Production process management method and device, electronic equipment and storage medium

Abstract

This application provides a production process management method, apparatus, electronic device, and storage medium. The method acquires a process verification standard knowledge base, information on the project to be verified, and production process data to be verified. The process verification standard knowledge base is generated based on a process document source; if the process document source changes, the process verification standard knowledge base is updated based on the changed process document source. The method verifies the production process data to be verified based on the process verification standard knowledge base and the information on the project to be verified. If the verification result is abnormal, the cause of the abnormality is determined, and then the abnormality handling object and abnormality handling rules are determined. The cause of the abnormality and the abnormality handling rules are sent to the abnormality handling object to manage the production process. By dynamically linking and updating the process verification standard knowledge base with the process document source, this method can better adapt to complex and ever-changing production scenarios, improve the efficiency and accuracy of the verification process, and enhance the real-time performance of the verification.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence technology, and in particular to a production process management method, apparatus, electronic device, and storage medium. Background Technology

[0002] To achieve production site management and control, it is often necessary to rely on industrial automation systems and information management platforms, such as Manufacturing Execution Systems (MES), Manufacturing Operation Management (MOM), and Quality Management Systems (QMS). In related technologies, when managing and controlling the production site, multi-channel camera devices can be used to capture images of the production line, and fixed detection rules can be used to determine whether the operators on the production line are operating according to regulations. Alternatively, sensor networks can be used to monitor equipment current and temperature parameters to determine if any abnormalities exist.

[0003] While the methods described above achieve automated data collection at the data perception level, they primarily rely on fixed judgment rules or basic classification models for data analysis and decision-making. This approach often exhibits insufficient adaptability when facing complex and ever-changing production scenarios, resulting in low real-time performance and poor accuracy in management and control. Summary of the Invention

[0004] This application provides a production process management method, apparatus, electronic device, and storage medium to solve the technical problems of insufficient adaptability, low real-time performance, and poor accuracy in production management and control in related technologies.

[0005] This application provides a production process management method, which includes: acquiring a process verification standard knowledge base, information on items to be verified, and production process data to be verified. The process verification standard knowledge base is generated based on a process document source. If the process document source changes, the process verification standard knowledge base is updated based on the changed process document source. The method verifies the production process data to be verified based on the process verification standard knowledge base and the information on items to be verified. If the verification result is abnormal, the cause of the abnormality is determined, and then the abnormality handling object and abnormality handling rules are determined. The cause of the abnormality and the abnormality handling rules are sent to the abnormality handling object to manage the production process. By dynamically linking the process verification standard knowledge base with the process document source and updating the process verification standard knowledge base in a timely manner, this production process management method can better adapt to complex and ever-changing production scenarios, improve the efficiency and accuracy of the verification process, and enhance the real-time performance of the verification.

[0006] In one embodiment of this application, the verification of the production process data to be verified based on the process verification standard knowledge base and the information of the project to be verified includes: matching the verification requirements in the process verification standard knowledge base according to the information of the project to be verified; verifying the production process data to be verified based on the verification requirements; if the production process data to be verified meets the verification requirements, the verification result is successful; if the production process data to be verified does not meet the verification requirements, the verification result is unsuccessful. Verifying the production process data to be verified through the verification requirements in the process verification standard knowledge base provides an objective evaluation method, which helps to improve the efficiency and accuracy of the verification process.

[0007] In one embodiment of this application, determining the cause of an anomaly, and then determining the object to be handled and the rules for handling anomalies, includes: recording production process data to be verified that does not meet the verification requirements as anomaly data; generating an anomaly cause based on the anomaly data, the verification requirements corresponding to the anomaly data, and the information of the item to be verified corresponding to the anomaly data; determining an anomaly handling rule based on the information of the item to be verified in the anomaly cause; and determining the object to be handled according to the information of the item to be verified in the anomaly cause and a preset item object mapping relationship, wherein the preset item object mapping relationship represents the mapping relationship between the verification item and the corresponding object to be handled. By collecting anomaly causes, effective reference information can be provided for the handling of subsequent anomalies, improving the efficiency of handling anomalies. By automatically matching the corresponding object to be handled and the rules for handling anomalies, it is even more helpful to improve the efficiency of resolving anomalies.

[0008] In one embodiment of this application, the generation method of the process verification standard knowledge base includes: obtaining a process document source; determining multiple verification items based on the process document source, and determining a process verification list and judgment criteria corresponding to each verification item; generating verification requirements based on the process verification list and judgment criteria, wherein the process verification list includes one or more verification sub-items, and the judgment criteria are generated based on the judgment sub-criteria of all verification sub-items; and generating the process verification standard knowledge base based on all the verification items and verification requirements, as well as the matching relationship between the verification items and verification requirements. By extracting key information from the process source documents to generate the process verification standard knowledge base, a solution for automatically generating the process verification standard knowledge base is provided, reducing the tediousness and possibility of errors in manually compiling rules, and improving work efficiency.

[0009] In one embodiment of this application, the method further includes: if the process document source changes, triggering an update to the process verification standard knowledge base; determining the modification content based on the new process document source and the original process document source; updating the process verification standard knowledge base based on the modification content; wherein the update method includes: determining the modification action of the modification content, the modification action including adding, deleting, or modifying; determining the modification item and modification requirement based on the modification content, the modification requirement including modifying the verification list and / or modifying the standard; if the modification action is adding, adding the modification item and modification requirement to the process verification standard knowledge base; if the modification action is deleting, matching the modification item and / or modification requirement with the verification item and verification requirement respectively, and deleting the matched verification item and verification requirement from the process verification standard knowledge base; if the modification action is modifying, matching the modification item with the verification item and verification requirement, and replacing the verification requirement corresponding to the matched verification item with the modification requirement to update the process verification standard knowledge base. By adopting corresponding update methods for different modification actions, the update of the process verification standard knowledge base can be completed efficiently.

