Disclosure of Invention
In view of this, the invention provides a chip production space control method and system, which aims to solve the problem that the pad space control method in the prior art is difficult to meet the requirement of modern chip manufacturing on high precision.
In one aspect, the invention provides a chip production interval control method, which comprises the following steps:
s100, determining a pad to be monitored, and acquiring pad state data of the pad to be monitored;
S200, acquiring welding requirement data and component characteristic data, and determining a welding distance threshold according to the welding pad state data, the welding requirement data and the component characteristic data;
s300, extracting corresponding historical welding records from a historical welding record library based on the welding disc state data and the welding distance threshold value, analyzing the historical welding records, and calculating a historical deviation coefficient of the welding distance threshold value based on an analysis result;
S400, judging whether the welding interval threshold needs to be corrected according to the historical deviation coefficient, if so, setting a correction coefficient corresponding to the welding interval threshold, and obtaining a corrected welding interval threshold;
S500, collecting environmental parameters and process parameters in a welding process, analyzing the environmental parameters and the process parameters, and generating a compensation control algorithm based on analysis results, wherein the environmental parameters comprise real-time temperature data and real-time humidity data, and the process parameters comprise welding time, welding temperature and welding pressure;
And S600, performing chip bonding according to the corrected bonding interval threshold value, and controlling the welding process by using an SPC tool and based on a compensation control algorithm.
Further, the determining a solder pitch threshold according to the solder pad state data, the solder requirement data and the component characteristic data includes:
the weld pitch threshold is obtained by:
Wherein D is a soldering pitch threshold, Dp is a pad diameter, Tp is a pad thickness, Cp is a pad surface flatness factor, Tw is a soldering requirement temperature, Pw is a soldering requirement pressure, Tw is a soldering requirement time, Sc is a component size factor, Wc is a component weight factor, K is an empirical coefficient, K includes K1 and K2, K1< K2, D is a first soldering pitch threshold when k=k1, and D is a second soldering pitch threshold when k=k2.
Further, the analyzing the historical welding record, calculating the historical deviation coefficient of the welding distance threshold based on the analysis result, includes:
Determining a welding influence factor corresponding to each abnormal welding behavior, and constructing a welding influence factor sequence;
counting a first number of normal welding behaviors and a second number of abnormal welding behaviors;
Calculating a historical deviation coefficient of the welding interval threshold according to the welding influence factor sequence, the first quantity and the second quantity;
The history deviation coefficient is obtained by the following formula:
Wherein HDC is a history deviation coefficient, Fi is a welding influence factor of the welding influence factor sequence i, ai is the number of i-th abnormal welding behaviors, N is a first number, M is a second number, and λ is a weight coefficient.
Further, the determining the welding impact factor corresponding to each abnormal welding behavior includes:
extracting actual welding time corresponding to abnormal welding behaviors, acquiring preset ideal welding time, and calculating a first welding time difference value according to the actual welding time and the ideal welding time;
analyzing all normal welding behaviors, determining the welding time corresponding to each normal welding behavior, and extracting the minimum welding time;
calculating a second welding time difference value according to the actual welding time and the minimum welding time;
Calculating a welding influence factor corresponding to each abnormal welding behavior based on the first welding time difference value and the second welding time difference value;
the calculation formula of the welding influence factor is as follows:
F=α1×△T1+α2×△T2;
Where F is a welding impact factor, Δt1 is a first welding time difference, Δt2 is a second welding time difference, α1 and α2 are time difference coefficients, and α1+α2=1 is satisfied.
Further, the determining whether the welding distance threshold needs to be corrected according to the historical deviation coefficient includes:
Acquiring a preset historical deviation coefficient, and judging that the welding interval threshold value does not need to be corrected when the historical deviation coefficient is smaller than or equal to the preset historical deviation coefficient;
and when the historical deviation coefficient is larger than the preset historical deviation coefficient, judging that the welding distance threshold value needs to be corrected.
