Software program flashing method for production line station controller

Abstract

The invention belongs to the technical field of controller flashing software programs, and particularly relates to a software program flashing method for a production line station controller, which comprises the following steps: S0, configuring a developed software program in an ALM system; the method comprises the following steps: S1, automatically selecting a software program needing to be flashed in a current time period through an ALM system, and packaging and encrypting the software program to obtain an encrypted software package; the encrypted software package is uploaded to the MES system; s2, automatically decrypting the encrypted software package through the MES system, verifying the decrypted software package, and storing the verified software package in a storage unit; s3, according to a preset distribution method, the verified software package is automatically sent to a corresponding flashing station through an MES system; and S4, after receiving the software package, the flashing station automatically decompresses the software package, recovers the software package into a software program, checks the software program, and flashes the software program passing the check. According to the method, the flashing efficiency can be greatly improved, human errors are reduced, and the method adapts to complex and changeable production environments.

Description

Technical Field

[0001] The present invention belongs to the technical field of controller software program flashing, and particularly relates to a method for flashing a software program for a production line station controller. Background Art

[0002] In current fields such as industrial automation, intelligent manufacturing, industrial Internet security services, and industrial Internet search services, as the core component of automation equipment, the update and maintenance of the software version of the controller play a crucial role in the stability and performance improvement of the system.

[0003] Currently, the method for flashing the software program of the controller on the production line is usually to manually copy the software program to the flashing station (i.e., the specific position on the production line where the software program needs to be flashed) for flashing. However, with the expansion of the production line scale, especially in large production lines where there are multiple flashing stations, and the controllers on these stations may involve multiple models, and the software programs to be flashed for each model are different. In this case, the disadvantages of the manual flashing method become more obvious: on the one hand, the manual operation efficiency is low and cannot adapt to the rhythm of large-scale production; on the other hand, since the correct software version needs to be manually selected and distributed to the corresponding stations, it is very easy to have version errors or omissions, which will in turn affect the production quality.

[0004] The existing technologies mainly have the following problems: First, low efficiency. The traditional manual flashing method requires operators to copy the software program to each flashing station one by one, consuming a large amount of time and human resources. Especially in the case of multiple stations and multiple models of controllers, the efficiency problem is particularly prominent. Second, error-prone. During the manual operation process, problems such as incorrect software version selection, file transfer failure, or flashing failure may occur due to negligence. These problems will not only increase the rework cost but also may lead to production interruption. Third, difficult to adapt to complex scenarios. In the scenario of multiple stations and multiple models of controllers, it is extremely difficult to manually manage complex version plans and distribution strategies, which is likely to cause resource waste or task delay. The root cause of these problems is that the traditional methods lack the support of automation and intelligence and cannot achieve the full-process closed-loop control from software version management to flashing execution.

[0005] Therefore, how to significantly improve the flashing efficiency, reduce human errors, and adapt to the complex and changeable production environment has become an urgent problem to be solved at present. Summary of the Invention

[0006] In view of the above deficiencies of the prior art, the present invention provides a method for flashing a software program for a production line station controller, which can significantly improve the flashing efficiency, reduce human errors, and adapt to the complex and changeable production environment.

[0007] To solve the above technical problems, the present invention adopts the following technical solutions: A method for flashing a software program for a production line station controller, comprising the following steps: S0. Configure the developed software program in the ALM system; and formulate a software version management strategy; the software version management strategy includes: the flashing stations corresponding to each software program, the flashing time arrangement, and the software version update plan; S1. According to the software version management strategy, automatically select the software program to be flashed in the current time period through the ALM system, package and encrypt it to obtain an encrypted software package; then upload the encrypted software package to the MES system; S2. Automatically decrypt the encrypted software package through the MES system, verify the decrypted software package, and store it in the storage unit; S3. Automatically send the verified software package to the corresponding flashing station through the MES system according to a preset allocation method; S4. After receiving the software package, the flashing station automatically decompresses it, restores it to the software program and performs verification, and flashes the software program that passes the verification.

[0008] Nomenclature: The ALM system, Application Lifecycle Management, is a set of tools and processes for managing the entire life cycle of software applications from requirements analysis, design, development, testing, deployment to maintenance and retirement.

