Engineering design full-process intelligent management and control method, device, equipment and medium

Abstract

The invention relates to an engineering design whole-process intelligent management and control method and device, equipment and a medium. The method comprises the steps that related information for an engineering construction project is acquired; constructing a main plan and a plurality of sub-plans of the engineering construction project according to project requirements; generating a reference curve, a prediction curve and an actual curve according to the main plan, the plurality of sub-plans and the related information; determining cumulative completion percentages corresponding to the reference curve, the prediction curve and the actual curve corresponding to the same time point, and calculating a deviation value according to all the cumulative completion percentages; and performing early warning and dynamic regulation and control on the project progress of the engineering construction project according to the deviation value. By means of the method, second-level quantification of progress deviation and automatic closed loop of risk tasks are achieved, and the accuracy, real-time performance and cooperation efficiency of full-cycle design management of petroleum engineering are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of engineering project management, in particular, the present application relates to an engineering design whole-process intelligent management and control method, device, equipment and medium. BACKGROUND

[0002] In the prior art, although some achievements have been made in the digital transformation of petroleum engineering, a digital collaborative and visual management and control system covering the whole process has not yet been formed. Therefore, it is necessary to establish a whole-process digital project management system to strictly coordinate the business of PMC, supervision and detection on a complete, digital, visual and intelligent platform, so as to achieve the goals of improving work quality, work efficiency, one-key delivery of completion data and empowering business through a digital platform.

[0003] However, in the engineering design management of the current digital project management system, the review process relies on manual transmission of files, the opinion feedback and risk identification are separated, and the progress tracking lacks automatic early warning, resulting in low efficiency and serious information island problem. The existing project design management system mainly has the following defects: the review opinion cannot be structured to associate risk and progress data; the design change impact analysis relies on manual experience and lacks data linkage; risk identification and task assignment need to be operated across systems, and the collaboration is insufficient.

[0004] In the traditional engineering project management system: the design review, progress management, risk management and change management function modules run independently, the review opinion cannot be structured to associate risk and progress data, the design change impact analysis relies on manual experience and lacks data linkage, the risk identification and task assignment need to be operated across systems, and the collaboration is insufficient. The progress tracking relies on manual statistics and lacks automatic early warning mechanism, cannot detect the progress deviation in real time, the progress report generation efficiency is low, and cannot be dynamically updated. A single design change needs to be manually recalculated for multiple associated tasks, and the change impact evaluation lacks quantitative analysis tools.

[0005] For example, in the prior art CN116611792A, only the structured review opinion and task assignment are implemented, the opinion is not automatically linked with progress, risk and cost data, there is a lack of S-curve quantitative deviation, multi-level early warning, change impact back calculation and cross-organization resource scheduling function, it still relies on manual secondary processing, and cannot solve the core needs of petroleum engineering whole-process digital collaboration and one-key completion delivery. CN110163509A only realizes the electronic circulation of design files and review opinions, does not establish a quantitative linkage mechanism of opinion-risk-progress-change, lacks S-curve automatic deviation calculation, multi-level early warning, resource rescheduling and cross-subject collaborative instruction, and the progress tracking and design change still rely on manual statistics and experience estimation, and cannot form a petroleum engineering whole-cycle digital closed-loop management and control.

[0006] Thus, the prior art realizes partial digitization, but still has the problems of review opinions and risks, progress data fragmentation, design change relying on manual experience evaluation, progress tracking without automatic early warning, serious information island, lack of full-process quantitative linkage and cross-organization collaboration mechanism, and difficulty in meeting the requirements of oil engineering full-cycle digitalization collaboration and one-key completion delivery. SUMMARY

[0007] The technical problem to be solved by the present application is to provide an engineering design full-process intelligent management and control method, device, equipment and medium, aiming to solve at least one of the above technical problems.

[0008] In a first aspect, the technical solution of the present application to solve the above technical problems is as follows: an engineering design full-process intelligent management and control method, comprising: obtaining related information for the engineering construction project, the related information including at least one of a delivery file list TDR, a review opinion, a design change, a risk event and an actual progress; constructing a main plan and a plurality of sub-plans of the engineering construction project according to the project requirements, the latest completion time corresponding to the plurality of sub-plans being not greater than the planned completion time of the main plan; generating a baseline curve, a prediction curve and an actual curve according to the main plan, the plurality of sub-plans and the related information, the baseline curve being a progress line calculated according to the originally formulated planned completion time in the engineering construction project, the prediction curve being a progress line calculated according to the currently latest reported predicted completion time of the engineering construction project, and the actual curve being a progress line calculated according to the time stamp of the files or tasks that have been actually completed in the engineering construction project; determining the respective cumulative completion percentages of the baseline curve, the prediction curve and the actual curve corresponding to the same time point, and calculating a deviation amount according to all the cumulative completion percentages; warning and dynamically regulating the project progress of the engineering construction project according to the deviation amount.

[0009] The present application has the beneficial effects that: by obtaining TDR, review opinions, design changes, risk events and actual progress and other multi-source data at one time, constructing a main-sub plan, and generating a baseline curve, a prediction curve and an actual curve with rigid time constraints, the cumulative completion percentages and the deviation amount can be automatically calculated at the same time point based on the three curves, and then the warning and dynamic regulation are triggered, thereby breaking the information island among review, progress, risk and change, realizing the second-level quantification of progress deviation and the automatic closed loop of risk tasks, and significantly improving the accuracy, real-time performance and collaboration efficiency of oil engineering full-cycle design management.

[0010] On the basis of the above technical solution, the present application can also be improved as follows.

[0011] Further, the project progress of the engineering construction project is prewarned and dynamically regulated according to the deviation, including: When the deviation exceeds the preset threshold, a prewarning information is generated, and corresponding risk items, task reassignment and resource rescheduling instructions are generated according to the deviation; and the risk closed loop, responsibility reassignment and resource supplement of the lag task are executed according to the risk items, task reassignment and resource rescheduling instructions.

[0012] Further, the deviation includes a first deviation and a second deviation, wherein: The first deviation = cumulative completion percentage corresponding to the reference curve - cumulative completion percentage corresponding to the actual curve; The second deviation = cumulative completion percentage corresponding to the reference curve - cumulative completion percentage corresponding to the predicted curve.

