An engineering cost risk monitoring system and method

Abstract

The application relates to the technical field of risk monitoring, and discloses an engineering cost risk monitoring system and method, which comprises an information insufficiency judging unit, an information delay judging unit and an information falsity judging unit. The information insufficiency judging unit judges whether cost data is missing according to material price fluctuation and construction progress deviation. The information delay judging unit estimates the delay time of reporting according to sudden severe weather and material shortage degree. The information falsity judging unit generates a three-dimensional engineering earthwork building material model according to unmanned aerial vehicle surveying and mapping, and judges whether information falsity exists by comparing the reported quantity of a construction party. The information insufficiency judging unit, the information delay judging unit and the information falsity judging unit can comprehensively cover three core risks of cost data missing, reporting delay and information falsity, and solve the limitations of single dependence on manual auditing or single data source in traditional technologies.

Description

Technical Field

[0001] This invention relates to the field of risk monitoring technology, and in particular to an engineering cost risk monitoring system and method. Background Technology

[0002] Construction cost risks include: independent risk allocation, internal risk allocation, external risk allocation, and information risk allocation. Independent risk allocation arises because cost consulting firms, by their very nature, lack independence, resulting in limited project scope and uncertain funding, leading to gaps in engineering consulting services and thus creating cost consulting risk. Internal risk allocation stems from inherent risks in consulting services caused by insufficient execution of internal control systems. External risk allocation arises from external risks caused by changes in the client or stakeholders.

[0003] Information risk refers to insufficient, delayed, or false information collection, or decision-making errors caused by technical problems in consulting, thereby affecting the interests of the consulted party. Insufficient information collection includes the lack of recording or missing data on key aspects (such as design changes, material price fluctuations, and construction schedule deviations), and reliance on a single channel (such as the contractor's report) without multi-party verification (supervisors, suppliers, third-party testing).

[0004] An existing patent (CN119151288A) discloses a method for monitoring engineering cost risks and an engineering cost management platform. The technology disclosed in this patent constructs a critical task chain (such as a first and second critical task chain) that directly links contract terms and construction progress, enabling dynamic review and early warning of contract performance. However, it lacks coverage for issues such as missing, delayed, and falsified cost data (e.g., material price fluctuations, construction progress deviations). Summary of the Invention

[0005] The main technical problem solved by this invention is to provide an engineering cost risk monitoring system and method, which solves the problems mentioned in the background art.

[0006] To solve the above-mentioned technical problems, according to one aspect of the present invention, more specifically, an engineering cost risk monitoring system includes an information insufficiency judgment unit, an information delay judgment unit, and an information falsification judgment unit;

[0007] The information insufficiency judgment unit determines whether cost data is missing based on fluctuations in material prices and deviations in construction progress.

[0008] The information delay judgment unit estimates the reporting delay time based on the severity of sudden severe weather and the degree of material shortage.

[0009] The information falsification judgment unit determines whether there is falsified information by comparing the three-dimensional engineering earthwork and building material model generated by UAV mapping with the quantities reported by the construction party.

[0010] Furthermore, the information insufficiency judgment unit and the information delay judgment unit jointly include an information collection module, an information processing module, and an early warning judgment module;

[0011] The information collection module is used to collect real-time data on material prices, construction progress information, as well as information on sudden severe weather and the degree of material shortage.

[0012] The information processing module is used to parameterize the real-time changes in material prices and deviations in construction progress, as well as to parameterize sudden severe weather and the degree of material shortage.

[0013] The early warning and judgment module determines whether cost data is missing based on real-time deviations in material prices and construction progress, and estimates the delay time for reporting based on the severity of weather and the degree of material shortage.

[0014] Furthermore, the condition coefficients for the insufficient information judgment unit to calculate the cost data as missing are as follows: In the formula, The condition coefficient indicates that the cost data is missing. Indicates the cost deviation of engineering materials, This indicates the price difference rate between the budgeted price and the actual purchase price. This indicates the cumulative number of days of deviation in construction progress.

[0015] Furthermore, when When this occurs, it indicates a significant lack of data regarding key aspects of the project cost; when If the data is accurate, it indicates that there are no significant missing data points in the key aspects of the project cost.

[0016] Furthermore, the information delay judgment unit estimates the postponement of the reporting time as follows: In the formula, This indicates the estimated number of days the reporting time will be delayed. Indicates the number of days affected by weather. This represents the efficiency coefficient. This indicates the difference between the actual delivery time of the materials and the original plan. This indicates the number of days of construction that the current inventory can support. This represents the critical path coefficient.

[0017] Furthermore, the information falsification judgment unit specifically includes a drone deployment module, a drone data acquisition module, and a 3D modeling module;

[0018] The drone deployment module is used to plan the drone's flight altitude, forward overlap rate, and lateral overlap rate.

