Engineering cost index dynamic conversion method based on material equipment price database

Abstract

This invention discloses a method and system for dynamic conversion of engineering cost indicators based on a materials and equipment price database, belonging to the field of engineering cost management technology. By constructing a standardized basic database of materials and equipment and updating it in real time based on multi-source data, this invention first solves the problems of incomplete data coverage and delayed updates, providing a comprehensive and timely data foundation for accurate conversion. On this basis, by calculating a dual-dimensional price index based on time and brand differences, the indicator items are deconstructed and labeled, and adjustments are made for each material according to time and brand differences. These technical features work synergistically to achieve high-precision, high-efficiency, and automated dynamic conversion from historical cost indicators to current market prices, significantly improving the scientific nature of cost management and the reliability of decision support.

Description

Technical Field

[0001] This invention relates to the field of engineering cost management technology, and in particular to a method, system, computer-readable storage medium, and engineering cost and BIM integrated management system based on a material and equipment price database for dynamic conversion of engineering cost indicators. Background Technology

[0002] In the field of construction cost estimation, the calculation and application of cost indicators mainly rely on historical data from projects under construction or completed. The core data components include key cost items such as labor costs, material costs, and machinery costs. However, this historical data only reflects market price levels at a specific time. Furthermore, material and equipment prices are easily affected by multiple factors such as market supply and demand, policy regulation, and technological innovation, exhibiting significant dynamic fluctuations. Therefore, the timeliness of traditional cost indicator data continuously diminishes over time, making it impossible to directly and accurately map current market costs using historical data in the cost estimation of new projects.

[0003] Currently, the industry generally uses manual methods to adjust prices based on historical indicator data. This not only consumes a lot of manpower, but also lacks unified standards and scientific basis in the adjustment process, making it difficult to guarantee the accuracy of the adjustment. This seriously restricts the efficiency and reliability of cost calculation and fails to meet the real-time and accurate requirements of engineering cost management. Summary of the Invention

[0004] In view of this, the technical problem to be solved by the present invention is: how to provide a high-precision, high-efficiency, and automated dynamic conversion method for engineering cost indicators from historical cost indicators to current market prices, so as to overcome the problems of insufficient accuracy caused by incomplete data coverage, delayed updates, and single adjustment dimensions in existing cost indicator conversion methods, as well as the low efficiency caused by cumbersome manual operation.

[0005] On the one hand, this invention provides a method for dynamic conversion of engineering cost indicators based on a material and equipment price database, including the following steps: S100, configuring standardized basic attribute fields for each sub-category according to material classification standards to form a unified standardized data structure, and constructing a material and equipment basic database based on the standardized data structure; S200, collecting material price data in real time from multiple priority data sources, processing the collected data to generate effective price data, and storing the effective price data in the material and equipment basic database; S300, calculating a time-dimensional price index reflecting material price fluctuations over time, and a brand difference price index reflecting price differences between different brands of the same material, based on the material and equipment basic database; S400, deconstructing the material demand indicators, identifying and labeling the sub-categories, brands, and consumption information they contain, and establishing a mapping relationship between the indicator items and the material and equipment basic database; S500. For each material item marked, adjust the price based on the time dimension by retrieving the corresponding time dimension price index according to its purchase time and the current time, and obtain the time-adjusted price. If the brand of the material is inconsistent with the benchmark brand, further adjust the price based on the brand difference dimension by retrieving the corresponding brand difference price index, and obtain the final material price. S600. Based on the final material price, recalculate the comprehensive unit price of the indicator item and output the dynamically updated cost indicator data.

[0006] Optionally, in step S100, the basic attribute fields shall include at least the material code, material name, specifications, brand, unit of measurement, and applicable project type.

[0007] Optionally, in step S200, the data sources, ranked from highest to lowest priority, include: market transaction data, publicly available government data, and historical project data.

[0008] Optionally, in step S200, the collected data is processed, specifically by cleaning, verifying, and arbitrating conflicts in the collected data.

[0009] Optionally, the conflict arbitration process is as follows: the valid price is determined according to the data source priority rules; if there is a price conflict among data sources of the same level, the weighted average of the data of the same level is calculated as the final valid price, and the weights are allocated according to the proportion of recent transaction volume of the data source platform.

[0010] Optionally, in step S300, the formula for calculating the price index in the time dimension is: Price index at a certain point in time = (Material price at that point in time ÷ Base period material price) × 100.

[0011] Optionally, in step S500, the calculation formula for adjusting the brand difference dimension is: final material price = time-adjusted price × brand difference price coefficient.

[0012] Optionally, in step S600, when recalculating the comprehensive unit price of the index item, the labor cost and machinery cost are adjusted using the same time-dimensional price index as the material cost.

[0013] Optionally, it also includes: S700, which integrates the output dynamically updated cost index data with the Building Information Model (BIM) to visualize and query real-time cost information in BIM.

[0014] On the other hand, the present invention provides a dynamic conversion system for engineering cost indicators based on a material and equipment price database, comprising: a processor; a memory connected to the processor and storing a computer program; when the computer program is executed by the processor, the dynamic conversion method for engineering cost indicators based on the material and equipment price database described above is implemented.