[0013] Further, the preset threshold includes a first threshold interval and a second threshold interval, for any one of the first deviation and the second deviation, wherein: When the deviation is in the first threshold interval, a first prewarning information is generated and pushed to the task person in charge; When the deviation is in the second threshold interval and greater than the upper limit of the first threshold interval, a second prewarning information is generated and synchronously pushed to the task person in charge, the supervisor and the project manager. Further, the main plan and the plurality of sub-plans of the engineering construction project are constructed according to the project requirements, including: The project overall target, milestone node and stage division requirement of the engineering construction project are acquired, and all control nodes of the engineering construction project are determined; Based on the work breakdown structure, the main plan covering the whole cycle of the project is constructed with the milestone node as an anchor point, and the planned completion time of each key control node is determined; According to the key control node in the main plan, in combination with the professional division, device unit and task attribute, the plurality of sub-plans are recursively decomposed and formed.

[0014] Further, the cumulative completion percentages corresponding to the reference curve, the predicted curve and the actual curve at the same time point are determined, including: A first task set that should be completed before the same time point is acquired, a reference weight sum is obtained by accumulating the task weight of each task in the first task set, the percentage of the reference weight sum in the project total weight of the engineering construction project is calculated, and the cumulative completion percentage corresponding to the reference curve is obtained; A second task set that should be completed according to the latest prediction before the same time point is acquired, a predicted weight sum is obtained by accumulating the task weight of each task in the second task set, the percentage of the predicted weight sum in the project total weight of the engineering construction project is calculated, and the cumulative completion percentage corresponding to the predicted curve is obtained; The third task set actually completed before the same time point is obtained, a task weight of each task in the third task set is accumulated to obtain an actual weight sum, a percentage of the actual weight sum in a total weight of the engineering construction project is calculated to obtain a cumulative completion percentage corresponding to the actual curve.

[0015] Further, for any one of the first task set, the second task set and the third task set, the determination of the task weight of each task in the task set comprises: at least one quantitative index corresponding to each task in any one of the task sets is obtained, the at least one quantitative index including an engineering quantity, a man-hour or a contract amount; the at least one quantitative index is normalized to obtain a normalized weight coefficient; the normalized weight coefficient is taken as a percentage of each task relative to the total weight of the project to obtain the task weight of each task.

[0016] In a second aspect, the present application also provides an engineering design whole-process intelligent management and control device to solve the above technical problems, the device comprising: an acquisition module configured to acquire relevant information of the engineering construction project, the relevant information including at least one of a TDR, an examination opinion, a design change, a risk event and an actual progress; a plan generation module configured to construct a master plan and a plurality of sub-plans of the engineering construction project according to a project requirement, a latest completion time corresponding to the plurality of sub-plans being not greater than a plan completion time of the master plan; a curve generation module configured to generate a benchmark curve, a prediction curve and an actual curve according to the master plan, the plurality of sub-plans and the relevant information, the benchmark curve being a progress line calculated according to an originally formulated plan completion time in the engineering construction project, the prediction curve being a progress line calculated according to a currently latest reported predicted completion time of the engineering construction project, and the actual curve being a progress line calculated according to a time stamp of a file or a task actually completed in the engineering construction project; a deviation amount calculation module configured to determine a cumulative completion percentage corresponding to each of the benchmark curve, the prediction curve and the actual curve corresponding to a same time point, and to calculate a deviation amount according to all the cumulative completion percentages; a management module configured to perform early warning and dynamic regulation and control on a project progress of the engineering construction project according to the deviation amount.

[0017] In a third aspect, the present application also provides an electronic device to solve the above technical problems, the electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the engineering design whole-process intelligent management and control method of the present application when executing the computer program.

[0018] In a fourth aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the intelligent management and control method for the whole process of engineering design.

[0019] Additional aspects and advantages of the application will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following and / or can be learned by practice of the application. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments of the present application will be briefly introduced.

[0021] Figure 1 A flowchart of an intelligent management and control method for the whole process of engineering design provided by an embodiment of the present application; Figure 2 A business process diagram provided by an embodiment of the present application; Figure 3 A data flow diagram provided by an embodiment of the present application; Figure 4 A data cleaning flowchart provided by an embodiment of the present application; Figure 5 A curve generation technical flowchart provided by an embodiment of the present application; Figure 6 A progress early warning flowchart provided by an embodiment of the present application; Figure 7 An interface diagram of a new early warning rule provided by an embodiment of the present application; Figure 8 An early warning rule configuration interface diagram provided by an embodiment of the present application; Figure 9 A field list diagram provided by an embodiment of the present application; Figure 10 A structural diagram of an intelligent management and control device for the whole process of engineering design provided by an embodiment of the present application; Figure 11 A structural diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0022] The principles and features of the present application are described below, and the examples are only used to explain the present application, and are not used to limit the scope of the present application.

[0023] The technical solutions of the present application and how the technical solutions solve the above technical problems will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes can not be described again in some embodiments. The embodiments of the present application will be described below with reference to the accompanying drawings.

[0024] The scheme provided by the embodiments of the present application can be applied to any application scenario that needs to warn the progress of an engineering construction project. The scheme provided by the embodiments of the present application can be executed by any electronic device, such as a terminal device of a user, including at least one of the following: a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, a smart television, and a smart vehicle-mounted device.

[0025] The embodiments of the present application provide a possible implementation manner, as shown in Figure 1 A flowchart of an intelligent management and control method for the whole process of engineering design is provided, and the scheme can be executed by any electronic device, for example, a terminal device, or jointly executed by a terminal device and a server. For the convenience of description, the method provided by the embodiments of the present application will be described below with the terminal device as an execution subject, as shown in the flowchart in Figure 1 The method can include the following steps: S10, obtaining related information for an engineering construction project, the related information including at least one of a turnover document list TDR, an examination opinion, a design change, a risk event, and an actual progress; S20, constructing a main plan and a plurality of sub-plans of the engineering construction project according to a project requirement, the latest completion time corresponding to the plurality of sub-plans being not greater than the planned completion time of the main plan; S30, generating a baseline curve, a prediction curve, and an actual curve according to the main plan, the plurality of sub-plans, and the related information, the baseline curve being a progress line calculated according to the originally formulated planned completion time in the engineering construction project, the prediction curve being a progress line calculated according to the currently latest reported predicted completion time of the engineering construction project, and the actual curve being a progress line calculated according to the time stamp of the file or task that has been actually completed in the engineering construction project; S40, determining the respective cumulative completion percentages corresponding to the baseline curve, the prediction curve, and the actual curve at the same time point, and calculating a deviation amount according to all the cumulative completion percentages; S50, warning and dynamically regulating and controlling the project progress of the engineering construction project according to the deviation amount.

[0026] The method of this invention acquires multi-source data such as TDR, review comments, design changes, risk events, and actual progress in one go, constructs master-sub-plans, and generates three curves—a baseline curve, a forecast curve, and an actual curve—based on these three curves. Based on these three curves, the cumulative percentage of completion and deviation can be automatically calculated at the same point in time, thereby triggering early warnings and dynamic adjustments. This breaks down the information silos between review, progress, risk, and change, achieving second-level quantification of progress deviations and automatic closed-loop management of risk tasks, significantly improving the accuracy, real-time performance, and collaborative efficiency of the entire lifecycle design management of petroleum engineering.