[0010] In one embodiment of this application, after updating the process verification standard knowledge base based on the modified content, the method further includes: determining the affected targets based on the modified content, generating a change notification based on the modified content, and notifying the users corresponding to the affected targets; and / or, displaying the updated process verification standard knowledge base, completing the update of the process verification standard knowledge base in response to an input change consent instruction, and further modifying the updated process verification standard knowledge base based on the instructions of the change modification instruction if a change modification instruction is received. When the process verification standard knowledge base is updated, relevant personnel need to be notified promptly to implement the latest requirements and improve management efficiency. For some important changes, it is also necessary to provide an opportunity for manual review to improve the legality of the changes.

[0011] After sending the exception handling rules to the exception reporting object, the method further includes: obtaining the exception handling feedback result from the exception reporting object, the exception handling feedback result including one or more of exception resolution status, exception resolution process data, and outstanding exception issues; sending the exception handling feedback result to the target management object; receiving the task closure indication from the target management object; if the task closure indication is closed, ending the process; if the task closure indication is not closed, generating an exception task re-handling notification and sending it to the exception reporting object to notify the exception reporting object to further process the exception event. This can achieve closed-loop processing of exception issues and further improve the possibility of problem resolution.

[0012] This application embodiment also provides a production process management device, which includes: an acquisition module, used to acquire a process verification standard knowledge base, information on items to be verified, and production process data to be verified, wherein the process verification standard knowledge base is generated based on a process document source, and if the process document source changes, the process verification standard knowledge base is updated based on the changed process document source; a verification module, used to verify the production process data to be verified based on the process verification standard knowledge base and the information on items to be verified; a determination module, used to determine the cause of the abnormality if the verification result is abnormal, and then determine the abnormality handling object and the abnormality handling rules; and a management module, used to send the abnormality cause and the abnormality handling rules to the abnormality handling object to manage the production process.

[0013] This application also provides an electronic device, including: a memory storing a computer program thereon; and a processor for executing the computer program in the memory to implement the steps of the method described in any of the above embodiments.

[0014] This invention also provides a computer-readable storage medium having a computer program stored thereon, the computer program being used to cause a computer to perform the method provided in any of the above embodiments.

[0015] The beneficial effects of the embodiments of this application are as follows: The production process management method, apparatus, electronic device, and storage medium proposed in the embodiments of this application acquire a process verification standard knowledge base, information on the project to be verified, and production process data to be verified. The process verification standard knowledge base is generated based on the process document source. If the process document source changes, the process verification standard knowledge base is updated based on the changed process document source. The production process data to be verified is verified based on the process verification standard knowledge base and the information on the project to be verified. If the verification result is abnormal, the cause of the abnormality is determined, and then the abnormality handling object and abnormality handling rules are determined. The cause of the abnormality and the abnormality handling rules are sent to the abnormality handling object to manage the production process. By dynamically linking the process verification standard knowledge base with the process document source and updating the process verification standard knowledge base in a timely manner, this production process management method can better adapt to complex and ever-changing production scenarios, improve the efficiency and accuracy of the verification process, and enhance the real-time performance of the verification. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0017] In the attached diagram:

[0018] Figure 1 A schematic flowchart of a production process management method provided in one embodiment of this application; Figure 2 A specific flowchart illustrating the construction of a process verification standard knowledge base is provided for one embodiment of this application; Figure 3 A schematic diagram illustrating a specific process for automatically updating and adjusting process verification standards, provided as an embodiment of this application; Figure 4 A specific flowchart illustrating an abnormal closed-loop management and intelligent dispatching method provided in an embodiment of this application; Figure 5 A schematic diagram of a production process management device provided in an embodiment of this application; Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0019] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0020] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the shape, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0021] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the present application. However, it will be apparent to those skilled in the art that embodiments of the present application may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the present application.

[0022] It should be noted that, in practical applications, the collection and processing of data such as production process data to be verified in this application must strictly comply with the requirements of relevant national laws and regulations, obtain the informed consent or separate consent of the personal information subject, and carry out subsequent data use and processing within the scope of laws and regulations and the authorization of the personal information subject.

[0023] In related technologies, production process control requires verification of a specific process node according to fixed rules. The inventors discovered that when the technical requirements of this process node change, the rules in these technologies fail to recognize this change and continue to verify according to the original fixed rules. This results in poor real-time performance, low accuracy, and an inability to adapt to complex and ever-changing production scenarios, demonstrating insufficient adaptability. Furthermore, once an anomaly is detected and an alarm is provided, the process ends, lacking monitoring of subsequent problem-solving and making it impossible to know the status of the resolution.

[0024] To address the aforementioned technical problems, this application provides a production process management method. This method acquires a process verification standard knowledge base, information on projects to be verified, and production process data to be verified. The process verification standard knowledge base is generated based on process document sources; if the process document sources change, the process verification standard knowledge base is updated based on the changed process document sources. The method verifies the production process data to be verified based on the process verification standard knowledge base and the information on projects to be verified. If the verification result is abnormal, the cause of the abnormality is determined, and then the abnormality handling object and abnormality handling rules are determined. The cause of the abnormality and the abnormality handling rules are sent to the abnormality handling object to manage the production process. By dynamically linking the process verification standard knowledge base with the process document sources and updating the process verification standard knowledge base in a timely manner, this production process management method can better adapt to complex and ever-changing production scenarios, improving the efficiency and accuracy of the verification process and enhancing the real-time performance of verification. By automating the compilation process of the process verification standard knowledge base, intelligentizing process verification, and implementing closed-loop processing of abnormality management, a collaborative and efficient intelligent process verification ecosystem is constructed, which can significantly improve the efficiency and accuracy of process verification.

