Method for bim-integrated project cost risk assessment and storage medium

Abstract

The application relates to a BIM-fused project cost risk assessment method and a storage medium. First, the component space table, the process plan table and the process dependency table are extracted from the BIM data of the target building project. Then, according to the component space table, the process plan table and the process dependency table, the mapping relationship among the components, the processes and the space units is established, and the dependency graph structure containing the transmission paths among different processes in the space unit is generated based on the mapping relationship. When it is detected that there is a process that produces waiting in the space unit, based on the dependency graph structure, the subsequent processes in the transmission path where the process is located are subjected to superposition operation of waiting time, resource idle cost and schedule delay cost, and the total waiting cost of the space unit is obtained. Finally, based on the total waiting cost, the risk assessment index data corresponding to the space unit is determined. The application can dynamically reflect the influence of local conflicts on the overall schedule, and improve the accuracy of the project cost risk assessment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of engineering cost evaluation, in particular to a method for engineering cost risk evaluation combined with BIM and a storage medium. BACKGROUND

[0002] With the continuous improvement of the informatization level of the construction industry, Building Information Modeling (BIM) as a digital tool integrating information at various stages of a construction project has been widely used in design, construction and operation, etc. BIM technology organically integrates multi-dimensional data such as component geometric information, construction progress and resource allocation in the form of a three-dimensional model, providing strong support for the whole life cycle management of a construction project.

[0003] In the field of engineering cost management, traditional cost control methods mainly rely on empirical rules and static data analysis, which are difficult to fully identify dynamic risk factors in the construction process. Especially in complex construction scenarios, when multiple processes need to be operated in the same space unit, the traditional risk assessment method has obvious limitations: on the one hand, it cannot effectively capture the spatio-temporal coupling relationship between processes, and on the other hand, it lacks quantitative analysis of the waiting transmission effect caused by space conflicts. This defect makes it difficult to accurately estimate the hidden costs caused by competition for space resources in the construction process, such as time loss caused by process waiting and waste caused by resource idling. SUMMARY

[0004] The purpose of the present application is to provide a method for engineering cost risk evaluation combined with BIM and a storage medium, to solve the problem of low precision of traditional engineering cost evaluation.

[0005] In order to achieve the above-mentioned purpose, the first aspect of the present application provides a method for engineering cost risk evaluation combined with BIM, comprising:

[0006] obtaining BIM data of a target construction project, extracting a component space table, a process plan table and a process dependency table from the BIM data, the component space table comprising the mapping relationship between the components of the target construction project and the space units where the components are located;

[0007] establishing the mapping relationship between components, processes and space units according to the component space table, the process plan table and the process dependency table, and generating a dependency graph structure based on the mapping relationship, the dependency graph structure containing the transmission paths between different processes in the space unit;

[0008] In response to detecting that the process that generates the waiting exists in the space unit, based on the dependency graph structure, a superposition operation is performed on subsequent processes in a conduction path of the process to obtain a total waiting cost of the space unit, wherein the superposition operation includes a superposition operation of waiting time, a superposition operation of resource idle cost and a superposition operation of schedule delay cost.

[0009] According to the total waiting cost of the space unit, risk assessment index data corresponding to the space unit is determined.

[0010] The second aspect of the present application provides a computer readable storage medium, the computer readable storage medium stores a program, the program can be loaded and executed by a processor to perform the above-mentioned BIM engineering cost risk assessment method.

[0011] The beneficial effects of the present application are:

[0012] The present application first extracts the component space table, the process plan table and the process dependency table from the BIM data of the target building project. Then, according to the component space table, the process plan table and the process dependency table, a mapping relationship between the components, the processes and the space units is established, and a dependency graph structure including the conduction paths between different processes in the space unit is generated based on the mapping relationship. By constructing the dependency graph structure, the process and space correlation is improved. When it is detected that there is a process that generates waiting in the space unit, based on the dependency graph structure, a superposition operation of waiting time, resource idle cost and schedule delay cost is performed on the subsequent processes in the conduction path of the process to obtain the total waiting cost of the space unit. Finally, based on the total waiting cost, risk assessment index data corresponding to the space unit is determined. The present application performs a superposition operation on the conduction path of the process that waits from the aspects of waiting time, resource limitation and schedule delay, which can quantify the resource waste caused by process waiting, more comprehensively assess the implicit cost, dynamically reflect the influence of local conflicts on the overall schedule, and improve the accuracy of engineering cost risk assessment.

[0013] Other features and advantages of the present application will be described in detail in the subsequent specific embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 A flowchart of a BIM integrated engineering cost risk assessment method provided in an embodiment of the present application;

[0015] Figure 2 A flowchart of a focus component marking method provided in an embodiment of the present application;

[0016] Figure 3 A flowchart of a risk assessment result output method provided in an embodiment of the present application;

[0017] Figure 4 A flowchart of a method for BIM-fused project cost risk assessment is provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, any other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0019] In the description of the present application, it should be understood that the terms "first", "second" are used only for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the technical features indicated. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "multiple" is two or more, unless otherwise specifically limited. In the present application, the word "exemplary" is used to mean "serving as an example, instance, or illustration". Any embodiment described as "exemplary" in the present application is not necessarily construed as preferred or advantageous over other embodiments. In order to enable any person skilled in the art to implement and use the present application, the following description is given. In the following description, details are listed for the purpose of explanation. It should be understood that those skilled in the art can realize the present application without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid unnecessary details making the description of the present application obscure. Therefore, the present application is not intended to be limited to the embodiments shown, but is consistent with the broadest scope consistent with the principles and features disclosed.

