Fabricated building tracking and auditing management method and system

Abstract

The invention relates to the technical field of building engineering management, in particular to a fabricated building tracking and auditing management method and system, and the method comprises the following steps: decomposing the construction process of a fabricated building into a plurality of task units based on construction project information, and acquiring task starting time, personnel configuration, equipment operation state and material consumption data in the execution process of each task, and generating project process monitoring data. According to the invention, the construction process is decomposed into task units and data is collected in real time, so that quality evaluation is changed from traditional manual sampling inspection to an automatic scoring mechanism based on construction standards, the traceability of construction problems is improved, and the accuracy of the quality evaluation is improved by combining the deviation calculation of a progress target and real-time completion time. Quantitative prediction of local delay on overall project risks and cross validation of fund flow data and progress risk information are realized, compliance of fund use is ensured, instantaneity and transparency of fabricated building construction management are improved, and project delay and quality problems are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of construction project management, and particularly to a method and system for tracking and auditing the management of prefabricated buildings. Background Art

[0002] The technical field of construction project management focuses on effectively monitoring and managing multiple processes of construction projects, including planning, design, construction, and operation, aiming to improve construction efficiency, ensure construction quality, and control costs. It involves technical means in multiple aspects such as project management, quality control, progress monitoring, cost control, and construction safety, covering various activities throughout the construction process. With the increasing demand for prefabricated buildings and intelligent building management in the construction industry, by combining various information technologies, including building information modeling, Internet of Things technology, and cloud computing, the management level of construction projects can be effectively improved, ensuring the efficiency and quality of projects during implementation, real-time monitoring of project progress, and optimization of resource allocation.

[0003] Among them, the method for tracking and auditing the management of prefabricated buildings conducts full-process tracking and auditing of multiple links of prefabricated building projects to ensure that the quality, progress, and cost of the projects reach the expected goals. It involves real-time monitoring and data recording of the construction process of prefabricated buildings through information technology means, using building information modeling and Internet of Things technology tools to conduct real-time tracking of the construction site to ensure strict compliance with various standards and specifications, including the use of real-time data analysis, progress management, and quality control during the construction process to ensure that the work at each stage meets the predetermined requirements.

[0004] Traditional methods for tracking and auditing the management of prefabricated buildings have problems of discrete data collection and lagging response in the management of prefabricated buildings. Traditional construction process monitoring relies on phased manual records and post-event summaries, resulting in a time delay in the discovery of quality anomalies. Milestone node comparison methods are mostly used for progress management, lacking task-level dynamic impact analysis. Fund monitoring is limited to the review of financial cycle statements and cannot achieve real-time matching of payment behavior and construction progress. There is no digital mapping relationship between quality assessment standards and on-site data, and the problem tracing link mostly relies on empirical judgment. These discrete management characteristics lead to lagging risk warnings and fragmented decision-making bases, increasing the cost of rectification. Summary of the Invention

[0005] In order to solve the technical problems existing in the prior art, embodiments of the present invention provide a method and system for tracking and auditing the management of prefabricated buildings. The technical solutions are as follows:

[0006] In order to achieve the above object, the present invention adopts the following technical solution. A method for tracking and auditing the management of prefabricated buildings includes the following steps:

[0007] S1: Based on the construction project information, decompose the construction process of the prefabricated building into multiple task units, obtain the task start time, personnel allocation, equipment operation status, and material consumption data during the execution of each task, and generate project process monitoring data;

[0008] S2: Based on the project process monitoring data, calculate the construction quality score of each task according to the construction standards of the prefabricated building and the on-site construction data, detect unqualified construction tasks and record them, and generate a quality score result;

[0009] S3: Based on the quality score result, calculate the schedule deviation according to the schedule target and the actual completion time of each task, identify tasks with schedule lags, and analyze the impact of task delays on the construction project schedule, and generate schedule risk assessment information;

[0010] S4: Invoke the schedule risk assessment information, obtain real-time fund flow information, including monitoring project fund payment, procurement, and budget adjustment data, compare the deviation between the actual expenditure and the budget, detect overspending and non-compliant payment behaviors, and generate fund flow detection data;

[0011] S5: According to the fund flow detection data, identify the causes of various construction problems by analyzing the task execution process, and generate a construction log audit result.

[0012] As a further solution of the present invention, the project process monitoring data includes construction project decomposition records, time information record data, and material consumption information. The quality score result includes multi-task construction quality scores, unqualified construction tasks, and construction standard comparison records. The schedule risk assessment information includes schedule identification information, schedule deviation calculation results, and delay impact analysis results. The fund flow detection data includes the deviation between the actual expenditure and the budget, overspending event records, and non-compliant payment behavior records. The construction log audit result includes quality problem traceability records, schedule problem analysis results, and fund problem traceability information.

[0013] As a further solution of the present invention, based on the construction project information, the steps of decomposing the construction process of the prefabricated building into multiple task units, obtaining the task start time, personnel allocation, equipment operation status, and material consumption data during the execution of each task, and generating project process monitoring data are specifically as follows:

[0014] S101: Obtain the construction project information, decompose the construction process into multiple task units, and generate a project task decomposition list;

[0015] S102: Based on the project task decomposition list, monitor the start time, personnel allocation, equipment operation status, and material consumption data of multiple tasks in real time, and obtain task execution data records;

[0016] S103: Based on the task execution data record, by analyzing the progress, resource utilization, and staffing of each task, summarize the task execution data to form project process monitoring data.

[0017] As a further solution of the present invention, based on the project process monitoring data, according to the construction standards of prefabricated buildings and on-site construction data, calculate the construction quality score of each task, detect unqualified construction tasks and record them. The steps for generating the quality score result are specifically as follows:

[0018] S201: Obtain the project process monitoring data. By monitoring on-site construction data, record multiple key data during the task execution process in real time, including material consumption, construction accuracy, and information on the implementation of construction techniques, to obtain construction process data;

[0019] S202: Based on the construction process data, by comparing with the quality standards of prefabricated buildings, calculate the construction quality score of each task to generate the construction task quality score;

[0020] S203: Based on the construction task quality score, according to the comparison result of the quality score and the construction standards, identify and record unqualified tasks to obtain the quality score result.