Further, the setting the correction coefficient corresponding to the welding interval threshold value and obtaining the corrected welding interval threshold value includes:
presetting a correction coefficient interval, wherein the correction coefficient interval comprises a first correction coefficient, a second correction coefficient and a third correction coefficient;
calculating a coefficient ratio of the historical deviation coefficient to the preset historical deviation coefficient;
When the coefficient ratio is greater than 1 and less than or equal to 1.2, selecting the first correction coefficient as a correction coefficient corresponding to the welding interval threshold, and taking the product value of the first correction coefficient and the welding interval threshold as a correction welding interval threshold;
When the coefficient ratio is greater than 1.2 and less than or equal to 1.4, selecting the second correction coefficient as a correction coefficient corresponding to the welding interval threshold, and taking the product value of the second correction coefficient and the welding interval threshold as a correction welding interval threshold;
When the coefficient ratio is greater than 1.4, selecting the third correction coefficient as a correction coefficient corresponding to the welding interval threshold, and taking the product value of the third correction coefficient and the welding interval threshold as a correction welding interval threshold;
the corrected welding distance threshold comprises a first corrected welding distance threshold and a second corrected welding distance threshold.
Further, the collecting environmental parameters and process parameters in the welding process, analyzing the environmental parameters and the process parameters, and generating a compensation control algorithm based on the analysis result, including:
Determining a real-time environment standard value, and calculating an environment parameter identification compensation amount according to the environment parameter and the real-time environment standard value, wherein the environment parameter identification compensation amount is obtained by the following formula:
TA＝r1×(mn-mr)+r2×(Hn-Hr);
Wherein, TA is the environmental parameter identification compensation amount, mn is the real-time environmental temperature, mr is the environmental temperature standard value, r1 is the temperature compensation coefficient, Hn is the real-time environmental humidity, Hr is the environmental humidity standard value, and r2 is the humidity compensation coefficient;
calculating a welding process parameter identification compensation amount, wherein the welding process parameter identification compensation amount is obtained by the following formula:
TB＝g1×9Tn-Tw)+g2×(Pn-Pw);
Wherein, TB is the process parameter identification compensation quantity, Tn is the welding temperature, Tw is the welding required temperature, Pn is the welding pressure, Pw is the welding required pressure, g1 is the welding temperature compensation coefficient, and g2 is the welding pressure compensation coefficient.
Further, the collecting environmental parameters and process parameters in the welding process, analyzing the environmental parameters and the process parameters, generating a compensation control algorithm based on the analysis result, and further comprising:
After correcting the environmental parameter identification compensation quantity and the welding process parameter identification compensation quantity, acquiring real-time pad spacing, comparing the real-time pad spacing with the first corrected welding spacing threshold value and the second corrected welding spacing threshold value, and compensating the real-time pad spacing according to the comparison result;
When the real-time bonding pad spacing is smaller than the first corrected bonding spacing threshold, a first compensation coefficient is selected to compensate the real-time bonding pad spacing;
when the real-time pad pitch is between the first and second modified bond pitch thresholds, not compensating;
And when the real-time bonding pad spacing is larger than the second corrected welding spacing threshold, selecting a second compensation coefficient to compensate the real-time bonding pad spacing.
Further, the performing die bonding according to the corrected bonding pitch threshold, controlling a bonding process using an SPC tool and based on a compensation control algorithm, includes:
Using a sensor to collect the environmental parameters and the process parameters in real time, and inputting data into an SPC tool for analysis;
and setting a control limit, and correcting the environment parameters and the process parameters when the key parameters exceed the control limit, wherein the control limit comprises an upper control limit threshold and a lower control limit threshold of each environment parameter and each process parameter, and the environment parameters and the process parameters are always controlled to be between the upper control limit threshold and the lower control limit threshold.
Compared with the prior art, the chip production space control method has the beneficial effects that the chip production space control method can effectively improve the welding quality in the chip production process and reduce welding defects caused by improper space. In addition, by monitoring and adjusting welding parameters in real time, the method can adapt to the changes of different environments and material conditions, and ensures the stability and reliability of the welding process. Ultimately, this will help to increase overall production efficiency, reduce production costs, and enhance market competitiveness of the product.
On the other hand, the invention also provides a chip production interval control system, which comprises the following steps:
The determining module is configured to determine a pad to be monitored and acquire pad state data of the pad to be monitored;
the interval threshold module is configured to acquire welding requirement data and component characteristic data and determine a welding interval threshold according to the welding pad state data, the welding requirement data and the component characteristic data;
A history deviation coefficient calculation module configured to extract a corresponding history welding record from a history welding record library based on the pad state data and the welding pitch threshold, analyze the history welding record, and calculate a history deviation coefficient of the welding pitch threshold based on an analysis result;
The correction module is configured to judge whether the welding interval threshold needs to be corrected according to the historical deviation coefficient, if so, setting a correction coefficient corresponding to the welding interval threshold, and obtaining a corrected welding interval threshold;
The system comprises an algorithm generation module, a compensation control module and a control module, wherein the algorithm generation module is configured to acquire and analyze environmental parameters and process parameters in a welding process, and generate a compensation control algorithm based on analysis results, wherein the environmental parameters comprise real-time temperature data and real-time humidity data, and the process parameters comprise welding time, welding temperature and welding pressure;
And a control module configured to perform die bonding in accordance with the modified bond pitch threshold, control the bonding process using the SPC tool and based on a compensation control algorithm.