[0020] In the traditional project cost control method, for a complex construction project, multi-process cross construction is easy to cause space resource contention. For example, in the construction process of a certain high-rise complex, the curtain wall installation and mechanical and electrical pipeline laying process often produce multiple operation conflicts in the vertical shaft space. The traditional risk prediction method can only identify the explicit time conflict, and it is difficult to capture the diffusion effect of process waiting time on the space transmission chain, resulting in that the actual construction resource idle cost and construction period delay risk are seriously underestimated. Based on this, the embodiments of the present application can more accurately evaluate the implicit cost risk of project cost by constructing the association network of space and process and establishing the transmission calculation model of waiting time.

[0021] Figure 1 A flowchart of a method for BIM-fused project cost risk assessment is provided in an embodiment of the present application. As shown inFigure 1 As shown, the method may include steps 101-104, which will be described in detail below.

[0022] Step 101: Obtain the BIM data of the target building project, and extract the component space table, process plan table and process dependency table from the BIM data.

[0023] BIM data, or BIM model data, can include component space tables, work sequence tables, and work sequence dependency tables. A component space table is a structured data table that records the correspondence between building components and their corresponding spatial units. It can include the mapping relationship between components of the target building project and the spatial units they occupy. Specifically, the component space table can include the mapping relationship between the component's identity document (ID) and the spatial unit number of the spatial unit. The mapping relationship between the component ID and the spatial unit number means that each building component corresponds to its spatial area. This can be achieved using a database table or hash table to store the component ID and its corresponding spatial unit number, thereby establishing the association between the component and its physical location. Therefore, the component space table can use a database table format to store the mapping relationship between component IDs and spatial unit numbers, serving as the basis for establishing the association between construction procedures and physical space.

[0024] The work schedule can include the work process ID, start and end times, required resource types, and component identifiers corresponding to the work process IDs, thus clarifying the execution logic of the work process within the spatial unit. The start and end times of the work schedule refer to the start and end times of the work process within the construction cycle. Resource types can include manpower, machinery, or material types, and the corresponding component IDs are used to identify the specific building components operated by the work process.

[0025] The process dependency table can include spatiotemporal dependency types between processes, defining the temporal order and spatial sharing relationships between processes. Dependency types include at least one of temporal order constraints and spatial sharing conflicts. Temporal order constraints refer to the logical temporal relationship that processes must satisfy to execute sequentially, while spatial sharing conflicts refer to resource usage conflicts arising from time overlap among multiple processes within the same spatial unit. These can be stored using a dependency matrix or graph structure.

[0026] These three types of structured data are interconnected, forming the foundational dataset that supports the construction of the dependency graph. For example, in a pipeline installation scenario, the "pipeline welding" process in the process schedule table is associated with a pipeline with component ID P-102, with a time interval of days 5-7 and a resource type of welding team. The process dependency table defines that this process has a time sequence constraint with the "pipeline testing" process and a spatial sharing conflict with the "electrical wiring" process within the same spatial unit.

[0027] The traditional method usually only relies on the geometric information of BIM, and does not establish an explicit mapping relationship between the components and the space units, resulting in insufficient process and space correlation. At the same time, the traditional process plan table lacks binding of resource types and components, and the dependency table does not distinguish between space-time dependency types, making it difficult to systematically identify space conflicts and transmission paths. The present application realizes the accurate association of processes, components, spaces and resources through three types of structured data tables, providing multi-dimensional data support for dependency graph generation. In this way, it can effectively solve the problem of low conflict recognition efficiency caused by the lack of process and space unit mapping relationship. Through the binding of component ID and space unit, the area where the process is located can be quickly located. Through the association of resource type and component, the idle cost of resource can be accurately calculated. Through the classification of space-time dependency type, the time constraint and space conflict can be distinguished, providing clear basis for dependency path transmission analysis.

[0028] Step 102, according to the component space table, the process plan table and the process dependency table, the mapping relationship between the components, the processes and the space units is established, and the dependency graph structure is generated based on the mapping relationship. The dependency graph structure includes the transmission paths between different processes in the space unit.

[0029] In the embodiment of the present application, the dependency graph structure refers to a network model describing the space-time dependency relationship between processes. By establishing the mapping relationship between components, processes and space units, the dependency graph result including the transmission paths between different processes in the space unit can be obtained. Specifically, the topological relationship of nodes and edges can be stored in a graph database, each node represents a process in a specific space unit, and the edge represents the transmission path, supporting the visualization analysis and calculation of conflict transmission effect. The transmission path refers to the chain of influence relationship between processes due to space or time dependency, which can be realized by traversing the connection relationship in the dependency graph structure, and is used to describe the transmission process of waiting time in the process network. In this way, the problem of missing implicit conflict detection caused by ignoring the space dimension in traditional engineering cost evaluation can be effectively solved, and the space-time coupling relationship between processes is systematically modeled through the structured dependency graph, providing an accurate data model basis for subsequent risk transmission path analysis.

[0030] Step 103, in response to detecting that there is a process that produces waiting in the space unit, based on the dependency graph structure, performing superposition operation on the subsequent processes in the transmission path where the process is located, to obtain the total waiting cost of the space unit. The superposition operation includes superposition operation of waiting time, superposition operation of resource idle cost and superposition operation of schedule delay cost.

