Engineering full life cycle management method and system

Abstract

This application provides a method and system for engineering full life cycle management. The method includes: in response to detecting a newly generated engineering project list, determining a target project to be controlled; based on a pre-configured agent, controlling each pre-deployed module to perform information control on the full life cycle of the target project; wherein, the life cycle includes an access stage, a statistics stage, an information dissemination stage, a project processing stage, a project update stage, a task assignment stage, a process monitoring stage, a personnel management stage, a weekly report processing stage, and an in-site message stage; wherein, each module includes a login module, a home page module, a message notification module, a project management module, a project progress overview module, a task management module, a process management module, a personnel management module, a weekly report management module, and an in-site message module; the login module is used to verify the identity information of the user and ensure that only authorized users can access the system.

Description

Technical Field

[0001] This application relates to the field of information management. Specifically, it relates to a method and system for the whole life cycle management of engineering projects. Background Art

[0002] Currently, traditional engineering project management often relies on manual operations and manual records, which are not only inefficient but also error-prone. With the development of information technology, especially the progress of cloud computing, big data, and artificial intelligence technologies, more and more enterprises have begun to seek to use these advanced technologies to improve the way of engineering project management.

[0003] In related technologies, products such as digital platforms, cloud platform applications, and intelligent management that can significantly reduce labor costs have gradually become the mainstream of information management. Among them, digital transformation converts traditional paper documents into electronic documents to achieve digital storage and management of information. Cloud platform applications use cloud computing technology to build a centralized project management platform to achieve resource sharing and service integration. Intelligent management introduces artificial intelligence technologies such as machine learning and natural language processing to achieve intelligent management and automated operations of projects. Although certain progress has been made in related technologies, there are still deficiencies, such as limited flexibility and adaptability, and poor user usability.

[0004] Therefore, this application provides a method and system for the whole life cycle management of engineering projects to solve one of the above technical problems. Summary of the Invention

[0005] The purpose of this application is to provide a method and system for the whole life cycle management of engineering projects, which can solve at least one of the above-mentioned technical problems. The specific solutions are as follows:

[0006] According to the specific embodiments of this application, in the first aspect, this application provides a method for the whole life cycle management of engineering projects, including:

[0007] In response to detecting a newly generated engineering project list, determine the target project to be controlled;

[0008] Based on a pre-configured agent, control each pre-deployed module to conduct information management and control over the entire life cycle of the target project; wherein, the life cycle includes an access stage, a statistics stage, an information dissemination stage, a project processing stage, a project update stage, a task assignment stage, a process monitoring stage, a personnel management stage, a weekly report processing stage, and an in-site message stage; wherein, each module includes a login module, a home page module, a message notification module, a project management module, a project progress overview module, a task management module, a process management module, a personnel management module, a weekly report management module, and an in-site message module; the login module is used to verify the identity information of the user and ensure that only authorized users can access the system; the home page module is used to analyze project data and generate statistical data and display it on the home page; the message notification module is used to automatically detect key nodes according to preset rules and notify relevant personnel in the form of in-site messages or text messages; the project management module is used to assist project leaders in creating, editing, starting, or archiving projects and provide intelligent suggestions according to the project status; the project progress overview module is used to update the project progress in real time and use algorithms to optimize the display method of the progress schedule; the task management module is used to automatically assign tasks according to the priority and deadline of the tasks and remind relevant personnel; the process management module is used to monitor the project process, automatically identify bottlenecks in the process, and trigger an automatic archiving process after the process is completed; the personnel management module is used to handle the addition, deletion, modification, and query of personnel information and ensure that the accounts comply with security regulations; the weekly report management module is used to collect and organize weekly report information and generate customized reports according to user needs; the in-site message module is used to automatically send in-site messages and track the reading status of the messages.

[0009] In one implementation, the agent includes a microservices architecture and an event-driven architecture. Each microservices sub-architecture in the microservices architecture is respectively used to control each module, and each event-driven sub-architecture in the event-driven architecture is respectively used to control each module; the agent selects each sub-architecture used to control each module based on a specified plan; wherein, the specified plan is one of multiple different optional plans, and the optional plans include selecting all the microservices sub-architectures, selecting all the event-driven sub-architectures, and selecting some of the microservices sub-architectures and some of the event-driven sub-architectures.

[0010] In one implementation, each of the microservice sub-architectures and each of the event-driven sub-architectures are pre-labeled with the driving computing power required by the driving sub-architecture, and the following method is used to determine the selected specified solution: real-time monitor the current available idle computing power; use the condition that only one sub-architecture for driving is selected for each module as the first screening condition, the condition that the total driving computing power required by the selected sub-architecture is less than or equal to the idle computing power as the second screening condition, and the condition that the total driving computing power required by the selected sub-architecture is closest to the idle computing power as the third screening condition to screen the alternative solutions to obtain the specified solution.

[0011] In one implementation, the screening of the alternative solutions to obtain the specified solution includes: in response to there being one alternative solution that meets all the screening conditions, taking the alternative solution that meets all the screening conditions as the specified solution; in response to there being at least two alternative solutions that meet all the screening conditions, based on the total entropy value gain of each of the at least two alternative solutions, taking the alternative solution with the highest total entropy value gain as the specified solution; where the total entropy value gain represents the sum of the entropy value gains generated by each sub-architecture in the alternative solution for driving the corresponding module, and the entropy value gain is used to characterize the driving effect of the sub-architecture in driving the module; where the entropy value gain generated by each sub-architecture in driving the corresponding module is calculated using the following formula: ; where P represents the completion rate of the sub-architecture in driving the module, c represents a fixed parameter used to adjust the curve radian represented by the formula so that the curve is applicable to each sub-architecture, N represents the complexity score of the sub-architecture, pre-labeled based on the scale and occupied character amount of the sub-architecture, and n represents the complexity score of the module, pre-labeled based on the complexity score of the functions executed by the module.

