CN113654686A - Reflow furnace temperature monitoring management method and system for ICT production line - Google Patents
Reflow furnace temperature monitoring management method and system for ICT production line Download PDFInfo
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Abstract
The invention provides a method and a system for monitoring and managing the temperature of a reflow furnace in an ICT production line, which comprises the following steps: the system comprises a plurality of sensors, a KIC temperature measuring instrument, a reflow furnace temperature monitoring module, a temperature prediction model, a reaction curved surface model and an assembly furnace temperature curve platform; the sensors acquire the wind speed, the temperature and the speed of the conveying belt in the reflow furnace; the temperature prediction model obtains a predicted temperature curve according to a KIC furnace temperature curve obtained by a KIC thermometer; the reaction curved surface model adjusts the temperature of a reflow furnace temperature zone according to the correlation between the input variable and the output variable and the difference between the output variable and the suggested set value; the assembly furnace temperature curve platform is used for presenting a temperature curve and pushing and early warning events exceeding set upper and lower limit values. According to the invention, through algorithm modeling prediction, the problems of inaccurate temperature monitoring and high difficulty of the reflow oven in the assembly process are solved, the production process of the reflow oven is finally controlled, the product quality is ensured, the production cost is reduced, and the production efficiency is improved.
Description
Technical Field
The invention relates to the technical field of reflow oven temperature monitoring and management, in particular to a reflow oven temperature monitoring and management method and system used in an assembly process.
Background
In the assembly of printed circuit boards using surface mount components, an optimized reflow temperature profile to obtain good quality solder joints is one of the core factors. The temperature profile is a function of temperature applied to the assembly versus time, and when plotted on a cartesian plane, represents the temperature at a particular point on the PCB during reflow as a curve on any given schedule.
The existing common furnace temperature curve setting method comprises the following steps:
1. and (5) testing the temperature of the reflow oven. Welding the temperature sensor to a corresponding test point of the PCB according to the operating specification and the requirement of the operating specification of the furnace temperature thermometer; and placing the furnace temperature thermometer and the PCB on a track of welding equipment according to the operating specification and the operating specification of the furnace temperature thermometer.
2. And importing reflow soldering temperature curve data obtained by a furnace temperature thermometer data collector into a furnace temperature thermometer, and analyzing an actual temperature curve by using analysis software. And if the actual welding temperature curve does not reach the preset result, correcting the temperature curve again, and guiding the corrected welding program to the welding equipment again.
3. And correcting the temperature curve of the reflow oven. And operating the reflow soldering equipment again, carrying out data acquisition on the corrected soldering temperature curve, and analyzing whether the temperature curve is overlapped with an ideal temperature curve.
The technical defects of the existing reflow furnace temperature monitoring management are summarized as follows:
1. the manual test has high requirements on the operation standard, the normative and the like;
2. for continuous use of a furnace temperature thermometer and consumable use of a thermocouple, the consumption of the thermometer is very large;
3. the furnace temperature curve verification has hysteresis, sampling is delayed and does not represent all process control data, and once the furnace temperature exceeds the range, all product spherical surfaces have defects before the next test;
4. the sampling inspection mode of the furnace temperature thermometer cannot be related to the data of each finished product, so that the risk of continuous bad products is caused;
therefore, the prior art has drawbacks and needs further improvement.
Disclosure of Invention
Aiming at more than one problem in the prior art, the invention provides a reflow furnace temperature monitoring and managing method and system used in the assembly process.
