Intelligent chemical single-process optimization design method and system based on dynamic decision

Abstract

The invention relates to the technical field of communication, in particular to an intelligent chemical single-process optimization design method and system based on dynamic decision, work order state change is carried out through a process engine according to a rule result, and when a rule engine returns a single node, a state field of a current work order record is updated as a target node name; the method has the beneficial effects that the flexibility and the automation degree of the process are improved, automatic adjustment of the process path is realized through a dynamic decision mechanism, manual intervention is reduced, and the processing efficiency is improved; multi-system integration and cooperative processing are supported, and seamless connection with a third-party system is realized due to an open interface and an integration capability, so that the cooperative efficiency of a business process is improved; the mobile terminal is adapted, so that the service linkage efficiency is improved; the process is imported and exported in a one-button mode, the traceability and stability of process configuration are ensured through a process management and version control mechanism, and maintenance and optimization of the process are facilitated.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication, in particular to an intelligent work order process optimization design method and system based on dynamic decision. BACKGROUND

[0002] With the rapid development of 5G network and mobile Internet, mobile network business is becoming increasingly complex, and users' requirements for network service quality are continuously improving. The traditional work order system of the operator industry often has the following problems:

[0003] 1. Strong binding with the customer relationship management system, and the system module coupling degree is very high;

[0004] 2. Poor process flexibility, fixed process path is difficult to adapt to changing business needs and complex processing scenarios, resulting in rigid process and inability to flexibly respond to actual situations;

[0005] 3. Weak exception handling capability, lacking automatic mechanism for handling abnormal situations, which can easily lead to work order backlog, processing delay and other problems;

[0006] 4. Poor system scalability, process configuration is scattered, maintenance is complex, and it is difficult to quickly adapt to new business strategies and process changes.

[0007] Most of the existing work order process systems use static configuration process chart method, and the transfer path between nodes is based on pre-set conditions. It cannot flexibly respond to different business scenarios and processing states, and manual judgment and intervention is more, which is low in efficiency and prone to misrouting problems. Therefore, an intelligent control mechanism is urgently needed to dynamically decide the transfer path according to business attributes, historical trajectory, system strategy, etc., in order to improve the overall operation efficiency. SUMMARY

[0008] The purpose of the present application is to provide an intelligent work order process optimization design method and system based on dynamic decision, to solve the problems raised in the background.

[0009] To achieve the above purpose, the present application provides the following technical scheme: an intelligent work order process optimization design method based on dynamic decision, which updates the state field of the current work order record to the target node name by the process engine according to the rule result, inserts the process transfer log record time, transfer source and target, and execution rule information, and automatically triggers the processing logic of the target node when the rule engine returns a single node; when multiple paths are returned by the rule, a subtask or a sub-process instance is created for the main process, an independent subtask object or a sub-process instance is generated for each target path, each subtask has independent state control and processing record, supports timeout and failure fallback strategy, and the main process can be configured with maximum waiting time or interruption strategy.

[0010] Preferably, it includes automated handling of process exceptions: based on preset exception recognition and handling rules, it automatically identifies and responds to abnormal events in the work order processing process; supports monitoring of various abnormal situations such as work order processing timeout, process stagnation, link jump failure, rule matching errors, and interface call exceptions; preset multi-dimensional exception handling rules, dynamically match corresponding processing solutions according to exception type, business type and priority factors, such as automatic retry, exception alarm, forced process jump, manual processing, and business recovery; at the same time, it supports users to customize exception handling strategies through the configuration center to improve the flexibility and customization capabilities of the system exception handling, and work in conjunction with the automatic flow mechanism to ensure the continuity and stability of the work order processing process.