[0012] The intelligent body is externally connected to an artificial management interface. The intelligent body uses the TensorFlow machine learning framework and, based on the specified learning process that occurs on the artificial management interface, deduces the control methods for each of the modules; where the specified learning process includes the operation process manually performed on the artificial management interface according to the engineering control standard. The intelligent body is externally connected to a user feedback window. The intelligent body determines the description information input from the user feedback window based on semantic analysis and, based on the description information, adjusts the operation methods for some or all of the modules.

[0013] In one implementation, the intelligent body communicates with each module based on the Representational State Transfer Application Programming Interface (RESTful API) protocol to achieve control over each pre-deployed module.

[0014] According to the specific implementation of the present application, in the second aspect, the present application provides an engineering full-life cycle management system, including:

[0015] A project detection unit, configured to determine a target project to be controlled in response to detecting a newly generated engineering project list; an agent control unit, configured to control each pre-deployed module based on a pre-configured agent to perform information control over the entire life cycle of the target project; wherein, the life cycle includes but is not limited to an access stage, a statistics stage, an information dissemination stage, a project processing stage, a project update stage, a task assignment stage, a process monitoring stage, a personnel management stage, a weekly report processing stage, and an in-site message stage; wherein, each of the modules includes a login module, a home page module, a message notification module, a project management module, a project progress overview module, a task management module, a process management module, a personnel management module, a weekly report management module, and an in-site message module; the login module is configured to verify the identity information of a user and ensure that only authorized users can access the system; the home page module is configured to analyze project data and generate statistical data and display it on the home page; the message notification module is configured to automatically detect key nodes according to preset rules and notify relevant personnel in the form of in-site messages or text messages; the project management module is configured to assist a project leader in creating, editing, starting, or archiving a project and provide intelligent suggestions according to the project status; the project progress overview module is configured to update the project progress in real time and optimize the display mode of the progress schedule using an algorithm; the task management module is configured to automatically assign tasks according to the priority and deadline of the tasks and remind relevant personnel; the process management module is configured to monitor the project process, automatically identify bottlenecks in the process, and trigger an automatic archiving process after the process is completed; the personnel management module is configured to handle the addition, deletion, modification, and query of personnel information and ensure that the accounts comply with security regulations; the weekly report management module is configured to collect and organize weekly report information and generate customized reports according to user requirements; the in-site message module is configured to automatically send in-site messages and track the reading status of the messages.

[0016] In one implementation, the agent control unit includes: a microservices architecture, wherein each microservices sub-architecture is respectively configured to control each of the modules; an event-driven architecture, wherein each event-driven sub-architecture is respectively configured to control each of the modules; the agent control unit selects each sub-architecture used to control each of the modules based on a specified scheme; wherein, the specified scheme is one of multiple different optional schemes, and the optional schemes include selecting all of the microservices sub-architecture, selecting all of the event-driven sub-architecture, and selecting some of the microservices sub-architecture and some of the event-driven sub-architecture.

[0017] In one implementation, each of the microservice sub-architectures and each of the event-driven sub-architectures are pre-annotated with the driving computing power required by the driving sub-architecture. The following method is used to determine the selected specified solution: Monitor the currently available idle computing power in real time; use the condition that only one sub-architecture for driving is selected for each module as the first screening condition, the condition that the total driving computing power required by the selected sub-architecture is less than or equal to the idle computing power as the second screening condition, and the condition that the total driving computing power required by the selected sub-architecture is closest to the idle computing power as the third screening condition to screen the alternative solutions to obtain the specified solution.

[0018] In one implementation, the agent control unit further includes: an artificial management interface. The agent uses the TensorFlow machine learning framework and derives the control methods for each module based on the specified learning process that occurs on the artificial management interface; wherein the specified learning process includes the operation process manually performed on the artificial management interface according to the engineering control standard.

[0019] The above solution of the embodiments of the present application has at least the following beneficial effects compared with the prior art:

[0020] The engineering full - life - cycle management method provided by this application realizes the automated management and monitoring of the entire life cycle of engineering projects, reduces the need for manual intervention, and thus improves work efficiency. This method verifies the user's identity through a login module, ensuring that system access is limited to authorized users, enhancing data security and compliance, and enabling real - time monitoring and rapid response. Moreover, each module can be applied to provide solution strategies for different stages in the engineering full - life cycle. For example, the home page module can analyze and display project data in real time, enabling managers to promptly understand the latest project progress. The message notification module can automatically detect changes in key nodes according to preset rules and notify relevant personnel in a timely manner to ensure the timely transmission of information. The project management module provides intelligent suggestions to help project leaders manage projects more effectively. The project progress overview module uses algorithms to optimize the display of the progress schedule, enabling project leaders to clearly grasp the overall project progress at a glance. The task management module can automatically assign tasks based on task priorities and deadlines to ensure the reasonable and efficient utilization of resources. The process management module can automatically identify bottlenecks in the process and trigger an automatic archiving process after the process is completed, contributing to the continuous improvement of the project process. The personnel management module can efficiently handle the addition, deletion, modification, and query of personnel information to ensure that all accounts comply with security regulations. The weekly report management module can automatically collect and organize weekly report information, generate customized reports according to user needs, and reduce the workload of manual report collation. The in - site message module can automatically send in - site messages and track the reading status of messages to ensure the effective transmission of important information. The engineering full - life - cycle management method provided by this application can not only improve the management efficiency of engineering projects, but also reduce the risk of human errors through automated means, while ensuring the smooth progress of projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 Shows a flowchart of the engineering full - life - cycle management method according to an embodiment of this application;