[0027] The following specific embodiments further illustrate the solution of the present invention. In this embodiment, in order to solve the above-mentioned technical problems, the present invention provides an intelligent management and control method for the entire process of engineering design. By constructing a full-cycle digital management platform, covering the entire process from preliminary consultation, overall design, basic design to detailed design of the project, the present invention achieves data interconnection, automated early warning and cross-functional collaboration, thereby improving the efficiency of engineering project management and risk control capabilities.

[0028] Based on this, the intelligent management and control method for the entire engineering design process provided in this embodiment may include the following steps: S10, Obtain relevant information for the engineering construction project, including at least one of the following: the deliverables list (TDR), review comments, design changes, risk events, and actual progress. The Delivery Documents (TDR) list refers to the complete list of deliverables, including drawings, models, and specifications, compiled by the design, procurement, and construction parties according to their respective specialties and installations, along with their planned / actual submission dates. Review comments refer to all modifications or reservations made online by the supervisor, PMC, and owner regarding the design documents, including verification, review, approval, and online submissions of comments on the design documents. Design changes refer to design change requests, change orders, and accompanying adjustments to quantities, costs, and schedules submitted by the contractor and approved by the owner / PMC. Risk events refer to potential issues selected during the review process or records of external QHSE, supply, or construction condition changes registered as risk items. Actual progress refers to the "completed work this week / month and cumulative percentage of completion" submitted online by the construction unit and signed by the supervisor, along with the actual approval timestamp of the documents.

[0029] External technical data can be processed to obtain engineering construction project information as follows: Format parsing: First, read the XML / JSON to extract core information such as task ID, start / finish time, and sequence relationship; 2. Field Mapping: A lookup table of "external fields ↔ system standard fields" is used to automatically align fields and solve the problem of inconsistent field names across different software. 3. Conflict check: automatically scan for logical errors such as duplicate IDs, time reversal, closed-loop dependencies, etc., and generate a check report with correction suggestions as an engineering construction project.

[0030] S20, according to the project requirements, constructing a master plan and multiple sub-plans of the engineering construction project, the latest completion time of the multiple sub-plans corresponding to the master plan is not greater than the planned completion time of the master plan; The master plan includes construction nodes, key milestones, etc., and the multiple sub-plans can be design sub-plans, procurement sub-plans, etc. The key milestones are major nodes in the engineering construction project that have a decisive influence on the overall progress, such as overall design approval, basic design completion, first batch of detailed design delivery, long-cycle equipment procurement order signing, construction commencement, mechanical completion, intermediate handover, and completion acceptance, etc. These nodes have clear time requirements and cannot be easily changed, and are the core basis for preparing the master plan and controlling the overall progress of the project.

[0031] Optionally, one implementation of the above S20 is: S201, obtaining project overall goals, milestone nodes, and stage division requirements of the engineering construction project, and determining all control nodes of the engineering construction project; S202, based on the work breakdown structure, taking the milestone nodes as anchor points, constructing a master plan covering the whole cycle of the project, and determining the planned completion time of each key control node; S203, according to the key control nodes in the master plan, combining professional division, device unit, and task attributes, recursively decomposing to form multiple sub-plans.

[0032] The milestone node is a time point on the project timeline that marks the formal completion of a stage or important achievement, and its characteristics are not consuming significant duration, quantifiable delivery, and being clearly defined by contract or management system, which is used to measure, control and report the overall progress of the project. The stage division requirement refers to dividing the whole process of the project into several manageable, acceptable, and deliverable time segments or work stages (such as pre-consultation→overall design→basic design→detailed design→procurement→construction→completion) according to the characteristics of the project, contract scope and regulatory standards, and clearly defining the start and end time, delivery results, responsible subject and approval requirements of each stage, so as to subsequently prepare the master plan, set the milestones and control the progress.

[0033] The control node is a wide range of time points or events in the project plan that need to be monitored and may trigger early warnings. The critical control node is a subset of the most rigid and non-floating nodes that directly affect the total duration and trigger escalation warnings and resource reallocation once delayed. Once the calendar date is written into the contract or the reply document, any party cannot move it unilaterally, and there is no buffer. Even if it is only one day, it must be reported, escalated, and measures such as catch-up or claim must be taken, which is equivalent to a legal / commercial deadline.

[0034] Among them, the professional division refers to the "work type dimension" divided according to engineering disciplines, such as process, piping, civil engineering, electrical, instrumentation, heating and ventilation, water supply and drainage, and fire protection.

[0035] The device unit refers to the "space / system dimension" divided according to the production process or physical area, such as the atmospheric-vacuum distillation unit, catalytic cracking unit, storage tank area, utility station, and power distribution station.

[0036] The task attribute refers to the "management tag" attached to the specific task, such as design / review / audit, procurement / construction, long cycle / non-long cycle, critical path / non-critical path, high risk / low risk, etc., which is used for subsequent sequencing, weighting, task allocation, and early warning.

[0037] Therefore, according to the key control nodes in the main plan, combined with professional division, device unit, and task attribute, the application scheme recursively decomposes to form multiple sub-plans. Specifically, the key control nodes with the strongest rigidity and non-floating in the main plan are used as time constraints, and the three-dimensional granularity of each professional, device unit, and task attribute is used to recursively split the main plan into secondary and tertiary sub-plans from top to bottom, ensuring that the latest completion time of each sub-task is less than or equal to the corresponding key control node, forming a time closed loop that cannot be broken.

[0038] Optionally, in S202, based on the work breakdown structure, the specific implementation process of the main plan covering the whole project cycle is constructed with the milestone node as the anchor point. Based on the project WBS (Work Breakdown Structure) hierarchical model, a "milestone anchoring-task decomposition" two-step method is used. First, generate the main plan skeleton with the construction node, key milestone, or any milestone node as the anchor point (such as formula 1); then, through recursive decomposition algorithm (such as formula 2), the main plan is decomposed into design, procurement, and other sub-plans, ensuring that the time nodes of the sub-plans and the main plan have rigid constraints (the completion time of the sub-plan is less than or equal to the corresponding node time of the main plan). The key milestone is the "hard core subset" in the milestone node: all key milestones are milestone nodes, but only those milestone nodes that determine the total project duration, are written into the contract or reply, and cannot be postponed are called key milestones; the rest of the negotiable adjustment milestone nodes belong to ordinary milestone nodes.

