature mapping model by inputting temperature detection data into the virtual temperature plate. It then performs process stability assessment and thermal performance analysis to generate a reflow soldering furnace process evaluation report. This system addresses the problems of existing reflow soldering process evaluation methods that rely on physical temperature plates for temperature acquisition, such as high cost, compromised measurement accuracy, reliance on experience, inability to monitor in real time, and lack of thermal performance analysis capabilities. By introducing alternative temperature measurement devices and virtual temperature plate technology, and performing process stability assessment and thermal performance analysis, the generated reflow soldering furnace process evaluation report comprehensively and in real-time reflects the operating conditions of the reflow soldering furnace, enabling early identification of furnace abnormalities and improving the efficiency of reflow soldering process evaluation.

[0018] Thirdly, this application provides an electronic device including a processor and a memory, the memory storing a computer program executable by the processor, wherein when the processor executes the computer program, it performs the steps in the reflow soldering process evaluation method described above.

[0019] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the steps of the reflow soldering process evaluation method described above.

[0020] Beneficial Effects: The reflow soldering process evaluation method, system, electronic equipment, and storage medium provided in this application calculate virtual temperature data from a temperature measuring plate by inputting temperature detection data into a preset temperature mapping model. This data is then used for process stability assessment and thermal performance analysis to generate a reflow soldering furnace process evaluation report. This addresses the problems of existing reflow soldering process evaluation methods that rely on physical temperature measuring plates for temperature acquisition, such as high cost, easily compromised temperature measurement accuracy, reliance on experience, inability to monitor in real time, and lack of thermal performance analysis capabilities. By introducing alternative temperature measuring devices and virtual temperature measuring plate technology, and performing process stability assessment and thermal performance analysis, the generated reflow soldering furnace process evaluation report can comprehensively and in real-time reflect the operating conditions of the reflow soldering furnace, enabling early identification of furnace abnormalities and improving the efficiency of reflow soldering process evaluation. Attached Figure Description

[0021] Figure 1 A flowchart of the reflow soldering process evaluation method provided in the embodiments of this application.

[0022] Figure 2 This is a schematic diagram of the reflow soldering process evaluation system provided in an embodiment of this application.

[0023] Figure 3This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0024] Labeling Explanation: 1. Acquisition Module; 2. Calculation Module; 3. Evaluation Module; 4. Analysis Module; 5. Generation Module; 301. Processor; 302. Memory; 303. Communication Bus. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0026] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0027] Please refer to Figure 1 , Figure 1 This application provides a reflow soldering process evaluation method in some embodiments, used to evaluate the reflow soldering process, comprising the following steps: Step S101: Obtain the target product information and temperature detection data of the alternative temperature measuring device during the reflow oven process. Step S102: Input the temperature detection data into the preset temperature mapping model for calculation to obtain the virtual temperature measuring plate temperature data of the reflow oven; Step S103: Based on the temperature data of the virtual temperature measuring plate and the target processed product information, perform a process stability assessment to obtain the process stability assessment result information; Step S104: Based on the temperature data of the virtual temperature measuring plate and the target processed product information, perform thermal performance analysis to obtain thermal performance analysis results. Step S105: Based on the process stability assessment results and thermal performance analysis results, generate a reflow oven process evaluation report.

[0028] This reflow soldering process evaluation method inputs temperature detection data into a preset temperature mapping model to calculate virtual temperature plate temperature data. This data is then used for process stability assessment and thermal performance analysis to generate a reflow soldering furnace process evaluation report. This method addresses the problems of existing reflow soldering process evaluation methods that rely on physical temperature plates for temperature acquisition, such as high cost, compromised temperature measurement accuracy, reliance on experience, inability to monitor in real time, and lack of thermal performance analysis capabilities. By introducing alternative temperature measurement devices and virtual temperature plate technology, and performing process stability assessment and thermal performance analysis, the generated reflow soldering furnace process evaluation report can comprehensively and in real-time reflect the operating conditions of the reflow soldering furnace, enabling early identification of furnace abnormalities and improving the efficiency of reflow soldering process evaluation.

[0029] Specifically, in step S101, the target product information and temperature detection data from the alternative temperature measuring device are acquired during the reflow soldering process. The reflow soldering process refers to the entire process of soldering surface-mount components in an electronic manufacturing process using a reflow oven. Its core lies in precisely controlling the temperature profile within the oven to ensure solder joint quality. The target product information refers to relevant information about the printed circuit board (PCB) to be reflow soldered and its components, such as the PCB's size, number of layers, material, component type, layout, and heat-sensitive areas. This information is crucial for subsequent temperature profile evaluation and thermal performance analysis. It can be obtained through the product ID of the current production batch or entered manually. The alternative temperature measuring device is a non-contact or non-invasive temperature measurement device, such as a K-type thermocouple, infrared thermometer, thermal imager, thermal capacity module, or a temperature sensor integrated inside the reflow oven. It can collect temperature data of the oven environment in real-time or near real-time. However, this data is not the direct solder joint temperature but rather indirectly reflects the thermal state of the oven. Temperature detection data refers to the raw temperature data collected by the alternative temperature measuring device. It may deviate from the actual solder joint temperature and needs to be corrected and mapped through the model.

[0030] Specifically, in step S102, the temperature detection data is input into a preset temperature mapping model for calculation to obtain the virtual temperature data of the reflow oven's temperature measuring plate. The temperature mapping model can be a machine learning model trained on historical data, such as a Support Vector Machine (SVM), Neural Network (NN), or Random Forest model. Upon receiving real-time temperature detection data, this data is used as input features to the model. The model performs calculations using internal complex algorithms and outputs predicted virtual temperature measuring plate temperature data. For example, the model can receive multiple temperature point data collected from different locations by an infrared thermometer, and combine this data with parameters such as heat capacity and thermal conductivity from the target product information to calculate the virtual temperature curves of key temperature measuring points on the PCB board using the trained model.

