District type engineering project management system

Abstract

The invention discloses a district type engineering project management system, which takes a main contract number as a root node, splits a project and generates a multi-level virtual number through a virtual number unit by adopting a WBS method, and marks virtual number identifiers on all workflow data marks managed by the system according to a data source; the data calculation unit can realize multi-dimensional accurate calculation of demand management, project progress, project cost, unit efficiency evaluation and the like, and supports hierarchical data summarization and penetrating check; a mirror image management unit is further arranged, a dynamic optimization unit optimizes system operation, and a visual unit assists in decision making. Besides, the system comprises an intelligent suggestion module integrated in a data calculation unit, intelligent suggestions such as risk prediction, scheme matching and optimization are provided through multi-source data processing, machine learning algorithm cluster and AIAgent cooperation, accurate identification, intelligent integration and whole-process tracking of project data are realized, and project management efficiency is improved.

Description

Technical Field

[0001] This invention belongs to the field of information technology for engineering project management, and more specifically, relates to a regional engineering project management system. Background Technology

[0002] Large-scale regional engineering projects, such as urban development and infrastructure clusters, are typically led by a general contractor, with multiple implementing companies and project departments collaborating. These projects are characterized by detailed division of labor, multiple layers, and dispersed data sources. While existing project management systems can support basic process management, they have significant shortcomings in data identification, classification, merging, and application. Traditional systems cannot effectively track the initiation, review, and execution of processes, especially in multi-departmental collaborations, where data integration and deduplication capabilities are weak. Existing numbering systems are mostly based on fixed structures, making it difficult to adapt to dynamic division of labor and hierarchical expansion, limiting the depth and breadth of data application. The lack of a unified division of labor identification mechanism makes it difficult to distinguish behavioral data from different companies within the same project, leading to duplicate statistics when pricing upwards and downwards, affecting the accuracy of economic activity analysis. The location of resource usage, such as materials and expenses, is difficult to automatically match, often relying on manual recording, which is inefficient and has a high error rate. These problems severely restrict the improvement of project management efficiency, urgently requiring a solution that can achieve accurate data identification, intelligent integration, and full-process tracking. Summary of the Invention

[0003] The main objective of this invention is to provide a regional engineering project management system. This system achieves accurate data identification by using a virtual numbering unit with the main contract number as the root node and employing a WBS method to generate multi-level virtual numbers. Combined with a multi-dimensional accurate calculation model of the data calculation unit, a virtual project department isolation and sharing mechanism of the mirror management unit, a system operation optimization strategy of the dynamic optimization unit, and the AI ​​collaboration capabilities of the intelligent suggestion module, this invention solves the problems of data identification chaos, integration difficulties, inefficient collaboration, and passive decision-making caused by the detailed division of labor, multiple levels, and dispersed data sources in large-scale regional engineering projects. It achieves full-process traceability of project data, real-time quantification of core data, and efficient collaboration among multiple stakeholders. To achieve the above objectives, this invention provides a regional engineering project management system comprising: Virtual numbering unit: The main contract number is the root node of the system; according to the task assignment or sub-contract, the project is divided into unit projects, sub-unit projects and sub-projects using the work breakdown structure method, and the system automatically generates a virtual number for each project; Data tagging and parsing unit: Data tagging: Tagging all system-managed workflow data with virtual numbers and names based on the source of project data upload; Data parsing: Sorting and calculating the required target data and transmitting it to the data calculation unit; The data calculation unit combines the data input and calculates and outputs accurate data results according to the preset calculation methods for decision-making. The preset calculation methods include: demand management calculation, project schedule calculation, project cost calculation, and unit efficiency evaluation calculation.

[0004] Furthermore, the management system also includes a mirror management unit: the workflow data included in each virtual number is mirrored to the core functions of the project management system, forming a virtual project department, and the data between virtual project departments is isolated by default.