It can be appreciated that the above method and system for controlling the chip production interval have the same beneficial effects, and are not described herein.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other. The invention will be described in detail below with reference to the drawings in connection with embodiments.
Referring to fig. 1, in some embodiments of the present application, a method for controlling a chip production pitch is provided, including the following steps:
S100, determining a pad to be monitored, and acquiring pad state data of the pad to be monitored;
In the present embodiment, the pad state data includes a pad diameter, a pad thickness, a pad shape, and a pad surface flatness.
S200, acquiring welding requirement data and component characteristic data, and determining a welding distance threshold according to the welding pad state data, the welding requirement data and the component characteristic data;
In the present embodiment, the soldering requirement data includes soldering requirement temperature, soldering requirement pressure, and soldering requirement time, and the component characteristic data includes component size and component weight.
In this embodiment, the pad pitch threshold includes a first modified bond pitch threshold and a second modified bond pitch threshold. The first modified bond pitch threshold is used to determine if the bond pad pitch is too small and the second modified bond pitch threshold is used to determine if the bond pad pitch is too large. By such arrangement, the pad pitch in the soldering process can be ensured to be kept within an ideal range, thereby improving soldering quality and chip production efficiency.
S300, extracting corresponding historical welding records from a historical welding record library based on the state data of the welding pads and the welding distance threshold value, analyzing the historical welding records, and calculating a historical deviation coefficient of the welding distance threshold value based on an analysis result;
in this embodiment, the history welding record library is a database in which a large amount of history welding data including, but not limited to, key parameters such as pad pitch, welding temperature, welding pressure, etc. under different welding conditions is stored in advance.
S400, judging whether the welding interval threshold is required to be corrected according to the historical deviation coefficient, if so, setting a correction coefficient corresponding to the welding interval threshold, and obtaining a corrected welding interval threshold;
S500, collecting environmental parameters and process parameters in the welding process, analyzing the environmental parameters and the process parameters, and generating a compensation control algorithm based on analysis results, wherein the environmental parameters comprise real-time temperature data and real-time humidity data, and the process parameters comprise welding time, welding temperature and welding pressure;
and S600, performing chip welding according to the corrected welding interval threshold value, and controlling the welding process by using an SPC tool and based on a compensation control algorithm.
In this embodiment SPC (Statistical Process Control) is statistical process control, which is a method for monitoring and controlling the production process to ensure that the product meets quality standards. By monitoring key parameters in real time, the SPC tool can timely find out anomalies in the process, so that measures are taken to adjust, and generation of unqualified products is avoided. In the invention, the SP C tool is combined with the compensation control algorithm, so that the welding process can be controlled more accurately, and the accuracy and consistency of the chip spacing are ensured.
It can be appreciated that the chip production space control method provided by the embodiment can effectively improve the welding quality in the chip production process and reduce the welding defects caused by improper space. In addition, by monitoring and adjusting welding parameters in real time, the method can adapt to the changes of different environments and material conditions, and ensures the stability and reliability of the welding process. Ultimately, this will help to increase overall production efficiency, reduce production costs, and enhance market competitiveness of the product.
Specifically, when determining the solder pitch threshold value based on the pad state data, the solder requirement data, and the component characteristic data, the method includes:
the weld spacing threshold is obtained by:
Wherein D is a soldering pitch threshold, Dp is a pad diameter, Tp is a pad thickness, Cp is a pad surface flatness factor, Tw is a soldering requirement temperature, Pw is a soldering requirement pressure, Tw is a soldering requirement time, Sc is a component size factor, Wc is a component weight factor, K is an empirical coefficient, K includes K1 and K2, K1< K2, D is a first soldering pitch threshold when k=k1, and D is a second soldering pitch threshold when k=k2.
It will be appreciated that the selection of the empirical coefficients K1 and K2 will depend on the particular manufacturing environment and welding process requirements.