[0015] On the other hand, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the steps of the above-described method for dynamically converting engineering cost indicators based on a material and equipment price database.

[0016] On the other hand, the present invention also provides an integrated management system for engineering cost and BIM, including: a Building Information Modeling (BIM) data module for storing and managing the BIM data of the project; a dynamic conversion system for engineering cost indicators based on a material and equipment price database, as described above; and an integration interface module for associating the dynamically updated cost indicator data output by the dynamic conversion system with the components in the BIM, so that users can view and query the current market cost information of any component in real time in the BIM visualization interface.

[0017] Implementing this invention offers the following advantages: By constructing a standardized basic database of materials and equipment and updating it in real time based on multi-source data, this invention first solves the problems of incomplete data coverage and delayed updates, providing a comprehensive and timely data foundation for accurate conversion. Furthermore, by calculating a dual-dimensional price index based on both time and brand differences, it addresses the issue of a single adjustment dimension. By deconstructing and labeling the indicator items and sequentially adjusting for time and brand differences for each material, it overcomes the inefficiency of traditional methods. These synergistic technical features enable high-precision, high-efficiency, and automated dynamic conversion from historical cost indicators to current market prices, significantly improving the scientific nature of cost management and the reliability of decision support. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating a method for dynamically converting engineering cost indicators based on a materials and equipment price database, as shown in one embodiment. Detailed Implementation

[0019] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments. The step numbers in the following embodiments are only for ease of explanation and do not limit the order of the steps. The execution order of each step in the embodiments can be adapted according to the understanding of those skilled in the art.

[0020] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the embodiments of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0021] Example 1 In this embodiment, as Figure 1 The method shown is a dynamic conversion method for engineering cost indicators based on a material and equipment price database. The method is executed by a computer system and includes the following steps: S100. Configure standardized basic attribute fields for each sub-category according to the material classification standard, thereby forming a unified standardized data structure, and build a basic database of materials and equipment based on the standardized data structure; S200: Collects material price data in real time from multiple priority data sources, processes the collected data to generate effective price data, and stores the effective price data in the material and equipment basic database. S300, based on the basic database of materials and equipment, calculates the time dimension price index that reflects the fluctuation of material prices over time, as well as the brand difference price index that reflects the price difference between different brands of the same material; S400: Deconstruct the material requirements indicators, identify and label the sub-categories, brands and consumption information they contain, and establish a mapping relationship between the indicators and the basic database of materials and equipment. S500. For each material marked, based on its purchase time and the current time, retrieve the corresponding time-dimensional price index to adjust the time dimension and obtain the time-adjusted price; if the brand of the material is different from the benchmark brand, further retrieve the corresponding brand difference price index to adjust the time-adjusted price to the brand difference dimension and obtain the final material price. S600: Based on the final material price, recalculate the comprehensive unit price of the indicator items and output the dynamically updated cost indicator data.

[0022] In this embodiment, the material classification standards that can be used in step S100 include, but are not limited to, building construction, decoration, and prefabricated component engineering. Materials and equipment are classified into primary categories; and based on attributes such as material, specifications, and uses, these primary categories are further subdivided into subcategories, with standardized basic attribute fields configured for each subcategory.

[0023] In one specific embodiment, the basic attribute fields include at least the material code, material name, specifications, brand, unit of measurement, and applicable project type. Thus, the basic attribute fields of materials and equipment form a unified standardized data structure, providing a unified data framework for subsequent data collection, analysis, and price adjustment.

[0024] Specifically, the materials and equipment database is the core foundation of the dynamic conversion method for the entire project cost index. Its standardized classification and data structure solve the problems of vague material descriptions and chaotic classifications in traditional indicators. By unifying basic attribute fields such as material codes, it achieves accurate matching between indicator items and material price data, ensuring consistency and operability in subsequent data collection, index calculation, and price adjustments.

[0025] In this embodiment, in step S200, the data sources, ranked from highest to lowest priority, include: market transaction data, publicly available government data, and historical project data.

[0026] In this embodiment, step S200 involves processing the collected data, specifically by cleaning, verifying, and arbitrating the collected data.

[0027] In this embodiment, the conflict arbitration process is specifically as follows: The valid price is determined according to the data source priority rules; if there is a price conflict among data sources at the same level, the weighted average of the data at the same level is calculated as the final valid price, and the weights are allocated according to the proportion of recent transaction volume of the data source platform.

[0028] In one specific embodiment, the methods for acquiring multiple priority data sources include, but are not limited to: real-time collection of price data for specific categories of materials and equipment through multiple channels such as web crawlers and API (Application Programming Interface) interfaces. The data sources are prioritized (from high to low) based on their authority and credibility.

[0029] In one possible embodiment, the data source priority is specifically divided as follows: (1) Market transaction data (first priority): Connect with e-commerce platforms and supplier quotation systems related to the materials and equipment to be purchased, and collect real-time transaction price data; (2) Government open data (secondary priority): capture official data such as information prices and price indices released by relevant government departments as the core reference for price conflicts; (3) Historical project data (level 3 priority): Import historical transaction data such as material purchase invoices and contract unit prices from the settlement documents of completed projects. Supporting materials such as project completion acceptance certificates must be associated.