[0031] Specifically, the preset temperature mapping model is constructed through the following steps: Acquire historical temperature data of the physical temperature measuring plate of the reflow oven and the corresponding historical temperature detection data; the historical temperature detection data is the historical data detected by temperature detection through an alternative temperature measuring device. Time alignment is performed on the historical temperature data and historical temperature detection data of the physical temperature measuring plate to obtain the aligned historical temperature data. Construct an initial temperature calculation model corresponding to the aligned historical temperature data; Based on the aligned historical temperature data, the initial temperature calculation model is trained and validated to obtain the preset temperature mapping model.

[0032] In constructing the temperature mapping model, historical temperature data from physical temperature measuring plates refers to historical temperature records obtained by actually placing temperature measuring plates inside the reflow oven and measuring the temperature. This data reflects the actual temperature distribution and changes during the actual operation of the reflow oven. Historical temperature detection data refers to historical data obtained through alternative temperature measuring devices (e.g., infrared sensors, thermocouple arrays, etc.). This data may not be the direct plate surface temperature, but it is related to the internal thermal environment of the reflow oven. This historical data is typically continuously collected and stored during the daily operation or specific testing of the reflow oven.

[0033] Because the data acquisition frequency or timestamps of the physical temperature measuring plate and the alternative temperature measuring device may differ, time synchronization processing of these two types of historical data is necessary to ensure the accuracy of subsequent model construction. Time alignment can be achieved through methods such as interpolation, resampling, or finding the most recent time point to ensure that the temperature data of the physical temperature measuring plate and the temperature detection data of the alternative temperature measuring device can correspond one-to-one at the same time point, thereby forming a dataset with time consistency.

[0034] Construct an initial temperature calculation model corresponding to the aligned historical temperature data. This initial temperature calculation model can be a machine learning model, such as a model built using existing algorithms like linear regression, support vector machines, neural networks, or decision trees. Its purpose is to establish a mapping relationship between temperature detection data from the alternative temperature measuring device and the temperature data from the physical temperature measuring plate. This initial temperature calculation model can learn and capture the complex nonlinear relationship between the temperature detection data and the physical temperature measuring plate data.

[0035] Historical temperature data, aligned to the given time, is used as both the training and validation sets to optimize the parameters and evaluate the performance of the initial temperature calculation model. The training process aims to minimize the error between the virtual temperature data output by the model and the actual temperature data from the physical temperature measuring plate by iteratively adjusting the model parameters. The validation process uses an independent validation set to assess the model's generalization ability and accuracy, ensuring good performance even on unseen data. After sufficient training and validation, when the model achieves the expected performance metrics, it can be adopted as the preset temperature mapping model.

[0036] Specifically, in step S103, based on the temperature data from the virtual temperature measuring plate and the target processed product information, a process stability assessment is performed to obtain process stability assessment result information, including: Determine the reference temperature information corresponding to the target processed product information; By comparing the temperature data from the virtual temperature measuring plate with the reference temperature information, the process stability assessment results are obtained.

[0037] In step S103, a standardized temperature profile or key temperature parameters are pre-set or acquired as an evaluation benchmark for a specific target product. This reference temperature information can be determined by comprehensively considering factors such as the characteristics of the target product, the type of solder paste used, the heat resistance of components, and industry standards. For example, an ideal temperature window or target temperature profile can be established for each product based on historical production data, simulation results, or expert experience.

[0038] By comparing the calculated virtual temperature sensor data with the aforementioned determined reference temperature information, process stability assessment results can be obtained. This comparison process can employ various methods, such as calculating the temperature deviation between the virtual temperature sensor data and the reference temperature information at the same time point or in the same area, evaluating the similarity of the temperature curve shapes, or determining whether key temperature points (such as preheating zone temperature, reflow zone peak temperature, cooling rate, etc.) fall within a preset tolerance range. Through this quantitative comparison, the degree of deviation between the current operating state of the reflow oven process and the ideal state can be objectively reflected, thereby generating specific process stability assessment results.

[0039] Specifically, in step S104, based on the temperature data from the virtual temperature measuring plate and the target processed product information, thermal performance analysis is performed to obtain thermal performance analysis results, including: Based on the target product information, determine the target parameter type information and the corresponding target parameter calculation method; Based on the temperature data of the virtual temperature measuring plate and the target parameter type information, the thermal performance parameters corresponding to the target parameter type information are obtained by using the target parameter calculation method. Based on the thermal performance parameters, thermal performance analysis is performed to obtain thermal performance analysis results.

[0040] Specifically, in step S104, based on the target processed product information, the target parameter type information and the corresponding target parameter calculation method are determined, including: Based on a preset thermal performance analysis strategy, determine the target parameter type information corresponding to the target processed product information; Determine the initial parameter calculation method corresponding to the target parameter type information; Based on the target product information, the initial parameter calculation method is adjusted to obtain the target parameter calculation method.

[0041] In step S104, the preset thermal performance analysis strategy is a predefined set of rules. Its purpose is to intelligently select or recommend the most suitable parameter types for thermal performance analysis based on different characteristics of the target processed product information (such as product size, material type, component density, number of solder joints, etc.). For example, for high-density integrated circuit boards, the strategy may recommend focusing on local temperature difference, heating slope, and immersion time; while for large power device boards, it may focus more on overall temperature uniformity and cooling rate.

[0042] Target parameter type information refers to the specific categories of thermal performance indicators of interest during thermal performance analysis, such as peak temperature, heating rate, cooling rate, wetting time, maximum temperature difference, and temperature uniformity. At least two parameters can be selected as thermal performance parameters based on a preset thermal performance analysis strategy, allowing for multi-dimensional analysis of the reflow soldering process's thermal performance. These parameter types are dynamically determined based on the preset thermal performance analysis strategy and the target processed product information to ensure the comprehensiveness and relevance of the analysis.

[0043] The initial parameter calculation method refers to a general calculation method or formula that is preset for a specific target parameter type before considering the specific product details. For example, the initial method for calculating the peak temperature may be to take the highest value among all temperature measurement points, or the initial method for calculating the average heating rate may be to take the average slope of all temperature measurement points over a specific time period.

[0044] Based on the specific characteristics of the target processed product information (such as component layout, heat capacity distribution, and sensitivity requirements of specific areas), the above initial parameter calculation method can be modified, optimized, or parameterized. For example, for areas with specific sensitive components, the temperature data of that area can be given higher weight in the calculation, or a more complex interpolation algorithm can be introduced to estimate the temperature of unmeasured points, so that the final target parameter calculation method can more accurately reflect the actual thermal performance of the current product.