[0011] Preferably, an asynchronous event-driven architecture is adopted: it is implemented based on message middleware technology and uses Kafka as a message queue to achieve asynchronous decoupling of work order status change events and subsequent business processing; during the work order life cycle, changes in the status of the work order and its links trigger corresponding event messages and are published to the Kafka message channel; business modules that subscribe to the channel consume events asynchronously on demand to achieve real-time notification, data synchronization or business linkage operations, reduce the coupling between systems, and improve processing throughput and system scalability.

[0012] Preferably, a mobile module is provided: supporting access to the work order system through mobile applications on smart phones and tablet mobile devices, realizing the creation, receipt, processing, signing, feedback, and photo upload of work orders; integrating encrypted communication mechanism and message push mechanism to ensure the security and real-time nature of data communication, supporting instant reminders of important work orders and real-time synchronization of processing status; the system interface supports offline caching and breakpoint resumption, which is suitable for work order processing scenarios outdoors or in unstable signal environments, so as to improve users' real-time processing capabilities and on-site response efficiency.

[0013] Preferably, it has multi-system integration, open interfaces, and process management, among which: multi-system integration and open interfaces support integration with multiple heterogeneous systems, are compatible with multiple communication protocols, and provide standardized RESTful API interfaces. Third-party systems can use the interfaces to create work orders, query status, advance processes, and synchronize processing results. It supports token-based authentication to ensure data transmission security, and implements business-triggered callback notifications through the interface event subscription mechanism, pushing work order status change events to third-party systems, thereby achieving process collaboration and data closed-loop among multiple systems.

[0014] The process management module collects full-quantity configuration information of a specified work order process and encapsulates the information into a standard format, including third-party integration configuration, supervision notification configuration, link node configuration, and process form configuration. Before import, structural integrity and field legality are checked. The import process is transactional, and if any module fails to parse, the whole process is rolled back. A snapshot record is automatically created for each import, with version number and import time marked. Historical version comparison, preview, and rollback are supported. The work order process "what you see is what you get" full-quantity configuration migration is realized, reducing human configuration errors, reducing the deployment cost of process switching and business iteration, and improving process template reuse rate and version controllability.

[0015] A system for intelligent work order process optimization design based on dynamic decision, comprising a process engine, through which work order state changes are made according to rule results, when the rule engine returns a single node, the state field of the current work order record is updated to the target node name, the process flow log record time, the flow transfer source and target, and the execution rule information are inserted, and the processing logic of the target node is automatically triggered; when the rule returns multiple paths, a main process creates a subtask or a sub-process instance, and an independent subtask object or a sub-process instance is generated for each target path, each subtask has independent state control and processing record, supports timeout and failure fallback strategy, and the main process can be configured with maximum waiting time or interruption strategy.

[0016] Preferably, the system comprises a process exception automatic processing module, which: based on pre-set exception recognition and processing rules, automatically recognizes and responds to abnormal events in the work order processing process; supports monitoring of work order processing timeout, process stagnation, link jump failure, rule matching error, and interface call exception; pre-sets multi-dimensional exception processing rules, dynamically matches the corresponding processing scheme according to the exception type, business type, and priority factors, such as automatic retry, exception alarm, process forced jump, manual processing, and business recovery; at the same time, users can customize exception processing strategies through the configuration center to improve the flexibility and customization ability of system exception processing, and work with the automatic flow transfer mechanism to ensure the continuity and stability of the work order processing process.

[0017] Preferably, an asynchronous event-driven architecture is used, which: is realized based on message middleware technology, uses Kafka as a message queue to realize asynchronous decoupling of work order state change events and subsequent business processing; in the work order life cycle, the work order and its link state change trigger corresponding event messages and publish them to the Kafka message channel; business modules subscribed to the channel asynchronously consume events as needed, realize real-time notification, data synchronization or business linkage operation, reduce the coupling degree between systems, and improve processing throughput and system scalability.