[0030] In this embodiment, to address issues such as data errors, duplication, inconsistent formats, and price conflicts, a three-tiered data processing mechanism of "cleaning-verification-conflict arbitration" is established, as detailed below: Data cleaning: A standardized format conversion algorithm is used to unify the price data of the same material and equipment from different data sources into a standardized data structure format of "material code-specification-brand-price-unit of measurement" to eliminate format differences; duplicate records are removed by hash deduplication algorithm; and erroneous data is screened and removed by numerical range verification (based on historical price fluctuation thresholds) and logical verification (e.g., if the unit price is much lower than / higher than the average price of the same category by 30%).

[0031] Data validation: Cross-validate the cleaned data. If price records for the same product category still exist in different data sources, trigger price conflict arbitration. Conflict arbitration: The valid price is determined according to the data source priority rules. First-level priority data is superior to second-level and third-level priority data, and second-level priority data is superior to third-level priority data. If there is a price conflict among data sources of the same level, the weighted average of the data of the same level (the weights are allocated according to the proportion of the platform's transaction volume in the past 3 months) is calculated as the final valid price.

[0032] To address the risks of data collection interruptions caused by external website interface changes, data structure updates, and access frequency restrictions, this invention provides an anti-interference data collection guarantee mechanism to ensure end-to-end stability and improve system robustness, as detailed below: Dynamic Adaptation of Access Frequency: This invention uses an access frequency monitoring module to identify the access restriction threshold of the target website in real time and automatically adjust the crawler request interval and concurrency. At the same time, it configures multiple IP pools and proxy rotation mechanisms to effectively avoid the blocking of a single IP. For API interfaces, a rate limiting adaptation algorithm is used to dynamically allocate the request volume according to the interface's rated access frequency, thereby preventing the triggering of rate limiting rules and ensuring the compliance and continuity of collection requests. Manual intervention channel: This invention provides real-time alarm prompts for extreme situations such as continuous adaptation failures and no available backup data source by configuring an abnormal status visualization monitoring panel. It supports manual data upload and manual configuration of parsing rules, further ensuring the continuity of the data collection process and ensuring no blind spots in data collection.

[0033] After data processing is completed, the collection time of each valid data point is marked with a timestamp to ensure the timeliness and traceability of price data; the database is automatically updated at a preset frequency (daily or weekly) to maintain the real-time performance and accuracy of the database data.

[0034] In this embodiment, a dynamic price pool covering all categories of materials is constructed by integrating the authority of government data, the real-time nature of market data, and the completeness of historical data. Data cleaning and automatic update mechanisms ensure the accuracy and timeliness of price data, avoiding the incompleteness and lag caused by relying solely on relevant government information, thus providing a solid data foundation for price index calculation.

[0035] In this embodiment, in step S300, the formula for calculating the time dimension price index is: Price index at a certain time point = (Material price at that time point ÷ Base period material price) × 100.

[0036] In a specific embodiment, the time-dimensional price index is constructed as follows: For each specific material in each sub-category (e.g., decoration engineering → decorative stone and stone products → slab → limestone slab), a fixed base period (e.g., 2020) is set. Using the base period price as a benchmark, the price fluctuation range of limestone slabs at each time point is calculated to form a time series price index. The calculation formula is as follows: The time-dimensional price index at a specific point in time is calculated as (material price at that point in time ÷ material price in the base period) × 100. This time-dimensional price index reflects the dynamic trend of material prices from the base period to the specific point in time over time.

[0037] It's important to note that the physical meaning of ×100 in the formula is: to convert the relative fluctuation ratio of material prices into a standardized index form with a base period of 100. This allows the price index value over time to intuitively and clearly reflect the rise and fall of material prices relative to the base period, thus better aligning with the general industry standards and usage habits of price indices in the engineering cost field. Specifically, the price index corresponding to the base period material price is fixed at 100. If the price index of a certain material is greater than 100 at a certain point in time, it means that the price of the material has increased compared to the base period, and the increase is (price index - 100)%%; If the price index of a material at a certain point in time is less than 100, it means that the price of the material has fallen compared to the base period, and the decline is (100 - price index)%.

[0038] This invention, by adopting a standardized index format, solves the problems of poor readability of decimal proportions and susceptibility to errors in manual calculation. On the other hand, it unifies the presentation standards of price indices for all categories and multiple dimensions of materials, providing standardized and highly readable basic data support for subsequent two-dimensional price adjustments and dynamic conversion of engineering cost indicators, further improving the efficiency and accuracy of indicator conversion.

[0039] In a specific embodiment, the brand difference price index is constructed as follows: Within the same sub-category (e.g., decoration engineering → decorative stone and stone products → sintered stone → limestone slab), the limestone slab market is divided into three price tiers: high-end, mid-range, and low-end, based on the positioning of different brands. A price tier model is established. Mainstream brands in the industry are selected as benchmark brands, and the price difference coefficient of each brand relative to the benchmark brand is calculated (e.g., if the price of a high-end brand of limestone slab is 1.2 times that of the benchmark brand, then the brand difference price index of that brand is 1.2). The brand difference price index is used to correct for price deviations caused by differences in materials and equipment brands.

