Project budgeting method based on BIM model

Abstract

The invention discloses a project budgeting method based on a BIM model, belongs to the technical field of constructional engineering informatization, and solves the problems of low data utilization rate and inaccurate budgeting rule matching in traditional project budgeting. The method comprises the following steps: constructing a first data extraction framework based on a BIM model; the method comprises the following steps: establishing a mapping relation among BIM model components, subsystems and a budget rule base through a first data extraction framework, and obtaining an initial budget data table which records specific cost subjects corresponding to each component and each subsystem and initial estimated values thereof; constructing a second analysis framework based on the BIM model, performing hierarchical decomposition on the multi-dimensional information through the second analysis framework, and forming an incidence matrix; and calculating the cost distribution of each budget unit layer by layer by adopting a recursive algorithm. According to the method, the efficiency and the precision of engineering budget compilation are remarkably improved, and reliable technical support is provided for management of complex construction engineering.

Description

Technical Field

[0001] The present invention belongs to the technical field of construction engineering information technology, and specifically relates to a method for compiling a project budget based on a BIM model. Background Art

[0002] The preparation of a project budget is a crucial step in construction project management, typically involving the estimation and allocation of project resources, costs, and duration. Traditional methods for preparing a project budget rely primarily on two-dimensional drawings and manual calculations, using manual quantities and combining them with standard quotas to generate cost estimates. This approach requires significant time and effort for complex projects and is prone to data errors caused by human error, impacting the accuracy of the budget.

[0003] The development of Building Information Modeling (BIM) technology, with its three-dimensional visualization and data integration capabilities, has provided new insights into the preparation of project budgets. Currently, some research and practice have attempted to apply BIM models to quantity counting and budgeting. However, existing methods often focus on extracting data from a single dimension, failing to fully tap into the multidimensional information inherent in BIM models. Furthermore, in practical applications, data exchange between BIM models and budgeting software still suffers from incompatibility issues, potentially leading to incomplete or inefficient information transfer.

[0004] Existing BIM-based methods for preparing project budgets and estimates lack a systematic solution for the in-depth utilization of model data and the intelligent matching of model data with budgeting rules. Therefore, effectively integrating the multidimensional information in BIM models and establishing precise associations with budgeting rules will not only improve the efficiency and accuracy of project budgeting, but also have significant technological innovation significance and broad application prospects. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for preparing engineering budget estimates based on the BIM model to solve the problems of low data utilization and inaccurate budget rule matching in traditional engineering budget estimates, thereby making in-depth use of BIM model data and matching it with budget rules.

[0006] The technical solution of the present invention is: a method for compiling a project budget based on a BIM model, comprising the following steps: A. Build the first data extraction framework based on the BIM model; B. Establish mapping relationships between BIM model components, subsystems, and the budget rule base through the first data extraction framework to obtain an initial budget data table that records the specific cost items and preliminary estimated values ​​corresponding to each component and subsystem; C. Construct a second analysis framework based on the BIM model, and use the second analysis framework to hierarchically decompose the multidimensional information and form a correlation matrix; D. Use a recursive algorithm to calculate the cost distribution of each budget unit layer by layer.

[0007] Furthermore, in step A, the first data extraction framework is composed of multiple levels, including a geometric dimension information level, a material type information level, and a construction process information level; wherein the geometric dimension information level is used to extract the geometric parameters of the building components in the BIM model, the material type information level is used to extract the types of materials used in the components and their related properties, and the construction process information level is used to extract process information related to the construction process.

[0008] Furthermore, in step A, each level in the first data extraction framework is connected via a preset data interface, and the data interface is designed in a standardized format to achieve continuity and consistency in information transmission.

[0009] Furthermore, in step B, the budget rule base includes labor costs, material costs, machinery usage fees and their corresponding calculation formulas.

[0010] Furthermore, in step C, the rows of the association matrix represent components and subsystems, the columns of the association matrix represent expense items in the budget rule, and each element in the matrix represents a weight coefficient of a component or subsystem under a certain expense item.

