Project full life cycle management method and system

Abstract

The invention provides a project full life cycle management method and system. The method comprises the steps of determining a to-be-controlled target project in response to detection of a newly generated project list; based on a pre-configured intelligent agent, controlling each pre-deployed module so as to perform information management and control on the whole life cycle of the target project; wherein the life cycle comprises an access stage, a statistics stage, an information transmission stage, a project processing stage, a project updating stage, a task distribution stage, a process monitoring stage, a personnel management stage, a weekly report processing stage and an in-station information stage; wherein each module comprises a login module, a home page module, a message notification module, a project management module, a project progress list module, a task management module, a process management module, a personnel management module, a weekly report management module and an in-station letter module; and the login module is used for verifying the identity information of the user and ensuring that only the authorized user can access the system.

Description

Technical Field

[0001] The present application relates to the field of information management, and more specifically, to a method and system for managing the entire life cycle of an engineering project. Background Art

[0002] At present, traditional engineering project management often relies on manual operations and manual records, which is not only inefficient but also prone to errors. With the development of information technology, especially the advancement of cloud computing, big data and artificial intelligence technology, more and more companies are beginning to seek ways to use these advanced technologies to improve engineering project management.

[0003] Among the related technologies, products that can significantly reduce labor costs, such as digital platforms, cloud platform applications, and intelligent management, have gradually become the mainstream of information management. Among them, digital transformation transforms 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 operation of projects. Although related technologies have made certain progress, there are still shortcomings, such as limited flexibility and adaptability, and poor user usability.

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

[0005] The purpose of this application is to provide a project life cycle management method and system that can solve at least one of the above-mentioned technical problems. The specific solution is as follows: According to the specific implementation of the present application, in the first aspect, the present application provides a method for managing the entire life cycle of an engineering project, including: In response to detecting a newly generated engineering project list, determining a target project to be controlled; Based on the pre-configured intelligent agent, the pre-deployed modules are manipulated to perform information management and control over the entire life cycle of the target project; wherein the life cycle includes the access stage, the statistical stage, the information communication stage, the project processing stage, the project update stage, the task allocation stage, the process monitoring stage, the personnel management stage, the weekly report processing stage, and the station letter stage; wherein the modules include the login module, the homepage module, the message notification module, the project management module, the project progress list module, the task management module, the process management module, the personnel management module, the weekly report management module, and the station letter module; the login module is used to verify the user's identity information and ensure that only authorized users can access the system; the homepage module is used to analyze project data and generate statistical data, and display it on the homepage; the message notification module is used to automatically detect key The project management module is used to assist the project leader in creating, editing, starting or archiving projects, and to provide intelligent suggestions based on the project status; the project progress overview module is used to update the project progress in real time, and to use algorithms to optimize the display of the progress chart; the task management module is used to automatically assign tasks according to their priorities and deadlines, and to remind relevant personnel; the process management module is used to monitor the project process, automatically identify bottlenecks in the process, and trigger the 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 based on user needs; the in-station message module is used to automatically send in-station messages and track the reading status of messages.

[0006] In one embodiment, the intelligent agent includes a microservice architecture and an event-driven architecture, wherein 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; the intelligent agent selects each sub-architecture for controlling each module based on a specified scheme; wherein the specified scheme is one of a plurality of different optional schemes, and the optional schemes include selecting all of the microservice sub-architectures, selecting all of the event-driven sub-architectures, and selecting part of the microservice sub-architectures and part of the event-driven sub-architectures.

[0007] In one embodiment, each of the microservice sub-architectures and each of the event-driven sub-architectures are pre-marked with the driving computing power required by the driving sub-architecture, and the selected designated scheme is determined in the following manner: real-time monitoring of the currently supported idle computing power; selecting only one sub-architecture for driving each module as the first screening condition, 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 the total driving computing power required by the selected sub-architecture being closest to the idle computing power as the third screening condition, and screening the optional schemes to obtain the designated scheme.

[0008] In one embodiment, the screening of the optional schemes to obtain the designated scheme includes: in response to the optional scheme satisfying each of the screening conditions being one, taking the optional scheme satisfying each of the screening conditions as the designated scheme; in response to the optional scheme satisfying each of the screening conditions being at least two, based on the total entropy gain values ​​of the at least two optional schemes, taking the optional scheme with the highest total entropy gain value as the designated scheme; wherein the total entropy gain value represents the sum of the entropy gains generated by each sub-architecture specified in the optional scheme driving the corresponding module, and the entropy gain value is used to characterize the driving effect of the sub-architecture driving module; wherein the entropy gain value generated by each sub-architecture driving the corresponding module is calculated using the following formula: ; Wherein, P represents the completion rate of the sub-architecture driving module, c represents a fixed parameter, which is used to adjust the curvature of the curve 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-marked based on the size of the sub-architecture and the number of characters occupied, and n represents the complexity score of the module, which is pre-marked based on the complexity score of the function performed by the module.