In order to achieve the purpose, the invention adopts the following specific scheme:
the invention provides a reflow furnace temperature monitoring and management system for an ICT production line, which comprises:
the system comprises a plurality of sensors, a KIC temperature measuring instrument, a reflow furnace temperature monitoring module, a temperature prediction model, a reaction curved surface model and an assembly furnace temperature curve platform;
the sensors are used for acquiring the wind speed, the temperature and the speed of the conveying belt in the reflow furnace;
the KIC thermodetector is used for acquiring a KIC temperature curve of the reflow oven;
the reflow furnace temperature monitoring module monitors whether the wind speed, the temperature and the conveyer belt speed acquired by the sensor exceed preset upper and lower limit values in real time;
the temperature prediction model obtains a predicted temperature curve according to a KIC furnace temperature curve obtained by a KIC thermometer;
the reaction curved surface model adjusts the temperature of a reflow furnace temperature zone according to the correlation between the input variable and the output variable and the difference between the output variable and the suggested set value;
the assembly furnace temperature curve platform is used for presenting a temperature curve and pushing and early warning events exceeding set upper and lower limit values.
Preferably, the plurality of sensors includes: a wind speed sensor, a temperature sensor and a motion speed sensor;
the wind speed sensor is used for monitoring the wind speed in the reflow furnace;
the temperature sensor is used for measuring the temperatures of different points in the reflow furnace, and adopts a thermocouple;
the movement speed sensor is used for monitoring the movement speed of a conveying belt of the reflow oven.
Preferably, the temperature prediction model is a polynomial regression model, and is obtained by taking a historical KIC temperature curve as a temperature data set and performing polynomial regression fitting.
Preferably, the input variables include: preheating zone temperature, infiltration zone temperature, melting zone temperature, cooling zone temperature, conveyor belt speed, part volume and finished product placement spacing;
the output variables include: preheating climbing slope, infiltration temperature, temperature climbing slope, peak temperature and 8 reflow furnace temperature action interval time values.
The invention also provides a temperature monitoring and management method of the reflow oven used in the ICT production line, which comprises the following steps:
step S1, determining an input variable, an output variable and upper and lower limits of the two variables;
step S2, collecting temperature data in the reflow oven through a temperature sensor;
step S3, determining the suggested set value of the output variable;
step S4, performing polynomial regression fitting to obtain a temperature prediction model;
step S5, judging the significance of the polynomial regression model;
and step S6, determining the correlation between the input variable and the output variable through the reaction surface model, and adjusting the temperature of the reflow furnace temperature zone according to the difference between the output variable and the suggested set value.
Preferably, in step S3, the suggested set value of the output variable is determined based on the correlation between the solder quality and the output variable.
Preferably, in step S4, the polynomial regression equation is as follows:
wherein the temperature value of each temperature sensor is taken as one
And (6) carrying out variable fitting to obtain a w coefficient.
Preferably, in step S5, the formula for judging the significance of the polynomial regression equation is as follows:
wherein, F is used for testing the overall significance of the multiple linear regression linear equation.
Preferably, in step S6, the reaction surface model formula is as follows:
wherein: beta represents the coefficient obtained by the fitting,
representing the input variables, y the output variables and epsilon the constant difference.
By adopting the technical scheme of the invention, the invention has the following beneficial effects:
1. the problems of inaccurate temperature monitoring, high difficulty and the like of the reflow furnace in the assembly process are solved, and the whole production process of the reflow furnace, product quality assurance, cost control and production efficiency improvement are finally achieved through algorithm modeling prediction;
2. the problems that the labor consumption is large, the consumption of a temperature measuring instrument is large, the test is inaccurate, the measurement cannot cover the whole product, the product quality cannot be guaranteed, and the production efficiency is low in the conventional reflow furnace temperature monitoring and management process are solved.
Drawings
FIG. 1 is a diagram illustrating an embodiment of the present invention;
FIG. 2 is a diagram of a reflow oven process monitoring architecture in accordance with an embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the following figures and specific examples.