[0025] Please see Figure 1 , Figure 1 A schematic flowchart of a production process management method provided in one embodiment of this application is shown below. Figure 1 As shown, the method includes the following steps: Step S110: Obtain the process verification standard knowledge base, information on the project to be verified, and production process data to be verified.

[0026] The process validation standard knowledge base is generated based on the process document source. If the process document source changes, the process validation standard knowledge base is updated based on the changed process document source.

[0027] The production process data to be verified can be multi-source data, and the specific data types can be set according to the needs of those skilled in the art. For example, it may include one or more types of data such as image data, audio data, and sensor data.

[0028] The information on the project to be verified may include one or more sub-projects, and the specific verification content may be set by those skilled in the art as needed.

[0029] In one embodiment, obtaining the project information to be verified and the production process data to be verified includes: obtaining the project information to be verified; determining the production process data field associated with the project information to be verified based on the project information to be verified and the preset target information verification data association relationship; and extracting the production process data to be verified based on the production process data field. A preset target information verification data association relationship can be pre-defined, which represents the corresponding production process data to be collected when verifying different projects. For example, if it is necessary to check whether employees' work safety attire complies with regulations, the project information to be verified could be work safety attire for a specific position. The corresponding production process data to be verified would be a full-body image of an employee in that position. Then, by collecting the full-body image of the employee in the corresponding position, the corresponding work safety tools and their placement can be identified through image recognition. Compliance is determined using verification requirements in the process verification standard knowledge base. This method allows users to select appropriate projects for subsequent verification as needed, making it easy to adjust verification projects and enhancing the flexibility of the solution.

[0030] In one embodiment, the process verification standard knowledge base is generated by: obtaining a process document source; determining multiple verification items based on the process document source, and determining a process verification list and judgment criteria corresponding to each verification item; generating verification requirements based on the process verification list and judgment criteria, wherein the process verification list includes one or more verification sub-items, and the judgment criteria are generated based on the judgment sub-criteria of all verification sub-items; and generating the process verification standard knowledge base based on all verification items and verification requirements, and the matching relationship between verification items and verification requirements.

[0031] Process document sources include, but are not limited to, documents such as enterprise control plans and work instructions. These process document sources can be used to extract process verification checklists and judgment criteria for different verification items. This process can be implemented using a large language model or other techniques known to those skilled in the art.

[0032] For example, for a specific verification project, should the corresponding data be used directly or processed in some way? Based on data processing rules, a process verification checklist is obtained. For instance, image data may be used for image recognition to find the target and its location. Or, for a specific sensor parameter, the average value over a period of time may be calculated as the baseline value for subsequent verification. What are the judgment thresholds or criteria for the parameters? Judgment criteria are obtained based on the judgment sub-criteria of all verification sub-projects. Based on these judgment criteria and the process verification checklist, the verification requirements are determined. These judgment criteria and the process verification checklist are linked and stored to obtain the corresponding process verification standard knowledge base.

[0033] In related technologies, process verification projects are scattered in origin, some relying on control plans, work instructions, and other superior documents. However, when converting these into process verification forms, misunderstandings or manual input errors often lead to high error rates, hindering the effective implementation of standards. Process verification forms for each position are primarily compiled manually by team leaders and others, which is time-consuming and labor-intensive. Revising these forms is equally inconvenient when production processes or standards change, resulting in delayed updates and low efficiency. The solution described above, however, intelligently extracts verification items and judgment criteria from process document sources, reducing errors caused by manual input and making the process more convenient and efficient. When process document sources need to be changed, the process verification standard knowledge base can be updated specifically based on the changes, ensuring greater timeliness.

[0034] As an example, a structured process verification standard knowledge base can be built. Through data interfaces, it can be deeply integrated with enterprise control plan systems, work instruction systems, and other process document sources. Based on the user's selected workshop, work section, and position (verification items), the system can automatically match and generate a process verification list and judgment criteria specific to that position. Specifically, when a user selects a specific tool (such as a "servo gun"), the system can automatically extract its torque standard value, verification frequency, and other parameters from the integrated control plan; when the "workwear" item is selected, the system automatically lists the mandatory protective equipment required for that position, thus achieving both unified standards at the source and differentiated generation of standards.

[0035] As an example, taking the verification project as a certain work method, the corresponding process verification checklist and judgment criteria can be: whether the documents are complete (whether there are similar part visual diagrams, safety operating procedures, on-site 5S standards, scratch and impact operation procedures, SOS (Standardized Operation Sheet) / JES (Job Element Sheet)), and according to the LianShan platform (or other platforms, this is just an example, the same applies below, and will not be elaborated on) similar part ledger, to determine whether the corresponding position has similar part visual diagrams; for example, whether SOS / JES is the latest controlled version, obtain the release time of the latest release record of a certain position according to the LianShan platform document release process; for example, whether the first piece confirmation key follows the work points (whether the left hand holds the gun tail and the right hand holds the gun head back to prevent the coil from getting caught), according to the work points corresponding to the element steps marked with cross, CC, and SC in the work instructions of that position on the LianShan platform.

[0036] As an example, taking the verification project as a "ring", the corresponding process verification checklist and judgment criteria can be: The Lianshan platform formulates corresponding on-site 5S standards (including pictures and standard descriptions) according to the job position, and obtains the corresponding inspection standards and standard pictures in the on-site 5S standards for that job position according to the job position number.