[0009] The intelligent body is connected to a manual management interface. The intelligent body adopts the TensorFlow machine learning framework and deduces the control method for each module based on the specified learning process occurring in the manual management interface; wherein the specified learning process includes the operation process manually executed in the manual management interface according to the engineering control standard. The intelligent body is connected to a user feedback window. The intelligent body determines the description information input by the user feedback window based on semantic analysis, and adjusts the operation method for some or all of the modules based on the description information.

[0010] In one implementation, the intelligent agent communicates with each module based on the RESTful API protocol to control each pre-deployed module.

[0011] According to the specific implementation of the present application, in the second aspect, the present application provides a project life cycle management system, including: A project detection unit is used to determine the target project to be controlled in response to detecting a newly generated list of engineering projects; an intelligent agent control unit is used to manipulate the pre-deployed modules based on the pre-configured intelligent agent to perform information control over the entire life cycle of the target project; wherein the life cycle includes but is not limited to the access stage, the statistical stage, the information communication stage, the project processing stage, the project update stage, the task allocation stage, the process monitoring stage, the personnel management stage, the weekly report processing stage, and the station letter stage; wherein the various modules include a login module, a homepage module, a message notification module, a project management module, a project progress list module, a task management module, a process management module, a personnel management module, a weekly report management module, and an station letter module; the login module is used to verify the user's identity information and ensure that only authorized users can access the system; the homepage module is used to analyze project data and generate statistical data, and display it on the homepage The message notification module is used to automatically detect key nodes according to preset rules, and notify relevant personnel through station letters or text messages; the project management module is used to assist project leaders in creating, editing, starting or archiving projects, and provide intelligent suggestions based on project status; the project progress overview module is used to update project progress in real time, and use algorithms to optimize the display of the progress chart; the task management module is used to automatically assign tasks according to task priorities and deadlines, and remind relevant personnel; the process management module is used to monitor project processes, automatically identify bottlenecks in the process, and trigger the 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 based on user needs; the station letter module is used to automatically send station letters and track the reading status of messages.

[0012] In one embodiment, the intelligent body control unit includes: a microservice architecture, wherein each microservice sub-architecture is used to control each module respectively; an event-driven architecture, wherein each event-driven sub-architecture is used to control each module respectively; the intelligent body control unit selects each sub-architecture for controlling each module based on a specified scheme; wherein the specified scheme is one of a plurality of different optional schemes, and the optional schemes include selecting all of the microservice sub-architectures, selecting all of the event-driven sub-architectures, and selecting part of the microservice sub-architectures and part of the event-driven sub-architectures.

[0013] In one embodiment, each of the microservice sub-architectures and each of the event-driven sub-architectures are pre-marked with the driving computing power required by the driving sub-architecture, and the selected designated scheme is determined in the following manner: real-time monitoring of the currently supported idle computing power; selecting only one sub-architecture for driving each module as the first screening condition, 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 the total driving computing power required by the selected sub-architecture being closest to the idle computing power as the third screening condition, and screening the optional schemes to obtain the designated scheme.

[0014] In one embodiment, the intelligent agent control unit also includes: a manual management interface, the intelligent agent adopts the TensorFlow machine learning framework, and based on the specified learning process occurring in the manual management interface, deduces the control method for each module; wherein the specified learning process includes the operation process manually executed in the manual management interface according to the engineering control standards.

