Flexible manufacturing electronic production line dynamic scheduling system and method

Abstract

The invention discloses a flexible manufacturing electronic production line dynamic scheduling system and method, and relates to the technical field of intelligent manufacturing, and the system collects the operation state data of a production line in real time through sensor groups installed at all stations of the production line, and obtains a load fluctuation data set and an equipment operation data set after data processing; carrying out load state evaluation by calculating a dynamic load disturbance index Lfz, evaluating the load state of the production line, executing process adaptability analysis when the production line is evaluated to be in a standard operation load, calculating a production process adaptability index Bsc, and analyzing the influence of the load on the production process; comprehensive process evaluation is carried out through the comprehensive scheduling response index Sdd, and whether the process is qualified or not is evaluated; and intelligent scheduling and optimization are carried out on the production process according to scheduling instructions generated by two times of evaluation. The system can dynamically respond to the change of the production line, improve the production efficiency and flexibility, reduce resource waste and ensure the process quality.

Description

Technical Field

[0001] This invention relates to the field of intelligent manufacturing technology, specifically to a dynamic scheduling system and method for flexible manufacturing electronic production lines. Background Technology

[0002] Flexible manufacturing systems, as the core of modern manufacturing, aim to improve the adaptability and responsiveness of production processes to cope with complex production environments and ever-changing market demands. In this system, the realization of dynamic scheduling of electronic production lines becomes crucial, especially when facing a wide variety of products and constantly changing production cycles. The dynamic scheduling system for electronic production lines dynamically adjusts production strategies and process parameters by collecting and analyzing production line operating data in real time, thereby achieving optimized scheduling and improving the overall efficiency and flexibility of the production line. Specifically, the load status of the production line is closely related to the process status; load fluctuations directly affect the operational stability and production efficiency of the equipment, while the adaptability of the production process affects product quality and the operational stability of the production line. Therefore, a comprehensive assessment of the production line load and process status can help achieve precise scheduling and optimization decisions.

[0003] While existing manufacturing systems can monitor and analyze production line load and process status to some extent, most suffer from poor real-time performance and insufficient data analysis when dealing with complex production processes, especially under dynamic load fluctuations and process changes, making timely and effective responses difficult. Traditional production line scheduling methods are typically based on static models and human experience, which are ill-suited to the complexity and variability of the production environment. Particularly when load fluctuations exceed predetermined ranges, scheduling strategies may not adapt quickly enough, leading to decreased production line efficiency. Furthermore, most existing process adaptability assessment methods do not consider the synergistic effects between equipment or the interactive impact of load fluctuations on the process flow. This often results in delays in production line adjustments and process optimization, making it difficult to reflect the actual impact of load fluctuations on the production process in real time. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a dynamic scheduling system and method for flexible manufacturing electronic production lines, solving the problems mentioned in the background section.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a dynamic scheduling system for flexible manufacturing electronic production lines, comprising a data monitoring module, a load analysis module, a process adaptability module, a comprehensive analysis module, and a scheduling optimization module;

[0006] The data monitoring module is used to install sensor groups on the electronic production line to collect the production line's operating status data in real time, and transmit it to the electronic production line dynamic scheduling system for data processing to obtain load fluctuation data groups and equipment operation data groups.

[0007] The load analysis module is used to perform load analysis on the electronic production line based on the load fluctuation data set, generate a load status assessment, and generate process adaptability analysis and assessment information based on the assessment results.

[0008] The process adaptability module is used to perform process adaptability analysis on electronic production lines operating at standard loads based on equipment operation data sets.

[0009] The comprehensive analysis module is used to fit the analysis results of electronic production line load analysis and process adaptability analysis, comprehensively analyze the impact of load adjustment on the electronic production line production process, generate a comprehensive process assessment, and then generate assessment information based on the assessment results.

[0010] The scheduling optimization module is used to receive scheduling instructions generated by load status assessment and comprehensive process assessment in real time, and execute corresponding optimized scheduling operations.

[0011] Preferably, the data monitoring module includes a data acquisition unit and a data processing unit;

[0012] The data acquisition unit is used to collect real-time operating status data of the production line based on the sensor groups installed at various locations on the electronic production line;

[0013] The sensor group includes a power analyzer, a load sensor, a vibration frequency sensor, a laser displacement sensor, an encoder, and a pressure sensor;

[0014] The power analyzer is used to connect to the power input terminal of the production line drive system to monitor the operating power of the production line in real time.

[0015] The load sensor is installed below each workstation on the production line to collect the real-time load fz of each workstation.

[0016] The vibration frequency sensor is used to be installed on the support frame of the production line equipment to directly collect the equipment vibration frequency fvi.

[0017] The laser displacement sensor is installed above the path the PCB board travels to monitor the warpage height h of the PCB board in real time. pc ;

[0018] The encoder is mounted on the drive shaft of the material rack to monitor the material changing speed V of the material rack in real time. fe ;

[0019] The pressure sensor is installed on the inlet pipe of the reflux furnace near the furnace inlet to monitor the reflux furnace inlet pressure P in real time. sm .

[0020] Preferably, the data processing unit is used to establish a communication connection between the sensor group and the electronic production line dynamic scheduling system through a wireless network, and transmit the operating status data to the electronic production line dynamic scheduling system in real time for data processing to obtain load fluctuation data group and equipment operation data group;

[0021] The data processing is used to preprocess the operating status data before performing data analysis;

[0022] The preprocessing includes timestamp alignment, noise reduction, missing value imputation, and dimensionless processing.

[0023] The timestamp alignment uses linear interpolation resampling technology to interpolate and predict missing time points in the running status data; the denoising uses wavelet denoising technology to preserve the transient structural features of the running status data and remove high-frequency noise; the missing value filling uses missing value interpolation technology to complete the running status data due to sampling interruption and communication packet loss; and the dimensionless processing uses the Max-Min method to remove the dimensional influence of the running status data.