[0031] Traditional construction cost evaluation methods can usually only detect explicit time conflicts and ignore the propagation effect. For example, in the construction of a certain subway station, existing tools identify the time overlap between civil engineering and decoration processes, but do not calculate the superimposed effect of this conflict on subsequent mechanical and electrical installation. However, the embodiments of the present application can not only find the current conflict, but also automatically track the propagation path of the waiting time on the process chain, and accurately calculate the cumulative effect of the resource idle cost. Moreover, traditional evaluation methods usually only calculate the static waiting time or resource idle cost, and do not include the schedule pressure in the risk quantification model, which can easily underestimate the delay risk in the key construction phase. However, the embodiments of the present application introduce the dimension of schedule delay cost, realize the dynamic response to schedule sensitivity, and couple the calculation of resource idle and schedule delay costs, which can make the risk assessment more in line with the actual engineering scene.

[0032] In the embodiments of the present application, the total waiting time refers to the sum of the waiting time of each process in the same space unit due to space conflicts, which can be calculated by summing the waiting time of each process using a time accumulation algorithm. This parameter is used to quantify the overall delay caused by space conflicts. The resource idle cost refers to the cost generated by the underutilization of construction resources due to process waiting, which can be calculated by accumulating the unit time idle cost of different resource types, such as the rental fee of mechanical equipment or the labor standby cost. The schedule delay cost coefficient is a preset multiplier factor for converting the total waiting cost into economic cost, which can be determined by historical engineering data statistics or industry standards. This coefficient reflects the impact of schedule delay on overall cost.

[0033] Step 104, determining the risk assessment index data corresponding to the space unit according to the total waiting cost of the space unit.

[0034] The risk assessment index data refers to the evaluation result of the risk assessment of the space unit. For example, the risk assessment index data can be the risk level, which can be divided into low risk, medium risk and high risk three level intervals according to the total waiting cost of the space unit. Each level interval sets a certain threshold range. In this way, the complex cost data is converted into an operable classification result, which can help managers quickly identify high-risk space units and associated components, so as to adjust the construction plan and resource allocation accordingly, and effectively reduce the cost overrun risk caused by the accumulation of waiting time.

[0035] By the technical solution, the implicit cost evaluation problem caused by space conflicts in multi-process construction can be effectively solved. Through the conduction path modeling and the waiting time superposition calculation, the influence degree of local conflicts on the overall engineering cost can be accurately quantified. Relying on the subgraph optimization mechanism, the resource efficiency of the critical path can be improved on the premise of ensuring the stability of the construction plan. The embodiment of the application performs superposition operation on the conduction path of the process waiting from the aspects of implicit costs such as waiting time, resource limitation and schedule delay, can quantify the resource waste caused by process waiting, more comprehensively evaluate the implicit cost, dynamically reflect the influence of local conflicts on the overall schedule, and improve the accuracy of engineering cost risk evaluation.

[0036] In step 102, first, based on the component space table and the process plan table, the process ID corresponding to the component identification of the component and the space unit number of the space unit where the component is located are determined. Then, the process ID corresponding to the component is mapped with the space unit number to obtain the mapping relationship between the space unit and the process.

[0037] In the embodiment of the application, the process-space mapping relationship refers to the corresponding relationship established by associating the process ID and the space unit number. Specifically, database table association or algorithm matching based on spatial topology can be used to achieve it, and its function is to bind the scattered process data and the physical space position, and provide a structured data basis for subsequent conflict detection.

[0038] Finally, according to the mapping relationship between the space unit and the process, and the space-time dependency type between the processes in the process dependency table, a dependency graph structure is generated. Specifically, first, based on the mapping relationship between the space unit and the process, according to the start and end time in the process plan table, the time interval occupied by the process in the space unit is marked. Then, based on the space-time dependency type in the process dependency table, the dependency graph structure containing time overlap conflict and sequence constraint is generated.

[0039] Time interval marking refers to mapping the start and end time of the process to the time axis of the corresponding space unit. Specifically, time axis visualization tools or timestamp-based sorting algorithms can be used to achieve it, and its function is to convert abstract time constraints into quantifiable time period data. The dependency graph structure refers to a graph model constructed by the space-time dependency type, which can be implemented by using a graph database or an adjacency matrix data structure, and its function is to describe the conflict and constraint conduction path between processes through the topological relationship of nodes and edges.

[0040] Specifically, in generating the dependency graph structure, first, the process ID is associated with the space unit number, for example, by SQL statement joint query of the component-space table and the process plan table, the space position index of each process is established. Then in the space unit dimension, according to the start and end time of the process, the time interval label is generated, for example, the concrete pouring process is labeled as occupying the A area space unit from the 5th to the 8th day. Finally, based on the time sequence constraint and the space sharing conflict type defined in the process dependency table, the dependency graph structure is constructed, for example, when there is time overlap between two processes in the same space unit, a directed edge representing the conflict is generated, and when there is a process execution sequence constraint, an undirected edge representing the dependency relationship is generated.

[0041] The traditional method only analyzes the time sequence conflict through the Gantt chart, does not model the space unit as an independent dimension, and cannot identify the space sharing conflict of multiple processes in the same area. The embodiment of the application can detect time sequence violations and space resource preemption conflicts by fusing space unit mapping and time interval labeling to convert the space-time dependency relationship between processes into a calculable graph structure.