[0022] Figure 2 Shows a flowchart of the method for determining a specified solution in an alternative solution according to an embodiment of this application;

[0023] Figure 3 Shows a block diagram of an engineering full - life - cycle management system. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] In order to make the objectives, technical solutions, and advantages of this application clearer, the following will further describe this application in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the scope of protection of this application.

[0025] The terms used in the embodiments of this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms "a", "the", and "said" used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. "Plural" generally includes at least two.

[0026] It should be understood that the term "and / or" used herein is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " herein generally represents an "or" relationship between the associated objects before and after.

[0027] It should be understood that although terms such as first, second, and third may be used in the embodiments of this application for description, these descriptions should not be limited to these terms. These terms are only used to distinguish descriptions. For example, without departing from the scope of the embodiments of this application, the first can also be called the second, and similarly, the second can also be called the first.

[0028] Depending on the context, the words "if", "when" as used herein can be interpreted as "when...", "when...", "in response to determining", or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detected (stated condition or event)" can be interpreted as "when determined", "in response to determining", "when detecting (stated condition or event)", or "in response to detecting (stated condition or event)".

[0029] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a commodity or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such commodity or device. Without further limitation, the element defined by the statement "including one..." does not exclude the existence of additional identical elements in the commodity or device including the said element.

[0030] It should be particularly noted that symbols and / or numbers existing in the specification, if not marked in the figure description, are not figure labels.

[0031] The optional embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0032] For the embodiments provided by this application, that is, the embodiments of an engineering full life cycle management method.

[0033] Below in conjunction with Figure 1A detailed description of the embodiments of the present application is provided.

[0034] Figure 1 The flowchart of the engineering full - life - cycle management method according to the embodiments of the present application is shown, as Figure 1 shown, including step S101 and step S102.

[0035] Step S101: In response to detecting a newly generated engineering project list, determine the target project to be controlled.

[0036] Step S102: Based on the pre - configured agent, control each pre - deployed module to perform information control over the full life - cycle of the target project.

[0037] Among them, the life - cycle includes an access stage, a statistics stage, an information dissemination stage, a project processing stage, a project update stage, a task assignment stage, a process monitoring stage, a personnel management stage, a weekly report processing stage, and an in - station message stage. Among them, some of these stages are sorted along the time axis, and some are partially or fully parallel along the time axis.

[0038] Among them, each module includes a login module, a home page module, a message notification module, a project management module, a project progress overview module, a task management module, a process management module, a personnel management module, a weekly report management module, and an in - station message module. The login module is used to verify the user's identity information and ensure that only authorized users can access the system. The home page module is used to analyze project data and generate statistical data, and display it on the home page. The message notification module is used to automatically detect key nodes according to preset rules and notify relevant personnel in the form of in - station messages or text messages. The project management module is used to assist the project leader in creating, editing, starting, or archiving projects, and providing intelligent suggestions according to the project status. The project progress overview module is used to update the project progress in real - time and optimize the display method of the progress schedule using algorithms. The task management module is used to automatically assign tasks according to the priority and deadline of the tasks and remind relevant personnel. The process management module is used to monitor the project process, automatically identify bottlenecks in the process, and trigger an automatic archiving process after the process is completed. The personnel management module is used to handle the addition, deletion, modification, and query of personnel information and ensure that the accounts comply with security regulations. The weekly report management module is used to collect and organize weekly report information and generate customized reports according to user needs. The in - station message module is used to automatically send in - station messages and track the reading status of the messages.

[0039] Generally, there are various related ways between the agent and the module. For example, in the modular design of the agent, the agent is used as a module, the interaction between the agent and the module, or the agent is integrated into the module.

[0040] In this application, the interaction between the agent and the modules is used to manage and control the information throughout the entire life cycle of the target project. During the whole process, the agent acts as the leader, and each module acts as the executor to conduct refined information management and control for each stage of the life cycle.

[0041] The engineering full life cycle management method provided by this application realizes the automated management and monitoring of the full life cycle of engineering projects, reduces the need for manual intervention, and thus improves work efficiency. This method verifies the user identity through the login module to ensure that system access is limited to authorized users, enhances data security and compliance, and enables real-time monitoring and rapid response. Moreover, each module can be applied to provide solutions for different stages in the engineering full life cycle. For example, the home page module can analyze and display project data in real time, enabling managers to promptly understand the latest progress of the project. The message notification module can automatically detect changes in key nodes according to preset rules and notify relevant personnel in a timely manner to ensure the timely transmission of information. The project management module provides intelligent suggestions to help project leaders manage projects more effectively. The project progress overview module uses algorithms to optimize the display of the progress schedule, enabling project leaders to clearly grasp the overall progress of the project at a glance. The task management module can automatically assign tasks according to the priority and deadline of the tasks to ensure the reasonable and efficient utilization of resources. The process management module can automatically identify bottlenecks in the process and trigger an automatic archiving process after the process is completed, which helps to continuously improve the project process. The personnel management module can efficiently handle the addition, deletion, modification, and query of personnel information to ensure that all accounts comply with security regulations. The weekly report management module can automatically collect and organize weekly report information and generate customized reports according to user needs, reducing the workload of manually sorting reports. The internal message module can automatically send internal messages and track the reading status of the messages to ensure the effective transmission of important information. The engineering full life cycle management method provided by this application can not only improve the management efficiency of engineering projects, but also reduce the risk of human errors through automated means, while ensuring the smooth progress of the project.