[0037] As an example, taking the verification item "personnel wearing safety helmets" as an example, the corresponding process verification checklist and judgment criteria can be: taking a picture of the person's head, performing image recognition, determining whether a safety helmet is being worn, whether the type of safety helmet is correct, whether the position of the safety helmet is correct, whether the way the safety helmet is worn is correct, etc.

[0038] As an example, taking the verification project as "servo gun verification", the corresponding process verification checklist and judgment criteria can be: obtain the torque of the servo gun, and determine whether the torque is within the preset standard torque range.

[0039] In one embodiment, the method further includes: if the process document source changes, triggering an update to the process validation standard knowledge base; determining the modification content based on the new process document source and the original process document source; updating the process validation standard knowledge base based on the modification content; wherein the update method includes: determining the modification action of the modification content, the modification action including adding, deleting, or modifying; determining the modification items and modification requirements based on the modification content, the modification requirements including modifying the validation checklist and / or modifying the standard; if the modification action is adding, adding the modification items and modification requirements to the process validation standard knowledge base; if the modification action is deleting, matching the modification items and / or modification requirements with validation items and validation requirements respectively, and deleting the matched validation items and validation requirements from the process validation standard knowledge base; if the modification action is modifying, matching the modification items with validation items and validation requirements, and replacing the validation requirements corresponding to the matched validation items with the modification requirements, so as to update the process validation standard knowledge base.

[0040] For newly added content, it might involve adding verification sub-projects and corresponding verification sub-requirements to a specific verification project, or it might involve creating a new verification project and its verification sub-requirements. In such cases, the modified projects and requirements determined by the modified content can be added to the process verification standard knowledge base. If a new verification project is added, it can be added entirely. If a new verification sub-project is added to a specific verification project D, then the verification sub-project and its verification sub-requirements can be added within the framework of verification project D.

[0041] Regarding deleted content, unlike the previously added content, it might involve deleting some verification sub-items and their corresponding verification sub-requirements from a specific verification project, or it might involve deleting the verification project and its verification sub-requirements. In such cases, the modified projects and requirements identified by the modified content can be removed from the process verification standard knowledge base. If a verification project is being deleted, it can be deleted entirely. If a verification sub-item of a specific verification project D is being deleted, then the verification sub-item and its verification sub-requirements can be deleted within the framework of verification project D.

[0042] The modifications typically involve changing the judgment criteria for a specific verification item or a sub-item under a verification item. In this case, it is necessary to first locate the verification item or sub-item that needs to be modified from the process verification standard knowledge base, and then replace the corresponding verification requirements with the modification requirements.

[0043] As an example, when performing an update, the file system where the process file source is located can be monitored. When a change is detected in the process source file, the update of the process verification standard knowledge base is triggered.

[0044] As another example, when performing an update, after the process document source has been transformed by re-uploading or modification, the process verification standard knowledge base can be updated in response to the update instruction of the process verification standard knowledge base. For example, if the process document source has been transformed, a transformation prompt will be displayed and a knowledge base update request will be generated. If the user agrees to the knowledge base update request, the process verification standard knowledge base update will be triggered.

[0045] The specific execution process and the triggering method for updating the standard knowledge base can also be implemented in ways known to those skilled in the art, and will not be elaborated here.

[0046] Following the above embodiments, after updating the process verification standard knowledge base based on the modified content, the method further includes: determining the affected targets based on the modified content, generating a change notification based on the modified content, and notifying the users corresponding to the affected targets; and / or, displaying the updated process verification standard knowledge base, completing the update of the process verification standard knowledge base in response to the input change consent instruction, and further modifying the updated process verification standard knowledge base based on the instruction content of the change modification instruction if a change modification instruction is received.

[0047] The affected targets can be the equipment, personnel, methods, processes, etc., targeted by the modification. Each target (equipment, personnel, method, process, etc.) is pre-configured with corresponding users. Once the affected targets are identified, the relevant users can be found through pre-defined matching relationships, and then notified. These users can be directly affected individuals or related individuals. For example, regarding helmet-wearing rules, it's necessary to notify not only the person actually wearing the helmet but also their supervisor. This method ensures timely notification of relevant changes to relevant personnel, reducing the possibility of anomalies.

[0048] When updating the process verification standard knowledge base based on modified content, in order to ensure the accuracy of the update, the updated content of the process verification standard knowledge base can be manually verified. The changes to the process verification standard knowledge base can be approved based on the results of the manual verification, or the process verification standard knowledge base can be further adjusted.

[0049] Sometimes, modifications may lead to changes in verification requirements across multiple stages. In such cases, the updated process verification standard knowledge base can be presented to relevant personnel at each stage. The update is complete only if all personnel approve it. Otherwise, a change order is issued based on consensus, and further modifications are made.

[0050] By establishing a dynamic mapping between process validation items and source process documents, an automatic synchronization mechanism is triggered when the tools, parameters, or other content in the control plan or work instructions change. This mechanism updates and adjusts all relevant validation tables (process validation standard knowledge base) in real time and proactively notifies relevant personnel, ensuring that validation standards are strictly consistent with the latest process requirements and achieving "synchronization upon change."

[0051] Step S120: Verify the production process data to be verified based on the process verification standard knowledge base and the information of the project to be verified.

[0052] In one implementation, the production process data to be verified is verified based on the process verification standard knowledge base and the information of the project to be verified, including: matching the verification requirements in the process verification standard knowledge base according to the information of the project to be verified; verifying the production process data to be verified based on the verification requirements; if the production process data to be verified meets the verification requirements, the verification result is successful; if the production process data to be verified does not meet the verification requirements, the verification result is unsuccessful.