[0011] Furthermore, in step C, the weight coefficient is calculated according to a pre-set formula, which comprehensively considers the geometric complexity of the component, material cost, and construction difficulty factors.

[0012] Furthermore, in step D, the recursive algorithm starts from the highest level and decomposes downwards to the lowest level in sequence, and in each level, the cost is allocated according to the weight coefficient in the association matrix and the result is passed to the next level.

[0013] Furthermore, in step D, the recursive algorithm calculates the preliminary cost allocation value of each subsystem at the highest level based on the total budget value of the overall project and the weight coefficient of each subsystem, and decomposes the cost of each subsystem into its subordinate components and subsystems at the next highest level.

[0014] The beneficial effects of the present invention are as follows: the present invention takes the BIM model as the object, combines the multi-level data extraction framework and the association matrix analysis method, and solves the problems of low data utilization and inaccurate budget rule matching in the traditional preparation of engineering budget estimates. Through the first data extraction framework, the comprehensive extraction of geometry, material and process information in the BIM model is achieved; through the second analysis framework, a clear mapping relationship between components and budget rules is established; and through the recursive algorithm, the layer-by-layer decomposition and precise allocation of budget costs are achieved. The above-mentioned technical means work together to significantly improve the efficiency and accuracy of engineering budget preparation, providing reliable technical support for the management of complex construction projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the process of the present invention; Figure 2 Schematic diagram of the hierarchical structure of the first data extraction framework in the present invention; Figure 3 Schematic diagram of the design of the correlation matrix in the second analysis framework. DETAILED DESCRIPTION

[0016] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0017] A method for preparing engineering budget based on BIM model, such as Figure 1 As shown, the following steps are included: A. Construct a first data extraction framework based on the BIM model. The first data extraction framework is used to extract information such as building components, material properties, and construction processes from the BIM model. Figure 2 As shown ( Figure 2 The first data extraction framework consists of multiple layers, including a geometry information layer, a material type information layer, and a construction process information layer. These layers are connected via pre-defined data interfaces to ensure the integrity and accuracy of information transmission. Each layer corresponds to a specific information dimension in the BIM model. The geometry information layer, located at the first layer, primarily extracts geometric parameters of building components in the BIM model, such as length, width, and height. The material type information layer, located at the second layer, extracts the material type and related properties of the component, such as concrete strength grade and steel type. The construction process information layer, located at the third layer, extracts process information related to the construction process, such as the specific requirements for formwork installation, rebar binding, and concrete pouring. The data interfaces between these layers are designed using standardized formats, automatically identifying and transferring information extracted from the previous layer to the next layer, thus ensuring continuity and consistency throughout the data extraction process.

[0018] B. Establish a mapping relationship between BIM model components, subsystems and the budget rule library through the first data extraction framework to obtain the initial budget data table. In this process, the extracted geometric dimension information, material type information and construction process information are first matched one by one with the entries in the budget rule library. The budget rule library contains various expense items and their corresponding calculation formulas, such as labor costs, material costs, machinery usage fees, etc. Based on the extracted information, a budget rule index table is automatically generated to achieve accurate matching. The index table records the specific expense items and their preliminary estimated values ​​corresponding to each component and subsystem. For example, for a concrete column component, the system will calculate the volume based on its geometric dimension information, and then determine the amount of concrete based on the material type information, and allocate the corresponding labor costs and machinery usage fees based on the construction process information. The final generated initial budget data table contains the cost estimates of all components and subsystems, laying the foundation for subsequent multi-dimensional information processing.