[0042] This application relates to an engineering full life cycle management method, aiming to effectively manage the entire process of engineering projects from creation to completion through intelligent means, and improve work efficiency and quality.

[0043] When the system detects a newly generated engineering project list, it automatically identifies the target project to be managed and controlled. The system will automatically match appropriate management and control strategies according to information such as the project type and scale, and control each pre-deployed module through a pre-configured agent to achieve information management and control of the full life cycle of the target project.

[0044] Exemplarily, the agent can select different architectures according to the actual situation, such as, for example, a microservices architecture and / or an event-driven architecture, to control each module.

[0045] As a feasible embodiment, the intelligent agent includes a microservice architecture and an event-driven architecture. Each microservice sub-architecture in the microservice architecture is used to control each module, and each event-driven sub-architecture in the event-driven architecture is used to control each module. For this application, each module can be controlled by a complete set of microservice architectures of the intelligent agent, or by a complete set of event-driven architectures of the intelligent agent. Of course, it is also possible to select some microservice sub-architectures and some event-driven sub-architectures separately, as long as the selected sub-architectures cover the driving of each module.

[0046] In this application, the intelligent agent can select various sub-architectures for controlling various modules based on a specified scheme.

[0047] Among them, the designated scheme is one of multiple different optional schemes, and the optional schemes include selecting all microservice sub-architectures, selecting all event-driven sub-architectures, and selecting some microservice sub-architectures and some event-driven sub-architectures. In one example, selecting some microservice sub-architectures and some event-driven sub-architectures, for example, the microservice sub-architecture can be selected for the operation of the login module, homepage module, message notification module, project management module, and project progress list module, and the event-driven sub-architecture can be selected for the task management module, process management module, personnel management module, weekly report management module, and in-station message module. In another example, selecting some microservice sub-architectures and some event-driven sub-architectures, for example, the event-driven sub-architecture can be selected for the operation of the login module, homepage module, message notification module, project management module, and project progress list module, and the microservice sub-architecture can be selected for the task management module, process management module, personnel management module, weekly report management module, and in-station message module. Of course, the optional schemes are not limited to these, and only two optional schemes are shown here as examples.

[0048] In this application, each microservice sub-architecture and each event-driven sub-architecture are pre-marked with the driving computing power required by the driving sub-architecture.

[0049] In a feasible implementation, the selected designated solution may be determined in the following manner.

[0050] Figure 2 A flow chart of a method for determining a specific solution from among optional solutions according to an embodiment of the present application is shown. Figure 2 As shown, the process includes the following steps S201 and S202.

[0051] Step S201: monitor the currently supported idle computing power in real time.

[0052] Step S202: Using the condition of selecting only one driving sub-architecture for each module as the first screening criterion, the condition that the total driving computing power required by the selected sub-architecture is less than or equal to the idle computing power as the second screening criterion, and the condition that the total driving computing power required by the selected sub-architecture is closest to the idle computing power as the third screening criterion, screen the alternative solutions to obtain the specified solution.

[0053] In this application, by monitoring the currently supported idle computing power in real time, the system can ensure that the operation of each sub-architecture of the intelligent agent (whether it is a microservices architecture or an event-driven architecture) does not exceed the available computing resource limits. This mechanism helps to avoid resource waste and at the same time ensures the stable operation of the system, preventing performance degradation or crashes due to insufficient resources. This method determines the best specified solution through three clear screening criteria, enabling the system to make the optimal choice among multiple alternative solutions.

[0054] Among them, the first screening criterion ensures that each module has a unique sub-architecture to drive, avoiding redundancy and conflicts. The second screening criterion ensures that the total driving computing power of the selected sub-architecture does not exceed the current idle computing power, preventing resource overload. The third screening criterion, on the basis of meeting the first two conditions, makes the total driving computing power of the selected sub-architecture as close as possible to the idle computing power, thereby maximizing resource utilization. This method allows the system to flexibly adjust its architecture selection according to the current actual available resources, so as to better adapt to changing workloads and business requirements. Moreover, by dynamically selecting the solution most suitable for the current resource situation in this way, the system can better handle engineering projects of different scales and types, and the system can also improve performance as much as possible without sacrificing stability.

[0055] In this application, the system checks the currently available idle computing power and screens out the solutions that meet the following conditions based on this computing power level:

[0056] First, for each module, only select one sub-architecture (microservices sub-architecture or event-driven sub-architecture) to drive it.

[0057] Second, the total driving computing power required by all the selected sub-architectures does not exceed the current idle computing power.

[0058] On the basis of meeting the first two conditions, select the solutions whose total required driving computing power is closest to the idle computing power.

[0059] Normally, there is only one solution closest to the idle computing power. However, in actual processing, there may be two or more solutions, and the driving computing power required by these solutions is the same and all meet the condition of being closest to the idle computing power. In this case, the system will enter the next comparison.

[0060] In this application, there can be one or more alternative solutions that meet each screening condition. For these two cases, the alternative solutions can be screened in the following ways to obtain the specified solution.