[0040] Specifically, the time-dimensional price index addresses the dynamic changes in material prices over time, while the brand differentiation index fills the gap in traditional indicators that neglect brand premium / discount. The combination of these two achieves a technological breakthrough from "coarse-grained category adjustment" to "fine-grained, precise adjustment across both brand and time dimensions," making the indicator conversion results closer to actual market prices.

[0041] In this embodiment, within the same sub-category (e.g., decoration engineering → decorative stone and stone products → slab rock → limestone slab), the price is divided into three price tiers: high-end, mid-range, and low-end, based on brand market positioning, and a price tier model is established. This invention uses the mid-range brand price as the core benchmark for calculating brand difference dimensions, and uniformly selects rules and coefficient determination methods to ensure the consistency, comparability, and repeatability of conversion results for different implementers. The specific rules are as follows: 1. Core Positioning of Benchmark Brands: This invention selects mainstream mid-range brands in each sub-category as benchmark brands, and uses the standard transaction price of these mid-range brands as the benchmark value for price comparison.

[0042] Specifically, mid-range brands are defined as brands whose market share is in the middle range of the category, whose product quality meets the general use requirements of engineering projects and can meet relevant standards (if corresponding national or industry standards exist), and whose price level is in the middle of the overall price range of the sub-category. This approach balances market representativeness and price fairness, and avoids the benchmark value deviating from the actual mainstream cost of engineering projects due to the selection of high-end / low-end brands.

[0043] 2. Brand Differential Price Coefficient Determination Rules: After the benchmark brand is determined, the brand differential price coefficient is determined based on quantitative indicators such as brand premium capability, market positioning, and quality level within the sub-category. The core logic is "taking the mid-range benchmark price as the core and converting it according to the premium ratio." The specific implementation method is as follows: (1) Reference for basic coefficients: In practical engineering applications, the coefficient conversion logic with the mid-range benchmark price as the core is generally adopted. That is, the price of high-end brands is calculated by mid-range benchmark price × brand premium coefficient, and the price of low-end brands is calculated by mid-range benchmark price × brand discount coefficient. For example, in conventional sub-categories, the reference value of the premium coefficient for high-end brands is 1.2, and the reference value of the discount coefficient for low-end brands is 0.8.

[0044] (2) Determination of Refinement Coefficients: The above basic coefficients are industry-standard references. This invention, for each sub-category, combines market transaction data and brand premium research to determine the brand difference price coefficient for that specific sub-category: ① High-end brands: Extract the average transaction price of high-end brands in this category over the past 12 months, calculate the price ratio between them and the mid-range benchmark brand, and use it as the precise premium coefficient (e.g., if a high-end steel brand has a 20% premium over the mid-range benchmark price, then the premium coefficient is fixed at 1.2). ②Low-end brands: Extract the average transaction price of low-end brands in this category over the past 12 months, calculate the price ratio between them and the mid-range benchmark brand, and use it as the accurate discount factor (e.g., if a low-end steel brand is discounted by 20% compared to the mid-range benchmark price, then the discount factor is fixed at 0.8). (3) Coefficient solidification and updating: The brand difference price coefficients of each sub-category are included in the standardized coefficient library and automatically reviewed and updated every 12 months to ensure that the coefficients are in line with actual market changes; in special scenarios, users can customize coefficients according to project needs, but the basis and records must be retained at the same time to ensure that the results are traceable.

[0045] 3. The brand differentiation price index is calculated using the price of a selected mid-range benchmark brand as the base price. The price difference coefficient of each brand relative to the benchmark brand is calculated (the benchmark brand's price difference coefficient is fixed at 1.0). The calculation formula is as follows: The price difference coefficient of a certain brand = the average market price of the brand ÷ the price of the mid-range benchmark brand.

[0046] For example, in one embodiment, aluminum profiles are subdivided into categories, and a mid-range mainstream brand is selected as the benchmark brand. If the price of a certain high-end aluminum profile brand is 1.2 times that of the benchmark brand, then the price difference coefficient of that brand is 1.2; if the price of a certain low-end aluminum profile brand is 0.8 times that of the benchmark brand, then the corresponding price difference coefficient is 0.8.

[0047] When adjusting prices based on brand differences in the future, the price difference coefficient corresponding to that brand will be used to correct the base price of the material, thereby achieving accurate conversion of material prices for different brands and ultimately ensuring the accuracy and comparability of the dynamic conversion results of engineering cost indicators.

[0048] In this embodiment, in step S400, the bill of quantities (e.g., the comprehensive unit price index for "slab interior wall surface") contained in each index item in the index library is deconstructed to identify the sub-categories and corresponding brand information contained in the index items; a structured annotation method is used to embed a material list in the index items, clarifying key parameters such as material code, brand name, and consumption quantity of each material sub-category (e.g., each square meter of slab interior wall surface contains 1.01㎡ of limestone slab, brand is XX stone), establishing a precise mapping relationship between the index items and the basic database of materials and equipment, providing data support for subsequent price adjustments.

[0049] Specifically, by deeply analyzing the indicators, clarifying their material composition and brand information, a direct link was established between the indicators and the basic database of materials and equipment. This process breaks the traditional "black box" price adjustment model of indicators, making every cost change traceable to the price influencing factors of specific materials, thus improving the transparency and credibility of indicator adjustments.