[0039] Formula 1: Weight of milestone anchor point = (node importance x influence range) / total project duration; Formula 2: Sub-plan task set = main plan task set x decomposition coefficient (decomposition coefficient is dynamically adjusted according to professional relevance, range 0.3-0.8); Among them, the node importance is a quantitative index to measure the influence degree of a certain milestone (or control node) on the overall goal of the project, reflecting the impact size of the node delay on the total duration, total cost or critical path, which can be set in advance. Influence range refers to "how many subsequent tasks will be affected on the time axis once the node is delayed", which is expressed by the proportion of the sum of the weights of all tasks affected by the delay to the total weight of the project. The larger the proportion, the wider the chain reaction of node delay, and the greater the impact on the overall progress.

[0040] Optionally, in the scheme of the present application, for each task corresponding to the main plan and / or sub-plan, a "role-task" bipartite graph matching algorithm can also be used to automatically recommend the responsible person and supervisor corresponding to the task by calculating the cosine similarity of the required skill label of the task and the user role label (such as formula 3), wherein the time node is calculated by the critical path method (CPM) to ensure that the earliest start time (ES) and the latest end time (LF) of the sub-plan task meet the main plan constraints.

[0041] Formula 3: Similarity = (task skill vector x user role vector) / (|| task skill vector || x || user role vector ||); Among them, the task skill vector is to encode all professional abilities required for a task (such as "process simulation, pressure vessel design, AutoCAD, ASPEN modeling") into a set of fixed dimension, calculable numerical vectors (one-hot or embedded vectors), and the user role vector is a fixed dimension numerical vector formed by digitizing the professional skills, qualifications, work experience and other information possessed by each user (designer, reviewer, auditor, etc.).

[0042] S30, generating a benchmark curve, a prediction curve and an actual curve according to the master plan, the plurality of sub-plans and the related information, the benchmark curve being a progress line calculated according to a time to complete originally formulated in the engineering construction project, the prediction curve being a progress line calculated according to a latest reported expected completion time of the engineering construction project, and the actual curve being a progress line calculated according to a time stamp of a file or a task that has been actually completed in the engineering construction project; The latest reported expected completion time is a "desired completion time" that is manually updated by a responsible person (or a progress engineer) in the system and verified and published for the last time; it is refreshed every week along with the progress of the site, and is used to replace the original plan date to drive real-time recalculation of the prediction curve.

[0043] The time of the file or the task that has been actually completed can be referred to as an actual completion time, and can be determined by a delivery file list TDR. Specifically, the delivery file list (TDR) is imported into an Excel template, the file coding rules are automatically checked, and the actual completion time is monitored; a responsible person (such as a professional engineer) feeds back the progress state online to ensure real-time data updating.

[0044] Specifically, based on a multi-mode matching algorithm of a regular expression engine, a regular template library (such as ^ [A-Z] {4} -\ d {4} -\ d {3} ) can be predefined for different professional file coding rules (such as a process professional "PROC-YYYY-NNN" and a pipeline professional "PIPE-YYYY-NNN"), the file coding of the imported delivery file list TDR is batch-verified by an Aho-Corasick multi-mode matching algorithm (time complexity O (n), n is the file coding length), and the abnormal coding is automatically marked and prompted with the highest matching degree of the standard template. An "event triggering-delta synchronization" mechanism is adopted. When a responsible person feeds back the progress state (such as "has started", "under review" and "has completed"), the state machine conversion algorithm (such as Figure 2 ) is used to update the task state, and a delta synchronization program is triggered to synchronize only the changed fields (such as the actual completion time and the state code) to the database, so as to avoid full data transmission, and the synchronization delay is ≤100 ms. Optionally, one implementation manner of the above S30 is: S301, obtaining a first task set that should be completed before a same time point, accumulating the task weights of each task in the first task set to obtain a benchmark weight sum, calculating a percentage of the benchmark weight sum in a total weight of the engineering construction project to obtain a cumulative completion percentage corresponding to the benchmark curve; S302, obtain a second task set that is predicted to be completed at a current latest time point before the same time point, accumulate the task weight of each task in the second task set to obtain a predicted weight sum, calculate the percentage of the predicted weight sum in the total weight of the project construction project, and obtain the cumulative completion percentage corresponding to the predicted curve; S303, obtain a third task set that is actually completed before the same time point, accumulate the task weight of each task in the third task set to obtain an actual weight sum, calculate the percentage of the actual weight sum in the total weight of the project construction project, and obtain the cumulative completion percentage corresponding to the actual curve.

[0045] Optionally, for any one of the first task set, the second task set and the third task set, the determination of the task weight of each task in the above task set comprises: obtaining at least one quantitative index corresponding to the engineering quantity, the man-hour or the contract amount of each task in any one of the task sets; normalizing the at least one quantitative index to obtain a normalized weight coefficient; using the normalized weight coefficient as the proportion of each task relative to the total weight of the project to obtain the task weight of each task.

[0046] S40, determining the cumulative completion percentages corresponding to the reference curve, the predicted curve and the actual curve respectively at the same time point, and calculating a deviation amount according to all the cumulative completion percentages; The reference curve can be determined based on the following method: Based on the planned completion time, the cumulative progress at any time point is calculated by a linear interpolation algorithm (such as formula 5); Formula 5: Cumulative completion percentage (t) = ∑ (planned task weight before t) / total weight × 100%; The predicted curve can be determined based on the following method: According to the predicted completion time of the TDR file, a weighted moving average algorithm (window size = 3 days) is used to smooth short-term fluctuations; The actual curve can be determined based on the following method: Based on the actual completion time, the cumulative completion percentage is calculated by a piecewise function (such as formula 6): the unstarted segment (0), the in-process segment (linear growth), and the completed segment (100%).

[0047] Formula 6: Cumulative completion percentage (t) = min (∑ (actual completed task weight) / total weight × 100%, 100%); Optionally, the deviation amount comprises a first deviation amount and a second deviation amount, wherein: The first deviation amount = the cumulative completion percentage corresponding to the reference curve - the cumulative completion percentage corresponding to the actual curve; Second deviation amount = cumulative completion percentage corresponding to reference curve - cumulative completion percentage corresponding to prediction curve.

[0048] S50, according to the deviation amount, the project progress of the engineering construction project is prewarned and dynamically controlled.

[0049] Optionally, one implementation of the above S50 is that when the deviation amount exceeds a preset threshold, an early warning information is generated, and corresponding risk items, task reassignment and resource rescheduling instructions are generated according to the deviation amount, and the risk items, task reassignment and resource rescheduling instructions are used to perform risk closed loop, responsibility reassignment and resource supplement for lagging tasks.