[0021] As a further solution of the present invention, the specific formula for calculating the construction quality score of each task is:

[0022]

[0023] Calculate the quality score;

[0024] where Q s represents the construction quality score of the task, β0 is the intercept term of the regression model, β1 is the regression coefficient of material consumption, β2 is the regression coefficient of construction accuracy, β3 is the regression coefficient of the implementation of construction techniques, C m represents the material consumption score, C p represents the construction accuracy score, C pr represents the construction technique score, C max represents the maximum value of the construction technique score.

[0025] As a further solution of the present invention, based on the quality score result, according to the progress target and actual completion time of each task, calculate the schedule deviation, identify tasks with schedule lags, and analyze the impact of task delays on the construction project schedule. The steps for generating the schedule risk assessment information are specifically as follows:

[0026] S301: Based on the quality score result, by obtaining the progress target and actual completion time information of each task, calculate the schedule deviation to obtain the task schedule deviation value;

[0027] S302: Based on the task progress deviation value, detect and identify the lagging tasks, and combine the delay time, resource consumption, and construction environment factors of the target task to calculate the risk scores of multiple delayed tasks and generate a risk assessment value;

[0028] S303: Based on the risk assessment value, by analyzing the impact of multiple task delays on the construction project progress, calculate the progress risk of the construction project and generate progress risk assessment information.

[0029] As a further solution of the present invention, the specific formula for calculating the risk scores of multiple delayed tasks is:

[0030]

[0031] Calculate the risk score and generate a risk assessment value;

[0032] where, R s,i is the risk score of the i-th delayed task, w1 is the weight coefficient of the delay time, T d,i is the delay time of the i-th task, w2 is the weight coefficient of the resource deviation, R c,i is the resource consumption of the i-th task, R avg is the historical average value of the resource consumption of similar tasks, E c is the comprehensive evaluation value of the construction environment factors, w3 is the weight coefficient of the dynamic cost factor, C k,i is the current value of the k-th dynamic cost parameter of the i-th task, C min is the theoretical minimum value of the k-th dynamic cost parameter, C max is the theoretical maximum value of the k-th dynamic cost parameter, n is the total number of dynamic cost parameters, i is the task number, and k is the index of the dynamic cost parameter.

[0033] As a further solution of the present invention, the steps of calling the progress risk assessment information to obtain real-time capital flow information, including monitoring the payment, procurement, and budget adjustment data of project funds, comparing the deviation between the actual expenditure and the budget, detecting overspending and non-compliant payment behaviors, and generating capital flow detection data are specifically as follows:

[0034] S401: Obtain the progress risk assessment information and monitor the capital flow data in real time, including the payment, procurement, and budget adjustment information of project funds, and obtain the capital flow data;

[0035] S402: Based on the capital flow data, by comparing the deviation between the actual expenditure and the budget, calculate the expenditure difference, identify the overspending projects, and generate budget difference data;

[0036] S403: Combine the budget difference data, identify non-compliant payment behaviors by analyzing the compliance of multiple fund expenditures, and generate fund flow detection data.

[0037] As a further solution of the present invention, according to the fund flow detection data, by analyzing the task execution process, the steps of identifying the causes of various construction problems and generating the construction log audit results are specifically as follows:

[0038] S501: According to the fund flow detection data, by analyzing the construction log, obtain the personnel, equipment, and construction process information involved in each task exception event, including quality exception events, schedule exception events, and fund exception events, and obtain task exception data;

[0039] S502: Based on the task exception data, analyze and identify the causes of multiple exception events, including quality problems of precast components, improper operations of construction personnel, and equipment failures, and generate cause analysis results;

[0040] S503: According to the cause analysis results, audit and file the exception events of multiple construction projects by recording the processes and causes of multiple exception events, and generate construction log audit results.

[0041] On the other hand, a prefabricated building tracking audit management system is provided. This system is applied to the prefabricated building tracking audit management method. The system includes:

[0042] The task monitoring module decomposes the construction process into multiple task units based on the construction project information, obtains the task start time, personnel configuration, equipment operation status, and material consumption data during the execution of each task, monitors the execution of each task, and generates project process monitoring data;

[0043] The construction quality analysis module calculates the construction quality score of each task based on the project process monitoring data, combines the construction standards of prefabricated buildings and on-site construction data, identifies unqualified construction tasks and records them, and generates quality score results;

[0044] The task schedule evaluation module analyzes the schedule target and actual completion time of each task according to the quality score results, calculates the schedule deviation, identifies lagging tasks, and evaluates the impact of multiple delayed tasks on the construction schedule in combination with the task delay time, resource consumption, and construction environment factors, and generates schedule risk assessment information;

[0045] The fund monitoring module calls the schedule risk assessment information, obtains real-time fund flow data, compares the deviation between the actual expenditure and the budget, detects overspending and non-compliant payments, and generates fund flow detection data;

[0046] Based on the detected fund flow data, the construction problem auditing module identifies the causes of multiple problems during the construction process by analyzing the task execution process and generates the auditing results of the construction log.

[0047] The beneficial effects brought by the technical solution provided by the embodiment of the present invention at least include:

[0048] By decomposing the construction process into task units and collecting data in real time, the quality assessment is transformed from traditional manual sampling inspection to an automated scoring mechanism based on construction standards, improving the traceability ability of construction problems. Combining the deviation calculation between the progress target and the real-time completion time, the quantitative prediction of the risk of the overall project caused by local delays is realized. The cross-verification of the fund flow data and the progress risk information ensures the compliance of fund use, improves the real-time performance and transparency of the construction management of prefabricated buildings, and reduces the occurrence of project delays and quality problems. Description of the Drawings

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0050] Figure 1 It is a schematic diagram of the work flow of the present invention;

[0051] Figure 2 It is a detailed flowchart of S1 of the present invention;

[0052] Figure 3 It is a detailed flowchart of S2 of the present invention;

[0053] Figure 4 It is a detailed flowchart of S3 of the present invention;

[0054] Figure 5 It is a detailed flowchart of S4 of the present invention;

[0055] Figure 6 It is a detailed flowchart of S5 of the present invention;

[0056] Figure 7 It is a system flowchart of the present invention. Detailed Embodiments

[0057] The following will describe the technical solutions in the present invention with reference to the drawings.

[0058] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to give examples, illustrations or explanations. Any embodiment or design solution described as an "example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of the word "example" is intended to present concepts in a specific manner. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two.

[0059] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meaning they express is the same. "(of)", "corresponding", and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meaning they express is the same.