Specifically, when analyzing the history welding record and calculating the history deviation coefficient of the welding pitch threshold based on the analysis result, the method includes:
Determining a welding influence factor corresponding to each abnormal welding behavior, and constructing a welding influence factor sequence;
counting a first number of normal welding behaviors and a second number of abnormal welding behaviors;
Calculating a historical deviation coefficient of a welding interval threshold according to the welding influence factor sequence, the first quantity and the second quantity;
The historical deviation coefficient is obtained by:
Wherein HDC is a history deviation coefficient, Fi is a welding influence factor of the welding influence factor sequence i, ai is the number of i-th abnormal welding behaviors, N is a first number, M is a second number, and λ is a weight coefficient.
It will be appreciated that the determination of the weight coefficient lambda is based on an evaluation of the impact on the stability and reliability of the welding process. In practical application, the value of λ may be adjusted according to the production environment and the specific requirements of the welding process, so as to ensure that the historical deviation coefficient HDC can accurately reflect the deviation degree of the welding pitch threshold. In this way, a more accurate correction of the welding pitch threshold can be ensured, thereby improving the welding quality.
Specifically, the determining the welding impact factor corresponding to each abnormal welding behavior includes:
extracting actual welding time corresponding to abnormal welding behaviors, acquiring preset ideal welding time, and calculating a first welding time difference value according to the actual welding time and the ideal welding time;
analyzing all normal welding behaviors, determining the welding time corresponding to each normal welding behavior, and extracting the minimum welding time;
calculating a second welding time difference value according to the actual welding time and the minimum welding time;
Calculating a welding influence factor corresponding to each abnormal welding behavior based on the first welding time difference value and the second welding time difference value;
the calculation formula of the welding influence factor is as follows:
F=α1×△T1+α2×△T2;
Where F is a welding impact factor, Δt1 is a first welding time difference, Δt2 is a second welding time difference, α1 and α2 are time difference coefficients, and α1+α2=1 is satisfied.
It will be appreciated that the selection of the time difference coefficients α1 and α2 will depend on the particular welding process and production environment. In practical application, the values of alpha 1 and alpha 2 can be dynamically adjusted according to real-time feedback in the welding process, so that the welding influence factor can be ensured to accurately reflect the influence degree of abnormal welding behaviors on welding quality. By accurately calculating the welding influence factor, the setting of the welding interval threshold value can be further optimized, so that a higher-quality welding effect is realized in the production process. In addition, by monitoring key parameters in the welding process in real time and combining a compensation control algorithm, welding defects can be effectively reduced, and the overall efficiency and the product quality of chip production are improved.
Specifically, the method for judging whether the welding distance threshold value needs to be corrected according to the historical deviation coefficient comprises the following steps:
Acquiring a preset historical deviation coefficient, and judging that the welding distance threshold value does not need to be corrected when the historical deviation coefficient is smaller than or equal to the preset historical deviation coefficient;
when the historical deviation coefficient is larger than the preset historical deviation coefficient, the welding distance threshold is judged to be needed to be corrected.
It will be appreciated that the setting of the preset historical deviation factor is based on consideration of the long-term stability of the welding process, as well as comprehensive analysis of the historical data. In actual production, the coefficient needs to be set in consideration of factors such as fluctuation of the production environment, variation of material characteristics, and performance of the welding equipment. By setting a reasonable preset history deviation coefficient, the welding interval threshold value can be adjusted neither too frequently nor to be delayed from the actual production requirement, so that the welding quality is ensured, and meanwhile, the production efficiency is improved and the cost is reduced. In addition, through real-time monitoring and analyzing key parameters in the welding process and combining a compensation control algorithm, dynamic adjustment of a welding distance threshold value can be realized, and the accuracy and reliability of chip welding are further improved.
Specifically, when setting a correction coefficient corresponding to the welding pitch threshold and obtaining the corrected welding pitch threshold, the method includes:
presetting a correction coefficient interval, wherein the correction coefficient interval comprises a first correction coefficient, a second correction coefficient and a third correction coefficient;
Calculating a coefficient ratio of the historical deviation coefficient to a preset historical deviation coefficient;
When the coefficient ratio is greater than 1 and less than or equal to 1.2, selecting the first correction coefficient as a correction coefficient corresponding to the welding interval threshold, and taking the product value of the first correction coefficient and the welding interval threshold as a correction welding interval threshold;
when the coefficient ratio is greater than 1.2 and less than or equal to 1.4, selecting the second correction coefficient as the correction coefficient corresponding to the welding interval threshold, and taking the product value of the second correction coefficient and the welding interval threshold as the correction welding interval threshold;
when the coefficient ratio is greater than 1.4, selecting a third correction coefficient as a correction coefficient corresponding to the welding interval threshold, and taking the product value of the third correction coefficient and the welding interval threshold as a correction welding interval threshold;
Wherein the corrected weld spacing threshold includes a first corrected weld spacing threshold and a second corrected weld spacing threshold.