[0005] Furthermore, the management system also includes a dynamic optimization unit that optimizes the encoding parsing path by analyzing data volume and historical execution efficiency; caches high-frequency application data to reduce redundant calculations and lower system load.

[0006] Furthermore, the project requirement management calculation of the data calculation unit includes: classifying the requirements submitted by each implementing entity into a tree structure according to the number hierarchy; implementing entities that fail to submit requirements as required and still fail to submit after being notified are defaulted to having no requirements; the superior implementing entity can obtain the requirement data of all corresponding subordinate implementing entities through the tree structure and can obtain the sum of all requirements of its subordinates.

[0007] Furthermore, the project progress calculation of the data calculation unit includes: Progress calculation for each implementing entity: according to the formula Calculation, where For the first Current progress of each implementing entity (expressed as a percentage). This represents the actual construction workload of the implementing entity. This refers to the planned construction workload (including planned workload for a specific period) corresponding to the implementing entity. Overall project schedule calculation: according to the formula Calculation, where For the overall project schedule. The total number of entities participating in the project implementation. For the first The construction weight of each implementing entity is allocated according to the importance and difficulty of the corresponding construction project, and satisfies the following conditions: .

[0008] Furthermore, the project cost calculation for the data calculation unit is as follows: ; in, For itemized planned costs, The WBS decomposition project usage is corresponding to the virtual number. The unit cost quota for the project; Formulas for calculating the actual cost of each item: ; in, For the actual cost of each item, For the first The corresponding itemized expenditures reported by each implementing entity, The total number of implementing entities participating in this sub-item; Cost deviation calculation formula: ; in, This represents the cost deviation rate; a positive value indicates overspending, and a negative value indicates savings.

[0009] Furthermore, the unit performance evaluation calculation of the data computing unit is as follows: ; in The planned schedule cost is calculated using the following method: "Planned Cost ÷ Planned Schedule" for each implementing entity in: For the itemized planned costs of this entity, For the main body's planned progress; The unit schedule cost is calculated using the method described in section [number]. The "actual cost input ÷ actual progress" of each implementing entity High efficiency, spending more than 20% less than planned, excellent cost control; : Satisfactory performance, with a good balance between cost and schedule; Inefficiency leads to cost waste.

[0010] Furthermore, the management system also includes an intelligent suggestion module, which includes: The data preprocessing unit, after data cleaning, standardization, and association mapping, provides high-quality data for algorithm computation based on historical case databases and knowledge bases. The machine learning algorithm unit includes prediction algorithms, classification and matching algorithms, optimization algorithms, and is paired with a rule engine to perform related calculations and rule execution. The Agent suggestion generation module includes an intent recognition agent, a solution optimization agent, and a natural language generation agent, which respectively realize the functions of problem intent recognition, solution optimization, and structured suggestion text generation.

[0011] Furthermore, the intelligent suggestion module is integrated into the data computing unit.

[0012] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: 1. The regional engineering project management system of the present invention uses the main contract number as the root node of the virtual numbering unit and the WBS method to generate multi-level virtual numbers. Combined with the "company-position" two-dimensional matrix, it completes data marking and parsing, and achieves the technical effect of accurate identification of project data and full-process traceability. It solves the problems of chaotic data identification and difficulty in distinguishing data from multiple subjects in traditional systems.

[0013] 2. The regional engineering project management system of the present invention uses a data calculation unit to build a multi-dimensional and accurate calculation model for demand management, project progress, project cost, and unit efficiency evaluation. It supports hierarchical data aggregation and penetrating viewing, and achieves the technical effect of real-time quantification of core project data (demand, progress, cost, efficiency) and rapid anomaly location, thereby improving the scientificity and efficiency of project management decision-making.

[0014] 3. The regional engineering project management system of the present invention forms a virtual project department by mirroring the core functions of the project management system for each virtual number through a mirror management unit. This achieves data isolation and on-demand sharing when multiple implementing entities work together, realizing the technical effect of virtualized and lightweight project management, and is suitable for the business scenario of multi-level collaboration in regional projects.