[0053] To determine whether the production process data to be verified meets the verification requirements, the data processing rules provided in the process verification checklist can be used to process the production process data to be verified, obtain the processed data, and then evaluate the processed data by various thresholds, conditions, and standards in the judgment criteria. The success is determined based on the comparison results with the thresholds, conditions, and standards.

[0054] As an example, this verification process can utilize artificial intelligence models such as computer vision to provide intelligent assistance and judgment in the verification process. For example: For personnel status analysis: Based on on-site images uploaded by employees, the system automatically analyzes whether their work protective clothing meets the standards and identifies any abnormal mental states.

[0055] For material and tooling identification: By taking pictures of the material area or tool area, the system automatically identifies the type of material, checks whether the quantity is complete, and detects whether there are obvious appearance defects.

[0056] For determining device operating status: This unit automatically analyzes whether the device is in a preset normal operating state by combining real-time data collected by the device's IoT sensors. This verification process is then implemented.

[0057] As can be seen, the solution provided in this application has been upgraded from the experience-based "human judgment" mode to the data- and algorithm-based "machine judgment" mode.

[0058] Step S130: If the verification result is abnormal, determine the cause of the abnormality, and then determine the object of abnormality handling and the abnormality handling rules.

[0059] In one embodiment, determining the cause of the anomaly, and then determining the object and rules for handling the anomaly, includes: recording production process data to be verified that does not meet the verification requirements as anomalous data; generating an anomaly cause based on the anomalous data, the verification requirements corresponding to the anomalous data, and the information of the item to be verified corresponding to the anomalous data; determining the rules for handling the anomaly based on the information of the item to be verified in the anomaly cause; and determining the object to be handled according to the information of the item to be verified in the anomaly cause and a preset mapping relationship between the preset mapping relationship between the verification item and the corresponding object to be handled.

[0060] The preset project object mapping relationship can be set by those skilled in the art as needed. Based on the granularity of the division, the preset project object mapping relationship can characterize the mapping relationship between verification projects and their corresponding exception handling objects. Sometimes a verification project may involve multiple exception handling objects; the exception handling object corresponding to each verification sub-project of the verification project can be set. If the data corresponding to any verification sub-project is abnormal, then the exception handling object corresponding to that verification sub-project will be designated as the exception handling object that needs to be notified.

[0061] Different exception handling rules can be set for different verification projects. Operators or equipment handling the exceptions can then use these rules to resolve the issues. For example, one set of exception handling rules can be set for a single verification project. If a verification project includes multiple sub-projects, exception handling rules can be set for each sub-project and for each combination of sub-projects. When an exception occurs in only some sub-projects, the appropriate exception handling rule can be determined based on the exception handling rules corresponding to the set of sub-projects experiencing the exception.

[0062] By systematically handling anomalies discovered during the verification process, a pre-defined anomaly classification rule base and personnel permission matrix are established. The personnel permission matrix includes a pre-defined mapping relationship between project objects, allowing the identification of verification projects and their corresponding anomaly handling targets. This personnel permission matrix can be adjusted according to actual needs. The anomaly classification rule base includes anomaly handling rules corresponding to different verification projects or sub-projects. When an anomaly occurs, the corresponding frontline manager (the corresponding anomaly handling target) is notified. Simultaneously, the system automatically matches the rules (finds the corresponding anomaly handling rule) and pushes the task to the responsible person's workbench based on the permission matrix, initiating a processing timer. This constructs a complete digital closed loop of "discovery-reporting-processing-feedback," ensuring timely and accurate handling of issues.

[0063] By employing the above methods, this approach establishes a closed loop for problem discovery and resolution. It goes beyond simply identifying anomalies; it also supports the automated matching of appropriate handling rules and the identification of suitable personnel, promptly informing them to take appropriate action.

[0064] Step S140: Send the cause of the abnormality and the rules for handling the abnormality to the object of the abnormality handling in order to manage the production process.

[0065] The targets of anomaly handling can be relevant personnel or devices with anomaly handling permissions, such as wearable glasses, smart bracelets, smartwatches, mobile phones, and large display screens. By distributing the cause of the anomaly and the anomaly handling rules to the relevant targets, the responsible party for resolving the anomaly can be identified in a timely manner, and corresponding guidance can be provided, further increasing the likelihood of successful handling of anomaly issues.

[0066] In one embodiment, after sending the exception handling rules to the exception reporting object, the method further includes: obtaining the exception handling feedback result from the exception reporting object, the exception handling feedback result including one or more of the exception resolution status, exception resolution process data, and outstanding exception issues; sending the exception handling feedback result to the target management object; receiving the task closure indication from the target management object; if the task closure indication is closed, ending the process; if the task closure indication is not closed, generating an exception task re-handling notification and sending it to the exception reporting object to notify the exception reporting object to further process the exception event.

[0067] Sometimes, the personnel or equipment currently handling an anomaly may not be able to resolve it. In this case, the anomaly status can be set to "unresolved," and the issue reported. After eliminating the factors that prevent resolving the anomaly with external assistance, an anomaly task re-handling notification is generated. The anomaly handler then uses this notification to re-handle the anomaly. For example, if an anomaly occurs due to unreasonable standards, and the execution end cannot resolve the issue, this feedback loop allows for standard modification. After modification, an anomaly task re-handling notification is generated, and further handling of the anomaly event follows.

[0068] Whether the handling of an anomaly was appropriate and whether the anomaly was truly eliminated cannot be determined solely by the reported anomaly resolution status. It is also necessary to combine the data from the anomaly resolution process, such as sensor data and image data before and after rectification, to judge whether the anomaly has been truly handled.