[0024] The data analysis includes load fluctuation analysis and load imbalance analysis;

[0025] The load fluctuation analysis is used to perform time-domain analysis on the obtained operating power based on the electronic production line dynamic scheduling system, and to calculate the difference between the maximum fluctuation amplitude and the minimum fluctuation amplitude to obtain the load fluctuation amplitude ∆La.

[0026] The load imbalance analysis is used to calculate the average load μ of each workstation based on the acquired real-time load fz through the electronic production line dynamic scheduling system. fz Then, the load unbalance degree Li is calculated using the mean absolute deviation method. The specific formula is as follows: In the formula, n represents the total number of workstations, and fz i This represents the load at the i-th workstation;

[0027] The load fluctuation data set includes the load fluctuation amplitude ∆La, the load imbalance degree Li, and the equipment vibration frequency fvi;

[0028] The equipment operation data set includes the PCB board warpage height h. pc Material changing speed V fe and reflux furnace inlet pressure P sm .

[0029] Preferably, the load analysis module includes a load analysis unit and a load status assessment unit;

[0030] The load analysis unit is used to perform correlation calculations based on the load fluctuation data set to analyze the load status of the production line, thereby forming a dynamic load disturbance index Lfz, which reflects the stability of the production line's mechanical equipment. The specific formula is as follows: In the formula, log represents the logarithmic function.

[0031] Preferably, the load status assessment unit is used to calculate the mean and standard deviation of the dynamic load disturbance index Lfz over the past 30 days according to statistical methods, and set the difference between the mean and the standard deviation as the load standard threshold φf, and the sum of the mean and the standard deviation as the load warning threshold φz, and then perform load status assessment with the real-time acquired dynamic load disturbance index Lfz. The specific assessment scheme is as follows.

[0032] When the dynamic load disturbance index Lfz < the load standard threshold φf, it indicates that the production line has excess load, and the first scheduling instruction is generated at this time.

[0033] If the load standard threshold φf ≤ dynamic load disturbance index Lfz ≤ load warning threshold φz, it means that the production line is under standard operating load, and process adaptability analysis is performed at this time.

[0034] When the dynamic load disturbance index Lfz > the load warning threshold φz, it indicates that the production line is operating under overload, and a second scheduling instruction is generated at this time.

[0035] Preferably, the process adaptability module is used to perform process adaptability analysis when the load condition assessment indicates that the production line is at a standard operating load;

[0036] The process adaptability analysis command is used to perform correlation calculations based on equipment operation data sets to analyze the impact of the operating load on the production process in the electronic production line, in order to form a production process adaptability index Bsc, which is used to determine the adaptability of the production process under the current standard operating load condition. The specific formula is as follows: In the formula, cos represents the cosine function.

[0037] Preferably, the comprehensive analysis module includes a comprehensive load analysis unit and an adaptability evaluation unit;

[0038] The comprehensive load analysis unit is used to perform correlation calculations based on the dynamic load disturbance index Lfz and the production process adaptability index Bsc to generate a comprehensive scheduling response index Sdd, which comprehensively reflects the load status and process adaptability of the production line. The specific formula is as follows: .

[0039] Preferably, the adaptability assessment unit is used to extract the comprehensive scheduling response index Sdd when all processes are qualified within the past 30 days, calculate the mean using a statistical method, preset the mean as the process adaptability threshold φd, and then perform a comprehensive process assessment with the real-time acquired comprehensive scheduling response index Sdd. The specific assessment scheme is as follows:

[0040] When the comprehensive scheduling response index Sdd ≤ process adaptability threshold φd, it indicates that the process is qualified. At this time, the current production line maintains the production standard and continues to monitor.

[0041] When the comprehensive scheduling response index Sdd > the process adaptability threshold φd, it indicates that the process is unqualified and the load scheduling has an impact on the process. At this time, a third scheduling instruction is generated.

[0042] Preferably, the scheduling optimization module is used to receive scheduling instructions generated by the load status assessment and comprehensive process assessment in real time according to the electronic production line dynamic scheduling system, and execute corresponding optimized scheduling operations, as follows;

[0043] Generate the first scheduling instruction: increase the production line's production pace by 10%, increase equipment uptime by 10%, and perform iterative evaluation through the load analysis module;

[0044] Generate a second scheduling instruction: reduce production batches by 30%, reduce runtime by 10%, and perform iterative evaluation through the load analysis module;

[0045] A third scheduling instruction is generated: it is transmitted to the electronic production line dynamic scheduling system to extend the material change cycle by 15% and reduce the production speed by 15%, and then iteratively evaluated through the load analysis module.

[0046] A dynamic scheduling method for flexible manufacturing electronic production lines includes the following steps:

[0047] S1. Install sensor groups on the electronic production line to collect real-time operating status data of the production line, and transmit the data to the electronic production line dynamic scheduling system for data processing to obtain load fluctuation data groups and equipment operation data groups.

[0048] S2. Perform load analysis on the electronic production line based on the load fluctuation data set, generate a load status assessment, and generate process adaptability analysis and assessment information based on the assessment results.

[0049] S3. Based on the equipment operation data set, conduct process adaptability analysis on the electronic production line under standard operating load;

[0050] S4. Fit the analysis results of the electronic production line load analysis and process adaptability analysis, comprehensively analyze the impact of load adjustment on the electronic production line production process, generate a comprehensive process assessment, and then generate assessment information based on the assessment results.

[0051] S5 receives scheduling instructions generated from load status assessment and comprehensive process assessment in real time, and executes corresponding optimized scheduling operations.