[0015] Compared with the prior art, the above solution of the embodiment of the present application has at least the following beneficial effects: The engineering life cycle management method provided by this application realizes the automated management and monitoring of the entire life cycle of the engineering project, reduces the need for manual intervention, and thus improves work efficiency. The method verifies the user identity through the login module, ensures that the access to the system is limited to authorized users, enhances the security and compliance of the data, and can achieve real-time monitoring and rapid response. In addition, each module can be applied to provide solutions for different stages in the entire life cycle of the project. For example, the homepage module can analyze and display project data in real time, so that managers can keep abreast of 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 delivery of information. The project management module provides intelligent suggestions to help project leaders manage projects more effectively. The project schedule module uses an algorithm to optimize the display of the schedule, so that the project leader can 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 task to ensure that resources are used reasonably and efficiently. The process management module can automatically identify bottlenecks in the process and trigger the 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, generate customized reports according to user needs, and reduce the workload of manually organizing reports. The in-station message module can automatically send in-station messages and track the reading status of messages to ensure that important information is effectively communicated. The engineering life cycle management method provided in this application can not only improve the management efficiency of engineering projects, but also reduce the risk of human error through automation, while ensuring the smooth progress of the project. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flowchart of a project life cycle management method according to an embodiment of the present application is shown; Figure 2 A flow chart of a method for determining a specified solution from optional solutions according to an embodiment of the present application is shown; Figure 3 A block diagram of a project life cycle management system is shown. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0018] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings, and "multiple" generally includes at least two.

[0019] It should be understood that the term "and / or" used in this article is only 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 at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0020] It should be understood that although the terms first, second, third, etc. may be used to describe in the embodiments of the present application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of the present application, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0021] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0022] It should also be noted that the term "includes", "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, so that a commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprising a ..." do not exclude the existence of other identical elements in the commodity or device including the elements.

[0023] It should be particularly noted that any symbols and / or numbers in the specification that are not marked in the accompanying drawings are not drawing marks.

[0024] The optional embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0025] The embodiment provided in this application is an embodiment of a method for managing the entire life cycle of an engineering project.

[0026] Combine the following Figure 1 The embodiments of the present application are described in detail.

[0027] Figure 1 A flowchart of a project life cycle management method according to an embodiment of the present application is shown. Figure 1 As shown, it includes step S101 and step S102.

[0028] Step S101, in response to detecting a newly generated engineering project list, determining a target project to be controlled.

[0029] Step S102, based on the pre-configured intelligent agent, the pre-deployed modules are controlled to perform information management and control over the entire life cycle of the target project.

[0030] The life cycle includes the visit phase, statistics phase, information transmission phase, project processing phase, project update phase, task allocation phase, process monitoring phase, personnel management phase, weekly report processing phase, and internal letter phase. Some of these phases are arranged along the timeline, while others are partially or completely parallel along the timeline.

[0031] Among them, the modules include login module, homepage 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 internal letter module. Among them, the login module is used to verify the user's identity information and ensure that only authorized users can access the system. The homepage module is used to analyze project data and generate statistical data, and display them on the homepage. The message notification module is used to automatically detect key nodes according to preset rules and notify relevant personnel through internal letters or text messages. The project management module is used to assist project leaders in creating, editing, starting or archiving projects, and provide intelligent suggestions based on project status. The project progress list module is used to update project progress in real time and use algorithms to optimize the display of the progress list. The task management module is used to automatically assign tasks according to their priority and deadline, and remind relevant personnel. The process management module is used to monitor project processes, automatically identify bottlenecks in the process, and trigger the 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. Weekly report management module is used to collect and organize weekly report information and generate customized reports according to user needs. Internal message module is used to automatically send internal messages and track the reading status of messages.

[0032] Typically, agents and modules are related in a variety of ways, such as modular design of agents, agents as modules, interaction between agents and modules, or integration of agents into modules.

[0033] In this application, the interaction between the intelligent agent and the module is used to perform information management and control over the entire life cycle of the target project. During the whole process, the intelligent agent acts as the leader and each module acts as the executor to perform refined information management and control at each stage of the life cycle.

[0034] The engineering life cycle management method provided by this application realizes the automated management and monitoring of the entire life cycle of the engineering project, reduces the need for manual intervention, and thus improves work efficiency. The method verifies the user identity through the login module, ensures that the access to the system is limited to authorized users, enhances the security and compliance of the data, and can achieve real-time monitoring and rapid response. In addition, each module can be applied to provide solutions for different stages in the entire life cycle of the project. For example, the homepage module can analyze and display project data in real time, so that managers can keep abreast of 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 delivery of information. The project management module provides intelligent suggestions to help project leaders manage projects more effectively. The project schedule module uses an algorithm to optimize the display of the schedule, so that the project leader can 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 task to ensure that resources are used reasonably and efficiently. The process management module can automatically identify bottlenecks in the process and trigger the 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, generate customized reports according to user needs, and reduce the workload of manually organizing reports. The in-station message module can automatically send in-station messages and track the reading status of messages to ensure that important information is effectively communicated. The engineering life cycle management method provided in this application can not only improve the management efficiency of engineering projects, but also reduce the risk of human error through automation, while ensuring the smooth progress of the project.