[0061] On the one hand, when there is one alternative solution that meets each screening condition, the alternative solution that meets each screening condition can be used as the specified solution.

[0062] On the other hand, when there are at least two alternative solutions that meet each screening condition, based on the total entropy value gain of each of the at least two alternative solutions, the alternative solution with the highest total entropy value gain can be used as the specified solution.

[0063] During the comparison process, the system calculates a "total entropy value gain" for each solution that meets the screening conditions. Among them, the total entropy value gain represents the sum of the entropy value gains generated by each sub-architecture specified in the alternative solution driving the corresponding module, and the entropy value gain is used to characterize the driving effect of the sub-architecture driving the module.

[0064] In this application, the entropy value gain is an index used to measure the effect of the sub-architecture driving the module. It comprehensively considers the completion rate (P) of the sub-architecture driving the module, the fixed parameter (c), the complexity score (N) of the sub-architecture, and the complexity score (n) of the module itself. The higher the entropy value gain, the better the efficiency and effect of the sub-architecture driving the corresponding module.

[0065] As a feasible embodiment, the calculation formula of the entropy value gain is as follows:

[0066] G m =P−c·N / n.

[0067] In this application, the above formula represents a relatively basic calculation method of the entropy value gain. Among them, G m is the entropy value gain, P is the completion rate of the sub-architecture driving the module, which reflects the success degree of the sub-architecture when performing tasks, c is a fixed parameter used to adjust the output value of the formula to adapt to the characteristics of different types of sub-architectures, N is the complexity score of the sub-architecture, marked based on the scale and resource occupancy of the sub-architecture, and n is the complexity score of the module, scored based on the module function complexity.

[0068] In addition, as another feasible embodiment, the calculation formula of the entropy value gain is as follows:

[0069] .

[0070] Among them, G mis the entropy gain value, P represents the completion rate of the sub-architecture driver module, c represents a fixed parameter used to adjust the curve radian represented by the formula so that the curve is applicable to each sub-architecture, N represents the complexity score of the sub-architecture, which is pre-labeled based on the scale of the sub-architecture and the amount of occupied characters, and n represents the complexity score of the module, which is pre-labeled based on the complexity score of the functions executed by the module. By way of example, this formula is an advanced algorithm of the previous formula. By introducing the log function, the output value of the formula is adjusted to a curve applicable to different sub-architectures. Among them, the adjustment of the curve radian is achieved by adjusting the value of c. Then, referring to the actual performance of the sub-architecture for different modules in the pre-experiment stage before use, the curve is adjusted to be closest to the discrete scatter plot formed by the experimental data points of the sub-architecture. Finally, the system will select the solution with the highest total entropy gain value as the designated solution, that is, this solution is considered to be the solution that can most effectively and efficiently complete the task under the current conditions. In this way, by combining computing power resource management and task execution effect evaluation, the system can select the optimal one from multiple possible control solutions, so as to achieve effective control over the entire life cycle of the engineering project.

[0071] In fact, the micro-service sub-architecture and the event-driven sub-architecture have differences in focus, execution mode, and even implementation effects. In addition to making a choice between the two architectures based on computing power to ensure that the architecture is selected with the maximum supportable computing power, it is also possible to make fixed combinations for some modules according to the actual benefits of the two architectures for the modules. Then, for other modules without fixed combinations, the above computing power screening strategy is further adopted. Such a result can further ensure that the smallest possible computing power is used to achieve the best possible control and execution effects.

[0072] In this application, the intelligent agent is externally connected to an artificial management interface. The intelligent agent uses the TensorFlow machine learning framework and, based on the specified learning process that occurs on the artificial management interface, deduces the control methods for each module.

[0073] Among them, the specified learning process includes the operation process manually executed on the artificial management interface according to the engineering control standards. For example, the operation process manually executed on the artificial management interface according to the engineering control standards is regarded as the specified learning process. These operation processes can include project management-related activities such as creating a project, editing project information, assigning tasks, and adjusting task priorities. When the user executes these operations on the artificial management interface, the intelligent agent will record these operations and use the TensorFlow machine learning framework to analyze and learn these operation processes.

[0074] In this application, the intelligent agent is externally connected to a user feedback window and can receive the feedback information of the user. In one implementation, the intelligent agent can determine the description information input from the user feedback window based on the semantic analysis method and, based on the description information, adjust the operation methods for some or all modules.

[0075] In this application, the agent communicates with each module based on the Representational State Transfer Application Programming Interface (RESTful API) protocol to control the pre-deployed modules.

[0076] In this application, the agent is externally connected to a manual management interface, which allows project managers or operators to directly interact with the agent. The agent adopts the TensorFlow machine learning framework, which is a powerful machine learning platform that can be used to train and deploy various machine learning models. Through the manual management interface, the agent can learn and deduce the control methods for each module. Specifically:

[0077] In this application, users can submit suggestions or opinions on system operations, functions, etc. through the user feedback window. These feedbacks can be descriptive information in text form. The agent uses advanced semantic analysis technology to understand the content of the feedback provided by users. For example, if a user mentions that a certain function is inconvenient to use, the agent can identify this as feedback on the usability of the function. Based on the results of semantic analysis, the agent will automatically adjust the operation methods for some or all of the modules. For example, if the user feedback points out that a certain function in the task assignment module is not intuitive enough, the agent may adjust the task assignment algorithm to improve the user experience. In this way, the agent can not only learn and imitate the operation process of manual managers, but also optimize itself according to user feedback to better meet user needs and improve the management efficiency and quality of the project.