[0009] The MES system, Manufacturing Execution System, is an industrial software system for monitoring, controlling, and optimizing the manufacturing process. It is located between the enterprise resource planning (ERP) system and the workshop equipment, acting as an information bridge to help enterprises achieve transparency, standardization, and high efficiency in the production process.

[0010] Flashing station: That is, the operation flashing station on the production line that needs to flash the software program.

[0011] Compared with the prior art, the present invention has the following beneficial effects: 1. Greatly improve the flashing efficiency. Through the automated collaboration of the ALM system and the MES system, the entire process from software program selection, packaging and encryption, uploading to distribution is automated. Compared with the traditional manual operation method, this method significantly reduces the time and steps of manual intervention. In a multi-station scenario, the MES system can automatically distribute software packages to the corresponding flashing stations according to the preset distribution method, avoiding the inefficient operation of manual copying one by one. After receiving the software package, the flashing station automatically completes the decompression, inspection and flashing operations, further improving the execution efficiency.

[0012] 2. Significantly reduce human errors. In the whole process, key links (such as software version selection, packaging and encryption, verification, distribution, etc.) are all automatically completed by the system, avoiding errors caused by human negligence (such as wrong version selection, file transfer failure, etc.). Through strict verification mechanisms (such as integrity verification, version verification), ensure the correctness and consistency of each software package during transmission and flashing, thereby reducing the risk of flashing failure.

[0013] 3. Adapt to complex and changing production environments. Based on the preset distribution method (such as by comprehensively analyzing factors such as the idle state and priority level of the flashing station), the MES system can dynamically adjust the software package distribution strategy to ensure the optimization of resource utilization. For a production line with multiple types of controllers and multiple stations, this method can flexibly handle different flashing requirements, avoiding task delays or resource waste caused by complex scenarios in traditional methods.

[0014] In summary, this method realizes the full-process automated management of the controller flashing software program by introducing the collaborative work of the ALM system and the MES system. It can greatly improve the flashing efficiency, reduce human errors, and adapt to complex and changing production environments, providing strong support for efficient production and quality assurance in the field of intelligent manufacturing.

[0015] Preferably, in S3, the preset distribution method includes: comprehensively analyzing the idle state and priority level of the flashing station, and sending software packages to each flashing station in turn.

[0016] Such a setting: 1. Optimize resource allocation. By analyzing the idle state of the flashing station in real time, ensure that software packages are only sent to the currently available stations, avoiding task delays or conflicts caused by busy stations. Dynamically adjust the distribution order according to the priority level, and give priority to high-priority tasks, thereby improving the overall production efficiency.

[0017] 2. Improve system flexibility. This method can adapt to complex production environments with multiple stations and multiple tasks, flexibly handle changes in the status of different stations (such as temporary failures, task switches, etc.), and ensure the continuity and stability of the distribution process.

[0018] 3. Enhanced load balancing. By comprehensively considering the idle status and priority levels of workstations, it avoids the situation where tasks are overly concentrated in a few workstations, achieves load balancing among workstations, and improves equipment utilization.

[0019] Preferably, in S3, when comprehensively analyzing the idle status and priority levels of flashing workstations, after respectively scoring the idle status and priority levels of each flashing workstation, a weighted sum is performed according to a preset weight coefficient to obtain a comprehensive score; and software packages are sent in descending order of the comprehensive score.

[0020] Such a setting has the following advantages: 1. Scientific and reasonable resource allocation. By quantitatively scoring the idle status and priority levels of flashing workstations and calculating the comprehensive score in combination with the preset weight coefficient, it ensures the scientificity and rationality of the software package distribution decision. The introduction of the weight coefficient enables the system to flexibly adjust the degree of attention to the idle status and priority levels according to actual needs, further optimizing the allocation strategy.

[0021] 2. Improve task execution efficiency. Software packages are sent in descending order of the comprehensive score, preferentially selecting the most suitable workstation for the current task, reducing task delays or repeated scheduling problems caused by improper workstation selection. This method based on scoring and sorting can quickly match the optimal workstation, significantly improving task execution efficiency.

[0022] 3. Enhance the adaptability of the system. This method can dynamically adapt to the complex scenarios of multiple workstations and multiple tasks in the production line. Even if the workstation status or task priority changes, the system can recalculate the comprehensive score in a timely manner and adjust the distribution order. For different types of controllers and diverse production requirements, this method shows strong adaptability.