[0035] This application relates to a project life cycle management method, which aims to achieve effective management of the entire process of engineering projects from creation to completion through intelligent means, thereby improving work efficiency and quality.

[0036] When the system detects a newly generated list of engineering projects, it automatically identifies the target project to be controlled. The system automatically matches the appropriate control strategy based on information such as the project type and scale, and uses pre-configured intelligent agents to control the pre-deployed modules to achieve information control over the entire life cycle of the target project.

[0037] For example, the intelligent agent can select different architectures according to actual conditions, such as microservice architecture and / or event-driven architecture, to realize the control of each module.

[0038] As a feasible embodiment, the intelligent body 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 body, or by a complete set of event-driven architectures of the intelligent body. Of course, some microservice sub-architectures and some event-driven sub-architectures can be selected separately, as long as the selected sub-architectures cover the drivers of each module.

[0039] In the present application, the intelligent agent can select various sub-architectures for manipulating various modules based on the specified scheme.

[0040] Among them, the specified scheme is one of a plurality of different optional schemes, and the optional schemes include selecting all microservice sub-architectures, selecting all event-driven sub-architectures, and selecting part of the microservice sub-architecture and part of the event-driven sub-architecture. In one example, selecting part of the microservice sub-architecture and part of the event-driven sub-architecture, for example, the microservice sub-architecture can be selected for the control of the login module, the homepage module, the message notification module, the project management module, and the project progress list module, and the event-driven sub-architecture can be selected for the task management module, the process management module, the personnel management module, the weekly report management module, and the station letter module. In another example, selecting part of the microservice sub-architecture and part of the event-driven sub-architecture, for example, the event-driven sub-architecture can be selected for the control of the login module, the homepage module, the message notification module, the project management module, and the project progress list module, and the microservice sub-architecture can be selected for the task management module, the process management module, the personnel management module, the weekly report management module, and the station letter module. Of course, the optional scheme is not limited to this, and only two of the optional schemes are shown here as examples.

[0041] In the present 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.

[0042] In a feasible implementation, the selected designated solution may be determined in the following manner.

[0043] Figure 2 A flow chart of a method for determining a specified solution from 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.

[0044] Step S201, real-time monitoring of currently supported idle computing power.

[0045] Step S202, with only one sub-architecture for driving selected for each module as the first screening condition, with 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 with 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 solutions are screened to obtain a specified solution.

[0046] In this application, by real-time monitoring of the currently supported idle computing power, the system can ensure that the operation of each sub-architecture of the intelligent body (whether it is a microservice architecture or an event-driven architecture) does not exceed the available computing resource limits. This mechanism helps to avoid waste of resources while ensuring stable operation of the system and will not cause performance degradation or crash due to insufficient resources. This method determines the best specified solution through three clear screening conditions, which enables the system to make the best choice among multiple optional solutions.

[0047] Among them, the first screening condition ensures that each module has a unique sub-architecture to drive it, avoiding redundancy and conflict. The second screening condition ensures that the total driving computing power of the selected sub-architecture does not exceed the current idle computing power to prevent resource overload. The third screening condition is to make the total driving computing power of the selected sub-architecture as close to the idle computing power as possible on the basis of satisfying the first two conditions, so as to maximize 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 needs. In addition, this method can better cope with engineering projects of different sizes and types by dynamically selecting the solution that best suits the current resource situation, and the system can also improve performance as much as possible without sacrificing stability.

[0048] In this application, the system will check the currently available idle computing power and filter out solutions that meet the following conditions based on this computing power level: 1. For each module, choose only one sub-architecture (microservice sub-architecture or event-driven sub-architecture) to drive it.

[0049] Second, the total driver computing power required by all selected sub-architectures does not exceed the current idle computing power.

[0050] On the basis of satisfying the first two conditions, select those solutions whose required total driving computing power is closest to the idle computing power.

[0051] Normally, there is only one solution that is closest to the idle computing power, but in actual processing, there may be two or more solutions that require the same driving computing power and meet the requirement of being closest to the idle computing power. In this case, the system will proceed to the next step of comparison.

[0052] In the present application, there may be one or more optional solutions that meet various screening conditions. For these two situations, the optional solutions can be screened in the following manner to obtain a specified solution.

[0053] On the one hand, when there is only one optional solution that satisfies each screening condition, the optional solution that satisfies each screening condition may be used as the designated solution.

[0054] On the other hand, when there are at least two options that meet each screening condition, based on the total entropy gain values ​​of the at least two options, the option with the highest total entropy gain value may be selected as the designated option.