[0078] The engineering full-life cycle management method proposed in this application realizes the automated management and monitoring of the whole process of engineering projects from creation to completion by integrating the agent and multiple modules. This application reduces the need for manual intervention through automated means, improves the management efficiency of engineering projects, and the agent can automatically match appropriate control strategies according to the specific situation of engineering projects, reducing the management complexity.

[0079] In this application, each module provides corresponding security for different stages of the project lifecycle. The login module ensures that only authorized users can access the system, enhancing data security and compliance. The personnel management module efficiently handles personnel information and ensures that accounts comply with security regulations. The homepage module analyzes and displays project data in real time, allowing managers to stay updated on project progress. The message notification module automatically detects changes in key milestones based on preset rules and promptly notifies relevant personnel, ensuring timely information delivery. The project management module provides intelligent recommendations to help project leaders manage projects more effectively. The project progress overview module uses algorithms to optimize the display of progress charts, allowing project leaders to clearly understand the overall progress of the project. The task management module automatically assigns tasks based on priority and deadlines, ensuring the rational and efficient use of resources. The process management module automatically identifies bottlenecks in processes and triggers automatic archiving upon completion, contributing to continuous improvement of project processes. The weekly report management module automatically collects and organizes weekly report information, reducing the workload of manual report compilation. The internal message module automatically sends internal messages and tracks message reading status to ensure that important information is effectively conveyed.

[0080] Furthermore, the agent can choose a microservices architecture, an event-driven architecture, or even a combination of the two, to adapt to projects of varying sizes and types. By monitoring the currently supported idle computing power in real time, the agent determines the optimal solution, ensuring stable system operation and high resource utilization.

[0081] Furthermore, the agent is connected to a human management interface, allowing it to learn and mimic the operational processes performed by human managers, deducing how to control each module. The agent can also receive user feedback and adjust its operational methods for some or all modules accordingly, continuously improving system performance.

[0082] In summary, the engineering lifecycle management method proposed in this application not only significantly improves the efficiency and quality of engineering project management, but also reduces the risk of human error through intelligent means, ensuring the smooth progress of projects. Furthermore, through flexible architecture selection and continuous learning and optimization, this method can better adapt to changing workloads and business needs.

[0083] The present application also provides a system embodiment that is consistent with the above embodiment, which is used to implement the method steps of the above embodiment. The explanation based on the same name meaning is the same as the above embodiment, and has the same technical effect as the above embodiment, which will not be repeated here.

[0084] Figure 3 A block diagram of a project life cycle management system is shown in Figure 3As shown in the figure, the engineering full life cycle management system 300 includes a project detection unit 301, an agent control unit 302, and each pre-deployed module 303. Among them, each pre-deployed module 303 includes the login module, home page module, message notification module, project management module, project progress list module, task management module, process management module, personnel management module, weekly report management module, and in-site message module involved below.

[0085] The project detection unit 301 is used to determine the target project to be controlled in response to detecting a newly generated engineering project list. The agent control unit 302 is used to control each pre-deployed module 303 based on a pre-configured agent to perform information control on the full life cycle of the target project. Among them, the life cycle includes but is not limited to the access stage, statistics stage, information dissemination stage, project processing stage, project update stage, task assignment stage, process monitoring stage, personnel management stage, weekly report processing stage, and in-site message stage. Among them, each module 303 includes a login module, home page module, message notification module, project management module, project progress list module, task management module, process management module, personnel management module, weekly report management module, and in-site message module. The login module is used to verify the user's identity information and ensure that only authorized users can access the system. The home page module is used to analyze project data and generate statistical data and display it on the home page. The message notification module is used to automatically detect key nodes according to preset rules and notify relevant personnel in the form of in-site messages or text messages. The project management module is used to assist the project leader in creating, editing, starting, or archiving projects and provide intelligent suggestions according to the project status. The project progress list module is used to update the project progress in real time and use an algorithm to optimize the display method of the progress schedule. The task management module is used to automatically assign tasks according to the priority and deadline of the tasks and remind relevant personnel. The process management module is used to monitor the project process, automatically identify bottlenecks in the process, and trigger an automatic archiving process after the process is completed. The personnel management module is used to handle the addition, deletion, modification, and query of personnel information and ensure that the account complies with security regulations. The weekly report management module is used to collect and organize weekly report information and generate customized reports according to user needs. The in-site message module is used to automatically send in-site messages and track the reading status of the messages.

[0086] In one implementation, the agent control unit 302 includes: a microservices architecture, where each microservices sub-architecture is respectively used to control each module 303. An event-driven architecture, where each event-driven sub-architecture is respectively used to control each module 303. The agent control unit 302 selects, based on a specified scheme, the respective sub-architectures for controlling each module 303. Here, the specified scheme is one of multiple different optional schemes, and the optional schemes include selecting all microservices sub-architectures, selecting all event-driven sub-architectures, and selecting some microservices sub-architectures and some event-driven sub-architectures.

[0087] In one implementation, each microservices sub-architecture and each event-driven sub-architecture are respectively pre-labeled with the driving computing power required by the sub-architecture, and the specified scheme to be selected is determined in the following manner: The current available idle computing power is monitored in real time. Taking only selecting one driving sub-architecture for each module as the first screening condition, taking the total driving computing power required by the selected sub-architecture being less than or equal to the idle computing power as the second screening condition, and taking the total driving computing power required by the selected sub-architecture being closest to the idle computing power as the third screening condition, the optional schemes are screened to obtain the specified scheme.