[0018] Preferably, a mobile module is provided, which supports access to the work order system through a mobile application on a smart phone or tablet mobile device, realizes creation, receiving, processing, signing, feedback and photograph uploading of the work order, integrates an encryption communication mechanism and a message pushing mechanism to ensure safety and real-time performance of data communication, supports instant reminding of important work orders and real-time synchronization of processing status, and supports offline caching and breakpoint resume of the system interface to adapt to work order processing scenarios in outdoor or unstable signal environments, thereby improving real-time processing capability and on-site response efficiency of users.

[0019] Preferably, a multi-system integration and interface opening module and a process management module are provided, wherein the multi-system integration and interface opening module supports integration with multiple heterogeneous systems, is compatible with multiple communication protocols, provides a standardized RESTful API interface, and supports creation, state query, process promotion, processing result synchronization operations of the work order through calling of the interface by a third-party system, supports a Token-based authentication mode to ensure data transmission safety, and realizes business trigger callback notification through an interface event subscription mechanism to push work order state change events to the third-party system, thereby realizing process collaboration and data closed loop among multiple systems.

[0020] The process management module collects full configuration information of a specified work order process and encapsulates the full configuration information into a standard format, including third-party integration configuration, supervision notification configuration, link node configuration and process form configuration, performs structure integrity and field legality verification before import, has transactionality in the import process, and if any module fails to be parsed, the whole is rolled back, a snapshot record is automatically created for each import, a version number and an import time are marked, historical version comparison, preview and rollback are supported, full configuration migration of the work order process is realized, human configuration errors are reduced, deployment cost of process switching and business iteration is reduced, and process template reuse rate and version controllability are improved.

[0021] Compared with the prior art, the present application has the following beneficial effects:

[0022] The intelligent work order process optimization design method and system based on dynamic decision proposed in the present application improve flexibility and automation degree of the process, realize automatic adjustment of the process path through a dynamic decision mechanism, reduce manual intervention and improve processing efficiency, support multi-system integration and collaborative processing, open interfaces and integration capabilities, realize seamless connection with third-party systems, improve collaborative efficiency of business processes, adapt to mobile terminals, improve business linkage efficiency, realize one-key import and export of the process through a process management and version control mechanism, ensure traceability and stability of the process configuration, and facilitate maintenance and optimization of the process. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 The present application is a method flowchart. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solutions of the present application, and the advantages are more clear and obvious, the following will be further described in detail with the embodiments of the present application. It should be understood that the specific embodiments described herein are part of the embodiments of the present application, not all embodiments, and are only used to explain the embodiments of the present application, and do not limit the embodiments of the present application. All other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0025] Embodiment one, please refer to Figure 1 The present application provides a technical solution: an intelligent work order process optimization design method based on dynamic decision, comprising the following steps:

[0026] I. Work order context information collection and modeling

[0027] The system automatically collects and records the context information of the work order during the creation and processing of the work order. The information includes but is not limited to:

[0028] Customer attributes: customer level (such as VIP, ordinary), user group, etc.

[0029] Business content: work order type (such as fault, opening, inspection), business line (such as fixed network, mobile network), problem classification, etc.

[0030] Processing characteristics: current processor, work order creation time, processing duration, historical operation track (whether it has been returned, forwarded, etc.);

[0031] External interface data: integrated interface call state and return value, work order associated alarm level, etc.

[0032] After the information is structured, it is injected into the work order processing context object for the rule engine. The rule engine needs to make judgments based on various real-time information of the current work order. Therefore, the work order and its associated data are encapsulated into a context object, which is dynamically injected into the rule execution environment during process flow determination, improving the rule expression ability and system extensibility.

[0033] II. Rule definition and configuration

[0034] The system provides a process node rule configuration interface, which can visually configure the flow branch of each node and its corresponding decision rule. The rule supports script language or DSL form writing, and calls the fields in the context for judgment. Each branch path can be configured with priority, and an explicit bottom path definition is supported to ensure that all processes have a walkable path.