It will be appreciated that the correction factor is selected based on a deep understanding of the impact on weld quality and the need for optimization of production efficiency. In practical application, the values of the first correction coefficient, the second correction coefficient and the third correction coefficient can be dynamically adjusted according to real-time data in the welding process, and the first correction coefficient is the second correction coefficient. The arrangement ensures that the adjustment of the welding interval threshold value can be flexibly handled according to the deviation degree in the actual welding process, so that the welding quality is not influenced by over correction, and the deviation in the welding process cannot be corrected in time due to insufficient correction. In this way, it is ensured that the correction of the welding pitch threshold value meets the actual production requirements without negatively affecting the welding quality. In addition, by monitoring key parameters in the welding process in real time and combining a compensation control algorithm, welding defects can be effectively reduced, and the overall efficiency and the product quality of chip production are improved.
Specifically, the method includes the steps of collecting environmental parameters and process parameters in a welding process, analyzing the environmental parameters and the process parameters, and generating a compensation control algorithm based on analysis results, wherein the method comprises the following steps:
Determining a real-time environment standard value, and calculating an environment parameter identification compensation amount according to the environment parameter and the real-time environment standard value, wherein the environment parameter identification compensation amount is obtained by the following formula:
TA＝r1×(mn-mr)+r2×(Hn-Hr);
Wherein, TA is the environmental parameter identification compensation amount, mn is the real-time environmental temperature, mr is the environmental temperature standard value, r1 is the temperature compensation coefficient, Hn is the real-time environmental humidity, Hr is the environmental humidity standard value, and r2 is the humidity compensation coefficient;
calculating a welding process parameter identification compensation amount, wherein the welding process parameter identification compensation amount is obtained by the following formula:
TB＝g1×(Tn-Tw)+g2×9Pn-Pw);
Wherein, TB is the process parameter identification compensation quantity, Tn is the welding temperature, Tw is the welding required temperature, Pn is the welding pressure, Pw is the welding required pressure, g1 is the welding temperature compensation coefficient, and g2 is the welding pressure compensation coefficient.
It will be appreciated that by accurately calculating the amount of compensation for the environmental and process parameters, the welding process can be effectively adjusted to accommodate environmental changes and ensure weld quality. The setting of the temperature and humidity compensation coefficients, as well as the compensation coefficients for the welding temperature and pressure, are based on a thorough understanding of the welding process and on stringent requirements for the welding quality. In actual production, these compensation coefficients need to be dynamically adjusted according to the environment and process parameters monitored in real time to ensure the stability of the welding process and consistency of the welding results. By the method, the accuracy and the reliability of chip welding can be further improved, and welding defects caused by environmental changes or improper operation are reduced, so that the overall production efficiency and the product quality are improved.
Specifically, the method includes the steps of collecting environmental parameters and process parameters in the welding process, analyzing the environmental parameters and the process parameters, and generating a compensation control algorithm based on an analysis result, wherein the method further comprises the following steps:
After the environmental parameter identification compensation quantity and the welding process parameter identification compensation quantity are corrected, acquiring real-time pad spacing, comparing the real-time pad spacing with a first corrected welding spacing threshold value and a second corrected welding spacing threshold value, and compensating the real-time pad spacing according to the comparison result;
when the real-time bonding pad spacing is smaller than a first corrected welding spacing threshold, selecting a first compensation coefficient to compensate the real-time bonding pad spacing;
when the real-time pad spacing is between the first corrected solder spacing threshold and the second corrected solder spacing threshold, not compensating;
and when the real-time pad spacing is larger than a second corrected welding spacing threshold, selecting a second compensation coefficient to compensate the real-time pad spacing.