[0019] C. Construct a second analysis framework based on the BIM model, and use the second analysis framework to decompose the multi-dimensional information hierarchically and form a correlation matrix to achieve in-depth processing of the multi-dimensional information. Figure 3 As shown ( Figure 3 , the rows and columns of the matrix represent the mapping relationship between components and subsystems and cost items, and the logic of weight coefficient allocation is marked). The core of the second analysis framework is the design and application of the association matrix. The association matrix consists of rows and columns, where the rows represent the components and subsystems in the BIM model, and the columns represent the cost items in the budget rules. Each element in the matrix represents the weight coefficient of a component or subsystem under a certain cost item. The weight coefficient is calculated based on a pre-set formula, which comprehensively considers factors such as the geometric complexity of the component, material cost, and construction difficulty. In this way, the association matrix achieves a precise mapping from the BIM model to the budget rules, ensuring that the cost allocation of each component and subsystem under different cost items is more reasonable.

[0020] D. To further refine the budgeting process, a recursive algorithm is used to calculate the cost distribution of each budget unit layer by layer. The basic principle of the recursive algorithm is to start from the highest level and decompose it down to the lowest level. At each level, costs are allocated according to the weight coefficients in the correlation matrix, and the results are passed to the next level. This process not only accurately reflects the contribution of each component and subsystem to the overall budget, but also quickly identifies potential budget deviations.

[0021] The method of the present invention can be widely applied to the management of complex construction projects. In order to better enable relevant personnel in this technical field to fully understand and implement the present invention, the specific implementation principle of the present invention is supplemented below with reference to a specific application scenario.

[0022] Example 1 During the budget preparation process for a large commercial complex project, the project team first used BIM software to construct a complete building model. Based on this model, they used the method presented in this paper to prepare the project budget. Using a first data extraction framework, the system automatically extracted the geometric dimensions, material type, and construction process information for all components in the model, generating an initial budget data table. The core of this process lies in the design and operational mechanism of the first data extraction framework. The first data extraction framework consists of multiple layers: a geometric dimensions layer, a material type information layer, and a construction process information layer. These layers are connected via standardized data interfaces to ensure the continuity and consistency of information transfer. For example, after extracting parameters such as the length, width, and height of a building component at the geometric dimensions layer, this information is automatically transferred to the material type information layer to further determine the required material type and its properties. Similarly, information extracted at the material type information layer is transferred to the construction process information layer to determine specific construction process requirements. Through this hierarchical data extraction approach, the system can comprehensively capture multidimensional information about each component, laying the foundation for subsequent budget preparation.

[0023] After completing the first data extraction framework, the system enters the second analysis framework. Using the association matrix within this framework, the multidimensional information is deeply processed, establishing a clear mapping between components and budget rules. The core of this second analysis framework is the design and application of the association matrix. The rows of the association matrix represent the components and subsystems in the BIM model, while the columns represent the cost items in the budget rules. Each element in the matrix represents the weight coefficient for a component or subsystem under a specific cost item. The weight coefficient is calculated based on a pre-defined formula that takes into account factors such as the component's geometric complexity, material cost, and construction difficulty. For example, a complex steel structure joint, due to its high geometric complexity, receives a higher weight coefficient under the labor cost item; whereas a simple concrete slab, due to its lower construction difficulty, receives a lower weight coefficient under the machinery usage fee item. In this way, the association matrix achieves a precise mapping from the BIM model to the budget rules, ensuring a more reasonable allocation of costs for each component or subsystem across different cost items.

[0024] Finally, a recursive algorithm calculates the cost distribution of each budget unit layer by layer, generating a detailed budget report with detailed cost breakdowns for each component or subsystem. The recursive algorithm's principle is to start at the highest level and work its way down to the lowest. At each level, costs are allocated based on the weight coefficients in the correlation matrix, and the results are passed down to the next level. For example, at the highest level, the system calculates a preliminary cost allocation for each subsystem based on the total project budget and the weight coefficients of each subsystem. At the next highest level, the system further decomposes each subsystem's costs into its subordinate components or subsystems and readjusts the cost allocation based on the weight coefficients in the correlation matrix. This process continues until the cost distribution of all components and subsystems at the lowest level is accurately calculated. This process not only accurately reflects the contribution of each component or subsystem to the overall budget but also quickly identifies potential budget deviations. For example, if the actual cost of a component significantly exceeds the budget, the system automatically flags the component and prompts the user to review it, effectively mitigating the risk of budget overruns.