[0060] In the embodiments of the present invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0061] To make the technical problems to be solved, technical solutions and advantages of the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0062] Please refer to Figure 1 , the present invention provides a technical solution, an assembly building tracking audit management method, including the following steps:

[0063] S1: Based on the construction project information, decompose the construction process of the assembly building into multiple task units, obtain the task start time, personnel allocation, equipment operation status, and material consumption data during the execution of each task, and generate project process monitoring data;

[0064] S2: Based on the project process monitoring data, calculate the construction quality score of each task according to the construction standards of the assembly building and the on-site construction data, detect unqualified construction tasks and record them, and generate a quality score result;

[0065] S3: Based on the quality score result, calculate the schedule deviation according to the schedule target and actual completion time of each task, identify tasks with schedule lags, and analyze the impact of task delays on the construction project schedule, and generate schedule risk assessment information;

[0066] S4: Invoke the schedule risk assessment information, obtain real-time fund flow information, including monitoring project fund payment, procurement, and budget adjustment data, compare the deviation between the actual expenditure and the budget, detect overspending and non-compliant payment behaviors, and generate fund flow detection data;

[0067] S5: Based on the fund flow detection data, by analyzing the task execution process, identify the causes of various construction problems and generate the construction log audit results.

[0068] The project process monitoring data includes the construction project breakdown records, time information record data, material consumption information. The quality scoring results include multi-task construction quality scoring, unqualified construction tasks, and construction standard comparison records. The progress risk assessment information includes progress identification information, progress deviation calculation results, and delay impact analysis results. The fund flow detection data includes the deviation between the actual expenditure and the budget, overspending event records, and non-compliant payment behavior records. The construction log audit results include quality problem trace records, progress problem analysis results, and fund problem trace information.

[0069] Please refer to Figure 2 , based on the construction project information, break down the construction process of the prefabricated building into multiple task units, and obtain the task start time, personnel allocation, equipment operation status, and material consumption data during the execution of each task. The specific steps for generating the project process monitoring data are as follows:

[0070] S101: Obtain the construction project information, break down the construction process into multiple task units, and generate a project task breakdown list;

[0071] The process of obtaining the construction project information first requires disassembling the various tasks of the project, breaking down the entire project into several small tasks. Each task unit needs to determine its goals and required resources according to the actual situation. During the execution process, first conduct a comprehensive analysis of the project to clarify its scope, goals, and key nodes. Subsequently, according to the actual requirements of the tasks, set reasonable resources, personnel allocation, time requirements, etc. For example, assume a building project includes multiple task units such as land leveling, infrastructure construction, steel bar erection, and electrical installation. For each task, set the required resources. For example, land leveling may require 10 bulldozers and 50 workers, while steel bar erection may require 30 welding workers and 20 tons of steel, etc. The execution of each task also requires setting time nodes. When formulating the plan, estimate the time based on historical data, experience, and the availability of resources. When setting the task time, the following formula can be used to estimate the required time for the task:

[0072]

[0073] where, T task is the required time for the task, R total is the total amount of resources required for the task, and P avg is the average productivity of the personnel.

[0074] For example, assume that the total amount of resources for a task is 100 units and the average productivity of personnel is 10 units per hour. Then the time required for this task is:

[0075]

[0076] Through the calculation of this formula, reasonably plan the execution time of tasks to ensure that resources can be efficiently allocated to each task, avoiding overly long task times or excessive resource consumption. During the task execution process, it is also necessary to make dynamic adjustments according to the actual progress to ensure that all links of the project are not disjointed and avoid phenomena such as resource waste or time delay.

[0077] S102: Based on the project task breakdown list, real-time monitor the start times, personnel configurations, equipment operation statuses, and material consumption data of multiple tasks to obtain task execution data records;

[0078] When performing real-time monitoring based on the task breakdown list, it is first necessary to record the start time of each task. The time node at the start of the task needs to be compared with the planned time to ensure that the task can start on time. The system obtains the start time of the task in real time and makes a comparison according to the preset planned time. Calculate the delay time of the task through the following formula:

[0079] ΔT = T actual -T planned ;

[0080] where ΔT is the delay time, T actual is the actual start time, and T planned is the planned start time.

[0081] For example, if the actual start time of a task is 10:30 and the planned start time is 10:00, then the delay time is:

[0082] ΔT = 10:30 - 10:00 = 30 minutes;

[0083] Once the delay time is calculated, the system will promptly notify the project management personnel to help them make corresponding adjustments. For the monitoring of personnel configuration, the system obtains in real time whether the required personnel for each task are in place. If a task cannot proceed smoothly due to insufficient personnel, the system will dynamically adjust the personnel allocation according to the remaining personnel situation of other tasks to ensure that the task can be executed smoothly. The operation status of the equipment is evaluated by monitoring the operation duration of the equipment. For example, the system will regularly obtain the operation duration and downtime of the equipment and analyze the utilization rate of the equipment. The monitoring formula is as follows:

[0084]

[0085] where U is the utilization rate of the equipment, Toperational is the actual working duration of the device, T total is the total available duration of the device.

[0086] For example, if the working duration of the device is 8 hours and the total available duration is 10 hours, the utilization rate of the device is:

[0087]

[0088] If the utilization rate of the device is lower than the set minimum threshold, the system will recommend device maintenance or reconfiguration. For the monitoring of material consumption, the system tracks the material usage during task execution in real time and compares it with the initial budgeted consumption. For example, if a task is expected to consume 100 tons of cement and the actual consumption has reached 110 tons, the system will issue a warning through a comparison formula for the project manager to allocate resources. Through these measures, the execution process of the project can be accurately monitored and managed.

[0089] S103: Based on the task execution data records, by analyzing the progress, resource usage, and staffing of each task, summarize the task execution data to form project process monitoring data;

[0090] Based on the task execution data records, conduct an analysis of task progress, resource usage, and staffing. First, the progress analysis requires comparing the actual progress with the planned progress to evaluate whether the project is advancing on schedule. The calculation of task completion is achieved through the following formula:

[0091]

[0092] where ΔP is the progress difference, P actual is the actual progress, and P planned is the planned progress.