[0050] In this embodiment, in step S500, the calculation formula for adjusting the brand difference dimension is: final material price = price after time adjustment × brand difference price coefficient.

[0051] In a specific implementation, price adjustments are made for each material in the indicator items based on both the time dimension and the brand difference dimension, specifically including: (1) Time dimension adjustment: Based on the material procurement time corresponding to the historical indicators and the current cost calculation time, retrieve the corresponding time dimension price index within the time period and calculate the price adjustment coefficient; calculate the price after time adjustment according to the following formula: Price after time adjustment = base period material price × time dimension price index ÷ 100; (2) Brand difference adjustment: If the material brand in the indicator item is inconsistent with the benchmark brand, the brand difference price index corresponding to the brand is retrieved, and the price after time adjustment is corrected for the second time. The calculation formula is: final material price = price after time adjustment × brand difference price coefficient.

[0052] Matrix operations enable batch processing of adjustments across multiple materials and dimensions, ensuring the efficiency and accuracy of price adjustments.

[0053] In this embodiment, in step S600, when recalculating the comprehensive unit price of the index item, the labor cost and machinery cost are adjusted using the same time-dimensional price index as the material cost.

[0054] Specifically, based on the final material price obtained in step S500, the time adjustment coefficients for labor costs and machinery costs are calculated using the same time-dimensional price index adjustment method as for material and equipment prices [i.e., the labor cost price index at a certain point in time = (labor cost price at that point in time ÷ base period labor cost price) × 100]. The comprehensive unit price and cost composition of the indicator items are recalculated. Dynamic indicator data containing the current market price level are output, and the system supports the generation of visual analysis reports by dimensions such as project type, region, and time, providing real-time data support for cost estimation and cost control.

[0055] In this embodiment, a batch processing mechanism based on a dual-dimensional (time dimension and brand difference dimension) price adjustment algorithm automates and scales the adjustment of indicator data compared to the inefficient traditional manual replacement and conversion method. It can quickly complete price conversions for massive amounts of indicator items, significantly reducing labor costs and meeting the real-time calculation needs of engineering cost management.

[0056] In one possible embodiment, the above-mentioned dynamic conversion method for engineering cost indicators further includes: S700 integrates the dynamically updated cost index data with Building Information Modeling (BIM) to visualize and query real-time cost information within BIM.

[0057] Example 2 Based on Example 1, this embodiment provides a comparative experiment to verify the accuracy and practicality of the dynamic conversion method of engineering cost indicators based on the material and equipment price database (hereinafter referred to as the present invention) in the calculation of economic indicators of glass curtain walls of super high-rise office buildings.

[0058] In this embodiment, by comparing with the existing traditional extensive conversion method (hereinafter referred to as the traditional method), the technical advantages of the present invention in improving the accuracy of cost index conversion and reducing cost calculation deviation are quantified, providing data support for practical engineering applications.

[0059] In this embodiment, the specific experimental parameters are set as follows: ① Experimental subject: Calculation of economic indicators of glass curtain walls of super high-rise office buildings to be built. The calculation base time is December 2025; the historical reference data is the economic indicators of glass curtain walls of similar super high-rise office buildings in October 2023.

[0060] ② Select historical indicator data and engineering quantity data as the core basic data.

[0061] Historical data: In October 2023, the economic indicator for glass curtain walls was 703.36 yuan / m² (calculation logic: total price of glass curtain wall project ÷ project building area). Project quantity data: The glass curtain wall of the project to be constructed has a quantity of 26,785.85 m², and the project building area is 66,340 m². Traditional method parameters: Material costs account for 75% of the comprehensive unit price of curtain walls, of which aluminum profiles account for 31%, glass accounts for 26%, and other auxiliary materials account for 18%. From October 2023 to December 2025, the price of float glass decreased by 42.6%, while the price of aluminum raw materials increased by 14.65%. Data support for this invention: Through the multi-source material and equipment price database constructed by this invention, precise data on price fluctuations of subdivided materials are collected - the price of aluminum profiles increased by 14.14%, the price of 8+1.52PVB+8+12A+8 tempered insulated laminated glass decreased by 51.52%, and the prices of other auxiliary materials (sealant, hardware, etc.) did not fluctuate significantly.

[0062] ③ Due to the lack of a detailed price database for specific product categories, existing technologies can only make general adjustments based on the price trends of broad material categories. The specific calculation steps are as follows: Step 1: Break down the proportion of various material and non-material costs in historical indicators: The economic indicator amount corresponding to glass materials = 703.36 yuan / m² × 26% ≈ 182.87 yuan / m²; The corresponding economic indicator for aluminum profiles = 703.36 yuan / m² × 31% ≈ 218.04 yuan / m²; The economic indicator amount corresponding to other auxiliary materials and non-material costs (labor, machinery, management fees, profit, etc.) = 703.36 yuan / m² × (1 - 26% - 31%) = 703.36 × 43% ≈ 302.44 yuan / m²; Step 2: Adjust the corresponding costs according to the price fluctuations of major material categories: The adjusted cost of glass materials = 182.87 yuan / m² × (1 - 42.6%) ≈ 182.87 × 0.574 ≈ 104.97 yuan / m²; The adjusted cost of aluminum profiles = 218.04 yuan / m² × (1 + 14.65%) ≈ 218.04 × 1.1465 ≈ 250.00 yuan / m²; Step 3: Calculate the economic indicators after conversion using the traditional method: The converted economic cost per unit = adjusted glass material cost + adjusted aluminum profile cost + other auxiliary materials and non-material costs = 104.97 + 250.00 + 302.44 ≈ 657.41 yuan / m².