[0069] Sometimes, only part of an anomaly can be resolved, leaving some unresolved issues. In such cases, these unresolved issues can be reported and addressed by the next person in the chain of command (the person who reported the anomaly). For example, if an anomaly is caused by an employee's lack of understanding of relevant operating procedures, the relevant personnel with training and guidance functions can be notified as the reporting party to further handle the anomaly.

[0070] By employing the above methods, we can minimize the risk of omissions, errors, or even falsification of records to pass inspections due to process verification personnel's lack of understanding of the specific standards or methods for each inspection item. This can significantly reduce the effectiveness of process verification. Automating verification through a process verification standard knowledge base can improve the accuracy of verification and avoid the problems associated with cumbersome paper-based recording methods, which require employees to use numerous forms, are inconvenient to fill out, and make subsequent data processing and analysis difficult, thus reducing employee willingness to perform. By providing corresponding exception handling rules and electronic feedback channels through automation, the difficulty of execution is reduced, making it easier for relevant personnel to implement the process.

[0071] By employing the above methods, in addition to notifying relevant personnel to resolve abnormal events, a closed-loop feedback process is added, further ensuring the effective resolution of identified anomalies. When an anomaly cannot be directly resolved, the resolution level can be escalated, and the issue promptly reassigned to personnel capable of handling it, thus forming a closed-loop process verification after the alert is issued.

[0072] The production process management method provided in the above embodiments acquires a process verification standard knowledge base, information on the project to be verified, and production process data to be verified. This process verification standard knowledge base is generated based on the process document source; if the process document source changes, the process verification standard knowledge base is updated based on the changed process document source. The method verifies the production process data to be verified based on the process verification standard knowledge base and the information on the project to be verified. If the verification result is abnormal, the cause of the abnormality is determined, and then the abnormality handling object and abnormality handling rules are determined. The cause of the abnormality and the abnormality handling rules are sent to the abnormality handling object to manage the production process. By dynamically linking the process verification standard knowledge base with the process document source and updating the process verification standard knowledge base in a timely manner, this production process management method can better adapt to complex and ever-changing production scenarios, improve the efficiency and accuracy of the verification process, and enhance the real-time performance of the verification.

[0073] Please see Figure 2 , Figure 2 A specific flowchart illustrating the construction of a process verification standard knowledge base is provided for one embodiment of this application, as shown below. Figure 2As shown, the method includes the following steps: Constructing a configurable rule engine. This engine defines the organizational hierarchy of "workshop-section-position" and the association logic (personnel permission matrix) between various process parameters (such as tool type and labor protection requirements). A modular design is adopted to bind verification items (such as "servo gun verification") to source data (such as the "torque" field in the control plan). When a user selects a specific position (the project information to be verified) on the front end, the rule engine is triggered, automatically querying all verified process modules associated with that position and extracting specific values ​​(the production process data to be verified) from the bound source data. These values ​​are then dynamically assembled into a complete personalized verification list in the background and pushed to the user's terminal. An example workflow is as follows: Collect the core attributes of the verification object (factory, workshop, section, position) as the basic data input for subsequent processes; based on the input information, identify and obtain verification items from process document sources such as control plans and work instructions, such as the use of a tightening gun in the rear suspension tightening station operation; through a modular standard library (obtained based on pre-set judgment criteria corresponding to different verification items), the verification items are automatically matched with the verification standard module to obtain the judgment criteria corresponding to the verification items; according to the man (worker), machine (equipment, tools, fixtures, containers), material (parts, auxiliary materials), and method (work method, operation)... The document (work environment, 5S (Seiri, Seiton, Seiso, Seiketsu, and Shitsuke)) generates verification items and standards for each module, resulting in a process verification list and judgment criteria for each verification item. Verification standards are then generated and output. Based on the input information, the generated process verification form is passed to the management personnel for approval and release. During the approval and release process, the process verification form (the process verification standard knowledge base is generated based on the process verification form) can be corrected through manual supplementation or other methods.

[0074] Please see Figure 3 , Figure 3 A specific flowchart illustrating the automatic updating and adjustment of process verification standards is provided for one embodiment of this application, as shown below. Figure 3 As shown, by establishing a perception network, changes or points of change in platforms such as Lianshan Zero Code and QMS are monitored, change detection and capture are performed, and dynamic correlation adjustments are made upon detecting changes. All correlation verification tables are incrementally updated to achieve efficient and accurate synchronization, triggering synchronization and notifications. The specific process is as follows: 1) Monitor changes in work instructions and control plans; establish a change sensing network to automatically capture all signals within the system that may trigger changes; 2) Upon detecting a change signal, quickly pinpoint the specific content and scope of the change to complete "change capture." Compare the data / configuration before and after the change (e.g., differences in database table structure, configuration file content, and process steps) to extract change details and obtain the modified content.

[0075] 3) Automatic mapping: Automatic adjustment of associated modules is triggered by preset "change-related adjustment" rules (such as adding a database field → automatically synchronizing to the report template, deleting a process step → automatically updating the approval path).

[0076] Manual intervention: For complex / critical changes, based on the impact analysis of the change, the administrator manually confirms the adjustment plan (such as major architectural changes that require approval from multiple departments). 4) Synchronization mechanism: Data synchronization: Push the changed data / configuration to the target system (e.g., synchronize database changes to the production environment, synchronize process changes to the execution end).

[0077] As an example, the notification mechanism includes, but is not limited to: Stakeholder coverage: Automatically push notifications to administrators, business owners, affected users, and other roles based on the scope of the change's impact.

[0078] As an example, notification formats include, but are not limited to: supporting multiple channels such as email, system pop-ups, and push notifications to ensure efficient information delivery.