[0023] 4. Reduce conflicts and resource waste. The comprehensive scoring mechanism avoids resource allocation conflicts (such as multiple workstations competing for the same task simultaneously) caused by simply relying on the idle status or priority level. Reasonably allocating tasks to the most suitable workstations minimizes the situation of resource idleness or overload, improving the overall resource utilization rate.

[0024] 5. Reduce human intervention. The automated scoring and sorting process replaces the traditional manual judgment method, reducing the subjectivity and potential errors brought by human intervention, and improving the accuracy and consistency of the allocation.

[0025] Preferably, in S3, when scoring the idle status of the flashing workstation, after comprehensively analyzing the real-time task load, equipment availability, resource occupancy situation, and historical reference data of the flashing workstation, the idle status score is obtained; The analysis of the real-time task load includes checking whether there is a currently ongoing flashing task at the flashing station. If a task is being executed at the flashing station, the remaining time is evaluated, and it is determined whether a new software package can be allocated immediately after the task is completed, thereby assigning a reference value for the idle state to the flashing station. The analysis of the equipment availability includes confirming whether the hardware devices on the flashing station are operating normally, thereby assigning a reference value for the idle state to the flashing station; the hardware devices include a controller and a communication interface. The analysis of the resource occupancy includes analyzing whether the resources of the flashing station are sufficient to support the download and flashing operations of a new software package, thereby assigning a reference value for the idle state to the flashing station; the resources include storage space and network bandwidth. The analysis of the historical reference data includes predicting the idle cycle of the flashing station within a preset future time based on historical records, thereby assigning a reference value for the idle state to the flashing station.

[0026] With such a setting, 1. The status of the station can be accurately evaluated. The real-time task load analysis can accurately determine whether the station is capable of immediately receiving a new task by checking the current task execution status and evaluating the remaining time, avoiding conflicts caused by overlapping tasks. The equipment availability analysis confirms whether the hardware devices (such as the controller and communication interface) are operating normally, ensuring that the station has the basic execution conditions, thereby increasing the success rate of task allocation. The resource occupancy analysis analyzes whether resources such as storage space and network bandwidth are sufficient, identifying potential bottleneck problems in advance to ensure the smooth execution of new tasks. The historical reference data analysis predicts the future idle cycle based on historical records, providing a basis for long-term task planning and further optimizing resource scheduling.

[0027] 2. The task allocation efficiency is improved. After comprehensively analyzing the above multiple dimensions, an idle state score is obtained, enabling the system to more accurately select the most suitable flashing station for the current task, reducing task delays or reallocations caused by inappropriate station selection. This multi-dimensional analysis method can quickly screen out the optimal station, significantly improving the overall efficiency of task allocation.

[0028] 3. The reliability of the system is enhanced. By comprehensively considering the status information of the station (including the current load, equipment health status, and resource availability), it is ensured that the assigned tasks can be executed in a stable and reliable environment, reducing the risk of task failure. The introduction of historical reference data further enhances the prediction ability of the system, reducing task interruptions caused by unexpected situations (such as equipment failures or resource shortages).

[0029] 4. Adapt to complex production environments. This method can flexibly handle the complex scenarios of multiple workstations and multiple tasks in the production line. Even if the status of the workstations changes dynamically, the system can adjust the scoring results in a timely manner through real-time analysis to ensure the rationality of task allocation. For different types of controllers and diverse production requirements, this method demonstrates strong adaptability.

[0030] Preferably, in S3, when scoring the priority level of the flashing workstation, after comprehensively analyzing the updated task urgency, the functional characteristics of the flashing workstation, the production plan matching, and the distance from the MES system, the priority level score is obtained; The analysis of the updated task urgency includes assigning higher priority reference values to relevant workstations according to the urgent requirements of software version updates; the urgent requirements include fixing critical vulnerabilities and meeting customer delivery deadlines; The analysis of the functional characteristics of the flashing workstation includes analyzing the complexity of the controllers of each workstation and assigning corresponding priority reference values; The analysis of the production plan matching includes analyzing the matching degree between the production plan of the production line where the workstation is located and the workstation, and assigning priority reference values to the flashing workstation based on the matching degree analysis results; the matching degree analysis includes task type matching degree, time schedule coincidence degree, and resource requirement adaptability; The analysis of the distance from the MES system includes assigning higher priority reference values to the flashing workstations that are closer to the MES system server.