[0093] For example, assume the planned progress of a task is 100% and the actual progress is 85%, then the progress difference is:

[0094]

[0095] Through this calculation, the project manager can clearly know the lag of the task progress and take measures to accelerate the task progress. Resource utilization analysis requires tracking the resources consumed by tasks to analyze whether they are within the budget. For example, if a task is expected to consume 500 units of materials and the actual consumption has reached 550 units, the system will issue a warning prompt to help project managers adjust resource allocation in a timely manner. Staffing analysis monitors the personnel arrival situation of each task in real time through the system to evaluate whether there is a shortage of personnel or unreasonable configuration. The system makes dynamic adjustments based on the priority of tasks and the availability of personnel to ensure the smooth progress of tasks. Through the summary and analysis of these real-time data, project managers can comprehensively grasp the execution situation of the project and make effective scheduling and resource optimization based on actual data to ensure that the project can be successfully completed as planned.

[0096] Please refer to Figure 3 , based on the project process monitoring data, according to the construction standards of prefabricated buildings and the on-site construction data, calculate the construction quality score of each task, detect unqualified construction tasks and record them. The specific steps for generating the quality score result are as follows:

[0097] S201: Obtain the project process monitoring data. By monitoring the on-site construction data, record multiple key data during the task execution process in real time, including material consumption, construction accuracy, and information on the implementation of construction techniques, to obtain the construction process data;

[0098] To obtain the project process monitoring data, first record the key data during the task execution process by monitoring the on-site construction data, which includes multiple key parameters such as material consumption, construction accuracy, and the implementation of construction techniques. During the specific implementation process, the monitoring system first needs to collect data related to material consumption, record the input and consumption of materials, ensure the rational use of materials, and avoid waste. In terms of construction accuracy, the system monitors the implementation of each process in real time to ensure that the construction meets the preset accuracy standards. Information on the implementation of construction techniques needs to be monitored in real time by comparing the construction process with the project standards to ensure that the construction process complies with technical specifications. When implementing this process, the actual situation of a specific material consumption is calculated through the following formula:

[0099] M actual = M input - M remaining ;

[0100] Among them, M actual is the actual consumption, M input is the initial material input, and M remaining is the remaining material after construction.

[0101] For example, if 100 tons of cement are initially invested in a certain task and 30 tons of cement remain after construction, the actual consumption is:

[0102] M actual =100 - 30 = 70 tons;

[0103] In addition, the monitoring of construction accuracy is completed by measuring the difference between the actual execution of on-site processes and the predetermined specifications. For example, if the preset thickness of a wall is 10 cm and the actual measurement result is 9.5 cm, the deviation is 0.5 cm. The system will feedback this data in real time for timely adjustment of the construction process. The execution of the construction process is compared through equipment monitoring and personnel operation records to ensure that all construction links are carried out according to the process requirements, and any deviation can be detected and corrected in a timely manner. Finally, the obtained construction process data is summarized into a comprehensive monitoring report for subsequent analysis and optimization.

[0104] S202: Based on the construction process data, by comparing with the quality standards of prefabricated buildings, calculate the construction quality score of each task and generate the construction task quality score;

[0105] The specific formula for calculating the construction quality score of each task is:

[0106]

[0107] Calculate the quality score;

[0108] Among them, Q s represents the construction quality score of the task, β0 is the intercept term of the regression model, β1 is the regression coefficient of material consumption, β2 is the regression coefficient of construction accuracy, β3 is the regression coefficient of the execution of the construction process, C m represents the material consumption score, C p represents the construction accuracy score, C pr represents the construction process score, C max represents the maximum value of the construction process score.

[0109] Formula:

[0110]

[0111] Detailed explanation of the formula and the derivation process of the formula calculation:

[0112] The formula is used to calculate the quality score of the construction task, and the result is used to evaluate the overall quality level of the task under various key indicators;

[0113] Meaning and setting values of parameters:

[0114] β0 is the intercept term of the regression model, assumed to be 5, which reflects the baseline value of the construction quality score in the absence of any influence from independent variables;

[0115] β1 is the regression coefficient of the material consumption score, assumed to be 0.4, indicating that the influence of material consumption on the quality score accounts for 40%;

[0116] β2 is the regression coefficient of the construction precision score, assumed to be 0.35, indicating that the influence of construction precision on the quality score accounts for 35%;

[0117] β3 is the regression coefficient of the construction process score, assumed to be 0.25, indicating that the influence of the construction process on the quality score accounts for 25%;

[0118] C m is the material consumption score. Assume C m = 94.74, which reflects the gap between the material consumption and the planned consumption;

[0119] C p is the construction precision score. Assume C p = 98, which reflects the compliance of the construction precision;

[0120] C pr is the construction process score, assumed to be 80, indicating that the construction task has achieved 80% of the expected standard in terms of process execution;

[0121] C max is the maximum value of the construction process score, assumed to be 100;

[0122] Substitute the parameters into the formula for calculation:

[0123]

[0124] 0.4·94.74 = 37.896;

[0125] 0.35·98 = 34.3;

[0126]

[0127] Q s = 5 + 37.896 + 34.3 + 0.2 = 77.396;

[0128] The result 77.396 indicates the quality score of the construction task, reflecting the comprehensive quality level of the task in terms of material consumption, construction precision, and construction process. By comparing with the quality standard, if it is lower than the preset quality threshold, it means that the quality of the task does not meet the standard and needs to be further optimized or adjusted.

[0129] S203: Based on the quality scores of construction tasks, identify and record non-conforming tasks according to the comparison results between the quality scores and construction standards, and obtain the quality score results;

[0130] Based on the quality scores of construction tasks, identify and record non-conforming tasks according to the comparison results between the quality scores and construction standards. During the execution process, first compare the quality score of each task with the minimum quality standard of the prefabricated building to calculate whether each task meets the standard. For non-conforming tasks, the system needs to identify them in a timely manner and record their relevant information for subsequent optimization. The threshold of the quality score is set according to the requirements of different tasks. Assume that the minimum standard of the quality score is 70 points. When the quality score of a certain task is lower than this standard, the system will mark this task as a non-conforming task, record this information, and notify the project management personnel to make adjustments or re-construct. To calculate whether a task is qualified, use the following formula:

[0131] ΔQ = Q score - Q min ;

[0132] where ΔQ is the quality score difference, Q score is the actual quality score of the construction task, and Q min is the set minimum quality score standard.