[0015] 4. The regional engineering project management system of the present invention integrates multi-source data processing, machine learning algorithm clusters and AI agent collaboration through the intelligent suggestion module to achieve the technical effects of early prediction of project risks and intelligent matching and optimization of solutions, thereby realizing the upgrade of project management mode from "passive response" to "proactive early warning and optimization". Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the structure of a regional engineering project management system according to an embodiment of the present invention.

[0017] Figure 2 This is a schematic diagram of the project engineering numbering in an embodiment of the present invention.

[0018] Figure 3 This is a schematic diagram illustrating the requirement submission process of the project management system according to an embodiment of the present invention.

[0019] Figure 4 This is a schematic diagram of the intelligent suggestion module structure of the project management system according to an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0021] Please refer to Figure 1 This embodiment provides a regional engineering project management system, including: a virtual numbering unit: with the main contract number as the system root node; based on the task assignment sheet or sub-contract, select unit project, sub-unit project or sub-project in WBS, and the system automatically generates a virtual number, which can support multi-level expansion; Please refer to Figure 2 A certain industrial park construction project was undertaken by a certain construction group. This group, or its cooperative system, includes several independent or relatively independent companies. These companies jointly participated in the collaborative performance of the same project. The group decided that company number 21 would act as the general contractor. Companies numbered 31 and 51 would act as subcontractors to company number 21 to complete the contractual tasks. Simultaneously, a private company, Universe Company (YZ), was brought in to undertake a specific professional task. Each of the aforementioned entities introduced professional subcontractors and labor subcontractors.

[0022] Therefore, the initial project number is 21AYX250001S. The system automatically generates a virtual number 21AYX250001S-00 for the project execution department of Company 21. The 00 indicates that it is executed by the project department of Company 21.

[0023] Company 31 uses this system module to virtually initiate a project, selecting its work content from the WBS (Work Breakdown Structure) decomposition of "21AYX250001S". After executing the approval process, the virtual project initiation is successful, with the virtual number "21AYX250001S-01". At this point, the system automatically generates a virtual number 21AYX250001S-01-00 for Company 31's execution project department.

[0024] Subcontractors or work groups of Company 31 can also use this system module to further break down and define their own work content, which is numbered 21AYX250001S-01-00-XX, and further subcontract or break down the work content, which is numbered 21AYX250001S-01-00-XX-XX—...

[0025] The numbering engine was used to identify and assign each step of the engineering project to its implementing unit, thus completing the data structuring of the project entity implementers.

[0026] Data Tagging and Parsing Unit: Based on the source of the project data upload, all workflow data managed by the system are tagged with virtual numbers and names; that is, all workflow data are classified into different project units, parsing units sort and calculate the target data required and transmit it to the data calculation unit; The data calculation unit combines the data input and performs calculations according to preset calculation methods to output calculation results for decision-making purposes. The preset calculation methods include: demand management calculation, project schedule calculation, project cost calculation, and unit efficiency evaluation calculation.

[0027] (1) Project Requirements Management Calculation Please refer to Figure 3 Demand calculation for data computing units The requirements submitted by each implementing entity are categorized into a tree structure according to their numbering hierarchy; the superior implementing entity can obtain the requirement data of all corresponding subordinate implementing entities through this tree structure and can obtain the sum of all requirements of its subordinates.

[0028] Taking cement as an example (this can be replaced with other materials or cost requirements). Each unit submits its cement usage requirements to the project management system. (Units that do not submit requirements after being notified are considered to have no requirements.) Based on the requirement source number, all requirements are categorized into a tree structure. Higher-level units can retrieve the cement usage requirements of all their corresponding lower-level units. The total requirements of lower-level units can be summed and calculated. This facilitates rapid resource allocation.