[0042] In the embodiment of the application, the dependency graph structure includes nodes and edges, the nodes represent processes, and the edges represent the transmission path between processes.

[0043] In step 103, the dependency graph structure can be traversed first to identify the space conflict points of different processes in the same space unit. The space conflict point is the node where the processes intersect in the same space unit with time overlap, that is, the resource competition point. It can be automatically detected by a time interval comparison algorithm, for example, it can be realized by traversing the process time axis and detecting overlapping intervals, triggering the waiting time calculation mechanism.

[0044] In one example, the processes in the same space unit are first sorted according to the target time in the start and end time of the process. The target time can be the start time, the end time, or any one of the time points located in the start time and the end time. For example, all processes in each space unit are sorted by start time.

[0045] If it is detected that the execution period of adjacent processes overlaps, the nodes with overlap are taken as space conflict nodes. The execution period overlaps, that is, the time interval overlaps, means that the execution period of two or more processes in the same space unit partially or completely overlaps, which can be determined by comparing the start time and the end time of the process.

[0046] Specifically, after sorting all processes in a space unit according to the starting time, it is checked in turn whether there is overlap in the time interval of adjacent processes. For example, if the end time of the previous process is later than the starting time of the subsequent process, it is determined that there is overlap in the time interval. When such overlap is detected, the system automatically generates a corresponding space conflict node and associates the node to the related process and space unit. In this way, the resource conflicts caused by space sharing can be systematically identified, providing a basis for subsequent transmission path analysis and optimization.

[0047] The traditional evaluation method can usually only identify the explicit conflicts of a single process, while the embodiments of the present application can capture the complex conflict relationship of multiple processes in the shared space through sorting and overlap detection. Moreover, the traditional evaluation method often relies on manual experience to determine the conflict range, while the embodiments of the present application can achieve accurate positioning of the conflict node through automatic comparison of the time interval.

[0048] Through the above technical solutions, the embodiments of the present application can quickly identify the space conflicts caused by process time overlap in the construction process, avoid process delay transmission caused by resource competition, reduce the errors and omissions of manual investigation through a systematic conflict detection mechanism, provide a reliable basis for subsequent adjustment of process timing, thereby reducing the risk of resource idling and optimizing construction efficiency.

[0049] Then, in response to detecting that a process generates a wait at a space conflict point, the process generating the wait is marked as a wait source point, the wait time of the process is recorded, and the wait time is added to the subsequent processes in the transmission path where the process is located.

[0050] The wait time addition refers to transferring the wait time generated by the current process due to space conflict to all subsequent processes that have a dependency relationship with the current process. Specifically, the time delay value can be added to the starting time of each subsequent process step by step by traversing the transmission path in the dependency graph structure, for example, by automatically updating the time parameters in the process schedule table through an algorithm. The dependent processes on the transmission path refer to all subsequent processes that have a time sequence constraint or resource dependency relationship with the current process. The transmission range can be determined by analyzing the directed edge connection relationship in the dependency graph structure, for example, by using a depth-first search algorithm to traverse all possible affected process nodes. For example, if a process needs to wait for time T due to a space conflict node, the starting time of all dependent processes (i.e., subsequent processes after the current wait source point in the transmission path) on the subsequent transmission path is delayed by T.

[0051] Specifically, when a procedure in a space unit is waiting due to time interval overlap, the procedure is marked as a waiting source point, and its waiting time T is automatically superimposed on all subsequent dependent procedures. For example, if a wall construction procedure needs to wait for 2 days due to space conflict, the start time of the subsequent circuit installation, pipeline laying and other dependent procedures needs to be delayed for 2 days. This process updates the start time of each procedure layer by layer by traversing the topological order of the conduction path in the dependency graph structure, and synchronously adjusts the global resource allocation plan, thereby ensuring that all conduction-affected procedure time parameters are dynamically correlated.

[0052] The traditional method usually only makes local adjustments for a single conflict node and does not consider the conduction effect of waiting time along the procedure dependency chain, which easily leads to new conflicts in subsequent procedures. However, the embodiment of the present application can systematically eliminate the chain reaction caused by the initial conflict through global delay superposition of the conduction path, avoid repeated adjustment, effectively reduce the overall optimization time consumption.

[0053] Through the above technical solutions, the embodiment of the present application can automatically track the conduction effect of space conflict on subsequent procedures, avoid the tedious operation of manual adjustment one by one, ensure the global consistency of time parameter adjustment, and improve the accuracy of engineering cost risk identification and control.

[0054] Then, the frequency of the occurrence of the waiting source point in the space unit is counted, and the components associated with the space unit whose frequency exceeds the set frequency are marked as focal components. The focal component refers to a key building element that frequently causes conduction waiting, and the frequency threshold can be set to automatically screen, for example, a steel beam node in a project is marked because it frequently causes installation procedure waiting, guiding the optimization of resource scheduling priority. The frequency is the ratio of the number of waiting source points to the number of conduction paths in the space unit. Figure 2 A flowchart for marking focal components in the embodiment of the present application is shown. After counting the frequency of the waiting source point, it is determined whether the frequency exceeds the frequency threshold. If yes, it is marked as a focal component, otherwise, it is not marked as a focal component.

[0055] Next, a dependency subgraph centered on the focal component is extracted in the dependency graph structure. In one example, the conduction path starting from the focal procedure corresponding to the focal component is first screened from the dependency graph structure. The conduction path can include a direct waiting path directly connected to the focal procedure and an indirect conduction path indirectly connected to the focal procedure. Then, the direct waiting path and the indirect conduction path are merged to form a dependency subgraph centered on the focal component.