[0063] ④ This invention achieves dynamic conversion through precise matching of subdivided product categories, dual-dimensional price adjustment, and indicator recalculation, all completed automatically. The specific steps for cost calculation using the dynamic conversion method of engineering cost indicators of this invention are as follows: Step 1: Collect price data for specific product categories This invention, through the construction of a multi-source material and equipment price database, integrates publicly available government data, market transaction data, and historical project data to accurately capture the real price fluctuations of subdivided materials in glass curtain walls—aluminum profiles rose by 14.14%, 8+1.52PVB+8+12A+8 tempered insulated laminated glass fell by 51.52%, and the prices of other auxiliary materials remained stable, providing a data foundation for accurate conversion.

[0064] Step 2: Deconstruction and Annotation of Material Information for Indicator Items This invention provides an in-depth analysis of the comprehensive unit price index for glass curtain walls in October 2023, clarifying the composition of sub-categories, unit usage, original unit price, and percentage of total cost. The analysis results are shown in Table 1. Table 1. Results of the Indicator Item Structure Step 3: Two-dimensional price adjustment and overall unit price recalculation This invention adjusts prices based on the time dimension for specific product categories, while simultaneously correcting labor and machinery costs according to a time index, ultimately recalculating the comprehensive unit price of glass curtain walls in December 2025: Precise price adjustments for specific product categories: The adjusted amount for aluminum profiles = 540 yuan / m² × (1 + 14.14%) = 616.38 yuan / m²; The adjusted price for tempered laminated insulated glass is 450 yuan / m² × (1 - 51.52%) = 218.17 yuan / m². Prices of other auxiliary materials remained stable at 300 yuan / m². The adjusted total material cost = 616.38 + 218.17 + 300 = 1134.55 yuan / m²; Adjustments to labor, machinery and other expenses: The processing and manufacturing costs, labor costs, and machinery costs are slightly adjusted according to the time index, and are adjusted to RMB 120.92 / m², RMB 120.92 / m², and RMB 30.43 / m² respectively. The transportation cost remains at RMB 60 / m², and the installation cost is adjusted to RMB 151.35 / m². The management fee is recalculated at 16.20% of the adjusted labor cost plus machinery cost, resulting in 40 yuan / m². The profit is recalculated as 5% of the adjusted direct cost plus management fee, resulting in 75 yuan / m². The recalculated comprehensive unit price for 2025 is 1134.55 + 120.92 + 60 + 151.35 + 40 + 75 = 1581.82 yuan / m².

[0065] Step 4: Economic Indicator Conversion This invention automatically calculates the economic indicators for glass curtain walls in December 2025 based on the actual workload of the project under construction. The converted economic indicator = (recalculated comprehensive unit price × curtain wall engineering quantity) ÷ project building area = (1581.82 yuan / m² × 26785.85m²) ÷ 66340m² ≈ 638.69 yuan / m².

[0066] It should be noted that this embodiment is for simplification and assumes that the material brand in the historical indicators is the benchmark brand. Therefore, when converting prices to 2025, only the time dimension needs to be adjusted, and the brand difference adjustment coefficient is 1. In practical applications, the brand difference dimension needs to be adjusted according to the specific brand using the method described above.

[0067] ⑤ Comparison and analysis of experimental results: The experimental results are shown in Table 2: Table 2 Comparison of Calculation Results Analysis of experimental results: Significantly improved accuracy: This invention breaks through the limitations of traditional methods that make "general adjustments to broad categories of materials". By using a material and equipment price database, it accurately captures the real price fluctuations of specific materials (such as using the actual price drop of 51.52% for tempered insulated laminated glass, rather than the general price drop of 42.6% for float glass), achieving "precise adjustments at the detailed level". The final calculation accuracy is 2.85% higher than that of traditional methods, and the conversion results are closer to the actual market cost in 2025.

[0068] The value of this invention in cost control is outstanding: based on the 26,785.85 m² curtain wall project of the project to be built, this invention reduces the cost calculation deviation by about 1.24 million yuan compared with the traditional method, effectively avoiding the risk of project cost overruns or budget waste caused by indicator deviations, and providing reliable data support for cost control.

[0069] High reliability and traceability: The calculation process of this invention is based on a standardized database and structured annotation. Every cost adjustment can be traced back to the price fluctuation of a specific sub-category, breaking the "black box" adjustment mode of traditional methods and improving the transparency and credibility of indicator conversion.

[0070] Example 3 Based on any of the above embodiments, this embodiment provides a comparative experiment to verify the technical advantages of the cost index conversion method based on the material price database (hereinafter referred to as the present invention) in terms of process efficiency.

[0071] In this embodiment, the actual effect of the present invention in shortening the conversion cycle and reducing labor input is quantified by comparing the time consumption with that of the traditional manual conversion method (hereinafter referred to as the traditional method).