[0019] The UAV data acquisition module is used to collect the height of each sampling point of the building material earthwork and the area occupied by the earthwork.

[0020] The 3D modeling module is used to generate a mathematical model of the earthwork for building materials based on UAV mapping data, and then calculate the volume of the earthwork for building materials.

[0021] Furthermore, the 3D modeling module is divided into sections based on the floor area occupied by the earthwork and building materials. Given a set of equal rectangular grids and the average height of each grid, calculate the volume of earthwork for building materials: In the formula, This represents the calculated volume of earthwork for building materials. Indicates the first The area of ​​a rectangular grid. Indicates the first The average height of the rectangular grid.

[0022] A method for monitoring engineering cost risks includes the following steps:

[0023] S1. The information insufficiency judgment unit monitors and judges in real time whether the cost data is missing;

[0024] S2. The information delay judgment unit estimates the reporting delay time and then judges whether the actual delayed reporting time exceeds 10% of the estimated reporting time.

[0025] S3. Generate a model of earthwork for building materials using drone surveying and compare it with the amount reported by the construction party to see if it exceeds 5%;

[0026] S4. If there are missing cost data, the estimated reporting time is exceeded by 10%, or the earthwork volume of building materials exceeds the reported amount by 5% during the factory cost estimation process, a third-party audit procedure will be initiated.

[0027] The present invention provides an engineering cost risk monitoring system and method, which, compared with the prior art, achieves the following advantages:

[0028] 1. This invention, through its information insufficiency judgment unit, information delay judgment unit, and information falsification judgment unit, enables the system to comprehensively cover the three core risks of missing cost data, reporting delay, and information falsification, thus overcoming the limitations of traditional technologies that rely solely on manual review or a single data source.

[0029] 2. This invention quantifies the risk of missing data by introducing a conditional coefficient g in a mathematical model. Combined with dynamic analysis of multiple parameters such as cost deviation, price difference rate, and construction progress deviation, it significantly improves the accuracy and objectivity of the judgment and avoids the errors of traditional subjective experience judgment.

[0030] 3. This invention uses the information delay judgment unit to scientifically estimate the reporting delay time by taking into account factors such as weather impact, material shortage, and critical path coefficient through formula D. This provides a quantitative basis for project management and is superior to traditional methods that rely on experience for estimation.

[0031] 4. This invention utilizes UAV surveying and 3D modeling technology to quickly generate earthwork and building material models and compare them with reported data, significantly improving the efficiency and accuracy of false information identification. An audit is triggered when the deviation exceeds 5%. Traditional manual measurement methods cannot achieve the same efficiency and accuracy.

[0032] 5. This invention provides a large number of mathematical models and empirical data to support decision-making, enhances the scientific nature and traceability of risk monitoring, and makes up for the lack of quantitative evidence in traditional technologies. Attached Figure Description

[0033] Figure 1 This is a flowchart of the present invention;

[0034] Figure 2 This is a mathematical model diagram of the ratio of missing information G to cost deviation a in this invention;

[0035] Figure 3 This is a mathematical model diagram of the proportion of missing information G and the number of days of deviation t in this invention;

[0036] Figure 4 This is a mathematical model diagram of the proportion of missing information G and the price difference rate m in this invention;

[0037] Figure 5 This is a mathematical model diagram of the proportion of missing information G, the price difference rate m, and the number of deviation days t in this invention. Detailed Implementation

[0038] To make the technical solution of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0039] like Figure 1 As shown, a method for monitoring engineering cost risks includes the following steps:

[0040] Step 1: Insufficient Information Judgment Unit monitors and determines in real time whether cost data is missing.

[0041] Step 2: The information delay judgment unit estimates the reporting delay time and then judges whether the actual delayed reporting time exceeds 10% of the estimated reporting time.

[0042] Step 3: Generate a model of earthwork for building materials using drone surveying and compare it with the amount reported by the construction party to see if it exceeds 5%.

[0043] Step 4: If there are missing cost data, the estimated reporting time is exceeded by 10%, or the earthwork volume of building materials exceeds the reported amount by 5% during the factory cost estimation process, a third-party audit procedure will be initiated.

[0044] Example 1

[0045] like Figure 1 As shown, according to one aspect of the present invention, an engineering cost risk monitoring system is provided, including an information insufficiency judgment unit, an information delay judgment unit, and an information falsification judgment unit. The information insufficiency judgment unit determines whether cost data is missing based on fluctuations in material prices and deviations in construction progress; the information delay judgment unit estimates the delay time for reporting based on sudden severe weather and the degree of material shortage; the information falsification judgment unit determines whether there is falsified information by comparing the three-dimensional engineering earthwork and building material model generated by UAV mapping with the quantities reported by the construction party. Through the information insufficiency judgment unit, information delay judgment unit, and information falsification judgment unit, the system can comprehensively cover the three core risks of missing cost data, reporting delays, and information falsification, overcoming the limitations of traditional technologies that rely solely on manual review or a single data source.