[0045] By introducing a pre-defined thermal performance analysis strategy, the required target parameter types can be intelligently and specifically determined based on the specific characteristics of the target processed product, thus ensuring the comprehensiveness and relevance of the thermal performance analysis. Based on this, by first determining the initial parameter calculation method corresponding to the target parameter type information and then finely adjusting it based on the target processed product information, the final target parameter calculation method can fully consider the unique attributes and process requirements of the product, avoiding the deviations or inapplicability that may arise from using a single, general calculation method. Therefore, when subsequently calculating thermal performance parameters based on virtual temperature plate data and these optimized target parameter calculation methods, the obtained parameters will be more accurate and adapted to the current processed product, significantly improving the accuracy and reliability of the thermal performance analysis.

[0046] For example, suppose we need to evaluate the reflow soldering process for two different target products: a small, low-density circuit board and a large, high-density, multilayer circuit board. When determining the target parameter types and calculation methods, we first identify, based on a pre-defined thermal performance analysis strategy, that for small circuit boards, the focus might be more on the uniformity of peak temperature and cooling rate; while for large, high-density circuit boards, a more detailed analysis of temperature differences, wetting times, and heating slopes in different regions might be needed. Specifically, for small circuit boards, the initial parameter calculation method might be a simple average temperature calculation formula; but for large, high-density circuit boards, a more complex region division and weighted average algorithm might be required. Subsequently, based on the specific dimensions, materials, and component layout of each target product, these initial parameter calculation methods are adjusted. For example, for high-density circuit boards, the weights of temperature sampling points in different regions can be adjusted according to the component distribution density and heat capacity, or a local hotspot analysis algorithm can be introduced to obtain a more realistic target parameter calculation method. This approach ensures that the selection of parameters and calculation methods for thermal performance analysis are highly adaptable to the characteristics of different products, thereby improving the accuracy and guidance of the evaluation.

[0047] In step S104, after determining the target parameter type information and the corresponding target parameter calculation method, the virtual temperature measuring plate temperature data obtained through the temperature mapping model is combined with the determined target parameter type information and the corresponding target parameter calculation method to perform actual numerical calculations. Thus, multiple dimensions of thermal performance indicators can be extracted from a single temperature curve, forming a comprehensive set of thermal performance parameters. For example, peak temperatures in different regions, heating / cooling rates at different stages, and residence time within a specific temperature range can be calculated.

[0048] Optionally, in step S104, based on the thermal performance parameters, thermal performance analysis is performed to obtain thermal performance analysis results, which may specifically include: Determine the reference thermal performance parameter information corresponding to the thermal performance parameters; By comparing the thermal performance parameters with the reference thermal performance parameters, the thermal performance analysis results are obtained.

[0049] Specifically, in step S104, based on the selected thermal performance parameters, corresponding reference thermal performance parameter information can be determined. The reference thermal performance parameter information refers to a pre-set or determined ideal or acceptable range or specific value of thermal performance parameters based on historical experience data, industry standards, product specifications, etc. This reference information serves as an evaluation benchmark to measure whether the thermal performance of the current reflow oven process meets the requirements.

[0050] By comparing the calculated thermal performance parameters with preset reference thermal performance parameters, the thermal performance analysis results can be obtained. This comparison can be conducted in various ways, such as determining whether the actual parameters fall within the allowable range of the reference parameters, or calculating the deviation between the actual and reference parameters.

[0051] By identifying and comparing reference thermal performance parameters with the actual thermal performance parameters, the thermal performance of the reflow oven process can be systematically evaluated. Significant deviations between the actual thermal performance parameters and the reference parameters indicate that the actual thermal performance of the reflow oven may be abnormal or fail to meet preset standards. This comparison mechanism transforms thermal performance analysis from a simple parameter listing into a quantitative judgment based on clear evaluation criteria, thereby accurately identifying potential problems in the process.

[0052] Optionally, in step S105, based on the process stability assessment results and thermal performance analysis results, a reflow oven process evaluation report is generated, which may specifically include: When abnormal information is found in the process stability assessment results and thermal performance analysis results, warning information and abnormal suggestion information are determined according to the type and severity of the abnormal indication information. Identify process deviation data of the reflow oven from the process stability assessment results and the thermal performance analysis results; Identify the potential causes of process deviations and provide recommendations for process adjustments; Based on the results of process stability assessment and thermal performance analysis, combined with early warning information, anomaly suggestions, process deviations, potential causes, and process adjustment suggestions, a reflow oven process evaluation report is generated.

[0053] Specifically, in step S105, when abnormal indication information is detected in the process stability assessment results and thermal performance analysis results, warning information and abnormal suggestion information can be automatically generated based on the type and severity information of the abnormality. The abnormal indication information refers to indicators detected in the process stability assessment results or thermal performance analysis results that suggest potential problems in the reflow soldering process. These abnormal indication information may include, but is not limited to, temperature exceeding limits, abnormal heating rate, abnormal cooling rate, and peak temperature deviation. The type information can be a classification identifier for the abnormal indication information, such as "temperature abnormality," "time abnormality," or "uniformity abnormality." The severity information is used to quantify the degree of harm or urgency of the abnormality; for example, based on the degree of deviation in the abnormal data, the severity information can be divided into "minor," "moderate," and "serious." The warning information is a alert issued to the user based on the type and severity information of the abnormal indication information, such as "furnace temperature is too low, please pay attention." The abnormal suggestion information is a preliminary handling suggestion provided for a specific abnormal situation, such as "check the power supply to the heating zone."

[0054] From the process stability assessment results and thermal performance analysis results, specific data that differ from the standard or target process parameters are extracted. These process deviation data may include the degree of deviation between the actual temperature curve and the target temperature curve, the temperature fluctuation range of each temperature zone, and the temperature difference at specific time points. These data are all within acceptable ranges and are not considered abnormal data.