[0079] Please see Figure 4 , Figure 4 A specific flowchart illustrating an anomaly closed-loop management and intelligent dispatching method according to an embodiment of this application is shown below. Figure 4 As shown, the implementation of closed-loop management and intelligent dispatch of anomalies is as follows: 1) Anomaly Detection and Reporting: During the verification process, the system monitors and records various data and indicators in real time. Once a situation is found that does not conform to the preset standards, it is judged as an anomaly. The cause of the anomaly is obtained based on the time, location, and specific manifestation of the anomaly.

[0080] 2) Abnormal information reception and preliminary processing: perform preliminary sorting and verification of information to ensure its completeness and accuracy. For example, the verification of the cause of the abnormality can be carried out by checking the obtained data through a preset data template. If there is missing data, it indicates poor completeness. If the source of the data is suspicious, or if the obtained data is found to actually meet the corresponding preset standards through secondary verification, it indicates poor accuracy.

[0081] 3) Pre-set a rule base to classify anomalies, match the sorted anomaly information with the conditions in the rule base, and determine the type of anomaly, such as personnel or equipment.

[0082] 4) Task Generation: Based on the anomaly classification results, the system automatically generates corresponding processing tasks. Task content includes a detailed description of the anomaly, processing objectives, and processing requirements. If an anomaly occurs due to a lack of standards, new standards need to be developed; if employees do not understand the anomaly, management needs to provide training and guidance; if the standards are unreasonable or insufficient, management needs to revise them. As an example, the determination of anomaly handling rules can be further selected based on the anomaly type. When formulating anomaly handling rules, corresponding rules are set for different anomaly types.

[0083] 5) Assign tasks to execution units. Based on preset assignment rules, the generated tasks are intelligently assigned to execution units. The system sends the tasks to the execution units, including the specific content of the tasks, the required completion time, and other information. As an example, the execution unit may be an exception handling object, and the task is generated based on exception handling rules.

[0084] 6) The execution unit handles exceptions and feedback. After receiving the task notification, the execution unit handles the exception according to the task requirements and provides feedback on the exception handling results (including whether the exception has been resolved (exception resolution status), the resolution method (exception resolution process data), and any remaining issues (exception legacy issues), etc.), and generates records on the no-code platform.

[0085] 7) Closed-loop processing of results: The processing results are transmitted to frontline managers (target management objects) to review and confirm whether the task has been closed-loop. If not, feedback is given to the responsible person (the object of the anomaly report) for further processing. For example, when a material shortage is identified, the corresponding material delivery personnel (the object of the anomaly report) are notified to deliver the required materials in a timely manner.

[0086] By digitizing process verification standards, automating process development, intelligentizing execution judgments, and establishing a closed-loop anomaly management system, a collaborative and efficient intelligent process verification ecosystem has been built. This not only significantly improves the efficiency and accuracy of process verification but also, through data-driven approaches, enables proactive early warning and control of production risks, ultimately driving a fundamental shift in manufacturing from reactive response to proactive assurance.

[0087] In one embodiment, a production process management device is provided, which is used to execute the production process management method provided in any of the above embodiments. Please refer to... Figure 5 , Figure 5 A schematic diagram of a production process management device provided in an embodiment of this application is shown below. Figure 5As shown, the production process management device 500 includes: an acquisition module 510, used to acquire a process verification standard knowledge base, information on items to be verified, and production process data to be verified. The process verification standard knowledge base is generated based on the process document source. If the process document source changes, the process verification standard knowledge base is updated based on the changed process document source; a verification module 520, used to verify the production process data to be verified based on the process verification standard knowledge base and the information on items to be verified; a determination module 530, used to determine the cause of the abnormality if the verification result is abnormal, and then determine the abnormality handling object and the abnormality handling rules; and a management module 540, used to send the abnormality cause and abnormality handling rules to the abnormality handling object to manage the production process.

[0088] In some embodiments, the device further includes: a standard modular management unit, which is deeply integrated with process document sources such as enterprise control planning systems and work instruction systems through a data interface, and can automatically match and generate a process verification list and judgment criteria specific to the selected workshop, section, and position based on the multi-dimensional attributes (items to be verified); an intelligent linkage and synchronization unit, which establishes a dynamic association mapping between process verification items and source process documents based on the standard modular management unit; and an anomaly closed-loop management and intelligent assignment unit, which automatically classifies anomalies according to a preset rule base and intelligently assigns tasks to the corresponding responsible persons according to the permission matrix, thereby constructing a complete digital closed loop of "discovery-reporting-processing-feedback" to ensure that problems are handled in a timely and accurate manner.

[0089] The digital process verification solution achieves standardization, automation, and intelligence in process verification work through a standardized modular management unit, intelligent linkage and synchronization unit, AI intelligent analysis and automated judgment unit (acquisition module, verification module, determination module) and anomaly closed-loop management and intelligent dispatch unit (management module).

[0090] Specific limitations regarding the production process management device can be found in the limitations of the production process management method described above, and will not be repeated here. Each module in the aforementioned production process management device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in the electronic device in hardware form, or stored in the memory of the electronic device in software form, so that the processor can call and execute the corresponding operations of each module.

[0091] In this embodiment, the production process management device is essentially equipped with multiple modules to execute the production process management method in any of the above embodiments. The specific functions and technical effects can be referred to in the above embodiments, and will not be repeated here.

[0092] See Figure 6 , Figure 6A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown below. Figure 6 As shown, this embodiment of the invention also provides an electronic device 600, including a processor 601, a memory 602, and a communication bus 603; the communication bus 603 is used to connect the processor 601 and the memory 602; the processor 601 is used to execute a computer program stored in the memory 602 to implement the method described in any of the above embodiments.

[0093] This invention also provides a computer-readable storage medium having a computer program stored thereon, the computer program being used to cause a computer to perform the method provided in any of the above embodiments.