The invention is explained in detail in connection with figures 1-2,
the invention provides a reflow furnace temperature monitoring and management system for an ICT production line, which comprises: the system comprises a plurality of sensors, a KIC temperature measuring instrument, a reflow furnace temperature monitoring module, a temperature prediction model, a reaction curved surface model and an assembly furnace temperature curve platform;
the sensors are used for acquiring the wind speed, the temperature and the speed of the conveying belt in the reflow furnace; the KIC thermodetector is used for acquiring a KIC temperature curve of the reflow oven; the reflow furnace temperature monitoring module monitors whether the wind speed, the temperature and the conveyer belt speed acquired by the sensor exceed preset upper and lower limit values in real time; the temperature prediction model obtains a predicted temperature curve according to a KIC furnace temperature curve obtained by a KIC thermometer; the reaction curved surface model adjusts the temperature of a reflow furnace temperature zone according to the correlation between the input variable and the output variable and the difference between the output variable and the suggested set value; the assembly furnace temperature curve platform is used for presenting a temperature curve and pushing and early warning events exceeding set upper and lower limit values.
The plurality of sensors includes: a wind speed sensor, a temperature sensor and a motion speed sensor; the wind speed sensor is used for monitoring the wind speed in the reflow furnace; the temperature sensor is used for measuring the temperatures of different points in the reflow furnace, and adopts a thermocouple; the movement speed sensor is used for monitoring the movement speed of a conveying belt of the reflow oven.
The temperature prediction model is a polynomial regression model, and is obtained by taking a historical KIC temperature curve as a temperature data set and performing polynomial regression fitting.
The input variables include: preheating zone temperature, infiltration zone temperature, melting zone temperature, cooling zone temperature, conveyor belt speed, part volume and finished product placement spacing;
the output variables include: preheating climbing slope, infiltration temperature, temperature climbing slope, peak temperature and 8 reflow furnace temperature action interval time values.
The temperature monitoring and managing method of the reflow furnace comprises the following steps:
1. in the first stage, a temperature curve (no-load time) of the surface of the solder ball of the product in each temperature zone is simulated through a temperature prediction model;
2. in the second stage, based on KIC temperature curves of the inner side and the outer side of the conveyor belt position when a large amount of data is fully loaded, the relevance between the soldering tin quality of the product at different positions and the temperature curves (when the conveyor belt is fully loaded) is searched;
3, the furnace temperature curve data measured by the KIC thermodetector is real, effective and complete in period;
4. the wind speed is fixed in the experiment, and the speed of the conveying belt is unchanged.
A reaction curved surface model method for constructing a temperature curve by using a reaction curved surface is used to construct a standard furnace temperature curve by matching with a nonlinear programming solution.
The first step is as follows: determining input variables, mainly comprising: the temperature of four areas (DEG C/Sec.) such as preheating, infiltration, melting, cooling and the like is set, the speed (m/min) of a conveying belt, the air return rate (m 3/min), the volume (cm3) of parts and the placing distance (cm) of finished products are eight controllable factors, and the upper limit and the lower limit of the controllable factors are also set.
The second step is that: determining an output variable, comprising: the method comprises the following steps of preheating rising slope (DEG C/Sec.), infiltration temperature (DEG C), temperature rising slope (DEG C/Sec.), peak temperature (DEG C), and 8 reflow furnace temperature action interval time values (T1-T8, Sec.), wherein the total number of the reflow temperature curve dependent variables is 12.
The third step: temperature data of all parts of the reflow oven in the production process are obtained through the thermocouples, temperature change in the formed reflow oven is judged under corresponding output variables, and reflow process effects of the reflow oven are judged, wherein an exemplary effect diagram is shown in figure 1.
The fourth step: determining a recommended set value of a reflow output variable:
by debugging the temperature of the reflow oven, the preheating climbing slope, the infiltration temperature, the temperature climbing slope, the peak temperature and other output variable suggested set values in a period of time are calculated based on the optimal soldering quality feedback in the period of time.
The fifth step: polynomial regression solution fitting historical temperature curve
The polynomial regression solving method and process are as follows:
and obtaining a temperature prediction model through polynomial regression fitting according to the plurality of historical KIC temperature curves serving as temperature data sets.
The polynomial regression model specifically means:
the data of historical KIC temperature curves are acquired as thermocouples at a plurality of different positions, and the temperature value of each thermocouple is taken as one
And (5) carrying out variable fitting to obtain a w coefficient, so as to obtain a polynomial regression equation. And subsequently calculating a real-time predicted temperature curve according to a polynomial regression equation.