[0055] Based on the identified process deviation data, combined with a pre-set knowledge base, expert experience, or machine learning models, the possible causes of these deviations are analyzed, and corresponding process adjustment solutions are provided. Potential cause information may include equipment malfunctions (such as heater damage or fan abnormalities), improper parameter settings, and environmental interference. Process adjustment suggestions can be specific, such as adjusting the set temperature of a particular temperature zone, changing the conveyor belt speed, or inspecting equipment components.

[0056] Finally, based on the process stability assessment results and thermal performance analysis results, combined with early warning information, anomaly suggestions, process deviations, potential cause information, and process adjustment suggestions, a reflow oven process evaluation report is generated. This report integrates all analysis results and recommendations into a comprehensive, detailed, and instructive document, transforming abstract evaluation results into concrete and actionable guidance, enabling users to quickly locate problems and take effective improvement measures.

[0057] For example, suppose that during the reflow soldering process evaluation of a batch of products, virtual temperature sensor data is calculated using a temperature mapping model, and process stability assessment and thermal performance analysis are performed based on this data and the target product information. If the evaluation results show that in the third temperature zone of the reflow oven, the virtual temperature sensor data is consistently lower than the reference temperature information corresponding to the target product information, and the heating rate is significantly lower than the standard value (i.e., the difference between the virtual temperature sensor data and the reference temperature information is greater than the preset temperature difference threshold, and the duration is greater than the preset abnormal time, where the preset temperature difference threshold and preset abnormal time can be set according to actual needs), then an abnormal warning message of "low temperature in the third temperature zone" will be identified. At this time, according to the preset rules, the type of the abnormality is determined to be "temperature abnormality", and the severity is determined to be "moderate". Subsequently, a warning message is generated, such as "Warning: The temperature in the third temperature zone of the reflow oven is too low, which may lead to cold solder joints or poor wetting," and abnormal suggestion information is provided, such as "Suggestion: Check the working status of the heater in the third temperature zone or increase the set temperature."

[0058] Furthermore, when specific process deviation data is identified, such as the actual peak temperature of the third temperature zone being 5°C lower than the target value (within acceptable limits), or the heating time being extended by 15 seconds (within acceptable limits), comparison with a pre-set knowledge base may determine the potential cause as "aging or insufficient power of the third temperature zone heater," and provide process adjustment suggestions, such as "replacing the third temperature zone heater, or increasing the third temperature zone set temperature by 5-8°C and re-verifying the temperature." Ultimately, all this information, including process stability assessment results, thermal performance analysis results, early warning information, anomaly suggestions, process deviations, potential cause information, and process adjustment suggestions, will be integrated into a comprehensive reflow oven process evaluation report, providing production personnel with comprehensive process diagnosis and improvement guidance.

[0059] As can be seen from the above, this reflow soldering process evaluation method obtains the target product information and temperature detection data from an alternative temperature measuring device during the reflow soldering process. The temperature detection data is then input into a preset temperature mapping model for calculation to obtain virtual temperature plate temperature data for the reflow soldering furnace. Based on the virtual temperature plate temperature data and the target product information, a process stability assessment is performed to obtain the process stability assessment result. Furthermore, based on the virtual temperature plate temperature data and the target product information, thermal performance analysis is conducted to obtain the thermal performance analysis result. Finally, based on the process stability assessment result and the thermal performance analysis result, a reflow soldering furnace process evaluation report is generated. Thus, by inputting temperature detection data into the preset temperature mapping model... The virtual temperature plate temperature data obtained through calculation is used for process stability assessment and thermal performance analysis to generate a reflow oven process evaluation report. This addresses the problems of existing reflow oven process evaluation methods that rely on physical temperature plates for temperature acquisition, such as high cost, easily compromised temperature measurement accuracy, reliance on experience, inability to monitor in real time, and lack of thermal performance analysis capabilities. By introducing alternative temperature measurement devices and virtual temperature plate technology, and performing process stability assessment and thermal performance analysis, the generated reflow oven process evaluation report can comprehensively and in real time reflect the operating conditions of the reflow oven, enabling early identification of oven abnormalities and improving the efficiency of reflow oven process evaluation.

[0060] refer to Figure 2 This application provides a reflow soldering process evaluation system for evaluating the reflow soldering process, including: Module 1 is used to acquire information about the target product being processed in the reflow oven and temperature detection data from the alternative temperature measuring device during the process. Calculation module 2 is used to input temperature detection data into a preset temperature mapping model for calculation to obtain virtual temperature measurement plate temperature data of the reflow oven; Evaluation module 3 is used to evaluate the process stability based on the temperature data of the virtual temperature measuring plate and the target processed product information, and obtain the process stability evaluation result information; Analysis module 4 is used to perform thermal performance analysis based on the temperature data of the virtual temperature measuring plate and the information of the target processed product, and obtain thermal performance analysis results. Module 5 is used to generate a reflow oven process evaluation report based on the process stability assessment results and thermal performance analysis results.

[0061] This reflow soldering process evaluation system calculates virtual temperature data from a pre-set temperature mapping model by inputting temperature detection data into the virtual temperature plate. It then performs process stability assessment and thermal performance analysis to generate a reflow soldering furnace process evaluation report. This system addresses the problems of existing reflow soldering process evaluation methods that rely on physical temperature plates for temperature acquisition, such as high cost, compromised measurement accuracy, reliance on experience, inability to monitor in real time, and lack of thermal performance analysis capabilities. By introducing alternative temperature measurement devices and virtual temperature plate technology, and performing process stability assessment and thermal performance analysis, the generated reflow soldering furnace process evaluation report comprehensively and in real-time reflects the operating conditions of the reflow soldering furnace, enabling early identification of furnace abnormalities and improving the efficiency of reflow soldering process evaluation.