[0052] This invention provides a dynamic scheduling system and method for flexible manufacturing electronic production lines. It offers the following advantages:

[0053] (1) The system's data monitoring module collects various operating status data of the production line in real time through sensor groups installed at key locations on the production line, including power analyzers, load sensors, vibration frequency sensors, laser displacement sensors, encoders, and pressure sensors. The data is then transmitted to the data processing unit for preprocessing, including timestamp alignment, noise reduction, missing value imputation, and dimensionless processing. After analysis, the preprocessed data can yield key information such as load fluctuation amplitude and load imbalance, which directly affect the stability of the production line. This efficient data acquisition and processing mechanism ensures that the system can reflect the operating status of the production line in real time, providing an accurate data foundation for subsequent load status assessment and process adaptability analysis, thereby optimizing the overall stability and reliability of the production line.

[0054] (2) The combined application of the load analysis module and the process adaptability module further enhances the system's ability to handle complex production environments. The load analysis module calculates the dynamic load disturbance index Lfz based on the load fluctuation data set. The system can analyze the load status of the production line in real time and evaluate the load status against the load standard threshold φf and the load warning threshold φz. When the evaluation indicates that the production line is under standard operating load, process adaptability analysis is performed. The process adaptability module calculates the production process adaptability index Bsc based on the equipment operation data set and further analyzes the adaptability of load changes to the production process. This combination enables timely adaptation between load changes and process adjustments during production, thereby ensuring the stability of the production process and avoiding production stagnation or quality fluctuations caused by uneven load or equipment malfunctions. At the same time, it improves the adaptability of the production process to load changes and ensures that the process can operate efficiently under varying load conditions.

[0055] (3) The system's comprehensive analysis module calculates the dynamic load disturbance index Lfz and the production process adaptability index Bsc by correlation, resulting in a comprehensive scheduling response index Sdd. This comprehensively reflects the load status and process adaptability of the production line and performs a comprehensive process evaluation with the process adaptability threshold φd. When the comprehensive scheduling response index Sdd exceeds the process adaptability threshold φd, it indicates that the production line process may be affected by load fluctuations, and the system will generate scheduling optimization instructions. The scheduling optimization module receives scheduling instructions generated by the load status evaluation and comprehensive process evaluation in real time. These instructions include adjusting production batches, changing equipment operating rhythms, and extending material changeover cycles. Through these precise scheduling optimizations, the system can reduce waste and downtime in production, and improve the flexibility and production efficiency of the production line. At the same time, the implementation of optimized scheduling strategies can continuously improve the production capacity of the production line under different load conditions, ensure that the production switching of different products is not affected by production line fluctuations, improve the overall production adaptability, and reduce potential risks caused by changes in the environment and equipment status. Attached Figure Description

[0056] Figure 1 This is a schematic diagram of the dynamic scheduling system for a flexible manufacturing electronic production line according to the present invention.

[0057] Figure 2 This is a schematic diagram illustrating the steps of a flexible manufacturing electronic production line dynamic scheduling method according to the present invention.

[0058] Figure 3 This is a schematic diagram illustrating the operating principle of a flexible manufacturing electronic production line dynamic scheduling system according to the present invention.

[0059] Figure 4 This is a line graph diagram illustrating the comprehensive process evaluation of the present invention. Detailed Implementation

[0060] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0061] Example 1

[0062] Please see Figure 1 and Figure 3 This invention provides a dynamic scheduling system for flexible manufacturing electronic production lines. To achieve the above objectives, this invention is implemented through the following technical solutions: including a data monitoring module, a load analysis module, a process adaptability module, a comprehensive analysis module, and a scheduling optimization module;

[0063] The data monitoring module is used to install sensor groups on the electronic production line to collect the production line's operating status data in real time, and transmit it to the electronic production line dynamic scheduling system for data processing to obtain load fluctuation data groups and equipment operation data groups.

[0064] The load analysis module is used to perform load analysis on the electronic production line based on the load fluctuation data set, generate a load status assessment, and generate process adaptability analysis and assessment information based on the assessment results.

[0065] The process adaptability module is used to perform process adaptability analysis on electronic production lines operating at standard loads based on equipment operation data sets.

[0066] The comprehensive analysis module is used to fit the analysis results of electronic production line load analysis and process adaptability analysis, comprehensively analyze the impact of load adjustment on the electronic production line production process, generate a comprehensive process assessment, and then generate assessment information based on the assessment results.

[0067] The scheduling optimization module is used to receive scheduling instructions generated by load status assessment and comprehensive process assessment in real time, and execute corresponding optimized scheduling operations.

[0068] In this embodiment, the data monitoring module collects real-time operating status data of the electronic production line through a high-precision sensor array, ensuring that the system can accurately capture load fluctuations and minute changes in equipment operation. After being transmitted to the data processing unit, this data undergoes preprocessing operations including timestamp alignment, noise reduction, missing value imputation, and dimensionless processing to ensure data accuracy and integrity. This provides reliable load fluctuation data sets and equipment operation data sets for subsequent load analysis and process adaptability assessment. Through real-time and high-precision data acquisition, this invention can promptly capture load fluctuations and equipment anomalies during production, minimizing problems caused by data delays or inaccuracies and providing more accurate information support for subsequent decision-making. The load analysis module calculates the dynamic load disturbance index Lfz using the load fluctuation data set, and performs load status assessment by combining the load standard threshold φf and the load warning threshold φz. When the assessment indicates that the production line is at a standard operating load, process adaptability analysis is performed. Compared with traditional production scheduling systems, the load analysis module can perceive load fluctuations in real time and take targeted measures, thus avoiding the shortcomings of slow response and untimely adjustment in traditional scheduling systems. Meanwhile, the process adaptability module performs process adaptability analysis. It calculates the production process adaptability index Bsc using equipment operation data sets to analyze the impact of operating load on the production process. This ensures that the production process can operate efficiently and stably under load fluctuations, avoiding process incompatibility issues caused by uneven loads, thereby effectively improving production flexibility, process stability, and product qualification rate. The comprehensive analysis module correlates the dynamic load disturbance index Lfz and the production process adaptability index Bsc to derive the comprehensive scheduling response index Sdd, used to comprehensively evaluate the production line's load status and process adaptability. By comparing this comprehensive scheduling response index Sdd with the process adaptability threshold φd, it can accurately determine whether the production line needs adjustment under the current load and process conditions. The scheduling optimization module generates optimized scheduling instructions based on real-time load status assessment and comprehensive process assessment results, and executes optimized scheduling operations. These instructions include scheduling strategies such as increasing production pace, reducing production batches, and extending material changeover cycles, enabling the production line to flexibly adjust under constantly changing process demands and load conditions. Compared with traditional static scheduling systems, the dynamic scheduling mechanism of this invention can automatically optimize and adjust according to the real-time changes in load status and process requirements during production, which significantly improves production efficiency, reduces production downtime, reduces equipment failure rate, and enhances the utilization rate of production resources and the adaptability of production lines.