[0025] In practice, the project team optimized the design based on the detailed budget reports generated by the system. For example, by adjusting the material type or construction process of certain high-cost components, they successfully reduced the overall project cost. Furthermore, the system monitors budget execution in real time, promptly identifying and correcting budget deviations, providing reliable technical support for the smooth implementation of the project.

[0026] Throughout the implementation process, the collaborative relationship between the primary data extraction framework and the secondary analysis framework was crucial. The primary framework extracted comprehensive foundational information from the BIM model, while the secondary analysis framework processed this information in depth, achieving a precise mapping from the model to budgeting rules. Data transfer between the two frameworks was achieved through standardized interfaces, ensuring information integrity and consistency. Furthermore, the application of recursive algorithms further enhanced the accuracy and efficiency of budget compilation, making the budget compilation process for complex construction projects more scientific and standardized.

[0027] The method proposed in this paper can efficiently extract geometric, material, and process information from BIM models, accurately establish a mapping relationship between components and budget rules, and accurately allocate budget costs through layer-by-layer decomposition. This method can not only significantly improve the efficiency and accuracy of project budget compilation, but also provide reliable technical support for the management of complex construction projects. The advantages of this method are particularly prominent when dealing with large-scale commercial complex projects. It can effectively solve the problems of low data utilization and inaccurate budget rule matching existing in traditional budget compilation methods.

Claims

1. A method for preparing a project budget based on a BIM model, characterized by The following steps are involved: A. Build the first data extraction framework based on the BIM model; B. Establish mapping relationships between BIM model components, subsystems, and the budget rule base through the first data extraction framework to obtain an initial budget data table that records the specific cost items and preliminary estimated values ​​corresponding to each component and subsystem; C. Construct a second analysis framework based on the BIM model, and use the second analysis framework to hierarchically decompose the multidimensional information and form a correlation matrix; D. Use a recursive algorithm to calculate the cost distribution of each budget unit layer by layer.

2. The method for compiling a project budget estimate based on a BIM model according to claim 1, wherein: In step A, the first data extraction framework consists of multiple levels, including a geometric dimension information level, a material type information level, and a construction process information level; wherein the geometric dimension information level is used to extract the geometric parameters of building components in the BIM model, the material type information level is used to extract the types of materials used in the components and their related properties, and the construction process information level is used to extract process information related to the construction process.

3. The method for compiling a project budget estimate based on a BIM model according to claim 2, wherein: In step A, each level in the first data extraction framework is connected via a preset data interface, which is designed in a standardized format to achieve continuity and consistency in information transmission.

4. The method for compiling a project budget estimate based on a BIM model according to claim 1, wherein: In step B, the budget rule base includes labor costs, material costs, machinery usage fees and their corresponding calculation formulas.

5. The method for compiling a project budget estimate based on a BIM model according to claim 1, wherein: In step C, the rows of the association matrix represent components and subsystems, the columns of the association matrix represent cost items in the budget rule, and each element in the matrix represents the weight coefficient of a component or subsystem under a certain cost item.

6. The method for compiling a project budget estimate based on a BIM model according to claim 5, characterized in that: In step C, the weight coefficient is calculated according to a pre-set formula.

7. The method for compiling a project budget estimate based on a BIM model according to claim 6, characterized in that: In step D, the recursive algorithm starts from the highest level and decomposes it downwards to the lowest level. In each level, the cost is allocated according to the weight coefficients in the correlation matrix and the result is passed to the next level.

8. The method for compiling a project budget estimate based on a BIM model according to claim 7, wherein: In step D, the recursive algorithm calculates the preliminary cost allocation value of each subsystem based on the total budget value of the overall project and the weight coefficient of each subsystem at the highest level, and decomposes the cost of each subsystem into its subordinate components and subsystems at the next highest level.

Images