[0062] Specifically, when module 1 is executed, it acquires information about the target product being processed in the reflow oven and temperature data from an alternative temperature measuring device. The reflow oven process refers to the entire process of soldering surface-mount components in electronic manufacturing using a reflow oven. Its core lies in precisely controlling the temperature profile within the oven to ensure solder joint quality. The target product information refers to relevant information about the printed circuit board (PCB) to be reflow soldered and its components, such as the PCB's size, number of layers, material, component type, layout, and heat-sensitive areas. This information is crucial for subsequent temperature profile evaluation and thermal performance analysis. It can be obtained through the product ID of the current production batch or entered manually. The alternative temperature measuring device is a non-contact or non-invasive temperature measurement device, such as a K-type thermocouple, infrared thermometer, thermal imager, thermal capacity module, or a temperature sensor integrated inside the reflow oven. It can collect temperature data of the oven environment in real-time or near real-time. However, this data is not the direct solder joint temperature but rather indirectly reflects the thermal state of the oven. Temperature detection data refers to the raw temperature data collected by the alternative temperature measuring device. It may deviate from the actual solder joint temperature and needs to be corrected and mapped through the model.

[0063] Specifically, during execution, calculation module 2 inputs temperature detection data into a preset temperature mapping model for calculation, obtaining virtual temperature data for the reflow oven's temperature measuring plate. The temperature mapping model can be a machine learning model trained on historical data, such as a Support Vector Machine (SVM), Neural Network (NN), or Random Forest model. Upon receiving real-time temperature detection data, this data is used as input features to the model. The model then performs calculations using internal complex algorithms, outputting predicted virtual temperature measuring plate temperature data. For example, the model can receive multiple temperature data points collected from different locations by an infrared thermometer, and combine this data with parameters such as heat capacity and thermal conductivity from the target product information to calculate the virtual temperature curves for key temperature measuring points on the PCB board using the trained model.

[0064] Specifically, the preset temperature mapping model is constructed through the following steps: Acquire historical temperature data of the physical temperature measuring plate of the reflow oven and the corresponding historical temperature detection data; the historical temperature detection data is the historical data detected by temperature detection through an alternative temperature measuring device. Time alignment is performed on the historical temperature data and historical temperature detection data of the physical temperature measuring plate to obtain the aligned historical temperature data. Construct an initial temperature calculation model corresponding to the aligned historical temperature data; Based on the aligned historical temperature data, the initial temperature calculation model is trained and validated to obtain the preset temperature mapping model.

[0065] In constructing the temperature mapping model, historical temperature data from physical temperature measuring plates refers to historical temperature records obtained by actually placing temperature measuring plates inside the reflow oven and measuring the temperature. This data reflects the actual temperature distribution and changes during the actual operation of the reflow oven. Historical temperature detection data refers to historical data obtained through alternative temperature measuring devices (e.g., infrared sensors, thermocouple arrays, etc.). This data may not be the direct plate surface temperature, but it is related to the internal thermal environment of the reflow oven. This historical data is typically continuously collected and stored during the daily operation or specific testing of the reflow oven.

[0066] Because the data acquisition frequency or timestamps of the physical temperature measuring plate and the alternative temperature measuring device may differ, time synchronization processing of these two types of historical data is necessary to ensure the accuracy of subsequent model construction. Time alignment can be achieved through methods such as interpolation, resampling, or finding the most recent time point to ensure that the temperature data of the physical temperature measuring plate and the temperature detection data of the alternative temperature measuring device can correspond one-to-one at the same time point, thereby forming a dataset with time consistency.

[0067] Construct an initial temperature calculation model corresponding to the aligned historical temperature data. This initial temperature calculation model can be a machine learning model, such as a model built using existing algorithms like linear regression, support vector machines, neural networks, or decision trees. Its purpose is to establish a mapping relationship between temperature detection data from the alternative temperature measuring device and the temperature data from the physical temperature measuring plate. This initial temperature calculation model can learn and capture the complex nonlinear relationship between the temperature detection data and the physical temperature measuring plate data.

[0068] Historical temperature data, aligned to the given time, is used as both the training and validation sets to optimize the parameters and evaluate the performance of the initial temperature calculation model. The training process aims to minimize the error between the virtual temperature data output by the model and the actual temperature data from the physical temperature measuring plate by iteratively adjusting the model parameters. The validation process uses an independent validation set to assess the model's generalization ability and accuracy, ensuring good performance even on unseen data. After sufficient training and validation, when the model achieves the expected performance metrics, it can be adopted as the preset temperature mapping model.

[0069] Specifically, when evaluation module 3 performs a process stability assessment based on virtual temperature plate temperature data and target processed product information, and obtains the process stability assessment results, it executes the following: Determine the reference temperature information corresponding to the target processed product information; By comparing the temperature data from the virtual temperature measuring plate with the reference temperature information, the process stability assessment results are obtained.

[0070] When executing the evaluation module 3, a standardized temperature profile or key temperature parameters are pre-set or acquired as an evaluation benchmark for a specific target product. This reference temperature information can be comprehensively considered and determined based on factors such as the characteristics of the target product, the type of solder paste used, the heat resistance of components, and industry standards. For example, an ideal temperature window or target temperature profile can be established for each product based on historical production data, simulation results, or expert experience.

[0071] By comparing the calculated virtual temperature sensor data with the aforementioned determined reference temperature information, process stability assessment results can be obtained. This comparison process can employ various methods, such as calculating the temperature deviation between the virtual temperature sensor data and the reference temperature information at the same time point or in the same area, evaluating the similarity of the temperature curve shapes, or determining whether key temperature points (such as preheating zone temperature, reflow zone peak temperature, cooling rate, etc.) fall within a preset tolerance range. Through this quantitative comparison, the degree of deviation between the current operating state of the reflow oven process and the ideal state can be objectively reflected, thereby generating specific process stability assessment results.

[0072] Specifically, when analysis module 4 performs thermal performance analysis based on the temperature data from the virtual temperature measuring plate and the target processed product information to obtain the thermal performance analysis results, it executes the following: Based on the target product information, determine the target parameter type information and the corresponding target parameter calculation method; Based on the temperature data of the virtual temperature measuring plate and the target parameter type information, the thermal performance parameters corresponding to the target parameter type information are obtained by using the target parameter calculation method. Based on the thermal performance parameters, thermal performance analysis is performed to obtain thermal performance analysis results.

[0073] Specifically, when analysis module 4 determines the target parameter type information and the corresponding target parameter calculation method based on the target processed product information, it executes the following: Based on a preset thermal performance analysis strategy, determine the target parameter type information corresponding to the target processed product information; Determine the initial parameter calculation method corresponding to the target parameter type information; Based on the target product information, the initial parameter calculation method is adjusted to obtain the target parameter calculation method.