[0133] For example, if the quality score of a certain task is 65 points and the minimum quality score standard is 70 points, then the calculation is as follows:

[0134] ΔQ = 65 - 70 = -5;

[0135] If the result is negative, it means that the task does not meet the quality standard and is non-conforming. The system will mark and record this task. The relevant data of these non-conforming tasks will be stored for subsequent improvement or re-construction. By identifying and recording non-conforming tasks, project managers can grasp the project quality problems in real time, take corrective measures in a timely manner, and ensure that the overall project quality meets the expected requirements.

[0136] Please refer to Figure 4 , for the steps of calculating the schedule deviation, identifying tasks with schedule lags, and analyzing the impact of task delays on the construction project schedule based on the quality score results according to the schedule target and actual completion time of each task, and generating schedule risk assessment information, specifically as follows:

[0137] S301: Based on the quality score results, calculate the schedule deviation by obtaining the schedule target and actual completion time information of each task, and obtain the task schedule deviation value;

[0138] Based on the quality scoring results, first obtain the progress target and actual completion time information for each task, and calculate the progress deviation value from this. During the execution process, the system first extracts the planned target progress time and actual completion time of each task from the task management platform. Next, by calculating the difference between the planned progress and the actual progress, the progress deviation value is obtained. The calculation formula for the progress deviation is as follows:

[0139] ΔT = T actual - T planned ;

[0140] where ΔT is the progress deviation, T actual is the actual completion time, and T planned is the planned completion time.

[0141] For example, if the planned completion time of a certain task is February 10, 2025, and the actual completion time is February 15, 2025, the progress deviation is:

[0142] ΔT = 2025 - 02 - 15 - 2025 - 02 - 10 = 5 days;

[0143] Calculating the progress deviation value helps project managers identify task delays in a timely manner, and then take measures for adjustment to ensure that the overall project progress is not significantly delayed.

[0144] S302: Based on the task progress deviation value, detect and identify lagging tasks, and combine the delay time, resource consumption, and construction environment factors of the target tasks to calculate the risk scores of multiple delayed tasks and generate a risk assessment value;

[0145] The specific formula for calculating the risk scores of multiple delayed tasks is:

[0146]

[0147] Calculate the risk scores and generate a risk assessment value;

[0148] where R s,i is the risk score of the i-th delayed task, w1 is the weight coefficient of the delay time, T d,i is the delay time of the i-th task, w2 is the weight coefficient of the resource deviation, R c,i is the resource consumption of the i-th task, R avg is the historical average of the resource consumption of similar tasks, E c is the comprehensive evaluation value of the construction environment factors, w3 is the weight coefficient of the dynamic cost factor, C k,i is the current value of the k-th dynamic cost parameter of the i-th task, C min is the theoretical minimum value of the k-th dynamic cost parameter, C maxis the theoretical maximum value of the k-th dynamic cost parameter, n is the total number of dynamic cost parameters, i is the task number, and k is the index of the dynamic cost parameter.

[0149] Formula:

[0150]

[0151] Detailed explanation of the formula and the derivation process of the formula calculation:

[0152] The formula is used to calculate the risk score of a delayed task, and the result is used to evaluate the possible risks brought by the task during the overall construction process, identify and quantify risk factors;

[0153] Meaning and setting values of parameters:

[0154] R s,i represents the risk score of the i-th delayed task, reflecting the risk level of the task;

[0155] w1 is the weight coefficient of the delay time, assumed to be 0.4, reflecting the impact of the task delay time on the risk score;

[0156] T d,i is the delay time of the i-th task. Assume T d,1 = 5 days, indicating that the actual completion time of the task is 5 days later than the planned time;

[0157] w2 is the weight coefficient of the resource deviation, assumed to be 0.3, reflecting the impact of the deviation between the resource consumption of the task and the historical average value on the risk score;

[0158] R c,i is the resource consumption of the i-th task, assumed to be 200, obtained by real-time monitoring and recording of the material consumption of the task;

[0159] R avg is the historical average value of the resource consumption of similar tasks, assumed to be 180, sourced from the resource consumption records of historical projects;

[0160] E c is the comprehensive evaluation value of the construction environment factors, assumed to be 1.2, indicating the degree of influence of the construction environment on the task;

[0161] w3 is the weight coefficient of the dynamic cost factor, assumed to be 0.3, reflecting the impact of the dynamic cost on the risk score;

[0162] C k,i is the current value of the k-th dynamic cost parameter of the i-th task. Assume the first cost parameter C 1,1 = 100;

[0163] C minis the theoretical minimum value of the k-th dynamic cost parameter, assumed to be 50 standard units, representing the lowest acceptable value of the task cost parameter;

[0164] C max is the theoretical maximum value of the k-th dynamic cost parameter, assumed to be 200 standard units, representing the highest acceptable value of the task cost parameter;

[0165] n represents the total number of items of the dynamic cost parameter, assumed to be 3;

[0166] Substitute the parameters into the formula for calculation:

[0167]

[0168] w2·|R c,i -R avg | = 0.3·|200 - 180| = 0.3·20 = 6;

[0169]

[0170] R s,1 = 5.7453 + 0.3 = 6.0453;

[0171] The result 6.0453 indicates the risk score of the first delayed task, indicating that the overall risk of this task is relatively high due to the impacts of delay, resource consumption deviation, and dynamic cost.

[0172] S303: Based on the risk assessment value, by analyzing the impacts of multiple task delays on the construction project schedule, calculate the schedule risk of the construction project and generate schedule risk assessment information;

[0173] Based on the risk assessment value, by analyzing the impacts of multiple task delays on the construction project schedule, calculate the schedule risk of the construction project and generate schedule risk assessment information. During the execution process, first, it is necessary to extract the respective risk scores from multiple lagging tasks and perform weighted calculations according to the relative importance of these tasks and their impacts on the overall project schedule. The risk score of each task is adjusted according to its impact on the overall project schedule, and finally, an overall schedule risk score is generated. The formula for schedule risk is shown as follows:

[0174]

[0175] Among them, P risk is the overall schedule risk score, w i is the weight of the i-th task on the overall project schedule, is the risk score of the i-th task, and n is the total number of delayed tasks.

[0176] Assume there are 3 lagging tasks with risk scores of 77, 60, and 45 respectively, and weights of 0.5, 0.3, and 0.2 respectively. Then the schedule risk score is:

[0177] P risk = 0.5·77 + 0.3·60 + 0.2·45 = 38.5 + 18 + 9 = 65.5;

[0178] The calculated schedule risk score is 65.5. The system will provide overall schedule risk assessment information for the construction project based on this score, helping project managers understand the sources of risks and take targeted measures to adjust the schedule and optimize resource allocation.