And a sixth step: performing multiple regression analysis on the polynomial regression model to obtain the F value (significance) of the regression model, calculating the interpretation capability of the polynomial regression model, and obtaining the establishment of the normality hypothesis of each model through residual analysis;
the original assumption is that Ho: β 0= β 1= β 2=. = 0; let us assume H1 that β 0 ≠ β 1 ≠ β 2 ≠ 0
By a given level of significance
Looking up the table to obtain the critical value F
(ii) a Calculating F statistic value according to the sample and passing F>F
The polynomial regression equation obtained has significance, and is as follows:
by F-testing the significance of the multiple linear regression linear equation as a whole, (it can be understood that the assumption of "linear model" is used to explain whether the variation of the explained variable is significant, that is to say when the testing of the equation is not significant, a non-linear model is considered)
The seventh step: the reactive surface method RSM is mainly used for finding out the relation between a controllable factor (input) and a reactive variable (output), and establishing a proper surface equation and an optimized reaction value.
Optimizing the reaction value: fitting the real-time temperature data through the fitted reaction surface model to obtain a predicted temperature curve, calculating the difference between the output variable and the suggested set value through the curve, and adjusting the temperature of the reflow furnace temperature zone
Reaction surface model:
wherein, beta represents the coefficient obtained by fitting,
representing the input variables, y the output variables and epsilon the constant difference.
The 8 thermocouple temperature detecting tubes are respectively arranged in eight temperature areas (respectively corresponding to T1-T8) of the reflow oven, the 8 thermocouple collecting modules convert information into temperature data, the temperature data are transmitted to an industrial gateway through an Ethernet, and finally the temperature data are wirelessly accessed to an industrial mobile network through a DTU (data transfer unit) to realize data up-casting. Reading a large amount of data through a temperature prediction model, training and simulating a periodic solder ball surface furnace temperature curve of a product passing through a reflow furnace, presenting the temperature curve on a furnace temperature curve platform, monitoring the wind speed and the speed of a conveying belt, monitoring and maintaining the optimal soldering tin effect in real time, and carrying out pushing alarm on abnormal furnace temperature.
The reflow furnace temperature detection data architecture comprises: temperature, wind speed, conveyor belt speed, KIC furnace temperature curve, see Table 1 for details;
table 1: temperature detection data framework of reflow furnace
The key index management and control data are detailed in table 2.
The 5 key indexes are as follows: rising slope, falling slope, constant temperature time, reflux time, peak temperature.
Table 2: key index management and control data
The invention has the following main technical effects:
1) based on the requirement of the assembly process on an optimized furnace temperature curve, the invention designs a method for obtaining the optimized reflux temperature curve;
2) aiming at the high-quality requirement of assembled products, a method capable of monitoring and maintaining the optimal soldering tin effect in real time is provided.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the contents of the present specification and the accompanying drawings, or directly/indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (9)
1. The utility model provides a reflow oven temperature monitoring management system for in ICT production line which characterized in that includes:
the system comprises a plurality of sensors, a KIC temperature measuring instrument, a reflow furnace temperature monitoring module, a temperature prediction model, a reaction curved surface model and an assembly furnace temperature curve platform;
the sensors are used for acquiring the wind speed, the temperature and the speed of the conveying belt in the reflow furnace;
the KIC thermodetector is used for acquiring a KIC temperature curve of the reflow oven;
the reflow furnace temperature monitoring module monitors whether the wind speed, the temperature and the conveyer belt speed acquired by the sensor exceed preset upper and lower limit values in real time;
the temperature prediction model obtains a predicted temperature curve according to a KIC furnace temperature curve obtained by a KIC thermometer;
the reaction curved surface model adjusts the temperature of a reflow furnace temperature zone according to the correlation between the input variable and the output variable and the difference between the output variable and the suggested set value;
the assembly furnace temperature curve platform is used for presenting a temperature curve and pushing and early warning events exceeding set upper and lower limit values.