[0046] Example 2

[0047] like Figure 1 As shown, the information insufficiency judgment unit and the information delay judgment unit jointly include an information collection module, an information processing module, and an early warning judgment module. The information collection module collects real-time material price data, construction progress information, and information on sudden severe weather and material shortages. The information processing module parameterizes the real-time changes in material prices and deviations in construction progress, as well as the sudden severe weather and material shortages. The early warning judgment module determines whether cost data is missing based on real-time deviations in material prices and construction progress, and estimates the reporting delay time based on the severity of weather and the degree of material shortage. The information delay judgment unit estimates the reporting delay time as follows: In the formula, This indicates the estimated number of days the reporting time will be delayed. Indicates the number of days affected by weather. This represents the efficiency coefficient. This indicates the difference between the actual delivery time of the materials and the original plan. This indicates the number of days of construction that the current inventory can support. This represents the critical path coefficient.

[0048] The information delay judgment unit collects future or past weather data. Weather with temperatures exceeding 30℃ is defined as high-temperature weather, and the number of days with temperatures exceeding 30℃ in the future is 12. Therefore, the number of days affected by the weather is calculated. (day), the efficiency coefficient for high-temperature weather is taken as (Efficiency coefficient for light rain = 0.5, efficiency coefficient for heavy rain = 0.9, efficiency coefficient for sandstorm = 0.3, efficiency coefficient for high temperature = 0.7).

[0049] Furthermore, the difference between the actual delivery time of the steel reinforcement materials and the original plan is taken as... (days), the current inventory of steel reinforcement materials can support the number of construction days. (Day), Critical Path Coefficient (If the process affects the critical path, the coefficient = 1; if it affects a non-critical path, the coefficient = 0). Therefore: The above calculations show that the estimated delay in reporting time is [number] days. sky.

[0050] Example 3

[0051] like Figure 1-5 As shown, the condition coefficients for calculating cost data missing in the insufficient information judgment unit are: In the formula, The condition coefficient indicates that the cost data is missing. Indicates the cost deviation of engineering materials, This indicates the price difference rate between the budgeted price and the actual purchase price. This indicates the cumulative number of days of deviation in construction progress.

[0052] This includes calculating a conditional coefficient for any missing cost data point. The cost deviation of engineering materials is taken as... (Cost deviation = (Actual purchase price - Purchase price and average price over the past 10 days) / Purchase price and average price over the past 10 days).

[0053] The price difference rate between the budgeted price and the actual purchase price is taken as follows: (Price difference rate = (actual price - budgeted price) / budgeted price). The cumulative number of days of construction progress deviation is taken as... (Heaven). Therefore: Based on the above calculations, it can be determined that the conditional coefficient for the missing cost data in this case is [value missing]. This indicates a significant lack of data regarding key aspects of the project cost. Furthermore, it is noted that:

[0054] Table 1 shows the parameters and cost information status of some examples.

[0055]

[0056] As shown in Table 1 above, when the sample data approaches infinity, a boundary emerges where there may be significant gaps in the data used to classify joint segments using the conditional coefficient g. That is, when... When this occurs, it indicates a significant lack of data regarding key aspects of the project cost; when When this is the case, it indicates that there are no significant missing data points in the key aspects of the project cost. In such cases, it is impossible to clearly determine whether there is missing information, and a cost engineer is needed to assist in the judgment.

[0057] In this embodiment, the derivation and principle of the formula for the condition coefficient g when the cost data is missing are as follows: where, The condition coefficient representing the presence of missing cost data can be used as the standard for modeling, based on the proportion G of missing cost information determined by manual sampling audits to identify the condition coefficient for missing cost data. Therefore, we have:

[0058] 1) Take a large number of samples and establish a mathematical model based on the proportion of missing project cost information G and the cost deviation a (this mathematical model is as follows). Figure 2 (As shown). From this mathematical model one, we can construct the following formulas: Formula 1;

[0059] 2) The proportion of missing project cost information G and the number of days of deviation t were used to establish a mathematical model based on a large sample size (the mathematical model is as follows). Figure 3 (As shown). From this mathematical model two, we can construct the following formulas: Formula 2;

[0060] 3) The proportion of missing project cost information G and the price difference rate m were compared using a large sample and a mathematical model was established (the mathematical model is as follows). Figure 4 (As shown). From this mathematical model three, we can construct the following formulas: Formula 3;

[0061] 4) After controlling for any variable, establish a mathematical model between the proportion G of missing information in project cost and the other two variables.