[0056] The direct waiting path refers to a conduction link formed by a focal component related process and its direct subsequent process, for example, the dependency relationship between the steel binding process and the concrete pouring process. The indirect conduction path refers to a path through which the focal component related process transmits influence through multiple intermediate processes, for example, the multi-stage conduction link formed by the influence of the steel binding process on the concrete pouring process and the further influence of the concrete pouring process on the formwork removal process. The dependency subgraph refers to a local network structure formed by merging the conduction paths, and specifically, a breadth-first search algorithm can be used to traverse all reachable nodes of the focal component related process, thereby generating a topological subgraph containing the conduction paths.

[0057] Specifically, when a certain space unit is marked as a focal component, first, all conduction paths starting from the process associated with the component are extracted from the global dependency graph structure. For example, if the focal component is a concrete wall in a certain area, the processes such as steel binding and formwork installation associated with the component are taken as starting points. The conduction paths include direct waiting paths (such as the delay of concrete pouring caused by spatial conflict of steel binding process) and indirect conduction paths (such as the further delay of subsequent maintenance process caused by the delay of concrete pouring). By merging the two types of paths, the influence range of the focal component can be completely mapped into the dependency subgraph. For example, in the dependency subgraph of the concrete pouring process, multiple process nodes such as formwork installation, steel binding, pouring operation and subsequent maintenance and their conduction relationships can be included, forming a complete local influence network.

[0058] The traditional method only makes local adjustments for direct spatial conflicts and does not consider the conduction effect between processes. For example, the traditional method may only adjust the overlapping time of steel binding and concrete pouring, but ignores the chain delay of subsequent maintenance process. The embodiment of the present application completely captures direct and indirect conduction paths through the dependency subgraph, so that the optimization range covers all affected process nodes, avoiding secondary risks caused by local adjustment.

[0059] Through the above technical solutions, the embodiment of the present application can accurately identify all conduction paths affected by the focal component, helping construction management personnel to quickly lock the key optimization area. For example, in the conflict scenario of the concrete wall process, the dependency subgraph can intuitively show the whole link influence from the steel binding to the maintenance process, providing complete data support for timing adjustment and avoiding repeated adjustment and resource waste caused by omission of indirect conduction paths.

[0060] Based on the extracted dependency subgraph, the execution timing of the focus component corresponding to the focus process can be adjusted, and the total waiting time and resource idle cost of the adjusted spatial unit are calculated. In one example, first, according to the pre-dependence relationship and post-constraint condition in the conduction path of the focus process in the dependency subgraph, the adjustable time interval of each focus process is determined. The adjustable time interval is the range of the sliding time window of the focus process under the condition of meeting the global resource type constraint. Then, within the adjustable time interval, the waiting time of the subsequent process of the focus process is shortened, and the time overlap between the focus process and the preceding process is eliminated. If the time overlap with the preceding process cannot be completely eliminated, the time overlap is compressed by sliding the time window. That is, within the adjustable time interval, the process time is adjusted in the following priority order. Priority one: shorten the waiting time of the post-start process, and preferentially eliminate the time overlap with the preceding process; priority two: if the time overlap with the preceding process cannot be completely eliminated, minimize the time overlap by sliding the time window.

[0061] The adjustable time interval can be implemented by the interval between the earliest start time and the latest end time of the process. The determination of this interval can avoid the chain resource conflict caused by process adjustment. The priority order adjustment refers to formulating process timing optimization rules based on conflict elimination effect. Specifically, it can be implemented by solving the conflict on the direct conduction path first and then processing the indirect conduction path. This step-by-step optimization strategy can effectively reduce the adjustment complexity.

[0062] Specifically, in the conduction path analysis of the dependency subgraph, first, the lower limit of the start time that each process must meet is determined according to the pre-dependence relationship of each process, and the upper limit of the latest start time that each process is allowed to meet is determined in combination with the global resource type constraint, thereby forming a slidable time window range. When adjusting the process execution timing, the scheme of eliminating the waiting time of the post-start process is preferentially selected, for example, the time window of the current process is slid forward to eliminate the time overlap with the preceding process. If there is a non-adjustable fixed process constraint, the overlapping part is compressed to the minimum by sliding the time window, for example, the time overlap is shortened from three days to half a day. This phased adjustment strategy can achieve the maximum conflict resolution within the resource constraint framework.

[0063] The traditional method usually adopts fixed process timing or one-way adjustment strategy, which is difficult to achieve dynamic balance between resource constraints and conflict resolution. The embodiment of the application defines the adjustable time interval to provide a quantitative adjustment space for process timing optimization, and sets the conflict elimination priority rules, so that the optimization process can be implemented step by step according to the conduction path influence degree, thereby improving the effectiveness and feasibility of the adjustment strategy.

[0064] By the technical solution, the process adjustment space can be accurately identified under the resource constraint condition, the waiting time on the critical path is effectively shortened by the phased optimization strategy, and the resource idling waste caused by the time sequence conflict is reduced. The dynamic adjustment mechanism provides an operable conflict resolution method for engineering progress optimization, and solves the cost risk problem caused by the process time sequence rigidity in the traditional method.

[0065] Finally, the total waiting cost of the space unit is recalculated according to the total waiting time and the resource idling cost of the adjusted space unit.