[0035] III. The process engine calls the rule engine for decision calculation

[0036] When a process reaches a certain point, the process engine passes all branch rules and contextual data for that point to the rule engine. Based on the actual data, the rule engine calculates a path that satisfies the conditions and returns the optimal path or multiple concurrent paths. If no rule matches, a fallback path is used. If all path conditions are not met, a fallback strategy is automatically triggered (such as entering the "pending manual confirmation" node, taking the default path, or suspending the process), avoiding process stalls or interruptions.

[0037] 4. Process state changes and asynchronous event dispatching

[0038] The process engine changes the state according to the rule results: updates the work order status to a new node and creates multiple subtasks or sub-processes concurrently in multi-path scenarios: In the case of normal flow, when the rule engine returns a single node: the system updates the status field of the current work order record to the target node name and inserts it into the process flow log, records the time, flow source and target, execution rules, etc., and automatically triggers the processing logic of the target node (such as assigning tasks, notifying processors, etc.). In multi-path scenarios, when the rules return multiple paths, the main process will create subtasks or sub-process instances and automatically generate an independent subtask object or sub-process instance for each target path. Each subtask has independent state control and processing records, supports timeout and failure recovery strategies, and the main process can be configured with a maximum waiting time or interruption strategy.

[0039] The process exception automation processing module realizes automatic identification and response to abnormal events in the work order processing process based on preset exception identification and processing rules. This module supports monitoring of various abnormal situations, including but not limited to work order processing timeouts, process stagnation, link jump failures, rule matching errors, interface call exceptions, etc. The system presets multi-dimensional exception handling rules, which can dynamically match corresponding processing solutions based on factors such as exception type, business type, priority, etc., such as automatic retry, exception alarm, forced process jump, manual processing, business recovery, etc. Users can also customize exception handling strategies through the configuration center to enhance the flexibility and customization capabilities of the system's exception handling. This module works in conjunction with the automatic flow mechanism to effectively ensure the continuity and stability of the work order processing process, and improve the robustness and intelligence of the overall business system.

[0040] An asynchronous event-driven architecture is used to improve the responsiveness and module decoupling of the work order system. This architecture is based on message middleware technology and uses Kafka as a message queue to achieve asynchronous decoupling of work order status change events and subsequent business processing. During the work order lifecycle, changes in the status of the work order and its links (such as creation, update, end, etc.) will trigger corresponding event messages and publish them to the Kafka message channel. Business modules that subscribe to this channel (such as notification services and work order business processing modules) can consume events asynchronously on demand, thereby achieving real-time notifications, data synchronization, or business linkage operations. Through this event-driven mechanism, there is no need for synchronous calls between modules within the work order system, which greatly reduces the coupling between systems while improving processing throughput and system scalability.

[0041] The mobile module is used to enable access to and operation of the work order system on mobile terminal devices, improving users' real-time processing capabilities and on-site response efficiency. This module supports access to the work order system through mobile applications on mobile devices such as smartphones and tablets, enabling operations such as work order creation, receipt, processing, signing, feedback, and photo upload. To ensure the security and real-time nature of data communication, the module integrates an encrypted communication mechanism and a message push mechanism, supporting instant reminders of important work orders and real-time synchronization of processing status. The system interface supports offline caching and breakpoint resumption, and is suitable for work order processing scenarios outdoors or in unstable signal environments. Through this module, operator engineers can achieve efficient response and closed-loop processing of work orders anytime and anywhere, further improving the processing efficiency and flexibility of the overall business.

[0042] The multi-system integration and interface opening module is designed to achieve efficient linkage and information synchronization between the work order system and other communication business support systems. This module supports integration with a variety of heterogeneous systems, including but not limited to customer relationship management systems, network management platforms, billing systems, etc., and is compatible with a variety of communication protocols, such as RESTful, Web Service, etc. The system provides a standardized RESTful API interface, and third-party systems can implement operations such as work order creation, status query, process advancement, and processing result synchronization by calling the interface. Token-based authentication methods are supported to ensure data transmission security. Through the interface event subscription mechanism, business trigger callback notifications can also be implemented, and support is provided for pushing work order status change events to third-party systems, realizing process collaboration and data closed loops among multiple systems.