[0062] For example, controlling cost deviation 'a', and constructing a mathematical model relating the proportion G of missing project cost information to the price difference rate 'm' and the number of deviation days 't' (e.g.) Figure 5 As shown in the figure, the percentage of missing information in the project cost G = formula 2 × formula 3;

[0063] 5) Therefore, based on the above derivation, we know that the conditional coefficient g for missing cost data is: .

[0064] Example 4

[0065] like Figure 1As shown, the information falsification judgment unit specifically includes a UAV deployment module, a UAV data acquisition module, and a 3D modeling module. The UAV deployment module is used to plan the UAV's flight altitude, forward overlap rate, and lateral overlap rate. The UAV data acquisition module is used to collect the height of each sampling point of the building material earthwork and the area occupied by the earthwork. The 3D modeling module is used to generate a mathematical model of the building material earthwork based on the UAV mapping data, and then calculate the volume of the building material earthwork.

[0066] The 3D modeling module is divided into sections based on the floor area occupied by building materials and earthwork. Given a set of equal rectangular grids and the average height of each grid, calculate the volume of earthwork for building materials: In the formula, This represents the calculated volume of earthwork for building materials. Indicates the first The area of ​​a rectangular grid. Indicates the first The average height of the rectangular grid.

[0067] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A project cost risk monitoring system, characterized in that, This includes an information insufficiency judgment unit, an information delay judgment unit, and an information falsification judgment unit; The information insufficiency judgment unit determines whether cost data is missing based on fluctuations in material prices and deviations in construction progress. The information delay judgment unit estimates the reporting delay time based on the severity of sudden severe weather and the degree of material shortage. The information falsification judgment unit determines whether there is falsified information by comparing the three-dimensional engineering earthwork and building material model generated by UAV mapping with the quantities reported by the construction party. The condition coefficients for the insufficient information judgment unit to calculate the cost data are as follows: ； In the formula, The condition coefficient indicates that the cost data is missing. Indicates the cost deviation of engineering materials, This indicates the price difference rate between the budgeted price and the actual purchase price. This indicates the cumulative number of days of deviation in construction progress; when If so, it indicates that there is a significant lack of data in key aspects of the project cost; when If the data is accurate, it indicates that there are no significant missing data points in the key aspects of the project cost.

2. The engineering cost risk monitoring system according to claim 1, characterized in that: The information insufficiency judgment unit and the information delay judgment unit are jointly provided with an information collection module, an information processing module and an early warning judgment module; The information collection module is used to collect real-time data on material prices, construction progress information, as well as information on sudden severe weather and the degree of material shortage. The information processing module is used to parameterize the real-time changes in material prices and deviations in construction progress, as well as to parameterize sudden severe weather and the degree of material shortage. The early warning and judgment module determines whether cost data is missing based on real-time deviations in material prices and construction progress, and estimates the delay time for reporting based on the severity of weather and the degree of material shortage.

3. The engineering cost risk monitoring system according to claim 1, characterized in that: The information delay judgment unit estimates the postponement of the reporting time, including: ； In the formula, This indicates the estimated number of days the reporting time will be delayed. Indicates the number of days affected by weather. This represents the efficiency coefficient. This indicates the difference between the actual delivery time of the materials and the original plan. This indicates the number of days of construction that the current inventory can support. This represents the critical path coefficient.

4. The engineering cost risk monitoring system according to claim 1, characterized in that: The information false judgment unit specifically includes a drone deployment module, a drone data acquisition module, and a 3D modeling module; The drone deployment module is used to plan the drone's flight altitude, forward overlap rate, and lateral overlap rate. The UAV data acquisition module is used to collect the height of each sampling point of the building material earthwork and the area occupied by the earthwork. The 3D modeling module is used to generate a mathematical model of the earthwork for building materials based on UAV mapping data, and then calculate the volume of the earthwork for building materials.

5. The engineering cost risk monitoring system according to claim 4, characterized in that: The 3D modeling module is divided into sections based on the floor area occupied by building materials and earthwork. Given a set of equal rectangular grids and the average height of each grid, calculate the volume of earthwork for building materials: ； In the formula, This represents the calculated volume of earthwork for building materials. Indicates the first The area of ​​a rectangular grid. Indicates the first The average height of the rectangular grid.

6. A method for monitoring engineering cost risks, characterized in that, The engineering cost risk monitoring method, applied to the engineering cost risk monitoring system according to any one of claims 1-5, includes the following steps: S1. The information insufficiency judgment unit monitors and judges in real time whether the cost data is missing; S2. The information delay judgment unit estimates the reporting delay time and then judges whether the actual delayed reporting time exceeds 10% of the estimated reporting time. S3. Generate a model of earthwork for building materials using drone surveying and compare it with the amount reported by the construction party to see if it exceeds 5%; S4. If there are missing cost data, the estimated reporting time is exceeded by 10%, or the earthwork volume of building materials exceeds the reported amount by 5% during the factory cost estimation process, a third-party audit procedure will be initiated.

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