[0031] With such settings, 1. It can accurately reflect the importance of tasks. The analysis of the updated task urgency assigns higher priority reference values to relevant workstations according to the urgent requirements of software version updates (such as fixing critical vulnerabilities or meeting customer delivery deadlines), ensuring that urgent tasks can be processed first. This method effectively avoids production interruptions or customer dissatisfaction caused by task delays. The analysis of the functional characteristics of the flashing workstation assigns priority reference values according to the complexity of the controllers responsible for different workstations, ensuring that complex tasks are assigned to the most suitable workstations, improving the success rate and efficiency of task execution.

[0032] 2. Improve the adaptability of the production plan. The production plan matching analysis makes the task allocation more in line with the overall production goal by comparing and analyzing the production plan of the production line where the workstation is located and assigning priority reference values based on the matching degree with the plan, reducing resource waste or production delays caused by task mismatches.

[0033] 3. Optimize the system communication efficiency. The analysis of the distance from the MES system assigns higher priority reference values to the flashing workstations that are closer to the MES system server, which can shorten the software package transmission time and reduce the impact of network latency on task execution, thereby improving the communication efficiency of the entire system.

[0034] 4. Enhance the flexibility and adaptability of the system. After comprehensively considering the above multiple dimensions, a priority rating is obtained, enabling the system to flexibly respond to task requirements in different scenarios. Whether it is an urgent task, a complex task, or a routine task, priorities can be reasonably allocated according to the actual situation. This multi-dimensional analysis method can adapt to complex production environments, especially in the case of multiple workstations and multiple tasks, showing strong adaptability.

[0035] Preferably, in S4, the flashing station calls a preset flashing software to flash the software program that has passed the inspection.

[0036] With such a setting, by the flashing station calling the preset flashing software to flash the software program that has passed the inspection, this method effectively ensures the reliability of the flashing process, improves the degree of automation and the consistency of flashing, while shortening the flashing time and reducing the maintenance cost, providing an important guarantee for realizing efficient and stable controller software flashing.

[0037] Preferably, in S4, the flashing station also feeds back the flashing result to the MES system.

[0038] With such a setting, full-process closed-loop management is realized. The feedback of the flashing result makes the entire flashing process form a complete closed loop. From the software version management of the ALM system, to the distribution and monitoring of the MES system, then to the actual execution of the flashing station, and finally through the feedback mechanism, the result is returned to the MES system, ensuring that the information of each link can be recorded and traced.

[0039] Preferably, key data in the flashing process in S1 - S4 is also recorded; the key data includes the time of uploading to the MES system, distribution time, flashing time, software version, and flashing result; for subsequent analysis and tracing.

[0040] With such a setting, 1. Improve traceability. Recording the key data in the flashing process (such as the time of uploading to the MES system, distribution time, flashing time, software version, and flashing result) establishes a complete data chain for each flashing task. Such detailed records enable any problem to be quickly traced back to a specific time point, workstation, or software version, facilitating the location of the root cause of the problem.

[0041] 2. Support problem diagnosis and quality analysis. By analyzing the recorded key data, problems that may exist in the flashing process can be identified (such as frequent flashing failures at certain workstations, low flashing success rate of specific software versions, etc.). This data analysis ability helps to promptly discover potential quality hazards and take improvement measures.

[0042] 3. Optimize the production process. Based on the recorded data, the efficiency of the entire flashing process (such as whether the upload time, distribution time, and flashing time are reasonable) can be evaluated, and bottleneck links can be identified. By optimizing these links, the production efficiency can be significantly improved.

[0043] Preferably, in S2, when inspecting the decrypted software package, the inspection content includes: integrity inspection of the software package, format verification, and version verification of the software package.