[0055] During the comparison process, the system will calculate a "total entropy gain" for each solution that meets the screening criteria. The total entropy gain represents the sum of the entropy gains generated by each sub-architecture driving the corresponding module specified in the optional solution. The entropy gain is used to characterize the driving effect of the sub-architecture driving module.

[0056] In this application, entropy gain is an indicator used to measure the effect of the sub-architecture driving module. It comprehensively considers the completion rate (P), fixed parameters (c), complexity score of the sub-architecture driving module (N), and the complexity score of the module itself (n). The higher the entropy gain, the better the efficiency and effect of the corresponding module driven by the sub-architecture.

[0057] As a feasible embodiment, the calculation formula of entropy gain is as follows: G m =P−c·N / n.

[0058] In this application, the above formula represents a relatively basic method for calculating entropy gain, where G m is the entropy gain value, P is the completion rate of the sub-architecture driving module, which reflects the success of the sub-architecture in 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, which is marked based on the scale and occupied resources of the sub-architecture, and n is the complexity score of the module, which is scored based on the complexity of the module function.

[0059] In addition, as another feasible embodiment, the calculation formula of the entropy gain is as follows: .

[0060] Among them, G mis the entropy gain value, P represents the completion rate of the sub-architecture driving module, c represents a fixed parameter, which is used to adjust the curvature of the curve 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-marked based on the size of the sub-architecture and the number of characters occupied, and n represents the complexity score of the module, which is pre-marked based on the complexity score of the function performed by the module. For example, this formula is an advanced algorithm of the previous formula, which adjusts the output value of the formula to a curve applicable to different sub-architectures by introducing the log function, wherein the curvature of the curve is adjusted by adjusting the value of c, and then the curve is adjusted to a discrete scatter plot formed by the experimental data points closest to the sub-architecture by referring to the actual performance of the sub-architecture for different modules in the experimental stage before use. Finally, the system will select the solution with the highest total entropy gain as the designated solution, that is, the 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 resource management and task execution effect evaluation, the system can select the best one among multiple possible control solutions, thereby realizing effective control over the entire life cycle of the engineering project.

[0061] In fact, the microservice sub-architecture and the event-driven sub-architecture have different focuses, execution methods, and even implementation effects. In addition to choosing between the two architectures based on computing power to ensure that the architecture is selected with the maximum computing power that can be supported, it is also possible to fix certain modules based on the actual benefits of the two architectures for certain modules, and then further adopt the above computing power screening strategy for other modules that are not set with fixed combinations. Such a result can further ensure that the best control and execution effects are achieved with the smallest possible computing power.

[0062] In this application, the intelligent agent is connected to a manual management interface. The intelligent agent uses the TensorFlow machine learning framework and deduces the control method for each module based on the specified learning process that occurs in the manual management interface.

[0063] The designated learning process includes the operation process performed by humans in the manual management interface according to the engineering control standards. For example, the operation process performed by humans in the manual management interface according to the engineering control standards is considered a designated learning process. These operation processes may include activities related to project management, such as creating projects, editing project information, assigning tasks, and adjusting task priorities. When users perform these operations on the manual management interface, the intelligent experience will record these operations and use the TensorFlow machine learning framework to analyze and learn these operation processes.

[0064] In the present application, the agent is connected to a user feedback window to receive user feedback information. In one embodiment, the agent can determine the description information input by the user feedback window based on semantic analysis, and adjust the operation mode for some or all modules based on the description information.

[0065] In this application, the intelligent agent communicates with each module based on the presentation state transfer application program interface RESTful API protocol to realize the control of each pre-deployed module.

[0066] In this application, the agent is connected to a manual management interface, which allows project managers or operators to interact directly with the agent. The agent uses 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: 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 feedback content provided by users. For example, if a user mentions that a certain function is inconvenient to use, the agent can recognize that this is feedback about the availability of the function. Based on the results of the semantic analysis, the agent will automatically adjust the operation mode for some or all modules. For example, if user feedback indicates 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 operating procedures of human managers, but also optimize itself according to user feedback to better meet user needs and improve project management efficiency and quality.

[0067] The project life cycle management method proposed in this application realizes the automated management and monitoring of the entire process from project creation to completion by integrating intelligent agents and multiple modules. This application reduces the need for manual intervention through automated means and improves the management efficiency of engineering projects. The intelligent agent can automatically match the appropriate management and control strategy according to the specific situation of the engineering project, reducing the complexity of management.

