Engineering cost progress management control method and system

Abstract

The invention relates to the technical field of project cost progress management control methods, in particular to a project cost progress management control method and system. Comprising a multi-dimensional data integration and simulation deduction module, an intelligent early warning and dynamic decision module and a block chain collaboration and knowledge evolution module. Through the unique coding rule, the engineering quantity list, the material price, the labor cost and the model component are dynamically associated, the construction progress plan is embedded in the BIM model, the 4D construction animation is automatically generated, the resource demand peak value of each time period is counted, the resource conflict is identified in advance, and the component coding integrity and the cost parameter logicality are automatically verified through the attribute checking tool. And the manual auditing time is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering cost progress management and control methods, and in particular to an engineering cost progress management and control method and system. Background Art

[0002] The construction cost and progress management and control system is an integrated information management system that aims to collaboratively monitor, dynamically adjust, and make scientific decisions on the cost and progress of engineering projects through digital means to ensure that projects are completed on time and within budget. Its core functions cover cost control, progress planning, resource allocation, risk warning, and multi-dimensional analysis. It also uses technical means to achieve data sharing and real-time collaboration, thereby improving project management efficiency, reducing risks, and optimizing resource allocation.

[0003] Existing construction cost schedule management and control methods usually store BIM models, cost data, and schedule plans on independent platforms. Professional teams need to manually integrate the models, which can easily lead to rework due to version inconsistencies. After the schedule is adjusted, it needs to be manually updated to the model, which is time-consuming and prone to omissions of related tasks.

[0004] In response to the existing construction cost progress management and control methods, each professional team needs to manually integrate the model, which is prone to rework due to version inconsistencies. After the schedule is adjusted, it needs to be manually updated to the model, which is time-consuming and prone to omissions of related tasks. This solution uses unique coding rules to dynamically associate the bill of quantities, material prices, labor costs and model components, embed the construction schedule in the BIM model, automatically generate 4D construction animations, count the peak resource demand in each time period, identify resource conflicts in advance, and automatically verify the component coding integrity and cost parameter logic through the "property inspection tool", reducing manual review time. Summary of the Invention

[0005] In order to overcome the problems raised in the above background technology, the present invention proposes a construction cost progress management and control method and system.

[0006] The technical solution of the present invention is: a method for project cost progress management and control, comprising the following steps:

[0007] S1001: Use BIM technology to build a refined model, associate cost parameters and time dimensions, and form a 4D model;

[0008] S1002: Set tiered warning thresholds for cost overruns and schedule delays, collect actual cost and schedule data in real time, calculate deviations, trigger linkage warnings, generate analysis reports, and drive timely corrections;

[0009] S1003: Use AI algorithms to predict future resource needs, scan market price data, generate multiple configuration plans, compare and select the optimal solution, and dynamically adjust the plan based on market changes or schedule deviations;

[0010] S1004: Initiate a change application through the blockchain platform, conduct parallel review, automatically execute smart contracts to update models, costs, and schedule benchmarks, and store full-cycle data on the blockchain;

[0011] S1005: Generate standardized digital delivery packages, analyze project performance, refine management experience to update the knowledge base, and continuously optimize management methods and parameters through data-driven methods.

[0012] Preferably, when establishing and associating the parameters of the BIM-based refined model, the following steps are included:

[0013] S2001: Use BIM technology to build a three-dimensional model covering architecture, structure, water supply and drainage, electrical, and HVAC. Each professional team will model separately to ensure that the model depth meets the standard requirements;

[0014] S2002: Associate cost parameters such as bill of quantities, material prices, labor costs, and machine hourly rates with model components, define unique coding rules for each type of component, enter construction properties, and verify data integrity using the "property check tool";

[0015] S2003: Embed the construction schedule in the BIM model. Import the construction schedule in Project or Excel format into the BIM platform, associate construction tasks with model components, and define the "planned start time" and "planned completion time" of each task.

[0016] S2004: Simulate the construction process according to the timeline, generate visual animations, calculate the peak demand for manpower, materials, and machinery in each time period, and identify the contradiction between construction progress and resource supply;

[0017] S2005: Detect physical collisions between pipelines and structural components, analyze conflicts in construction procedures, simulate efficiency differences between different construction plans, adjust material yards and crane positions, and reduce secondary handling;

[0018] S2006: List various issues, propose design adjustments and construction plan optimization suggestions based on the issues, and estimate the cost savings and construction period reduction benefits after optimization;

[0019] S2007: Export the bill of quantities in Excel or CSV format, including the sub-project name, code, quantity and comprehensive unit price; export the 3D model in IFC format for use in subsequent stages; export the schedule in Project or PDF format, including task name, duration and associated model components.

[0020] As a preferred method, the detailed implementation of the dynamic cost and progress linkage early warning mechanism includes the following steps:

[0021] S3001: First, the threshold benchmark is determined. The cost benchmark is based on the total contract price and the cost parameters associated with the BIM model. The progress benchmark is based on the construction schedule embedded in the BIM model.

[0022] S3002: Calculate the warning thresholds. Level 1 warning is when the cost overrun or schedule lag reaches 5% of the baseline value, and level 2 warning is when the cost overrun or schedule lag reaches 10% of the baseline value. The calculation is based on the following formulas: Level 1 cost threshold = Total contract price × 5%; Level 1 schedule threshold = Scheduled duration × 5%;

[0023] S3003: Collect cost and progress data in real time, check whether the data is logically consistent, and ensure that required fields are not missing;

[0024] S3004: Quantify the difference between actual and planned costs and locate the source of the deviation. Cost deviation is the actual cost minus the planned cost, and schedule deviation is the actual progress minus the planned progress.