[0029] Higher-level units can also collect statistics on the historical, changing trends, and future forecasts of cement demand from lower-level units, promptly identify units and projects exceeding budget, and facilitate project management.

[0030] (2) Project schedule calculation The data calculation unit calculates project progress, including the overall project progress and the progress of each unit.

[0031] Each unit calculates its current construction progress (percentage) based on its construction plan and current construction status.

[0032] The overall project schedule is calculated by multiplying the schedule of each unit by its corresponding construction weight. The construction weight is allocated according to the importance of each unit's construction project. The more important and difficult the construction project, the greater the weight it is assigned. The total weight of all units is 1.

[0033] The current progress of each unit under the plan (e.g., the progress set under the quarterly plan) (for projects divided into parts), that is, the actual construction of each unit in the current quarter divided by the planned construction of the current quarter. (Record the construction status of each unit under the historical plan).

[0034] (3) Project cost calculation Project cost calculation, including: itemized cost accounting and deviation analysis. Calculation logic: Basic data: the quantity of work corresponding to each virtual number (obtained from WBS decomposition), the unit cost quota for the quantity of work (e.g., 5,000 yuan per ton for steel bars and 300 yuan per ton for cement), and the actual cost expenditure (e.g., material procurement costs and labor costs). Calculation formula: Itemized planned cost = Quantity of work × Cost quota; Itemized actual cost = Total expenditure reported by all implementing entities; Cost deviation = (Actual cost - Planned cost) / Planned cost × 100%; Hierarchical statistics: Costs are summarized in layers according to "Master Contract Number → Company Level → Project Department Level → Subcontractor Level", and superiors can view the cost details of subordinates.

[0035] Application value: Quickly identify sub-projects that are over-cost or under-cost (such as "21AYX250001S-01" where the cost of subcontracted steel reinforcement exceeds the budget by 8%), providing a basis for cost optimization.

[0036] Cost forecasting calculation logic: Percentage of completed costs = Total completed costs of individual items / Total planned costs of individual items; Remaining cost forecast = Unfinished itemized cost × Percentage of completed cost (if the percentage is greater than 1, adjust by 1.1 times to account for overspending risk). Total cost forecast = Actual cost already completed + Remaining cost forecast.

[0037] Application value: Predict in advance whether the total project cost will exceed the budget, and if the overspending is predicted.

[0038] Traditional performance evaluation only considers a single indicator such as cost or schedule. This algorithm introduces a "cost-schedule matching coefficient" and, combined with the hierarchical characteristics of virtual numbering, supports penetrating analysis from "subcontractor level → company level → project master level".

[0039] (4) Calculation of project effectiveness Unit schedule cost : No. The "actual cost input ÷ actual progress" of each implementing entity in: For the first The actual cost of each entity (taken from the system cost calculation module). This represents the current progress (percentage, taken from the system progress calculation module) of the subject.

[0040] Planned schedule cost : No. "Planned Cost ÷ Planned Schedule" for each implementing entity in: For the itemized planned costs of this entity, This refers to the planned progress of the entity (such as the quarterly planned progress).

[0041] Key performance indicator: Cost-schedule matching coefficient ; High efficiency (actual progress completed is more than 20% less than planned, with excellent cost control); : Satisfactory performance (good cost-to-schedule ratio); Inefficiency (the actual progress completed takes more than 20% longer than planned, resulting in wasted costs).

[0042] Company-level efficiency in: This refers to the number of subcontractors or project departments under the company. For the first The cost weight of each subordinate entity (allocated according to the proportion of its planned cost to the company's total planned cost).

[0043] Please refer to Figure 4 The intelligent suggestion module includes a data preprocessing unit and a machine learning algorithm unit. The agent suggestion generation module... The intelligent suggestion module relies on a multi-source data access component to provide data: the multi-source data access component supports the access of structured data (virtual numbering system data, cost, schedule, performance calculation results, contract terms, inventory data) and unstructured data (construction logs, equipment operation records), and uses API interfaces, database synchronization, Internet of Things (IoT) data collection and other methods to ensure data real-time performance.