[0043] The process management module is used to implement cross-system migration and version management at the process level. The system collects the full configuration information of the specified work order process and encapsulates it into a standard format, including third-party integration configuration, supervision notification configuration, link node configuration, process form configuration, etc. The system performs structural integrity and field legitimacy verification before importing. The import process is transactional. If any module fails to parse, the entire system will be rolled back. The system automatically creates a snapshot record for each import, marks the version number and import time, and supports historical version comparison, preview, and rollback. Process import and export management realizes the "what you see is what you get" full configuration migration of the work order process, reduces human configuration errors, reduces the deployment cost of process switching and business iteration, and improves the reuse rate of process templates and version controllability.

[0044] Example 2, based on Example 1, proposes a system for an intelligent work order process optimization design method based on dynamic decision-making, including a process engine, which changes the work order status according to the rule results. When the rule engine returns a single node, the status field of the current work order record is updated to the target node name, and the process flow log record time, flow source and target, and execution rule information are inserted, and the processing logic of the target node is automatically triggered; when the rule returns multiple paths, the main process creates subtasks or subprocess instances, and generates independent subtask objects or subprocess instances for each target path. Each subtask has independent status control and processing records, supports timeout and failure protection strategies, and the main process can be configured with a maximum waiting time or interruption strategy.

[0045] It includes a process exception automation processing module, which: automatically identifies and responds to abnormal events in the work order processing process based on preset exception identification and processing rules; supports monitoring of various abnormal situations such as work order processing timeout, process stagnation, link jump failure, rule matching errors, and interface call exceptions; preset multi-dimensional exception handling rules, and dynamically matches corresponding processing solutions according to exception type, business type and priority factors, such as automatic retry, exception alarm, process forced jump, manual processing, and business recovery; at the same time, it supports users to customize exception handling strategies through the configuration center to improve the flexibility and customization capabilities of the system exception handling, and work together with the automatic flow mechanism to ensure the continuity and stability of the work order processing process.

[0046] An asynchronous event-driven architecture is adopted. This architecture is based on message-based middleware technology and uses Kafka as a message queue to achieve asynchronous decoupling of work order status change events and subsequent business processing. During the work order lifecycle, changes in the status of the work order and its links trigger corresponding event messages and publish them to the Kafka message channel. Business modules that subscribe to this channel consume events asynchronously on demand to achieve real-time notification, data synchronization, or business linkage operations, reduce the coupling between systems, and improve processing throughput and system scalability.

[0047] A mobile module is provided, which supports access to the work order system through a mobile application on a smart phone or tablet mobile device to realize creation, receiving, processing, signing, feedback, and photograph uploading of the work order; integrates an encryption communication mechanism and a message pushing mechanism to ensure safety and real-time performance of data communication, supports instant reminding of important work orders and real-time synchronization of processing status; the system interface supports offline caching and breakpoint resuming, which is suitable for work order processing scenarios in outdoor or unstable signal environments to improve real-time processing capability and on-site response efficiency of users.

[0048] The system has a multi-system integration and interface opening module and a process management module, wherein: the multi-system integration and interface opening module supports integration with multiple heterogeneous systems, is compatible with multiple communication protocols, provides a standardized RESTful API interface, and third-party systems can realize creation, state query, process promotion, processing result synchronization operations on work orders by calling the interface, supports Token-based authentication to ensure data transmission safety, and realizes business trigger callback notification through an interface event subscription mechanism to push work order state change events to third-party systems, and realizes process collaboration and data closed loop among multiple systems;

[0049] The process management module collects full configuration information of a specified work order process and encapsulates it into a standard format, including third-party integration configuration, supervision notification configuration, link node configuration, and process form configuration, performs structure integrity and field legality verification before import, and has transactionality in the import process, and if any module fails to parse, the whole is rolled back, a snapshot record is automatically created for each import, version number and import time are marked, historical version comparison, preview and rollback are supported, and the work order process "what you see is what you get" full configuration migration is realized, human configuration errors are reduced, deployment costs of process switching and business iteration are reduced, and process template reuse rate and version controllability are improved.