[0025] S3005: Summarize the causes of cost overruns and schedule delays, predict overrun trends, estimate total cost increases, calculate the number of days of delay, and assess the impact on subsequent tasks;

[0026] S3006: Set warning rules. A red warning is when both cost overruns and schedule delays reach the second-level threshold. A yellow warning is when a single indicator reaches the second-level threshold, or when both indicators reach the first-level threshold.

[0027] S3007: When the warning threshold is triggered, push warning information via email, SMS or project management platform. The warning information needs to include the project name, warning level, deviation indicator, cause analysis and recommended measures;

[0028] S3008: After the early warning information is sent, an early warning report is generated and sent to relevant parties according to preset rules. At the same time, the report is archived in the project document management system for subsequent audit and review.

[0029] Preferably, when configuring and optimizing AI-assisted resources, the following steps are included:

[0030] S4001: Extract model data and progress data. Model data is to extract component geometry information and process parameters from the BIM model. Progress data is to obtain the planned start or completion time and project volume of each task in the construction schedule.

[0031] S4002: Train the algorithm based on historical data and feature engineering, input historical project data, train the AI ​​prediction model, and extract key features as predictive variables;

[0032] S4003: Forecast material demand, labor demand, and machinery demand, and generate a demand forecast report containing resource type, demand period, forecast quantity, and confidence interval;

[0033] S4004: Access the API of cooperative suppliers to obtain material inventory and real-time quotes, crawl price indices and machinery rental market information from industry websites, and configure data resources;

[0034] S4005: Clean the data, merge duplicate data, and remove data that significantly deviates from the market price;

[0035] S4006: Update the cost database daily to record the historical prices and fluctuation trends of materials, machinery, and labor, and generate price trend charts to assist in analyzing seasonal price changes;

[0036] S4007: Generate multiple resource allocation plans and calculate the total cost using the formula: total cost = material procurement cost + machinery rental cost + labor cost + transportation cost + taxes. This will assess the potential impact of resource shortages or surpluses on the project duration.

[0037] S4008: Track material price fluctuations and supplier inventory changes in real time, compare actual progress with planned progress, predict changes in resource demand, and adjust resource allocation plans in real time;

[0038] S4009: Automatically generate standardized contract text based on the optimization results.

[0039] Preferably, when collaboratively managing changes to blockchain evidence, the following steps are included:

[0040] S5001: The construction unit submits a change application through the blockchain platform, including the reason for the change and the impact analysis;

[0041] S5002: Cost impact is the cost increase or decrease caused by the estimated change, and schedule impact is the potential impact of the predicted change on the construction period;

[0042] S5003: Design, supervision, and owner review the project in parallel on the blockchain, with review opinions recorded in real time and cannot be tampered with.

[0043] S5004: Blockchain node permissions are assigned to each participant to ensure that only data within the scope of the permissions can be accessed. Each reviewer views the change application on the blockchain platform and submits their review opinions. The blockchain automatically summarizes the review opinions of all parties and generates a review report.

[0044] S5005: After the review is passed, the smart contract is automatically triggered to update the BIM model, cost baseline and schedule;

[0045] S5006: Automatically modify the BIM model and update the cost parameters and schedule associated with the model based on the changed content;

[0046] S5007: All change records, review comments, and model versions are stored on the blockchain to support subsequent audits;

[0047] S5008: Use encryption algorithms to protect sensitive data and display the entire change process in a timeline format to assist auditors in conducting compliance reviews. Auditors can access a specified range of stored evidence data after passing identity verification.

[0048] S5009: Automatically calculate change costs based on the changed model data and link them to progress payments;

[0049] S5010: Automatically calculate change costs based on preset settlement rules and extract the changed data from the BIM model to ensure calculation accuracy.

[0050] As a preference, the following steps are included during digital delivery and post-evaluation:

[0051] S6001: After completion acceptance, package the final BIM model, cost data and progress records into digital deliverables;

[0052] S6002: Export the final BIM model in IFC or COBie format, collect scanned copies of contracts, change orders, and acceptance reports, convert them to PDF / A format, and run the delivery package verification tool to check data integrity, consistency, and viruses;

[0053] S6003: Compare actual costs with budget and calculate cost savings; compare actual progress with plan and calculate duration reduction;

[0054] S6004: The formula for the savings rate is (budgeted cost - actual cost) / budgeted cost × 100%, and the formula for the duration reduction rate is (planned duration - actual duration) / planned duration × 100%;

[0055] S6005: Use AI to analyze historical project data and extract best practices for cost control and schedule optimization;

[0056] S6006: Eliminate outliers, convert cost and schedule data from different projects into comparable data, and use clustering algorithms to identify common characteristics of high-performing projects;

[0057] S6007: Store experience summaries and lessons learned in the enterprise knowledge base, review them quarterly or semi-annually, and conduct them in conjunction with the project closing phase. Optimize warning thresholds based on historical project data.

[0058] A construction cost progress management and control system, including the following modules:

[0059] Multi-dimensional data integration and simulation module: used to build a digital twin base based on BIM technology, perform parametric modeling and full-factor association;

[0060] Intelligent early warning and dynamic decision-making module: used for cost-progress linkage monitoring and intelligent error correction through AI + big data;

[0061] Blockchain collaboration and knowledge evolution module: used for multi-party collaboration and organizational-level knowledge accumulation through distributed ledgers.