[0066] Specifically, the cumulative value of the waiting time of all processes of the adjusted space unit is taken as the total waiting time of the adjusted space unit. And the cumulative value of the unit time cost corresponding to the resource type in the space unit is taken as the resource idling cost of the adjusted space unit. Then, according to the total waiting time, the schedule delay cost of the adjusted space unit is calculated according to the preset schedule delay cost coefficient.

[0067] Then, according to the start and end time of the process in the process plan and the remaining time ratio of the global schedule, the time weight coefficient is allocated to the waiting time of the process in the space unit. Finally, the total waiting cost of the space unit is calculated according to the adjusted resource idling cost, schedule delay cost and time weight coefficient. The time weight coefficient is a weight value dynamically adjusted based on the ratio relationship between the process execution time and the remaining time of the global schedule, and can be calculated by the remaining time ratio algorithm. The coefficient is used to strengthen the contribution of the waiting time near the schedule node to the overall risk.

[0068] Specifically, the calculation of the total waiting cost is divided into three stages: first, the total waiting time is obtained by accumulating the waiting time of each process, and the schedule delay cost is generated in combination with the preset schedule delay cost coefficient. Second, according to the start and end time of the process and the remaining time ratio of the global schedule, the time weight coefficient is dynamically allocated, so that the delay event near the schedule deadline has a higher risk weight. Finally, the resource idling cost and the weighted schedule delay cost are added to form the total waiting cost which comprehensively reflects the risk level of the space unit. In this process, the dynamic allocation mechanism of the time weight coefficient can effectively capture the influence of the schedule progress pressure on the risk assessment.

[0069] The traditional optimization method usually adopts global process rearrangement, and the embodiment of the application realizes the balance of local optimization and global stability through focus component positioning and dependent subgraph extraction, and avoids the chain reaction caused by large-scale plan adjustment. Through the above technical solution, the embodiment of the application can more accurately quantify the comprehensive cost risk caused by spatial conflict, and avoid the evaluation deviation caused by ignoring the dynamic change of construction period. Through the dynamic adjustment of the time weight coefficient, the high-risk space unit with significant influence on the overall construction period can be preferentially identified, which provides more accurate decision basis for construction resource allocation, and prevents the problem of global cost rising caused by local optimization adjustment.

[0070] In the embodiment of the application, the target construction project can include at least two space units. In step 104, the total waiting costs of the at least two space units can be sorted to obtain a cost sequence. Then, the cost sequence is divided into at least two continuous intervals according to a preset threshold range, and each interval corresponds to a risk level. Finally, the space unit corresponding to each total waiting cost in the cost sequence is associated with the risk level to obtain the risk assessment index data corresponding to the space unit.

[0071] The risk level refers to a label for classifying the risk degree of the space unit according to the total waiting cost, which can be realized by using quantile division method or equidistant interval method. By setting different threshold ranges to distinguish risks of different levels, high-risk areas can be quickly located. The total waiting cost sorting refers to arranging the total waiting cost values of all space units in ascending or descending order, which can be realized by using quicksort algorithm or merge sort algorithm. After sorting, a cost distribution curve is formed to support interval division. The preset threshold range refers to the pre-defined cost interval boundary value, which can be set through historical data analysis or expert experience, for example, defining the interval with total cost lower than 20% quantile as low risk, 20%-80% quantile as medium risk, and higher than 80% quantile as high risk.

[0072] Figure 3 A flowchart for outputting risk assessment results is provided in the embodiment of the application. The dependent subgraph centered on the focus component is extracted, the execution time sequence of the focus component related process is adjusted, the adjusted total waiting time and resource idle cost are calculated, and compared with the adjustment before. If the total waiting time and resource idle cost after adjustment are reduced, the time interval of the process in the dependent graph structure is updated; otherwise, re-adjustment is made, and when the continuous N times of adjustment still do not reduce, the dependent subgraph is marked as unoptimizable state, and the repeated adjustment of the dependent subgraph is stopped. The total waiting cost of each space unit is recalculated according to the adjusted total waiting time and resource idle cost, and the assessment result is output according to the corresponding relationship between the total waiting cost and the preset level interval.

[0073] Specifically, after the total waiting cost of each space unit is calculated, the total cost values of all units are sorted in ascending order to generate a cost sequence. The cost sequence is divided into three consecutive intervals according to a preset threshold range, and each interval corresponds to a different risk level. For example, when the total cost is in the lowest 20% interval, it is marked as low risk, the middle 60% interval is medium risk, and the highest 20% interval is high risk. By associating the space unit number and the corresponding component, the final output includes a risk level classification evaluation result list, which can be used by managers to quickly identify areas that need to be prioritized for optimization.

[0074] In some embodiments, the preset threshold range can be dynamically adjusted according to the size of the project. For example, in a large project, the threshold proportion of the high-risk interval can be set to the top 10%, while in a small or medium-sized project, it is adjusted to the top 15%. In addition, the division of risk levels can also be modified in combination with resource type weights, such as appropriately increasing the risk level of space units with a high proportion of high-priced resources.

[0075] Traditional methods usually only output the absolute value of the total waiting cost, lack dynamic risk level division, and make it difficult for managers to quickly determine priorities. However, the embodiments of the present application convert cost data into intuitive risk levels through sorting and interval division, and combine the association between space units and components to achieve dual optimization of risk positioning and classification. Through the above technical solutions, the embodiments of the present application can convert complex cost data into operational classification results, helping managers quickly identify high-risk space units and associated components, and thus adjust construction plans and resource allocation accordingly, effectively reducing the risk of cost overruns due to accumulated waiting time.