[0044] Historical Case Library and Knowledge Base: Stores 100+ similar regional project management cases, industry standards, construction specifications, and cost quotas. A vector database is used to improve case matching efficiency and provide reference for suggestion generation.

[0045] The data preprocessing module provides high-quality data for algorithm calculations through data cleaning (removing outliers), standardization (unifying data formats and units), and association mapping (establishing a "data-responsible entity-construction stage" association based on virtual numbering).

[0046] Machine learning algorithm unit: Predictive algorithms: LSTM (Long Short-Term Memory) networks are used to predict cost overrun trends and schedule delay risks. The model is trained based on historical data. Classification and matching algorithms: The random forest algorithm is used to identify problem types (such as classification of reasons for cost overruns), and the KNN algorithm is used to match successful cases of similar projects and recommend reusable measures.

[0047] Optimization Algorithm: The genetic algorithm is used to optimize the resource allocation scheme, and the critical path method (CPM) is combined to adjust the construction schedule to maximize resource utilization efficiency.

[0048] Rule Engine: Based on predefined hard and flexible rules for business scenarios, rule configuration and execution are implemented using Tencent Cloud TSF rule engine components or Serverless Workflow. Hard rules include compliance constraints (such as "the deviation rate of subcontracting requirements shall not exceed ±10%)" and security standards; flexible rules include optimization priorities (such as "low-cost, high-return measures are given priority") and responsibility division specifications.

[0049] Agent Collaboration Module: Integrates a small AIAgent responsible for intent recognition (identifying the core pain points of the project), suggestion optimization (adjusting suggestion details according to project scale and collaboration mode), and natural language generation (converting algorithm results into easy-to-understand and structured suggestion text).

[0050] Preferably, the intelligent suggestion module is integrated into the data computing unit.

[0051] The management system also includes a mirror management unit: the workflow data included in each virtual number is mirrored to the core functions of the project management system, forming a virtual project department, and the data between virtual project departments is isolated by default.

[0052] The proposed project team structure includes: a workflow data mirroring of the core functional modules of the project management system for each virtual number, including schedule management, cost management, requirements management, document management, and collaborative approval, forming an independent virtual project team operation interface; Data is isolated between virtual project departments by default, and they can only access data associated with their own number; cross-virtual project department data sharing configuration is supported, and necessary data exchange between superiors and subordinates and collaborating units can be achieved through permission approval; Data from different virtual project departments (such as progress data, cost expenditures, and requirement records) are independent of each other by default, and each department can only access data associated with its own virtual ID. For example, the virtual project department of Company 31 cannot directly view the cost details of Company 51, thus preventing data leakage or misoperation from the source.

[0053] The management system also includes a dynamic optimization unit that optimizes the code parsing path by analyzing data volume and historical execution efficiency; caches high-frequency application data to reduce redundant calculations and lower system load.

[0054] Encoding and parsing optimization: Track parsing QPS, average time consumption, and success rate; generate JSON pre-compiled templates for high-frequency paths; segment parsing complex numbers; adapt to preset rules for abnormal scenarios; and deploy on a single node.

[0055] Intelligent caching strategy: Three-level cache (local memory + single-machine Redis + file server), core data is updated immediately after writing, non-core data is refreshed periodically, sharded by virtual number + data type, and timestamp comparison is used to avoid dirty reads.

[0056] Load balancing methods: Monitor CPU, memory, database connection count, and task queue length; when under high load, pause low-priority tasks, merge duplicate calculations, implement rate limiting, and manually scale up to adapt to the project cycle.

[0057] The preferred project management system for this project is equipped with a visual interface to facilitate decision-makers in making clear and reasonable decisions.