[0062] Preferably, the multidimensional data integration and simulation deduction module includes:

[0063] A1001: Multi-disciplinary collaborative modeling unit, including a 3D modeling engine, a parametric component library, version control components, and a multi-disciplinary collision detection module, used to build a high-precision digital twin base across disciplines;

[0064] A1002: A four-dimensional space-time correlation unit, including a schedule parser, resource loader, timeline simulator, and virtual construction engine, is used to integrate the time dimension into the 3D model to achieve dynamic simulation of the construction process;

[0065] A1003: Data verification and export unit, including attribute checking tools, multi-format converters and delivery package generators, is used to ensure data integrity and generate standardized deliverables.

[0066] As a preferred option, the intelligent early warning and dynamic decision-making module includes:

[0067] A2001: Threshold Management Unit, including a benchmark calculator, early warning grading matrix, and risk transmission model, used to define rules for cost and progress monitoring;

[0068] A2002: Real-time monitoring unit, including a data acquisition gateway, a deviation diagnosis engine, and a trend prediction module, used to continuously track project status and detect deviations in a timely manner;

[0069] A2003: Decision support unit, including solution selector, smart contract trigger and mobile push component, used to provide correction solutions and automatically execute them.

[0070] As a preferred option, the blockchain collaboration and knowledge evolution module includes:

[0071] A3001: Change management unit, including a smart contract template library, parallel review workflow, and model automatic updater, to achieve transparency and automation of the change process;

[0072] A3002: Data evidence storage unit, including blockchain browser, privacy protection components and audit evidence interface, used to ensure data security and support audit traceability;

[0073] A3003: Knowledge evolution unit, including performance analysis engine, experience extractor and optimization recommendation system, is used to transform project experience into organizational assets.

[0074] Beneficial effects of the present invention:

[0075] 1. Compared with traditional construction cost and progress management and control methods that usually store BIM models, cost data, and schedules on independent platforms, each professional team needs to manually integrate the models, which is prone to rework due to version inconsistencies. After the schedule is adjusted, it needs to be manually updated to the model, which is time-consuming and prone to omissions of related tasks. This solution uses unique coding rules to dynamically associate the bill of quantities, material prices, labor costs, and model components. The construction schedule is embedded in the BIM model, 4D construction animations are automatically generated, resource demand peaks in each time period are counted, resource conflicts are identified in advance, and the "property inspection tool" automatically verifies the integrity of component coding and the logic of cost parameters, reducing manual review time.

[0076] 2. Compared with traditional construction cost and schedule management and control methods, cost overrun and schedule delay warnings are usually based on a single indicator, without considering the impact of cost-schedule linkage. After the warning, manual analysis of the cause of the deviation is required, and the decision-making cycle can take several weeks. This solution sets dual thresholds of 5% / 10% for cost overruns and 5% / 10% for schedule delays. When the cost overrun reaches 8% and the schedule delay reaches 7%, a red warning is triggered, and corrective measures are automatically issued. At the same time, the LSTM algorithm is used to predict the cost overrun trend and the source of the deviation is located in combination with the BIM model. When the warning is triggered, a change order is automatically generated, the procurement plan is adjusted, and the corrective measures are synchronized with the model, cost, and schedule baselines.

[0077] 3. Compared with the traditional construction cost schedule management and control method, resource planning is based on static schedule preparation, which does not take into account market price fluctuations. At the same time, after the schedule deviation, the resource plan needs to be re-prepared. There is a lack of dynamic adjustment mechanism. Supplier quotations need to be manually compared, and it is impossible to match the optimal procurement plan in real time. This solution extracts component geometry information based on the BIM model, combines the construction schedule to predict future resource needs, and scans the supplier API to obtain real-time quotations. It also tracks material price fluctuations and supplier inventory changes, and dynamically adjusts the resource allocation plan based on actual schedule deviations. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1Shown is a flow chart of a method for project cost progress management and control according to the present invention;

[0079] Figure 2 Shown is a schematic diagram of the process of establishing a model and associating parameters for a method of project cost schedule management and control according to the present invention;

[0080] Figure 3 Shown is a schematic diagram of the framework of a construction cost progress management and control system of the present invention. DETAILED DESCRIPTION

[0081] The present invention will be further described below with reference to the accompanying drawings and examples.

[0082] See also Figure 1-2 The present invention provides an embodiment: a method for controlling construction cost schedule management, comprising the following steps:

[0083] Step 1: BIM refined model construction and multi-dimensional parameter association

[0084] Multi-disciplinary collaborative modeling and data governance

[0085] Modeling standard implementation: The architecture / structure profession implements the LOD400 standard, including detailed construction nodes; the MEP profession implements the LOD350 standard, which specifies parameters such as pipeline slope and insulation layer thickness; adopts the BIM collaboration platform, sets version conflict warning rules, and automatically marks unsynchronized component changes.

[0086] Cost parameter association: Coding system, establish a five-level coding of "professional-floor-system-component type-serial number"; data entry, batch import Excel bill of quantities through Dynamo script, associate with the material price library, set the formula to automatically calculate the comprehensive unit price; verification tool, develop a Python-based "property inspection tool" to verify the completeness of required fields and mark missing or abnormal data.