[0074] When the analysis module 4 is executed, the preset thermal performance analysis strategy is a predefined set of rules. Its purpose is to intelligently select or recommend the most suitable parameter types for thermal performance analysis based on the different characteristics of the target processed product information (such as product size, material type, component density, number of solder joints, etc.). For example, for high-density integrated circuit boards, the strategy may recommend focusing on local temperature difference, heating slope, and immersion time; while for large power device boards, it may focus more on overall temperature uniformity and cooling rate.

[0075] Target parameter type information refers to the specific categories of thermal performance indicators of interest during thermal performance analysis, such as peak temperature, heating rate, cooling rate, wetting time, maximum temperature difference, and temperature uniformity. At least two parameters can be selected as thermal performance parameters based on a preset thermal performance analysis strategy, allowing for multi-dimensional analysis of the reflow soldering process's thermal performance. These parameter types are dynamically determined based on the preset thermal performance analysis strategy and the target processed product information to ensure the comprehensiveness and relevance of the analysis.

[0076] The initial parameter calculation method refers to a general calculation method or formula that is preset for a specific target parameter type before considering the specific product details. For example, the initial method for calculating the peak temperature may be to take the highest value among all temperature measurement points, or the initial method for calculating the average heating rate may be to take the average slope of all temperature measurement points over a specific time period.

[0077] Based on the specific characteristics of the target processed product information (such as component layout, heat capacity distribution, and sensitivity requirements of specific areas), the above initial parameter calculation method can be modified, optimized, or parameterized. For example, for areas with specific sensitive components, the temperature data of that area can be given higher weight in the calculation, or a more complex interpolation algorithm can be introduced to estimate the temperature of unmeasured points, so that the final target parameter calculation method can more accurately reflect the actual thermal performance of the current product.

[0078] By introducing a pre-defined thermal performance analysis strategy, the required target parameter types can be intelligently and specifically determined based on the specific characteristics of the target processed product, thus ensuring the comprehensiveness and relevance of the thermal performance analysis. Based on this, by first determining the initial parameter calculation method corresponding to the target parameter type information and then finely adjusting it based on the target processed product information, the final target parameter calculation method can fully consider the unique attributes and process requirements of the product, avoiding the deviations or inapplicability that may arise from using a single, general calculation method. Therefore, when subsequently calculating thermal performance parameters based on virtual temperature plate data and these optimized target parameter calculation methods, the obtained parameters will be more accurate and adapted to the current processed product, significantly improving the accuracy and reliability of the thermal performance analysis.

[0079] For example, suppose we need to evaluate the reflow soldering process for two different target products: a small, low-density circuit board and a large, high-density, multilayer circuit board. When determining the target parameter types and calculation methods, we first identify, based on a pre-defined thermal performance analysis strategy, that for small circuit boards, the focus might be more on the uniformity of peak temperature and cooling rate; while for large, high-density circuit boards, a more detailed analysis of temperature differences, wetting times, and heating slopes in different regions might be needed. Specifically, for small circuit boards, the initial parameter calculation method might be a simple average temperature calculation formula; but for large, high-density circuit boards, a more complex region division and weighted average algorithm might be required. Subsequently, based on the specific dimensions, materials, and component layout of each target product, these initial parameter calculation methods are adjusted. For example, for high-density circuit boards, the weights of temperature sampling points in different regions can be adjusted according to the component distribution density and heat capacity, or a local hotspot analysis algorithm can be introduced to obtain a more realistic target parameter calculation method. This approach ensures that the selection of parameters and calculation methods for thermal performance analysis are highly adaptable to the characteristics of different products, thereby improving the accuracy and guidance of the evaluation.

[0080] During execution, analysis module 4, after determining the target parameter type information and the corresponding target parameter calculation method, uses the virtual temperature measuring plate temperature data obtained through the temperature mapping model, combined with the determined target parameter type information and corresponding calculation method, to perform actual numerical calculations. This allows for the extraction of multiple dimensions of thermal performance indicators from a single temperature curve, forming a comprehensive set of thermal performance parameters. For example, it can calculate peak temperatures in different regions, heating / cooling rates at different stages, and residence time within a specific temperature range.

[0081] Optionally, when the analysis module 4 performs thermal performance analysis based on the thermal performance parameters to obtain thermal performance analysis results, it may specifically perform the following: determine the reference thermal performance parameter information corresponding to the thermal performance parameters; compare the thermal performance parameters and the reference thermal performance parameter information to obtain thermal performance analysis results.

[0082] Specifically, during execution, analysis module 4 determines the corresponding reference thermal performance parameters based on the selected thermal performance parameters. These reference thermal performance parameters refer to pre-set or determined ideal or acceptable ranges or specific values ​​of thermal performance parameters based on historical experience data, industry standards, product specifications, etc. This reference information serves as an evaluation benchmark to measure whether the thermal performance of the current reflow oven process meets the requirements.

[0083] By comparing the calculated thermal performance parameters with preset reference thermal performance parameters, the thermal performance analysis results can be obtained. This comparison can be conducted in various ways, such as determining whether the actual parameters fall within the allowable range of the reference parameters, or calculating the deviation between the actual and reference parameters.

[0084] By identifying and comparing reference thermal performance parameters with the actual thermal performance parameters, the thermal performance of the reflow oven process can be systematically evaluated. Significant deviations between the actual thermal performance parameters and the reference parameters indicate that the actual thermal performance of the reflow oven may be abnormal or fail to meet preset standards. This comparison mechanism transforms thermal performance analysis from a simple parameter listing into a quantitative judgment based on clear evaluation criteria, thereby accurately identifying potential problems in the process.

[0085] Optionally, when generating the reflow oven process evaluation report based on the process stability assessment results and thermal performance analysis results, module 5 can specifically perform the following: When abnormal information is found in the process stability assessment results and thermal performance analysis results, warning information and abnormal suggestion information are determined according to the type and severity of the abnormal indication information. Identify process deviation data of the reflow oven from the process stability assessment results and the thermal performance analysis results; Identify the potential causes of process deviations and provide recommendations for process adjustments; Based on the results of process stability assessment and thermal performance analysis, combined with early warning information, anomaly suggestions, process deviations, potential causes, and process adjustment suggestions, a reflow oven process evaluation report is generated.