[0069] Example 2

[0070] Please refer to Figure 1 Specifically: the data monitoring module includes a data acquisition unit and a data processing unit;

[0071] The data acquisition unit is used to collect real-time operating status data of the production line based on the sensor groups installed at various locations on the electronic production line;

[0072] The sensor group includes a power analyzer, a load sensor, a vibration frequency sensor, a laser displacement sensor, an encoder, and a pressure sensor;

[0073] The power analyzer is used to connect to the power input terminal of the production line drive system to monitor the operating power of the production line in real time.

[0074] The load sensor is installed below each workstation on the production line to collect the real-time load fz of each workstation.

[0075] The vibration frequency sensor is installed on the support frame of the production line equipment to directly collect the equipment vibration frequency fvi, reflecting the vibration of the equipment during high-speed operation.

[0076] The laser displacement sensor is installed above the path the PCB board travels to monitor the warpage height h of the PCB board in real time. pc This indicates the warpage height of the PCB board when it is heated unevenly during the reflow oven process.

[0077] The encoder is mounted on the drive shaft of the material rack to monitor the material changing speed V of the material rack in real time. fe This indicates the material changing efficiency of the material rack. Processes with fast material changing speeds can quickly switch between different products, avoid production delays, and improve production flexibility.

[0078] The pressure sensor is installed on the inlet pipe of the reflux furnace near the furnace inlet to monitor the reflux furnace inlet pressure P in real time. sm This indicates the inlet pressure of the reflow oven. Both excessively high and low pressures can lead to uneven heating, which in turn affects the welding quality.

[0079] The data processing unit is used to establish a communication connection between the sensor group and the electronic production line dynamic scheduling system through a wireless network, and to transmit the operating status data to the electronic production line dynamic scheduling system in real time for data processing, and to obtain load fluctuation data group and equipment operation data group.

[0080] The data processing is used to preprocess the operating status data before performing data analysis;

[0081] The preprocessing includes timestamp alignment, noise reduction, missing value imputation, and dimensionless processing.

[0082] The timestamp alignment uses linear interpolation resampling technology to interpolate and predict missing time points in the running status data; the denoising uses wavelet denoising technology to preserve the transient structural features of the running status data and remove high-frequency noise; the missing value filling uses missing value interpolation technology to complete the running status data due to sampling interruption and communication packet loss; and the dimensionless processing uses the Max-Min method to remove the dimensional influence of the running status data.

[0083] The data analysis includes load fluctuation analysis and load imbalance analysis;

[0084] The load fluctuation analysis is used to perform time-domain analysis on the obtained operating power based on the electronic production line dynamic scheduling system, and calculate the difference between the maximum fluctuation amplitude and the minimum fluctuation amplitude to obtain the load fluctuation amplitude ∆La, which reflects the upper and lower fluctuation amplitude of the equipment load and directly affects the stability of the production line.

[0085] The load imbalance analysis is used to calculate the average load μ of each workstation based on the acquired real-time load fz through the electronic production line dynamic scheduling system. fz Then, the load imbalance degree Li is calculated using the mean absolute deviation method, reflecting the difference in load between each workstation. Load imbalance will cause fluctuations in the overall production line. The specific formula is as follows: In the formula, n represents the total number of workstations, and fz i This represents the load at the i-th workstation;

[0086] The load fluctuation data set includes the load fluctuation amplitude ∆La, the load imbalance degree Li, and the equipment vibration frequency fvi;

[0087] The equipment operation data set includes the PCB board warpage height h. pc Material changing speed V fe and reflux furnace inlet pressure P sm .

[0088] In this embodiment, the data acquisition unit utilizes the collaborative operation of multiple sensors, including a power analyzer, load sensor, vibration frequency sensor, laser displacement sensor, encoder, and pressure sensor, to monitor key production line indicators in real time, such as load fluctuations, equipment vibration, reflow oven inlet pressure, PCB board warpage, and material rack changing speed. The data processing unit transmits the collected operating status data to the electronic production line dynamic scheduling system via a wireless network, performing timestamp alignment, noise reduction, missing value imputation, and dimensionless processing to ensure data accuracy and reliability. After processing, the data undergoes load fluctuation analysis and load imbalance analysis to obtain load fluctuation data sets and equipment operation data sets. This helps to assess the stability of the production line and the load status of each workstation in real time, providing accurate decision-making basis for the scheduling system. This system effectively avoids production interruptions caused by load fluctuations and equipment imbalance, improving the flexibility, stability, and efficiency of the production process. It further enhances the production line's adaptive scheduling capability, reduces equipment failure rate, and improves production reliability and response speed, thereby significantly optimizing the production process and improving overall production efficiency.

[0089] Example 3

[0090] Please refer to Figure 1 Specifically: the load analysis module includes a load analysis unit and a load status assessment unit;

[0091] The load analysis unit is used to perform correlation calculations based on the load fluctuation data set to analyze the load status of the production line, thereby forming a dynamic load disturbance index Lfz, which reflects the stability of the production line's mechanical equipment. The specific formula is as follows: In the formula, log represents the logarithmic function, and log(Li+1) is the logarithmic transformation of the load imbalance, representing the impact of load differences between workstations or equipment. This is the square root of the equipment vibration frequency, representing the impact of equipment vibration on load fluctuations.