[0087] Time dimension embedding: Import the schedule, convert the Project file into an XML format recognizable by the BIM platform, and associate construction tasks with model components through a "task-component" mapping table; 4D simulation optimization: Use Synchro PRO to generate construction process animations, identify critical path resource conflicts, and adjust the logical relationships of non-critical path tasks; Resource peak statistics: Generate resource histograms by week / month, mark peak demands for manpower, materials, and machinery, and output over-limit warning reports.

[0088] Model verification and delivery: geometric verification, checking model coordinate system and overall plan Figure 1For consistency, the error must be ≤5mm; for data verification, the component attribute table is exported according to the COBie standard, and the difference rate between the engineering quantity and the list is checked; for delivery format, the main model is in IFC4×3 format, the cost data is in Excel / CSV, and the schedule is in XML / PDF, all with MD5 checksums.

[0089] Step 2: Dynamic cost-progress linkage warning mechanism

[0090] Dynamic calibration of threshold benchmarks: The cost benchmark is based on the total contract price and combines the cost parameters associated with the BIM model, with floating intervals set according to the sub-projects; the progress benchmark adopts a three-level control of "planned construction period - free time difference - total time difference", and the warning thresholds for critical path tasks are set separately; the update mechanism dynamically adjusts the benchmark value every month based on actual progress and cost data.

[0091] Real-time data collection and cleaning: data source, connecting to financial systems, progress management systems, and IoT devices; cleaning rules, removing outliers, filling missing values, and converting data formats; quality inspection, using Pandas scripts to automatically generate data quality reports and mark fields with missing rates > 2%.

[0092] Deviation quantification and root cause analysis: Cost deviation = Budgeted cost of work completed - Actual cost of work completed; Schedule deviation = Budgeted cost of work completed - Budgeted cost of planned work; Root cause analysis uses the fishbone diagram method to trace the causes of deviations from five dimensions: people, machines, materials, methods, and environment.

[0093] Warning classification and response: Red warning: Activate the emergency plan and submit the correction plan to the management within 48 hours; Yellow warning: Complete the deviation analysis report within 3 days and implement corrective measures within 7 days; Warning push: Send structured messages through the enterprise WeChat robot, synchronized to the BIM model to highlight the problem components.

[0094] Step 3: AI-driven dynamic resource allocation and optimization

[0095] Data preparation and feature engineering: For historical data, extract data from similar projects in the past three years to build a feature matrix; access real-time data through APIs such as Guangcai.com and Mysteel.com to obtain T+0 material prices and crawl weather data; feature screening, using SHAP value analysis to eliminate low-correlation features.

[0096] Forecast model training and deployment: In terms of algorithm selection, the LSTM time series model is used for material demand, XGBoost regression is used for labor demand, and Monte Carlo simulation is used for mechanical demand; for model evaluation, the MAPE must be ≤8%, and the model is automatically deployed through the Kubernetes cluster; for forecast output, a resource demand heat map is generated, and the confidence interval is set to ±15%.

[0097] Market data integration and solution selection: Supplier management, establishing a qualified supplier database and recording historical performance data; solution generation, using genetic algorithms to generate a Pareto optimal solution set with the dual objectives of minimizing total cost and shortest construction period; dynamic adjustment, triggering the solution re-optimization process when the actual progress deviation is greater than 5% or the material price fluctuation is greater than 10%.

[0098] Step 4: Blockchain-enabled collaborative change management

[0099] Change application and impact assessment: Application template, mandatory filling in the change reason classification, impact scope, and related model component code; impact calculation, automatic linking of BIM model, marking of affected components, and calling the cost database to estimate cost changes.

[0100] Smart contracts and automatic execution: Contract terms, preset change approval processes, and payment terms; automatic updates. After approval, model version control is triggered and cost baselines and schedules are updated synchronously.

[0101] Evidence storage and audit support: Data is uploaded to the blockchain using the Hyperledger Fabric consortium chain, with node permissions set so that the design institute can only write model data, while the owner can read all data. Audit trails generate timestamp records based on the "application-review-approval-execution" process, supporting searches by change number, applicant, and time range. Compliance checks automatically compare change content with bidding documents and contract terms, flagging potential compliance risks.

[0102] Step 5: Digital Delivery and Knowledge Accumulation

[0103] Deliverable construction: Model delivery, IFC format model with metadata, COBie table containing information required for operation and maintenance; document archiving, contracts / change orders / acceptance reports converted to PDF / A-3b format, embedded with digital signatures; verification rules, running the delivery package verification tool to check file integrity, data consistency, and virus scanning.

[0104] Performance analysis and knowledge base update: Indicator calculation: Cost savings rates must exclude price increases, and project duration reduction rates must be compared with actual calendar days including rainy seasons and holidays. Experience extraction: Use NLP technology to analyze change records, extract high-frequency issues, and generate a standardized solution library. Knowledge update: Publish a quarterly "Cost Control White Paper" containing typical cases and early warning threshold optimization suggestions.

[0105] See also Figure 3 The present invention provides an embodiment: a construction cost progress management and control system, comprising the following modules:

[0106] Module 1: Multidimensional Data Integration and Simulation Module

[0107] Multi-disciplinary collaborative modeling unit: A 3D modeling engine supports independent modeling of architecture, structure, electromechanics, and other disciplines, with a built-in parametric component library containing both geometric and non-geometric attributes. The version control component uses a "central file + workset" model to record each model modification and supports version rollback and difference comparison. The collision detection module detects hard and soft collisions based on geometric algorithms, generates collision reports, and locates the specific component code.