[0044] With such a setting, by performing integrity inspection, format verification, and version verification on the decrypted software package, this method ensures the integrity and correctness of the software package, prevents version errors and potential security risks, reduces the occurrence of subsequent problems, improves the security of the system and the reliability of the automated process, and provides an important guarantee for realizing efficient and stable software package distribution and flashing. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to make the objectives, technical solutions, and advantages of the invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings, where: Figure 1 is a flowchart of this method. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] The following will be further described in detail through specific embodiments: Embodiment: As Figure 1 shown, in this embodiment, a method for flashing a software program for a production line station controller is disclosed, including the following steps: S0. Configure the developed software program in the ALM system (Application Lifecycle Management, application program lifecycle management system); and formulate a software version management strategy; the software version management strategy includes: the flashing stations corresponding to each software program, the flashing time arrangement, and the software version update plan.

[0047] The ALM system is a set of tools and processes for managing the entire lifecycle of software applications from requirements analysis, design, development, testing, deployment to maintenance and retirement. It aims to improve software development efficiency, ensure product quality, optimize team collaboration, and achieve transparent management of projects.

[0048] S1. According to the software version management strategy, the ALM system automatically selects the software program to be flashed in the current time period, packs and encrypts it to obtain an encrypted software package; then uploads the encrypted software package to the MES system (Manufacturing Execution System). The MES system is an industrial software system used to monitor, control, and optimize the manufacturing process. It is located between the enterprise resource planning (ERP) system and the workshop equipment, acting as an information bridge to help enterprises achieve transparency, standardization, and high efficiency in the production process.

[0049] S2. The MES system automatically decrypts the encrypted software package, verifies the decrypted software package, and stores it in the storage unit.

[0050] Specifically, when verifying the decrypted software package, the verification content includes: integrity verification, format verification, and version verification of the software package. In this way, by performing integrity verification, format verification, and version verification on the decrypted software package, this method ensures the integrity and correctness of the software package, prevents version errors and potential security risks, reduces the occurrence of subsequent problems, improves the security of the system and the reliability of the automated process, and provides an important guarantee for achieving efficient and stable software package distribution and flashing.

[0051] S3. According to the preset distribution method, the MES system automatically sends the verified software package to the corresponding flashing workstation.

[0052] Among them, the preset distribution method includes: comprehensively analyzing the idle status and priority level of the flashing workstations, and sending software packages to each flashing workstation in turn. When comprehensively analyzing the idle status and priority level of the flashing workstations, each flashing workstation is scored for its idle status and priority level respectively, and then weighted summation is performed according to the preset weight coefficient to obtain a comprehensive score; and the software packages are sent in descending order of the comprehensive score.

[0053] In this way, scientific and reasonable resource allocation can be achieved. By quantitatively scoring the idle status and priority level of the flashing stations and calculating the comprehensive score in combination with the preset weight coefficient, the scientificity and rationality of the software package distribution decision are ensured. The introduction of the weight coefficient enables the system to flexibly adjust the attention degree to the idle status and priority level according to the actual needs, further optimizing the allocation strategy. It can also improve the task execution efficiency. The software packages are sent in descending order of the comprehensive score, and the stations most suitable for the current task are preferentially selected, reducing task delays or repeated scheduling problems caused by inappropriate station selection. This method based on score ranking can quickly match the optimal station, significantly improving the task execution efficiency. In addition, it can enhance the adaptability of the system. This method can dynamically adapt to the complex scenarios of multiple stations and multiple tasks in the production line. Even if the station status or task priority changes, the system can recalculate the comprehensive score in a timely manner and adjust the distribution order. For different types of controllers and diverse production requirements, this method shows strong adaptability. Moreover, the comprehensive score mechanism avoids resource allocation conflicts (such as multiple stations competing for the same task) caused by simply relying on the idle status or priority level. Tasks are reasonably assigned to the most suitable stations, minimizing the situation of resource idleness or overload and improving the overall resource utilization rate.