[0092] The load status assessment unit is used to calculate the mean and standard deviation of the dynamic load disturbance index Lfz over the past 30 days based on statistical methods, and sets the difference between the mean and standard deviation as the load standard threshold φf, and the sum of the mean and standard deviation as the load warning threshold φz. Then, it performs load status assessment with the real-time acquired dynamic load disturbance index Lfz. The specific assessment scheme is as follows.

[0093] When the dynamic load disturbance index Lfz < the load standard threshold φf, it indicates that the production line has excess load, and the first scheduling instruction is generated at this time.

[0094] If the load standard threshold φf ≤ dynamic load disturbance index Lfz ≤ load warning threshold φz, it means that the production line is under standard operating load, and process adaptability analysis is performed at this time.

[0095] When the dynamic load disturbance index Lfz > the load warning threshold φz, it indicates that the production line is operating under overload, and a second scheduling instruction is generated at this time.

[0096] In this embodiment, the load analysis unit calculates the dynamic load disturbance index Lfz based on the load fluctuation data set, which reflects the stability of the production line equipment. By logarithmic transformation of the load imbalance and the square root of the equipment vibration frequency, the unit comprehensively analyzes the impact of load differences and vibration on load fluctuations.

[0097] The formula's logic, derivation basis, and significance aim to quantify the impact of load fluctuations on the stability of equipment in an electronic production line. The introduction of the load fluctuation amplitude ∆La is based on system dynamics theory, reflecting the load fluctuation amplitude of the production line over a period of time, directly reflecting the load change. This parameter can measure the severity of load changes. The load imbalance Li represents the load difference between different workstations on the production line. The existence of load imbalance leads to uneven equipment operation, reducing the stability of the production line. By using the logarithmic function log(Li+1), the formula effectively controls the adverse effects of imbalance on the system when dealing with large load differences, making the formula's values ​​smoother and avoiding excessive amplification of extreme values. In statistics, using logarithmic transformation to narrow the data distribution range is called log-normal distribution, often used to describe physical phenomena that exhibit geometric growth or multiple changes in value. The equipment vibration frequency fvi reflects the vibration intensity of the equipment during operation. An increase in vibration frequency usually means an increase in equipment instability. The effect of vibration on load fluctuation has a non-linear relationship because the impact of increasing vibration on the load decreases. Therefore, the vibration frequency in the formula is treated by taking the square root. This reflects the diminishing effect of vibration intensity on load fluctuations. It is derived from classical vibration theory. Through nonlinear vibration theory, the vibration of equipment is usually not a simple linear action, but rather produces a nonlinear effect through the relationship between amplitude and frequency.

[0098] The load status assessment unit uses the mean and standard deviation of the dynamic load disturbance index Lfz over the past 30 days to pre-set a standard load threshold φf and a warning load threshold φz to assess the production line's load status, ensuring that load management remains within a reasonable range. When the dynamic load disturbance index Lfz is below the standard load threshold φf, the system generates scheduling instructions to optimize production line operation; when the dynamic load disturbance index Lfz is within the standard operating range, process adaptability analysis is performed to ensure stable production processes; and when the dynamic load disturbance index Lfz exceeds the warning load threshold φz, the system takes emergency scheduling measures to prevent the production line from operating under overload. The implementation of this module effectively avoids production fluctuations caused by uneven load distribution, improves production line stability, optimizes scheduling efficiency, reduces equipment wear and production downtime, and thus significantly improves overall production efficiency and resource utilization.

[0099] Example 4

[0100] Please refer to Figure 1 Specifically: the process adaptability module is used to perform process adaptability analysis when the load condition assessment indicates that the production line is at a standard operating load;

[0101] The process adaptability analysis command is used to perform correlation calculations based on equipment operation data sets to analyze the impact of the operating load on the production process in the electronic production line, in order to form a production process adaptability index Bsc, which is used to determine the adaptability of the production process under the current standard operating load condition. The specific formula is as follows: In the formula, cos represents the cosine function. This formula dynamically calculates the adjustment range for production batches based on the ratio of PCB board warpage height to material rack changeover speed. Adding 1 to the PCB board warpage height prevents the formula from reaching zero when the warpage height is zero. Adding 0.5 to the material rack changeover speed balances the impact of material changeover speed, ensuring that batch adjustments are not excessively reduced when the material changeover speed is low. The influence of the inlet pressure of the reflow oven on its heating uniformity is adjusted by using a cosine function. 1000 represents the scaling factor, which is used to convert the inlet pressure of the reflow oven from a larger Pa value to a range more suitable for the input of the cosine function, so as to ensure the balance and rationality of the calculation.

[0102] In this embodiment, the process adaptability module performs process adaptability analysis when the production line is assessed to be under standard operating load. It performs correlation calculations based on equipment operating data sets to generate a production process adaptability index (Bsc) to determine the adaptability of the production process under the current standard load. Through this module, the system can dynamically and precisely adjust production process parameters based on factors such as PCB warpage height, rack changing speed, and reflow oven inlet pressure. Specifically, it calculates the ratio of PCB warpage to rack changing speed using a cosine function to ensure that the adjustment range of production batches adapts to actual load changes. Simultaneously, it adjusts the impact of reflow oven inlet pressure to ensure heating uniformity. The implementation of this module effectively optimizes the adaptability of the production process under load changes, improves production stability, reduces process imbalances caused by uneven load, improves product quality and production efficiency, and ultimately achieves intelligent coordination between the production process and the production line load, significantly enhancing the flexibility and stability of the production line.