[0108] Four-dimensional space-time association unit: Schedule parser, which imports Project / Excel format schedules, analyzes task logical relationships and durations, and associates them with model components; resource loader, which automatically loads resource requirements based on construction tasks, generates resource histograms based on the timeline, and marks peak demand periods; virtual construction engine, which simulates the construction process according to time steps, outputs visual animations, and identifies resource conflicts.

[0109] Data Verification and Export Unit: Attribute checking tool to verify the integrity and logical consistency of model component attributes; multi-format converter, supporting IFC, Excel / CSV, PDF / A and other format conversions to ensure data compatibility; delivery package generator, packaging model files, cost data, and schedule plans into standardized deliverables, with MD5 checksums and data dictionaries.

[0110] Module 2: Intelligent Early Warning and Dynamic Decision-making Module

[0111] Threshold Management Unit: Benchmark value calculator, which uses the total contract price and BIM model-related cost parameters as the benchmark and sets floating intervals according to the sub-projects; early warning classification matrix, which defines the first and second level early warning thresholds and supports custom extensions; risk transmission model, which analyzes the impact of deviations on subsequent tasks and generates a risk transmission path diagram.

[0112] Real-time monitoring unit: Data collection gateway, connecting to financial systems, IoT devices, and third-party APIs; Deviation diagnosis engine, calculating cost and schedule deviations and locating the source of deviations; Trend prediction module, using the LSTM algorithm to predict cost and schedule trends for the next seven days and mark potential risk points.

[0113] Decision support unit: A solution selector generates multiple correction plans and calculates the total cost change and the impact on the construction period; a smart contract trigger automatically calls the preset contract terms and pushes them to the blockchain platform when a deviation triggers a second-level warning; a mobile push component sends structured warning information via WeChat / DingTalk for Enterprise and supports one-click initiation of correction meetings.

[0114] Module 3: Blockchain Collaboration and Knowledge Evolution Module

[0115] Change Management Unit: Smart contract template library with preset change approval process and payment terms; parallel review workflow, where design, supervision, owner and other units can view change applications in real time on the blockchain, submit review opinions and electronically sign; model automatic updater, which automatically modifies the BIM model, updates the cost baseline and schedule after approval.

[0116] Data evidence storage unit: Blockchain browser, which displays the entire change process in the form of a timeline and supports retrieval of evidence data by transaction hash value; privacy protection component, which encrypts and stores sensitive data and only authorized parties can access it; audit evidence interface, after the audit agency passes the identity verification, it can export the evidence data of a specified time range to support compliance review.

[0117] Knowledge Evolution Unit: Performance analysis engine, which compares actual costs with budgets and actual progress with plans, and calculates cost savings and duration reduction rates; experience extractor, which uses NLP technology to analyze change records and correction plans, extracting high-frequency issues and best practices; and optimization recommendation system, which uses clustering algorithms to identify the characteristics of high-performance projects and dynamically adjust warning thresholds and resource allocation strategies.

[0118] Example 1

[0119] 1. Use BIM technology to build a refined model, associate cost parameters and time dimensions, and form a 4D model.

[0120] 1. Multi-disciplinary model construction:

[0121] S11: Use tools such as Revit / Tekla / MagiCAD to build architectural, structural, and electromechanical models respectively. The model depth must meet the LOD400 standard.

[0122] S12: Model integration is performed through Navisworks, and the collision detection error is ≤5mm.

[0123] 2. Cost parameter association:

[0124] S21: Define the component coding rules: discipline-system-component-serial number (such as A-MEP-PL-001).

[0125] S22: Use Dynamo scripts to batch associate Excel bills of quantities with model component properties.

[0126] S23: Use Solibri Model Checker to verify data integrity.

[0127] 3. Time dimension embedding:

[0128] S31: Import the Project format schedule into the BIM platform and associate it with the model components through the "task ID".

[0129] S32: Use Synchro PRO to generate 4D construction animations and simulate the construction process on a weekly basis.

[0130] 4. 4D model generation:

[0131] S41: Integrate cost parameters, time dimensions and models through Synchro PRO to generate a 4D model with queryable cost / schedule information.

[0132] 2. Set graded warning thresholds for cost overruns and schedule delays, collect data in real time, and trigger linkage warnings.

[0133] 1. Determination of threshold benchmark:

[0134] A11: Cost basis: ,in is the total contract price, is the engineering quantity of the model components, The unit price is for materials / labor / machinery.

[0135] A12: Progress benchmark: ,in Plan the total duration for the construction schedule embedded in the BIM model.

[0136] 2. Calculation of warning threshold:

[0137] A21: Level 1 warning threshold: ,in A baseline value for cost or schedule.

[0138] A22: Level 2 warning threshold: .

[0139] 3. Real-time data collection:

[0140] S31: Collect actual cost / progress data from financial systems and IoT devices through API interfaces.

[0141] S32: Use data verification rules to check data logic.

[0142] 4. Deviation quantification and early warning triggering:

[0143] A41: Cost deviation: .

[0144] A42: Schedule deviation: .

[0145] A43: When ∣≥ or | ∣≥ When the alarm is triggered.

[0146] 3. Use AI algorithms to predict future resource demand, scan market price data, and generate multiple configuration plans.