[0094] This application also provides a non-volatile readable storage medium storing one or more modules (programs) that, when applied to a device, enable the device to execute the instructions included in the steps provided in this application.

[0095] This application also provides a computer program product, including a computer program that, when executed by a processor, can implement the steps and corresponding content of the aforementioned method embodiments.

[0096] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0097] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0098] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0099] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0100] It should be understood that the terms "first," "second," etc., used in this application are used to distinguish similar objects and do not necessarily indicate a specific order or sequence. The technical features to which these terms are used can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in a sequence other than that shown in the figures or text.

[0101] It should be understood that although the flowcharts provided in the embodiments of this application indicate the various steps with arrows, the order indicated by the arrows does not necessarily limit the implementation order of these steps. Those skilled in the art can perform these steps in other orders according to different implementation scenarios and requirements.

[0102] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A production process management method characterized by, The method includes: The process validation standard knowledge base, the project information to be validated, and the production process data to be validated are acquired. The process validation standard knowledge base is generated based on the process document source. If the process document source changes, the process validation standard knowledge base is updated based on the changed process document source. The production process data to be verified is verified based on the process verification standard knowledge base and the information of the project to be verified. If the verification result is abnormal, determine the cause of the abnormality, and then determine the object of abnormality handling and the abnormality handling rules; The cause of the anomaly and the rules for handling the anomaly are sent to the anomaly handling object to manage the production process.

2. The production process management method according to Claim 1, wherein The verification of the production process data to be verified is performed based on the process verification standard knowledge base and the information of the project to be verified, including: Match the verification requirements in the process verification standard knowledge base according to the information of the project to be verified; The production process data to be verified is verified based on the verification requirements; If the production process data to be verified meets the verification requirements, the verification result is successful. If the production process data to be verified does not meet the verification requirements, the verification result is a failure.

3. The production process management method according to Claim 1, wherein Determine the cause of the anomaly, and then determine the objects and rules for handling the anomaly, including: Production process data that does not meet the verification requirements will be recorded as abnormal data. An anomaly cause is generated based on the abnormal data, the verification requirements corresponding to the abnormal data, and the information of the project to be verified corresponding to the abnormal data. The rules for handling anomalies are determined based on the information of the unverified items in the aforementioned causes of anomalies. The exception handling object is determined based on the information of the project to be verified in the exception cause and the preset project object mapping relationship, wherein the preset project object mapping relationship represents the mapping relationship between the verification project and the corresponding exception handling object.

4. The production process management method according to Claim 1, wherein The generation methods of the process verification standard knowledge base include: Obtain the source of the process documents; Based on the aforementioned process document source, multiple verification items are determined, as well as a process verification checklist and judgment criteria corresponding to each verification item; Verification requirements are generated based on the process verification checklist and judgment criteria. The process verification checklist includes one or more verification sub-items, and the judgment criteria are generated based on the judgment criteria of all verification sub-items. The process verification standard knowledge base is generated based on all the verification items and verification requirements, as well as the matching relationships between the verification items and verification requirements.

5. The production process management method according to Claim 4, characterized by, The method further includes: If the source of the process documents changes, an update to the process verification standard knowledge base is triggered. The modifications are determined based on the new and existing process document sources; The process verification standard knowledge base will be updated based on the aforementioned modifications. The update methods include: Determine the modification action for the modified content, wherein the modification action includes adding, deleting, or altering; Based on the aforementioned modifications, the modification items and requirements are determined, including modifications to the verification checklist and / or modifications to the standards. If the modification is a new addition, the modification item and modification requirements will be added to the process verification standard knowledge base; If the modification action is deletion, the modified item and / or modification requirement are matched with the verification item and verification requirement respectively, and the matched verification item and verification requirement are deleted from the process verification standard knowledge base; If the modification action is a change, the modified item is matched with the verification item and verification requirements, and the verification requirements corresponding to the matched verification item are replaced with the modified requirements to update the process verification standard knowledge base.

6. The production process management method according to Claim 5, wherein After updating the process verification standard knowledge base based on the aforementioned modifications, the method further includes: Based on the modifications, the affected targets are identified, a change notification is generated based on the modifications, and the users corresponding to the affected targets are notified. And / or, The updated process verification standard knowledge base is displayed. In response to the input change consent instruction, the process verification standard knowledge base is updated. If a change modification instruction is received, the updated process verification standard knowledge base is further modified based on the instructions of the change modification instruction.

7. The production process management method according to any one of claims 1-6, characterized in that, After sending the exception handling rules to the exception reporting object, the method further includes: Obtain the anomaly handling feedback result of the anomaly report object, wherein the anomaly handling feedback result includes one or more of the following: anomaly resolution status, anomaly resolution process data, and anomaly legacy issues; The abnormality handling feedback results are sent to the target management object; Receive the task closed-loop instruction from the target management object; If the task loop indication is closed, the process ends; If the task closure indication is not closed, an abnormal task reprocessing notification is generated and sent to the abnormal reporting object to notify the abnormal reporting object to further process the abnormal event.

8. A production process management device, characterized in that, The device includes: The acquisition module is used to acquire the process verification standard knowledge base, the project information to be verified, and the production process data to be verified. The process verification standard knowledge base is generated based on the process document source. If the process document source changes, the process verification standard knowledge base is updated based on the changed process document source. The verification module is used to verify the production process data to be verified based on the process verification standard knowledge base and the information of the project to be verified. The determination module is used to determine the cause of the exception if the verification result is abnormal, and then determine the object of exception handling and the exception handling rules. The management module is used to send the cause of the anomaly and the rules for handling the anomaly to the anomaly handling object in order to manage the production process.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 7.

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