[0103] Formula logic, derivation basis and significance Derived from fundamental theories of material deformation and kinematics in physics, this method calculates how PCB warpage interacts with feeder switching speed. Adding 1 to the warpage value ensures that zero or minimal warpage does not result in division by zero, while adding 0.5 to the feeder speed ensures that even lower feeder speeds have minimal impact on the results. The PCB warpage height h is used to calculate this. pc This involves the stress-strain relationship in materials science, through the introduction of h pc +1 To avoid zero warpage under normal process conditions, V fe The +0.5 factor relates to the kinematic relationship between velocity and deformation. On a production line, the material changeover speed directly affects the flexibility and speed of production. By adding a constant of 0.5, calculation errors caused by very low speeds can be avoided. This adjustment ensures that calculation flexibility and accuracy can still be maintained even at low speeds, and is a classic theory of dynamics and kinematics. It involves descriptions of periodic phenomena and introduces classical heat transfer and fluid dynamics theories. Derived from Bernoulli's law in fluid mechanics, where gas pressure affects fluid flow characteristics, the airflow in the reflow oven plays a crucial role in the heating uniformity of the PCB. During the heating process, the airflow state in the reflow oven directly affects the heating uniformity of the PCB, and pressure changes affect heat transfer efficiency, thus affecting soldering quality. In physics, the cosine function is often used to describe periodic phenomena. In heat transfer, the pressure fluctuations and temperature distribution changes of a fluid are periodic. By modeling the influence of airflow pressure on the production process, the cosine function ensures that the model's response to heating uniformity is smooth when the air pressure changes. The cosine function can reduce the drastic effects of high or low pressure, thereby achieving a balanced adjustment of the heating effect.

[0104] Example 5

[0105] Please refer to Figure 1 and Figure 4 Specifically: the comprehensive analysis module includes a comprehensive load analysis unit and an adaptability evaluation unit;

[0106] The comprehensive load analysis unit is used to perform correlation calculations based on the dynamic load disturbance index Lfz and the production process adaptability index Bsc to generate a comprehensive scheduling response index Sdd, which comprehensively reflects the load status and process adaptability of the production line. The specific formula is as follows: In the formula, Lfz 2 +Bsc 2 This represents the sum of the squares of the load fluctuation index and the batch adjustment index, used to enhance the influence on dispatching decisions. This represents the difference between the dynamic load disturbance index Lfz and the production process adaptability index Bsc. It is used to suppress scheduling abrupt changes when the difference between load fluctuation and process adaptability is too large, ensuring a smooth transition in production scheduling. Adding 1 avoids the overall value being 0.

[0107] The adaptive evaluation unit is used to extract the comprehensive scheduling response index Sdd when all processes are qualified within the past 30 days, and calculate the mean using a statistical method. The mean is preset as the process adaptability threshold φd, and then a comprehensive process evaluation is performed with the real-time acquired comprehensive scheduling response index Sdd. The specific evaluation scheme is as follows:

[0108] When the comprehensive scheduling response index Sdd ≤ process adaptability threshold φd, it indicates that the process is qualified. At this time, the current production line maintains the production standard and continues to monitor.

[0109] When the comprehensive scheduling response index Sdd > the process adaptability threshold φd, it indicates that the process is unqualified and the load scheduling has an impact on the process. At this time, a third scheduling instruction is generated.

[0110] In this embodiment, the comprehensive load analysis unit generates a comprehensive scheduling response index Sdd based on the correlation calculation of the dynamic load disturbance index Lfz and the production process adaptability index Bsc. This index is used to comprehensively reflect the load fluctuations and process adaptability of the production line, thereby balancing the differences between load fluctuations and process adjustments and ensuring a smooth transition in production scheduling.

[0111] Formula logic, derivation basis, and significance: The dynamic load disturbance index Lfz quantifies the fluctuation or instability of load throughout the manufacturing process, describing the adaptability of the production process to load fluctuations. The square of this index Lfz... 2 These fluctuations are amplified to reflect their significance in disrupting production line stability. The Process Adaptability Index (Bsc) measures the production process's ability to handle and adapt to load fluctuations. 2 The strength of this adaptability and its impact on overall production efficiency were quantified. The dynamic load disturbance index Lfz and the production process adaptability index Bsc assess the stability of the production line from two different dimensions: load fluctuation and process adaptability, respectively. Analyzing either the dynamic load disturbance index Lfz or the production process adaptability index Bsc alone may not be sufficient to fully reflect the operating status of the production line. The dynamic load disturbance index Lfz only describes load fluctuations, while the production process adaptability index Bsc only reflects the adaptability of the production process; the two complement each other, and considering them together allows for a more accurate assessment of the system's response requirements. (Numerator Lfz) 2 +Bsc 2 The formula uses power function theory from signal processing and control systems to represent the combined impact of load disturbances and process adaptability on the overall scheduling response. By squaring these terms, the formula ensures significant emphasis on high disturbances and high adaptability, assigning greater weight to larger values, which is crucial for accurate scheduling in highly dynamic production environments. (Denominator) This further smooths the response to the Lfz-Bsc difference, avoiding excessive adjustments caused by small differences. The introduction of the square root makes the system's response to load differences more gradual. When the dynamic load disturbance index Lfz and the production process adaptability index Bsc are not significantly different, the adjustment amplitude will also decrease, maintaining the stability of the production process. |Lfz-Bsc| represents the difference between load disturbance and production process adaptability. This part is introduced based on deviation control in system stability theory. In optimal control, we need to control system error to minimize it. In this formula, |Lfz-Bsc| represents the deviation between load and process adaptability, indicating that when the difference between the two is too large, the system must make a more drastic response. Adding 1 to the denominator ensures that the formula is still calculable when the dynamic load disturbance index Lfz and the production process adaptability index Bsc are equal, and does not lead to division by zero.

[0112] The adaptability assessment unit determines the process adaptability threshold φd by statistically analyzing historical data and performs a comprehensive process evaluation with the real-time acquired integrated scheduling response index Sdd to ensure that the production line maintains optimal process adaptability during load fluctuations. When the integrated scheduling response index Sdd exceeds the process adaptability threshold φd, the system automatically generates adjustment instructions to avoid adverse effects on the process due to load fluctuations. Through this innovative mechanism, the system effectively avoids over-adjustment or unnecessary production interruptions in traditional scheduling methods, significantly improving the stability, flexibility, and adaptability of the production line, optimizing production efficiency, reducing the risk of equipment damage, and ensuring the efficient and stable operation of the production process.