[0054] During specific implementation, when scoring the idle status of the flashing stations, after comprehensive analysis based on the real-time task load, equipment availability, resource occupancy of the flashing stations, and historical reference data, the idle status score is obtained; The analysis of the real-time task load includes checking whether there is a flashing task in progress at the flashing station currently. If the flashing station is executing a task, the remaining time is evaluated, and it is judged whether a new software package can be immediately allocated after the task is completed, thereby assigning an idle status reference value to the flashing station; The analysis of the equipment availability includes confirming whether the hardware devices on the flashing station are operating normally, thereby assigning an idle status reference value to the flashing station; the hardware devices include controllers and communication interfaces; The analysis of the resource occupancy includes analyzing whether the resources of the flashing station are sufficient to support the download and flashing operations of new software packages, thereby assigning an idle status reference value to the flashing station; the resources include storage space and network bandwidth; The analysis of the historical reference data includes predicting the idle cycle of the flashing station within a preset future time based on historical records, thereby assigning an idle status reference value to the flashing station.

[0055] In this way, the status of the workstations can be accurately evaluated. Through real-time task load analysis, by examining the current task execution situation and evaluating the remaining time, it is possible to accurately determine whether a workstation has the ability to immediately receive new tasks, avoiding conflicts caused by overlapping tasks. Equipment availability analysis confirms whether hardware devices (such as controllers and communication interfaces) are operating normally, ensuring that the workstations have the basic execution conditions, thereby increasing the success rate of task allocation. Resource occupancy analysis examines whether resources such as storage space and network bandwidth are sufficient, identifying potential bottleneck problems in advance to ensure the smooth execution of new tasks. Historical reference data analysis combines historical records to predict future idle cycles, providing a basis for long-term task planning and further optimizing resource scheduling.

[0056] In addition, the task allocation efficiency can be improved. After comprehensively analyzing the above-mentioned multiple dimensions to obtain an idle status score, the system can more accurately select the most suitable flashing workstation for the current task, reducing task delays or reallocations caused by inappropriate workstation selection. This multi-dimensional analysis method can quickly screen out the optimal workstation, significantly improving the overall efficiency of task allocation. Moreover, by comprehensively considering the status information of the workstations (including current load, equipment health status, and resource availability), it is ensured that the allocated tasks can be executed in a stable and reliable environment, reducing the risk of task failure. The introduction of historical reference data further enhances the system's prediction ability, reducing task interruptions caused by unexpected situations (such as equipment failures or resource shortages). In addition, this method can flexibly handle complex scenarios with multiple workstations and multiple tasks in the production line. Even if the workstation status changes dynamically, the system can adjust the scoring results in a timely manner through real-time analysis to ensure the rationality of task allocation. For different types of controllers and diverse production requirements, this method shows strong adaptability.

[0057] During specific implementation, when assigning a priority score to the flashing workstation, after comprehensively analyzing the urgency of the update task, the functional characteristics of the flashing workstation, the match with the production plan, and the distance from the MES system, a priority score is obtained; The analysis of the urgency of the update task includes assigning a higher priority reference value to the relevant workstations according to the urgent requirements of software version updates; the urgent requirements include fixing critical vulnerabilities and meeting customer delivery deadlines; The analysis of the functional characteristics of the flashing workstation includes analyzing the complexity of the controllers of each workstation and assigning corresponding priority reference values; The analysis of the match with the production plan includes analyzing the match degree between the production plan of the production line where the workstation is located and the workstation, and assigning a priority reference value to the flashing workstation based on the match degree analysis results; the match degree analysis includes task type match degree, time schedule coincidence degree, and resource requirement adaptability; The analysis of the distance to the MES system includes assigning a higher priority reference value to the flashing station closer to the MES system server.

[0058] In this way, the importance of tasks can be accurately reflected. The update of the task urgency analysis assigns a higher priority reference value to the relevant stations according to the urgent requirements for software version updates (such as fixing critical vulnerabilities or meeting customer delivery deadlines), ensuring that urgent tasks can be processed first. This method effectively avoids production interruptions or customer dissatisfaction caused by task delays. The analysis of the functional characteristics of the flashing station assigns a priority reference value according to the complexity of the controllers responsible for different stations, ensuring that complex tasks are assigned to the most suitable stations, improving the success rate and efficiency of task execution. It can also enhance the adaptability of the production plan. The production plan matching analysis assigns a priority reference value based on the comparison and analysis of the production plan of the production line where the station is located and the degree of matching with the plan, making the task assignment more in line with the overall production goal and reducing resource waste or production delays caused by task mismatches. In addition, the analysis of the distance to the MES system assigns a higher priority reference value to the flashing station closer to the MES system server, which can shorten the software package transmission time and reduce the impact of network latency on task execution, thereby enhancing the communication efficiency of the entire system. After comprehensively considering the above multiple dimensions, the priority level score is obtained, enabling the system to flexibly respond to task requirements in different scenarios. Whether it is an urgent task, a complex task or a regular task, the priority can be reasonably assigned according to the actual situation. This multi-dimensional analysis method can adapt to complex production environments, especially in the case of multiple stations and multiple tasks, showing strong adaptability.