[0050] Although embodiments of the present application have been shown and described, it is to be understood that various modifications, substitutions, replacements and changes can be made to these embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. An intelligent work order process optimization design method based on dynamic decision-making, characterized by: The process engine changes the work order status according to the rule results. When the rule engine returns a single node, the status field of the current work order record is updated to the target node name, the process flow log record time, flow source and target, and execution rule information are inserted, and the processing logic of the target node is automatically triggered; when the rule returns multiple paths, the main process creates subtasks or sub-process instances, and generates independent subtask objects or sub-process instances for each target path. Each subtask has independent status control and processing records, supports timeout and failure protection strategies, and the main process can be configured with a maximum waiting time or interruption strategy.

2. The intelligent work order process optimization design method based on dynamic decision-making according to claim 1 is characterized by: Includes automated handling of process exceptions: Based on preset exception identification and handling rules, it automatically identifies and responds to abnormal events during the work order processing process; it supports monitoring of various abnormal situations such as work order processing timeouts, process stagnation, link jump failures, rule matching errors, and interface call anomalies; Multi-dimensional exception handling rules are preset to dynamically match corresponding processing solutions based on exception type, business type and priority factors, such as automatic retry, exception alarm, forced process jump, manual processing and business recovery; at the same time, users are supported to customize exception handling strategies through the configuration center to improve the flexibility and customization capabilities of system exception handling, and work together with the automatic flow mechanism to ensure the continuity and stability of the work order processing process.

3. The intelligent work order process optimization design method based on dynamic decision-making according to claim 2 is characterized by: Adopting an asynchronous event-driven architecture: Based on message middleware technology, using Kafka as a message queue, it realizes asynchronous decoupling of work order status change events and subsequent business processing; during the work order life cycle, changes in the status of the work order and its links trigger corresponding event messages and publish them to the Kafka message channel; business modules subscribed to this channel consume events asynchronously on demand to achieve real-time notification, data synchronization or business linkage operations, reduce the coupling between systems, and improve processing throughput and system scalability.

4. The intelligent work order process optimization design method based on dynamic decision-making according to claim 3 is characterized by: Set up a mobile module: support access to the work order system through mobile applications on smart phones and tablet mobile devices, and realize the creation, receipt, processing, signing, feedback, and photo upload of work orders; integrate encrypted communication mechanism and message push mechanism to ensure the security and real-time nature of data communication, support instant reminders of important work orders and real-time synchronization of processing status; the system interface supports offline caching and breakpoint resumption, which is suitable for work order processing scenarios outdoors or in unstable signal environments, so as to improve users' real-time processing capabilities and on-site response efficiency.

5. The intelligent work order process optimization design method based on dynamic decision-making according to claim 4 is characterized in that: It features multi-system integration, open interfaces, and process management. These features support integration with multiple heterogeneous systems, are compatible with multiple communication protocols, and provide a standardized RESTful API interface. Third-party systems can use the interface to create work orders, query status, advance processes, and synchronize processing results. It supports token-based authentication to ensure data transmission security, and implements business-triggered callback notifications through an interface event subscription mechanism. Work order status change events are pushed to third-party systems, enabling process collaboration and data closure among multiple systems. The process management module collects the full configuration information of the specified work order process and encapsulates it into a standard format, including third-party integration configuration, supervision notification configuration, link node configuration, and process form configuration. Structural integrity and field legitimacy verification are performed before importing. The import process is transactional. If any module fails to parse, the entire process is rolled back. A snapshot record is automatically created for each import, marking the version number and import time. Historical version comparison, preview, and rollback are supported, realizing the "what you see is what you get" full configuration migration of the work order process, reducing human configuration errors, lowering the deployment cost of process switching and business iteration, and improving the reuse rate of process templates and version controllability.