[0113] Example 6

[0114] Please refer to Figure 1 Specifically: the scheduling optimization module is used to receive scheduling instructions generated by the load status assessment and comprehensive process assessment in real time according to the electronic production line dynamic scheduling system, and execute corresponding optimization scheduling operations, as follows;

[0115] Generate the first scheduling instruction: increase the production line's production pace by 10%, increase equipment uptime by 10%, and perform iterative evaluation through the load analysis module;

[0116] Generate a second scheduling instruction: reduce production batches by 30%, reduce runtime by 10%, and perform iterative evaluation through the load analysis module;

[0117] A third scheduling instruction is generated: it is transmitted to the electronic production line dynamic scheduling system to extend the material change cycle by 15% and reduce the production speed by 15%, and then iteratively evaluated through the load analysis module.

[0118] In this embodiment, the scheduling optimization module receives scheduling instructions generated from real-time load status assessment and comprehensive process assessment, flexibly adjusting the production rhythm, batch size, running time, and material changeover cycle of the production line to cope with different load and process requirements. During implementation, the scheduling optimization module automatically generates and executes three types of scheduling instructions based on real-time assessment results: increasing production rhythm and equipment running time, reducing production batches and running time, and extending material changeover cycle and reducing production speed. These optimized scheduling instructions ensure that the production line maintains efficient operation under load fluctuations and process changes, avoiding production stagnation or overloading, improving the flexibility and stability of the production line, and maximizing resource utilization and production efficiency. Through this mechanism, the present invention can dynamically adapt to various production needs, optimize production scheduling, reduce equipment failure rate and downtime, and ultimately achieve comprehensive optimization and continuous improvement of the production process.

[0119] Example 7

[0120] Please refer to Figure 2A dynamic scheduling method for flexible manufacturing electronic production lines includes the following steps:

[0121] S1. Install sensor groups on the electronic production line to collect real-time operating status data of the production line, and transmit the data to the electronic production line dynamic scheduling system for data processing to obtain load fluctuation data groups and equipment operation data groups.

[0122] S2. Perform load analysis on the electronic production line based on the load fluctuation data set, generate a load status assessment, and generate process adaptability analysis and assessment information based on the assessment results.

[0123] S3. Based on the equipment operation data set, conduct process adaptability analysis on the electronic production line under standard operating load;

[0124] S4. Fit the analysis results of the electronic production line load analysis and process adaptability analysis, comprehensively analyze the impact of load adjustment on the electronic production line production process, generate a comprehensive process assessment, and then generate assessment information based on the assessment results.

[0125] S5 receives scheduling instructions generated from load status assessment and comprehensive process assessment in real time, and executes corresponding optimized scheduling operations.

[0126] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A dynamic scheduling system for a flexible manufacturing electronic production line, characterized in that: It includes a data monitoring module, a load analysis module, a process adaptability module, a comprehensive analysis module, and a scheduling optimization module; The data monitoring module is used to install sensor groups on the electronic production line to collect the production line's operating status data in real time, and transmit it to the electronic production line dynamic scheduling system for data processing to obtain load fluctuation data groups and equipment operation data groups. The load analysis module is used to perform load analysis on the electronic production line based on the load fluctuation data set, generate a load status assessment, and generate process adaptability analysis and assessment information based on the assessment results. The process adaptability module is used to perform process adaptability analysis on electronic production lines operating at standard loads based on equipment operation data sets. The comprehensive analysis module is used to fit the analysis results of electronic production line load analysis and process adaptability analysis, comprehensively analyze the impact of load adjustment on the electronic production line production process, generate a comprehensive process assessment, and then generate assessment information based on the assessment results. The scheduling optimization module is used to receive scheduling instructions generated by load status assessment and comprehensive process assessment in real time, and execute corresponding optimized scheduling operations.

2. The flexible manufacturing electronic production line dynamic scheduling system according to claim 1, characterized in that: The data monitoring module includes a data acquisition unit and a data processing unit; The data acquisition unit is used to collect real-time operating status data of the production line based on the sensor groups installed at various locations on the electronic production line; The sensor group includes a power analyzer, a load sensor, a vibration frequency sensor, a laser displacement sensor, an encoder, and a pressure sensor; The power analyzer is used to connect to the power input terminal of the production line drive system to monitor the operating power of the production line in real time. The load sensor is installed below each workstation on the production line to collect the real-time load fz of each workstation. The vibration frequency sensor is used to be installed on the support frame of the production line equipment to directly collect the equipment vibration frequency fvi. The laser displacement sensor is installed above the path the PCB board travels to monitor the warpage height h of the PCB board in real time. pc ; The encoder is mounted on the drive shaft of the material rack to monitor the material changing speed V of the material rack in real time. fe ; The pressure sensor is installed on the inlet pipe of the reflux furnace near the furnace inlet to monitor the reflux furnace inlet pressure P in real time. sm .