[0059] S4. After receiving the software package, the flashing station automatically decompresses it, restores it to a software program and conducts an inspection, and then flashes the software program that passes the inspection.

[0060] Among them, the flashing station calls a preset flashing software to flash the software program that passes the inspection. In this way, by using the preset flashing software called by the flashing station to flash the software program that passes the inspection, this method effectively ensures the reliability of the flashing process, improves the automation degree and the consistency of flashing, while shortening the flashing time and reducing the maintenance cost, providing an important guarantee for realizing efficient and stable controller software flashing.

[0061] The flashing station also feeds back the flashing result to the MES system. Such a setting realizes full-process closed-loop management. The feedback of the flashing result makes the entire flashing process form a complete closed loop. From the software version management of the ALM system, to the distribution and monitoring of the MES system, to the actual execution of the flashing station, and finally the result is returned to the MES system through the feedback mechanism, ensuring that the information of each link can be recorded and traced.

[0062] During specific implementation, key data in the flashing process of S1 - S4 is also recorded; the key data includes the time of uploading to the MES system, distribution time, flashing time, software version, and flashing result; for subsequent analysis and tracking.

[0063] In this way, traceability is enhanced. Recording the key data in the flashing process (such as the time of uploading to the MES system, distribution time, flashing time, software version, and flashing result) establishes a complete data chain for each flashing task. Such detailed records enable any problem to be quickly traced back to a specific time point, workstation, or software version, facilitating the identification of the root cause of the problem. In addition, it also supports problem diagnosis and quality analysis. By analyzing the recorded key data, potential problems in the flashing process (such as frequent flashing failures at certain workstations, low flashing success rate for specific software versions, etc.) can be identified. This data analysis ability helps to promptly detect potential quality hazards and take improvement measures. Moreover, based on the recorded data, the efficiency of the entire flashing process (such as whether the uploading time, distribution time, and flashing time are reasonable) can be evaluated, and bottleneck links can be identified. By optimizing these links, production efficiency can be significantly improved.

[0064] Through the automated collaboration of the ALM system and the MES system, this method realizes the full - process automation from software program selection, packaging and encryption, uploading to distribution. Compared with the traditional manual operation method, this method significantly reduces the time and steps of manual intervention. In a multi - workstation scenario, the MES system can automatically distribute software packages to the corresponding flashing workstations according to the preset distribution method, avoiding the inefficient operation of manual copying one by one. After receiving the software package, the flashing workstation automatically completes decompression, verification, and flashing operations, further improving the execution efficiency. In addition, this method can also significantly reduce human errors. In the whole process, key links (such as software version selection, packaging and encryption, verification, distribution, etc.) are automatically completed by the system, avoiding errors caused by human negligence (such as incorrect version selection, file transfer failure, etc.). Through a strict verification mechanism (such as integrity verification, version verification), the correctness and consistency of each software package during transmission and flashing are ensured, thereby reducing the risk of flashing failure. Moreover, based on the preset distribution method (such as by comprehensively analyzing factors such as the idle state and priority of workstations), the MES system can dynamically adjust the distribution strategy of software packages to ensure the optimal utilization of resources. For production lines with multiple types of controllers and multiple workstations, this method can flexibly meet different flashing requirements, avoiding task delays or resource waste caused by complex scenarios in the traditional method.

[0065] Through the collaborative work of introducing the ALM system and the MES system, this method realizes the full-process automated management of the controller's software program flashing. It can greatly improve the flashing efficiency, reduce human errors, and adapt to complex and changeable production environments, providing strong support for efficient production and quality assurance in the field of intelligent manufacturing.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than limiting them. Those of ordinary skill in the art should understand that any modifications or equivalent replacements made to the technical solutions of the present invention without departing from the purpose and scope of the present technical solution should be covered within the scope of the claims of the present invention.