[0068] In this application, each module provides corresponding protection for different stages of the project life cycle. The login module ensures that only authorized users can access the system, enhancing data security and compliance. The personnel management module can efficiently process personnel information and ensure that accounts comply with security regulations. The homepage module analyzes and displays project data in real time, allowing managers to keep abreast of 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 timely delivery of information. The project management module provides intelligent suggestions to help project leaders manage projects more effectively. The project schedule module uses algorithms to optimize the display of the schedule, so that project leaders can clearly grasp the overall progress of the project. The task management module can automatically assign tasks according to the priority and deadline of the task to ensure that resources are used reasonably and efficiently. The process management module can automatically identify bottlenecks in the process and trigger the automatic archiving process after the process is completed, which helps to continuously improve the project process. The weekly report management module can automatically collect and organize weekly report information, reducing the workload of manually organizing reports. The internal letter module can automatically send internal letters and track the reading status of messages to ensure that important information is effectively communicated.

[0069] In addition, the agent can choose microservice architecture or event-driven architecture, or even a combination of the two, according to actual needs to adapt to engineering projects of different sizes and types. The best specified solution is determined by real-time monitoring of the currently supported idle computing power to ensure stable system operation and high resource utilization.

[0070] In addition, the agent is connected to a human management interface, which can learn and imitate the operation process performed by the human manager, and deduce the control method for each module. The agent can also receive user feedback and adjust the operation method for some or all modules accordingly to continuously improve the performance of the system.

[0071] In summary, the engineering life cycle management method provided by this application can not only significantly improve the efficiency and quality of engineering project management, but also reduce the risk of human error through intelligent means to ensure the smooth progress of the project. In addition, through flexible architecture selection and continuous learning optimization, this method can better adapt to changing workloads and business needs.

[0072] The present application also provides a system embodiment that is based on 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.

[0073] Figure 3 A block diagram of a project life cycle management system is shown in FIG. Figure 3As shown, the engineering life cycle management system 300 includes a project detection unit 301, an intelligent body control unit 302, and pre-deployed modules 303. Among them, the pre-deployed modules 303 include the following involved login module, homepage module, message notification module, project management module, project progress list module, task management module, process management module, personnel management module, weekly report management module, station letter module.

[0074] The project detection unit 301 is used to determine the target project to be controlled in response to detecting a newly generated list of engineering projects. The intelligent agent control unit 302 is used to manipulate the pre-deployed modules 303 based on the pre-configured intelligent agent to perform information control on the entire life cycle of the target project. Among them, the life cycle includes but is not limited to the access stage, the statistical stage, the information communication stage, the project processing stage, the project update stage, the task allocation stage, the process monitoring stage, the personnel management stage, the weekly report processing stage, and the station letter stage. Among them, each module 303 includes a login module, a homepage module, a message notification module, a project management module, a project progress list module, a task management module, a process management module, a personnel management module, a weekly report management module, and a station letter module. The login module is used to verify the user's identity information and ensure that only authorized users can access the system. The homepage module is used to analyze project data and generate statistical data, and display it on the homepage. The message notification module is used to automatically detect key nodes according to preset rules and notify relevant personnel in the form of station letters 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 based on the project status. The project progress summary module is used to update the project progress in real time and use algorithms to optimize the display of the progress chart. The task management module is used to automatically assign tasks according to their priority and deadline, and remind relevant personnel. The process management module is used to monitor the project process, automatically identify bottlenecks in the process, and trigger the 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 based on user needs. The internal message module is used to automatically send internal messages and track the reading status of messages.

[0075] In one embodiment, the intelligent control unit 302 includes: a microservice architecture, wherein each microservice sub-architecture is used to control each module 303. An event-driven architecture, wherein each event-driven sub-architecture is used to control each module 303. The intelligent control unit 302 selects each sub-architecture for controlling each module 303 based on a specified scheme. The specified scheme is one of a plurality of 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.

[0076] In one implementation, each microservice sub-architecture and each event-driven sub-architecture are respectively pre-marked with the driving computing power required by the driving sub-architecture, and the selected designated solution is determined in the following manner: real-time monitoring of the currently supported idle computing power. The first screening condition is that only one sub-architecture for driving is selected for each module, the second screening condition is that the total driving computing power required by the selected sub-architecture is less than or equal to the idle computing power, and the third screening condition is that the total driving computing power required by the selected sub-architecture is closest to the idle computing power. The optional solutions are screened to obtain the designated solution.