[0050] Optionally, the above preset threshold includes a first threshold interval and a second threshold interval, for any one of the first deviation amount and the second deviation amount, wherein: When the deviation amount is in the first threshold interval, a first early warning information is generated and pushed to the task person in charge; When the deviation amount is in the second threshold interval and greater than the upper limit of the first threshold interval, a second early warning information is generated and synchronously pushed to the task person in charge, the supervisor and the project manager.

[0051] As an embodiment, the specific progress early warning process can be seen from Figure 6 .

[0052] Among them, the first threshold interval and the second threshold interval can be determined in the following way: Set "start date difference > 7 days" as a condition, and the corresponding action is "yellow early warning", that is, the upper limit of the first threshold interval is formed; continue to set "progress deviation > 14 days" or "early warning priority ≥ 80 points" as a higher order condition, and the corresponding action is "red early warning", that is, the lower limit of the second threshold interval is formed. When scanning every hour, automatically compare the calculated deviation amount or formula 4 priority with the above fixed conditions, and trigger the early warning of the interval where it falls without manual intervention.

[0053] Formula 4: Early warning priority = (task weight × 0.4) + (deviation degree / threshold × 0.3) + (number of affected subtasks / total number of tasks × 0.3); Among them, the early warning priority corresponding to the yellow early warning can be 50-79 points. Deviation degree refers to the size of the deviation amount; the number of affected subtasks = the total number of all lower level / successive subtasks directly caused by the delay of the current node (or task) and unable to start according to the plan; it is automatically traversed downward from the network logical relationship to obtain, used to quantify the chain range of "dragging one item, disordering a string", and as an input variable for early warning priority calculation.

[0054] Specifically, in the process of determining the first threshold interval and the second threshold interval, user-defined rules (such as "start date difference > 7 days") can be converted into executable logical expressions based on the Drools rule engine. A "condition-action" model is adopted, in which the condition part parses parameters such as time difference and progress deviation through SQL-like syntax (such as DATEDIFF (scheduled start time, current time) > 7), and the action part is associated with the message push interface. Rule scanning is performed once an hour (scanning frequency can be configured), and the scanning range is limited by index optimization algorithms (such as B + tree index based on task ID) to ensure that the scanning time is ≤ 5 minutes under a million task volume. Optionally, after the pre-warning and dynamic regulation, the corrected structured data, including progress plan data, actual progress data and TDR file data, can be obtained, further referring to Figure 4 and Figure 5 The method further comprises: Through the structured cleaning engine, the imported raw data (such as external technical data, or corrected structured data) is cleaned, matched and standardized to ensure data quality, and the engineering construction project is obtained.

[0055] Among them, the structured cleaning engine specially processes externally imported data (such as Excel, Project files), solves the problems of inconsistent data formats, redundancy and errors. Its core is regular expression matching technology, which is used for automatic data parsing, field extraction and standardization.

[0056] Among them, the working principle of regular expression matching is: The structured cleaning engine processes external data (such as Excel, Project files) through a "detection-correction-standardization" three-stage pipeline: Data detection algorithm: field feature extraction algorithm (such as field type recognition based on decision tree) is adopted to detect data format inconsistency (such as date format "YYYY / MM / DD" and "MM-DD-YYYY"), redundancy (such as duplicate task records), and errors (such as task time earlier than project start time); Data correction algorithm: for date format errors, through date regular matching and conversion algorithm (such as re.sub(r'(\d{2})-(\d{2})-(\d{4})', r'\3-\1-\2', raw_date)), unify to "YYYY-MM-DD"; for redundant data, through MD5 hash deduplication algorithm to keep the latest record; Data standardization algorithm: Adopt dictionary mapping (e.g., map "Design Unit A" to "DUTY_UNIT_001") and normalization processing (e.g., constrain progress percentage to [0, 100]) to ensure output data conforms to system standard format.

[0057] For cases where the structured cleaning engine detects mismatches (e.g., illegal characters or missing fields), automatically trigger error correction processes: Use Regex replacement functions (e.g., replace("\s+","")) to remove excess spaces.

[0058] Key fields (e.g., "Task Code") are verified by Regex rules (e.g., ^[A-Z0-9]{8}) to ensure uniqueness and consistency.

[0059] Integration of cleaning engine with progress warning: The output of the cleaning engine is directly integrated into the progress warning subsystem. Structured data is used to dynamically generate warning rules: Warning rule configuration: Users can define Regex-based rules (e.g., "Start date difference > 7 days") through the interface. The system periodically scans the cleaned data and triggers warning notifications.

[0060] Optionally, the method further comprises: According to the preset Word / HTML template containing placeholders, the deviation and warning statistical data (data generated when progress warning, including yellow / red warning number, new / loop risk item number, delay task weight proportion, professional over-standard ranking, etc. Quantitative indicators) are filled into the text position through XSLT conversion algorithm, the same kind of data is rendered into charts through ECharts API, and finally a customizable PDF progress report is obtained by processing through iText and other PDF rendering engines, which can be filtered by professional / time interval.

[0061] Specifically, a "template-driven-data filling" framework is adopted. The preset report template (containing fixed text and dynamic data placeholders) is mapped to the placeholders through the XSLT conversion algorithm Structured data (such as deviation and warning statistical data); For chart content, call ECharts API to generate S-curve, warning trend chart, etc. Finally, through the PDF rendering engine (such as iText), a customizable report is generated, which supports filtering data by "professional", "time interval" and other dimensions.

[0062] Further, the S-curve (progress accumulation curve) is a core visualization tool for engineering project progress management. Through the comparison of benchmark curve, actual curve and prediction curve, it directly shows the progress deviation. Identify progress lag (actual curve lower than benchmark curve) or advance (actual curve higher than benchmark curve); Warning about time risk (e.g., sudden change in slope); Support decision optimization of resource allocation.

[0063] Wherein, the benchmark curve: taken from the "scheduled completion time" in the progress plan. The prediction curve: generated based on the "expected completion time" maintained in the TDR (delivery document list).

[0064] As an example: TDR file automatically associates the plan task: Benchmark S-curve → scheduled completion time; Predictive S-curve → expected completion time; Actual S-curve → actual completion time; Actual progress data, collected through the quantity reporting function: the construction unit fills in the completed quantity and the cumulative completion percentage every week; after the data is approved, it is automatically summarized: Cumulative completion percentage = ∑ (completed quantity) / total quantity × 100%.

[0065] Optionally, the scheme of the present application can also be used for new warning rules, which are configured by the user in the interface shown in Figure 7 , see Figure 8 In the warning configuration interface, the user can customize the monitoring time.

[0066] Optionally, when the progress of the engineering construction project is found to need to be warned, the corresponding field list can be generated to record and automatically fill in / enter information related to task lag and warning processing, which can be seen in Figure 9 .