[0179] Please refer to Figure 5 , call the schedule risk assessment information, obtain real-time fund flow information, including monitoring project fund payment, procurement, and budget adjustment data, comparing the deviation between actual expenditure and budget, detecting overspending and non-compliant payment behaviors. The steps to generate fund flow detection data are specifically as follows:

[0180] S401: Obtain schedule risk assessment information, and monitor fund flow data in real time, including project fund payment, procurement, and budget adjustment information, to obtain fund flow data;

[0181] The process of obtaining schedule risk assessment information first requires real-time monitoring of the project's fund flow data, including project fund payment, procurement, and budget adjustment information. The execution of this process starts with obtaining relevant fund flow data of the project from the fund management system, and real-time recording of the project's payment situation, such as the amount already paid, the fund outflow for procurement, and any adjustment changes in the budget. The system needs to analyze these data to understand the dynamic changes in project funds, especially for real-time tracking of the fund payment progress and procurement situation. For example, a project sets a fund of 10 million yuan at the beginning of the budget, and 6 million yuan has been paid for material procurement. The system will record this 6 million yuan payment amount in real time and compare it with the payment plan in the budget. If there are unplanned expenditures during the procurement process, the system will promptly remind project managers. In addition, the system also needs to obtain budget adjustment information in real time. If the expenditure in a certain link exceeds the expectation, the manager can make a budget adjustment in the system, and the system will automatically update the budget and monitor the fund flow data in real time through the following formula:

[0182] F diff = F actual - F planned ;

[0183] where, F diff is the fund difference, F actual is the actual payment amount, and F planned is the planned payment amount.

[0184] For example, if the planned payment is 5 million yuan and the actual payment is 6 million yuan, the fund difference is:

[0185] F diff = 6 - 5 = 1 million yuan;

[0186] This difference will be used as a monitoring indicator to help managers promptly detect and correct anomalies in the fund flow.

[0187] S402: Based on the fund flow data, by comparing the deviation between the actual expenditure and the budget, calculate the expenditure difference, identify overspending items, and generate budget difference data;

[0188] Based on the fund flow data, by comparing the deviation between the actual expenditure and the budget, calculate the expenditure difference, identify overspending items, and generate budget difference data. During the execution process, first compare the deviation between the actual expenditure and the budget, and use the following formula to calculate the difference:

[0189] ΔF = F actual - F budget ;

[0190] where ΔF is the expenditure difference, F actual is the actual expenditure amount, and F budget is the expected expenditure amount in the budget.

[0191] For example, assume that the planned expenditure in the budget for a certain project is 3 million yuan, while the actual expenditure is 3.5 million yuan. Then the expenditure difference is:

[0192] ΔF = 3.5 - 3 = 0.5 million yuan;

[0193] At this time, the difference is 0.5 million yuan. The system will mark this project as an overspending item and generate budget difference data. The system can identify which projects are overspending by comparing the budget and actual expenditures of each project's expenditure, and mark these overspending projects for further inspection by managers. Based on these differences, the system also generates a detailed budget report listing each overspending item and its reasons for decision-makers to make adjustments.

[0194] S403: Combine the budget difference data, by analyzing the compliance of multiple fund expenditures, identify non-compliant payment behaviors, and generate fund flow detection data;

[0195] Combined with budget variance data, by analyzing the compliance of multiple fund expenditures, identify non-compliant payment behaviors and generate fund flow detection data. During the execution process, the system determines whether there are non-compliant payment behaviors by comparing the budget variance data and the actual payment data. If a payment does not go through the approval process or the payment amount exceeds the contractually agreed scope, the system will mark it. Special attention should be paid to the compliance of procurement contracts and payment documents during the analysis. Combining information such as procurement lists and payment forms, determine whether each payment complies with the regulations. Analyze the compliance through the following formula:

[0196]

[0197] Among them, C compliance is the compliance score, P actual is the actual payment amount, and P contract is the payment amount agreed in the contract.

[0198] For example, assume that the payment amount agreed in the contract is 2 million yuan, and the actual payment is 2.2 million yuan. Then the compliance score is:

[0199]

[0200] The compliance score of 0.9 indicates that this payment behavior is compliant. However, if the score is lower than the set threshold, the system will mark this payment as a non-compliant payment behavior and generate fund flow detection data for subsequent auditing and risk management. Through this process, the system can effectively monitor the fund flow in the project, timely detect non-compliant behaviors, and generate detection reports for relevant personnel for further processing.

[0201] Please refer to Figure 6 , according to the fund flow detection data, by analyzing the task execution process, the steps to identify the causes of various construction problems and generate the construction log audit results are specifically as follows:

[0202] S501: According to the fund flow detection data, by analyzing the construction log, obtain the information of the personnel, equipment, and construction process involved in each task abnormal event, including quality abnormal events, progress abnormal events, and fund abnormal events, and obtain task abnormal data;

[0203] According to the capital flow detection data, by analyzing the construction logs, information on the personnel, equipment, and construction process involved in each task's abnormal event is obtained. During the execution process, the system first needs to extract relevant event records from the construction logs, covering multiple aspects such as quality anomalies, schedule anomalies, and capital anomalies. By monitoring the data in the construction logs in real-time, the system can identify abnormal situations in each task and further extract the information on the personnel, equipment, and construction process involved. Abnormal situations of personnel may involve worker absenteeism, insufficient skills, or improper operation. Equipment anomalies may manifest as equipment failures, improper use, or untimely maintenance. Abnormalities in the construction process may include substandard quality, improper processes, or improper use of materials. For example, assume that in a construction task, a task delay is caused by a malfunction of a certain piece of equipment. The system will record in the construction logs information such as the failure time of the equipment, the repair time, the model of the equipment, and its relevant responsible person. Quality abnormal events may be related to unqualified construction materials or non-standard processes. The system needs to correlate the relevant data and calculate the abnormal duration of each task through the following formula:

[0204] T exception =T finish -T planned ;

[0205] where, T exception is the abnormal duration, T finish is the actual completion time of the task, and T planned is the planned completion time.