[0077] In one embodiment, the agent control unit 302 further includes: a manual management interface, the agent uses the TensorFlow machine learning framework, and based on the specified learning process that occurs in the manual management interface, deduce the control method for each module 303. The specified learning process includes the operation process that is manually executed in the manual management interface according to the engineering control standard.

[0078] In this application, the intelligent agent control unit 302 is responsible for controlling each module 303 based on the preconfigured intelligent agent to achieve information management and control throughout the life cycle. The control unit can choose a microservice architecture or an event-driven architecture to control each module 303, and can dynamically adjust the architecture used according to the current computing power situation. The intelligent 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.

[0079] In this application, the manual management interface allows manual intervention. Through the TensorFlow framework, the intelligent agent can learn from manual operations and optimize the control method.

[0080] Through the above embodiments, the present application provides an efficient and intelligent engineering life cycle management method and system, which can effectively improve the efficiency and quality of engineering project management.

[0081] Although operations are described in a particular order in the drawings, this should not be understood as requiring that the operations be performed in the particular order shown or in serial order, or that all shown operations be performed to achieve desired results. In certain circumstances, multitasking and parallel processing may be advantageous.

[0082] The methods and devices of the present application can be implemented using standard programming techniques, using rule-based logic or other logic to implement various method steps. It should also be noted that the words "device" and "module" 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.

[0083] Any steps, operations or procedures described herein may 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 including a computer-readable medium containing computer program code, which can be executed by a computer processor to perform any or all of the described steps, operations or procedures.

[0084] The foregoing description of the implementation of the present application has been given for the purpose of illustration and description. The foregoing description is not exhaustive nor is it intended to limit the present application to the exact form disclosed, and various variations and modifications may exist according to the above teachings or may be obtained from the practice of the present application. These embodiments are selected and described in order to illustrate the principles of the present application and its practical application, so that those skilled in the art can utilize the present application in various embodiments and various modifications suitable for the specific purpose contemplated.

[0085] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0086] It can be further understood that, unless otherwise specified, “connection” includes a direct connection without other components between the two, and also includes an indirect connection with other components between the two.

[0087] It is further understood that, although the operations are described in a specific order in the drawings in the embodiments of the present application, it should not be understood as requiring the operations to be performed in the specific order or serial order shown, or requiring the execution of all the operations shown to obtain the desired results. In certain environments, multitasking and parallel processing may be advantageous.

[0088] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to encompass any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the field of the present application that are not disclosed in the present application. The specification and embodiments are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following scope of rights.

[0089] It should be understood that the present application is not limited to the precise structures described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the scope of the appended claims.

[0090] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for managing the entire life cycle of an engineering project, characterized in that: The method comprises: In response to detecting a newly generated engineering project list, determining a target project to be controlled; Based on the pre-configured intelligent agent, the pre-deployed modules are controlled to perform information management and control over the entire life cycle of the target project; The life cycle includes the access phase, the statistics phase, the information transmission phase, the project processing phase, the project update phase, the task allocation phase, the process monitoring phase, the personnel management phase, the weekly report processing phase, and the internal letter phase; The modules include login module, homepage 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 internal letter module. The login module is used to verify the user's identity information and ensure that only authorized users can access the system; The homepage module is used to analyze project data and generate statistical data, which are then displayed on the homepage; The message notification module is used to automatically detect key nodes according to preset rules and notify relevant personnel through in-station messages or text messages; The project management module is used to assist project leaders in creating, editing, starting or archiving projects, and to provide intelligent suggestions based on 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 mode of the progress list; The task management module is used to automatically assign tasks according to their priorities and deadlines, and remind relevant personnel; The process management module is used to monitor the project process, automatically identify bottlenecks in the process, and trigger the automatic archiving process after the process is completed; The personnel management module is used to process 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 internal message module is used to automatically send internal messages and track the reading status of the messages.

2. The project life cycle management method according to claim 1, characterized in that: The intelligent agent includes a microservice architecture and an event-driven architecture, wherein 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; The intelligent agent selects each sub-architecture for controlling each module based on a specified scheme; wherein the specified scheme is one of a plurality of different optional schemes, and the optional schemes include selecting all of the microservice sub-architectures, selecting all of the event-driven sub-architectures, and selecting part of the microservice sub-architectures and part of the event-driven sub-architectures.

3. The project life cycle management method according to claim 2 is characterized in that: Each of the microservice sub-architectures and each of the event-driven sub-architectures is pre-marked with the driving computing power required by the driving sub-architecture, and the selected designated solution is determined in the following manner: Real-time monitoring of currently supported idle computing power; The optional solutions are screened to obtain the specified solution by selecting only one sub-architecture for driving each module as the first screening condition, 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 the total driving computing power required by the selected sub-architecture being closest to the idle computing power as the third screening condition.