[0147] 1. Data extraction and preprocessing:

[0148] S11: Extract component geometry information and process parameters from the BIM model.

[0149] S12: Extract task start / completion time and project quantity from the construction schedule.

[0150] 2. AI model training:

[0151] S21: Input historical project data and train the LSTM prediction model.

[0152] S22: Extract key features as predictor variables.

[0153] 3. Resource demand forecast:

[0154] S31: Generate a demand forecast report, including resource type, demand period, forecast quantity and confidence interval.

[0155] 4. Market price scanning and scheme comparison:

[0156] S41: Access supplier APIs to obtain real-time quotes and crawl price indices from industry websites;

[0157] S42: Generate multiple resource allocation plans and calculate the total cost: .

[0158] 4. Initiate change applications through the blockchain platform, conduct parallel reviews, and automatically execute smart contracts.

[0159] 1. Submit change application:

[0160] S11: The construction unit submits a change application through the blockchain platform, including the reason for the change and impact analysis.

[0161] 2. Parallel review and smart contract triggering:

[0162] S21: Design, supervision, owner and other units conduct parallel reviews on the blockchain, and review opinions are recorded in real time.

[0163] S22: After the review is passed, the smart contract is automatically triggered to update the BIM model, cost baseline and schedule.

[0164] 3. Data storage and auditing:

[0165] S31: All change records, review comments, and model versions are stored on the chain.

[0166] S32: Use encryption algorithms to protect sensitive data and display the entire change process in a timeline format.

[0167] 5. Generate standardized digital delivery packages, analyze project performance, and extract management experience.

[0168] 1. Digital deliverable packaging:

[0169] S11: Export the final BIM model, cost data, and progress records.

[0170] S12: Run the delivery package verification tool to check data integrity, consistency and viruses.

[0171] 2. Project performance analysis:

[0172] S21: Compare actual costs with budget and calculate cost savings: .

[0173] S22: Compare the actual progress with the plan and calculate the shortening rate of the construction period: .

[0174] 3. Management experience extraction and knowledge base update:

[0175] S31: Use AI to analyze historical project data and extract best practices.

[0176] S32: Store the experience summary in the enterprise knowledge base, review it once a quarter, and optimize the warning threshold.

[0177] Example 2

[0178] Background: A commercial complex project with a total construction area of ​​150,000 square meters consists of a shopping mall, office buildings, and a hotel. The total contract value is 1.2 billion yuan, and the planned construction period is 36 months. The project adopts a general contracting model. The owner requires the implementation of refined cost and schedule control to ensure a cost savings rate of ≥3% and a construction period reduction rate of ≥5%.

[0179] Implementation steps:

[0180] The architecture, structure, and mechanical and electrical professional teams respectively model based on Revit. The component coding rule is "professional-floor-system-component type-serial number". The version control component records each model modification and generates a version history tree diagram.

[0181] The collision detection module discovered a conflict between the structural beam and the air conditioning duct, generated a collision report, and located the specific component. The design institute then resolved the conflict after adjusting the duct elevation.

[0182] The schedule parser imports the Project file and associates tasks such as "concrete pouring" and "masonry engineering" with model components. The resource loader automatically loads resource requirements based on construction tasks.

[0183] The virtual construction engine simulated the construction process on a weekly basis and generated visual animations. It was found that weeks 8 to 12 were the peak period for tower crane use, posing a risk of conflict.

[0184] The property checker verifies the integrity of model component attributes, marks missing fields, and prompts for completion. The multi-format converter exports models in IFC format, Excel bills of quantities, and PDF schedules. The deliverable generator packages files into standardized deliverables with MD5 checksums.

[0185] The benchmark calculator sets the cost benchmark as the total contract price of RMB 1.2 billion and the progress benchmark as a 36-month construction period. The warning classification matrix defines first-level and second-level warnings, and the risk transmission model analyzes the impact of deviations on subsequent tasks.

[0186] The data collection gateway connects to the financial system, IoT devices, and third-party APIs. The deviation diagnosis engine calculates the cost deviation for the sixth month, CV = +8.2 million yuan, a 6.8% overrun, and the schedule deviation SV = -15 days, a 4.2% lag.

[0187] The trend forecast module, based on the LSTM algorithm, predicts that costs will exceed 10% in the next seven days, triggering a level 2 warning.

[0188] The solution selector generates three sets of correction plans, calculates the total cost change, and the smart contract trigger calls the preset contract terms and pushes them to the blockchain platform. The mobile push component sends early warning information through WeChat for Business.

[0189] The construction unit submits a change application through the blockchain platform, along with the cost and schedule impacts. The designer, supervisor, and owner conduct parallel reviews on the blockchain and submit their opinions. Once the review is passed, the smart contract automatically updates the BIM model, cost baseline, and schedule plan.

[0190] The blockchain browser displays the entire change process in a timeline format. Audit agencies can access the stored data after identity verification. The privacy protection component encrypts and stores sensitive data, making it accessible only to authorized parties.

[0191] The performance analysis engine compares actual costs with budgets, actual progress with plans, and calculates cost savings and duration reduction rates. The experience extractor analyzes change records and correction plans, extracts best practices, and the optimization recommendation system identifies high-performance project characteristics based on clustering algorithms and dynamically adjusts warning thresholds.