6. A system for the intelligent work order process optimization design method based on dynamic decision-making according to claim 5, characterized in that: It includes a process engine, which changes the work order status according to the rule results. When the rule engine returns a single node, it updates the status field of the current work order record to the target node name, inserts the process flow log record time, flow source and target, and execution rule information, and automatically triggers the processing logic of the target node; when the rule returns multiple paths, the main process creates subtasks or sub-process instances, and generates independent subtask objects or sub-process instances for each target path. Each subtask has independent status control and processing records, supports timeout and failure protection strategies, and the main process can be configured with a maximum waiting time or interruption strategy.

7. A system according to claim 6, characterized in that: It includes a process exception automatic processing module, which automatically identifies and responds to abnormal events during the work order processing based on preset exception identification and processing rules. It also supports monitoring of various abnormal situations such as work order processing timeouts, process stagnation, link jump failures, rule matching errors, and interface call anomalies. Multi-dimensional exception handling rules are preset to dynamically match corresponding processing solutions based on exception type, business type and priority factors, such as automatic retry, exception alarm, forced process jump, manual processing and business recovery; at the same time, users are supported to customize exception handling strategies through the configuration center to improve the flexibility and customization capabilities of system exception handling, and work together with the automatic flow mechanism to ensure the continuity and stability of the work order processing process.

8. A system according to claim 7, characterized in that: An asynchronous event-driven architecture is adopted. This architecture is based on message-based middleware technology and uses Kafka as a message queue to achieve asynchronous decoupling of work order status change events and subsequent business processing. During the work order lifecycle, changes in the status of the work order and its links trigger corresponding event messages and publish them to the Kafka message channel. Business modules that subscribe to this channel consume events asynchronously on demand to achieve real-time notification, data synchronization, or business linkage operations, reduce the coupling between systems, and improve processing throughput and system scalability.

9. A system according to claim 8, characterized in that: It is equipped with a mobile module, which: supports access to the work order system through mobile applications on smart phones and tablet mobile devices, and realizes the creation, reception, processing, signing, feedback, and photo upload of work orders; integrates encrypted communication mechanism and message push mechanism to ensure the security and real-time nature of data communication, and supports instant reminders of important work orders and real-time synchronization of processing status; the system interface supports offline caching and breakpoint resumption, which is suitable for work order processing scenarios outdoors or in unstable signal environments, so as to improve users' real-time processing capabilities and on-site response efficiency.

10. A system according to claim 9, characterized in that: It has a multi-system integration and interface opening module and a process management module. The multi-system integration and interface opening module supports integration with multiple heterogeneous systems, is compatible with multiple communication protocols, and provides a standardized RESTful API interface. Third-party systems can use the interface to create work orders, query status, advance processes, and synchronize processing results. It supports token-based authentication to ensure data transmission security, and implements business trigger callback notifications through the interface event subscription mechanism, pushing work order status change events to third-party systems, achieving process collaboration and data closed-loop among multiple systems. The process management module collects the full configuration information of the specified work order process and encapsulates it into a standard format, including third-party integration configuration, supervision notification configuration, link node configuration, and process form configuration. Structural integrity and field legitimacy verification are performed before importing. The import process is transactional. If any module fails to parse, the entire process is rolled back. A snapshot record is automatically created for each import, marking the version number and import time. Historical version comparison, preview, and rollback are supported, realizing the "what you see is what you get" full configuration migration of the work order process, reducing human configuration errors, lowering the deployment cost of process switching and business iteration, and improving the reuse rate of process templates and version controllability.

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