[0076] Figure 4A flowchart of a method for BIM-based project cost risk assessment is provided in an embodiment of the present application. In an embodiment, first, BIM data of a target construction project is obtained, and a component-space table, a process plan table, and a process dependency table are extracted from the BIM data. A mapping relationship between a space unit and a process is generated according to the component-space table, the time interval of a process in the process plan table is marked to the corresponding space unit, and a dependency graph structure is generated. The dependency graph structure includes a conduction path between different processes in a space unit. Then, the dependency graph structure is traversed, and a space conflict node of different processes in the same space unit is identified. When a process waits due to the space conflict node, the process is marked as a waiting source point of the conduction path, the waiting time of the process is recorded, and the waiting time is added to the processes on the subsequent conduction path. The frequency of the occurrence of the waiting source point in each space unit is counted, and the components associated with the space unit whose frequency exceeds a set threshold are marked as focus components. Then, a dependency subgraph centered on the focus components is extracted, the execution timing of the focus component-related processes is adjusted, the adjusted total waiting time and resource idle cost are calculated, and are compared with those before the adjustment. If the adjusted total waiting time and resource idle cost are both reduced, the time interval of the process in the dependency graph structure is updated. Otherwise, the adjustment is re-performed, and when the adjustment is still not reduced for N consecutive times, the dependency subgraph is marked as an unoptimizable state, and the repeated adjustment of the dependency subgraph is stopped. Finally, the total waiting cost of each space unit is recalculated according to the adjusted total waiting time and resource idle cost, and the evaluation result is output according to the corresponding relationship between the total waiting cost and the preset level interval.

[0077] Specifically, the method first obtains three-dimensional space data and construction plan data through BIM model analysis, and establishes an associated mapping of components, processes, and spaces. For example, in the dependency graph structure generation process, the operation time of the curtain wall installation process and the mechanical and electrical construction process in the shaft space is visually marked, and the conflict nodes with overlap are automatically identified. When the pipe pressure test waits due to space occupation, the system adds the waiting time to the subsequent ventilation system debugging process, and traces back to the conduction to the fire acceptance link. For the pipe well space with more than three times of conduction waiting, the system automatically marks the related pipe as a focus component, and extracts a dependency subgraph including multiple processes such as water supply and drainage, heating and ventilation, and fire protection. By adjusting the operation period of the pipe installation process, the system finds that the total waiting time is reduced, and the efficiency of the tower crane is improved, and finally the risk level of the space unit is reduced from high risk to medium risk.

[0078] Compared with the traditional technology, the embodiments of the present application have the following advantages.

[0079] 1. By establishing the dependency graph structure of the process in the spatial unit, the waiting time caused by spatial conflict and its transmission effect are identified and quantified, which can dynamically capture the chain effect of local conflict in time and space dimensions, thereby realizing accurate assessment of implicit cost.

[0080] 2. By screening the focal component through the statistical spatial conflict frequency and extracting the dependency subgraph centered on it, local process timing optimization is implemented to reduce waiting time and resource idle cost, and the optimization range of this method is more concentrated and the adjustment response is more flexible, avoiding the triggering of large-scale process plan changes and improving the practicality and operation efficiency of engineering management.

[0081] 3. The total waiting cost of the spatial unit is calculated by the total waiting time, the time weight coefficient of resource idle cost and time delay, and the cost distribution is divided into low, medium and high risk levels, realizing the unified evaluation of multi-dimensional cost factors, which helps managers to take differentiated control strategies for different risk levels and optimize resource allocation.

[0082] 4. Based on the automatic extraction of component-space table, process plan table and process dependency table from BIM model data, the system module completes the whole process operation of dependency graph generation, conflict identification and risk output, greatly reducing the need for manual intervention and improving the automation level and timeliness of engineering cost risk assessment.

[0083] The embodiments of the present application also provide a computer readable storage medium, which stores a program capable of being loaded by a processor and executing any one of the methods of BIM engineering cost risk assessment in the embodiments of the present application.

[0084] Those skilled in the art can understand that all or part of the functions of the various methods in the above embodiments can be realized by hardware or by a computer program. When all or part of the functions in the above embodiments are realized by a computer program, the program can be stored in a computer readable storage medium, which can include read-only memory, random access memory, magnetic disk, optical disk, hard disk, etc. The above functions are realized by executing the program by a computer. For example, the program is stored in the memory of the device, and when the program in the memory is executed by the processor, the above all or part of the functions are realized. In addition, when all or part of the functions in the above embodiments are realized by a computer program, the program can also be stored in a server, another computer, a storage medium such as a disk, an optical disk, a flash disk or a mobile hard disk, and is downloaded or copied into the memory of the local device or the system of the local device is updated, and when the program in the memory is executed by the processor, the above all or part of the functions are realized.

[0085] The above describes the present application by using specific examples, which is only used to help understand the present application and does not limit the present application. According to the idea of the present application, a person skilled in the art of the present application can make several simple deductions, deformations or substitutions.