4. The project life cycle management method according to claim 3 is characterized in that: The screening of the optional solutions to obtain the designated solution includes: In response to there being only one optional solution satisfying each of the screening conditions, taking the optional solution satisfying each of the screening conditions as the designated solution; In response to there being at least two optional solutions satisfying each of the screening conditions, based on the total entropy gain values ​​of the at least two optional solutions, taking the optional solution with the highest total entropy gain value as the designated solution; The total entropy gain value represents the sum of the entropy gains generated by each sub-architecture driving the corresponding module specified in the optional solution, and the entropy gain is used to characterize the driving effect of the sub-architecture driving module; The entropy gain generated by each sub-architecture driving the corresponding module is calculated using the following formula: ； Among them, G m represents the entropy 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.

5. The project life cycle management method according to claim 1, characterized in that: The intelligent body is connected to a manual management interface. The intelligent body adopts the TensorFlow machine learning framework and deduces the control method for each module based on the specified learning process that occurs in the manual management interface; wherein the specified learning process includes the operation process manually executed in the manual management interface according to the engineering control standards.

6. The project life cycle management method according to claim 1, characterized in that: The agent is connected to a user feedback window, and the agent determines the description information inputted from the user feedback window based on semantic analysis, and adjusts the operation mode for part or all of the modules based on the description information; The intelligent agent communicates with each module based on the presentation layer state transfer application program interface RESTful API protocol to realize the control of each pre-deployed module.

7. A project life cycle management system, characterized in that: The system comprises: A project detection unit, configured to determine a target project to be controlled in response to detecting a newly generated list of engineering projects; An agent control unit, for manipulating the pre-deployed modules based on the pre-configured agents, so as to perform information management and control over the entire life cycle of the target project; wherein the life cycle includes but is not limited to an access phase, a statistics phase, an information transmission phase, a project processing phase, a project update phase, a task allocation phase, a process monitoring phase, a personnel management phase, a weekly report processing phase, and an internal letter phase; wherein the modules include a login module, a homepage module, a message notification module, a project management module, a project progress list module, a task management module, a process management module, a personnel management module, a weekly report management module, and an internal letter module; The login module is used to verify the user's identity information and ensure that only authorized users can access the system; The homepage module is used to analyze project data and generate statistical data, which are then displayed on the homepage; The message notification module is used to automatically detect key nodes according to preset rules and notify relevant personnel through in-station messages or text messages; The project management module is used to assist project leaders in creating, editing, starting or archiving projects, and to provide intelligent suggestions based on 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 mode of the progress list; The task management module is used to automatically assign tasks according to their priorities and deadlines, and remind relevant personnel; The process management module is used to monitor the project process, automatically identify bottlenecks in the process, and trigger the automatic archiving process after the process is completed; The personnel management module is used to process 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 internal message module is used to automatically send internal messages and track the reading status of the messages.

8. The engineering life cycle management system according to claim 7 is characterized in that: The intelligent agent control unit comprises: Microservice architecture, where each microservice sub-architecture is used to control each module; An event-driven architecture, wherein each event-driven sub-architecture is used to control each of the modules; The intelligent control unit selects each sub-architecture for controlling each module based on a specified scheme; wherein the specified scheme is one of a plurality of different optional schemes, and the optional schemes include selecting all of the microservice sub-architectures, selecting all of the event-driven sub-architectures, and selecting part of the microservice sub-architectures and part of the event-driven sub-architectures.

9. The engineering life cycle management system according to claim 8, characterized in that: Each of the microservice sub-architectures and each of the event-driven sub-architectures is pre-marked with the driving computing power required by the driving sub-architecture, and the selected designated solution is determined in the following manner: Real-time monitoring of currently supported idle computing power; The optional solutions are screened to obtain the specified solution by selecting only one sub-architecture for driving each module as the first screening condition, 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 the total driving computing power required by the selected sub-architecture being closest to the idle computing power as the third screening condition.

10. The engineering life cycle management system according to claim 7, characterized in that: The intelligent body control unit also includes: Manual management interface, the intelligent agent adopts the TensorFlow machine learning framework, and based on the specified learning process occurring in the manual management interface, deduce the control method for each module; wherein the specified learning process includes the operation process manually executed in the manual management interface according to the engineering control standards.

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