[0192] Implementation Results: Through dynamic resource allocation and error correction solutions, actual costs were saved by 20 million yuan, approximately 1.67%, exceeding the expected target by 3%. Through 4D simulation optimization and progress correction, the actual construction period was shortened by 5.56%, exceeding the expected target by 5%. The change approval cycle was shortened by 60%, and the data integrity verification error rate was reduced by 80%.

[0193] Summary: The engineering cost progress management control method and system of this patented technical solution are applied throughout the entire process of commercial complex projects. Through the integration of BIM+AI+blockchain technology, it realizes cost-progress linkage monitoring, intelligent error correction, multi-party collaboration and knowledge accumulation, significantly improving project management efficiency and performance.

[0194] The embodiments of the present invention are described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Various changes can be made within the scope of knowledge of those skilled in the art without departing from the spirit of the present invention.

Claims

1. A method for project cost progress management and control, characterized by: The following steps are included: S1001: Use BIM technology to build a refined model, associate cost parameters and time dimensions, and form a 4D model; S1002: Set tiered warning thresholds for cost overruns and schedule delays, collect actual cost and schedule data in real time, calculate deviations, trigger linkage warnings, generate analysis reports, and drive timely corrections; S1003: Use AI algorithms to predict future resource needs, scan market price data, generate multiple configuration plans, compare and select the optimal solution, and dynamically adjust the plan based on market changes or schedule deviations; S1004: Initiate a change application through the blockchain platform, conduct parallel review, automatically execute smart contracts to update models, costs, and schedule benchmarks, and store full-cycle data on the blockchain; S1005: Generate standardized digital delivery packages, analyze project performance, refine management experience to update the knowledge base, and continuously optimize management methods and parameters through data-driven methods.

2. A construction cost progress management and control method according to claim 1, characterized in that: When establishing and associating parameters in a BIM-based refined model, the following steps are included: S2001: Use BIM technology to build a three-dimensional model covering architecture, structure, water supply and drainage, electrical, and HVAC. Each professional team will model separately to ensure that the model depth meets the standard requirements; S2002: Associate cost parameters such as bill of quantities, material prices, labor costs, and machine hourly rates with model components, define unique coding rules for each component type, enter construction properties, and verify data integrity using the "Property Check Tool"; S2003: Embed the construction schedule in the BIM model. Import the construction schedule in Project or Excel format into the BIM platform, associate construction tasks with model components, and define the "planned start time" and "planned completion time" of each task. S2004: Simulate the construction process according to the timeline, generate visual animations, calculate the peak demand for manpower, materials, and machinery in each time period, and identify the contradiction between construction progress and resource supply; S2005: Detect physical collisions between pipelines and structural components, analyze conflicts in construction procedures, simulate efficiency differences between different construction plans, adjust material yards and crane positions, and reduce secondary handling; S2006: List various issues, propose design adjustments and construction plan optimization suggestions based on the issues, and estimate the cost savings and construction period reduction benefits after optimization; S2007: Export the bill of quantities in Excel or CSV format, including the sub-project name, code, quantity and comprehensive unit price; export the 3D model in IFC format for use in subsequent stages; export the schedule in Project or PDF format, including task name, duration and associated model components.

3. A construction cost progress management and control method according to claim 1, characterized in that: The detailed implementation of the dynamic cost and schedule linkage early warning mechanism includes the following steps: S3001: First, the threshold benchmark is determined. The cost benchmark is based on the total contract price and the cost parameters associated with the BIM model. The progress benchmark is based on the construction schedule embedded in the BIM model. S3002: Calculate the warning thresholds. Level 1 warning is when the cost overrun or schedule lag reaches 5% of the baseline value, and level 2 warning is when the cost overrun or schedule lag reaches 10% of the baseline value. The calculation is based on the following formulas: Level 1 cost threshold = Total contract price × 5%; Level 1 schedule threshold = Scheduled duration × 5%; S3003: Collect cost and progress data in real time, check whether the data is logically consistent, and ensure that required fields are not missing; S3004: Quantify the difference between actual and planned costs and locate the source of the deviation. Cost deviation is the actual cost minus the planned cost, and schedule deviation is the actual progress minus the planned progress. S3005: Summarize the causes of cost overruns and schedule delays, predict overrun trends, estimate total cost increases, calculate the number of days of delay, and assess the impact on subsequent tasks; S3006: Set warning rules. A red warning is when both cost overruns and schedule delays reach the second-level threshold. A yellow warning is when a single indicator reaches the second-level threshold, or when both indicators reach the first-level threshold. S3007: When the warning threshold is triggered, push warning information via email, SMS or project management platform. The warning information needs to include the project name, warning level, deviation indicator, cause analysis and recommended measures; S3008: After the early warning information is sent, an early warning report is generated and sent to relevant parties according to preset rules. At the same time, the report is archived in the project document management system for subsequent audit and review.

4. A construction cost progress management and control method according to claim 1, characterized in that: When configuring and optimizing AI-assisted resources, the following steps are involved: S4001: Extract model data and progress data. Model data is to extract component geometry information and process parameters from the BIM model. Progress data is to obtain the planned start or completion time and project volume of each task in the construction schedule. S4002: Train the algorithm based on historical data and feature engineering, input historical project data, train the AI ​​prediction model, and extract key features as predictive variables; S4003: Forecast material demand, labor demand, and machinery demand, and generate a demand forecast report containing resource type, demand period, forecast quantity, and confidence interval; S4004: Access the API of cooperative suppliers to obtain material inventory and real-time quotes, crawl price indices and machinery rental market information from industry websites, and configure data resources; S4005: Clean the data, merge duplicate data, and remove data that significantly deviates from the market price; S4006: Update the cost database daily to record the historical prices and fluctuation trends of materials, machinery, and labor, and generate price trend charts to assist in analyzing seasonal price changes; S4007: Generate multiple resource allocation plans and calculate the total cost using the formula: total cost = material procurement cost + machinery rental cost + labor cost + transportation cost + taxes. This will assess the potential impact of resource shortages or surpluses on the project duration. S4008: Track material price fluctuations and supplier inventory changes in real time, compare actual progress with planned progress, predict changes in resource demand, and adjust resource allocation plans in real time; S4009: Automatically generate standardized contract text based on the optimization results.