[0206] For example, if the planned completion time of a certain task is February 10, 2025, and the actual completion time is February 15, 2025, then the abnormal duration is:

[0207] T exception =2025 - 02 - 15 - 2025 - 02 - 10 = 5 days;

[0208] The system analyzes the abnormal data of each task in this way to identify the problems existing in the tasks and conduct effective tracking.

[0209] S502: Based on the task abnormal data, analyze and identify the causes of multiple abnormal events, including quality problems of precast components, improper operation of construction personnel, and equipment failures, and generate the cause analysis results;

[0210] Based on task exception data, analyze and identify the causes of multiple exception events, and generate cause analysis results. During the execution process, the system needs to carefully analyze the exception data of each task to identify the specific causes of each exception event. For example, quality problems may be caused by substandard production quality of prefabricated components, improper operations may stem from the technical level or operational mistakes of construction personnel, and equipment failures may be due to equipment aging or untimely maintenance. To analyze exception events, the system needs to classify different types of exception data and set cause classification and evaluation criteria for each type of exception event. The cause analysis of quality problems may require comparison with material inspection reports and quality standards, the cause of improper operations needs to be judged based on construction logs and personnel operation records, and the analysis of equipment failures needs to refer to equipment maintenance records and operating conditions. Suppose the system discovers during the analysis of the exception data of a certain task that equipment failures account for 60% of the total exception duration, improper personnel operations account for 30%, and quality problems account for 10%. The system will calculate the contribution degree of each cause based on these data and output the cause analysis results. The specific calculation formula is as follows:

[0211]

[0212] Among them, C fault is the contribution degree of the cause of equipment failure, T fault is the exception duration caused by equipment failure, and T exception is the total exception duration of the task.

[0213] Suppose the total exception duration of a certain task is 10 days, and the exception duration caused by equipment failure is 6 days. Then the contribution degree of the cause of equipment failure is:

[0214]

[0215] Through this kind of analysis, the system can generate the cause analysis results of each exception event and provide targeted improvement suggestions.

[0216] S503: According to the cause analysis results, by recording the processes and causes of multiple exception events, audit and file the exception events of multiple construction projects to generate construction log audit results;

[0217] Based on the cause analysis results, by recording the processes and causes of multiple abnormal events, the abnormal events of multiple construction projects are archived to generate the audit results of construction problems. During the execution process, the system needs to archive the abnormal events in multiple construction projects, record the specific process, occurrence cause, and the participation of relevant personnel and equipment of each event. This information will be used for subsequent auditing and rectification work. By analyzing the frequency, severity of different abnormal events in the task and their impact on the overall project progress, the system can classify construction problems and generate an audit report. The archived information of each abnormal event needs to describe in detail the background, time, responsible person, equipment, materials, etc. of the event, and conduct a comprehensive evaluation in combination with the construction log and cause analysis results. Suppose the system records the abnormal events in three construction projects, among which the quality anomalies in Project A account for 30% of the events, the equipment failures in Project B account for 40%, and the schedule anomalies in Project C account for 30%. The system will summarize these data and generate an audit report on construction problems. For example, if the equipment failure in Project B causes a 10-day delay, the system will record the process of this event and generate audit results based on it.

[0218] Please refer to Figure 7 , a prefabricated building tracking audit management system. The prefabricated building tracking audit management system is used to execute the above-mentioned prefabricated building tracking audit management method. The system includes:

[0219] The task monitoring module decomposes the construction process into multiple task units based on the construction project information, obtains the task start time, personnel allocation, equipment operation status, and material consumption data during the execution of each task, monitors the execution of each task, and generates project process monitoring data;

[0220] The construction quality analysis module calculates the construction quality score of each task based on the project process monitoring data, combines the construction standards of prefabricated buildings and on-site construction data, identifies unqualified construction tasks and records them, and generates the quality score result;

[0221] The task progress evaluation module analyzes the progress target and actual completion time of each task according to the quality score result, calculates the progress deviation, identifies lagging tasks, and evaluates the impact of multiple delayed tasks on the construction progress in combination with the task delay time, resource consumption, and construction environment factors, and generates progress risk assessment information;

[0222] The funds monitoring module calls the progress risk assessment information, obtains real-time funds flow data, compares the deviation between the actual expenditure and the budget, detects overspending and non-compliant payments, and generates funds flow detection data;

[0223] The construction problem audit module generates the audit results of the construction log by analyzing the task execution process and identifying the causes of multiple problems in the construction process based on the funds flow detection data.

[0224] It should be understood that in various embodiments of the present invention, the sequence numbers of the above processes do not imply the order of execution, and the order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0225] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0226] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the devices, apparatuses, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0227] In several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0228] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0229] In addition, the functional units in various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0230] When the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0231] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for tracking and auditing prefabricated buildings, characterized in that: The method comprises: S1: Based on the construction project information, the construction process of the prefabricated building is decomposed into multiple task units, and the task start time, personnel configuration, equipment operation status, and material consumption data of each task execution process are obtained to generate project process monitoring data; S2: Based on the project process monitoring data, according to the construction standards of prefabricated buildings and on-site construction data, calculate the construction quality score of each task, detect and record unqualified construction tasks, and generate quality score results; S3: Based on the quality scoring results, according to the progress target and actual completion time of each task, calculate the progress deviation and identify the tasks that are behind schedule, analyze the impact of task delays on the progress of the construction project, and generate progress risk assessment information; S4: calling the progress risk assessment information to obtain real-time fund flow information, including monitoring the payment, procurement and budget adjustment data of project funds, comparing the deviation between actual expenditure and budget, detecting overspending and non-compliant payment behaviors, and generating fund flow detection data; S5: Based on the fund flow detection data, by analyzing the task execution process, identifying the causes of various construction problems, and generating construction log audit results.

2. The method for tracking and auditing prefabricated buildings according to claim 1 is characterized in that: The project process monitoring data includes construction project decomposition records, time information record data, and material consumption information; the quality scoring results include multi-task construction quality scores, unqualified construction tasks, and construction standard comparison records; the progress risk assessment information includes progress identification information, progress deviation calculation results, and delay impact analysis results; the capital flow detection data includes deviations between actual expenditures and budgets, overspending event records, and non-compliant payment behavior records; the construction log audit results include quality problem tracing records, progress problem analysis results, and capital problem tracing information.