3. The flexible manufacturing electronic production line dynamic scheduling system according to claim 2, characterized in that: The data processing unit is used to establish a communication connection between the sensor group and the electronic production line dynamic scheduling system through a wireless network, and to transmit the operating status data to the electronic production line dynamic scheduling system in real time for data processing, and to obtain load fluctuation data group and equipment operation data group. The data processing is used to preprocess the operating status data before performing data analysis; The preprocessing includes timestamp alignment, noise reduction, missing value imputation, and dimensionless processing. The timestamp alignment uses linear interpolation resampling technology to interpolate and predict missing time points in the running status data; the denoising uses wavelet denoising technology to preserve the transient structural features of the running status data and remove high-frequency noise; the missing value filling uses missing value interpolation technology to complete the running status data due to sampling interruption and communication packet loss; and the dimensionless processing uses the Max-Min method to remove the dimensional influence of the running status data. The data analysis includes load fluctuation analysis and load imbalance analysis; The load fluctuation analysis is used to perform time-domain analysis on the obtained operating power based on the electronic production line dynamic scheduling system, and to calculate the difference between the maximum fluctuation amplitude and the minimum fluctuation amplitude to obtain the load fluctuation amplitude ∆La. The load imbalance analysis is used to calculate the average load μ of each workstation based on the acquired real-time load fz through the electronic production line dynamic scheduling system. fz Then, the load unbalance degree Li is calculated using the mean absolute deviation method. The specific formula is as follows: In the formula, n represents the total number of workstations, and fz i This represents the load at the i-th workstation; The load fluctuation data set includes the load fluctuation amplitude ∆La, the load imbalance degree Li, and the equipment vibration frequency fvi; The equipment operation data set includes the PCB board warpage height h. pc Material changing speed V fe and reflux furnace inlet pressure P sm .

4. The flexible manufacturing electronic production line dynamic scheduling system according to claim 3, characterized in that: The load analysis module includes a load analysis unit and a load status assessment unit; The load analysis unit is used to perform load analysis on the electronic production line based on the load fluctuation data set, and to construct a dynamic load disturbance index Lfz to analyze the load status of the production line and reflect the stability of the production line's mechanical equipment. The specific formula is as follows: In the formula, log represents the logarithmic function.

5. The flexible manufacturing electronic production line dynamic scheduling system according to claim 4, characterized in that: The load status assessment unit is used to calculate the mean and standard deviation of the dynamic load disturbance index Lfz over the past 30 days based on statistical methods, and sets the difference between the mean and standard deviation as the load standard threshold φf, and the sum of the mean and standard deviation as the load warning threshold φz. Then, it performs load status assessment with the real-time acquired dynamic load disturbance index Lfz. The specific assessment scheme is as follows. When the dynamic load disturbance index Lfz < the load standard threshold φf, it indicates that the production line has excess load, and the first scheduling instruction is generated at this time. If the load standard threshold φf ≤ dynamic load disturbance index Lfz ≤ load warning threshold φz, it means that the production line is under standard operating load, and process adaptability analysis is performed at this time. When the dynamic load disturbance index Lfz > the load warning threshold φz, it indicates that the production line is operating under overload, and a second scheduling instruction is generated at this time.

6. The flexible manufacturing electronic production line dynamic scheduling system according to claim 5, characterized in that: The process adaptability module is used to perform process adaptability analysis when the load condition assessment indicates that the production line is at a standard operating load; The process adaptability analysis command is used to perform process adaptability analysis based on equipment operation data sets and construct a production process adaptability index Bsc to analyze the impact of the operating load on the electronic production line on the production process. This index is used to determine the adaptability of the production process under the current standard operating load condition. The specific formula is as follows: In the formula, cos represents the cosine function.

7. The flexible manufacturing electronic production line dynamic scheduling system according to claim 6, characterized in that: The comprehensive analysis module includes a comprehensive load analysis unit and an adaptability evaluation unit; The comprehensive load analysis unit is used to perform correlation calculations based on the dynamic load disturbance index Lfz and the production process adaptability index Bsc to generate a comprehensive scheduling response index Sdd, which comprehensively reflects the load status and process adaptability of the production line. The specific formula is as follows: .

8. The flexible manufacturing electronic production line dynamic scheduling system according to claim 7, characterized in that: The adaptive evaluation unit is used to extract the comprehensive scheduling response index Sdd when all processes are qualified within the past 30 days, and calculate the mean using a statistical method. The mean is preset as the process adaptability threshold φd, and then a comprehensive process evaluation is performed with the real-time acquired comprehensive scheduling response index Sdd. The specific evaluation scheme is as follows: When the comprehensive scheduling response index Sdd ≤ process adaptability threshold φd, it indicates that the process is qualified. At this time, the current production line maintains the production standard and continues to monitor. When the comprehensive scheduling response index Sdd > the process adaptability threshold φd, it indicates that the process is unqualified and the load scheduling has an impact on the process. At this time, a third scheduling instruction is generated.

9. The flexible manufacturing electronic production line dynamic scheduling system according to claim 1, characterized in that: The scheduling optimization module is used to receive scheduling instructions generated by the load status assessment and comprehensive process assessment in real time from the electronic production line dynamic scheduling system, and to execute corresponding optimized scheduling operations, as follows; Generate the first scheduling instruction: increase the production line's production pace by 10%, increase equipment uptime by 10%, and perform iterative evaluation through the load analysis module; Generate a second scheduling instruction: reduce production batches by 30%, reduce runtime by 10%, and perform iterative evaluation through the load analysis module; A third scheduling instruction is generated: it is transmitted to the electronic production line dynamic scheduling system to extend the material change cycle by 15% and reduce the production speed by 15%, and then iteratively evaluated through the load analysis module.

10. A dynamic scheduling method for a flexible manufacturing electronic production line, applied to the dynamic scheduling system for a flexible manufacturing electronic production line as described in any one of claims 1-9, characterized in that: Includes the following steps: S1. Install sensor groups on the electronic production line to collect real-time operating status data of the production line, and transmit the data to the electronic production line dynamic scheduling system for data processing to obtain load fluctuation data groups and equipment operation data groups. S2. Perform load analysis on the electronic production line based on the load fluctuation data set, generate a load status assessment, and generate process adaptability analysis and assessment information based on the assessment results. S3. Based on the equipment operation data set, conduct process adaptability analysis on the electronic production line under standard operating load; S4. Fit the analysis results of the electronic production line load analysis and process adaptability analysis, comprehensively analyze the impact of load adjustment on the electronic production line production process, generate a comprehensive process assessment, and then generate assessment information based on the assessment results. S5 receives scheduling instructions generated from load status assessment and comprehensive process assessment in real time, and executes corresponding optimized scheduling operations.

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