[0067] In order to better illustrate and understand the principle of the method provided by the present application, the scheme of the present application will be described below in combination with an optional specific embodiment. It should be noted that the specific implementation of each step in the specific embodiment should not be understood as a limitation of the scheme of the present application. On the basis of the principle of the scheme provided by the present application, other implementation manners that can be thought of by those skilled in the art should also be regarded as within the protection scope of the present application.

[0068] In an embodiment of the present application, as shown in Figure 2 and 3 , an engineering design full-process intelligent management and control system specifically comprises: A design review module for receiving drawings, models and other files, automatically identifying file codes and names, and generating unique identifiers; and automatically generating structured review opinion sheets (such as drawing and model reviews), meeting applications and summary tracking according to file types, realizing digitalization of the review process and risk association of opinions; this module corresponds to obtaining relevant information for the engineering construction project; A two-dimensional and three-dimensional review module for assisting in drawing review and model review; this module also corresponds to obtaining relevant information for the engineering construction project; The design change management module is used for online approval of change application and instruction, automatic analysis of change reason, progress and cost, association of progress, cost, device unit and other data according to change content, automatic generation of influence analysis report (such as delay of construction period, change of cost), and acquisition of relevant information of the engineering construction project. Different relevant information of the engineering construction project can be acquired from the design review module, the two-dimensional and three-dimensional review module and the design change management module.

[0069] The design progress management module is used for formulating main plan and sub-plan, monitoring progress through delivery file list (TDR), automatically reminding task person in charge, and generating S-curve to compare benchmark and actual progress. The module corresponds to the previous step of "constructing main plan and multiple sub-plans of the engineering construction project according to project requirements", and continuously provides core data such as plan completion time, TDR actual completion time and current latest reported estimated completion time for "generating benchmark / prediction / actual curve", which is the direct data source for generation of the three curves and subsequent deviation amount calculation.

[0070] The design risk management module is used for embedding risk identification options in review opinions, automatically generating a risk list, and performing closed-loop management of risk tracking, task assignment and problem registration. The module corresponds to the previous step of "acquiring relevant information of the engineering construction project", is responsible for collecting and structuring "risk event" data, and provides input for subsequent generation of three curves, calculation of deviation amount and triggering of early warning control.

[0071] The design report management module is used for automatically summarizing review optimization items and risk problem list, and generating engineer weekly report and project weekly report. The module corresponds to the "control" output link in the previous "warning and dynamic control of project progress of the engineering construction project according to deviation amount", is responsible for automatically summarizing deviation amount, early warning information and risk disposal results into customizable PDF progress / risk report, and realizes solidification and release of control results.

[0072] Further, the two-dimensional and three-dimensional review module includes a model review unit and a drawing review unit. The model review unit is used for loading and online viewing of target model files based on three-dimensional model analysis capability, and managing and tracking the whole review process. The drawing review unit is used for loading and online viewing of target drawing files based on two-dimensional drawing analysis capability, and managing and tracking the whole review process.

[0073] Further, the design change management module includes a design change application unit, a design change instruction unit, a design change analysis unit and a red head file uploading unit.

[0074] Among them, the design change application unit is used to receive the structured filled change application submitted online by the contractor, and automatically assign to the owner or PMC for approval according to the preset rules.

[0075] The design change instruction unit is used to generate a change instruction after approval, and push it to the contractor for confirmation.

[0076] The design change analysis unit is used to classify and analyze the change reason, progress influence, cost influence, device unit and other factors according to the change application information, and generate a report.

[0077] The red head file uploading unit is used to upload the red head file and automatically archive it to ensure that the change basis is traceable.

[0078] Further, the design progress management module mainly includes a project progress plan unit, a delivery file list unit, a design progress control unit and a design progress report unit. Among them, the project progress plan unit is used to establish the main plan (including the construction plan) and the design and procurement sub-plans according to the secondary (or tertiary) plans established in the main data, and the sub-plan tasks are automatically associated with the responsible person and the supervisor.

[0079] The delivery file list unit is used to import the Excel template to generate the delivery file list (TDR), automatically check the file coding rules, monitor the actual completion time and generate three S curves of benchmark, expected and actual, and intuitively compare the progress deviation. Among them: the benchmark S curve takes the planned completion time; the expected S curve needs to maintain an expected completion time for each TDR file, and takes the value of the expected completion time; the actual S curve takes the actual completion time.

[0080] The design progress control unit is used to notify the corresponding professional engineers in advance according to the start time of each task in the progress plan, so as to remind them to prepare in advance. Therefore, in each line of work, there should be "responsible person" and "supervisor" two roles: "responsible person" is used to associate the design unit document, so that the design unit document can log in the account to upload the design file (because the specific personnel of the design unit do not participate in the system use, only an account for uploading files is given to the document of each design unit), and "supervisor" is associated with professional engineers to facilitate notification before or after the start of the work. A week before the start of the plan, the system reminds the professional engineers and publishes the to-do tasks, which are followed up by the design engineers. When the task reaches the planned completion date and has not been completed, the system sends a reminder to the professional engineer, and the professional engineer feeds back the cause analysis, suggestion measures, risk warning, etc.

[0081] The design progress report unit is used to generate a progress report according to the above information, and the specific style can be determined according to the actual situation.

[0082] In a preferred embodiment of the present application, the engineering project whole cycle design management method and system based on structured process linkage takes project design as the control object, and realizes the whole process management of early consultation, overall design, basic design and detailed design. The system supports project data storage, retrieval and management, process file review, meeting review, etc. The "design management" module includes 5 secondary directories, which are design review, design change management, design progress management, design risk management and design report management, as shown in Table 1.

[0083] Table 1 In a preferred embodiment of the present application, in the engineering project whole cycle design management method and system based on structured process linkage, the specific process of design process review is as follows: The design institute compiles the file number and name according to the requirements offline, uploads the file to the document control platform and sends it to the CPMC document control. After receiving the file, the document control selects the corresponding professional engineers to assign the review task. The professional engineers fill in the review opinion sheet online. In this process, the system should have the following functions: a. Support multiple file uploads; b. Automatically identify file codes and names and fill them into the review opinion sheet. In the generated review opinion sheet, review opinion sheet number = file number (filled automatically by the system), and the review opinion sheet realizes the function of jumping to the document upload record by clicking the document name, and the corresponding review opinion sheet record can be viewed in the document upload record, which is convenient for querying whether the associated opinion sheet is closed); After the review opinion sheet process is completed, it needs to be automatically archived.

[0084] In the review opinion form, the

whether to join the risk identification list

risk identification

[0085] In a preferred embodiment of the present application, the specific application of the cleaning engine in progress management is taken as an example of the engineering quantity reporting function: data import stage: when the user uploads the Excel engineering quantity list, the cleaning engine uses Regex to match the field (such as "total engineering quantity" and "cumulative completion percentage"). For example, the Regex pattern \d+\.\d{2} is used to verify the numerical format.