[0072] (1) Experimental subjects: The same super high-rise office building construction cost conversion task was selected to ensure that the conversion targets and data basis of the traditional method and the method of this invention are completely consistent, thus ensuring the fairness of the comparison. (2) Basis for working hours statistics: Using conventional labor hours in the engineering field (8 hours of effective working time per person per day) as the statistical unit, the actual labor input at each process node of the two methods is recorded.

[0073] (3) Calculation of the process and time consumption of traditional manual conversion method The traditional method involves entirely manual, step-by-step operations. The process and time consumption at each step are as follows: Step 1: Select conversion items - manually filter target items and corresponding indicators, time taken 0.5 person / day; Step 2: Extracting materials to be converted from pricing documents - Manually sorting out and extracting the list of curtain wall-related materials from the pricing documents, taking 1 person / day; Step 3: Collect material prices to be converted - manually verify material prices through market research, platform queries, etc., which takes 3 person-days; Step 4: Replace the material prices that need to be converted in the pricing document - manually modify the material unit prices in the pricing document item by item and manually verify them, which takes 5 person-days; Step 5: Pricing documents are assigned to indicators based on the iBIM platform - the updated pricing documents are manually linked to the iBIM platform to complete the indicator classification, which takes 1 person / day; Step 6: Output the indicator conversion results - manually summarize the data and organize it into a result document, which takes 0.3 person / day.

[0074] The total time required by the traditional method is: 0.5 + 1 + 3 + 5 + 1 + 0.3 = 11.8 person-days.

[0075] (4) Flowchart and time calculation of the method of the present invention This invention simplifies the operation process by integrating a material price database with automated processing logic. The process and the time consumption of each node are as follows: Step 1: Select conversion project indicators - Quickly locate the target project and corresponding indicators through the system interface, taking 0.5 person / day; Step 2: Select the conversion time node - Select the target calculation time in the system (e.g., December 2025), which takes 0.3 person / day; Step 3: Automatically convert data based on the material price database - The system calls the built-in multi-source material price database, automatically matches the subdivided material prices and completes the indicator data adjustment, taking 0.5 person / day; Step 4: Re-summarize indicator data - The system automatically completes the calculation, classification and summarization of the adjusted indicator data, taking 0.3 person-days.

[0076] The total time required for the method of this invention is: 0.5 + 0.3 + 0.5 + 0.3 = 1.6 person-days.

[0077] (5) Analysis of experimental results Process simplification and automation replacement: This invention simplifies the six manual operation steps of the traditional method into four "light manual intervention + system automation" steps, and replaces the "material price collection and replacement" step, which accounts for 67.8% (8 / 11.8) of the time in the traditional method, with automatic retrieval and calculation of the material price database, which greatly reduces repetitive manual labor; Labor costs have been significantly reduced: Based on a labor cost of 800 yuan per person per day in the engineering field, the traditional method requires an investment of approximately 9,440 yuan (11.8 × 800) for a single conversion, while the present invention only requires 1,280 yuan (1.6 × 800), saving approximately 8,160 yuan in labor costs per conversion.

[0078] The conversion cycle has been significantly reduced: Traditional methods require approximately 6 days to complete if two people are working in parallel; this invention can complete the process in less than 1 day when two people are working, reducing the calculation cycle by over 85%, fully meeting the business needs for rapid calculation of engineering costs. Improved operational robustness: This invention, through automated system processing, avoids problems such as data errors and repeated verifications in traditional manual operations, improving efficiency while further ensuring the stability and consistency of conversion results.

[0079] Combining Embodiments 2 and 3, it can be seen that, compared with traditional methods, the present invention has the following significant advantages: Comprehensive data coverage: This invention constructs a material and equipment price database through multi-source data collection, which can cover more sub-categories, brands, and specifications of material and equipment price records, and achieves automatic updates on a regular basis. This effectively solves the problems of insufficient data coverage and delayed updates in traditional methods, ensuring that there are no blind spots in the conversion of indicators. Conversion accuracy has been significantly improved: This invention constructs a dual-dimensional price index system that combines the time dimension and the brand difference dimension. It can not only reflect the dynamic trend of market price changes, but also accurately correct the price deviation caused by brand differences. It achieves a technical breakthrough from "coarse-grained category adjustment" to "fine-grained brand-time dual-dimensional precise adjustment", making the conversion results closer to the actual market price and greatly improving the accuracy of cost calculation.

[0080] Operational efficiency has been greatly improved: This invention achieves fully automated processing of the entire process from data collection, index calculation, indicator deconstruction to price adjustment and result output through standardized database construction, structured annotation, and batch processing of matrix operations. It shortens the time for single indicator conversion, improves efficiency, and significantly reduces the cost of manual intervention and the risk of operational errors.

[0081] The adjustment process is transparent and traceable. By deeply deconstructing the indicators and structurally labeling the material information, a direct link between indicator data and material price data was established, making it possible to trace every cost change back to the specific material price influencing factors. This breaks the traditional "black box" price adjustment model of indicators and improves the transparency and credibility of indicator adjustments.

[0082] In summary, this invention, by constructing a material and equipment price database and a two-dimensional price adjustment system, breaks through the technical bottleneck of traditional index conversion, providing an efficient and accurate method for generating dynamic indicators in the field of engineering cost, and has significant engineering application value and market promotion prospects.