[0088] In one implementation, the agent control unit 302 further includes: an artificial management interface. The agent uses the TensorFlow machine learning framework and, based on a specified learning process that occurs on the artificial management interface, deduces the control methods for each module 303. Here, the specified learning process includes the operation process manually performed by a human on the artificial management interface in accordance with the engineering management standards.

[0089] In this application, the agent control unit 302 is responsible for controlling each module 303 based on a pre-configured agent to achieve information management and control throughout the life cycle. The control unit can select a microservices architecture or an event-driven architecture to control each module 303, and can dynamically adjust the architecture adopted according to the current computing power situation. The agent control unit 302 can decide which architecture combination to use to control each module 303 based on the idle computing power monitored in real time.

[0090] In this application, the artificial management interface allows human intervention. Through the TensorFlow framework, the agent can learn from the manual operations and optimize the control methods.

[0091] Through the above embodiments, this application provides an efficient and intelligent engineering full life cycle management method and its system, which can effectively improve the efficiency and quality of engineering project management.

[0092] Although the operations are depicted in the drawings in a particular order, it should not be construed that the operations are required to be performed in the particular order shown or in a sequential order, or that all of the illustrated operations are required to obtain the desired result. In certain environments, multitasking and parallel processing may be advantageous.

[0093] The methods and apparatuses of this application can be accomplished using standard programming techniques, implementing various method steps using rule-based logic or other logic. It should also be noted that the terms "apparatus" and "module" as used herein and in the claims are intended to include implementations using one or more lines of software code and / or hardware implementations and / or devices for receiving input.

[0094] Any of the steps, operations, or procedures described herein can be performed or implemented using one or more hardware or software modules, either alone or in combination with other devices. In one embodiment, the software module is implemented using a computer program product that includes a computer-readable medium containing computer program code that can be executed by a computer processor to perform any or all of the described steps, operations, or procedures.

[0095] For purposes of illustration and description, the foregoing description of the implementation of this application has been given. The foregoing description is not exhaustive and is not intended to limit this application to the exact form disclosed, and various variations and modifications may be possible in light of the above teachings, or may be derived from the practice of this application. These embodiments were chosen and described in order to explain the principles of this application and its practical application, so that those skilled in the art can utilize this application in various embodiments and various modifications suitable for the particular purposes contemplated.

[0096] Regarding the apparatuses in the above embodiments, the specific manner in which each module performs the operations has been described in detail in the embodiments related to the method, and will not be elaborated herein.

[0097] It can be further understood that, unless otherwise specified, "connection" includes direct connection between two parties without other components therebetween, and also includes indirect connection between two parties with other elements therebetween.

[0098] It can be further understood that, although the operations are depicted in the drawings in a particular order in the embodiments of this application, it should not be construed that the operations are required to be performed in the particular order shown or in a sequential order, or that all of the illustrated operations are required to obtain the desired result. In certain environments, multitasking and parallel processing may be advantageous.

[0099] Other embodiments of the present application will be readily apparent to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include well-known knowledge or conventional technical means in the field of the present application not disclosed herein. The specification and examples are only illustrative, and the true scope and spirit of the present application are pointed out by the following claims.

[0100] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

[0101] The above embodiments are only used to illustrate the technical solutions of the present application, not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. An engineering full life cycle management method, characterized in that, The method includes: In response to detecting a newly generated engineering project list, determining a target project to be controlled; Based on a pre-configured agent, controlling each pre-deployed module to perform information control over the entire life cycle of the target project; Wherein, the life cycle includes an access stage, a statistics stage, an information dissemination stage, a project processing stage, a project update stage, a task assignment stage, a process monitoring stage, a personnel management stage, a weekly report processing stage, and an in-site message stage; Wherein, each of the modules includes a login module, a home page module, a message notification module, a project management module, a project progress summary module, a task management module, a process management module, a personnel management module, a weekly report management module, and an in-site message module; The login module is used to verify the identity information of the user and ensure that only authorized users can access the system; The home page module is used to analyze project data and generate statistical data and display it on the home page; The message notification module is used to automatically detect key nodes according to preset rules and notify relevant personnel in the form of in-site messages or text messages; The project management module is used to assist project leaders in creating, editing, starting, or archiving projects and provide intelligent suggestions according to the project status; The project progress summary module is used to update the project progress in real time and optimize the display method of the progress schedule using an algorithm; The task management module is used to automatically assign tasks according to the priority and deadline of the tasks and remind relevant personnel; The process management module is used to monitor the project process, automatically identify bottlenecks in the process, and trigger an automatic archiving process after the process is completed; The personnel management module is used to handle the addition, deletion, modification, and query of personnel information and ensure that the account complies with security regulations; The weekly report management module is used to collect and organize weekly report information and generate customized reports according to user needs; The in-site message module is used to automatically send in-site messages and track the reading status of the messages; The agent includes a microservice architecture and an event-driven architecture. Each microservice sub-architecture in the microservice architecture is respectively used to control each of the modules, and each event-driven sub-architecture in the event-driven architecture is respectively used to control each of the modules; The agent selects each sub-architecture for controlling each of the modules based on a specified scheme; wherein, the specified scheme is one of multiple different optional schemes, and the optional schemes include selecting all the microservice sub-architectures, selecting all the event-driven sub-architectures, and selecting some of the microservice sub-architectures and some of the event-driven sub-architectures; Each of the microservice sub-architectures and each of the event-driven sub-architectures are respectively pre-labeled with the driving computing power required by the driving sub-architecture. The following method is used to determine the selected specified scheme: Real-time monitor the currently available idle computing power; Taking only one sub-architecture for driving as the first screening criterion for each of the said modules, taking the total driving computing power required by the selected sub-architecture to be less than or equal to the idle computing power as the second screening criterion, and taking the total driving computing power required by the selected sub-architecture to be closest to the idle computing power as the third screening criterion, screen the said alternative solutions to obtain the said designated solution.