5. A construction cost progress management and control method according to claim 1, characterized in that: When collaboratively managing changes to blockchain evidence, the following steps are included: S5001: The construction unit submits a change application through the blockchain platform, including the reason for the change and the impact analysis; S5002: Cost impact is the cost increase or decrease caused by the estimated change, and schedule impact is the potential impact of the predicted change on the construction period; S5003: Design, supervision, and owner review the project in parallel on the blockchain, with review opinions recorded in real time and cannot be tampered with. S5004: Blockchain node permissions are assigned to each participant to ensure that only data within the scope of the permissions can be accessed. Each reviewer views the change application on the blockchain platform and submits their review opinions. The blockchain automatically summarizes the review opinions of all parties and generates a review report. S5005: After the review is passed, the smart contract is automatically triggered to update the BIM model, cost baseline and schedule; S5006: Automatically modify the BIM model and update the cost parameters and schedule associated with the model based on the changed content; S5007: All change records, review comments, and model versions are stored on the blockchain to support subsequent audits; S5008: Use encryption algorithms to protect sensitive data and display the entire change process in a timeline format to assist auditors in conducting compliance reviews. Auditors can access a specified range of stored evidence data after passing identity verification. S5009: Automatically calculate change costs based on the changed model data and link them to progress payments; S5010: Automatically calculate change costs based on preset settlement rules and extract the changed data from the BIM model to ensure calculation accuracy.

6. A construction cost progress management and control method according to claim 1, characterized in that: The following steps are included in digital delivery and post-evaluation: S6001: After completion acceptance, package the final BIM model, cost data and progress records into digital deliverables; S6002: Export the final BIM model in IFC or COBie format, collect scanned copies of contracts, change orders, and acceptance reports, convert them to PDF / A format, and run the delivery package verification tool to check data integrity, consistency, and viruses; S6003: Compare actual costs with budget and calculate cost savings; compare actual progress with plan and calculate duration reduction; S6004: The formula for the savings rate is (budgeted cost - actual cost) / budgeted cost × 100%, and the formula for the duration reduction rate is (planned duration - actual duration) / planned duration × 100%; S6005: Use AI to analyze historical project data and extract best practices for cost control and schedule optimization; S6006: Eliminate outliers, convert cost and schedule data from different projects into comparable data, and use clustering algorithms to identify common characteristics of high-performing projects; S6007: Store experience summaries and lessons learned in the enterprise knowledge base, review them quarterly or semi-annually, and conduct them in conjunction with the project closing phase. Optimize warning thresholds based on historical project data.

7. A construction cost progress management and control system, comprising the following modules: Multi-dimensional data integration and simulation module: used to build a digital twin base based on BIM technology, perform parametric modeling and full-factor association; Intelligent early warning and dynamic decision-making module: used for cost-progress linkage monitoring and intelligent error correction through AI + big data; Blockchain collaboration and knowledge evolution module: used for multi-party collaboration and organizational-level knowledge accumulation through distributed ledgers.

8. The construction cost progress management and control system according to claim 7, characterized in that: The multi-dimensional data integration and simulation deduction module includes: A1001: Multi-disciplinary collaborative modeling unit, including a 3D modeling engine, a parametric component library, version control components, and a multi-disciplinary collision detection module, used to build a high-precision digital twin base across disciplines; A1002: A four-dimensional space-time correlation unit, including a schedule parser, resource loader, timeline simulator, and virtual construction engine, is used to integrate the time dimension into the 3D model to achieve dynamic simulation of the construction process; A1003: Data verification and export unit, including attribute checking tools, multi-format converters and delivery package generators, is used to ensure data integrity and generate standardized deliverables.

9. The construction cost progress management and control system according to claim 7, characterized in that: The intelligent early warning and dynamic decision-making module includes: A2001: Threshold Management Unit, including a benchmark calculator, early warning grading matrix, and risk transmission model, used to define rules for cost and progress monitoring; A2002: Real-time monitoring unit, including a data acquisition gateway, a deviation diagnosis engine, and a trend prediction module, used to continuously track project status and detect deviations in a timely manner; A2003: Decision support unit, including solution selector, smart contract trigger and mobile push component, used to provide correction solutions and automatically execute them.

10. The construction cost progress management and control system according to claim 7, characterized in that: The blockchain collaboration and knowledge evolution module includes: A3001: Change management unit, including a smart contract template library, parallel review workflow, and model automatic updater, to achieve transparency and automation of the change process; A3002: Data evidence storage unit, including blockchain browser, privacy protection components and audit evidence interface, used to ensure data security and support audit traceability; A3003: Knowledge evolution unit, including performance analysis engine, experience extractor and optimization recommendation system, is used to transform project experience into organizational assets.

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