[0083] Example 4 Based on the above embodiments, this embodiment provides a dynamic conversion system for engineering cost indicators based on a material and equipment price database.

[0084] In this embodiment, the dynamic conversion system for engineering cost indicators based on a materials and equipment price database includes: processor; Memory, connected to the processor and storing computer programs; When the computer program is executed by the processor, it implements the dynamic conversion method of engineering cost indicators based on the material and equipment price database, as described above.

[0085] Example 5 This embodiment provides a computer-readable storage medium based on the above embodiments.

[0086] In this embodiment, a computer program is stored on a computer-readable storage medium. When the computer program is executed by a processor, it implements the steps of the above-described method for dynamically converting engineering cost indicators based on a material and equipment price database.

[0087] Example 6 This embodiment, based on embodiment four, provides an integrated management system for engineering cost and BIM.

[0088] In this embodiment, the integrated management system for engineering cost and BIM includes: The Building Information Modeling (BIM) data module is used to store and manage the BIM data of a project. As described in Example 4, a dynamic conversion system for engineering cost indicators based on a material and equipment price database; The integrated interface module is used to associate the dynamically updated cost index data output by the cost index dynamic conversion system with the components in BIM, enabling users to view and query the current market cost information of any component in real time in the BIM visualization interface.

[0089] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A method for dynamically converting engineering cost indicators based on a materials and equipment price database, characterized in that, Includes the following steps: S100. Configure standardized basic attribute fields for each sub-category according to the material classification standard, thereby forming a unified standardized data structure, and build a basic database of materials and equipment based on the standardized data structure. S200. Collect material price data in real time from multiple priority data sources, process the collected data to generate effective price data, and store the effective price data in the material and equipment basic database. S300. Based on the aforementioned material and equipment database, calculate the time-dimensional price index reflecting the fluctuation of material prices over time, and the brand difference price index reflecting the price differences between different brands of the same material. S400. Deconstruct the material requirements indicators, identify and label the sub-categories, brands and consumption information they contain, and establish a mapping relationship between the indicators and the material equipment basic database. S500. For each material marked, based on its purchase time and the current time, retrieve the corresponding time dimension price index to adjust the time dimension and obtain the time-adjusted price; if the material brand is inconsistent with the benchmark brand, further retrieve the corresponding brand difference price index to adjust the time-adjusted price to obtain the final material price. S600. Based on the final material price, recalculate the comprehensive unit price of the index item and output the dynamically updated cost index data.

2. The method for dynamic conversion of engineering cost indicators according to claim 1, characterized in that, In step S100, the basic attribute fields include at least the material code, material name, specifications, brand, unit of measurement, and applicable project type.

3. The method for dynamic conversion of engineering cost indicators according to claim 1, characterized in that, In step S200, the data sources, ranked from highest to lowest priority, include: market transaction data, publicly available government data, and historical project data.

4. The method for dynamic conversion of engineering cost indicators according to claim 3, characterized in that, In step S200, the collected data is processed, specifically by cleaning, verifying, and arbitrating conflicts in the collected data.

5. The method for dynamic conversion of engineering cost indicators according to claim 4, characterized in that, The specific conflict arbitration process is as follows: Determine the valid price based on data source priority rules; If there are price conflicts among data sources at the same level, the weighted average of the data at the same level is calculated as the final effective price, with the weights allocated according to the proportion of recent transaction volume on the data source platform.

6. The method for dynamic conversion of engineering cost indicators according to claim 1, characterized in that, In step S300, the calculation formula for the time dimension price index is: Price index at a certain time point = (Material price at that time point ÷ Base period material price) × 100.

7. The method for dynamic conversion of engineering cost indicators according to claim 1, characterized in that, In step S500, the calculation formula for adjusting the brand difference dimension is: final material price = time-adjusted price × brand difference price coefficient.

8. The method for dynamic conversion of engineering cost indicators according to claim 1, characterized in that, In step S600, when recalculating the comprehensive unit price of the indicator item, the labor cost and machinery cost are adjusted using the same time-dimensional price index as the material cost.

9. The method for dynamic conversion of engineering cost indicators according to claim 1, characterized in that, Also includes: S700 integrates the dynamically updated cost index data with the Building Information Model (BIM) to visualize and query real-time cost information within the BIM.

10. A dynamic conversion system for engineering cost indicators based on a materials and equipment price database, characterized in that, include processor; A memory connected to the processor and storing computer programs; When the computer program is executed by the processor, it implements the dynamic conversion method for engineering cost indicators based on the material and equipment price database as described in any one of claims 1 to 9.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the dynamic conversion method for engineering cost indicators based on the material and equipment price database as described in any one of claims 1 to 9.

12. An integrated management system for engineering cost and BIM, characterized in that, include: The Building Information Modeling (BIM) data module is used to store and manage the BIM data of a project. The dynamic conversion system for engineering cost indicators based on a material and equipment price database as described in claim 10; An integrated interface module is used to associate the dynamically updated cost index data output by the cost index dynamic conversion system with the components in the BIM, so that users can view and query the current market cost information of any component in real time in the BIM visualization interface.

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