[0086] Automatic processing: the engine executes the "automatic creation of engineering physical quantity" process: the matched data is filled into the structured form, and the failed items generate error logs and notify the user to correct. Output and integration: the cleaned data is synchronized to the progress plan and investment management module to ensure the accuracy of progress weight calculation and early warning.

[0087] Efficiency improvement: regular expression matching realizes millisecond-level data cleaning, reducing manual intervention by 90%.

[0088] Data quality assurance: the structured cleaning engine solves the "information island" problem and ensures the consistency of data in the progress, risk, and investment modules.

[0089] Extensibility: the engine supports custom Regex rules to adapt to different project needs (such as the differences in fields between oil and gas fields and refining engineering). For example, as shown in Figure 4 .

[0090] Taking a certain refining engineering project as an application scenario: 1. Project Phase: Detailed Design Phase; Monitoring targets: the delivery progress of design documents for process / piping / electrical disciplines; Technical objective: To achieve accurate early warning for schedule deviations ≤5%; 2. System configuration and data input; 2.1 System initialization; Master plan established: Master Plan ID: P2025-P01 Milestone Nodes: [Overall Design Approval] → [Basic Design Completion] → [Detailed Design Delivery] Time Range: 2025.06.01 - 2025.12.31.

[0091] Sub-plan association table 2: 2.2 Data input source; Baseline data: Imported planned completion times from Oracle Primavera P6; Actual data: TDR file entry system; File encoding rule: PROC-2025-001 (regular expression validation: ^[AZ]{4}-\d{4}-\d{3}); 3. Core process for generating S-curves; 3.1 Data Cleaning Engine; Regular expression processing: # Date standardization clean_date=re.sub(r'(\d{4})[ / ](\d{1,2})[ / ](\d{1,2})',r'\1-\2-\3', raw_date) # File encoding validation if not re.match(r'^[AZ]{4}-\d{4}-\d{3}',file_code): raise ValueError("Invalid TDR file code") 3.2 Progress Aggregation Algorithm; Professional progress calculation: Process completion rate = Number of delivered PROC documents / 120 Total schedule = (Process completion rate × 40%) + (Pipeline completion rate × 35%) + (Electrical completion rate × 25%); The logic for generating the three curves is shown in Table 3. 3.3 Dynamic visualization output; ECharts rendering: Horizontal axis: Time (daily granularity); Vertical axis: progress accumulation percentage; Interaction function: display deviation value on hover; Benchmark / actual / predicted curve example; PDF report automatic generation: Output path: / project documents / design progress / monthly report / 2025-08.pdf; 4. Early warning linkage mechanism implementation; 4.1 Early warning rule configuration; Early warning parameter setting, Table 4: 4.2 Early warning trigger instance; Scenario description (2025.08.20): Pipeline professional progress lags behind 12% (actual progress 58% vs benchmark 70%); System automatically detects deviation > red threshold; Action performed: Risk item generated: Risk ID: RISK-2025-081 Description: Pipeline design document delivery lags behind 12% Associated file: PIPE-2025-045; Push in-site message to responsible person:

Emergency warning

[0092] Based on the same principle as the method shown in Figure 1 The embodiment of the present application also provides an engineering design whole-process intelligent management and control device 20 based on the same principle as the method shown in Figure 10 The engineering design whole-process intelligent management and control device 20 can include an acquisition module 210, a plan generation module 220, a curve generation module 230, a deviation amount calculation module 240 and a management module 250, wherein: The acquisition module 210 is configured to acquire relevant information for the engineering construction project, and the relevant information includes at least one of a delivery file list TDR, a review opinion, a design change, a risk event and an actual progress; The plan generation module 220 is configured to construct a main plan and a plurality of sub-plans of the engineering construction project according to project requirements, and the latest completion time corresponding to the plurality of sub-plans is not greater than the planned completion time of the main plan; The curve generation module 230 is configured to generate a benchmark curve, a predicted curve and an actual curve according to the main plan, the plurality of sub-plans and the relevant information, the benchmark curve is a progress line calculated according to the originally formulated planned completion time in the engineering construction project, the predicted curve is a progress line calculated according to the currently latest reported predicted completion time of the engineering construction project, and the actual curve is a progress line calculated according to the time stamp of the file or task that has been actually completed in the engineering construction project; The deviation amount calculation module 240 is configured to determine the respective cumulative completion percentages of the benchmark curve, the predicted curve and the actual curve corresponding to the same time point, and calculate a deviation amount according to all the cumulative completion percentages; The management module 250 is configured to prewarn and dynamically control the project progress of the engineering construction project according to the deviation amount.

[0093] The engineering design whole-process intelligent management and control device provided in the embodiments of the present application can execute the engineering design whole-process intelligent management and control method provided in the embodiments of the present application, and the implementation principles are similar. The actions performed by each module and unit in the engineering design whole-process intelligent management and control device in the embodiments of the present application are corresponding to the steps in the engineering design whole-process intelligent management and control method in the embodiments of the present application. The detailed function description of each module of the engineering design whole-process intelligent management and control device can be referred to the description of the corresponding engineering design whole-process intelligent management and control method in the foregoing, and will not be described herein again.

[0094] The engineering design whole-process intelligent management and control device can be a computer program (including program code) running in a computer device, for example, the engineering design whole-process intelligent management and control device is an application software. The device can be used to execute the corresponding steps in the method provided in the embodiments of the present application.

[0095] In some embodiments, the engineering design whole-process intelligent management and control device provided in the embodiments of the present application can be implemented in a combination of software and hardware. For example, the engineering design whole-process intelligent management and control device provided in the embodiments of the present application can be a processor in the form of a hardware decoding processor, which is programmed to execute the engineering design whole-process intelligent management and control method provided in the embodiments of the present application. For example, the processor in the form of a hardware decoding processor can be one or more application specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field programmable gate arrays (FPGAs), or other electronic elements.

[0096] In some other embodiments, the engineering design whole-process intelligent management and control device provided in the embodiments of the present application can be implemented in a software manner, Figure 10 The engineering design whole-process intelligent management and control device stored in the memory is shown, which can be software in the form of programs and plug-ins, and includes a series of modules, including the acquisition module 210, the plan generation module 220, the curve generation module 230, the deviation amount calculation module 240, and the management module 250, for implementing the engineering design whole-process intelligent management and control method provided in the embodiments of the present application.

[0097] The modules described in the embodiments of the present application can be implemented in the form of software or in the form of hardware. In some cases, the names of the modules do not constitute a limitation on the modules themselves.