[0086] Specifically, when the generation module 5 is executed, if abnormal prompts are detected in the process stability assessment results and thermal performance analysis results, it can automatically generate warning messages and abnormal suggestion messages based on the type and severity of the abnormality. The abnormal prompts are indications detected in the process stability assessment results or thermal performance analysis results that suggest potential problems in the reflow soldering process. These abnormal prompts may include, but are not limited to, temperature exceeding limits, abnormal heating rate, abnormal cooling rate, and peak temperature deviation. The type information can be a classification identifier for the abnormal prompts, such as "temperature abnormality," "time abnormality," or "uniformity abnormality." The severity information quantifies the degree of harm or urgency of the abnormality; for example, based on the degree of deviation in the abnormal data, the severity information can be divided into "minor," "moderate," and "severe." Warning messages are alerts issued to the user based on the type and severity information of the abnormal indications, such as "furnace temperature is too low, please be careful." Abnormal suggestion messages are preliminary handling suggestions provided for specific abnormal situations, such as "check the power supply to the heating zone."

[0087] From the process stability assessment results and thermal performance analysis results, specific data that differ from the standard or target process parameters are extracted. These process deviation data may include the degree of deviation between the actual temperature curve and the target temperature curve, the temperature fluctuation range of each temperature zone, and the temperature difference at specific time points. These data are all within acceptable ranges and are not considered abnormal data.

[0088] Based on the identified process deviation data, combined with a pre-set knowledge base, expert experience, or machine learning models, the possible causes of these deviations are analyzed, and corresponding process adjustment solutions are provided. Potential cause information may include equipment malfunctions (such as heater damage or fan abnormalities), improper parameter settings, and environmental interference. Process adjustment suggestions can be specific, such as adjusting the set temperature of a particular temperature zone, changing the conveyor belt speed, or inspecting equipment components.

[0089] Finally, based on the process stability assessment results and thermal performance analysis results, combined with early warning information, anomaly suggestions, process deviations, potential cause information, and process adjustment suggestions, a reflow oven process evaluation report is generated. This report integrates all analysis results and recommendations into a comprehensive, detailed, and instructive document, transforming abstract evaluation results into concrete and actionable guidance, enabling users to quickly locate problems and take effective improvement measures.

[0090] For example, suppose that during the reflow soldering process evaluation of a batch of products, virtual temperature sensor data is calculated using a temperature mapping model, and process stability assessment and thermal performance analysis are performed based on this data and the target product information. If the evaluation results show that in the third temperature zone of the reflow oven, the virtual temperature sensor data is consistently lower than the reference temperature information corresponding to the target product information, and the heating rate is significantly lower than the standard value (i.e., the difference between the virtual temperature sensor data and the reference temperature information is greater than the preset temperature difference threshold, and the duration is greater than the preset abnormal time, where the preset temperature difference threshold and preset abnormal time can be set according to actual needs), then an abnormal warning message of "low temperature in the third temperature zone" will be identified. At this time, according to the preset rules, the type of the abnormality is determined to be "temperature abnormality", and the severity is determined to be "moderate". Subsequently, a warning message is generated, such as "Warning: The temperature in the third temperature zone of the reflow oven is too low, which may lead to cold solder joints or poor wetting," and abnormal suggestion information is provided, such as "Suggestion: Check the working status of the heater in the third temperature zone or increase the set temperature."

[0091] Furthermore, when specific process deviation data is identified, such as the actual peak temperature of the third temperature zone being 5°C lower than the target value (within acceptable limits), or the heating time being extended by 15 seconds (within acceptable limits), comparison with a pre-set knowledge base may determine the potential cause as "aging or insufficient power of the third temperature zone heater," and provide process adjustment suggestions, such as "replacing the third temperature zone heater, or increasing the third temperature zone set temperature by 5-8°C and re-verifying the temperature." Ultimately, all this information, including process stability assessment results, thermal performance analysis results, early warning information, anomaly suggestions, process deviations, potential cause information, and process adjustment suggestions, will be integrated into a comprehensive reflow oven process evaluation report, providing production personnel with comprehensive process diagnosis and improvement guidance.

[0092] As can be seen from the above, this reflow soldering process evaluation system acquires the target product information and temperature detection data from a substitute temperature measuring device during the reflow soldering process. The temperature detection data is then input into a preset temperature mapping model for calculation, resulting in virtual temperature plate temperature data for the reflow soldering furnace. Based on the virtual temperature plate temperature data and the target product information, a process stability assessment is performed, yielding the process stability assessment result. Furthermore, based on the virtual temperature plate temperature data and the target product information, thermal performance analysis is conducted, yielding the thermal performance analysis result. Finally, based on the process stability assessment result and the thermal performance analysis result, a reflow soldering furnace process evaluation report is generated. Thus, by inputting temperature detection data into the preset temperature mapping model... The virtual temperature plate temperature data obtained through calculation is used for process stability assessment and thermal performance analysis to generate a reflow oven process evaluation report. This addresses the problems of existing reflow oven process evaluation methods that rely on physical temperature plates for temperature acquisition, such as high cost, easily compromised temperature measurement accuracy, reliance on experience, inability to monitor in real time, and lack of thermal performance analysis capabilities. By introducing alternative temperature measurement devices and virtual temperature plate technology, and performing process stability assessment and thermal performance analysis, the generated reflow oven process evaluation report can comprehensively and in real time reflect the operating conditions of the reflow oven, enabling early identification of oven abnormalities and improving the efficiency of reflow oven process evaluation.