2. The reflow oven temperature monitoring and management system for ICT production line according to claim 1,
the plurality of sensors includes: a wind speed sensor, a temperature sensor and a motion speed sensor;
the wind speed sensor is used for monitoring the wind speed in the reflow furnace;
the temperature sensor is used for measuring the temperatures of different points in the reflow furnace, and adopts a thermocouple;
the movement speed sensor is used for monitoring the movement speed of a conveying belt of the reflow oven.
3. The reflow oven temperature monitoring and management system for ICT production line according to claim 1,
the temperature prediction model is a polynomial regression model, and is obtained by taking a historical KIC temperature curve as a temperature data set and performing polynomial regression fitting.
4. The reflow oven temperature monitoring and management system for ICT production line according to claim 1,
the input variables include: preheating zone temperature, infiltration zone temperature, melting zone temperature, cooling zone temperature, conveyor belt speed, part volume and finished product placement spacing;
the output variables include: preheating climbing slope, infiltration temperature, temperature climbing slope, peak temperature and 8 reflow furnace temperature action interval time values.
5. A temperature monitoring and management method for a reflow furnace in an ICT production line is characterized by comprising the following steps:
step S1, determining an input variable, an output variable and upper and lower limits of the two variables;
step S2, collecting temperature data in the reflow oven through a temperature sensor;
step S3, determining the suggested set value of the output variable;
step S4, performing polynomial regression fitting to obtain a temperature prediction model;
step S5, judging the significance of the polynomial regression model;
and step S6, determining the correlation between the input variable and the output variable through the reaction surface model, and adjusting the temperature of the reflow furnace temperature zone according to the difference between the output variable and the suggested set value.
6. The temperature monitoring and management method for the reflow oven in the ICT production line according to claim 5, characterized in that,
in step S3, specifically, the suggested set value of the output variable is determined based on the correlation between the solder quality and the output variable.
7. The temperature monitoring and management method for the reflow oven in the ICT production line according to claim 5, characterized in that,
in step S4, the polynomial regression equation is as follows:
wherein the temperature value of each temperature sensor is taken as one
And (6) carrying out variable fitting to obtain a w coefficient.
8. The temperature monitoring and management method for the reflow oven in the ICT production line as set forth in claim 5,
in step S5, the formula for determining the significance of the polynomial regression equation is as follows:
wherein, F is used for testing the overall significance of the multiple linear regression linear equation.
9. The temperature monitoring and management method for the reflow oven in the ICT production line as set forth in claim 5,
in step S6, the reaction surface model formula is as follows:
wherein: beta represents the coefficient obtained by the fitting,
representing the input variables, y the output variables and epsilon the constant difference.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114700575A (en) * | 2022-04-19 | 2022-07-05 | 江西兆驰半导体有限公司 | Method for optimizing reflux curve of back-brushed tin product |
| CN117548782A (en) * | 2024-01-12 | 2024-02-13 | 山东理工职业学院 | Welding temperature monitoring method and system for welding equipment |
| CN118050579A (en) * | 2024-02-19 | 2024-05-17 | 江苏华鹏变压器有限公司 | Intelligent analysis control method based on data analysis |
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| CN114700575A (en) * | 2022-04-19 | 2022-07-05 | 江西兆驰半导体有限公司 | Method for optimizing reflux curve of back-brushed tin product |
| CN114700575B (en) * | 2022-04-19 | 2024-01-19 | 江西兆驰半导体有限公司 | Reflow curve optimization method for back tin brushing product |
| CN117548782A (en) * | 2024-01-12 | 2024-02-13 | 山东理工职业学院 | Welding temperature monitoring method and system for welding equipment |
| CN118050579A (en) * | 2024-02-19 | 2024-05-17 | 江苏华鹏变压器有限公司 | Intelligent analysis control method based on data analysis |
| CN118050579B (en) * | 2024-02-19 | 2024-07-23 | 江苏华鹏变压器有限公司 | Intelligent analysis control method based on data analysis |
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