[0058] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A regional engineering project management system, characterized in that, include: Virtual numbering unit: The main contract number is the root node of the system; Based on the task assignment sheet or contract, the project is divided into unit projects, sub-unit projects, and sub-projects using the work breakdown structure method. The system automatically generates a virtual number for each project. Data tagging and parsing unit: Data tagging: Based on the source of the project data upload, all workflow data managed by the system are tagged with virtual numbers and names; Data parsing involves sorting and calculating the target data required and transmitting it to the data processing unit. Data computing unit; Based on the input data, the system performs calculations according to a preset calculation method and outputs the results for decision-making purposes. The preset calculation methods include: demand management calculation, project schedule calculation, project cost calculation, and unit performance evaluation calculation.

2. The regional engineering project management system according to claim 1, characterized in that, The management system also includes a mirror management unit: the workflow data included in each virtual number is mirrored to the core functions of the project management system, forming a virtual project department, and the data between virtual project departments is isolated by default.

3. The regional engineering project management system according to claim 1, characterized in that, The management system also includes a dynamic optimization unit that optimizes the encoding parsing path by analyzing data volume and historical execution efficiency; caches high-frequency application data to reduce redundant calculations and lower system load.

4. The regional engineering project management system according to claim 1, characterized in that, The project requirement management calculation of the data calculation unit includes: classifying the requirements submitted by each implementing entity into a tree structure according to the number hierarchy; the superior implementing entity can obtain the requirement data of all corresponding subordinate implementing entities through the tree structure and can obtain the sum of all requirements of its subordinates.

5. The regional engineering project management system according to claim 1, characterized in that, The project progress calculation of the data calculation unit includes: Progress calculation for each implementing entity: according to the formula Calculation, where For the first The current progress of each implementing entity This represents the actual construction workload of the implementing entity. This refers to the planned construction workload (including planned workload for a specific period) corresponding to the implementing entity. Overall project schedule calculation: according to the formula Calculation, where The total project progress (expressed as a percentage). The total number of entities participating in the project implementation. For the first The construction weight of each implementing entity is allocated according to the importance and difficulty of the corresponding construction project, and satisfies the following conditions: .

6. The regional engineering project management system according to claim 1, characterized in that, The project cost calculation for the data calculation unit is as follows: ； in, For itemized planned costs, The WBS decomposition project usage is corresponding to the virtual number. The unit cost quota for the project; Formulas for calculating the actual cost of each item: ； in, For the actual cost of each item, For the first The corresponding itemized expenditures reported by each implementing entity, The total number of implementing entities participating in this sub-item; Cost deviation calculation formula: ； in, This represents the cost deviation rate; a positive value indicates overspending, and a negative value indicates savings.

7. The regional engineering project management system according to claim 1, characterized in that, The unit performance evaluation calculation of the data calculation unit includes: ; in The planned schedule cost is calculated using the following method: "Planned Costs ÷ Planned Schedule" for each implementing entity in: For the itemized planned costs of this entity, For the main body's planned progress; The unit schedule cost is calculated using the method described in section [number]. The "actual cost input ÷ actual progress" of each implementing entity ; High efficiency, spending more than 20% less than planned, excellent cost control; : Satisfactory performance, with a good balance between cost and schedule; Inefficiency leads to cost waste.

8. The regional engineering project management system according to claim 1, characterized in that, The management system further includes an intelligent suggestion module, which includes: The data preprocessing unit, after data cleaning, standardization, and association mapping, provides high-quality data for algorithm computation based on historical case databases and knowledge bases. The machine learning algorithm unit includes prediction algorithms, classification and matching algorithms, optimization algorithms, and is paired with a rule engine to perform related calculations and rule execution. The Agent suggestion generation module includes an intent recognition agent, a solution optimization agent, and a natural language generation agent, which respectively realize the functions of problem intent recognition, solution optimization, and structured suggestion text generation.

9. A regional engineering project management system according to claim 8, characterized in that, The intelligent suggestion module is integrated into the data computing unit.

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