[0093] Please refer to Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device includes a processor 301 and a memory 302. The processor 301 and the memory 302 are interconnected and communicate with each other via a communication bus 303 and / or other connection mechanisms (not shown). The memory 302 stores a computer program executable by the processor 301. When the electronic device is running, the processor 301 executes the computer program to perform the reflow soldering process evaluation method in any optional implementation of the above embodiments, to achieve the following functions: acquiring target product information and temperature detection data from an alternative temperature measuring device during the reflow soldering process; inputting the temperature detection data into a preset temperature mapping model for calculation to obtain virtual temperature plate temperature data of the reflow soldering furnace; performing process stability evaluation based on the virtual temperature plate temperature data and target product information to obtain process stability evaluation result information; performing thermal performance analysis processing based on the virtual temperature plate temperature data and target product information to obtain thermal performance analysis result information; and generating a reflow soldering furnace process evaluation report based on the process stability evaluation result information and the thermal performance analysis result information.

[0094] This application provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it performs the reflow soldering process evaluation method in any optional implementation of the above embodiments to achieve the following functions: acquiring target product information and temperature detection data from an alternative temperature measuring device during the reflow soldering process; inputting the temperature detection data into a preset temperature mapping model for calculation to obtain virtual temperature plate temperature data of the reflow soldering furnace; performing process stability evaluation based on the virtual temperature plate temperature data and target product information to obtain process stability evaluation result information; performing thermal performance analysis based on the virtual temperature plate temperature data and target product information to obtain thermal performance analysis result information; and generating a reflow soldering furnace process evaluation report based on the process stability evaluation result information and the thermal performance analysis result information. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0095] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0096] Furthermore, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0097] Furthermore, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0098] In this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying any such actual relationship or order between these entities or operations.

[0099] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for evaluating reflow soldering process, characterized in that, include: To obtain information on the target products being processed in the reflow oven and temperature detection data from alternative temperature measuring devices; The temperature detection data is input into a preset temperature mapping model for calculation to obtain the virtual temperature measuring plate temperature data of the reflow oven; Based on the temperature data of the virtual temperature measuring plate and the information of the target processed product, a process stability assessment is performed to obtain the process stability assessment result information; Based on the temperature data of the virtual temperature measuring plate and the information of the target processed product, thermal performance analysis is performed to obtain thermal performance analysis results. Based on the process stability assessment results and the thermal performance analysis results, a reflow oven process evaluation report is generated.

2. The reflow soldering process evaluation method according to claim 1, characterized in that, The preset temperature mapping model is constructed through the following steps: Acquire historical temperature data of the physical temperature measuring plate of the reflow oven and historical temperature detection data corresponding to the historical temperature measuring plate; the historical temperature detection data is historical data detected by temperature detection through the alternative temperature measuring device. The historical temperature data of the physical temperature measuring plate and the historical temperature detection data are time-aligned to obtain aligned historical temperature data. Construct an initial temperature calculation model corresponding to the aligned historical temperature data; Based on the aligned historical temperature data, the initial temperature calculation model is trained and validated to obtain the preset temperature mapping model.

3. The reflow soldering process evaluation method according to claim 1, characterized in that, Based on the temperature data from the virtual temperature measuring plate and the information of the target processed product, a process stability assessment is performed to obtain process stability assessment results, including: Determine the reference temperature information corresponding to the target processed product information; By comparing the temperature data from the virtual temperature measuring plate with the reference temperature information, the process stability assessment results are obtained.

4. The reflow soldering process evaluation method according to claim 1, characterized in that, Based on the temperature data from the virtual temperature measuring plate and the information of the target processed product, thermal performance analysis is performed to obtain thermal performance analysis results, including: Based on the target processed product information, determine the target parameter type information and the target parameter calculation method corresponding to the target parameter type information; Based on the temperature data of the virtual temperature measuring plate and the target parameter type information, the thermal performance parameters corresponding to the target parameter type information are calculated using the target parameter calculation method. Based on the aforementioned thermal performance parameters, thermal performance analysis is performed to obtain thermal performance analysis results.

5. The reflow soldering process evaluation method according to claim 4, characterized in that, Based on the target processed product information, determine the target parameter type information and the target parameter calculation method corresponding to the target parameter type information, including: Based on a preset thermal performance analysis strategy, the target parameter type information corresponding to the target processed product information is determined; Determine the initial parameter calculation method corresponding to the target parameter type information; Based on the target processed product information, the initial parameter calculation method is adjusted to obtain the target parameter calculation method.

6. The reflow soldering process evaluation method according to claim 4, characterized in that, Based on the aforementioned thermal performance parameters, thermal performance analysis is performed to obtain thermal performance analysis results, including: Determine the reference thermal performance parameter information corresponding to the aforementioned thermal performance parameters; By comparing the thermal performance parameters with the reference thermal performance parameters, the thermal performance analysis results are obtained.

7. The reflow soldering process evaluation method according to claim 1, characterized in that, Based on the process stability assessment results and the thermal performance analysis results, a reflow oven process evaluation report is generated, including: When there are abnormal prompts in the process stability assessment results and the thermal performance analysis results, warning information and abnormal suggestion information are determined according to the type and severity of the abnormal indication information. Identify process deviation data of the reflow oven from the process stability assessment results and the thermal performance analysis results; Identify the potential causes of the process deviation data and provide process adjustment recommendations; Based on the process stability assessment results and the thermal performance analysis results, combined with the early warning information, the anomaly suggestion information, the process deviation, the potential cause information, and the process adjustment suggestion information, a reflow oven process evaluation report is generated.

8. A reflow soldering process evaluation system, characterized in that, include: The acquisition module is used to acquire information about the target product being processed in the reflow oven during the process, as well as temperature detection data from the alternative temperature measuring device. The calculation module is used to input the temperature detection data into a preset temperature mapping model for calculation to obtain the virtual temperature measuring plate temperature data of the reflow oven; The evaluation module is used to perform a process stability evaluation based on the temperature data of the virtual temperature measuring plate and the target processed product information, and obtain the process stability evaluation result information. The analysis module is used to perform thermal performance analysis based on the temperature data of the virtual temperature measuring plate and the information of the target processed product, and to obtain thermal performance analysis results. The generation module is used to generate a reflow oven process evaluation report based on the process stability assessment results and the thermal performance analysis results.

9. An electronic device, characterized in that, It includes a processor and a memory, the memory storing a computer program executable by the processor, and when the processor executes the computer program, it performs the steps in the reflow soldering process evaluation method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it performs the steps in the reflow soldering process evaluation method as described in any one of claims 1-7.

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