2. The engineering full life cycle management method according to claim 1, characterized in that The screening of the said alternative solutions to obtain the said designated solution includes: In response to there being one alternative solution that meets each of the said screening criteria, taking the alternative solution that meets each of the said screening criteria as the said designated solution; In response to there being at least two alternative solutions that meet each of the said screening criteria, based on the total entropy value gain of each of the at least two alternative solutions, taking the alternative solution with the highest total entropy value gain as the said designated solution; Wherein, the total entropy value gain represents the sum of the entropy value gains generated by each of the sub-architectures specified in the alternative solution for driving the corresponding module, and the entropy value gain is used to characterize the driving effect of the sub-architecture in driving the module; Wherein, the entropy value gain generated by each of the said sub-architectures for driving the corresponding module is calculated using the following formula: Among them, G m represents the entropy value gain, P represents the completion rate of the sub-architecture driving module, c represents the fixed parameter, N represents the complexity score of the sub-architecture, and n represents the complexity score of the module.

3. The engineering full life cycle management method according to claim 1, characterized in that The intelligent body is externally connected to an artificial management interface, the intelligent body uses the TensorFlow machine learning framework, and based on the specified learning process occurring on the artificial management interface, deduces the control methods for the said respective modules; wherein, the specified learning process includes the operation process manually performed by the user on the artificial management interface in accordance with the engineering management standards.

4. The engineering full life cycle management method according to claim 1, characterized in that The intelligent body is externally connected to a user feedback window, the intelligent body determines the description information input from the user feedback window based on semantic analysis, and based on the description information, adjusts the operation methods for some or all of the said modules; The intelligent body communicates with each module based on the Representational State Transfer Application Programming Interface (RESTful API) protocol of the usage presentation layer to achieve the control of each pre-deployed module.

5. An engineering full-life cycle management system, characterized in that, The said system includes: A project detection unit for determining the target project to be managed in response to detecting a newly generated engineering project list; An intelligent body control unit for controlling each pre-deployed module based on a pre-configured intelligent body to perform information management and control over the entire life cycle of the said target project; wherein, the life cycle includes but is not limited to the access stage, statistics stage, information dissemination stage, project processing stage, project update stage, task assignment stage, process monitoring stage, personnel management stage, weekly report processing stage, and internal message stage; wherein, each of the said modules includes a login module, a home page module, a message notification module, a project management module, a project progress summary module, a task management module, a process management module, a personnel management module, a weekly report management module, and an internal message module; The said login module is used to verify the user's identity information and ensure that only authorized users can access the system; The said home page module is used to analyze project data and generate statistical data and display it on the home page; The said message notification module is used to automatically detect key nodes according to preset rules and notify relevant personnel in the form of internal messages or text messages; The project management module is used to assist the project leader in creating, editing, starting, or archiving projects, and providing intelligent suggestions based on the project status; The project progress summary module is used to update the project progress in real time and optimize the display mode of the progress schedule using algorithms; The task management module is used to automatically assign tasks according to the priority and deadline of the tasks and remind relevant personnel; The process management module is used to monitor the project process, automatically identify bottlenecks in the process, and trigger an automatic archiving process after the process is completed; The personnel management module is used to handle the addition, deletion, modification, and query of personnel information and ensure that the accounts comply with security regulations; The weekly report management module is used to collect and collate weekly report information and generate customized reports according to user needs; The in-site message module is used to automatically send in-site messages and track the reading status of the messages; The intelligent agent control unit includes: A microservices architecture, where each microservices sub-architecture is used to control each of the above modules; An event-driven architecture, where each event-driven sub-architecture is used to control each of the above modules; The intelligent agent control unit selects the respective sub-architectures for controlling each of the above modules based on a specified scheme; wherein, the specified scheme is one of multiple different optional schemes, and the optional schemes include selecting all of the microservices sub-architectures, selecting all of the event-driven sub-architectures, and selecting some of the microservices sub-architectures and some of the event-driven sub-architectures; Each of the microservices sub-architectures and each of the event-driven sub-architectures are pre-labeled with the driving computing power required by the driving sub-architecture, and the specified scheme is determined in the following manner: Real-time monitor the currently available idle computing power; Using the condition that only one driving sub-architecture is selected for each of the above modules as the first screening condition, the condition that the total driving computing power required by the selected sub-architecture is less than or equal to the idle computing power as the second screening condition, and the condition that the total driving computing power required by the selected sub-architecture is closest to the idle computing power as the third screening condition, screen the optional schemes to obtain the specified scheme.

6. The engineering full life cycle management system according to claim 5, characterized in that The intelligent agent control unit further includes: An artificial management interface, the intelligent agent uses the TensorFlow machine learning framework, and based on the specified learning process that occurs on the artificial management interface, deduces the control methods for each of the above modules; wherein, the specified learning process includes the operation process manually performed by an operator on the artificial management interface in accordance with engineering control standards.

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