It can be appreciated that by compensating the pitch of the pads in real time, the pitch in the soldering process can be ensured to be always kept within an ideal range, thereby avoiding soldering defects caused by too large or too small pitch. The first compensation coefficient and the second compensation coefficient are selected based on in-depth analysis of the impact on welding quality and optimization requirements on production efficiency. In practical application, the two compensation coefficients can be dynamically adjusted according to the real-time monitored pad spacing data so as to adapt to different production conditions and material characteristics. By the mode, welding defects can be effectively reduced, and the overall efficiency and the product quality of chip production are improved. In addition, through the key parameters in the real-time monitoring welding process and the combination of the compensation control algorithm, the accuracy and the reliability of the chip welding can be further improved, the welding quality is ensured, and meanwhile, the production efficiency is improved and the cost is reduced.
Specifically, performing die bonding according to the corrected bonding pitch threshold, controlling the bonding process using the SPC tool and based on the compensation control algorithm includes:
using a sensor to collect environmental parameters and process parameters in real time, and inputting data into an SPC tool for analysis;
and setting a control limit, and correcting the environmental parameters and the process parameters when the key parameters exceed the control limit, wherein the control limit comprises an upper control limit threshold and a lower control limit threshold of each environmental parameter and each process parameter, and the environmental parameters and the process parameters are always controlled to be between the upper control limit threshold and the lower control limit threshold.
It will be appreciated that the use of SPC tools enables real-time monitoring of key parameters during the welding process, ensuring weld quality stability. The control limits are set to prevent parameter fluctuations during the welding process from exceeding acceptable limits, thereby avoiding producing unacceptable welding results. The upper and lower limit thresholds are set based on in-depth study and historical data analysis of the welding process to ensure that each link of the welding process operates in an optimal state. When the parameters are detected to exceed the control limits, the system automatically adjusts the environmental parameters and the process parameters to quickly restore to the normal working state. The real-time monitoring and automatic adjusting mechanism not only improves the reliability of the welding process, but also reduces the need of manual intervention, and further improves the production efficiency and the product quality.
Referring to fig. 2, in some embodiments of the present application, a chip production pitch control system is provided, including:
The determining module is configured to determine a pad to be monitored and acquire pad state data of the pad to be monitored;
The interval threshold module is configured to acquire welding requirement data and component characteristic data and determine a welding interval threshold according to the welding pad state data, the welding requirement data and the component characteristic data;
A history deviation coefficient calculation module configured to extract a corresponding history welding record from a history welding record library based on the pad state data and the welding pitch threshold, analyze the history welding record, and calculate a history deviation coefficient of the welding pitch threshold based on an analysis result;
The correction module is configured to judge whether the welding interval threshold needs to be corrected according to the historical deviation coefficient, if so, setting a correction coefficient corresponding to the welding interval threshold, and obtaining a corrected welding interval threshold;
The system comprises an algorithm generation module, a compensation control module and a control module, wherein the algorithm generation module is configured to acquire and analyze environmental parameters and process parameters in the welding process, and generate a compensation control algorithm based on analysis results, wherein the environmental parameters comprise real-time temperature data and real-time humidity data, and the process parameters comprise welding time, welding temperature and welding pressure;
a control module configured to perform die bonding in accordance with the corrected bond pitch threshold, the use of the SPC tool and control the bonding process based on the compensation control algorithm.
It can be appreciated that the chip production space control system provided by the embodiment can effectively adapt to various production environments, and ensures the stability of the welding process and the consistency of the welding quality. Through real-time monitoring and dynamic adjustment, welding defects caused by environmental changes or improper operation can be obviously reduced, so that the overall production efficiency and the product quality are improved. In addition, the method can monitor key parameters in the welding process in real time through the use of SPC tools, and ensure the stability of welding quality. The control limits are set to prevent parameter fluctuations during the welding process from exceeding acceptable limits, thereby avoiding producing unacceptable welding results. The upper and lower limit thresholds are set based on in-depth study and historical data analysis of the welding process to ensure that each link of the welding process operates in an optimal state. When the parameters are detected to exceed the control limits, the system automatically adjusts the environmental parameters and the process parameters to quickly restore to the normal working state. The real-time monitoring and automatic adjusting mechanism not only improves the reliability of the welding process, but also reduces the need of manual intervention, and further improves the production efficiency and the product quality.
It will be appreciated by those skilled in the art that embodiments of the application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flowchart and/or block of the flowchart illustrations and/or block diagrams, and combinations of flowcharts and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the specific embodiments of the present invention without departing from the spirit and scope of the present invention, and any modifications and equivalents are intended to be included in the scope of the claims of the present invention.