[0098] Based on the same principles as the methods shown in the embodiments of the present application, an electronic device is also provided in the embodiments of the present application, which can include but is not limited to: a processor and a memory; the memory is configured to store a computer program; the processor is configured to execute the method shown in any of the embodiments of the present application by invoking the computer program.

[0099] In an optional embodiment, an electronic device is provided, as shown in Figure 11 , as shown in Figure 11 The electronic device 4000 shown in the embodiment includes a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, such as through a bus 4002. Optionally, the electronic device 4000 can also include a transceiver 4004, which can be used for data interaction between the electronic device and other electronic devices, such as data transmission and / or data reception, etc. It should be noted that in actual applications, the transceiver 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present application.

[0100] The electronic device can also be a terminal device, Figure 11 The electronic device shown is only an example and should not limit the functions and use range of the embodiments of the present application.

[0101] According to another aspect of the present application, a computer program product or computer program is also provided, which includes computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to make the computer device execute the methods provided in the various embodiments of the present application.

[0102] The above description is only the preferred embodiments of the present application and the explanation of the applied technical principles. Those skilled in the art should understand that the disclosed range of the present application is not limited to the technical solutions formed by the specific combinations of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the disclosed concept. For example, the above features can be replaced with the technical features disclosed in the present application (but not limited to) having similar functions to form technical solutions.

Claims

1. A method for intelligent control of the entire engineering design process, characterized in that, include: Obtain relevant information for the engineering construction project, including at least one of the following: the deliverables list (TDR), review comments, design changes, risk events, and actual progress. Based on the project requirements, a master plan and multiple sub-plans are constructed for the engineering construction project, wherein the latest completion time of the multiple sub-plans is no greater than the planned completion time of the master plan. Based on the master plan, multiple sub-plans, and the relevant information, a baseline curve, a forecast curve, and an actual curve are generated. The baseline curve is a progress line calculated according to the originally planned completion time of the engineering construction project. The forecast curve is a progress line calculated according to the latest estimated completion time of the engineering construction project. The actual curve is a progress line calculated according to the timestamps of documents or tasks that have been actually completed in the engineering construction project. Determine the cumulative percentage of completion for the baseline curve, forecast curve, and actual curve at the same point in time, and calculate the deviation based on all cumulative percentages of completion. Based on the deviation, the project progress of the engineering construction project is monitored and dynamically adjusted.

2. The method according to claim 1, characterized in that, The step of providing early warning and dynamic adjustment of the project progress based on the deviation includes: When the deviation exceeds a preset threshold, an early warning message is generated, and corresponding risk items, task reallocation, and resource rescheduling instructions are generated based on the deviation. Based on the risk items, task reallocation, and resource rescheduling instructions, a risk closed loop, responsibility redistribution, and resource allocation are performed on the delayed tasks.

3. The method according to claim 2, characterized in that, The deviation includes a first deviation and a second deviation, wherein: The first deviation = the cumulative percentage of completion corresponding to the baseline curve - the cumulative percentage of completion corresponding to the actual curve; The second deviation is equal to the cumulative percentage of completion corresponding to the baseline curve minus the cumulative percentage of completion corresponding to the prediction curve.

4. The method according to claim 3, characterized in that, The preset threshold includes a first threshold interval and a second threshold interval. For any one of the first deviation and the second deviation, the method further includes: When the deviation is within the first threshold range, a first warning message is generated and pushed to the person in charge of the task; When the deviation is within the second threshold range and greater than the upper limit of the first threshold range, a second early warning message is generated and simultaneously pushed to the person in charge of the task, the supervisor, and the project manager.

5. The method according to any one of claims 1 to 4, characterized in that, Based on project requirements, the process involves constructing a master plan and multiple sub-plans for the construction project, including: Obtain the overall project objectives, milestone nodes, and phase division requirements of the engineering construction project, and determine all control nodes of the engineering construction project; Based on the work breakdown structure, a master plan covering the entire project lifecycle is constructed using the aforementioned milestone nodes as anchor points, and the planned completion time for each key control node is determined. Based on the key control nodes in the master plan, and combined with professional divisions, device units, and task attributes, multiple sub-plans are recursively decomposed.

6. The method according to any one of claims 1 to 4, characterized in that, The determination of the cumulative completion percentage corresponding to the baseline curve, the predicted curve, and the actual curve at the same point in time includes: Obtain the first set of tasks that should be completed before the same time point, sum the task weights of each task in the first set of tasks to obtain the baseline weight sum, calculate the percentage of the baseline weight sum to the total project weight of the engineering construction project, and obtain the cumulative completion percentage corresponding to the baseline curve; Obtain the latest predicted set of second tasks to be completed before the same time point, sum the task weights of each task in the second task set to obtain the predicted weight sum, calculate the percentage of the predicted weight sum to the total project weight of the engineering construction project, and obtain the cumulative completion percentage corresponding to the prediction curve; Obtain the set of third tasks that have actually been completed before the same time point, sum the task weights of each task in the third task set to obtain the actual weight sum, calculate the percentage of the actual weight sum to the total project weight of the engineering construction project, and obtain the cumulative completion percentage corresponding to the actual curve.

7. The method according to claim 6, characterized in that, For any one of the first task set, the second task set, and the third task set, the steps for determining the task weight of each task in the task set include: Obtain at least one quantitative indicator from the workload, man-hours, or contract amount corresponding to each task in any of the task sets; Normalize the at least one quantitative indicator to obtain a normalized weight coefficient; The normalized weight coefficients are used as the proportion of each task relative to the total weight of the project to obtain the task weight of each task.

8. An intelligent control device for the entire engineering design process, characterized in that, include: The acquisition module is used to acquire relevant information for the engineering construction project, including at least one of the following: Delivery Documents List (TDR), review comments, design changes, risk events, and actual progress. The plan generation module is used to construct a master plan and multiple sub-plans for the engineering construction project according to the project requirements. The latest completion time of the multiple sub-plans is no greater than the planned completion time of the master plan. The curve generation module is used to generate a baseline curve, a forecast curve, and an actual curve based on the master plan, multiple sub-plans, and the relevant information. The baseline curve is a progress line calculated according to the originally planned completion time of the engineering construction project. The forecast curve is a progress line calculated according to the latest estimated completion time of the engineering construction project. The actual curve is a progress line calculated according to the timestamps of the documents or tasks that have been actually completed in the engineering construction project. The deviation calculation module is used to determine the cumulative completion percentage of the baseline curve, the predicted curve, and the actual curve at the same time point, and to calculate the deviation based on all the cumulative completion percentages. The management module is used to provide early warnings and dynamically adjust the project progress of the engineering construction project based on the deviation amount.

9. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1-7.

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