Claims

1. A method for engineering cost risk assessment integrating BIM, characterized in that, include: Obtain BIM data of the target building project, and extract component space table, process plan table and process dependency table from the BIM data. The component space table includes the mapping relationship between the components of the target building project and the spatial unit where the components are located. Based on the component space table, the process plan table, and the process dependency table, a mapping relationship between components, processes, and spatial units is established, and a dependency graph structure is generated based on the mapping relationship. The dependency graph structure contains the transmission paths between different processes within the spatial unit. The dependency graph structure includes nodes and edges, where nodes represent processes and edges represent transmission paths between processes. Traverse the dependency graph structure to identify spatial conflict points of different processes within the same spatial unit. The spatial conflict point is a node where processes with overlapping time intersect within the same spatial unit. In response to the detection that the process is waiting at the spatial conflict point, the process that is waiting is marked as the waiting source point, the waiting time of the process is recorded, and the waiting time is added to the subsequent processes in the transmission path where the process is located. The frequency of the waiting source points appearing in the spatial unit is counted, and the components associated with the spatial unit whose frequency exceeds a set frequency are marked as focal components. The frequency is the ratio of the number of waiting source points to the number of conduction paths in the spatial unit. Extract the dependency subgraph centered on the focal component from the dependency graph structure, adjust the execution sequence of the focal process corresponding to the focal component, and calculate the total waiting time and resource idle cost of the adjusted spatial unit. Based on the adjusted total waiting time and resource idle cost of the space unit, recalculate the total waiting cost of the space unit; Based on the total waiting cost of the space unit, determine the risk assessment index data corresponding to the space unit.

2. The method according to claim 1, characterized in that, The component space table includes a mapping relationship between the component identifier of the component and the space unit number of the space unit. The process plan table includes the process identifier, start and end time, required resource type and component identifier corresponding to the process identifier of the process. The process dependency table includes the spatiotemporal dependency type between the processes. The dependency type includes at least one of time sequence constraints and space sharing conflicts. The step of establishing a mapping relationship between components, processes, and spatial units based on the component space table, the process plan table, and the process dependency table, and generating a dependency graph structure based on the mapping relationship, includes: Based on the component space table and the process plan table, determine the process identifier corresponding to the component identifier of the component and the space unit number of the space unit where the component is located; The process identifier corresponding to the component is mapped to the spatial unit number to obtain the mapping relationship between the spatial unit and the process; The dependency graph structure is generated based on the mapping relationship between the spatial unit and the process, and the spatiotemporal dependency type between the processes in the process dependency table.

3. The method according to claim 2, characterized in that, The step of generating the dependency graph structure based on the mapping relationship between the spatial unit and the process, and the spatiotemporal dependency types between the processes in the process dependency table, includes: Based on the mapping relationship between the spatial unit and the process, and according to the start and end times in the process schedule, the time interval occupied by the process is marked in the spatial unit; Based on the spatiotemporal dependency types in the process dependency table, a dependency graph structure containing time overlap conflicts and sequence constraints is generated.

4. The method according to claim 1, characterized in that, The step of traversing the dependency graph structure and identifying spatial conflict points between different processes within the same spatial unit includes: The processes within the same spatial unit are sorted according to the target time in the start and end times of the processes; If an overlap is detected between the execution periods of adjacent processes, the overlapping nodes will be designated as spatial conflict nodes.

5. The method according to claim 1, characterized in that, Extracting the dependency subgraph centered on the focal component from the dependency graph structure includes: The transmission path originating from the focal process corresponding to the focal component is selected from the dependency graph structure. The transmission path includes direct waiting paths directly connected to the focal process and indirect transmission paths indirectly connected to it. The direct waiting path and the indirect transmission path are merged to form the dependency subgraph centered on the focal component.

6. The method according to claim 1, characterized in that, The adjustment of the execution sequence of the focal process corresponding to the focal component includes: Based on the transmission path of the focal process in the dependency subgraph, the lower limit of the start time and the upper limit of the latest start time are determined to form the range of the sliding time window of the focal process, so as to determine the adjustable time interval of each focal process; Within the adjustable time interval, the waiting time of subsequent processes of the focal process is shortened, and the time overlap between the focal process and the preceding process is eliminated; If the time overlap with the preceding process cannot be completely eliminated, the time overlap is compressed through the sliding time window.

7. The method according to claim 1, characterized in that, The step of recalculating the total waiting cost of the space unit based on the adjusted total waiting time and resource idle cost of the space unit includes: The sum of the waiting times of all processes in the adjusted space unit is taken as the total waiting time of the adjusted space unit; The adjusted resource idle cost of the space unit is calculated by accumulating the unit time cost corresponding to the resource type within the space unit. Based on the adjusted total waiting time, the adjusted construction period delay cost of the spatial unit is calculated according to the preset construction period delay cost coefficient; Based on the ratio of the start and end times of the process in the process schedule to the remaining time of the overall project duration, a time weighting coefficient is assigned to the waiting time of the process within the spatial unit. The total waiting cost of the spatial unit is calculated based on the adjusted resource idle cost, the construction period delay cost, and the time weighting coefficient.

8. The method according to any one of claims 1 to 7, characterized in that, The target building project includes at least two spatial units, and the determination of risk assessment index data corresponding to the spatial unit based on the total waiting cost of the spatial unit includes: The total waiting costs of at least two of the spatial units are sorted to obtain a cost sequence; The cost sequence is divided into at least two consecutive intervals based on a preset threshold range, with each interval corresponding to a risk level; Associating each spatial unit corresponding to the total waiting cost in the cost sequence with the risk level yields the risk assessment index data corresponding to the spatial unit.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program that can be loaded by a processor and executed as described in any one of claims 1 to 8, for the method of engineering cost risk assessment using BIM.

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