Claims

1. A method for flashing a software program for a production line station controller, characterized in that, It includes the following steps: S0. Configure the developed software program in the ALM system; and formulate a software version management strategy; The software version management strategy includes: the flashing station corresponding to each software program, the flashing time arrangement, and the software version update plan; S1. According to the software version management strategy, automatically select the software program to be flashed in the current time period through the ALM system, package and encrypt it to obtain an encrypted software package; then upload the encrypted software package to the MES system; S2. Automatically decrypt the encrypted software package through the MES system, verify the decrypted software package, and store it in the storage unit; S3. Automatically send the verified software package to the corresponding flashing station through the MES system according to the preset allocation method; S4. After receiving the software package, the flashing station automatically decompresses it, restores it to the software program and conducts an inspection, and flashes the software program that passes the inspection.

2. The method for flashing a software program for a production line station controller according to claim 1, characterized in that: In S3, the preset allocation method includes: comprehensively analyzing the idle status and priority level of the flashing stations, and sequentially sending software packages to each flashing station.

3. The method for flashing a software program for a production line station controller according to claim 2, characterized in that: In S3, when comprehensively analyzing the idle status and priority level of the flashing stations, after respectively scoring the idle status and priority level of each flashing station, perform a weighted sum according to the preset weight coefficient to obtain a comprehensive score; And send software packages in descending order of the comprehensive score.

4. The method for flashing a software program for a production line station controller according to claim 3, characterized in that: In S3, when scoring the idle status of the flashing station, after comprehensively analyzing based on the real-time task load, equipment availability, resource occupancy situation and historical reference data of the flashing station, obtain the idle status score; The analysis of the real-time task load includes checking whether there is a flashing task in progress at the flashing station currently. If the flashing station is executing a task, evaluate the remaining time and determine whether a new software package can be immediately allocated after the task is completed, so as to assign an idle status reference value to the flashing station; The analysis of the equipment availability includes confirming whether the hardware equipment on the flashing station is operating normally, so as to assign an idle status reference value to the flashing station; the hardware equipment includes a controller and a communication interface; The analysis of the resource occupancy situation includes analyzing whether the resources of the flashing station are sufficient to support the download and flashing operations of the new software package, so as to assign an idle status reference value to the flashing station; the resources include storage space and network bandwidth; The analysis of the historical reference data includes predicting the idle cycle of the flashing station within a preset future time based on historical records, so as to assign an idle status reference value to the flashing station.

5. The method for flashing a software program for a production line station controller according to claim 3, characterized in that: In S3, when scoring the priority level of the flashing station, after comprehensively analyzing based on the urgency of the update task, the functional characteristics of the flashing station, the production plan matching, and the distance from the MES system, obtain the priority level score; The analysis of the urgency of the update task includes assigning a higher priority reference value to the relevant stations according to the urgent requirements of the software version update; the urgent requirements include fixing critical vulnerabilities and meeting customer delivery deadlines; The analysis of the functional characteristics of the flashing station includes analyzing the complexity of the controller of each station and assigning corresponding priority reference values; The analysis of the production plan matching includes analyzing the matching degree between the production plan of the production line where the station is located and the station, and assigning a priority reference value to the flashing station based on the matching degree analysis result; The matching degree analysis includes task type matching degree, time arrangement coincidence degree, and resource requirement adaptability; The analysis of the distance from the MES system includes assigning a higher priority reference value to the flashing station closer to the MES system server.

6. The method for flashing a software program for a production line station controller according to claim 1, characterized in that: In S4, the flashing station calls the preset flashing software to flash the software program after passing the inspection.

7. The method for flashing a software program for a production line station controller according to claim 1, characterized in that: In S4, the flashing station also feeds back the flashing result to the MES system.

8. The method for flashing a software program for a production line station controller according to claim 1, characterized in that: The key data in the flashing process in S1 - S4 are also recorded; the key data include the time of uploading to the MES system, distribution time, flashing time, software version, and flashing result; for subsequent analysis and tracking.

9. The method for flashing a software program for a production line station controller according to claim 1, wherein: In S2, when inspecting the decrypted software package, the inspection content includes: integrity inspection of the software package, format verification, and version verification of the software package.

Images