3. The method for tracking and auditing prefabricated buildings according to claim 1 is characterized in that: Based on the construction project information, the construction process of prefabricated buildings is decomposed into multiple task units, and the task start time, personnel configuration, equipment operation status, and material consumption data of each task execution process are obtained. The specific steps for generating project process monitoring data are as follows: S101: Acquire construction project information, decompose the construction process into multiple task units, and generate a project task decomposition list; S102: Based on the project task decomposition list, real-time monitoring of multiple task start times, personnel configuration, equipment operation status, and material consumption data is performed to obtain task execution data records; S103: Based on the task execution data records, by analyzing the progress, resource usage, and staffing of each task, the task execution data is summarized to form project process monitoring data.

4. The method for tracking and auditing prefabricated buildings according to claim 1 is characterized in that: Based on the project process monitoring data, according to the construction standards of prefabricated buildings and on-site construction data, the construction quality score of each task is calculated, and unqualified construction tasks are detected and recorded. The specific steps for generating the quality score results are as follows: S201: Acquire the project process monitoring data, monitor the on-site construction data, and record multiple key data in the task execution process in real time, including material consumption, construction accuracy, and construction process execution information, to acquire the construction process data; S202: Based on the construction process data, by comparing with the quality standards of prefabricated buildings, a construction quality score of each task is calculated to generate a construction task quality score; S203: Based on the quality score of the construction task and according to the comparison result between the quality score and the construction standard, unqualified tasks are identified and recorded to obtain a quality score result.

5. The method for tracking and auditing prefabricated buildings according to claim 4 is characterized in that: The specific formula for calculating the construction quality score of each task is: Calculate quality scores; Among them, Q s represents the construction quality score of the task, β0 is the intercept term of the regression model, β1 is the regression coefficient of material consumption, β2 is the regression coefficient of construction accuracy, β3 is the regression coefficient of construction process execution, and C m Represents the material consumption score, C p Represents the construction accuracy score, C pr Represents the construction process score, C max Represents the maximum value of the construction workmanship score.

6. The method for tracking and auditing prefabricated buildings according to claim 1 is characterized in that: Based on the quality scoring results, according to the progress target and actual completion time of each task, the progress deviation is calculated and the delayed tasks are identified, and the impact of task delays on the progress of the construction project is analyzed. The specific steps for generating progress risk assessment information are as follows: S301: Based on the quality scoring result, by obtaining the progress target and actual completion time information of each task, the progress deviation is calculated to obtain the task progress deviation value; S302: Based on the task progress deviation value, detect and identify the delayed tasks, and calculate the risk scores of multiple delayed tasks in combination with the delay time, resource consumption, and construction environment factors of the target tasks to generate a risk assessment value; S303: Based on the risk assessment value, by analyzing the impact of multiple task delays on the progress of the construction project, the progress risk of the construction project is calculated, and progress risk assessment information is generated.

7. The method for tracking and auditing prefabricated buildings according to claim 6 is characterized in that: The specific formula for calculating the risk scores of multiple delayed tasks is: Calculate risk scores and generate risk assessment values; Among them, R s,i is the risk score of the i-th delayed task, w1 is the weight coefficient of the delay time, T d,i is the delay time of the i-th task, w2 is the weight coefficient of resource deviation, R c,i is the resource consumption of the i-th task, R avg is the historical average resource consumption of similar tasks, E c is the comprehensive evaluation value of construction environment factors, w3 is the weight coefficient of dynamic cost factors, C k,i is the current value of the kth dynamic cost parameter of the ith task, C min is the theoretical minimum value of the kth dynamic cost parameter, C max is the theoretical maximum value of the kth dynamic cost parameter, n is the total number of dynamic cost parameters, i is the task number, and k is the index of the dynamic cost parameter.

8. The method for tracking and auditing prefabricated buildings according to claim 1 is characterized in that: The progress risk assessment information is called to obtain real-time fund flow information, including monitoring the payment, procurement and budget adjustment data of project funds, comparing the deviation between actual expenditure and budget, detecting overspending and non-compliant payment behavior, and generating fund flow detection data in the following steps: S401: Obtain the progress risk assessment information, monitor the fund flow data in real time, including the payment, procurement and budget adjustment information of the project funds, and obtain the fund flow data; S402: Based on the fund flow data, by comparing the deviation between the actual expenditure and the budget, calculating the expenditure difference, identifying the overspending items, and generating budget difference data; S403: In combination with the budget difference data, the compliance of multiple fund expenditures is analyzed to identify non-compliant payment behaviors and generate fund flow detection data.

9. The method for tracking and auditing prefabricated buildings according to claim 1 is characterized in that: Based on the fund flow detection data, by analyzing the task execution process, identifying the causes of various construction problems, and generating the construction log audit results, the specific steps are: S501: According to the capital flow detection data, by analyzing the construction log, the personnel, equipment, and construction process information involved in each task abnormality event are obtained, including quality abnormality events, progress abnormality events, and capital abnormality events, and task abnormality data are obtained; S502: Based on the task abnormality data, analyzing and identifying the causes of multiple abnormal events, including quality problems of prefabricated components, improper operation of construction personnel, and equipment failure, and generating cause analysis results; S503: According to the cause analysis result, by recording the processes and causes of multiple abnormal events, auditing and archiving the abnormal events of multiple construction projects, and generating construction log audit results.

10. An assembled building tracking and auditing management system, characterized in that: According to the method for tracking and auditing management of prefabricated buildings according to any one of claims 1 to 9, the system comprises: The task monitoring module decomposes the construction process into multiple task units based on the construction project information, obtains the task start time, personnel configuration, equipment operation status, and material consumption data during the execution of each task, monitors the execution of each task, and generates project process monitoring data; The construction quality analysis module calculates the construction quality score of each task based on the project process monitoring data, combined with the construction standards and on-site construction data of the prefabricated building, identifies and records unqualified construction tasks, and generates quality score results; The task progress assessment module analyzes the progress target and actual completion time of each task based on the quality scoring results, calculates the progress deviation, identifies delayed tasks, and evaluates the impact of multiple delayed tasks on the construction progress in combination with task delay time, resource consumption, and construction environment factors, and generates progress risk assessment information; The fund monitoring module calls the progress risk assessment information, obtains real-time fund flow data, compares the deviation between actual expenditure and budget, detects overspending and non-compliant payments, and generates fund flow detection data; The construction problem audit module is based on the capital flow detection data, analyzes the task execution process, identifies the causes of multiple problems in the construction process, and generates construction log audit results.

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